Heresy in ENSO teleconnections: Atmospheric Rivers as disruptors of canonical seasonal precipitation anomalies in the Southwestern US

Heresy in ENSO teleconnections: Atmospheric Rivers as disruptors of canonical seasonal precipitation anomalies in the Southwestern US | 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 Research Article Heresy in ENSO teleconnections: Atmospheric Rivers as disruptors of canonical seasonal precipitation anomalies in the Southwestern US Rosa Luna-Niño, Alexander Gershunov, F. Martin Ralph, Alexander Weyant, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4583843/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Feb, 2025 Read the published version in Climate Dynamics → Version 1 posted 5 You are reading this latest preprint version Abstract In spite of forecasts for anomalous dryness based on the canonical La Niña signal, Water Years 2011, 2017, and 2023 brought copious precipitation to California and the Southwestern United States (SWUS). Although El Niño—Southern Oscillation (ENSO) is the main source of seasonal precipitation predictability for the region, outstanding Atmospheric River (AR) activity produced the unexpected regional wetness in each of these heretical water years (WYs). We define heretical WYs as those that result in precipitation anomalies that oppose those expected based on ENSO alone. We assess the contribution of ARs and other storms to these WYs, finding that heretical La Niña/El Niño WYs were characterized by anomalously robust/deficient AR activity. In California, precipitation accumulation during the heretical La Niña WYs was comparable to or even exceeded that observed during the exceedingly wet WY1998 — the textbook canonical El Niño year. Our findings indicate a weaker/stronger relationship between ENSO and AR/non-AR precipitation, primarily driven by storm frequency. Although ARs can disrupt the ENSO-precipitation signal, ENSO still influences the frequency of AR precipitation in the southwestern U.S. desert, the region influenced by ARs that make landfall in Baja California, Mexico. These results highlight the complexity of ENSO's impact on precipitation in the Western US and underscore the need for a nuanced understanding of ENSO’s influence on ARs to improve seasonal precipitation prediction. ENSO seasonal precipitation Atmospheric Rivers disruptors heresy Southwestern US Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Sea surface temperature (SST) in the tropical Pacific Ocean during fall provides insights into the likelihood of anomalously wet or dry conditions in the Western United States (WUS), notably during winter and early spring (DeFlorio et al. 2013 ). This information is crucial for anticipating water supply for the upcoming warm growing season (e.g. Cayan and Webb 1992 ; Dettinger et al. 1999 ; Cayan et al. 1999 ). El Niño-Southern Oscillation (ENSO) is the main mode of interannual SST variability in the Pacific, and it has been the leading source of seasonal precipitation predictability in the WUS (e.g., Gershunov and Cayan 2003 ). The influence of ENSO on seasonal precipitation varies regionally and temporally; among regions of the WUS, ENSO tends to have its greatest influence on the Southwestern US (SWUS), especially across the southern tier from Southern California to New Mexico (Cayan and Redmond, 1994 ; DeFlorio et al. 2013 , their Fig. 5 c), during January through March (Horel and Wallace 1981 ; Cayan and Redmond 1994 , Gershunov and Cayan 2003 ) when the teleconnection is strongest and the internal variability is weakest (Chapman et al. 2021 ). Historically, canonical seasonal precipitation anomalies have been linked to ENSO phase and magnitude. During El Niño, the Pacific Northwest tends to experience dry conditions while the Southwest tends to be wet. Opposite anomalies are associated with La Niña (e.g. Ropelewski and Halpert, 1989 ; Redmond and Koch, 1991 ; Cayan and Remond, 1994; Dettinger et al. 1999 ). However, some studies have shown that the influence of equatorial Pacific SST forcing on precipitation across WUS is not symmetrical with respect to ENSO phase (e.g. Gershunov 1998 ; Jiménez-Esteve and Domeisen, 2019 ; Chapman et al. 2021 ) as well as with respect to precipitation frequency and intensity (Gershunov, 1998 ). Atmospheric rivers (ARs) are key contributors to the western hydroclimate, particularly along the US West Coast. Climatologically, ARs account for up to 65% of local annual precipitation in northern California and up to 40% in southern California (Gershunov et al. 2017 ). The interannual variability of this contribution ranges between 5% in 1977 and 71% in 1956 in Southern California (SoCal). The wettest storms, which tend to be ARs (Dettinger and Cayan, 2014 ), drive the inordinate hydroclimate variability in California and especially SoCal, compared to other regions in the contiguous US (Dettinger et al. 2011 ); when a few big AR storms occur, the Water Year (WY) ends up being wet, while the relative absence of strong storms typically results in a dry year. The predictability of AR frequency and AR-related precipitation is complicated by the presence of multiple competing drivers that operate on different timescales, such as ENSO, the Pacific Decadal Oscillation (PDO), the Madden-Julian Oscillation (MJO), the Pacific North American pattern (PNA), and the Arctic Oscillation (AO). Kim et al. (2017) suggested that during Central-Pacific El Niño events, the southward shift of the Aleutian Low favors the frequency of ARs over the Northeast Pacific, while during La Niña, AR activity is reduced due to the anticyclonic circulation in the eastern North Pacific. However, no clear and consistent ENSO signal has been shown for anomalous AR activity in California and the western US (Guan and Waliser, 2015 ; Williams et al 2024a ). Williams et al. (2024) found little-to-no ENSO signal in cool-season AR precipitation totals in California’s hydrologically important Sierra Nevada mountains, but did find a positive association between El Niño-like SSTs and non-AR precipitation. Dettinger ( 2004 ) found that near-neutral ENSO years during positive PDO favor the transport of tropical moisture (through Pineapple-express storms — one type of AR) into the west coast of North America. Similarly, Bao et al. ( 2006 ) suggested that a weak subtropical Pacific high during the neutral phase of ENSO favors the direct entrainment of tropical water vapor by ARs in the eastern Pacific. Examining a 70-year record, Gershunov et al. ( 2017 ) found AR landfalling activity along the west coast of North America to be modulated by PDO but not by ENSO. Guirguis et al. ( 2019 ) found that ENSO, along with the PDO, modulates the position and orientation of landfalling ARs in Northern California where El Niño and the positive phase of the PDO favor a southward displaced storm track and more southerly orientated ARs relative to ARs storms during La Niña and the negative PDO phase. Though previous research has found no clear and significant relationship between ENSO and AR frequency at the US West Coast (e.g. Guan and Waliser, 2015 ; Gershunov et al., 2017 ; Guirguis et al., 2019 ), the subtle influence of ENSO and PDO on storm track position and AR orientation contributes to the canonical ENSO precipitation anomalies (Guirguis et al. 2019 ). These results hark back to Gershunov and Barnett ( 1998 ), who showed that ENSO teleconnections to heavy precipitation frequency are similarly sensitive to PDO phase – specifically that ENSO canon seems to originate during constructive phases of the PDO. More recent results of Maher et al. ( 2022 ) support this notion. Nevertheless, subseasonal climate modes are more influential than ENSO in modulating specifically regional AR activity (Castellano et al. 2023; Guan et al. 2013 ; Guirguis et al. 2019 and 2024 ; Guan and Waliser, 2015 ; Wang et al. 2023 ). Clearly, ENSO influence on AR landfalling activity is obscure at present. Turning back to total water-year precipitation, a few recent years have raised questions about the reliability of the teleconnection between tropical Pacific SST and precipitation over the Western US (e.g. Lee et al. 2018 ). The winter of 2010–2011, a moderate-strong La Niña season, was anomalously wet in Southern California and brought near-record snowfall to the Sierra Nevada (Guan et al. 2013 ). During the “Godzilla El Niño” of 2016 (Schiermeier 2015 ), Tropical Pacific SST anomalies were comparable to the major El Niño events of 1983 and 1998, leading to predictions of positive precipitation anomalies over the SWUS. The expected wetness from El Niño 2016 was anticipated to provide relief from a four-year Southwestern drought (2012–2015), but the observed totals were very close to climatology (e.g. Lee et al. 2018 ; Patricola et al. 2020 ), which is unusual given California’s strong interannual precipitation variability. Drought relief finally arrived in WY2017 when an outstanding AR season, unprecedented in at least seven decades (Gershunov et al. 2017 ), impacted California during a weak La Niña event, resulting in one of the two wettest water years on record (WY2017 and WY1983). WY2023, which was a rare third consecutive La Niña year, featured a historic run of nine strong ARs making landfall in California and alleviating La Niña-related drought of the two previous water years (DeFlorio et al. 2024 ). Although the three-week period between late December 2022 and early January 2023 featured the most prominent AR activity, excessive wetness continued through March 2023, resulting in locally record- or near-record cool-season precipitation totals (e.g. Williams et al. 2024b ). These anomalous WYs demonstrate that La Niña (El Niño) does not reliably result in canonically dry (wet) winters in the SWUS, though canonical patterns are typically produced by most seasonal precipitation prediction systems due to their overreliance on ENSO alone (Gibson et al. 2021; DeFlorio et al. 2024 ). Water years that deviated from ENSO canon and brought opposite precipitation anomalies motivated this study to re-examine ENSO's influence on precipitation in the Western US, focusing on California and, especially on SoCal, given the strong canonical ENSO signal seen there. Below, we examine such years — which we term “heretical” ENSO years — and we assess the role of ARs in ENSO heresy, i.e. radical deviation from ENSO canon. 