Concurrent Warming and Freshening Led to a Record-High Sea Level in the Labrador Sea

Concurrent Warming and Freshening Led to a Record-High Sea Level in the Labrador Sea | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Concurrent Warming and Freshening Led to a Record-High Sea Level in the Labrador Sea Igor Yashayaev, Yang Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5747822/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract The Labrador Sea plays a pivotal role in the global climate system as a primary source of newly ventilated intermediate-depth water masses and a major carbon sink of the North Atlantic. Since the 1950s, this region has seen significant shifts in heat and freshwater contents, resulting in arguably the largest full-depth deep-ocean temperature and salinity changes ever recorded. However, the contribution of these changes to sea level variability has yet to be thoroughly quantified and investigated. Using satellite altimetry in conjunction with profiling Argo float and ship-based hydrographic measurements, we show that between 2017 and in 2023 the central Labrador Sea experienced an exceptionally fast sea level rise elevating the level to a record high. Six concurrent factors contributed to these rise and, consequently, extreme height – reduced winter surface cooling, increased summer surface warming (i.e., oceanic heat uptake), anomalous freshening, drastically shoaled winter convection, reduced deep-water density, and water-column mass gain. We also claim that the effect of salinity changes on sea level switched from counterbalancing (1948–2015) to reinforcing (2015–onward) the effect of temperature changes in result of Labrador Sea freshening caused by increased Arctic sea ice melt. This mechanism raises possibility of greater environmental impacts of both recent and imminent heat and freshwater regime shifts than predicted. Earth and environmental sciences/Ocean sciences/Physical oceanography Earth and environmental sciences/Climate sciences/Ocean sciences/Physical oceanography Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction The Earth's climate system is in a state of imbalance, with excess heat accumulating at a rate of 0.5–1 W/m² since 1970s, approximately 90% of which has been absorbed by the ocean 1 – 7 . The excessive heat accumulation has not only contributed to ocean warming but also accelerated the melting of glaciers, ice sheets, and sea ice, and the hydrologic cycle of the Earth 8 significantly impacting oceanic freshwater content, particularly in high-latitude regions 9 – 12 . Sea-level rise is one of the most significant consequences of these trends, resulting from the thermal expansion of seawater caused by ocean warming and addition of freshwater from the melting land-ice 13 – 15 . Additionally, the planetary distribution of freshwater can be shifted by the accelerating hydrologic cycle 8 . Regionally, freshening caused by melting sea ice also contributes to seawater expansion and sea-level rise. The Labrador Sea, which has the lowest mean dynamic sea level in the Northern Hemisphere, is a unique region where sea level is influenced by a combination of these factors. Situated in the western part of the subpolar North Atlantic and bounded by the cold fresh Arctic waters carried by the West Greenland Current (WGC) to the northeast and Labrador Current (LC) to the southwest (Fig. 1 b), the Labrador Sea serves the entire North Atlantic as its primary major receiving basin for freshwater inputs from Arctic and Greenland, especially melting Arctic sea ice 16 , 17 , enhanced by Arctic amplification 18 , and the melting Greenland Ice Sheet 19 , 20 . The central Labrador Sea (CLS, magenta contour in Fig. 1 ) is the primary region where intense winter cooling, driven by high extractions of heat from the surface (known as surface heat losses), transfers heat from the deeper layers to surface through vigorous convective mixing 21 , 22 . This process forms Labrador Sea Water (LSW) 21 , a well-mixed, dense intermediate water mass in the North Atlantic. LSW, with its distinct properties, replenishes the lower limb of the Atlantic Meridional Overturning Circulation (AMOC) 22 , 23 , signifying the role of the CLS in the planetary ocean and climate research. Unless specified otherwise, the values and statements in this study pertain to the CLS. Although the formation, variability, and spreading of the LSW have been studied in detail 21 , 22 , 24 – 27 , sea level – one of the key climate variables – has not been investigated for the CLS since 2006 28 . Sea level in the Labrador Sea has varied significantly throughout the satellite altimetry era (1993–present), reaching a record high in 2023 (Fig. 2 ), with 2024 potentially setting a new record. Among many important implications, the CLS sea level changes (a regional climatological low in Fig. 1 b) influence the shoreward sea level gradients (Figs. 1 b-d), which in turn impact the transport of volume, freshwater, and heat by the geostrophic boundary currents; the positive trends in this region are unique for all deep basins of the subpolar North Atlantic. Furthermore, sea level variations directly affect the safety, health and well-being of coastal communities in Atlantic Canada 29 and Greenland 30 , underscoring the importance of diagnosing, understanding, and predicting the sea level changes to address broader climate challenges. Two factors drive sea level change: density-induced steric height variation and mass changes 14 , 15 . Total steric height or surface-to-bottom integrated specific volume (i.e., inverse density, equations xx in Data and Methods) dominates dynamic sea level variability in the Labrador Sea (Fig. 2 ). It is influenced by both air-sea exchange and horizontal advection through ocean currents 14 , 31 – 34 , with heat and freshwater fluxes directly impacting temperature, salinity, and thus full-depth steric height profiles. The temperature-based thermosteric and salinity-based halosteric components are known to generally counterbalance each other in the subpolar North Atlantic 34 – 37 . As a result the sea level does not rise as fast as it would rise without the halosteric compensation of the thermosteric drive. How does the rate of the sea level rise respond to both steric components starting to coact by (positively) adding to the rise, instead of counteracting by counterbalancing each other? If such reversal in the halosteric compensation has already happened, is it one the reasons of the extreme sea level rise during the 2018–2024 period? If that is the case, it will be crucial to bring the regional salinity record and the multiyear cycles of intensification, relaxation, and shutdown of Labrador Sea deep convection 21 to the sea level rise alert. We thus investigate how these cycles, largely affecting temperature and salinity over the whole water column, contribute to the prominent ship and Argo float based steric height anomalies (SHA) and satellite altimetry based sea level anomalies (SLA). This study examines seasonal cycle and interannual-to-multidecadal variability of SLA and SHA in CLS for the 1992–2024 period, marked by significant changes in the regional heat and freshwater content and large variations in the winter mixing depth; and SHA variability extending back to 1948. We first identify key trends and extreme events through an examination of these records, underlining the rapid sea level rise from 2018 to 2023 to a record high. By comparing total steric height, and its thermosteric and halosteric components, we explore the drivers behind this rapid sea level rise. Then, we place the recent changes in the context of longer-term, namely, 1948–2023, variability to examine if similar events have occurred in the past and to assess the typicality versus/or uniqueness of the coaction of the steric height components observed throughout 2018–2023. Furthermore, we assess contribution of certain vertical layers to the total steric height changes, with particular focus on the deep ocean's contribution. Finally, we discuss how air-sea heat exchange and Arctic sea ice meltwater contribute to regional heat and freshwater content changes, and how this knowledge can help us to accurately model thermosteric and halosteric variations, and hence sea level trends. Results Extreme sea level observed in the central Labrador Sea in 2023 The SLA time series derived from both along-track (Fig. 2 ) and gridded altimetry (Supplementary Fig. 1) show consistent patterns across seasonal, interannual, and multidecadal timescales throughout the record. While distinctly showing in both records, the seasonal cycles of SLA and SHA, discussed in the “ Remaining challenges and future steps ” and “ Methods ” sections, are considerably different in magnitude (Fig. 2 ). To properly analyze interannual changes, trends and extremes, the regular or climatological seasonal cycle was subtracted from individual SLA and SHA values prior to filtering, smoothing and bin-averaging as explained in the “ Methods ” section. As the deep ocean, dominated by interannual variability, lacks sufficient hydrographic measurements below 2000 dbar to resolve sub-annual changes, we analyze the 1900–3300 dbar layer separately from the overlaying, 10–1900 dbar layer. This approach facilitates a focused assessment of the deep layer's SHA interannual variability, and long-term trends, providing a baseline study for understanding the deep layer steric contribution. To represent the full-depth, 10–3300 dbar, water column we combine the upper, 10–1900 dbar, and deep, 1900–3300 dbar, layer-based estimates. Although SLA and full-depth SHA, averaged over the CLS domain, exhibit noticeably different seasonal magnitudes, their interannual variations and state transitions are strikingly similar. This similarity is evidenced by a high, 0.98, correlation of the yearly-averaged SLA (YASLA) and SHA (YASHA) and a low, 0.79 cm, standard deviation of their difference. Detrending of YASLA and YASHA does not affect the strength of their similarity giving, respectively, 0.95 and 0.75 cm for the noted metrics. Furthermore, YASHA accounts for approximately 96% of the interannual variability in YASLA (91% after detrending), with individual values within 1.4 cm of each other in 95% of all cases (97% after detrending). In 2023, both YASLA and YASHA reached record highs, signified by the respective squares in Fig. 2 standing 15.1 cm and 13.4 cm higher than 30 years earlier, at the dawn of the satellite altimetry era. The 33-year, 1992–2024, trends of YASLA and YASHA, 0.313 ± 0.008 and 0.285 ± 0.008 cm/year, respectively, which small difference of ~ 9% is attributed to the water-column mass change. Coincidentally, a 30-year period is commonly regarded as a baseline for climatological normal 38 , making this study the first climatological analysis of sea level changes in the CLS. The strong alignment of SLA and SHA underscores the fact that sea level variability in the CLS is essentially steric, and it is primarily driven by variations of temperature and salinity throughout the water column. Three critical questions arise from this conclusion: [1] Given that winter convection dominates hydrographic variability integrated over the entire 200–2000 dbar layer 21 , is it also true in regard to YASHA and, therefore, YASLA? [2] Do salinity changes always extensively counterbalance and hence offset the concurrent temperature-driven effects on SHA and YASHA, as indicated in previous studies 34 – 37 ? Also can either of these effect make a difference in achieving a record high sea level? [3] How significant are the impacts of deep water changes, lying beyond the standard Argo floats depth reach (2000 dbar) and thus often overlooked, on SHA-dominated SLA? These questions are answered one by one in the following three subsections. Winter convection regime changes as the primary driver of sea level variability in the Labrador Sea Variations of steric height, and its thermal expansion driven or thermosteric and haline contraction driven or halosteric components (Fig. 3 ) result from full-depth changes in density (i.e., inverse specific volume), and temperature, and salinity, respectively. In turn, these three key ocean state variables are controlled both locally and remotely through heat, salt and freshwater fluxes driven by air-sea exchange, circulation-driven transport, and vertical and horizontal mixing. The Labrador Sea receives and subsequently transforms the inflows of modified yet still relatively warm and saline Atlantic Water, shallow outflows and deep overflows of cold and fresh Arctic water, and continental freshwater runoffs from rivers, groundwater, and glacier and permafrost meltwater 19 , 22 , 39 , 40 . In winter, the surface waters from different sources emit enormous amounts of heat to the atmosphere, consequently cooling, densifying and sinking entraining the underlying waters. This mixing process – winter convection – homogenizes a 500–to–2500 m top layer producing LSW. The properties and volume of newly-formed LSW are shaped by local atmospheric cooling, advection of cold fresh Arctic and warm saline Atlantic waters, and the water column’s retention of low stratification from previous convective events – a process known as convective preconditioning 21 , 22 , 24 – 26 . Ref. 21 examined two recent shutdowns of deep convection and predicted that this suppression would continue through 2024. Our updated time series shown in Fig. 4 confirm the prediction of continued convective shutdown beyond 2023. Furthermore, Fig. 4 provides insight into the role of the multiyear convective cycles in SHA and consequently SLA variabilities. The key feature in this figure, the 2012–2024 convective cycle, comprises the phases of recurrent intensification and deepening (2012–2018), and subsequent relaxation (2019–2024) of deep convection, ending with its full shutdown (2021–2024, except 2022). The bottom panel of Fig. 4 highlights the essence of this most recent cyclic water-mass development – a conglomeration of progressively deepening densifying convective vintages into a voluminous multiyear LSW class. The density and thickness of the recurrently mixed uniform-density layer, termed as pycnostad, are key regional climate state variables. Indeed, the stronger and deeper the winter mixing, the denser and thicker the pycnostad. In turn, dense thick pycnostads make the 0–2000 dbar average density higher, and vice versa . These linked relationships connect the convective phase changes with the YASHA and YASLA trend changeovers (Figs. 2 – 3 ). Stronger convective mixing events produce denser thicker pycnostads, and, in turn, lower SHA and SLA. In contrast, weaker convections produce lighter thinner pycnostads, stronger vertical stratification, and, in turn, higher SHA and SLA. This explains why the main driver of convection and deep ocean cooling – net winter surface heat loss – is also in control of YASHA and YASLA through ocean cooling dominating mixed layer density, convection depth and vertical stratification. Consequently, the thermosteric component dominates both seasonal and longer-term steric height variability (Fig. 3 ). However, as shown next, from moderating (i.e., reducing) the sea level trend the halosteric component has recently switched to reinforcing (i.e., amplifying) it. A reversal in the upper layer temperature-salinity steric balance drove the sea level to a record high The yearly-averaged full-depth halosteric height resides within about half the thermosteric height range (Fig. 3 , squares). Besides, the interannual halosteric and thermosteric height changes are often opposite in sign, with the former tending to counterbalance the latter. Can it be concluded that the sea level changes driven by thermal expansion are generally half-compensated by concurrent haline contraction? Apparently, it can. Indeed, according to Fig. 3 , nearly every year from 1990 to 2015, the full-depth halosteric component consistently counteracts against the thermosteric component, offsetting year-to-year thermosteric height changes by about a half. This recurring counterbalance suggests that the partial compensation of thermal expansion by haline contraction was predictably common until 2015. The situation has radically changed afterwards. In 2016, the halosteric contribution to the interannual steric height change switched from counterbalancing to reinforcing the thermosteric contribution. This transition arose as the halosteric height maintained a positive trend throughout the 2011–2023 period, while the thermosteric height rebounded from its decline in response to the 2012–2023 convective cycle’s phase change (Fig. 4 ). The physical processes responsible for the recent transition from halosteric-thermosteric counterbalancing (before 2016) to their allying and covarying (2016–2024) become evident from Fig. 4 and the published analysis of the relevant signals and their causes 21 recapped here. The CLS water column steadily cooled as convection deepened between 2011 and 2018. Then, these trend reversed as convection entered a relaxation phase. Unlike temperature, salinity, and thus the halosteric component, exhibited a distinct steady multiyear trend throughout the entire 2011–2024 period, with upper-layer freshening being interrupted only briefly in 2016 and 2017 without disturbing the overall trend. In 2023, the salinity reached a record low, imposed by advection of anomalous quantities of freshwater produced by extreme Arctic sea ice melt a few years earlier 21 . Driven by the unbalanced freshwater inflow into the Labrador Sea, the halosteric height increased by approximately 5 cm between 2011 and 2023. In contrast, the thermosteric height was lower in 2023 than 2011, as post–2018 warming could not fully offset the 2011–2018 cooling. Overall, the contribution of salinity amplified that of temperature after the convective phase reversal, resulting in a higher sea level in 2023 compared to 2011 (Figs. 2 – 3 ). Although the 2024 cycle is still underway at the time of preparation of this article, the ongoing concurrent warming and freshening trends is expected to result in an even high sea level in 2024. Overall, in contrast to moderating the effect of temperature changes on density in the pre–2016 years, the concurrent salinity changes served to amplify the effect of temperature changes throughout the subsequent reversal and rebound phases of the thermosteric (convective by nature) cycle. By switching from compensating to reinforcing the thermosteric heigh changes in 2016, the halosteric component boosted the temperature-driven sea level rise creating a marked extreme. Indeed, while thermosteric height in 2023 remained 3.6 cm below its 2011 peak (Fig. 3 , red squares), the reported changeover in the halosteric–thermosteric relationship, from counterbalance to reinforcement, is the second reason behind the CLS sea level rise to a record high in 2023. Moreover, record-breaking rates of the YASHA and YASLA changes over a sliding eight-year interval also fall on 2017–2024. These rates surpass even those for the 1994–2001 period brought up by a rapid recovery from record cold, fresh and dense conditions, alongside record low YASHA and YASLA levels (Figs. 2 and 3 ). A fundamental difference between these two periods lies in