The role of soil moisture on summer atmospheric circulation climatology in the Northern Hemisphere

The role of soil moisture on summer atmospheric circulation climatology in the Northern Hemisphere | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The role of soil moisture on summer atmospheric circulation climatology in the Northern Hemisphere Fei Luo, Frank Selten, Dim Coumou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6420148/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Feb, 2026 Read the published version in npj Climate and Atmospheric Science → Version 1 posted 10 You are reading this latest preprint version Abstract Soil moisture–atmosphere interactions intensify extremes like heat waves and droughts. Atmospheric circulation and soil moisture are key drivers for both local and remote extreme events via dynamical and thermodynamical mechanisms. Understanding the interaction between soil moisture and atmosphere dynamics, including potential feedback loops, is crucial for both climate attribution studies and sub-seasonal to seasonal forecasts. Here, we study the effect of soil moisture on large-scale atmospheric circulation using large ensemble simulations from the fully coupled climate model EC-Earth 3 from 2009 to 2016. The atmosphere evolves freely in all the experiments. Four sets of experiments are carried out with one control run in which the interaction between the atmosphere and the land is fully interactive. In contrast, in the other three experiments soil moisture is prescribed. The main finding of this study is that soil moisture impacts the climatological mean state of the atmospheric circulation in the Northern Hemisphere during the summer season (June to August) and especially in July. Specifically, we observe poleward shifts of subtropical jets and a stronger polar front jet in the experiment with the prescribed soil moisture climatology of the control experiment with interactive soil moisture. Additionally, by allowing the two-way interaction between land and atmosphere (control experiment), the wave amplitudes over land are strengthened by approximately 24% (compared to soil moisture prescribed), which implies the key role of land-atmosphere coupling in modulating atmospheric wave dynamics. The Stationary wave patterns over North America are triggered in the experiment with prescribed climatological soil moisture of the ERA land reanalysis. In addition, we find that interactive soil moisture leads to higher mean summer surface temperatures for most land areas up to + 1.5 k and even higher (+ 3 k) for temperature extremes (90th near-surface daily temperature). We conclude that soil moisture impacts the atmospheric circulation. Therefore, we expect circulation changes triggered by drying soils in large areas of the summer continents in projections of our future climate. Earth and environmental sciences/Climate sciences/Atmospheric science/Atmospheric dynamics Earth and environmental sciences/Climate sciences Earth and environmental sciences/Climate sciences/Climate change/Climate and earth system modelling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Soil moisture plays a vital role in the climate system. The exchange of water and heat between land and atmosphere depends on the amount of soil moisture. Soil moisture impacts the surface energy balance and the hydrological cycle by directly affecting evaporation. Two major feedback loops are described in the literature soil moisture and temperature and soil moisture and precipitation (Seneviratne et al. 2010). The soil moisture-temperature feedback works as follows. When the surface air temperature rises, more water evaporates from the soil, reducing the soil moisture content. At some point, a lack of soil moisture limits evaporation and the associated evaporative cooling. As a result, the ground heats, and the sensible heat flux increases, leading to higher surface air temperatures. Reduced evaporation and higher air temperatures lead to reduced cloud cover and enhanced solar radiation at the surface. This further amplifies the drying and the surface warming. The soil moisture-precipitation feedback works as follows. Precipitation increases soil moisture. Wetter soils lead to more evaporation and moistening of the planetary boundary layer, favouring cloud formation. More clouds lead to enhanced precipitation. The drying and wetting of the soil takes time and introduces a memory into the climate system. Therefore, knowledge of the soil moisture state can lead to skillful forecasts on sub-seasonal to seasonal time scales (Lorenz, Jaeger, and Seneviratne 2010). Previous studies have shown the significance of soil moisture in promoting and maintaining extreme events such as heat waves and droughts, both as local and remote drivers. Locally, there are various pathways in which dry soils trigger and amplify heat waves. These processes and mechanisms are mainly land-atmosphere coupling (Seneviratne et al. 2006; Miralles et al. 2014), evapotranspiration (Fischer et al. 2007), feedback mechanisms (Seneviratne et al. 2010), and surface energy balance (Lorenz, Jaeger, and Seneviratne 2010; Haghighi et al. 2018; Hsu and Dirmeyer 2023). Miralles et al. (2014) demonstrated that the mega-heatwave in Europe in 2003 and 2010 summers would not have been possible without the soil desiccation conditions, emphasizing the land-atmosphere coupling. When soil drying enhances the diurnal warm air entrainment, it accumulates atmospheric heat that lasts (Miralles et al. 2014). Usually, the evapotranspiration process from soil and plants regulates the land surface temperature as it has a cooling effect. However, when the soil moisture becomes limited, the evapotranspiration rate reduces, which induces heat wave conditions, if prolonged, even drought conditions (Miralles et al. 2019). Soil moisture temperature and soil moisture precipitation are two dominating feedback mechanisms; for soil moisture-temperature feedback, surface drying is induced by reduced soil moisture, enhancing surface heating during heat waves. The heated surface again dries the soil moisture