2. Data and Methodology Atmospheric river activity. This study examines atmospheric river activity, focusing on ARs that make landfall along the North American West Coast (20°N-60°N). We used the Scripps Institution of Oceanography (SIO)-R1 catalog (Gershunov et al. 2017 ; https://weclima.ucsd.edu/data-products/ ) spanning 1948 to near-present. The SIO AR catalog uses humidity and wind data at six-hourly intervals from NCEP reanalysis (Kalnay et al. 1996) on a 2.5° grid across pressure levels between 1000 and 300 hPa. The process to identify landfalling ARs involves detecting contiguous areas where the integrated vapor transport (IVT) exceeds 250 kg/m/s and the integrated water vapor (IWV) exceeds 15 mm. To qualify as a landfalling AR, these areas must extend at least 1500 km and maintain their characteristics for a minimum of 18 hours. For each day and gridcell, we check the IVT, IWV, and extension requirements to construct daily binary AR footprints. These footprints are then used to count AR days and classify precipitation as either AR or nonAR related, referred to as ARpr and nonARpr, respectively. Observed precipitation. Daily precipitation observations gridded at 4 km from nClimGrid (Durre et al. 2022 ; https://www.ncei.noaa.gov/products/land-based-station/nclimgrid-daily ), available from 1951 to near-present, are used to assess the relationship between AR precipitation and ENSO. Daily AR precipitation is estimated by interpolating AR footprints (described above) to the nClimGrid grid. Total precipitation of the WY is defined as the accumulated precipitation during the wet season from October to April (ONDJFMA), with the WY label assigned to the year containing January-April (e.g. WY2023 refers to October 2022 – April 2023). Precipitation frequency is defined as the number of days with precipitation higher or equal to exceeding 1 mm. Precipitation intensity is calculated as the accumulated precipitation during a WY or season divided by its frequency. ENSO conditions. To represent ENSO conditions, we used the Oceanic Niño Index (ONI), which is based on SST in the east-central tropical Pacific Ocean, specifically the Niño 3.4 region, from the NOAA Extended Reconstructed SST V5 data ( https://psl.noaa.gov ; Huang et al. 2017 ). Following the approach of NOAA’s Climate Prediction Center, we categorized 3-month seasons as follows: El Niño when ONI \(\ge\) 0.5°C, La Niña ONI \(\le\) -0.5 and Neutral events − 0.5 < ONI < 0.5. We assessed the relationship between seasonal precipitation and ENSO conditions by calculating the Spearman correlation between total WY precipitation and ONI values averaged over the same period, as well as for each of five three-month overlapping seasons (OND, NDJ, DJF, JFM, and FMA; Figures S10 and S11 in Supplementary Material). Since ENSO diversity may not be completely captured by a single index, a sensitivity analysis of these correlations with the chosen ENSO index is presented in the Supplementary Material (Figures S14, S15). We compared the ONI-based results with those using two additional ENSO indices: 1) The Southern Oscillation Index (SOI) based on sea level pressure differences between Tahiti and Darwin, Australia, and 2) the nonlinear ENSO Longitude Index (ELI; Williams et al. 2017), which tracks the longitude of convection over the tropical Pacific that triggers ENSO teleconections. Additionally, we present Pacific SST anomaly patterns for specific WYs and compare them with SST composites during ENSO phases — Las Niñas and Los Niños (Figures S7, S8). Heretical water years. We term WYs “heretical” when precipitation anomalies do not behave as expected with respect to ENSO conditions, i.e. behave in a way opposite to ENSO canon. Heretical WYs were identified based on precipitation anomalies in Southern California (red box in Fig. 1 ), part of the region where ENSO influence has been historically observed, but also a subregion where WY precipitation totals are highly sensitive to AR activity (Dettinger et al. 2011 ). We define two types of heretical WYs: unexpectedly wet and unexpectedly dry. Unexpectedly wet years occur when La Niña is present at the beginning of the WY (although we acknowledge that ENSO state may have intensified or weakened during the course of the WY) and precipitation anomalies for October-April are positive, exceeding 0.75 interannual standard deviation (0.75σ). On the other hand, heretical dry years are defined as El Niño WYs with ONDJFMA negative anomalies <- \(0.75\sigma\) . Heretical WYs defined using a higher (1σ) and lower (0.5σ) threshold are listed in Table S1 . Since heretical behavior is not necessarily persistent throughout the entire WY – precipitation anomalies may transition from wet to dry between seasons, and vice versa – we also present unexpected seasons in Supplementary Material (Figure S5). Canonical ENSO precipitation anomalies. Canonical correlation analysis (CCA, Hotteling 1936) is used to illustrate the ENSO signal in precipitation anomalies and to contrast it with observed precipitation. As an example, we show the signal expected during the strongest teleconnection season: JFM. ENSO canonical signal is displayed as correlations between the temporal evolution of the leading CCA mode and the observed precipitation (Fig. 1 g). CCA identifies pairs of spatial patterns in two fields of variables — SST and precipitation, in this case — whose temporal evolutions are optimally correlated. These are linear relationships that can be used for CCA-based seasonal prediction models (e.g., Barnett and Preisendorfer, 1987 ; Gershunov and Cayan, 2003 ), but are used in the diagnostic mode here. 3. Results a) Precipitation anomalies and AR activity Negative SST anomalies over the tropical Pacific during fall and early winter 2022, indicative of the cold phase of ENSO (La Niña), tilted the odds towards a dry WY2023 in the southwestern US and wet in the northwestern US. However, the observed precipitation anomalies from early (OND) through late winter and spring (FMA) consistently deviated from this expected La Niña pattern, i.e. La Niña canon. While the Northwest and the desert Southwest recorded near-normal precipitation totals, much of the mid-latitude WUS (where historical correlation between precipitation and ENSO is weak ) and Southern California experienced unexpectedly high levels of precipitation (Fig. 1 a-e). Noteworthy regional features included: 1) Central Sierra Nevada recording its second snowiest winter since 1946 (UC Berkeley Central Sierra Snow Lab, https://www.cbsnews.com/sacramento/news/2nd-snowiest-season-history-since-1946-uc-berkeley-central-sierra-snow-lab/ ) , as well as record precipitation in Central California and regions inland from there in a northeasterly swath (Williams et al. 2014b) and 2) precipitation over the southeastern California desert, the only place La Niña canon materialized, was slightly below-normal. Overall, considering the westwide domain, WY2023 precipitation anomalies were opposite to those expected and predicted in a majority of seasonal precipitation prediction systems based on the concurrent La Niña conditions (DeFlorio et al. 2024 , their Fig. 6). Overall, WY2023 provided a glaring example of widespread and rampant La Niña heresy. If anything, the WY2023 precipitation anomaly pattern was strongly in tune with El Niño, rather than La Niña canon. Figures 1 e) and 1g) show the impressive contrast between observed and expected precipitation during late winter JFM; anomalous precipitation in Southern California was strongly positive and the extent of the heresy over the entire domain was such that the spatial correlation between JFM anomalies and La Niña canon (Fig. 1 a,g, respectively) was − 0.52. Identifying other heretical ENSO years in our record, La Niña WYs 1967, 2011 and 2017 were also unexpectedly wet in southern California while El Niño WYs 1964, 1977, 1987, 2007, 2013, and 2015 were unexpectedly dry (Fig. 2 ). WY2016 does not appear as an outstanding heretical year because even though the expected wetness from the “Godzilla El Niño” did not occur, the negative anomalies fell short of the − 0.75 \(\sigma\) SoCal precipitation anomaly threshold chosen to define heretical years. Nevertheless, WY2016 was special — certainly not canonical — and we scrutinize it below alongside the true heretical years. Among those true heretical years, WY2023 was the most anomalous in SoCal (Fig. 2 a); the precipitation was 2 \(\sigma\) above climatology — comparable to the exceedingly wet canonical El Niño WYs 1983 and 1998. We observe that the heretical La Niña WYs in SoCal were marked by outstanding AR activity as gaged by the number of days with landfalling ARs impacting SoCal, whereas the heretical El Niño WYs experienced deficient AR landfalls (Fig. 2 b). Consequently, AR precipitation (ARpr) was greater than precipitation from non-AR events (nonARpr) during heretical La Niña WYs, while ARpr was scarce during most heretical El Niño WYs (Fig. 2 a). The anomalous AR activity during the heretical WYs contributed inordinately to total WY precipitation not only in SoCal, but also in most of the Western US. During the heretical La Niña WYs, ARs contributed more than 60% of the total precipitation in SoCal (Figure S1 a, S2a), far exceeding their climatological average contribution of ~ 40% (Figure S2, S3). Remarkably, during the weak La Niña of WY2017, ARs accounted for over 60% of the precipitation received across nearly all of California. In contrast, the lack of ARs in the heretical El Niño years (Figure S1 b, S2b) caused the AR precipitation contribution to fall to as low as 10% during the weak El Niño event of WY2007 (Figure S1 , S2, and S3). Notably, three out of the five lowest-ranking seasons, with respect to AR landfall days, occurred during heretical El Niño years (WYs 1964, 1977, 1987; Fig. 2 b). Also the record high frequency of AR days was set during the weak La Niña WY2017 — one of the wettest years on record for California as a whole (Figure S4). These results highlight the outsized influence of ARs on SoCal precipitation variability, accounting for most of the interannual precipitation variability in this region: ARpr (nonARpr) and WY precipitation correlation is approximately 0.9 (0.7). Clearly, ARpr is not completely independent of nonARpr, often being associated with the same midlatitude cyclones (e.g. Zhang et al. 2019 ). ARpr and nonARpr are correlated at 0.4 across WYs over SoCal (purple and blue time series in Fig. 2 a). Considering all of California (Figure S4), other heretical La Niña years with outstanding AR activity are identified (1956 and 1974 with 15 and 28 anomalous landfalling AR days, respectively; Figure S5), but WY2017 holds the record for the most active AR year (81 landfalling AR days compared to 37 days on average; 44 days above normal, Figure S5b) and for excessive precipitation (only slightly surpassed by WY1983). Weak La Niña WY2017 was the wettest heretical year on record for California. This aligns with the findings of Dettinger ( 2004 ) and Bao (2006) that near-neutral ENSO years favor tropical water vapor transport by ARs in the eastern Pacific, and findings by Gershunov et al ( 2017 ) that positive PDO tends to favor landfalling ARs and positive precipitation anomalies in California. It is noteworthy that heretical precipitation anomalies developed differently across the WYs. For instance, La Niña 2011 brought anomalous wetness in OND and DJF, while in 2017 and 2023, anomalous wetness persisted across the entire wet season (Figure S5). The heretical La Niña and El Niño precipitation anomalies vary latitudinally, especially when they are compared with canonical WYs (Fig. 3 ). In SoCal, precipitation totals in heretical Las Niña WYs were similar to each other and comparable to those of canonical El Niño WYs 1998 and 1983. In Northern California, the wettest heretical year was the weak La Niña 2017, with total precipitation and frequency (number of rainy days) comparable to El Niño WY1998, surpassed only by El Niño WY1983. The latitudinal profile of El Niño WY2016 shows that precipitation was very close to climatology in SoCal, but in Central and Northern California, WY2016 did produce positive precipitation anomalies, though still well short of the canonical Los Niños 1983, 1998, or the heretical Las Niñas 2011, 2017, and 2023. It is informative to observe the wide range of total precipitation and frequency during canonical versus heretical years under the same ENSO active phase, for instance, the two strong Las Niñas 1989 (dry) and 2011 (wet) or the two very strong Los Niños 1983 (wet) and 2016 (close to normal). Also interesting are the similarities between the canonical and heretical years under opposite ENSO phases, such as, the canonical moderate La Niña 2012 (dry) and the heretical moderate El Niño 1987 (dry), and vice versa e.g. WYs 1983 and 2007. Looking beyond the ENSO region, we have explored the possible influence of Pacific SST anomalies on heretical WYs (see