the behavior of the halosteric height: in 1994–2001, it counterbalanced about a half of the thermosteric heigh change, whereas in 2017–2024, one reinforced the other, accelerating the total SHA and hence SLA increase. The deep layer reinforced the recent sea level trend The role of the deep layer in the recent SLA trend and extreme becomes evident when comparing full-depth YASHA (Fig. 2 ) with that of the upper layer (Supplementary Fig. 2). While the upper-layer YASHA reached its peak in 2012 rather than in 2023, the full-depth YASHA set a record high in 2023. After two decades, 1992–2011, of relative stability with rather small fluctuations (± 0.6 cm) deep layer YASHA underwent a positive trend of ~ 0.22 cm/year, resulting in a cumulative deep SHA increase of ~ 2.4 cm from 2012 to 2023 (Figs. 2 , 3 ). This change exceeds the increase in full-depth YASHA over the same period (~ 1.1 cm), emphasizing the critical role of the deep layer in driving the full-depth SHA, and consequently SLA, to respective unprecedented highs in 2023. The origin of the positive 2012-onward trend in deep layer is revealed through decomposition of deep layer YASHA into its thermosteric and halosteric components. Between 1990 and 2011, these two components recurrently balanced each other (Fig. 3 ), suppressing development of significant decadal trends in deep layer YASHA. This equilibrium was irreversibly disrupted in 2012, leading to a shift in the thermohaline balance that persisted for 11 consecutive years. Throughout this period, the lower variability in halosteric height compared to thermosteric height contributed to the cumulative upward trend in deep layer YASHA. The [1] multiyear development of deep convection shaping the upper layer’s thermosteric heigh trends, [2] covariation and thus reinforcement of the upper layer’s thermosteric height changes with the halosteric ones (responding to massive upper layer freshening events), and [3] deep layer’s steric heigh trend collectively, through their joint control of full-depth YASHA, drove the CLS sea level to an unprecedented high. Where there other occurrences of halosteric reinforcements of thermosteric heigh changes in the Labrador Sea in the past? Recognizing the critical role of the halosteric reinforcement of the 2016–2024 thermosteric heigh change in the recent sea level rise to a record heigh (Fig. 3 ), we extend our analysis to historical hydrographic records dating back to 1948 to assess the occurrence of similar events in the past. The ship and Argo float based hydrographic measurements collected in the CLS from 1948 to 2023 have provided insights into multidecadal cycles of winter convection, water-column cooling and warming, freshening, and salinization 21 . In this study, we use the updated hydrographic dataset (see “Data and Method” and Ref. 21 for details) to derive the YASHA time series and its components across pressure levels, spaced at 5 dbar intervals from 200 to 3000 dbar and referenced to 3300 dbar (Fig. 5 , the 3000–3300 dbar layer is not displayed as changes are weak there). To perform adequate comparison with the pre–Argo observations, the Argo and Deep Argo data are only used in the present analysis for the years without a ship survey (e.g., 2017 and 2021). In all other cases, the long time series shown in Fig. 5 are derived from less frequent ship-based measurements. As seen in Figs. 4 and 6 , the seasonal cycle dominates temporal variability in the top 200 dbar layer (e.g., the seasonal cycle accounts for > 92% of the total temperature variance at 10 dbar). Furthermore, even with the regular seasonal cycle subtracted from infrequent pre–Argo (1948–2002) ship-based measurements, undersampled irregular seasonal variations may still be present there contributing spurious signals to yearly-averaged values. The upper 200 dbar (meter) layer data, prone to residual seasonal aliasing, has been excluded from the pre-2003 compilations shown in Fig. 5 . This exclusion has an insignificant effect on the full-depth, 10–3300 dbar, steric, thermosteric and halosteric heights. The corresponding 10–3300 dbar and 200–3300 dbar height differences, particularly for the steric height, are much smaller than the decadal changes (Fig. 5 , top ), justifying our choice of the 200–3300 dbar heights for analyzing longer-term variations in CLS steric sea level. Furthermore, while the exclusion of the upper 200 dbar layer slightly reduces the ranges of height changes, the patterns remain unaffected. The 200–3300 dbar steric, thermosteric, and halosteric height extremes for the 1948–2023 period are highlighted with triangles in Fig. 5 . The timing of these events suggests the following: [1] A thermosteric high and a halosteric low occurred between 1970 and 1971. [2] Conversely, a thermosteric low and a halosteric high were recorded in 1994. [3] The total steric height reached its absolute minimum concurrent with the lowest thermosteric and highest halosteric values, whereas its absolute maximum, achieved in 2023, is comparatively less pronounced in both components. [4] While in the major events of 1948–2015 the halosteric changes typically counterbalanced the thermosteric changes, after 2015 the halosteric- thermosteric correlation reversed with the two recently showing changes of the same sign and comparable magnitude. Notably, the positive coupling of the post-2015 thermosteric and halosteric heigh changes, coinciding with the most substantial freshening of the 300–700 dbar layer (Fig. 4 ), challenges the conventional vision of CLS steric heigh changes based on assumption of counteraction of halosteric and thermosteric changes and trends through density compensation. Figure 5 also provides detailed insight into the intermediate and deep layers' contributions to YASHA variability. YASHA time series constructed for pressure levels spaced at 5 dbar are brought together in its second panel (top-down). This compilation clearly shows where in the water column, when and how fast each trend developed, weakened and reversed, and what layer shaped it the most. In most cases, the interannual changes and trends tend to reverse anywhere between the pressure levels of 1250 dbar and 2000 dbar. These reversals, regardless of their exact vertical positions, explain why the trends observed at 200 dbar and 2250 dbar are so profoundly different. Over the 1990–2021 period, the 200 dbar and 2250 dbar YASHA series displayed opposing trends, each punctuated by short-term reversals in the opposite direction. This inverse symmetry of YASHA changes between the upper and deep layers suggests a counterbalancing effect, where upper-layer changes are offset by those in the deep layer, or vice versa. What particularly important to our study is that in 2022 and 2023, unlike the previous years, YASHA were consistent across all pressure levels, indicating a positive contribution from the deep layers to the 200–3300 dbar and full-depth steric heights. Further insights into the impact of the deep layer on upper ocean SHA changes are obtained by comparing thermosteric and halosteric component variations with depth (Fig. 5 , with reversed color-coding for the halosteric height to facilitate comparison). Below 1500 dbar, the two components largely counterbalance each other, although the resulting compensation is not full at all times. For instance, the halosteric component dominated deep-layer residuals from 1991 to 1999, while the thermosteric component did so from 2005 to 2016. In 2022 and 2023, both deep halosteric and thermosteric height anomalies were positive, amplifying the upper layer signal significantly. Unlike its deeper counterpart, the water column’s segment above ~ 1500 dbar, throughout its most extent, is typically stronger affected by the thermosteric component as the upward halosteric gain remains relatively weak. This promotes faster accumulation of thermosteric anomalous signals toward the surface and their prevalence in full-depth YASHA. Strikingly, here again 2022 and 2023 were exceptional. In these years, the upward halosteric gain matched the thermosteric one. The provided explanation of the deep and intermediate layer contributions to the exceptional CLS sea level of 2023 underscores the uniqueness of the event, and raises its importance for the subpolar and larger North Atlantic domains as local deep and full-depth regime gifts are likely to affect broader scale ocean dynamics and exchanges. Discussion The sea level of the central Labrador Sea (CLS) reached a 76-year record high in 2023. The rapid sea level rise that led to this event was caused by the joint action of mild winters, warm summers, sustained shutdown of deep convection, exceptional upper ocean freshening, deep ocean halosteric-thermosteric balance shift, and full water-column mass gain. While both deep, 1900–3300 dbar, layer steric height and full-column mass changes contribute to the long-term sea level trend, the interannual-to-decadal variability is predominantly shaped by the upper, 10–1900 dbar, layer thermosteric and halosteric components. We advance our understanding of the interannual-to-decadal sea level changes with a new approach to reconstruction and prediction of the two steric heigh components (Fig. 7 ). We first demonstrate how the thermosteric height series can be reconstructed detailly and accurately, and then discuss the factors affecting the predictability of the halosteric height. Reconstruction of the interannual thermosteric height changes in the central Labrador Sea using the atmospheric forcing data The thermosteric component dominates both interannual and seasonal steric height (Figs. 3 and 8 ) and hence sea level (Fig. 2 ) changes. A detailed examination of seasonal patterns across pressure levels (Fig. 6 ) reveals two vital signals with distinct vertical penetration, time lags and signatures – a deeper winter cooling signal and a shallower summer warming signal. The winter cooling is regulated by Winter Surface Heat Loss (WSHL), which was thoroughly analyzed in Ref 21 and is calculated by integrating all components of surface heat budget over an individually-defined cooling period 21 . In contrast, Summer Surface Heat Gain (SSHG), is calculated for the period when the accumulated net heat flux is directed into the sea. Another characteristic of seasonal warming, used in our work, is Summer Heat Peak (SHP). SHP is averaged over a fixed-length time interval (e.g., 15, 21, 31 days) centered on a daily surface heat gain peak. The surface heat exchange characteristics are further detailed in the “Seasonal air-sea heat exchange metrics” subsection and Supplementary Fig. 5 caption. Three key assumptions allow us to empirically model the observed yearly-averaged thermosteric height changes: [1] air-sea heat exchange is the leading factor controlling the thermosteric height, [2] the interannual changes of WSHL and SSHG have different and differently lagged effects on the thermosteric height, and need to be assessed separately, and [3] the residual impacts of previous cooling and warming events (preconditioning 21 ) can be approximated by asymmetric low-pass filtering. We reconstruct the yearly-averaged thermosteric height series by optimally low-pass filtering, scaling and merging WSHL and SSHG or, alternatively, SHP (SSHG|SHP). All sought parameters are found through iterative approximations aiming to minimize either squared or absolute deviations from the thermosteric heights. The atmospheric variables (e.g., WSHL, SSHG, SHP and NAO) are low-pass filtered using a left-side triangular window with weights decreasing linearly backward from the central point and equal zero forward. The best thermosteric reconstruction is achieved with different WSHL and SSHG|SHP filter window sizes. The reconstructed thermosteric heights closely approach their targets, especially after 2000 (Fig. 7 ). The reconstruction captures 96% of the observed variance. The strong correlation (0.98) underscores the robustness of the model in simulating thermosteric contributions to sea level changes over the past three and a half decades, accurately tracking both the overall trend and individual cycles, with observed changes replicated with a 1.0 cm accuracy in 27 out of 33 years (~ 83%). The overall level of fit that is achieved by using optimally filtered and weighted (scaled) CLS WSHL and SSHG|SHP time series, supports our assumptions and demonstrates the effectiveness of the proposed empirical model, making it suitable for further investigation and interpretation of both atmospheric forcing and signal transfer. The difference between the found optimal WSHL and SSHG|SHP left-side triangular window sizes of 7 and 13 years, respectively, emphasizes the different roles of the previous winter conditions retained by the water column, known as convective preconditioning 21 , and the cumulative effect of summer warming. Indeed, while the winter cooling and mixing are uniquely strong and deep in the Labrador Sea, leaving an immediate trace over a thick layer, the direct effect of summer warming is not that deep. Therefore, it must have taken a longer time and, possibly, a larger region of influence for SSHG to achieve a sizable effect on YASHA and YASLA. By accumulating its signal over a broader domain, SSHG spreads its influence on the thermosteric height over a longer time, hence a longer memory of SSHG changes in YASHA. Yet, while both WSHL and SSHG take turns driving thermosteric height, and the SSHG changes are more influential there on the longer time scales, WSHL dominates in this linkage as a whole. Basing on our results, the WSHL–thermosteric interaction is performed through convection, hence the leading role of convective cycles in sea level variability in the CLS domain. Notably, while the low-pass filtered winter (DJFM) NAO index shows some limited agreement with the yearly-averaged thermosteric height, it lacks the precision and detail captured by the presented heat-based model, highlighting the superior predictive accuracy of the heat-based reconstruction approach. Linking halosteric height to the extreme Arctic sea ice losses The significant reductions in Arctic sea ice in 2007, 2012, and 2019–2020 (Fig. 7 ) were each followed by pronounced freshening in the upper layer of the Labrador Sea approximately two years later 21 . This freshening could also be influenced by a recent shift in the Beaufort Gyre’s regime from freshwater accumulation to stabilization, with a potential release phase that may contribute to the latest CLS freshening event. In contrast, the Greenland freshwater flux anomaly, which changes more gradually over time, is unlikely to drive rapid freshening events in the CLS 19 . For this reason, we focus our analysis on the impacts of extreme Arctic sea ice loss as the primary driver of intermittent CLS halosteric height changes. The arrows in Fig. 7 point from the 2007, 2012 and 2020 extreme winter-to-summer Arctic sea ice reductions to the 2009, 2015 and 2022 CLS halosteric height maxima – with the latter lagged relative to the former by 2–3 years. The connection between these two sets of extremes follows from the analysis of the respective negative salinity anomalies originated from the freshened Arctic outflow entering the Labrador Sea through Davis Strait 21 . However, one might question the lack of substantial annual reductions in Arctic sea ice preceding the 1996–2005 period, during which CLS halosteric height was decreasing alongside rising salinity. This period coincided with exceptionally strong and sustained deep convection from the late 1980s to the mid–1990s, which infused the CLS water column with an estimated 7-meter freshwater equivalent 21 , 39 , 41 – 43 . As the sea entered a convective relaxation phase in 1996, freshwater began to discharge from its intermediate layer into the broader North Atlantic, resulting in a gradual reduction in halosteric height during this relaxation phase. Remaining challenges and future steps Interannual and seasonal water-column mass budgets Although the differences between YASLA and full-depth YASHA are relatively small, they are systematically persistent over time and thus comparable to deep-layer YASHA, particularly since 2016 (Fig. 2 ). These differences reflect water-column mass changes expressed in equivalent water thickness. The inferred mass changes (black line in Fig. 2 ) show stable variations over the period of 1993–2005, followed by a continuous decrease between 2005 and 2015, and a subsequent reversal to an increase lasting from 2016 to 2021, amounting to 3 cm and thus becoming a contributing factor to the recent sea level rise and extreme. The Gravity Recovery and Climate Experiment (GRACE) satellite data offer an alternative method to assess water-column mass changes. However, the mass measurements extracted from the JPL and CSR GRACE datasets and de-seasoned show inconsistent interannual patterns and opposing trends that appear unrealistic for our study region (see Supplementary Fig. 3), making any direct comparison with YASLA–YASHA differences unattainable at the moment. However, once a linear trend is removed from the CSR GRACE time series (green line in Fig. 2 ), the interannual variability aligns more closely with the inferred mass changes. Unlike the unrealistic long-term trends dominating the JPL and CSR GRACE time series, the associated regular seasonal cycles appear very similar in magnitude to the seasonal cycle based on the YASLA – full-depth YASHA differences (Fig. 8 ). Both GRACE and altimetry-hydrography based regular seasonal cycles clearly show a systematic mass increase toward summer and decrease toward winter. Although there is a time difference between achieving high states by the two types of mass estimates, requiring future investigation, the common mass cycle pattern can be explained by intensification of the cyclonic circulation and hence the divergence of mass over the basin in winter, and weakening of the boundary currents reducing the divergence in summer. This mechanism as well as alternative explanations of the seasonal water-column mass changes await a dedicated study. However, a comparison of the winter and summer altimetry-derived kinetic energy maps (Fig. 9) supports our hypothesis with the wintertime intensification of the boundary currents and hence cyclonic circulation act against the convergence of mass over the CLS domain. Given the overall importance of water-column mass changes to diagnosing and predicting sea level changes, further examinations of the GRACE data quality and derived mass, and finding the reasons behind the unrealistic interannual and longer-term changes in the Labrador Sea are necessary. Methods To fully understand the sea level budget in the central Labrador Sea (CLS), we co-analyze multi-mission satellite altimetry, historical (1948–1989) and high-quality World Ocean Circulation Experiment legacy ship-based (1990–2019), standard (2002–2024) and Deep Argo (2020–2024) float, satellite gravimetry (2002–2024), atmospheric reanalysis, and Arctic sea ice extent (1979–2024) data 21 . The “ Data Sources ” section offers a brief overview of the respective data sources, while the “ Methods ” section recaps data processing and analysis steps followed in this study. Time series decomposition Our study is based on hydrographic and altimetric observations at specific locations and times without temporal and spatial interpolation, gridding and smoothing. This approach to data analysis eliminates errors and uncertainties related to interpolation over extensive data gaps, excessive data smoothing and signal aliasing. Even vertical interpolation of water sample, reversing thermometer and low-resolution Argo float data is only performed with observations with sufficiently close vertical range of each other. Observations collected within certain geographic locations vary in time with respect to sampling or measurement frequency, contain extensive data omissions or gaps, and therefore form irregular time series. Irregular time series are analyzed by applying a special technique of iterative time series decomposition to all available measurements supplied with their corresponding times 21 , 44 , 45 . In this method, each value in a long-term record is regarded as a sum of [1] a regular (i.e., long-term mean or climatological normal) seasonal cycle, [2] irregular seasonal variations, which may be imposed by interannual seasonal phase and amplitude shifts), [3] interannual-to-multidecadal changes and trends, [4] mesoscale and synoptic natural variability (e.g., driven by mesoscale eddies and jet-like currents), [5] high-frequency (e.g., diurnal, inertial, tidal) variability, and [6] instrumental noise, including sampling and data processing errors. The successive iterations of reevaluation of these components and noise removal are performed until the first three components and residual variance (associated with the mesoscale and higher-frequency components) are stabilized, and no new outliers (errors) are detected and removed. The regular seasonal cycles of sea level and steric height anomalies, and of thermosteric and halosteric height components are shown in Figs. 6 and 8 , and in Supplementary Fig. 4, respectively. The dots in Fig. 8 and Supplementary Fig. 4, represent the observed values with removed low-frequency variability. Each regular seasonal cycle has been reevaluated on every successive iteration of the time series decomposition process – the original data series, with the outliers and low-frequency variability revealed on the previous iteration removed, is approximated with a sum of multiple-annual-frequency (i.e., [0, 1, 2, 3, 4, etc.] cycles/year) harmonics. The multiple-annual-frequency cutoff is based on the amount of variance of the original series explained by higher frequencies. The amount of variance explained by the cutoff and higher frequencies is negligibly small. Depending on characteristic features and scales of underlying variability, and temporal changes of sampling frequency and consistency, the low-frequency component is evaluated through either low-pass filtering or polynomial fitting of deviations from the last evaluated regular seasonal cycle. The deviations are either time-bin-averaged or weighted prior to evaluation of the low-frequency component to suppress the effects or biases of temporally uneven data distributions on the time series decomposition. The results shown in Figs. 2 , 3 and 6 – 8 are obtained with polynomial fitting of bin-averaged deviation. The markers in Figs. 2 , 3 , 5 and 7 represent yearly averaged deviations from the regular seasonal cycle. The dark red and dark blue lines in Fig. 2 show the low-frequency component, representing interannual-to-multidecadal changes of sea level and steric height, while the red and blue lines show this component summed with the regular seasonal cycle and irregular seasonal variations. Calculation of steric, thermosteric and halosteric heigh anomalies Steric height anomaly and its thermosteric and halosteric components are computed as follows. Steric Height Anomaly (SHA): where \({V_{sp}}\) is the specific volume (i.e., the inverse of density); \({S_A}\) is the absolute salinity (g/kg); \({T_C}\) is the conservative temperature ( o C); \({S_{A - mean}}\) , \({T_{C - mean}}\) are climatology mean of \({S_A}\) and \({T_C}\) ; \({p_1}\) , \({p_2}\) are the upper and lower pressure limits of corresponding layers; g is the gravitational acceleration constant as 9.81 m/s 2 . Absolute salinity, conservative temperature, and pressure are used to compute specific volume, enabling the calculation of steric sea level based on the TEOS-10 equation of state 46 . Reconstruction and prediction of 10-1900 dbar thermosteric height based on optimization of contributions of winter cooling and summer warming As discussed in the main text, the yearly-averaged thermosteric height is reconstructed by optimizing contributions from low-pass filtered total Winter Surface Heat Loss (WSHL) and total Summer Surface Heat Gain (SSHG) or, alternatively to SSHG, mean Summer Heat Peak (SHP), explained in the “ Seasonal air-sea heat exchange metrics ” subsection. The model employs a filter window, which weight decreases linearly with each step backward from the central point having the highest weight. The points located ahead of the central point are assigned zero weights. The filter size is defined as the number of points, including the central point, with non-zero weights (one year means retaining unfiltered data). Such low-pass filter design allows to prorate the contributions of the past forcing conditions to the present ocean state simply and efficiently. WSHL and SSHG|SHP were low-pass filtered independent from each other with the respective left-side triangular filter window sizes ranging from 1 to 25 years. The WSHL and SSHG|SHP low-pass filtered series were then added together for all 25×25 = 625 filter size combinations and for each weigh of the SSHG|SHP-based contribution selected from a wide range of closely-spaced values. This approach led us to a stable optimal solution of the thermosteric height reconstruction problem. As partially (for four of 25 tested WSHL filter window sizes) shown in Supplementary Fig. 5, the closest match of the observed and reconstructed yearly-averaged thermosteric heights is unambiguously achieved with the 7-year and 13-year low-pass filtering of SSHG|SHP, respectively, for a certain weight (~ 26) of the SHP relative to WSHL. Remarkably, the WSHL and SSHG|SHP low-pass filter window sizes, yielding the best agreement with both thermosteric height and 10-1900 dbar ocean heat content, are different. Namely, these sizes are 7 years for WSHL and 13 years for SSHG|SHP. This difference reflects the distinct roles of deep, rapidly progressing (5–7 years) during its active phase, winter convection and broader slower-acting interannual variations of summer warming. Our new approach to diagnosing the thermosteric heigh variations highlights the stronger and immediate impact of winter cooling compared to the longer-lasting cumulative effects of summer warming. Statistical analysis The polynomial, including linear, approximation of the analyzed series is based on the least-squares fitting technique. To improve stability of higher-order polynomial fits, the input variables (e.g., year) are centered and scaled to the ranges providing most stable solutions. The 95% confidence interval was derived based on the standard error scaled by two-tailed Student’s t test. Data sources Along-track satellite altimetry data Level-3 1Hz along-track sea surface height anomalies (SLA), computed relative to a 20-year mean climatology (1993–2012) with ~ 7 km (1 Hz) spatial sampling, were used to derive the CLS sea level time series (Fig. 2 ). These data were processed by the DUACS multimission altimeter system (product SEALEVEL_GLO_PHY_L3_MY_008_062, https://doi.org/10.48670/moi-00146 ) and include observations from multiple satellite missions (e.g., ERS-1, ERS-2, Topex/Poseidon, Jason-1/2/3, Envisat, Cryosat-2, Saral/AltiKa, Sentinel-3A/3B, Sentinel-6A, HY-2A/2B, Geosat Follow-On). The dataset was accessed through the Copernicus Marine Service portal (last accessed in November, 2024; https://data.marine.copernicus.eu ). Gridded satellite altimetry data Level-4 gridded SLA merges Level-3 along-track measurements from multiple altimeter missions by optimal interpolation (cmems_obs-sl_glo_phy-ssh_my_allsat-l4-duacs-0.25deg_P1D, https://doi.org/10.48670/moi-00148 ). In addition to SLA, the product provides variables such as Absolute Dynamic Topography and geostrophic currents (both absolute values and anomalies). The gridded dataset was used to generate Fig. 1 and last accessed in November, 2024. Satellite gravimetry data To evaluate mass contributions to sea-level change, we use two GRACE/GRACE-FO datasets, including the JPL GRACE and GRACE-FO Mascon Ocean, Ice, and Hydrology Equivalent Water Height Coastal Resolution Improvement (CRI) Filtered Release 06 Version 02 (TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06_V2) 47 – 49 and the CSR GRACE/GRACE-FO RL06 Mascon Solutions (Version 02) 50 , 51 . The JPL dataset, processed and distributed by the Jet Propulsion Laboratory ( http://grace.jpl.nasa.gov ) , provides monthly equivalent water thickness anomalies (in cm) at its nominal resolution is 0.5°×0.5°. The CSR dataset, processed by the Center for Space Research and accessible at http://www2.csr.utexas.edu/grace , offers monthly 1/4°×1/4° global coverage. The effective resolution 47 – 49 , 51 of both monthly gravity fields is 3°×3°. Spanning January 1993 to present, GRACE datasets includes data gaps due to technical issues, with details available at the GRACE mission portal ( https://grace.jpl.nasa.gov/data/grace_months/ ). Both satellite gravimetry datasets were last accessed in October 2024. Multiplatform hydrographic measurements This study integrates hydrographic data from multiple sources, including profiling Argo float (2002–2024), historical water sample and reversing thermometer ship-based (1948–1985) and recent high-resolution ship-based observations, to construct steric sea level time series in the CLS (Figs. 2 – 8 ). Comprehensive details on hydrographic data quality control, editing, and merging procedures are provided in Ref 21 , while here we recap the history of these observations. Systematic observations in the Labrador Sea date back to the late 1940s, with the major contributions for more than two decades being associated with the International Ice Patrol, U.S. Coast Guard, and Ocean Weather Ship Bravo 21 , 45 , 52 , 53 . Dedicated research missions, such as the 1966 and 1976 CSS Hudson expeditions, raised attention to the Labrador Sea as a key intermediate-depth water source of the North Atlantic. The Atlantic Repeat Hydrography Line 7-West (AR7W) line surveys conducted by the Bedford Institute of Oceanography over the period of 1990–2019 21,24,53,54 provided measurements of exceptionally high accuracy. The Argo float profiles, massively increasing in numbers since 2002, reduce our reliance on ship-based observations, offering year-round 0–2000 m and full-depth data to resolve seasonal and interannual variability, particularly in years without ship surveys (e.g., 2017, 2021). Rigorous quality control, including calibration of ship-based sensors and advanced Argo float data quality control, validation and correction carried forward from our previous study 21 , 24 , 53 , 54 , ensures consistency and accuracy across datasets. Advanced, adapted to routine utilization of observations from various platforms (e.g., floats, ships), data processing techniques further improve temporal and spatial resolution, enabling detailed analysis of long-term trends and seasonal cycles in the CLS. North Atlantic Oscillation (NAO) The North Atlantic Oscillation (NAO) is a key teleconnection pattern affecting atmospheric conditions in the Labrador Sea 21 , 55 . A positive NAO phase increases the sea level pressure (SLP) difference between the Icelandic low and Azores high, intensifying westerlies that bring cold, dry air to the region. Conversely, a negative NAO weakens westerlies, leading to warmer conditions. The winter NAO index (Fig. 7 ) is derived from December-to-March principal component-based values using the first empirical orthogonal function of 500-mbar height anomalies ( https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml ). Seasonal air-sea heat exchange metrics The atmospheric variables and reconstructed Winter Surface Heat Loss (WSHL), Summer Surface Heat Gain (SSHG) and Summer Heat Peak (SHP) used in this study (Fig. 7 and Supplementary Fig. 5) are based on the NCEP/NCAR Reanalysis datasets 56 , 57 ( https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html ; https://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html ) , provided by NOAA, USA. The Reanalysis products (R1 and R2) of the highest available resolution (6-hourly) were compared and jointly utilized to achieve comprehensive and detailed atmospheric data coverage. Net surface heat flux (NSHF) values were computed by combining the shortwave and longwave radiative fluxes and turbulent latent and sensible heat fluxes from 6-hourly NCEP/NCAR fields, averaged over the central Labrador Sea (CLS, Fig. 1 , green circle). The start and end points of an individual winter season were defined from NSHF sign reversals. Starting in late fall with a positive-to-negative NSHF transition, the cooling or winter season ends in early spring, when NSHF changes from negative to positive. Summer seasons were defined as the periods between the spring and fall NSHF sign reversals, when the net surface heat flux remained consistently positive, indicating ocean heat gain. WSHL was determined by integrating NSHF over a full cooling period, excluding short-term reversals have negligible impact on the total heat loss. Integrating NSHF over a warming period gives SSHG, averaging it over a period (e.g., 31-day long) centered on an outgoing flux high gives SHP Arctic sea ice extent Arctic sea ice extent and volume 58 data were downloaded from the National Snow and Ice Data Center ( https://nsidc.org/home ) and Polar Science Center ( https://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/ ). Annual winter-to-summer Arctic sea ice extent reductions (Fig. 7 ) were calculated by interpolating small data gaps, computing 1979–2024 daily means from gap-free years, and subtracting these means from daily values. Late-winter (Feb-Mar) and late-summer (Aug-Oct) averages and their differences were derived from the anomalies. Declarations Acknowledgements The authors thank the Editors for bringing the exceptional climate condition of 2023 to public attention, and the reviewers for their critical and constructive suggestions helping to improve this article. Code Availability Matlab, including M_Map toobox 59 , Visual Basic for Applications (VBA) and Golden Software Surfer were used for computations and visualization. Continuously updated codes and related instructions are available from the corresponding author (Igor Yashayaev, emails: [email protected] ; [email protected] ) upon reasonable request. References Hansen, J., Sato, M., Kharecha, P. & von Schuckmann, K. Earth’s energy imbalance and implications. Atmospheric Chemistry and Physics 11 , 13421–13449 (2011). Trenberth, K. E., Fasullo, J. T. & Balmaseda, M. A. Earth’s Energy Imbalance. (2014) doi:10.1175/JCLI-D-13-00294.1. Roemmich, D. et al. Unabated planetary warming and its ocean structure since 2006. Nature Clim Change 5 , 240–245 (2015). von Schuckmann, K. et al. Heat stored in the Earth system 1960–2020: where does the energy go? Earth System Science Data 15 , 1675–1709 (2023). von Schuckmann, K. et al. An imperative to monitor Earth’s energy imbalance. Nature Clim Change 6 , 138–144 (2016). Hakuba, M. Z., Frederikse, T. & Landerer, F. W. Earth’s Energy Imbalance From the Ocean Perspective (2005–2019). Geophysical Research Letters 48 , e2021GL093624 (2021). Hakuba, M. Z. et al. Trends and Variability in Earth’s Energy Imbalance and Ocean Heat Uptake Since 2005. Surv Geophys (2024). Curry, R., Dickson, B. & Yashayaev, I. A change in the freshwater balance of the Atlantic Ocean over the past four decades. Nature 426 , 826–829 (2003). Chen, J. L., Wilson, C. R. & Tapley, B. D. Satellite Gravity Measurements Confirm Accelerated Melting of Greenland Ice Sheet. Science 313 , 1958–1960 (2006). Perovich, D. K. & Richter-Menge, J. A. Loss of Sea Ice in the Arctic*. Annual Review of Marine Science 1 , 417–441 (2009). Maksym, T. Arctic and Antarctic Sea Ice Change: Contrasts, Commonalities, and Causes. Annu. Rev. Mar. Sci. 11 , 187–213 (2019). Rignot, E., Jacobs, S., Mouginot, J. & Scheuchl, B. Ice-Shelf Melting Around Antarctica. Science 341 , 266–270 (2013). Llovel, W., Willis, J. K., Landerer, F. W. & Fukumori, I. Deep-ocean contribution to sea level and energy budget not detectable over the past decade. Nature Clim Change 4 , 1031–1035 (2014). Gregory, J. M. et al. Concepts and Terminology for Sea Level: Mean, Variability and Change, Both Local and Global. Surv Geophys 40 , 1251–1289 (2019). Chambers, D. P. et al. Evaluation of the Global Mean Sea Level Budget Between 1993 and 2014. in Integrative Study of the Mean Sea Level and Its Components (eds. Cazenave, A., Champollion, N., Paul, F. & Benveniste, J.) 315–333 (2017). Zhang, J. et al. Labrador Sea freshening linked to Beaufort Gyre freshwater release. Nat Commun 12 , 1229 (2021). Yang, Q. et al. Recent increases in Arctic freshwater flux affects Labrador Sea convection and Atlantic overturning circulation. Nat Commun 7 , 10525 (2016). Previdi, M., Smith, K. L. & Polvani, L. M. Arctic amplification of climate change: a review of underlying mechanisms. Environ. Res. Lett. 16 , 093003 (2021). Dukhovskoy, D. S. et al. Role of Greenland Freshwater Anomaly in the Recent Freshening of the Subpolar North Atlantic. JGR Oceans 124 , 3333–3360 (2019). Böning, C. W., Behrens, E., Biastoch, A., Getzlaff, K. & Bamber, J. L. Emerging impact of Greenland meltwater on deepwater formation in the North Atlantic Ocean. Nature Geosci 9 , 523–527 (2016). Yashayaev, I. Intensification and shutdown of deep convection in the Labrador Sea were caused by changes in atmospheric and freshwater dynamics. Commun Earth Environ 5 , 1–23 (2024). Yashayaev, I., Holliday, N. P., Bersch, M. & van Aken, H. M. The History of the Labrador Sea Water: Production, Spreading, Transformation and Loss. in Arctic–Subarctic Ocean Fluxes: Defining the Role of the Northern Seas in Climate (eds. Dickson, R. R., Meincke, J. & Rhines, P.) 569–612 (Springer Netherlands, Dordrecht, 2008). doi:10.1007/978-1-4020-6774-7_25. Feucher, C., Garcia‐Quintana, Y., Yashayaev, I., Hu, X. & Myers, P. G. Labrador Sea Water Formation Rate and Its Impact on the Local Meridional Overturning Circulation. JGR Oceans 124 , 5654–5670 (2019). Lazier, J., Hendry, R., Clarke, A., Yashayaev, I. & Rhines, P. Convection and restratification in the Labrador Sea, 1990–2000. Deep Sea Research Part I: Oceanographic Research Papers 49 , 1819–1835 (2002). Van Aken, H. M., Femke De Jong, M. & Yashayaev, I. Decadal and multi-decadal variability of Labrador Sea Water in the north-western North Atlantic Ocean derived from tracer distributions: Heat budget, ventilation, and advection. Deep Sea Research Part I: Oceanographic Research Papers 58 , 505–523 (2011). Yashayaev, I. & Loder, J. W. Recurrent replenishment of Labrador Sea Water and associated decadal-scale variability: 2015 Convection in Labrador Sea. J. Geophys. Res. Oceans 121 , 8095–8114 (2016). Chomiak, L. N., Yashayaev, I., Volkov, D. L., Schmid, C. & Hooper, J. A. Inferring Advective Timescales and Overturning Pathways of the Deep Western Boundary Current in the North Atlantic Through Labrador Sea Water Advection. JGR Oceans 127 , e2022JC018892 (2022). Funk, A., Brandt, P., Schott, F. & Emery, W. SEA LEVEL ANOMALIES IN THE LABRADOR SEA. (2006). Thompson, K. R., Bernier, N. B. & Chan, P. Extreme sea levels, coastal flooding and climate change with a focus on Atlantic Canada. Nat Hazards 51 , 139–150 (2009). Hayashi, N. & Delaney, A. E. Climate change, community well-being, and consumption: Reconsidering human-environment relationships in Greenland under global change. Polar Science 41 , 101102 (2024). Gill, A. E. & Niller, P. P. The theory of the seasonal variability in the ocean. Deep Sea Research and Oceanographic Abstracts 20 , 141–177 (1973). Ferry, N., Reverdin, G. & Oschlies, A. Seasonal sea surface height variability in the North Atlantic Ocean. J. Geophys. Res. 105 , 6307–6326 (2000). Straneo, F. Heat and Freshwater Transport through the Central Labrador Sea. (2006) doi:10.1175/JPO2875.1. Volkov, D. L. et al. Interannual to decadal sea level variability in the subpolar North Atlantic: the role of propagating signals. Ocean Sci. 18 , 1741–1762 (2022). Antonov, J. I., Levitus, S. & Boyer, T. P. Steric sea level variations during 1957–1994: Importance of salinity. Journal of Geophysical Research: Oceans 107 , SRF 14-1-SRF 14-8 (2002). Levitus, S., Antonov, J. I., Boyer, T. P., Garcia, H. E. & Locarnini, R. A. Linear trends of zonally averaged thermosteric, halosteric, and total steric sea level for individual ocean basins and the world ocean, (1955–1959)–(1994–1998). Geophysical Research Letters 32 , (2005). Wang, G., Cheng, L., Boyer, T. & Li, C. Halosteric Sea Level Changes during the Argo Era. Water 9 , 484 (2017). Trewin, B. C. The role of climatological normals in a changing climate. WMO-TD 1377, WCDMP 61. World Climate Data and Monitoring Programme. World Meteorological Organization, Geneva (2007). Dickson, R. et al. Current estimates of freshwater flux through Arctic and subarctic seas. Progress in Oceanography 73 , 210–230 (2007). Dickson, R. R., Curry, R. & Yashayaev, I. Recent changes in the North Atlantic. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 361 , 1917–1934 (2003). Dickson, B. et al. Rapid freshening of the deep North Atlantic Ocean over the past four decades. Nature 416 , 832–837 (2002). Yashayaev, I. Hydrographic changes in the Labrador Sea, 1960–2005. Progress in Oceanography 73 , 242–276 (2007). Yashayaev, I., Van Aken, H. M., Holliday, N. P. & Bersch, M. Transformation of the Labrador Sea Water in the subpolar North Atlantic. Geophysical Research Letters 34 , 2007GL031812 (2007). Yashayaev, I. M. & Zveryaev, I. I. Climate of the seasonal cycle in the North Pacific and the North Atlantic oceans. Intl Journal of Climatology 21 , 401–417 (2001). Yashayaev, I. & Seidov, D. The role of the Atlantic Water in multidecadal ocean variability in the Nordic and Barents Seas. Progress in Oceanography 132 , 68–127 (2015). McDougall, T. J. et al. The International Thermodynamic Equation Of Seawater 2010 (TEOS-10): Calculation and Use of Thermodynamic Properties. Wiese, D. N., Landerer, F. W. & Watkins, M. M. GRACE:Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution. Water Resources Research 52 , 7490–7502 (2016). Watkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C. & Landerer, F. W. Improved methods for observing Earth’s time variable mass distribution with GRACE using spherical cap mascons. Journal of Geophysical Research: Solid Earth 120 , 2648–2671 (2015). Landerer, F. W. et al. Extending the Global Mass Change Data Record: GRACE Follow-On Instrument and Science Data Performance. Geophysical Research Letters 47 , e2020GL088306 (2020). Save, H. CSR GRACE and GRACE-FO RL06 Mascon Solutions v02. University of Texas at Austin 1 (2020). Save, H., Bettadpur, S. & Tapley, B. D. High-resolution CSR GRACE RL05 mascons. Journal of Geophysical Research: Solid Earth 121 , 7547–7569 (2016). Yashayaev, I., Seidov, D. & Demirov, E. A new collective view of oceanography of the Arctic and North Atlantic basins. Progress in Oceanography 132 , 1–21 (2015). Kieke, D. & Yashayaev, I. Studies of Labrador Sea Water formation and variability in the subpolar North Atlantic in the light of international partnership and collaboration. Progress in Oceanography 132 , (2014). Yashayaev, I. Hydrographic changes in the Labrador Sea, 1960–2005. Progress in Oceanography 73 , 242–276 (2007). Hauser, T., Demirov, E., Zhu, J. & Yashayaev, I. North Atlantic atmospheric and ocean inter-annual variability over the past fifty years – Dominant patterns and decadal shifts. Progress in Oceanography 132 , 197–219 (2015). Kalnay, E. et al. The NCEP/NCAR 40-Year Reanalysis Project. (1996). Kanamitsu, M. et al. NCEP–DOE AMIP-II Reanalysis (R-2). (2002) doi:10.1175/BAMS-83-11-1631. Schweiger, A. et al. Uncertainty in modeled Arctic sea ice volume. Journal of Geophysical Research: Oceans 116 , (2011). Pawlowicz, R. M_Map: a mapping package for MATLAB, version 1.4m, [Computer software], available online at www.eoas.ubc.ca/~rich/map.html. (2020). Additional Declarations There is NO Competing Interest. Supplementary Files CLSSLSupplement2024Dec31.docx Supplementary Dataset 1 Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5747822","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":402303138,"identity":"cb5ad7eb-ab66-43ad-821d-5361290439cb","order_by":0,"name":"Igor Yashayaev","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-6976-7803","institution":"Bedford Institute of Oceanography","correspondingAuthor":true,"prefix":"","firstName":"Igor","middleName":"","lastName":"Yashayaev","suffix":""},{"id":402303139,"identity":"17b3c887-4812-4f80-94e0-e060a1277b19","order_by":1,"name":"Yang Zhang","email":"","orcid":"https://orcid.org/0000-0001-7718-1303","institution":"School of Marine Science and Policy, University of Delaware","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-01-01 22:50:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5747822/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5747822/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-65747-3","type":"published","date":"2025-11-28T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":74907959,"identity":"2fe0c00e-cfa9-40ba-90d6-9f9fbd5a207e","added_by":"auto","created_at":"2025-01-28 08:35:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":492627,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTopographic features, ocean currents, and sea level characteristics of the Labrador Sea.\u003c/strong\u003e Major current systems and isobaths at 200 m, 2000 m, 3000 m, and 3500 m (black contours) (a), mean annual sea level lows averaged over 1993–2023 (b), Linear trends in annual sea level lows (c) and highs (d), with dots indicating insignificant trends. The central Labrador Sea (CLS), defined by the magenta boundary, highlights the primary region of analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/9506be8154432149849d7c81.png"},{"id":74907958,"identity":"fda757d2-dc03-438e-90d5-aabf5087d74d","added_by":"auto","created_at":"2025-01-28 08:35:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":283281,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInterannual variability of sea level and steric height in the central Labrador Sea.\u003c/strong\u003e \u003cem\u003eTop-down \u003c/em\u003e(cm): the along-track satellite altimetry-based sea level (\u003cem\u003ered\u003c/em\u003e), full-depth steric height (\u003cem\u003eblue\u003c/em\u003e) and deep layer steric height (\u003cem\u003epurple\u003c/em\u003e) anomalies; water column mass change derived by subtracting full-depth steric height from sea level (\u003cem\u003egrey/black\u003c/em\u003e); and CSR GRACE mass change with the linear trend being removed (\u003cem\u003egreen\u003c/em\u003e). Square markers indicate yearly averaged deviations from the respective regular seasonal cycles underlined by optimal polynomial fits. For both sea level and full-depth steric height the regular seasonal, irregular seasonal and low-frequency signals are summed up for each date and shown with respectively colored lines.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/de11fe526f080a169d8ebb81.png"},{"id":74907961,"identity":"61e469f0-44ba-4584-9577-722c43f8ee88","added_by":"auto","created_at":"2025-01-28 08:35:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":306470,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCentral Labrador Sea steric, thermosteric and halosteric heights from 1990 to 2024.\u003c/strong\u003e \u0026nbsp;\u003cem\u003eTop-down \u003c/em\u003e(cm): full-depth (10-3300 dbar) total steric, thermosteric and halosteric (\u003cem\u003egrey/black, red and blue, respectively\u003c/em\u003e), and deep layer (1900-3300 dbar) total steric, thermosteric and halosteric (\u003cem\u003egrey/black, red and blue, respectively\u003c/em\u003e) height anomalies. Square markers indicate yearly averaged deviations from the respective regular seasonal cycles underlined by optimal polynomial fits. For the full-depth total and decomposed steric heights the regular seasonal, irregular seasonal and low-frequency signals are summed up for each date and shown with respectively colored lines.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/0ac746175fa8aa175588d009.png"},{"id":74909352,"identity":"fe79f21c-dccc-48ff-b123-fc7468987901","added_by":"auto","created_at":"2025-01-28 08:51:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":831699,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e2002–2023 central Labrador Sea temperature, salinity, density, and 0.005 kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e density layer thickness.\u003c/strong\u003e\u0026nbsp; The values used in the figure are based on quality-controlled and calibrated Argo float and ship-based observations. Short horizontal lines indicate the convection depths. LSW subscripts denote year classes.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/567e338089e37310a3ff9315.png"},{"id":74907964,"identity":"86512659-b9f2-4304-86f6-81df9ff1429f","added_by":"auto","created_at":"2025-01-28 08:35:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":383469,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e1948-2023 evolution of the central Labrador Sea steric, thermosteric and halosteric height 200-3000 dbar profiles.\u003c/strong\u003e \u003cem\u003eTop-down\u003c/em\u003e: 1990-2023 all-inclusive hydrography 10-3300 dbar and 1948-2023 ship-based hydrography 200-3300 dbar total steric, thermosteric and halosteric (\u003cem\u003egrey/black, red and blue, respectively\u003c/em\u003e) height anomalies; and evolutions of 200-3000 dbar total steric, thermosteric and halosteric height yearly averaged profiles.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/b08f1ad3a49d9952ca5d43ce.png"},{"id":74907967,"identity":"2b988a69-d15e-49f2-b3f1-cb6b62a1ceae","added_by":"auto","created_at":"2025-01-28 08:35:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":329139,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRegular seasonal cycles of the key central Labrador Sea state variables from the surface to 900 dbar. \u003c/strong\u003eThe seasonal cycles of specific volume, temperature and salinity (\u003cem\u003eleft\u003c/em\u003e), and steric, thermosteric and halosteric heights (\u003cem\u003eright\u003c/em\u003e) are based on the quality-controlled and calibrated Argo float and ship-based measurements collected in the central Labrador Sea during the period of 2002-2024.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/d541f25b617f8fa2f813a0aa.png"},{"id":74907987,"identity":"4b9a7e64-a105-448b-8041-bc03f522dc6b","added_by":"auto","created_at":"2025-01-28 08:35:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":158181,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReconstruction and prediction of the central Labrador Sea thermosteric and halosteric heights using the atmospheric forcing indices and annual Arctic sea ice losses. \u003c/strong\u003e\u003cem\u003eTop-down\u003c/em\u003e: observed 10-1900 dbar halosteric height anomaly (cm, \u003cem\u003eblue\u003c/em\u003e), winter-to-summer Arctic sea ice extent reduction and (10\u003csup\u003e6\u003c/sup\u003e km\u003csup\u003e2\u003c/sup\u003e, \u003cem\u003epurple\u003c/em\u003e), the winter (DJFM) North Atlantic Oscillation (NAO) index (inversed, \u003cem\u003egrey\u003c/em\u003e), and observed (cm, \u003cem\u003ered\u003c/em\u003e) and reconstructed from winter surface heat loss and summer surface heat gain (cm, \u003cem\u003egreen\u003c/em\u003e) 10-1900 dbar thermosteric height anomalies. Arrows connect extreme winter-to-summer Arctic sea ice losses to local halosteric maxima/highs.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/dd24d571319a22905eb21815.png"},{"id":74909354,"identity":"b725f1b8-a6c3-4257-88be-2e515e0111dd","added_by":"auto","created_at":"2025-01-28 08:51:16","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":244440,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReconstruction and prediction of the central Labrador Sea thermosteric and halosteric heights using the atmospheric forcing indices and annual Arctic sea ice losses. \u003c/strong\u003e\u003cem\u003eTop-down\u003c/em\u003e: observed 10-1900 dbar halosteric height anomaly (cm, \u003cem\u003eblue\u003c/em\u003e), winter-to-summer Arctic sea ice extent reduction and (10\u003csup\u003e6\u003c/sup\u003e km\u003csup\u003e2\u003c/sup\u003e, \u003cem\u003epurple\u003c/em\u003e), the winter (DJFM) North Atlantic Oscillation (NAO) index (inversed, \u003cem\u003egrey\u003c/em\u003e), and observed (cm, \u003cem\u003ered\u003c/em\u003e) and reconstructed from winter surface heat loss and summer surface heat gain (cm, \u003cem\u003egreen\u003c/em\u003e) 10-1900 dbar thermosteric height anomalies. Arrows connect extreme winter-to-summer Arctic sea ice losses to local halosteric maxima/highs.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/fc136115784dbe65b7e3ca10.png"},{"id":97039818,"identity":"7f4a17b6-398d-4b36-bcce-824481acdb6f","added_by":"auto","created_at":"2025-11-29 08:07:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4719939,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/c69b8673-f43d-4421-91a3-4e011f5ee3c3.pdf"},{"id":74907963,"identity":"45b8e717-0414-45c2-959f-f3cb7e15b87b","added_by":"auto","created_at":"2025-01-28 08:35:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14245059,"visible":true,"origin":"","legend":"Supplementary Dataset 1","description":"","filename":"CLSSLSupplement2024Dec31.docx","url":"https://assets-eu.researchsquare.com/files/rs-5747822/v1/94ab4bccbc33dc25f775e7d8.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Concurrent Warming and Freshening Led to a Record-High Sea Level in the Labrador Sea","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Earth's climate system is in a state of imbalance, with excess heat accumulating at a rate of 0.5\u0026ndash;1 W/m\u0026sup2; since 1970s, approximately 90% of which has been absorbed by the ocean\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The excessive heat accumulation has not only contributed to ocean warming but also accelerated the melting of glaciers, ice sheets, and sea ice, and the hydrologic cycle of the Earth\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e significantly impacting oceanic freshwater content, particularly in high-latitude regions\u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Sea-level rise is one of the most significant consequences of these trends, resulting from the thermal expansion of seawater caused by ocean warming and addition of freshwater from the melting land-ice\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Additionally, the planetary distribution of freshwater can be shifted by the accelerating hydrologic cycle\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Regionally, freshening caused by melting sea ice also contributes to seawater expansion and sea-level rise. The Labrador Sea, which has the lowest mean dynamic sea level in the Northern Hemisphere, is a unique region where sea level is influenced by a combination of these factors.\u003c/p\u003e \u003cp\u003eSituated in the western part of the subpolar North Atlantic and bounded by the cold fresh Arctic waters carried by the West Greenland Current (WGC) to the northeast and Labrador Current (LC) to the southwest (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), the Labrador Sea serves the entire North Atlantic as its primary major receiving basin for freshwater inputs from Arctic and Greenland, especially melting Arctic sea ice\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, enhanced by Arctic amplification\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, and the melting Greenland Ice Sheet\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The central Labrador Sea (CLS, magenta contour in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) is the primary region where intense winter cooling, driven by high extractions of heat from the surface (known as surface heat losses), transfers heat from the deeper layers to surface through vigorous convective mixing\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. This process forms Labrador Sea Water (LSW)\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, a well-mixed, dense intermediate water mass in the North Atlantic. LSW, with its distinct properties, replenishes the lower limb of the Atlantic Meridional Overturning Circulation (AMOC) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, signifying the role of the CLS in the planetary ocean and climate research. Unless specified otherwise, the values and statements in this study pertain to the CLS.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlthough the formation, variability, and spreading of the LSW have been studied in detail\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, sea level \u0026ndash; one of the key climate variables \u0026ndash; has not been investigated for the CLS since 2006\u003csup\u003e28\u003c/sup\u003e. Sea level in the Labrador Sea has varied significantly throughout the satellite altimetry era (1993\u0026ndash;present), reaching a record high in 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with 2024 potentially setting a new record. Among many important implications, the CLS sea level changes (a regional climatological low in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) influence the shoreward sea level gradients (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb-d), which in turn impact the transport of volume, freshwater, and heat by the geostrophic boundary currents; the positive trends in this region are unique for all deep basins of the subpolar North Atlantic. Furthermore, sea level variations directly affect the safety, health and well-being of coastal communities in Atlantic Canada\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e and Greenland\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, underscoring the importance of diagnosing, understanding, and predicting the sea level changes to address broader climate challenges.