Supplementary Materials: Figures S6 and S7 and associated text). Since tropical SST anomalies differed greatly between heretical WYs, SST does not directly explain the heresy and instead reinforces the notion that each heretical year was unique in its own way. b) Implications for seasonal prediction Up to this point, we showed that ARs were key wildcards in producing the unexpected precipitation anomalies during heretical WYs. Therefore, a natural question is: What exactly are we predicting when we predict canonical precipitation anomalies during ENSO-active years? To address this question, we reexamined the relationship between ENSO and seasonal precipitation — separating precipitation into non-AR and AR components. In concordance with previous studies (e.g., Dettinger et al. 2011 ; DeFlorio et al. 2013 ), we found that the correlation between ENSO and total seasonal precipitation is positive and significant mostly in the southwestern US (Fig. 4 a). This correlation strengthens toward late winter (JFM) and even early spring (FMA) (Figure S10), consistent with previous results (e.g. Gershunov and Cayan 2003 , Chapman et al. 2021 ). Warm SST anomalies along the Pacific Coast, typically occurring during El Niño events (Figure S7a), may explain the strong correlation during FMA. At a glance, the correlation of ENSO with non-AR precipitation looks very similar to that with total precipitation (Figs. 4 and S10c). On the other hand, the overall correlation patterns for AR precipitation are weaker, with the highest correlations obtained over southern Arizona, and New Mexico (Sonoran) desert (Figs. 4 b and S10b). Besides precipitation from the ARs hitting the California Coast, precipitation in these regions is highly dependent on the landfalling ARs in Baja California that penetrate the interior Southwest (Rutz and Steenburg 2012; Guirguis et al. 2023a ).Opposite landfalling AR-associated IVT anomalies during La Niña (Fig. 8a) and El Niño years (Fig. 9a) in Baja California and Sonora suggest that ENSO influence on AR precipitation over the southwestern desert is related to ARs that make landfall in Mexico, especially during the late winter and early spring. Given that the frequency of AR precipitation could be lower than that of non-AR precipitation, part of the difference in the correlations could be impacted by sample size: the smaller samples of ARs compared to that of other storms would lead to larger interannual (sampling) variability of ARpr vs nonARpr (see Table S2 for an example in SoCal). To ensure that the stronger correlation with nonARpr is not only due to a sample size issue, we estimated the total precipitation selecting the n -heaviest nonARpr days, where n is the frequency of ARpr. Using the same interannually varying sample size, the influence of ENSO on non-AR and AR precipitation becomes more alike (Fig. 4 b,d), suggesting that ENSO influence on AR precipitation might be partially hidden due to the smaller sample size of ARpr days compared to that of non-ARpr days. The reduced region of significant correlation associated with a reduced sample size indicates a robust linear relationship mainly over the low Southwestern (Sonoran) desert (Fig. 4 d). The ENSO signal in both non-AR and AR precipitation comes mostly from precipitation frequency (Figs. 5 a,c S11, and S12) since the correlation with intensity lacks significance in most of the Western US, except over a small region in coastal northern California (Fig. 5 b,d). The frequencies of ARpr and non-ARpr correlate over the Sonoran desert and most of California (Fig. 5 e), indicating a relationship between daily AR and non-AR precipitation events. However, their intensities are not correlated in most of the Western US (Fig. 5 f). ENSO influences the frequency of both ARpr and nonARpr precisely in the region where ARpr and nonARpr frequencies are significantly correlated. Composites of AR and nonARpr show that El Niño and La Niña contribute similarly to the ENSO signal found over the southwestern desert for precipitation totals and frequency (Figure S12). During El Niño winters, landfalling ARs have a stronger southerly component over the West Coast and a more westerly component over the Baja California peninsula, enhancing the humidity source and resulting in a positive anomaly in vertically integrated water vapor (IWV) and slightly more landfalling AR days in parts of Baja California. On the contrary, during La Niña winters, the northeasterly and easterly components of AR IVT are stronger over the US West Coast and Baja California, respectively. This leads to lower IWV compared to climatology and El Niño winters, a lower frequency of landfalling AR days in Baja California, and fewer AR precipitation days in the southwestern desert (Figure S13). 4. Conclusions and Discussion WY2023 is a clear example of a heretical wet La Niña WY in California when most seasonal forecasts tilted the odds towards canonically dry La Niña anomalies, especially over Southern California and the desert Southwest (DeFlorio et al. 2024 , Fig. 6). We showed that strong AR activity was instrumental for the unanticipated well-above-normal precipitation in the Southwestern US during La Niña 2023 as well as for other heretical La Niña WYs on record: 1967, 2011, and 2017. Meanwhile, anomalously weak AR activity played the decisive role in heretically dry El Niño WYs (1964, 1977, 1987, 2007, 2013, and 2015), and the close-to-average “Godzilla El Niño” WY2016. The outsized influence of ARs on California’s hydroclimate (e.g. Dettinger et al. 2011 , Gershunov et al. 2019 ), and specifically in ENSO heresy as described here, lead us to speculate about alternative precipitation anomalies that did not materialize but were possible in the Western US during famously wet Los Niños of 1983 and 1998 under different AR frequencies from those that actually happened to occur. What would the precipitation anomalies for Los Niños 1983 and 1998 have been given fewer ARs? Would our interpretation of the canonical El Niño precipitation anomalies have been different? On the contrary, would the possible wetness from a few additional ARs (which have not occurred) have been attributed to ENSO during the most recent “Godzilla El Niño” 2016? As few as two or three additional moderate or intense ARs making landfall in SoCal would have produced the expected wetness, which would have been interpreted according to El Niño canon. The results from this study emphasize the critical role of AR activity in shaping ENSO-related precipitation anomalies in the Southwestern US. The anomalous bounty or paucity of ARs, their intensity and orientation (Guirguis et al. 2019 ), can either amplify the expected anomalies based on ENSO conditions or negate them, disrupting seasonal predictions made according to historical correlation with ENSO to the extent of generating entirely unexpected — heretical — precipitation anomalies. Meanwhile, AR activity is modulated by many influences from synoptic and subseasonal (MJO, PNA, AO; e.g. Guan and Waliser, 2015 ; Wang et al. 2023 ) to interannual and decadal (PDO, ENSO; e.g. Gershunov et al. 2017 ; Guirguis et al. 2019 ) as well as high frequency internal atmospheric variability (e.g. Jiang et al. 2022 ). This complex interplay of influences makes predicting AR landfalls and associated precipitation extremely challenging at seasonal scale. We therefore consider ARs as wild cards and potential disruptors of seasonal prediction in California and Western US. The results of this study suggest that the canonical ENSO pattern in western US precipitation is mainly determined via teleconnections to non-AR precipitation frequency. Williams et al. ( 2024a ) also found a stronger relationship between ENSO and non-AR vs AR precipitation over the Sierra Nevada, the largest source of above-ground water resources for California. Meanwhile, AR precipitation frequency contributes to the ENSO signal mainly in the northern Sonoran desert stretching from the interior of SoCal across southern Arizona and into southern New Mexico. The Desert Southwest may be the one region of the Western US where AR landfalling activity produces a precipitation signal that is somewhat reliably synchronized with contemporaneous ENSO activity, especially during late winter (JFM) and early spring (FMA). This needs further investigation, focusing on the landfalling ARs in Baja California and their inland penetration into the southwestern desert. However, this region experiences fewer AR days and less AR precipitation compared to the coastal region (Figures S1 a, S2a) The idea that atmospheric rivers are the wild cards of seasonal precipitation prediction remains particularly relevant for coastal California. Relying solely on ENSO signals for seasonal precipitation prediction, therefore, does not give adequate recognition of the relevance of ARs in the hydroclimate of most of the Western US. Although we have discussed the influence of ENSO on ARpr and nonARpr separately, it is important to keep in mind that ARpr and nonARpr precipitation events are not mutually exclusive. As Zhang et al. ( 2019 ) found, 82% of the ARs impacting the West Coast are associated with extratropical cyclones, where pre-frontal widespread precipitation (ARpr) and post-frontal convective precipitation (nonARpr) are organized by the same synoptic storm. AR intensity, however, is only moderately proportional to the storm strength, i.e. the depth of the low pressure organizing the cyclonic circulation. The stronger correlation between the frequencies of ARpr and nonARpr compared to that between their intensities is, therefore, consistent with Zhang et al. ( 2019 ). Notably, ENSO influences the frequency of both ARpr and nonARpr precisely in the region where ARpr and nonARpr frequencies are significantly correlated. Whether ENSO influences the likelihood of a midlatitude cyclone to be associated with an AR and vice versa is yet to be determined. Overreliance on ENSO canon for seasonal prediction has resulted in inaccurate forecasts that exacerbated the challenges facing California’s water resource managers (DeFlorio et al. 2021 ; Jiang et al. 2022 ). Moreover, seasonal predictability skill could worsen under evolving climate change since model projections suggest a gradually enhanced contribution of AR precipitation to the annual total, boosting the year-to-year variability of the western hydroclimate (Gershunov et al. 2019 ). In a warming future, predicting WY precipitation will become even more important, yet apparently more challenging given that WY precipitation totals are projected to become increasingly dominated by ARs and delivered in increasingly intense storms. The observational and model-based results of Williams et al. ( 2024b ), however, suggest that such changes are not expected to clearly emerge from the envelope of natural variability until the second half of this century, indicating there is likely some time to resolve this seasonal prediction challenge before it becomes even more acute. It will be important to examine in future work whether the heresy of recent Las Niñas (WYs 2011, 2017, and 2023) had anything to do with anthropogenic causes – particularly polar-amplified global warming – already marking a new period when precipitation is becoming less predictable in the West. In other words, it should be determined if unexpected precipitation anomalies are becoming more likely to occur in the changing climate, i.e. if global warming promotes ENSO heresy. Such future studies should continue to investigate the potential of ARs to strongly influence the overall seasonal precipitation outcomes over the western US. For the time being, exploring new variables related