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTwo factors drive sea level change: density-induced steric height variation and mass changes\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Total steric height or surface-to-bottom integrated specific volume (i.e., inverse density, equations xx in Data and Methods) dominates dynamic sea level variability in the Labrador Sea (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). It is influenced by both air-sea exchange and horizontal advection through ocean currents\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, with heat and freshwater fluxes directly impacting temperature, salinity, and thus full-depth steric height profiles. The temperature-based thermosteric and salinity-based halosteric components are known to generally counterbalance each other in the subpolar North Atlantic\u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. As a result the sea level does not rise as fast as it would rise without the halosteric compensation of the thermosteric drive. How does the rate of the sea level rise respond to both steric components starting to coact by (positively) adding to the rise, instead of counteracting by counterbalancing each other? If such reversal in the halosteric compensation has already happened, is it one the reasons of the extreme sea level rise during the 2018\u0026ndash;2024 period? If that is the case, it will be crucial to bring the regional salinity record and the multiyear cycles of intensification, relaxation, and shutdown of Labrador Sea deep convection\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e to the sea level rise alert. We thus investigate how these cycles, largely affecting temperature and salinity over the whole water column, contribute to the prominent \u003cem\u003eship and Argo float based\u003c/em\u003e steric height anomalies (SHA) and \u003cem\u003esatellite altimetry based\u003c/em\u003e sea level anomalies (SLA).\u003c/p\u003e \u003cp\u003eThis study examines seasonal cycle and interannual-to-multidecadal variability of SLA and SHA in CLS for the 1992\u0026ndash;2024 period, marked by significant changes in the regional heat and freshwater content and large variations in the winter mixing depth; and SHA variability extending back to 1948. We first identify key trends and extreme events through an examination of these records, underlining the rapid sea level rise from 2018 to 2023 to a record high. By comparing total steric height, and its thermosteric and halosteric components, we explore the drivers behind this rapid sea level rise. Then, we place the recent changes in the context of longer-term, namely, 1948\u0026ndash;2023, variability to examine if similar events have occurred in the past and to assess the typicality versus/or uniqueness of the coaction of the steric height components observed throughout 2018\u0026ndash;2023. Furthermore, we assess contribution of certain vertical layers to the total steric height changes, with particular focus on the deep ocean's contribution. Finally, we discuss how air-sea heat exchange and Arctic sea ice meltwater contribute to regional heat and freshwater content changes, and how this knowledge can help us to accurately model thermosteric and halosteric variations, and hence sea level trends.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eExtreme sea level observed in the central Labrador Sea in 2023\u003c/h2\u003e\n \u003cp\u003eThe SLA time series derived from both along-track (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) and gridded altimetry (Supplementary Fig.\u0026nbsp;1) show consistent patterns across seasonal, interannual, and multidecadal timescales throughout the record. While distinctly showing in both records, the seasonal cycles of SLA and SHA, discussed in the \u0026ldquo;\u003cem\u003eRemaining challenges and future steps\u003c/em\u003e\u0026rdquo; and \u0026ldquo;\u003cem\u003eMethods\u003c/em\u003e\u0026rdquo; sections, are considerably different in magnitude (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). To properly analyze interannual changes, trends and extremes, the regular or climatological seasonal cycle was subtracted from individual SLA and SHA values prior to filtering, smoothing and bin-averaging as explained in the \u0026ldquo;\u003cem\u003eMethods\u003c/em\u003e\u0026rdquo; section.\u003c/p\u003e\n \u003cp\u003eAs the deep ocean, dominated by interannual variability, lacks sufficient hydrographic measurements below 2000 dbar to resolve sub-annual changes, we analyze the 1900\u0026ndash;3300 dbar layer separately from the overlaying, 10\u0026ndash;1900 dbar layer. This approach facilitates a focused assessment of the deep layer\u0026apos;s SHA interannual variability, and long-term trends, providing a baseline study for understanding the deep layer steric contribution. To represent the full-depth, 10\u0026ndash;3300 dbar, water column we combine the upper, 10\u0026ndash;1900 dbar, and deep, 1900\u0026ndash;3300 dbar, layer-based estimates.\u003c/p\u003e\n \u003cp\u003eAlthough SLA and full-depth SHA, averaged over the CLS domain, exhibit noticeably different seasonal magnitudes, their interannual variations and state transitions are strikingly similar. This similarity is evidenced by a high, 0.98, correlation of the yearly-averaged SLA (YASLA) and SHA (YASHA) and a low, 0.79 cm, standard deviation of their difference. Detrending of YASLA and YASHA does not affect the strength of their similarity giving, respectively, 0.95 and 0.75 cm for the noted metrics. Furthermore, YASHA accounts for approximately 96% of the interannual variability in YASLA (91% after detrending), with individual values within 1.4 cm of each other in 95% of all cases (97% after detrending). In 2023, both YASLA and YASHA reached record highs, signified by the respective squares in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e standing 15.1 cm and 13.4 cm higher than 30 years earlier, at the dawn of the satellite altimetry era. The 33-year, 1992\u0026ndash;2024, trends of YASLA and YASHA, 0.313\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008 and 0.285\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008 cm/year, respectively, which small difference of ~\u0026thinsp;9% is attributed to the water-column mass change. Coincidentally, a 30-year period is commonly regarded as a baseline for climatological normal\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, making this study the first climatological analysis of sea level changes in the CLS.\u003c/p\u003e\n \u003cp\u003eThe strong alignment of SLA and SHA underscores the fact that sea level variability in the CLS is essentially steric, and it is primarily driven by variations of temperature and salinity throughout the water column. Three critical questions arise from this conclusion:\u003c/p\u003e\n \u003cp\u003e[1] Given that winter convection dominates hydrographic variability integrated over the entire 200\u0026ndash;2000 dbar layer\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, is it also true in regard to YASHA and, therefore, YASLA?\u003c/p\u003e\n \u003cp\u003e[2] Do salinity changes always extensively counterbalance and hence offset the concurrent temperature-driven effects on SHA and YASHA, as indicated in previous studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e? Also can either of these effect make a difference in achieving a record high sea level?\u003c/p\u003e\n \u003cp\u003e[3] How significant are the impacts of deep water changes, lying beyond the standard Argo floats depth reach (2000 dbar) and thus often overlooked, on SHA-dominated SLA?\u003c/p\u003e\n \u003cp\u003eThese questions are answered one by one in the following three subsections.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eWinter convection regime changes as the primary driver of sea level variability in the Labrador Sea\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eVariations of steric height, and its thermal expansion driven or thermosteric and haline contraction driven or halosteric components (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e) result from full-depth changes in density (i.e., inverse specific volume), and temperature, and salinity, respectively. In turn, these three key ocean state variables are controlled both locally and remotely through heat, salt and freshwater fluxes driven by air-sea exchange, circulation-driven transport, and vertical and horizontal mixing. The Labrador Sea receives and subsequently transforms the inflows of modified yet still relatively warm and saline Atlantic Water, shallow outflows and deep overflows of cold and fresh Arctic water, and continental freshwater runoffs from rivers, groundwater, and glacier and permafrost meltwater\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. In winter, the surface waters from different sources emit enormous amounts of heat to the atmosphere, consequently cooling, densifying and sinking entraining the underlying waters. This mixing process \u0026ndash; winter convection \u0026ndash; homogenizes a 500\u0026ndash;to\u0026ndash;2500 m top layer producing LSW. The properties and volume of newly-formed LSW are shaped by local atmospheric cooling, advection of cold fresh Arctic and warm saline Atlantic waters, and the water column\u0026rsquo;s retention of low stratification from previous convective events \u0026ndash; a process known as convective preconditioning\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Ref.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e examined two recent shutdowns of deep convection and predicted that this suppression would continue through 2024. Our updated time series shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e confirm the prediction of continued convective shutdown beyond 2023.\u003c/p\u003e\n \u003cp\u003eFurthermore, Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e provides insight into the role of the multiyear convective cycles in SHA and consequently SLA variabilities. The key feature in this figure, the 2012\u0026ndash;2024 convective cycle, comprises the phases of recurrent intensification and deepening (2012\u0026ndash;2018), and subsequent relaxation (2019\u0026ndash;2024) of deep convection, ending with its full shutdown (2021\u0026ndash;2024, except 2022). The bottom panel of Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e highlights the essence of this most recent cyclic water-mass development \u0026ndash; a conglomeration of progressively deepening densifying convective vintages into a voluminous multiyear LSW class. The density and thickness of the recurrently mixed uniform-density layer, termed as pycnostad, are key regional climate state variables. Indeed, the stronger and deeper the winter mixing, the denser and thicker the pycnostad. In turn, dense thick pycnostads make the 0\u0026ndash;2000 dbar average density higher, and \u003cem\u003evice versa\u003c/em\u003e. These linked relationships connect the convective phase changes with the YASHA and YASLA trend changeovers (Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Stronger convective mixing events produce denser thicker pycnostads, and, in turn, lower SHA and SLA. In contrast, weaker convections produce lighter thinner pycnostads, stronger vertical stratification, and, in turn, higher SHA and SLA. This explains why the main driver of convection and deep ocean cooling \u0026ndash; net winter surface heat loss \u0026ndash; is also in control of YASHA and YASLA through ocean cooling dominating mixed layer density, convection depth and vertical stratification. Consequently, the thermosteric component dominates both seasonal and longer-term steric height variability (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). However, as shown next, from moderating (i.e., reducing) the sea level trend the halosteric component has recently switched to reinforcing (i.e., amplifying) it.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eA reversal in the upper layer temperature-salinity steric balance drove the sea level to a record high\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe yearly-averaged full-depth halosteric height resides within about half the thermosteric height range (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, squares). Besides, the interannual halosteric and thermosteric height changes are often opposite in sign, with the former tending to counterbalance the latter. Can it be concluded that the sea level changes driven by thermal expansion are generally half-compensated by concurrent haline contraction? Apparently, it can. Indeed, according to Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, nearly every year from 1990 to 2015, the full-depth halosteric component consistently counteracts against the thermosteric component, offsetting year-to-year thermosteric height changes by about a half. This recurring counterbalance suggests that the partial compensation of thermal expansion by haline contraction was predictably common until 2015. The situation has radically changed afterwards.\u003c/p\u003e\n \u003cp\u003eIn 2016, the halosteric contribution to the interannual steric height change switched from counterbalancing to reinforcing the thermosteric contribution. This transition arose as the halosteric height maintained a positive trend throughout the 2011\u0026ndash;2023 period, while the thermosteric height rebounded from its decline in response to the 2012\u0026ndash;2023 convective cycle\u0026rsquo;s phase change (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The physical processes responsible for the recent transition from halosteric-thermosteric counterbalancing (before 2016) to their allying and covarying (2016\u0026ndash;2024) become evident from Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and the published analysis of the relevant signals and their causes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e recapped here. The CLS water column steadily cooled as convection deepened between 2011 and 2018. Then, these trend reversed as convection entered a relaxation phase. Unlike temperature, salinity, and thus the halosteric component, exhibited a distinct steady multiyear trend throughout the entire 2011\u0026ndash;2024 period, with upper-layer freshening being interrupted only briefly in 2016 and 2017 without disturbing the overall trend. In 2023, the salinity reached a record low, imposed by advection of anomalous quantities of freshwater produced by extreme Arctic sea ice melt a few years earlier\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Driven by the unbalanced freshwater inflow into the Labrador Sea, the halosteric height increased by approximately 5 cm between 2011 and 2023. In contrast, the thermosteric height was lower in 2023 than 2011, as post\u0026ndash;2018 warming could not fully offset the 2011\u0026ndash;2018 cooling. Overall, the contribution of salinity amplified that of temperature after the convective phase reversal, resulting in a higher sea level in 2023 compared to 2011 (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Although the 2024 cycle is still underway at the time of preparation of this article, the ongoing concurrent warming and freshening trends is expected to result in an even high sea level in 2024.\u003c/p\u003e\n \u003cp\u003eOverall, in contrast to moderating the effect of temperature changes on density in the pre\u0026ndash;2016 years, the concurrent salinity changes served to amplify the effect of temperature changes throughout the subsequent reversal and rebound phases of the thermosteric (convective by nature) cycle. By switching from compensating to reinforcing the thermosteric heigh changes in 2016, the halosteric component boosted the temperature-driven sea level rise creating a marked extreme. Indeed, while thermosteric height in 2023 remained 3.6 cm below its 2011 peak (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, red squares), the reported changeover in the halosteric\u0026ndash;thermosteric relationship, from counterbalance to reinforcement, is the second reason behind the CLS sea level rise to a record high in 2023.\u003c/p\u003e\n \u003cp\u003eMoreover, record-breaking rates of the YASHA and YASLA changes over a sliding eight-year interval also fall on 2017\u0026ndash;2024. These rates surpass even those for the 1994\u0026ndash;2001 period brought up by a rapid recovery from record cold, fresh and dense conditions, alongside record low YASHA and YASLA levels (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). A fundamental difference between these two periods lies in the behavior of the halosteric height: in 1994\u0026ndash;2001, it counterbalanced about a half of the thermosteric heigh change, whereas in 2017\u0026ndash;2024, one reinforced the other, accelerating the total SHA and hence SLA increase.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eThe deep layer reinforced the recent sea level trend\u003c/h3\u003e\n\u003cp\u003eThe role of the deep layer in the recent SLA trend and extreme becomes evident when comparing full-depth YASHA (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) with that of the upper layer (Supplementary Fig.\u0026nbsp;2). While the upper-layer YASHA reached its peak in 2012 rather than in 2023, the full-depth YASHA set a record high in 2023. After two decades, 1992\u0026ndash;2011, of relative stability with rather small fluctuations (\u0026plusmn;\u0026thinsp;0.6 cm) deep layer YASHA underwent a positive trend of ~\u0026thinsp;0.22 cm/year, resulting in a cumulative deep SHA increase of ~\u0026thinsp;2.4 cm from 2012 to 2023 (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). This change exceeds the increase in full-depth YASHA over the same period (~\u0026thinsp;1.1 cm), emphasizing the critical role of the deep layer in driving the full-depth SHA, and consequently SLA, to respective unprecedented highs in 2023.\u003c/p\u003e\n\u003cp\u003eThe origin of the positive 2012-onward trend in deep layer is revealed through decomposition of deep layer YASHA into its thermosteric and halosteric components. Between 1990 and 2011, these two components recurrently balanced each other (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), suppressing development of significant decadal trends in deep layer YASHA. This equilibrium was irreversibly disrupted in 2012, leading to a shift in the thermohaline balance that persisted for 11 consecutive years. Throughout this period, the lower variability in halosteric height compared to thermosteric height contributed to the cumulative upward trend in deep layer YASHA.\u003c/p\u003e\n\u003cp\u003eThe [1] multiyear development of deep convection shaping the upper layer\u0026rsquo;s thermosteric heigh trends, [2] covariation and thus reinforcement of the upper layer\u0026rsquo;s thermosteric height changes with the halosteric ones (responding to massive upper layer freshening events), and [3] deep layer\u0026rsquo;s steric heigh trend collectively, through their joint control of full-depth YASHA, drove the CLS sea level to an unprecedented high.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhere there other occurrences of halosteric reinforcements of thermosteric heigh changes in the Labrador Sea in the past?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRecognizing the critical role of the halosteric reinforcement of the 2016\u0026ndash;2024 thermosteric heigh change in the recent sea level rise to a record heigh (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), we extend our analysis to historical hydrographic records dating back to 1948 to assess the occurrence of similar events in the past. The ship and Argo float based hydrographic measurements collected in the CLS from 1948 to 2023 have provided insights into multidecadal cycles of winter convection, water-column cooling and warming, freshening, and salinization\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In this study, we use the updated hydrographic dataset (see \u0026ldquo;Data and Method\u0026rdquo; and Ref.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e for details) to derive the YASHA time series and its components across pressure levels, spaced at 5 dbar intervals from 200 to 3000 dbar and referenced to 3300 dbar (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, the 3000\u0026ndash;3300 dbar layer is not displayed as changes are weak there). To perform adequate comparison with the pre\u0026ndash;Argo observations, the Argo and Deep Argo data are only used in the present analysis for the years without a ship survey (e.g., 2017 and 2021). In all other cases, the long time series shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e are derived from less frequent ship-based measurements.\u003c/p\u003e\n\u003cp\u003eAs seen in Figs. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, the seasonal cycle dominates temporal variability in the top 200 dbar layer (e.g., the seasonal cycle accounts for \u0026gt;\u0026thinsp;92% of the total temperature variance at 10 dbar). Furthermore, even with the regular seasonal cycle subtracted from infrequent pre\u0026ndash;Argo (1948\u0026ndash;2002) ship-based measurements, undersampled irregular seasonal variations may still be present there contributing spurious signals to yearly-averaged values. The upper 200 dbar (meter) layer data, prone to residual seasonal aliasing, has been excluded from the pre-2003 compilations shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. This exclusion has an insignificant effect on the full-depth, 10\u0026ndash;3300 dbar, steric, thermosteric and halosteric heights. The corresponding 10\u0026ndash;3300 dbar and 200\u0026ndash;3300 dbar height differences, particularly for the steric height, are much smaller than the decadal changes (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cem\u003etop\u003c/em\u003e), justifying our choice of the 200\u0026ndash;3300 dbar heights for analyzing longer-term variations in CLS steric sea level. Furthermore, while the exclusion of the upper 200 dbar layer slightly reduces the ranges of height changes, the patterns remain unaffected.\u003c/p\u003e\n\u003cp\u003eThe 200\u0026ndash;3300 dbar steric, thermosteric, and halosteric height extremes for the 1948\u0026ndash;2023 period are highlighted with triangles in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. The timing of these events suggests the following: [1] A thermosteric high and a halosteric low occurred between 1970 and 1971. [2] Conversely, a thermosteric low and a halosteric high were recorded in 1994. [3] The total steric height reached its absolute minimum concurrent with the lowest thermosteric and highest halosteric values, whereas its absolute maximum, achieved in 2023, is comparatively less pronounced in both components. [4] While in the major events of 1948\u0026ndash;2015 the halosteric changes typically counterbalanced the thermosteric changes, after 2015 the halosteric- thermosteric correlation reversed with the two recently showing changes of the same sign and comparable magnitude. Notably, the positive coupling of the post-2015 thermosteric and halosteric heigh changes, coinciding with the most substantial freshening of the 300\u0026ndash;700 dbar layer (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e), challenges the conventional vision of CLS steric heigh changes based on assumption of counteraction of halosteric and thermosteric changes and trends through density compensation.\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e also provides detailed insight into the intermediate and deep layers\u0026apos; contributions to YASHA variability. YASHA time series constructed for pressure levels spaced at 5 dbar are brought together in its second panel (top-down). This compilation clearly shows where in the water column, when and how fast each trend developed, weakened and reversed, and what layer shaped it the most. In most cases, the interannual changes and trends tend to reverse anywhere between the pressure levels of 1250 dbar and 2000 dbar. These reversals, regardless of their exact vertical positions, explain why the trends observed at 200 dbar and 2250 dbar are so profoundly different. Over the 1990\u0026ndash;2021 period, the 200 dbar and 2250 dbar YASHA series displayed opposing trends, each punctuated by short-term reversals in the opposite direction. This inverse symmetry of YASHA changes between the upper and deep layers suggests a counterbalancing effect, where upper-layer changes are offset by those in the deep layer, or vice versa. What particularly important to our study is that in 2022 and 2023, unlike the previous years, YASHA were consistent across all pressure levels, indicating a positive contribution from the deep layers to the 200\u0026ndash;3300 dbar and full-depth steric heights.\u003c/p\u003e\n\u003cp\u003eFurther insights into the impact of the deep layer on upper ocean SHA changes are obtained by comparing thermosteric and halosteric component variations with depth (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, with reversed color-coding for the halosteric height to facilitate comparison). Below 1500 dbar, the two components largely counterbalance each other, although the resulting compensation is not full at all times. For instance, the halosteric component dominated deep-layer residuals from 1991 to 1999, while the thermosteric component did so from 2005 to 2016. In 2022 and 2023, both deep halosteric and thermosteric height anomalies were positive, amplifying the upper layer signal significantly.\u003c/p\u003e\n\u003cp\u003eUnlike its deeper counterpart, the water column\u0026rsquo;s segment above ~\u0026thinsp;1500 dbar, throughout its most extent, is typically stronger affected by the thermosteric component as the upward halosteric gain remains relatively weak. This promotes faster accumulation of thermosteric anomalous signals toward the surface and their prevalence in full-depth YASHA. Strikingly, here again 2022 and 2023 were exceptional. In these years, the upward halosteric gain matched the thermosteric one.\u003c/p\u003e\n\u003cp\u003eThe provided explanation of the deep and intermediate layer contributions to the exceptional CLS sea level of 2023 underscores the uniqueness of the event, and raises its importance for the subpolar and larger North Atlantic domains as local deep and full-depth regime gifts are likely to affect broader scale ocean dynamics and exchanges.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe sea level of the central Labrador Sea (CLS) reached a 76-year record high in 2023. The rapid sea level rise that led to this event was caused by the joint action of mild winters, warm summers, sustained shutdown of deep convection, exceptional upper ocean freshening, deep ocean halosteric-thermosteric balance shift, and full water-column mass gain. While both deep, 1900\u0026ndash;3300 dbar, layer steric height and full-column mass changes contribute to the long-term sea level trend, the interannual-to-decadal variability is predominantly shaped by the upper, 10\u0026ndash;1900 dbar, layer thermosteric and halosteric components. We advance our understanding of the interannual-to-decadal sea level changes with a new approach to reconstruction and prediction of the two steric heigh components (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). We first demonstrate how the thermosteric height series can be reconstructed detailly and accurately, and then discuss the factors affecting the predictability of the halosteric height.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eReconstruction of the interannual thermosteric height changes in the central Labrador Sea using the atmospheric forcing data\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe thermosteric component dominates both interannual and seasonal steric height (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) and hence sea level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) changes. A detailed examination of seasonal patterns across pressure levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) reveals two vital signals with distinct vertical penetration, time lags and signatures \u0026ndash; a deeper winter cooling signal and a shallower summer warming signal. The winter cooling is regulated by \u003cem\u003eWinter Surface Heat Loss\u003c/em\u003e (WSHL), which was thoroughly analyzed in Ref\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e and is calculated by integrating all components of surface heat budget over an individually-defined cooling period\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In contrast, \u003cem\u003eSummer Surface Heat Gain\u003c/em\u003e (SSHG), is calculated for the period when the accumulated net heat flux is directed into the sea. Another characteristic of seasonal warming, used in our work, is \u003cem\u003eSummer Heat Peak\u003c/em\u003e (SHP). SHP is averaged over a fixed-length time interval (e.g., 15, 21, 31 days) centered on a daily surface heat gain peak. The surface heat exchange characteristics are further detailed in the \u0026ldquo;Seasonal air-sea heat exchange metrics\u0026rdquo; subsection and Supplementary Fig.\u0026nbsp;5 caption.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThree key assumptions allow us to empirically model the observed yearly-averaged thermosteric height changes:\u003c/p\u003e \u003cp\u003e[1] air-sea heat exchange is the leading factor controlling the thermosteric height,\u003c/p\u003e \u003cp\u003e[2] the interannual changes of WSHL and SSHG have different and differently lagged effects on the thermosteric height, and need to be assessed separately, and\u003c/p\u003e \u003cp\u003e[3] the residual impacts of previous cooling and warming events (preconditioning\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e) can be approximated by asymmetric low-pass filtering.\u003c/p\u003e \u003cp\u003eWe reconstruct the yearly-averaged thermosteric height series by optimally low-pass filtering, scaling and merging WSHL and SSHG or, alternatively, SHP (SSHG|SHP). All sought parameters are found through iterative approximations aiming to minimize either squared or absolute deviations from the thermosteric heights. The atmospheric variables (e.g., WSHL, SSHG, SHP and NAO) are low-pass filtered using a left-side triangular window with weights decreasing linearly backward from the central point and equal zero forward. The best thermosteric reconstruction is achieved with different WSHL and SSHG|SHP filter window sizes.\u003c/p\u003e \u003cp\u003eThe reconstructed thermosteric heights closely approach their targets, especially after 2000 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The reconstruction captures 96% of the observed variance. The strong correlation (0.98) underscores the robustness of the model in simulating thermosteric contributions to sea level changes over the past three and a half decades, accurately tracking both the overall trend and individual cycles, with observed changes replicated with a 1.0 cm accuracy in 27 out of 33 years (~\u0026thinsp;83%). The overall level of fit that is achieved by using optimally filtered and weighted (scaled) CLS WSHL and SSHG|SHP time series, supports our assumptions and demonstrates the effectiveness of the proposed empirical model, making it suitable for further investigation and interpretation of both atmospheric forcing and signal transfer.\u003c/p\u003e \u003cp\u003eThe difference between the found optimal WSHL and SSHG|SHP left-side triangular window sizes of 7 and 13 years, respectively, emphasizes the different roles of the previous winter conditions retained by the water column, known as convective preconditioning\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and the cumulative effect of summer warming. Indeed, while the winter cooling and mixing are uniquely strong and deep in the Labrador Sea, leaving an immediate trace over a thick layer, the direct effect of summer warming is not that deep. Therefore, it must have taken a longer time and, possibly, a larger region of influence for SSHG to achieve a sizable effect on YASHA and YASLA. By accumulating its signal over a broader domain, SSHG spreads its influence on the thermosteric height over a longer time, hence a longer memory of SSHG changes in YASHA. Yet, while both WSHL and SSHG take turns driving thermosteric height, and the SSHG changes are more influential there on the longer time scales, WSHL dominates in this linkage as a whole. Basing on our results, the WSHL\u0026ndash;thermosteric interaction is performed through convection, hence the leading role of convective cycles in sea level variability in the CLS domain.\u003c/p\u003e \u003cp\u003eNotably, while the low-pass filtered winter (DJFM) NAO index shows some limited agreement with the yearly-averaged thermosteric height, it lacks the precision and detail captured by the presented heat-based model, highlighting the superior predictive accuracy of the heat-based reconstruction approach.\u003c/p\u003e\n\u003ch3\u003eLinking halosteric height to the extreme Arctic sea ice losses\u003c/h3\u003e\n\u003cp\u003eThe significant reductions in Arctic sea ice in 2007, 2012, and 2019\u0026ndash;2020 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) were each followed by pronounced freshening in the upper layer of the Labrador Sea approximately two years later\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. This freshening could also be influenced by a recent shift in the Beaufort Gyre\u0026rsquo;s regime from freshwater accumulation to stabilization, with a potential release phase that may contribute to the latest CLS freshening event. In contrast, the Greenland freshwater flux anomaly, which changes more gradually over time, is unlikely to drive rapid freshening events in the CLS\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. For this reason, we focus our analysis on the impacts of extreme Arctic sea ice loss as the primary driver of intermittent CLS halosteric height changes.\u003c/p\u003e \u003cp\u003eThe arrows in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e point from the 2007, 2012 and 2020 extreme winter-to-summer Arctic sea ice reductions to the 2009, 2015 and 2022 CLS halosteric height maxima \u0026ndash; with the latter lagged relative to the former by 2\u0026ndash;3 years. The connection between these two sets of extremes follows from the analysis of the respective negative salinity anomalies originated from the freshened Arctic outflow entering the Labrador Sea through Davis Strait\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, one might question the lack of substantial annual reductions in Arctic sea ice preceding the 1996\u0026ndash;2005 period, during which CLS halosteric height was decreasing alongside rising salinity. This period coincided with exceptionally strong and sustained deep convection from the late 1980s to the mid\u0026ndash;1990s, which infused the CLS water column with an estimated 7-meter freshwater equivalent\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. As the sea entered a convective relaxation phase in 1996, freshwater began to discharge from its intermediate layer into the broader North Atlantic, resulting in a gradual reduction in halosteric height during this relaxation phase.\u003c/p\u003e\n\u003ch3\u003eRemaining challenges and future steps\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eInterannual and seasonal water-column mass budgets\u003c/h2\u003e \u003cp\u003eAlthough the differences between YASLA and full-depth YASHA are relatively small, they are systematically persistent over time and thus comparable to deep-layer YASHA, particularly since 2016 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These differences reflect water-column mass changes expressed in equivalent water thickness. The inferred mass changes (black line in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) show stable variations over the period of 1993\u0026ndash;2005, followed by a continuous decrease between 2005 and 2015, and a subsequent reversal to an increase lasting from 2016 to 2021, amounting to 3 cm and thus becoming a contributing factor to the recent sea level rise and extreme.\u003c/p\u003e \u003cp\u003eThe Gravity Recovery and Climate Experiment (GRACE) satellite data offer an alternative method to assess water-column mass changes. However, the mass measurements extracted from the JPL and CSR GRACE datasets and de-seasoned show inconsistent interannual patterns and opposing trends that appear unrealistic for our study region (see Supplementary Fig.\u0026nbsp;3), making any direct comparison with YASLA\u0026ndash;YASHA differences unattainable at the moment. However, once a linear trend is removed from the CSR GRACE time series (green line in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), the interannual variability aligns more closely with the inferred mass changes.\u003c/p\u003e \u003cp\u003eUnlike the unrealistic long-term trends dominating the JPL and CSR GRACE time series, the associated regular seasonal cycles appear very similar in magnitude to the seasonal cycle based on the YASLA \u0026ndash; full-depth YASHA differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Both GRACE and altimetry-hydrography based regular seasonal cycles clearly show a systematic mass increase toward summer and decrease toward winter. Although there is a time difference between achieving high states by the two types of mass estimates, requiring future investigation, the common mass cycle pattern can be explained by intensification of the cyclonic circulation and hence the divergence of mass over the basin in winter, and weakening of the boundary currents reducing the divergence in summer. This mechanism as well as alternative explanations of the seasonal water-column mass changes await a dedicated study. However, a comparison of the winter and summer altimetry-derived kinetic energy maps (Fig.\u0026nbsp;9) supports our hypothesis with the wintertime intensification of the boundary currents and hence cyclonic circulation act against the convergence of mass over the CLS domain.\u003c/p\u003e \u003cp\u003eGiven the overall importance of water-column mass changes to diagnosing and predicting sea level changes, further examinations of the GRACE data quality and derived mass, and finding the reasons behind the unrealistic interannual and longer-term changes in the Labrador Sea are necessary.