to AR activity (e.g. Integrated Vapor Transport as in Lavers et al. 2016 and Wang et al. 2021 ) might provide added skill for AR precipitation prediction. Seasonal prediction progress along those lines is not guaranteed, however, since seasonal predictor variables must offer climate memory in order to provide seasonal prediction skill at least one month ahead. Another potentially promising approach is the development of a new S2S prediction framework (e.g. DeFlorio et al. 2021 ; White et al. 2022), which would address the challenge of merging the seasonal signal from SST conditions (mainly ENSO-based precipitation prediction) with subseasonal information such as synoptic weather regimes related to AR landfalls and AR IVT and precipitation (e.g. DeFlorio et al. 2019 , Zhang et al. 2023 , Guirguis et al. 2023b ). Such an integrated approach to S2S prediction could improve the accuracy of both seasonal and subseasonal predictions by addressing both timescales in one integrated S2S prediction system. Of course, it is also essential to keep evolving water management strategies that enhance society’s flexibility and capability to adapt to the inherent uncertainty in seasonal predictions. Declarations Acknowledgments This work was supported by the California Department of Water Resources and Department of the Interior via the Southwest Climate Adaptation Science Center. Funding CW3E personnel were supported by the California Department of Water Resources Atmospheric River Program Phase III (Grant 4600014294). Data availability Data sharing is not applicable to this article as no datasets were generated. Data used in this study are available from publicly accessible data archives. Author Contributions All authors contributed to the study conception and design. Rosa Luna-Niño processed data and produced figures. Rosa Luna-Niño and Alexander Gershunov wrote the manuscript and all authors provided valuable comments and suggestions. All authors reviewed and approved the final manuscript. Conflict of interest The authors have no conflict of interest to declare. References Barnett, T. P., and Preisendorfer, R. 1987. 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Journal of Geophysical Research: Atmospheres , 128(7), e2022JD037608. Supplementary Files SupplementaryMaterialsLunaNinoetal2024.docx Cite Share Download PDF Status: Published Journal Publication published 07 Feb, 2025 Read the published version in Climate Dynamics → Version 1 posted Editorial decision: Minor Revision 04 Dec, 2024 Reviewers agreed at journal 05 Sep, 2024 Reviewers invited by journal 21 Jun, 2024 Editor assigned by journal 15 Jun, 2024 First submitted to journal 14 Jun, 2024 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. 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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-4583843","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":317503570,"identity":"e5738975-6d8e-4139-b2af-8c07e43e16f8","order_by":0,"name":"Rosa Luna-Niño","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACdjApAWQ0AGk2ID5ASAszTAvPAdK0gHQlEKnFvJnH7MHPHRZ5/JJvDD/+KGOQ47uRgF+LzGEec8PeMxLFkrNzjKV5zjEYSxLSIsHMYybB2yaRuOF2jhkzYxtD4gZitEj+BWm5ecaM8WcbQz1RWqTBttzgMWPgbWNIMCCsha1MWhaoZWZPWjHQLxKGM888IKCFvXmb5Nu2usR+9sMbgSFmI893nIAtGEaQpnwUjIJRMApGAXYAABwKOsoy6kzfAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-3679-6410","institution":"University of California San Diego Scripps Institution of Oceanography","correspondingAuthor":true,"prefix":"","firstName":"Rosa","middleName":"","lastName":"Luna-Niño","suffix":""},{"id":317503571,"identity":"7c6ca495-6a36-449b-ade1-d67b03898d8c","order_by":1,"name":"Alexander Gershunov","email":"","orcid":"","institution":"University of California San Diego Scripps Institution of Oceanography","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Gershunov","suffix":""},{"id":317503572,"identity":"261b6f58-6cfe-41a4-baef-587e7bbc9fb8","order_by":2,"name":"F. Martin Ralph","email":"","orcid":"","institution":"University of California San Diego Scripps Institution of Oceanography","correspondingAuthor":false,"prefix":"","firstName":"F.","middleName":"Martin","lastName":"Ralph","suffix":""},{"id":317503573,"identity":"d3d0fc92-0f71-4609-9866-8a0d5a12349f","order_by":3,"name":"Alexander Weyant","email":"","orcid":"","institution":"University of California San Diego Scripps Institution of Oceanography","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Weyant","suffix":""},{"id":317503574,"identity":"b146de74-74cc-494f-ba5c-8ab0d793bb87","order_by":4,"name":"Kristen Guirguis","email":"","orcid":"","institution":"University of California San Diego Scripps Institution of Oceanography","correspondingAuthor":false,"prefix":"","firstName":"Kristen","middleName":"","lastName":"Guirguis","suffix":""},{"id":317503575,"identity":"d6f5351a-818a-474d-87a7-3e3885ae485e","order_by":5,"name":"Michael J. DeFlorio","email":"","orcid":"","institution":"University of California San Diego Scripps Institution of Oceanography","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"J.","lastName":"DeFlorio","suffix":""},{"id":317503576,"identity":"cd7b622d-f954-4124-bd91-b86b208e5a3e","order_by":6,"name":"Daniel R. Cayan","email":"","orcid":"","institution":"University of California San Diego Scripps Institution of Oceanography","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"R.","lastName":"Cayan","suffix":""},{"id":317503577,"identity":"80f8e8ce-bdc1-4c7f-8ccb-cfaf1302949e","order_by":7,"name":"A. Park Williams","email":"","orcid":"","institution":"University of California Los Angeles Department of Geography","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"Park","lastName":"Williams","suffix":""}],"badges":[],"createdAt":"2024-06-14 19:34:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4583843/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4583843/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00382-025-07583-1","type":"published","date":"2025-02-07T15:58:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60286772,"identity":"eff9981a-30e1-4c9d-8398-afe8d1f51c00","added_by":"auto","created_at":"2024-07-15 07:58:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":716801,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea-e) Observed seasonal precipitation anomalies (%) during WY2023 based on the period 1948-2022. f) Canonical precipitation anomalies for JFM during La Niña. The red box indicates the Southern California region.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4583843/v1/7a9ca5f88bd1c64d8f0c1f70.jpg"},{"id":60286771,"identity":"35400313-1ad0-42ae-b340-6443672d694e","added_by":"auto","created_at":"2024-07-15 07:58:54","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":431116,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea) Total precipitation (October-April; mm) and b) Number of days of landfalling ARs in Southern California (red box in Figure 1). Solid horizontal lines in a) and b) indicate mean annual precipitation and average landfalling AR days, respectively; dashed lines in a) show thresholds based on the standard deviation (σ). Circles in b) show the October SST anomalies in the Niño3.4 region as indicator of ENSO conditions at the beginning of the WY. Green and brown colors highlight unexpected wet and dry water years, respectively, based on ENSO: unexpectedly wet for La Niña and unexpectedly dry for El Niño.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4583843/v1/9ef5627d43b647b4f084415b.jpg"},{"id":60286777,"identity":"138666a3-04bd-449c-8e84-8fad22dd1600","added_by":"auto","created_at":"2024-07-15 07:58:55","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":968988,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLatitudinal profiles of total precipitation (October-April; mm) and frequency in California highlighting heretical versus canonical a) La Niña and b) El Niño water years.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4583843/v1/ac787490d83cef40bec25303.jpg"},{"id":60287271,"identity":"ad293179-1b2b-4c26-a9bb-f55f460be559","added_by":"auto","created_at":"2024-07-15 08:06:55","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":326074,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpearman correlation between ONI index and seasonal a) total precipitation, b) AR precipitation, and c) nonAR precipitation during the WYs 1952-2023 (ONDJFMA). d) shows the correlation for non-AR precipitation using the same sample size as AR precipitation (total nonARpr using the n-heaviest days, where n is the frequency of AR precipitation). Shaded colors indicate significant correlations at 95% confidence level. Black contour limits areas of positive and negative correlation. The robustness of the correlation between ENSO and AR and nonAR precipitation was validated with additional ENSO indices to account for ENSO diversity: SOI and ELI (Figure S14).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4583843/v1/af8cbc7fb6ae6849a8939ffc.jpg"},{"id":60286773,"identity":"f0b9fe08-5f82-40d5-b773-fb6950b65e09","added_by":"auto","created_at":"2024-07-15 07:58:55","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":536682,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpearman correlation between ONI index and a) nonAR precipitation frequency, b) nonAR precipitation intensity, c) AR precipitation frequency and d) AR precipitation intensity during the WYs 1952-2023 (ONDJFMA). Spearman correlation between nonAR and AR precipitation e) frequency and f) intensity. Shaded colors indicate significant correlations at 95% confidence level. Black contour limits areas of positive and negative correlation. The robustness of the correlation between ENSO and AR and nonAR precipitation was validated with additional ENSO indices to account for ENSO diversity: SOI and ELI (Figure S15).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4583843/v1/20608fadb63601e94805b6ac.jpg"},{"id":75931303,"identity":"3cc3950c-9d73-4678-8ab2-03438d3cde33","added_by":"auto","created_at":"2025-02-10 16:14:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4400947,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4583843/v1/c20c4eb0-86e2-4e8f-83e7-20ed5a95ad17.pdf"},{"id":60286776,"identity":"d1907da8-9f6d-4359-a36e-6beaa42019b6","added_by":"auto","created_at":"2024-07-15 07:58:55","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":8004845,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialsLunaNinoetal2024.docx","url":"https://assets-eu.researchsquare.com/files/rs-4583843/v1/8a65edf172026570c1ff3e14.docx"}],"financialInterests":"","formattedTitle":"Heresy in ENSO teleconnections: Atmospheric Rivers as disruptors of canonical seasonal precipitation anomalies in the Southwestern US","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSea surface temperature (SST) in the tropical Pacific Ocean during fall provides insights into the likelihood of anomalously wet or dry conditions in the Western United States (WUS), notably during winter and early spring (DeFlorio et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This information is crucial for anticipating water supply for the upcoming warm growing season (e.g. Cayan and Webb \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Dettinger et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Cayan et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). El Ni\u0026ntilde;o-Southern Oscillation (ENSO) is the main mode of interannual SST variability in the Pacific, and it has been the leading source of seasonal precipitation predictability in the WUS (e.g., Gershunov and Cayan \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The influence of ENSO on seasonal precipitation varies