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003eTo fully understand the sea level budget in the central Labrador Sea (CLS), we co-analyze multi-mission satellite altimetry, historical (1948\u0026ndash;1989) and high-quality World Ocean Circulation Experiment legacy ship-based (1990\u0026ndash;2019), standard (2002\u0026ndash;2024) and Deep Argo (2020\u0026ndash;2024) float, satellite gravimetry (2002\u0026ndash;2024), atmospheric reanalysis, and Arctic sea ice extent (1979\u0026ndash;2024) data\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The \u0026ldquo;\u003cem\u003eData Sources\u003c/em\u003e\u0026rdquo; section offers a brief overview of the respective data sources, while the \u0026ldquo;\u003cem\u003eMethods\u003c/em\u003e\u0026rdquo; section recaps data processing and analysis steps followed in this study.\u003c/p\u003e\n\u003ch3\u003eTime series decomposition\u003c/h3\u003e\n\u003cp\u003eOur study is based on hydrographic and altimetric observations at specific locations and times without temporal and spatial interpolation, gridding and smoothing. This approach to data analysis eliminates errors and uncertainties related to interpolation over extensive data gaps, excessive data smoothing and signal aliasing. Even vertical interpolation of water sample, reversing thermometer and low-resolution Argo float data is only performed with observations with sufficiently close vertical range of each other. Observations collected within certain geographic locations vary in time with respect to sampling or measurement frequency, contain extensive data omissions or gaps, and therefore form irregular time series. Irregular time series are analyzed by applying a special technique of iterative time series decomposition to all available measurements supplied with their corresponding times\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. In this method, each value in a long-term record is regarded as a sum of [1] a regular (i.e., long-term mean or climatological normal) seasonal cycle, [2] irregular seasonal variations, which may be imposed by interannual seasonal phase and amplitude shifts), [3] interannual-to-multidecadal changes and trends, [4] mesoscale and synoptic natural variability (e.g., driven by mesoscale eddies and jet-like currents), [5] high-frequency (e.g., diurnal, inertial, tidal) variability, and [6] instrumental noise, including sampling and data processing errors. The successive iterations of reevaluation of these components and noise removal are performed until the first three components and residual variance (associated with the mesoscale and higher-frequency components) are stabilized, and no new outliers (errors) are detected and removed.\u003c/p\u003e\n\u003cp\u003eThe regular seasonal cycles of sea level and steric height anomalies, and of thermosteric and halosteric height components are shown in Figs. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, and in Supplementary Fig. 4, respectively. The dots in Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e and Supplementary Fig. 4, represent the observed values with removed low-frequency variability. Each regular seasonal cycle has been reevaluated on every successive iteration of the time series decomposition process \u0026ndash; the original data series, with the outliers and low-frequency variability revealed on the previous iteration removed, is approximated with a sum of multiple-annual-frequency (i.e., [0, 1, 2, 3, 4, etc.] cycles/year) harmonics. The multiple-annual-frequency cutoff is based on the amount of variance of the original series explained by higher frequencies. The amount of variance explained by the cutoff and higher frequencies is negligibly small.\u003c/p\u003e\n\u003cp\u003eDepending on characteristic features and scales of underlying variability, and temporal changes of sampling frequency and consistency, the low-frequency component is evaluated through either low-pass filtering or polynomial fitting of deviations from the last evaluated regular seasonal cycle. The deviations are either time-bin-averaged or weighted prior to evaluation of the low-frequency component to suppress the effects or biases of temporally uneven data distributions on the time series decomposition. The results shown in Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e are obtained with polynomial fitting of bin-averaged deviation. The markers in Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e represent yearly averaged deviations from the regular seasonal cycle. The dark red and dark blue lines in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e show the low-frequency component, representing interannual-to-multidecadal changes of sea level and steric height, while the red and blue lines show this component summed with the regular seasonal cycle and irregular seasonal variations.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eCalculation of steric, thermosteric and halosteric heigh anomalies\u003c/h2\u003e\n \u003cp\u003eSteric height anomaly and its thermosteric and halosteric components are computed as follows.\u003c/p\u003e\n \u003cp\u003eSteric Height Anomaly (SHA):\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({V_{sp}}\\)\u003c/span\u003e\u003c/span\u003e is the specific volume (i.e., the inverse of density); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({S_A}\\)\u003c/span\u003e\u003c/span\u003e is the absolute salinity (g/kg); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T_C}\\)\u003c/span\u003e\u003c/span\u003e is the conservative temperature (\u003csup\u003eo\u003c/sup\u003eC); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({S_{A - mean}}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T_{C - mean}}\\)\u003c/span\u003e\u003c/span\u003e are climatology mean of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({S_A}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T_C}\\)\u003c/span\u003e\u003c/span\u003e; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({p_1}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({p_2}\\)\u003c/span\u003e\u003c/span\u003e are the upper and lower pressure limits of corresponding layers; g is the gravitational acceleration constant as 9.81 m/s\u003csup\u003e2\u003c/sup\u003e. Absolute salinity, conservative temperature, and pressure are used to compute specific volume, enabling the calculation of steric sea level based on the TEOS-10 equation of state\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eReconstruction and prediction of 10-1900 dbar thermosteric height based on optimization of contributions of winter cooling and summer warming\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAs discussed in the main text, the yearly-averaged thermosteric height is reconstructed by optimizing contributions from low-pass filtered total \u003cem\u003eWinter Surface Heat Loss\u003c/em\u003e (WSHL) and total \u003cem\u003eSummer Surface Heat Gain\u003c/em\u003e (SSHG) or, alternatively to SSHG, mean \u003cem\u003eSummer Heat Peak\u003c/em\u003e (SHP), explained in the \u0026ldquo;\u003cem\u003eSeasonal air-sea heat exchange metrics\u003c/em\u003e\u0026rdquo; subsection. The model employs a filter window, which weight decreases linearly with each step backward from the central point having the highest weight. The points located ahead of the central point are assigned zero weights. The filter size is defined as the number of points, including the central point, with non-zero weights (one year means retaining unfiltered data). Such low-pass filter design allows to prorate the contributions of the past forcing conditions to the present ocean state simply and efficiently.\u003c/p\u003e\n \u003cp\u003eWSHL and SSHG|SHP were low-pass filtered independent from each other with the respective left-side triangular filter window sizes ranging from 1 to 25 years. The WSHL and SSHG|SHP low-pass filtered series were then added together for all 25\u0026times;25\u0026thinsp;=\u0026thinsp;625 filter size combinations and for each weigh of the SSHG|SHP-based contribution selected from a wide range of closely-spaced values. This approach led us to a stable optimal solution of the thermosteric height reconstruction problem. As partially (for four of 25 tested WSHL filter window sizes) shown in Supplementary Fig.\u0026nbsp;5, the closest match of the observed and reconstructed yearly-averaged thermosteric heights is unambiguously achieved with the 7-year and 13-year low-pass filtering of SSHG|SHP, respectively, for a certain weight (~\u0026thinsp;26) of the SHP relative to WSHL.\u003c/p\u003e\n \u003cp\u003eRemarkably, the WSHL and SSHG|SHP low-pass filter window sizes, yielding the best agreement with both thermosteric height and 10-1900 dbar ocean heat content, are different. Namely, these sizes are 7 years for WSHL and 13 years for SSHG|SHP. This difference reflects the distinct roles of deep, rapidly progressing (5\u0026ndash;7 years) during its active phase, winter convection and broader slower-acting interannual variations of summer warming. Our new approach to diagnosing the thermosteric heigh variations highlights the stronger and immediate impact of winter cooling compared to the longer-lasting cumulative effects of summer warming.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe polynomial, including linear, approximation of the analyzed series is based on the least-squares fitting technique. To improve stability of higher-order polynomial fits, the input variables (e.g., year) are centered and scaled to the ranges providing most stable solutions. The 95% confidence interval was derived based on the standard error scaled by two-tailed Student\u0026rsquo;s t test.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eData sources\u003c/strong\u003e\u003c/p\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlong-track satellite altimetry data\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLevel-3 1Hz along-track sea surface height anomalies (SLA), computed relative to a 20-year mean climatology (1993\u0026ndash;2012) with ~\u0026thinsp;7 km (1 Hz) spatial sampling, were used to derive the CLS sea level time series (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). These data were processed by the DUACS multimission altimeter system (product SEALEVEL_GLO_PHY_L3_MY_008_062, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.48670/moi-00146\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e and include observations from multiple satellite missions (e.g., ERS-1, ERS-2, Topex/Poseidon, Jason-1/2/3, Envisat, Cryosat-2, Saral/AltiKa, Sentinel-3A/3B, Sentinel-6A, HY-2A/2B, Geosat Follow-On). The dataset was accessed through the Copernicus Marine Service portal (last accessed in November, 2024; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.marine.copernicus.eu\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGridded satellite altimetry data\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLevel-4 gridded SLA merges Level-3 along-track measurements from multiple altimeter missions by optimal interpolation (cmems_obs-sl_glo_phy-ssh_my_allsat-l4-duacs-0.25deg_P1D, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.48670/moi-00148\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e In addition to SLA, the product provides variables such as Absolute Dynamic Topography and geostrophic currents (both absolute values and anomalies). The gridded dataset was used to generate Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and last accessed in November, 2024.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSatellite gravimetry data\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTo evaluate mass contributions to sea-level change, we use two GRACE/GRACE-FO datasets, including the JPL GRACE and GRACE-FO Mascon Ocean, Ice, and Hydrology Equivalent Water Height Coastal Resolution Improvement (CRI) Filtered Release 06 Version 02\u003c/p\u003e\n \u003cp\u003e(TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06_V2)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e and the CSR GRACE/GRACE-FO RL06 Mascon Solutions (Version 02)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. The JPL dataset, processed and distributed by the Jet Propulsion Laboratory (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://grace.jpl.nasa.gov\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, provides monthly equivalent water thickness anomalies (in cm) at its nominal resolution is 0.5\u0026deg;\u0026times;0.5\u0026deg;. The CSR dataset, processed by the Center for Space Research and accessible at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www2.csr.utexas.edu/grace\u003c/span\u003e\u003c/span\u003e, offers monthly 1/4\u0026deg;\u0026times;1/4\u0026deg; global coverage. The effective resolution\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e of both monthly gravity fields is 3\u0026deg;\u0026times;3\u0026deg;. Spanning January 1993 to present, GRACE datasets includes data gaps due to technical issues, with details available at the GRACE mission portal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://grace.jpl.nasa.gov/data/grace_months/\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Both satellite gravimetry datasets were last accessed in October 2024.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultiplatform hydrographic measurements\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis study integrates hydrographic data from multiple sources, including profiling Argo float (2002\u0026ndash;2024), historical water sample and reversing thermometer ship-based (1948\u0026ndash;1985) and recent high-resolution ship-based observations, to construct steric sea level time series in the CLS (Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). Comprehensive details on hydrographic data quality control, editing, and merging procedures are provided in Ref\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, while here we recap the history of these observations. Systematic observations in the Labrador Sea date back to the late 1940s, with the major contributions for more than two decades being associated with the International Ice Patrol, U.S. Coast Guard, and Ocean Weather Ship Bravo\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Dedicated research missions, such as the 1966 and 1976 CSS Hudson expeditions, raised attention to the Labrador Sea as a key intermediate-depth water source of the North Atlantic. The Atlantic Repeat Hydrography Line 7-West (AR7W) line surveys conducted by the Bedford Institute of Oceanography over the period of 1990\u0026ndash;2019\u003csup\u003e21,24,53,54\u003c/sup\u003e provided measurements of exceptionally high accuracy. The Argo float profiles, massively increasing in numbers since 2002, reduce our reliance on ship-based observations, offering year-round 0\u0026ndash;2000 m and full-depth data to resolve seasonal and interannual variability, particularly in years without ship surveys (e.g., 2017, 2021). Rigorous quality control, including calibration of ship-based sensors and advanced Argo float data quality control, validation and correction carried forward from our previous study\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, ensures consistency and accuracy across datasets. Advanced, adapted to routine utilization of observations from various platforms (e.g., floats, ships), data processing techniques further improve temporal and spatial resolution, enabling detailed analysis of long-term trends and seasonal cycles in the CLS.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eNorth Atlantic Oscillation (NAO)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe North Atlantic Oscillation (NAO) is a key teleconnection pattern affecting atmospheric conditions in the Labrador Sea\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. A positive NAO phase increases the sea level pressure (SLP) difference between the Icelandic low and Azores high, intensifying westerlies that bring cold, dry air to the region. Conversely, a negative NAO weakens westerlies, leading to warmer conditions. The winter NAO index (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e) is derived from December-to-March principal component-based values using the first empirical orthogonal function of 500-mbar height anomalies (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeasonal air-sea heat exchange metrics\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe atmospheric variables and reconstructed \u003cem\u003eWinter Surface Heat Loss\u003c/em\u003e (WSHL), \u003cem\u003eSummer Surface Heat Gain\u003c/em\u003e (SSHG) and \u003cem\u003eSummer Heat Peak\u003c/em\u003e (SHP) used in this study (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e and Supplementary Fig. 5) are based on the NCEP/NCAR Reanalysis datasets\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html\u003c/span\u003e\u003c/span\u003e; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, provided by NOAA, USA. The Reanalysis products (R1 and R2) of the highest available resolution (6-hourly) were compared and jointly utilized to achieve comprehensive and detailed atmospheric data coverage.\u003c/p\u003e\n \u003cp\u003eNet surface heat flux (NSHF) values were computed by combining the shortwave and longwave radiative fluxes and turbulent latent and sensible heat fluxes from 6-hourly NCEP/NCAR fields, averaged over the central Labrador Sea (CLS, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, green circle). The start and end points of an individual winter season were defined from NSHF sign reversals. Starting in late fall with a positive-to-negative NSHF transition, the cooling or winter season ends in early spring, when NSHF changes from negative to positive. Summer seasons were defined as the periods between the spring and fall NSHF sign reversals, when the net surface heat flux remained consistently positive, indicating ocean heat gain. WSHL was determined by integrating NSHF over a full cooling period, excluding short-term reversals have negligible impact on the total heat loss. Integrating NSHF over a warming period gives SSHG, averaging it over a period (e.g., 31-day long) centered on an outgoing flux high gives SHP\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003cp\u003e\u003cstrong\u003eArctic sea ice extent\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eArctic sea ice extent and volume\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e data were downloaded from the National Snow and Ice Data Center (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nsidc.org/home\u003c/span\u003e\u003c/span\u003e) and Polar Science Center (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Annual winter-to-summer Arctic sea ice extent reductions (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e) were calculated by interpolating small data gaps, computing 1979\u0026ndash;2024 daily means from gap-free years, and subtracting these means from daily values. Late-winter (Feb-Mar) and late-summer (Aug-Oct) averages and their differences were derived from the anomalies.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Editors for bringing the exceptional climate condition of 2023 to public attention, and the reviewers for their critical and constructive suggestions helping to improve this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eCode Availability\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMatlab, including M_Map toobox\u003csup\u003e59\u003c/sup\u003e, Visual Basic for Applications (VBA) and Golden Software Surfer were used for computations and visualization.\u003c/p\u003e\n\u003cp\u003eContinuously updated codes and related instructions are available from the corresponding author (Igor Yashayaev, emails: [email protected]; [email protected]) upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHansen, J., Sato, M., Kharecha, P. \u0026amp; von Schuckmann, K. Earth\u0026rsquo;s energy imbalance and implications. \u003cem\u003eAtmospheric Chemistry and Physics\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 13421\u0026ndash;13449 (2011).\u003c/li\u003e\n \u003cli\u003eTrenberth, K. E., Fasullo, J. T. \u0026amp; Balmaseda, M. A. Earth\u0026rsquo;s Energy Imbalance. (2014) doi:10.1175/JCLI-D-13-00294.1.\u003c/li\u003e\n \u003cli\u003eRoemmich, D. \u003cem\u003eet al.\u003c/em\u003e Unabated planetary warming and its ocean structure since 2006. \u003cem\u003eNature Clim Change\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 240\u0026ndash;245 (2015).\u003c/li\u003e\n \u003cli\u003evon Schuckmann, K. \u003cem\u003eet al.\u003c/em\u003e Heat stored in the Earth system 1960\u0026ndash;2020: where does the energy go? \u003cem\u003eEarth System Science Data\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1675\u0026ndash;1709 (2023).\u003c/li\u003e\n \u003cli\u003evon Schuckmann, K. \u003cem\u003eet al.\u003c/em\u003e An imperative to monitor Earth\u0026rsquo;s energy imbalance. \u003cem\u003eNature Clim Change\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 138\u0026ndash;144 (2016).\u003c/li\u003e\n \u003cli\u003eHakuba, M. Z., Frederikse, T. \u0026amp; Landerer, F. W. Earth\u0026rsquo;s Energy Imbalance From the Ocean Perspective (2005\u0026ndash;2019). \u003cem\u003eGeophysical Research Letters\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, e2021GL093624 (2021).\u003c/li\u003e\n \u003cli\u003eHakuba, M. Z. \u003cem\u003eet al.\u003c/em\u003e Trends and Variability in Earth\u0026rsquo;s Energy Imbalance and Ocean Heat Uptake Since 2005. \u003cem\u003eSurv Geophys\u003c/em\u003e (2024).\u003c/li\u003e\n \u003cli\u003eCurry, R., Dickson, B. \u0026amp; Yashayaev, I. A change in the freshwater balance of the Atlantic Ocean over the past four decades. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e426\u003c/strong\u003e, 826\u0026ndash;829 (2003).\u003c/li\u003e\n \u003cli\u003eChen, J. L., Wilson, C. R. \u0026amp; Tapley, B. D. Satellite Gravity Measurements Confirm Accelerated Melting of Greenland Ice Sheet. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e313\u003c/strong\u003e, 1958\u0026ndash;1960 (2006).\u003c/li\u003e\n \u003cli\u003ePerovich, D. K. \u0026amp; Richter-Menge, J. A. Loss of Sea Ice in the Arctic*. \u003cem\u003eAnnual Review of Marine Science\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 417\u0026ndash;441 (2009).\u003c/li\u003e\n \u003cli\u003eMaksym, T. Arctic and Antarctic Sea Ice Change: Contrasts, Commonalities, and Causes. \u003cem\u003eAnnu. Rev. Mar. Sci.\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 187\u0026ndash;213 (2019).\u003c/li\u003e\n \u003cli\u003eRignot, E., Jacobs, S., Mouginot, J. \u0026amp; Scheuchl, B. Ice-Shelf Melting Around Antarctica. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e341\u003c/strong\u003e, 266\u0026ndash;270 (2013).\u003c/li\u003e\n \u003cli\u003eLlovel, W., Willis, J. K., Landerer, F. W. \u0026amp; Fukumori, I. Deep-ocean contribution to sea level and energy budget not detectable over the past decade. \u003cem\u003eNature Clim Change\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 1031\u0026ndash;1035 (2014).\u003c/li\u003e\n \u003cli\u003eGregory, J. M. \u003cem\u003eet al.\u003c/em\u003e Concepts and Terminology for Sea Level: Mean, Variability and Change, Both Local and Global. \u003cem\u003eSurv Geophys\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 1251\u0026ndash;1289 (2019).\u003c/li\u003e\n \u003cli\u003eChambers, D. P. \u003cem\u003eet al.\u003c/em\u003e Evaluation of the Global Mean Sea Level Budget Between 1993 and 2014. in \u003cem\u003eIntegrative Study of the Mean Sea Level and Its Components\u003c/em\u003e (eds. Cazenave, A., Champollion, N., Paul, F. \u0026amp; Benveniste, J.) 315\u0026ndash;333 (2017).\u003c/li\u003e\n \u003cli\u003eZhang, J. \u003cem\u003eet al.\u003c/em\u003e Labrador Sea freshening linked to Beaufort Gyre freshwater release. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 1229 (2021).\u003c/li\u003e\n \u003cli\u003eYang, Q. \u003cem\u003eet al.\u003c/em\u003e Recent increases in Arctic freshwater flux affects Labrador Sea convection and Atlantic overturning circulation. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 10525 (2016).\u003c/li\u003e\n \u003cli\u003ePrevidi, M., Smith, K. L. \u0026amp; Polvani, L. M. Arctic amplification of climate change: a review of underlying mechanisms. \u003cem\u003eEnviron. Res. Lett.\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 093003 (2021).\u003c/li\u003e\n \u003cli\u003eDukhovskoy, D. S. \u003cem\u003eet al.\u003c/em\u003e Role of Greenland Freshwater Anomaly in the Recent Freshening of the Subpolar North Atlantic. \u003cem\u003eJGR Oceans\u003c/em\u003e \u003cstrong\u003e124\u003c/strong\u003e, 3333\u0026ndash;3360 (2019).\u003c/li\u003e\n \u003cli\u003eB\u0026ouml;ning, C. W., Behrens, E., Biastoch, A., Getzlaff, K. \u0026amp; Bamber, J. L. Emerging impact of Greenland meltwater on deepwater formation in the North Atlantic Ocean. \u003cem\u003eNature Geosci\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 523\u0026ndash;527 (2016).\u003c/li\u003e\n \u003cli\u003eYashayaev, I. Intensification and shutdown of deep convection in the Labrador Sea were caused by changes in atmospheric and freshwater dynamics. \u003cem\u003eCommun Earth Environ\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 1\u0026ndash;23 (2024).\u003c/li\u003e\n \u003cli\u003eYashayaev, I., Holliday, N. P., Bersch, M. \u0026amp; van Aken, H. M. The History of the Labrador Sea Water: Production, Spreading, Transformation and Loss. in \u003cem\u003eArctic\u0026ndash;Subarctic Ocean Fluxes: Defining the Role of the Northern Seas in Climate\u003c/em\u003e (eds. Dickson, R. R., Meincke, J. \u0026amp; Rhines, P.) 569\u0026ndash;612 (Springer Netherlands, Dordrecht, 2008). doi:10.1007/978-1-4020-6774-7_25.\u003c/li\u003e\n \u003cli\u003eFeucher, C., Garcia‐Quintana, Y., Yashayaev, I., Hu, X. \u0026amp; Myers, P. G. Labrador Sea Water Formation Rate and Its Impact on the Local Meridional Overturning Circulation. \u003cem\u003eJGR Oceans\u003c/em\u003e \u003cstrong\u003e124\u003c/strong\u003e, 5654\u0026ndash;5670 (2019).\u003c/li\u003e\n \u003cli\u003eLazier, J., Hendry, R., Clarke, A., Yashayaev, I. \u0026amp; Rhines, P. Convection and restratification in the Labrador Sea, 1990\u0026ndash;2000. \u003cem\u003eDeep Sea Research Part I: Oceanographic Research Papers\u003c/em\u003e \u003cstrong\u003e49\u003c/strong\u003e, 1819\u0026ndash;1835 (2002).\u003c/li\u003e\n \u003cli\u003eVan Aken, H. M., Femke De Jong, M. \u0026amp; Yashayaev, I. Decadal and multi-decadal variability of Labrador Sea Water in the north-western North Atlantic Ocean derived from tracer distributions: Heat budget, ventilation, and advection. \u003cem\u003eDeep Sea Research Part I: Oceanographic Research Papers\u003c/em\u003e \u003cstrong\u003e58\u003c/strong\u003e, 505\u0026ndash;523 (2011).\u003c/li\u003e\n \u003cli\u003eYashayaev, I. \u0026amp; Loder, J. W. Recurrent replenishment of Labrador Sea Water and associated decadal-scale variability: 2015 Convection in Labrador Sea. \u003cem\u003eJ. Geophys. Res. Oceans\u003c/em\u003e \u003cstrong\u003e121\u003c/strong\u003e, 8095\u0026ndash;8114 (2016).\u003c/li\u003e\n \u003cli\u003eChomiak, L. N., Yashayaev, I., Volkov, D. L., Schmid, C. \u0026amp; Hooper, J. A. Inferring Advective Timescales and Overturning Pathways of the Deep Western Boundary Current in the North Atlantic Through Labrador Sea Water Advection. \u003cem\u003eJGR Oceans\u003c/em\u003e \u003cstrong\u003e127\u003c/strong\u003e, e2022JC018892 (2022).\u003c/li\u003e\n \u003cli\u003eFunk, A., Brandt, P., Schott, F. \u0026amp; Emery, W. SEA LEVEL ANOMALIES IN THE LABRADOR SEA. (2006).\u003c/li\u003e\n \u003cli\u003eThompson, K. R., Bernier, N. B. \u0026amp; Chan, P. Extreme sea levels, coastal flooding and climate change with a focus on Atlantic Canada. \u003cem\u003eNat Hazards\u003c/em\u003e \u003cstrong\u003e51\u003c/strong\u003e, 139\u0026ndash;150 (2009).\u003c/li\u003e\n \u003cli\u003eHayashi, N. \u0026amp; Delaney, A. E. Climate change, community well-being, and consumption: Reconsidering human-environment relationships in Greenland under global change. \u003cem\u003ePolar Science\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 101102 (2024).\u003c/li\u003e\n \u003cli\u003eGill, A. E. \u0026amp; Niller, P. P. The theory of the seasonal variability in the ocean. \u003cem\u003eDeep Sea Research and Oceanographic Abstracts\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 141\u0026ndash;177 (1973).\u003c/li\u003e\n \u003cli\u003eFerry, N., Reverdin, G. \u0026amp; Oschlies, A. Seasonal sea surface height variability in the North Atlantic Ocean. \u003cem\u003eJ. Geophys. Res.\u003c/em\u003e \u003cstrong\u003e105\u003c/strong\u003e, 6307\u0026ndash;6326 (2000).\u003c/li\u003e\n \u003cli\u003eStraneo, F. Heat and Freshwater Transport through the Central Labrador Sea. (2006) doi:10.1175/JPO2875.1.\u003c/li\u003e\n \u003cli\u003eVolkov, D. L. \u003cem\u003eet al.\u003c/em\u003e Interannual to decadal sea level variability in the subpolar North Atlantic: the role of propagating signals. \u003cem\u003eOcean Sci.\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 1741\u0026ndash;1762 (2022).\u003c/li\u003e\n \u003cli\u003eAntonov, J. I., Levitus, S. \u0026amp; Boyer, T. P. Steric sea level variations during 1957\u0026ndash;1994: Importance of salinity. \u003cem\u003eJournal of Geophysical Research: Oceans\u003c/em\u003e \u003cstrong\u003e107\u003c/strong\u003e, SRF 14-1-SRF 14-8 (2002).\u003c/li\u003e\n \u003cli\u003eLevitus, S., Antonov, J. I., Boyer, T. P., Garcia, H. E. \u0026amp; Locarnini, R. A. Linear trends of zonally averaged thermosteric, halosteric, and total steric sea level for individual ocean basins and the world ocean, (1955\u0026ndash;1959)\u0026ndash;(1994\u0026ndash;1998). \u003cem\u003eGeophysical Research Letters\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, (2005).\u003c/li\u003e\n \u003cli\u003eWang, G., Cheng, L., Boyer, T. \u0026amp; Li, C. Halosteric Sea Level Changes during the Argo Era. \u003cem\u003eWater\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 484 (2017).\u003c/li\u003e\n \u003cli\u003eTrewin, B. C. The role of climatological normals in a changing climate. WMO-TD 1377, WCDMP 61. World Climate Data and Monitoring Programme. \u003cem\u003eWorld Meteorological Organization, Geneva\u003c/em\u003e (2007).\u003c/li\u003e\n \u003cli\u003eDickson, R. \u003cem\u003eet al.\u003c/em\u003e Current estimates of freshwater flux through Arctic and subarctic seas. \u003cem\u003eProgress in Oceanography\u003c/em\u003e \u003cstrong\u003e73\u003c/strong\u003e, 210\u0026ndash;230 (2007).\u003c/li\u003e\n \u003cli\u003eDickson, R. R., Curry, R. \u0026amp; Yashayaev, I. Recent changes in the North Atlantic. \u003cem\u003ePhilosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences\u003c/em\u003e \u003cstrong\u003e361\u003c/strong\u003e, 1917\u0026ndash;1934 (2003).\u003c/li\u003e\n \u003cli\u003eDickson, B. \u003cem\u003eet al.\u003c/em\u003e Rapid freshening of the deep North Atlantic Ocean over the past four decades. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e416\u003c/strong\u003e, 832\u0026ndash;837 (2002).\u003c/li\u003e\n \u003cli\u003eYashayaev, I. Hydrographic changes in the Labrador Sea, 1960\u0026ndash;2005. \u003cem\u003eProgress in Oceanography\u003c/em\u003e \u003cstrong\u003e73\u003c/strong\u003e, 242\u0026ndash;276 (2007).\u003c/li\u003e\n \u003cli\u003eYashayaev, I., Van Aken, H. M., Holliday, N. P. \u0026amp; Bersch, M. Transformation of the Labrador Sea Water in the subpolar North Atlantic. \u003cem\u003eGeophysical Research Letters\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 2007GL031812 (2007).\u003c/li\u003e\n \u003cli\u003eYashayaev, I. M. \u0026amp; Zveryaev, I. I. Climate of the seasonal cycle in the North Pacific and the North Atlantic oceans. \u003cem\u003eIntl Journal of Climatology\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 401\u0026ndash;417 (2001).\u003c/li\u003e\n \u003cli\u003eYashayaev, I. \u0026amp; Seidov, D. The role of the Atlantic Water in multidecadal ocean variability in the Nordic and Barents Seas. \u003cem\u003eProgress in Oceanography\u003c/em\u003e \u003cstrong\u003e132\u003c/strong\u003e, 68\u0026ndash;127 (2015).\u003c/li\u003e\n \u003cli\u003eMcDougall, T. J. \u003cem\u003eet al.\u003c/em\u003e The International Thermodynamic Equation Of Seawater 2010 (TEOS-10): Calculation and Use of Thermodynamic Properties.\u003c/li\u003e\n \u003cli\u003eWiese, D. N., Landerer, F. W. \u0026amp; Watkins, M. M. GRACE:Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution. \u003cem\u003eWater Resources Research\u003c/em\u003e \u003cstrong\u003e52\u003c/strong\u003e, 7490\u0026ndash;7502 (2016).\u003c/li\u003e\n \u003cli\u003eWatkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C. \u0026amp; Landerer, F. W. Improved methods for observing Earth\u0026rsquo;s time variable mass distribution with GRACE using spherical cap mascons. \u003cem\u003eJournal of Geophysical Research: Solid Earth\u003c/em\u003e \u003cstrong\u003e120\u003c/strong\u003e, 2648\u0026ndash;2671 (2015).\u003c/li\u003e\n \u003cli\u003eLanderer, F. W. \u003cem\u003eet al.\u003c/em\u003e Extending the Global Mass Change Data Record: GRACE Follow-On Instrument and Science Data Performance. \u003cem\u003eGeophysical Research Letters\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, e2020GL088306 (2020).\u003c/li\u003e\n \u003cli\u003eSave, H. CSR GRACE and GRACE-FO RL06 Mascon Solutions v02. \u003cem\u003eUniversity of Texas at Austin\u003c/em\u003e 1 (2020).\u003c/li\u003e\n \u003cli\u003eSave, H., Bettadpur, S. \u0026amp; Tapley, B. D. High-resolution CSR GRACE RL05 mascons. \u003cem\u003eJournal of Geophysical Research: Solid Earth\u003c/em\u003e \u003cstrong\u003e121\u003c/strong\u003e, 7547\u0026ndash;7569 (2016).\u003c/li\u003e\n \u003cli\u003eYashayaev, I., Seidov, D. \u0026amp; Demirov, E. A new collective view of oceanography of the Arctic and North Atlantic basins. \u003cem\u003eProgress in Oceanography\u003c/em\u003e \u003cstrong\u003e132\u003c/strong\u003e, 1\u0026ndash;21 (2015).\u003c/li\u003e\n \u003cli\u003eKieke, D. \u0026amp; Yashayaev, I. Studies of Labrador Sea Water formation and variability in the subpolar North Atlantic in the light of international partnership and collaboration. \u003cem\u003eProgress in Oceanography\u003c/em\u003e \u003cstrong\u003e132\u003c/strong\u003e, (2014).\u003c/li\u003e\n \u003cli\u003eYashayaev, I. Hydrographic changes in the Labrador Sea, 1960\u0026ndash;2005. \u003cem\u003eProgress in Oceanography\u003c/em\u003e \u003cstrong\u003e73\u003c/strong\u003e, 242\u0026ndash;276 (2007).\u003c/li\u003e\n \u003cli\u003eHauser, T., Demirov, E., Zhu, J. \u0026amp; Yashayaev, I. North Atlantic atmospheric and ocean inter-annual variability over the past fifty years \u0026ndash; Dominant patterns and decadal shifts. \u003cem\u003eProgress in Oceanography\u003c/em\u003e \u003cstrong\u003e132\u003c/strong\u003e, 197\u0026ndash;219 (2015).\u003c/li\u003e\n \u003cli\u003eKalnay, E. \u003cem\u003eet al.\u003c/em\u003e The NCEP/NCAR 40-Year Reanalysis Project. (1996).\u003c/li\u003e\n \u003cli\u003eKanamitsu, M. \u003cem\u003eet al.\u003c/em\u003e NCEP\u0026ndash;DOE AMIP-II Reanalysis (R-2). (2002) doi:10.1175/BAMS-83-11-1631.\u003c/li\u003e\n \u003cli\u003eSchweiger, A. \u003cem\u003eet al.\u003c/em\u003e Uncertainty in modeled Arctic sea ice volume. \u003cem\u003eJournal of Geophysical Research: Oceans\u003c/em\u003e \u003cstrong\u003e116\u003c/strong\u003e, (2011).\u003c/li\u003e\n \u003cli\u003ePawlowicz, R. M_Map: a mapping package for MATLAB, version 1.4m, [Computer software], available online at www.eoas.ubc.ca/~rich/map.html. (2020).\u003cstrong\u003e\u003cu\u003e\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5747822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5747822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Labrador Sea plays a pivotal role in the global climate system as a primary source of newly ventilated intermediate-depth water masses and a major carbon sink of the North Atlantic. Since the 1950s, this region has seen significant shifts in heat and freshwater contents, resulting in arguably the largest full-depth deep-ocean temperature and salinity changes ever recorded. However, the contribution of these changes to sea level variability has yet to be thoroughly quantified and investigated. Using satellite altimetry in conjunction with profiling Argo float and ship-based hydrographic measurements, we show that between 2017 and in 2023 the central Labrador Sea experienced an exceptionally fast sea level rise elevating the level to a record high. Six concurrent factors contributed to these rise and, consequently, extreme height \u0026ndash; reduced winter surface cooling, increased summer surface warming (i.e., oceanic heat uptake), anomalous freshening, drastically shoaled winter convection, reduced deep-water density, and water-column mass gain. We also claim that the effect of salinity changes on sea level switched from counterbalancing (1948\u0026ndash;2015) to reinforcing (2015\u0026ndash;onward) the effect of temperature changes in result of Labrador Sea freshening caused by increased Arctic sea ice melt. This mechanism raises possibility of greater environmental impacts of both recent and imminent heat and freshwater regime shifts than predicted.\u003c/p\u003e","manuscriptTitle":"Concurrent Warming and Freshening Led to a Record-High Sea Level in the Labrador Sea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-28 08:35:10","doi":"10.21203/rs.3.rs-5747822/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"acc05e79-418b-4e21-97a7-7117186099c0","owner":[],"postedDate":"January 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":42879115,"name":"Earth and environmental sciences/Ocean sciences/Physical oceanography"},{"id":42879116,"name":"Earth and environmental sciences/Climate sciences/Ocean sciences/Physical oceanography"}],"tags":[],"updatedAt":"2025-11-29T08:07:11+00:00","versionOfRecord":{"articleIdentity":"rs-5747822","link":"https://doi.org/10.1038/s41467-025-65747-3","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-11-28 05:00:00","publishedOnDateReadable":"November 28th, 2025"},"versionCreatedAt":"2025-01-28 08:35:10","video":"","vorDoi":"10.1038/s41467-025-65747-3","vorDoiUrl":"https://doi.org/10.1038/s41467-025-65747-3","workflowStages":[]},"version":"v1","identity":"rs-5747822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5747822","identity":"rs-5747822","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}