regionally and temporally; among regions of the WUS, ENSO tends to have its greatest influence on the Southwestern US (SWUS), especially across the southern tier from Southern California to New Mexico (Cayan and Redmond, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; DeFlorio et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, their Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec), during January through March (Horel and Wallace \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Cayan and Redmond \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1994\u003c/span\u003e, Gershunov and Cayan \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) when the teleconnection is strongest and the internal variability is weakest (Chapman et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Historically, canonical seasonal precipitation anomalies have been linked to ENSO phase and magnitude. During El Ni\u0026ntilde;o, the Pacific Northwest tends to experience dry conditions while the Southwest tends to be wet. Opposite anomalies are associated with La Ni\u0026ntilde;a (e.g. Ropelewski and Halpert, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Redmond and Koch, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Cayan and Remond, 1994; Dettinger et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). However, some studies have shown that the influence of equatorial Pacific SST forcing on precipitation across WUS is not symmetrical with respect to ENSO phase (e.g. Gershunov \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Jim\u0026eacute;nez-Esteve and Domeisen, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Chapman et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) as well as with respect to precipitation frequency and intensity (Gershunov, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAtmospheric rivers (ARs) are key contributors to the western hydroclimate, particularly along the US West Coast. Climatologically, ARs account for up to 65% of local annual precipitation in northern California and up to 40% in southern California (Gershunov et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The interannual variability of this contribution ranges between 5% in 1977 and 71% in 1956 in Southern California (SoCal). The wettest storms, which tend to be ARs (Dettinger and Cayan, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), drive the inordinate hydroclimate variability in California and especially SoCal, compared to other regions in the contiguous US (Dettinger et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); when a few big AR storms occur, the Water Year (WY) ends up being wet, while the relative absence of strong storms typically results in a dry year.\u003c/p\u003e \u003cp\u003eThe predictability of AR frequency and AR-related precipitation is complicated by the presence of multiple competing drivers that operate on different timescales, such as ENSO, the Pacific Decadal Oscillation (PDO), the Madden-Julian Oscillation (MJO), the Pacific North American pattern (PNA), and the Arctic Oscillation (AO). Kim et al. (2017) suggested that during Central-Pacific El Ni\u0026ntilde;o events, the southward shift of the Aleutian Low favors the frequency of ARs over the Northeast Pacific, while during La Ni\u0026ntilde;a, AR activity is reduced due to the anticyclonic circulation in the eastern North Pacific. However, no clear and consistent ENSO signal has been shown for anomalous AR activity in California and the western US (Guan and Waliser, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Williams et al \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e). Williams et al. (2024) found little-to-no ENSO signal in cool-season AR precipitation totals in California\u0026rsquo;s hydrologically important Sierra Nevada mountains, but did find a positive association between El Ni\u0026ntilde;o-like SSTs and non-AR precipitation. Dettinger (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) found that near-neutral ENSO years during positive PDO favor the transport of tropical moisture (through Pineapple-express storms \u0026mdash; one type of AR) into the west coast of North America. Similarly, Bao et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) suggested that a weak subtropical Pacific high during the neutral phase of ENSO favors the direct entrainment of tropical water vapor by ARs in the eastern Pacific. Examining a 70-year record, Gershunov et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found AR landfalling activity along the west coast of North America to be modulated by PDO but not by ENSO. Guirguis et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found that ENSO, along with the PDO, modulates the position and orientation of landfalling ARs in Northern California where El Ni\u0026ntilde;o and the positive phase of the PDO favor a southward displaced storm track and more southerly orientated ARs relative to ARs storms during La Ni\u0026ntilde;a and the negative PDO phase. Though previous research has found no clear and significant relationship between ENSO and AR frequency at the US West Coast (e.g. Guan and Waliser, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Gershunov et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Guirguis et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the subtle influence of ENSO and PDO on storm track position and AR orientation contributes to the canonical ENSO precipitation anomalies (Guirguis et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These results hark back to Gershunov and Barnett (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), who showed that ENSO teleconnections to heavy precipitation frequency are similarly sensitive to PDO phase \u0026ndash; specifically that ENSO canon seems to originate during constructive phases of the PDO. More recent results of Maher et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) support this notion. Nevertheless, subseasonal climate modes are more influential than ENSO in modulating specifically regional AR activity (Castellano et al. 2023; Guan et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Guirguis et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e and \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Guan and Waliser, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Clearly, ENSO influence on AR landfalling activity is obscure at present.\u003c/p\u003e \u003cp\u003eTurning back to total water-year precipitation, a few recent years have raised questions about the reliability of the teleconnection between tropical Pacific SST and precipitation over the Western US (e.g. Lee et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The winter of 2010\u0026ndash;2011, a moderate-strong La Ni\u0026ntilde;a season, was anomalously wet in Southern California and brought near-record snowfall to the Sierra Nevada (Guan et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). During the \u0026ldquo;Godzilla El Ni\u0026ntilde;o\u0026rdquo; of 2016 (Schiermeier \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Tropical Pacific SST anomalies were comparable to the major El Ni\u0026ntilde;o events of 1983 and 1998, leading to predictions of positive precipitation anomalies over the SWUS. The expected wetness from El Ni\u0026ntilde;o 2016 was anticipated to provide relief from a four-year Southwestern drought (2012\u0026ndash;2015), but the observed totals were very close to climatology (e.g. Lee et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Patricola et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which is unusual given California\u0026rsquo;s strong interannual precipitation variability. Drought relief finally arrived in WY2017 when an outstanding AR season, unprecedented in at least seven decades (Gershunov et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), impacted California during a weak La Ni\u0026ntilde;a event, resulting in one of the two wettest water years on record (WY2017 and WY1983). WY2023, which was a rare third consecutive La Ni\u0026ntilde;a year, featured a historic run of nine strong ARs making landfall in California and alleviating La Ni\u0026ntilde;a-related drought of the two previous water years (DeFlorio et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Although the three-week period between late December 2022 and early January 2023 featured the most prominent AR activity, excessive wetness continued through March 2023, resulting in locally record- or near-record cool-season precipitation totals (e.g. Williams et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e). These anomalous WYs demonstrate that La Ni\u0026ntilde;a (El Ni\u0026ntilde;o) does not reliably result in canonically dry (wet) winters in the SWUS, though canonical patterns are typically produced by most seasonal precipitation prediction systems due to their overreliance on ENSO alone (Gibson et al. 2021; DeFlorio et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Water years that deviated from ENSO canon and brought opposite precipitation anomalies motivated this study to re-examine ENSO's influence on precipitation in the Western US, focusing on California and, especially on SoCal, given the strong canonical ENSO signal seen there. Below, we examine such years \u0026mdash; which we term \u0026ldquo;heretical\u0026rdquo; ENSO years \u0026mdash; and we assess the role of ARs in ENSO heresy, i.e. radical deviation from ENSO canon.\u003c/p\u003e"},{"header":"2. Data and Methodology","content":"\u003cp\u003e \u003cb\u003eAtmospheric river activity.\u003c/b\u003e This study examines atmospheric river activity, focusing on ARs that make landfall along the North American West Coast (20\u0026deg;N-60\u0026deg;N). We used the Scripps Institution of Oceanography (SIO)-R1 catalog (Gershunov et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://weclima.ucsd.edu/data-products/\u003c/span\u003e\u003cspan address=\"https://weclima.ucsd.edu/data-products/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) spanning 1948 to near-present. The SIO AR catalog uses humidity and wind data at six-hourly intervals from NCEP reanalysis (Kalnay et al. 1996) on a 2.5\u0026deg; grid across pressure levels between 1000 and 300 hPa. The process to identify landfalling ARs involves detecting contiguous areas where the integrated vapor transport (IVT) exceeds 250 kg/m/s and the integrated water vapor (IWV) exceeds 15 mm. To qualify as a landfalling AR, these areas must extend at least 1500 km and maintain their characteristics for a minimum of 18 hours. For each day and gridcell, we check the IVT, IWV, and extension requirements to construct daily binary AR footprints. These footprints are then used to count AR days and classify precipitation as either AR or nonAR related, referred to as ARpr and nonARpr, respectively.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObserved precipitation.\u003c/b\u003e Daily precipitation observations gridded at 4 km from nClimGrid (Durre et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncei.noaa.gov/products/land-based-station/nclimgrid-daily\u003c/span\u003e\u003cspan address=\"https://www.ncei.noaa.gov/products/land-based-station/nclimgrid-daily\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), available from 1951 to near-present, are used to assess the relationship between AR precipitation and ENSO. Daily AR precipitation is estimated by interpolating AR footprints (described above) to the nClimGrid grid. Total precipitation of the WY is defined as the accumulated precipitation during the wet season from October to April (ONDJFMA), with the WY label assigned to the year containing January-April (e.g. WY2023 refers to October 2022 \u0026ndash; April 2023). Precipitation frequency is defined as the number of days with precipitation higher or equal to exceeding 1 mm. Precipitation intensity is calculated as the accumulated precipitation during a WY or season divided by its frequency.\u003c/p\u003e \u003cp\u003e \u003cb\u003eENSO conditions.\u003c/b\u003e To represent ENSO conditions, we used the Oceanic Ni\u0026ntilde;o Index (ONI), which is based on SST in the east-central tropical Pacific Ocean, specifically the Ni\u0026ntilde;o 3.4 region, from the NOAA Extended Reconstructed SST V5 data (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://psl.noaa.gov\u003c/span\u003e\u003cspan address=\"https://psl.noaa.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; Huang et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Following the approach of NOAA\u0026rsquo;s Climate Prediction Center, we categorized 3-month seasons as follows: El Ni\u0026ntilde;o when ONI \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\ge\\)\u003c/span\u003e\u003c/span\u003e 0.5\u0026deg;C, La Ni\u0026ntilde;a ONI \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le\\)\u003c/span\u003e\u003c/span\u003e -0.5 and Neutral events \u0026minus;\u0026thinsp;0.5 \u0026lt; ONI \u0026lt; 0.5. We assessed the relationship between seasonal precipitation and ENSO conditions by calculating the Spearman correlation between total WY precipitation and ONI values averaged over the same period, as well as for each of five three-month overlapping seasons (OND, NDJ, DJF, JFM, and FMA; Figures S10 and S11 in Supplementary Material). Since ENSO diversity may not be completely captured by a single index, a sensitivity analysis of these correlations with the chosen ENSO index is presented in the Supplementary Material (Figures S14, S15). We compared the ONI-based results with those using two additional ENSO indices: 1) The Southern Oscillation Index (SOI) based on sea level pressure differences between Tahiti and Darwin, Australia, and 2) the nonlinear ENSO Longitude Index (ELI; Williams et al. 2017), which tracks the longitude of convection over the tropical Pacific that triggers ENSO teleconections. Additionally, we present Pacific SST anomaly patterns for specific WYs and compare them with SST composites during ENSO phases \u0026mdash; Las Ni\u0026ntilde;as and Los Ni\u0026ntilde;os (Figures S7, S8).\u003c/p\u003e \u003cp\u003e \u003cb\u003eHeretical water years.\u003c/b\u003e We term WYs \u0026ldquo;heretical\u0026rdquo; when precipitation anomalies do not behave as expected with respect to ENSO conditions, i.e. behave in a way opposite to ENSO canon. Heretical WYs were identified based on precipitation anomalies in Southern California (red box in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), part of the region where ENSO influence has been historically observed, but also a subregion where WY precipitation totals are highly sensitive to AR activity (Dettinger et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). We define two types of heretical WYs: unexpectedly wet and unexpectedly dry. Unexpectedly wet years occur when La Ni\u0026ntilde;a is present at the beginning of the WY (although we acknowledge that ENSO state may have intensified or weakened during the course of the WY) and precipitation anomalies for October-April are positive, exceeding 0.75 interannual standard deviation (0.75σ). On the other hand, heretical dry years are defined as El Ni\u0026ntilde;o WYs with ONDJFMA negative anomalies \u0026lt;-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(0.75\\sigma\\)\u003c/span\u003e\u003c/span\u003e. Heretical WYs defined using a higher (1σ) and lower (0.5σ) threshold are listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eSince heretical behavior is not necessarily persistent throughout the entire WY \u0026ndash; precipitation anomalies may transition from wet to dry between seasons, and vice versa \u0026ndash; we also present unexpected seasons in Supplementary Material (Figure S5).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCanonical ENSO precipitation anomalies.\u003c/b\u003e Canonical correlation analysis (CCA, Hotteling 1936) is used to illustrate the ENSO signal in precipitation anomalies and to contrast it with observed precipitation. As an example, we show the signal expected during the strongest teleconnection season: JFM. ENSO canonical signal is displayed as correlations between the temporal evolution of the leading CCA mode and the observed precipitation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg).\u003c/p\u003e \u003cp\u003eCCA identifies pairs of spatial patterns in two fields of variables \u0026mdash; SST and precipitation, in this case \u0026mdash; whose temporal evolutions are optimally correlated. These are linear relationships that can be used for CCA-based seasonal prediction models (e.g., Barnett and Preisendorfer, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Gershunov and Cayan, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), but are used in the diagnostic mode here.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cem\u003ea) Precipitation anomalies and AR activity\u003c/em\u003e \u003c/p\u003e \u003cp\u003eNegative SST anomalies over the tropical Pacific during fall and early winter 2022, indicative of the cold phase of ENSO (La Ni\u0026ntilde;a), tilted the odds towards a dry WY2023 in the southwestern US and wet in the northwestern US. However, the observed precipitation anomalies from early (OND) through late winter and spring (FMA) consistently deviated from this expected La Ni\u0026ntilde;a pattern, i.e. La Ni\u0026ntilde;a canon. While the Northwest and the desert Southwest recorded near-normal precipitation totals, much of the mid-latitude WUS (where historical correlation between precipitation and ENSO is weak ) and Southern California experienced unexpectedly high levels of precipitation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-e). Noteworthy regional features included: 1) Central Sierra Nevada recording its second snowiest winter since 1946 (UC Berkeley Central Sierra Snow Lab, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbsnews.com/sacramento/news/2nd-snowiest-season-history-since-1946-uc-berkeley-central-sierra-snow-lab/\u003c/span\u003e\u003cspan address=\"https://www.cbsnews.com/sacramento/news/2nd-snowiest-season-history-since-1946-uc-berkeley-central-sierra-snow-lab/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, as well as record precipitation in Central California and regions inland from there in a northeasterly swath (Williams et al. 2014b) and 2) precipitation over the southeastern California desert, the only place La Ni\u0026ntilde;a canon materialized, was slightly below-normal. Overall, considering the westwide domain, WY2023 precipitation anomalies were opposite to those expected and predicted in a majority of seasonal precipitation prediction systems based on the concurrent La Ni\u0026ntilde;a conditions (DeFlorio et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, their Fig.\u0026nbsp;6). Overall, WY2023 provided a glaring example of widespread and rampant La Ni\u0026ntilde;a heresy. If anything, the WY2023 precipitation anomaly pattern was strongly in tune with El Ni\u0026ntilde;o, rather than La Ni\u0026ntilde;a canon. Figures\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee) and 1g) show the impressive contrast between observed and expected precipitation during late winter JFM; anomalous precipitation in Southern California was strongly positive and the extent of the heresy over the entire domain was such that the spatial correlation between JFM anomalies and La Ni\u0026ntilde;a canon (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea,g, respectively) was \u0026minus;\u0026thinsp;0.52.\u003c/p\u003e \u003cp\u003eIdentifying other heretical ENSO years in our record, La Ni\u0026ntilde;a WYs 1967, 2011 and 2017 were also unexpectedly wet in southern California while El Ni\u0026ntilde;o WYs 1964, 1977, 1987, 2007, 2013, and 2015 were unexpectedly dry (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). WY2016 does not appear as an outstanding heretical year because even though the expected wetness from the \u0026ldquo;Godzilla El Ni\u0026ntilde;o\u0026rdquo; did not occur, the negative anomalies fell short of the \u0026minus;\u0026thinsp;0.75\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\sigma\\)\u003c/span\u003e\u003c/span\u003e SoCal precipitation anomaly threshold chosen to define heretical years. Nevertheless, WY2016 was special \u0026mdash; certainly not canonical \u0026mdash; and we scrutinize it below alongside the true heretical years. Among those true heretical years, WY2023 was the most anomalous in SoCal (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea); the precipitation was 2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\sigma\\)\u003c/span\u003e\u003c/span\u003e above climatology \u0026mdash; comparable to the exceedingly wet canonical El Ni\u0026ntilde;o WYs 1983 and 1998.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe observe that the heretical La Ni\u0026ntilde;a WYs in SoCal were marked by outstanding AR activity as gaged by the number of days with landfalling ARs impacting SoCal, whereas the heretical El Ni\u0026ntilde;o WYs experienced deficient AR landfalls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Consequently, AR precipitation (ARpr) was greater than precipitation from non-AR events (nonARpr) during heretical La Ni\u0026ntilde;a WYs, while ARpr was scarce during most heretical El Ni\u0026ntilde;o WYs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The anomalous AR activity during the heretical WYs contributed inordinately to total WY precipitation not only in SoCal, but also in most of the Western US. During the heretical La Ni\u0026ntilde;a WYs, ARs contributed more than 60% of the total precipitation in SoCal (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea, S2a), far exceeding their climatological average contribution of ~\u0026thinsp;40% (Figure S2, S3). Remarkably, during the weak La Ni\u0026ntilde;a of WY2017, ARs accounted for over 60% of the precipitation received across nearly all of California. In contrast, the lack of ARs in the heretical El Ni\u0026ntilde;o years (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eb, S2b) caused the AR precipitation contribution to fall to as low as 10% during the weak El Ni\u0026ntilde;o event of WY2007 (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, S2, and S3). Notably, three out of the five lowest-ranking seasons, with respect to AR landfall days, occurred during heretical El Ni\u0026ntilde;o years (WYs 1964, 1977, 1987; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Also the record high frequency of AR days was set during the weak La Ni\u0026ntilde;a WY2017 \u0026mdash; one of the wettest years on record for California as a whole (Figure S4). These results highlight the outsized influence of ARs on SoCal precipitation variability, accounting for most of the interannual precipitation variability in this region: ARpr (nonARpr) and WY precipitation correlation is approximately 0.9 (0.7). Clearly, ARpr is not completely independent of nonARpr, often being associated with the same midlatitude cyclones (e.g. Zhang et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). ARpr and nonARpr are correlated at 0.4 across WYs over SoCal (purple and blue time series in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eConsidering all of California (Figure S4), other heretical La Ni\u0026ntilde;a years with outstanding AR activity are identified (1956 and 1974 with 15 and 28 anomalous landfalling AR days, respectively; Figure S5), but WY2017 holds the record for the most active AR year (81 landfalling AR days compared to 37 days on average; 44 days above normal, Figure S5b) and for excessive precipitation (only slightly surpassed by WY1983). Weak La Ni\u0026ntilde;a WY2017 was the wettest heretical year on record for California. This aligns with the findings of Dettinger (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and Bao (2006) that near-neutral ENSO years favor tropical water vapor transport by ARs in the eastern Pacific, and findings by Gershunov et al (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) that positive PDO tends to favor landfalling ARs and positive precipitation anomalies in California. It is noteworthy that heretical precipitation anomalies developed differently across the WYs. For instance, La Ni\u0026ntilde;a 2011 brought anomalous wetness in OND and DJF, while in 2017 and 2023, anomalous wetness persisted across the entire wet season (Figure S5).\u003c/p\u003e \u003cp\u003eThe heretical La Ni\u0026ntilde;a and El Ni\u0026ntilde;o precipitation anomalies vary latitudinally, especially when they are compared with canonical WYs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In SoCal, precipitation totals in heretical Las Ni\u0026ntilde;a WYs were similar to each other and comparable to those of canonical El Ni\u0026ntilde;o WYs 1998 and 1983. In Northern California, the wettest heretical year was the weak La Ni\u0026ntilde;a 2017, with total precipitation and frequency (number of rainy days) comparable to El Ni\u0026ntilde;o WY1998, surpassed only by El Ni\u0026ntilde;o WY1983. The latitudinal profile of El Ni\u0026ntilde;o WY2016 shows that precipitation was very close to climatology in SoCal, but in Central and Northern California, WY2016 did produce positive precipitation anomalies, though still well short of the canonical Los Ni\u0026ntilde;os 1983, 1998, or the heretical Las Ni\u0026ntilde;as 2011, 2017, and 2023. It is informative to observe the wide range of total precipitation and frequency during canonical versus heretical years under the same ENSO active phase, for instance, the two strong Las Ni\u0026ntilde;as 1989 (dry) and 2011 (wet) or the two very strong Los Ni\u0026ntilde;os 1983 (wet) and 2016 (close to normal). Also interesting are the similarities between the canonical and heretical years under opposite ENSO phases, such as, the canonical moderate La Ni\u0026ntilde;a 2012 (dry) and the heretical moderate El Ni\u0026ntilde;o 1987 (dry), and vice versa e.g. WYs 1983 and 2007.\u003c/p\u003e \u003cp\u003eLooking beyond the ENSO region, we have explored the possible influence of Pacific SST anomalies on heretical WYs (see Supplementary Materials: Figures S6 and S7 and associated text). Since tropical SST anomalies differed greatly between heretical WYs, SST does not directly explain the heresy and instead reinforces the notion that each heretical year was unique in its own way.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eb) Implications for seasonal prediction\u003c/em\u003e \u003c/p\u003e \u003cp\u003eUp to this point, we showed that ARs were key wildcards in producing the unexpected precipitation anomalies during heretical WYs. Therefore, a natural question is: What exactly are we predicting when we predict canonical precipitation anomalies during ENSO-active years? To address this question, we reexamined the relationship between ENSO and seasonal precipitation \u0026mdash; separating precipitation into non-AR and AR components. In concordance with previous studies (e.g., Dettinger et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; DeFlorio et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), we found that the correlation between ENSO and total seasonal precipitation is positive and significant mostly in the southwestern US (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). This correlation strengthens toward late winter (JFM) and even early spring (FMA) (Figure S10), consistent with previous results (e.g. Gershunov and Cayan \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Chapman et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Warm SST anomalies along the Pacific Coast, typically occurring during El Ni\u0026ntilde;o events (Figure S7a), may explain the strong correlation during FMA. At a glance, the correlation of ENSO with non-AR precipitation looks very similar to that with total precipitation (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and S10c). On the other hand, the overall correlation patterns for AR precipitation are weaker, with the highest correlations obtained over southern Arizona, and New Mexico (Sonoran) desert (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb and S10b). Besides precipitation from the ARs hitting the California Coast, precipitation in these regions is highly dependent on the landfalling ARs in Baja California that penetrate the interior Southwest (Rutz and Steenburg 2012; Guirguis et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e).Opposite landfalling AR-associated IVT anomalies during La Ni\u0026ntilde;a (Fig.\u0026nbsp;8a) and El Ni\u0026ntilde;o years (Fig.\u0026nbsp;9a) in Baja California and Sonora suggest that ENSO influence on AR precipitation over the southwestern desert is related to ARs that make landfall in Mexico, especially during the late winter and early spring.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGiven that the frequency of AR precipitation could be lower than that of non-AR precipitation, part of the difference in the correlations could be impacted by sample size: the smaller samples of ARs compared to that of other storms would lead to larger interannual (sampling) variability of ARpr vs nonARpr (see Table S2 for an example in SoCal). To ensure that the stronger correlation with nonARpr is not only due to a sample size issue, we estimated the total precipitation selecting the \u003cem\u003en\u003c/em\u003e-heaviest nonARpr days, where \u003cem\u003en\u003c/em\u003e is the frequency of ARpr. Using the same interannually varying sample size, the influence of ENSO on non-AR and AR precipitation becomes more alike (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb,d), suggesting that ENSO influence on AR precipitation might be partially hidden due to the smaller sample size of ARpr days compared to that of non-ARpr days. The reduced region of significant correlation associated with a reduced sample size indicates a robust linear relationship mainly over the low Southwestern (Sonoran) desert (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). The ENSO signal in both non-AR and AR precipitation comes mostly from precipitation frequency (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea,c S11, and S12) since the correlation with intensity lacks significance in most of the Western US, except over a small region in coastal northern California (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb,d). The frequencies of ARpr and non-ARpr correlate over the Sonoran desert and most of California (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee), indicating a relationship between daily AR and non-AR precipitation events. However, their intensities are not correlated in most of the Western US (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef). ENSO influences the frequency of both ARpr and nonARpr precisely in the region where ARpr and nonARpr frequencies are significantly correlated.\u003c/p\u003e \u003cp\u003eComposites of AR and nonARpr show that El Ni\u0026ntilde;o and La Ni\u0026ntilde;a contribute similarly to the ENSO signal found over the southwestern desert for precipitation totals and frequency (Figure S12). During El Ni\u0026ntilde;o winters, landfalling ARs have a stronger southerly component over the West Coast and a more westerly component over the Baja California peninsula, enhancing the humidity source and resulting in a positive anomaly in vertically integrated water vapor (IWV) and slightly more landfalling AR days in parts of Baja California. On the contrary, during La Ni\u0026ntilde;a winters, the northeasterly and easterly components of AR IVT are stronger over the US West Coast and Baja California, respectively. This leads to lower IWV compared to climatology and El Ni\u0026ntilde;o winters, a lower frequency of landfalling AR days in Baja California, and fewer AR precipitation days in the southwestern desert (Figure S13).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Conclusions and Discussion","content":"\u003cp\u003eWY2023 is a clear example of a heretical wet La Ni\u0026ntilde;a WY in California when most seasonal forecasts tilted the odds towards canonically dry La Ni\u0026ntilde;a anomalies, especially over Southern California and the desert Southwest (DeFlorio et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Fig.\u0026nbsp;6). We showed that strong AR activity was instrumental for the unanticipated well-above-normal precipitation in the Southwestern US during La Ni\u0026ntilde;a 2023 as well as for other heretical La Ni\u0026ntilde;a WYs on record: 1967, 2011, and 2017. Meanwhile, anomalously weak AR activity played the decisive role in heretically dry El Ni\u0026ntilde;o WYs (1964, 1977, 1987, 2007, 2013, and 2015), and the close-to-average \u0026ldquo;Godzilla El Ni\u0026ntilde;o\u0026rdquo; WY2016.\u003c/p\u003e \u003cp\u003eThe outsized influence of ARs on California\u0026rsquo;s hydroclimate (e.g. Dettinger et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, Gershunov et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and specifically in ENSO heresy as described here, lead us to speculate about alternative precipitation anomalies that did not materialize but were possible in the Western US during famously wet Los Ni\u0026ntilde;os of 1983 and 1998 under different AR frequencies from those that actually happened to occur. What would the precipitation anomalies for Los Ni\u0026ntilde;os 1983 and 1998 have been given fewer ARs? Would our interpretation of the canonical El Ni\u0026ntilde;o precipitation anomalies have been different? On the contrary, would the possible wetness from a few additional ARs (which have not occurred) have been attributed to ENSO during the most recent \u0026ldquo;Godzilla El Ni\u0026ntilde;o\u0026rdquo; 2016? As few as two or three additional moderate or intense ARs making landfall in SoCal would have produced the expected wetness, which would have been interpreted according to El Ni\u0026ntilde;o canon. The results from this study emphasize the critical role of AR activity in shaping ENSO-related precipitation anomalies in the Southwestern US. The anomalous bounty or paucity of ARs, their intensity and orientation (Guirguis et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), can either amplify the expected anomalies based on ENSO conditions or negate them, disrupting seasonal predictions made according to historical correlation with ENSO to the extent of generating entirely unexpected \u0026mdash; heretical \u0026mdash; precipitation anomalies. Meanwhile, AR activity is modulated by many influences from synoptic and subseasonal (MJO, PNA, AO; e.g. Guan and Waliser, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) to interannual and decadal (PDO, ENSO; e.g. Gershunov et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Guirguis et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) as well as high frequency internal atmospheric variability (e.g. Jiang et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This complex interplay of influences makes predicting AR landfalls and associated precipitation extremely challenging at seasonal scale. We therefore consider ARs as wild cards and potential disruptors of seasonal prediction in California and Western US.\u003c/p\u003e \u003cp\u003eThe results of this study suggest that the canonical ENSO pattern in western US precipitation is mainly determined via teleconnections to non-AR precipitation frequency. Williams et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e) also found a stronger relationship between ENSO and non-AR vs AR precipitation over the Sierra Nevada, the largest source of above-ground water resources for California. Meanwhile, AR precipitation frequency contributes to the ENSO signal mainly in the northern Sonoran desert stretching from the interior of SoCal across southern Arizona and into southern New Mexico. The Desert Southwest may be the one region of the Western US where AR landfalling activity produces a precipitation signal that is somewhat reliably synchronized with contemporaneous ENSO activity, especially during late winter (JFM) and early spring (FMA). This needs further investigation, focusing on the landfalling ARs in Baja California and their inland penetration into the southwestern desert. However, this region experiences fewer AR days and less AR precipitation compared to the coastal region (Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea, S2a) The idea that atmospheric rivers are the wild cards of seasonal precipitation prediction remains particularly relevant for coastal California. Relying solely on ENSO signals for seasonal precipitation prediction, therefore, does not give adequate recognition of the relevance of ARs in the hydroclimate of most of the Western US.\u003c/p\u003e \u003cp\u003eAlthough we have discussed the influence of ENSO on ARpr and nonARpr separately, it is important to keep in mind that ARpr and nonARpr precipitation events are not mutually exclusive. As Zhang et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found, 82% of the ARs impacting the West Coast are associated with extratropical cyclones, where pre-frontal widespread precipitation (ARpr) and post-frontal convective precipitation (nonARpr) are organized by the same synoptic storm. AR intensity, however, is only moderately proportional to the storm strength, i.e. the depth of the low pressure organizing the cyclonic circulation. The stronger correlation between the frequencies of ARpr and nonARpr compared to that between their intensities is, therefore, consistent with Zhang et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Notably, ENSO influences the frequency of both ARpr and nonARpr precisely in the region where ARpr and nonARpr frequencies are significantly correlated. Whether ENSO influences the likelihood of a midlatitude cyclone to be associated with an AR and vice versa is yet to be determined.\u003c/p\u003e \u003cp\u003eOverreliance on ENSO canon for seasonal prediction has resulted in inaccurate forecasts that exacerbated the challenges facing California\u0026rsquo;s water resource managers (DeFlorio et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jiang et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, seasonal predictability skill could worsen under evolving climate change since model projections suggest a gradually enhanced contribution of AR precipitation to the annual total, boosting the year-to-year variability of the western hydroclimate (Gershunov et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In a warming future, predicting WY precipitation will become even more important, yet apparently more challenging given that WY precipitation totals are projected to become increasingly dominated by ARs and delivered in increasingly intense storms. The observational and model-based results of Williams et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e), however, suggest that such changes are not expected to clearly emerge from the envelope of natural variability until the second half of this century, indicating there is likely some time to resolve this seasonal prediction challenge before it becomes even more acute. It will be important to examine in future work whether the heresy of recent Las Ni\u0026ntilde;as (WYs 2011, 2017, and 2023) had anything to do with anthropogenic causes \u0026ndash; particularly polar-amplified global warming \u0026ndash; already marking a new period when precipitation is becoming less predictable in the West. In other words, it should be determined if unexpected precipitation anomalies are becoming more likely to occur in the changing climate, i.e. if global warming promotes ENSO heresy. Such future studies should continue to investigate the potential of ARs to strongly influence the overall seasonal precipitation outcomes over the western US.\u003c/p\u003e \u003cp\u003eFor the time being, exploring new variables related to AR activity (e.g. Integrated Vapor Transport as in Lavers et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e and Wang et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) might provide added skill for AR precipitation prediction. Seasonal prediction progress along those lines is not guaranteed, however, since seasonal predictor variables must offer climate memory in order to provide seasonal prediction skill at least one month ahead. Another potentially promising approach is the development of a new S2S prediction framework (e.g. DeFlorio et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; White et al. 2022), which would address the challenge of merging the seasonal signal from SST conditions (mainly ENSO-based precipitation prediction) with subseasonal information such as synoptic weather regimes related to AR landfalls and AR IVT and precipitation (e.g. DeFlorio et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Zhang et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Guirguis et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Such an integrated approach to S2S prediction could improve the accuracy of both seasonal and subseasonal predictions by addressing both timescales in one integrated S2S prediction system. Of course, it is also essential to keep evolving water management strategies that enhance society\u0026rsquo;s flexibility and capability to adapt to the inherent uncertainty in seasonal predictions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the California Department of Water Resources and Department of the Interior via the Southwest Climate Adaptation Science Center.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCW3E personnel were supported by the California Department of Water Resources Atmospheric River Program Phase III (Grant 4600014294).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData sharing is not applicable to this article as no datasets were generated. Data used in this study are available from publicly accessible data archives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Rosa Luna-Niño processed data and produced figures. Rosa Luna-Niño and Alexander Gershunov wrote the manuscript and all authors provided valuable comments and suggestions. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBarnett, T. P., and Preisendorfer, R. 1987. 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Geophysical Research Letters, 46(3), 1814-1823.\u003c/li\u003e\n\u003cli\u003eZhang, Z., DeFlorio, M. J., Delle Monache, L., Subramanian, A. C., Ralph, F. M., Waliser, D. E., ... and Lin, H. 2023. Multi‐Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated With Atmospheric Rivers Over the Western US. \u003cem\u003eJournal of Geophysical Research: Atmospheres\u003c/em\u003e, 128(7), e2022JD037608.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"climate-dynamics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cldy","sideBox":"Learn more about [Climate Dynamics](https://www.springer.com/journal/382)","snPcode":"382","submissionUrl":"https://submission.nature.com/new-submission/382/3","title":"Climate Dynamics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"ENSO, seasonal precipitation, Atmospheric Rivers, disruptors, heresy, Southwestern US","lastPublishedDoi":"10.21203/rs.3.rs-4583843/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4583843/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn spite of forecasts for anomalous dryness based on the canonical La Ni\u0026ntilde;a signal, Water Years 2011, 2017, and 2023 brought copious precipitation to California and the Southwestern United States (SWUS). Although El Ni\u0026ntilde;o\u0026mdash;Southern Oscillation (ENSO) is the main source of seasonal precipitation predictability for the region, outstanding Atmospheric River (AR) activity produced the unexpected regional wetness in each of these heretical water years (WYs). We define \u003cem\u003eheretical\u003c/em\u003e WYs as those that result in precipitation anomalies that oppose those expected based on ENSO alone. We assess the contribution of ARs and other storms to these WYs, finding that heretical La Ni\u0026ntilde;a/El Ni\u0026ntilde;o WYs were characterized by anomalously robust/deficient AR activity. In California, precipitation accumulation during the heretical La Ni\u0026ntilde;a WYs was comparable to or even exceeded that observed during the exceedingly wet WY1998 \u0026mdash; the textbook canonical El Ni\u0026ntilde;o year. Our findings indicate a weaker/stronger relationship between ENSO and AR/non-AR precipitation, primarily driven by storm frequency. Although ARs can disrupt the ENSO-precipitation signal, ENSO still influences the frequency of AR precipitation in the southwestern U.S. desert, the region influenced by ARs that make landfall in Baja California, Mexico. These results highlight the complexity of ENSO's impact on precipitation in the Western US and underscore the need for a nuanced understanding of ENSO\u0026rsquo;s influence on ARs to improve seasonal precipitation prediction.\u003c/p\u003e","manuscriptTitle":"Heresy in ENSO teleconnections: Atmospheric Rivers as disruptors of canonical seasonal precipitation anomalies in the Southwestern US","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-15 07:58:50","doi":"10.21203/rs.3.rs-4583843/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor Revision","date":"2024-12-04T23:42:27+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-09-05T17:21:17+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-21T22:35:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-15T04:47:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Climate Dynamics","date":"2024-06-15T00:42:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"climate-dynamics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cldy","sideBox":"Learn more about [Climate Dynamics](https://www.springer.com/journal/382)","snPcode":"382","submissionUrl":"https://submission.nature.com/new-submission/382/3","title":"Climate Dynamics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b3b05b28-bb0e-4992-bb40-2ff47588242c","owner":[],"postedDate":"July 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-10T16:10:16+00:00","versionOfRecord":{"articleIdentity":"rs-4583843","link":"https://doi.org/10.1007/s00382-025-07583-1","journal":{"identity":"climate-dynamics","isVorOnly":false,"title":"Climate Dynamics"},"publishedOn":"2025-02-07 15:58:27","publishedOnDateReadable":"February 7th, 2025"},"versionCreatedAt":"2024-07-15 07:58:50","video":"","vorDoi":"10.1007/s00382-025-07583-1","vorDoiUrl":"https://doi.org/10.1007/s00382-025-07583-1","workflowStages":[]},"version":"v1","identity":"rs-4583843","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4583843","identity":"rs-4583843","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}