below (Seneviratne et al. 2010). Various studies, including a generalized framework (Haghighi et al. 2018) and both regional (Lorenz, Jaeger, and Seneviratne 2010) and global climate models (Hsu and Dirmeyer 2023), show that the partitioning of land surface energy is strongly affected by soil moisture as it affects the balance between sensible and latent heat fluxes; the dry soil moisture contributes to increased sensible heat flux and, thus, persistent heat waves. Additionally, apart from the role of soil moisture in heat waves, circulation and atmospheric dynamics are indispensable. The recent ExtremeX global climate model experiment study from Wehrli et al. (2022), where the different multi-model experiments covered free atmospheric and land interaction, atmospheric nudging, and soil moisture prescription, showed the results from recent heatwave case studies demonstrated that atmospheric circulation patterns and soil moisture anomalies play key roles in extreme heat occurrences. While soil moisture effects are essential for the US Great Plains, tropics and monsoon regions, the circulation anomaly pattern overrides the rest of the extratropic and high latitudes areas. Furthermore, a critical aspect of extreme events study is atmospheric dynamics. In middle latitudes, large-scale atmospheric circulation, namely jet streams, affects the day-to-day weather systems and governs the land surface conditions. Previous studies showed that high-amplitude quasi-stationary Rossby waves can trigger extreme events (Petoukhov et al. 2013; Mann et al. 2018; Teng and Branstator 2019). Both observational (reanalysis) and model studies have illustrated the importance of specific Rossby wave patterns, especially amplified circumglobal waves 5 and 7 in boreal summer, in promoting stagnating weather systems and, therefore, also responsible for global simultaneous extremes (Kornhuber et al. 2020; Luo et al. 2022). Regionally, the waviness of jets can impact the numbers and locations of weather extremes at mid-latitudes (Röthlisberger, Pfahl, and Martius, 2016). A “recurrent synoptic-scale Rossby wave pattern” (RRWP) was identified based on reanalysis data that showed it to be responsible for persistent hot spells (Röthlisberger et al. 2019). An overview of Waveguide theory and its association with surface extremes weather was summarised in a recent study (White et al. 2022). Linking soil moisture to upper-level atmospheric circulation, a few studies have looked at the soil moisture-atmosphere interaction in one way: dry soils affect large-scale circulation in the Northern Hemisphere (Teng and Branstator 2019; Teng et al. 2019) and Southern Hemisphere (Ali, Martius, and Röthlisberger 2021; Martius, Wehrli, and Rohrer 2021). For example, during mega heat waves, dry soils can influence local circulation (Miralles et al. 2014), and dry soil conditions can even affect remote circulation (Di Capua et al. 2021). Di Capua et al. (2021) showed that the dry soil moisture in western Russia enhances flood risks in Pakistan via a Rossby wave response. Gloege et al. (2022) also looked into spring but focused on the case study of the 2020 Siberian Heatwave. The study from Koster et al. (2016) supported the positive feedback loop idea that drying various interior regions in North America leads to atmospheric circulation changes that reinforce the heating on the continental interior. In their experiments, drying soil moisture simulations were performed with a stationary wave model (SWM) and an atmospheric general circulation model (AGCM). In the SWM experiments, the model was forced to use idealized diabatic heating at a few locations in the continental United States. Whereas in the AGCM experiments, soil moisture dryness was imposed in several places in the US interior. Despite the different models used and locations chosen, the atmospheric circulation anomaly shows similar patterns: a high-pressure anomaly in West-Central North America and a low-pressure anomaly to the east. The proposed potential positive feedback loop suggests that drying in soil moisture imposed in the US interior triggers a specific atmospheric circulation pattern which warms up the central US with increased surface sensible heating that reinforces the original atmospheric circulation anomalies (Koster et al., 2016). The need for large ensembles (96–192) was also emphasized for detecting the spatial patterns of the induced stream function, precipitation, and 2-m temperature anomalies in their results. In this paper we build upon this earlier work and try to understand the role of soil-moisture-atmosphere interactions on the hemispheric-scale boreal summer circulation. We cover the analysis of the summer season, mainly using the month of July as an example to understand the soil moisture conditions and, hence, their implications for surface variables. Furthermore, we analyze jet stream patterns and planetary wave changes induced by different soil moisture experiments. This is the first study to examine the role of two-way soil moisture interaction between land and atmosphere on the climatological summer circulation employing large ensemble global climate model experiments. This paper aims to answer the following research questions: - How does the two-way interaction between soil moisture and atmosphere dynamics influence the climatological mean state of the jet stream and planetary wave in boreal summer? - What is the circulation’s response to variability in soil moisture? 2. Data and Methods 2.1 European Community Earth System Model version 3 (EC-Earth3) The model output from the European Community Earth System Model (EC-Earth3) (Döscher et al. 2021 ) is used in this study. The atmosphere component from EC-Earth is based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System IFS cycle cy36r4. There are 91 vertical model levels; the horizontal model resolution is T255 (ca. 80km). IFS also has a land component H-TESSEL land surface model (Balsamo et al. 2015 ) that consists of four soil layers: 0–7, 7–28, 28–100, and 100–255 cm. The monthly sea surface temperature and sea ice is prescribed in the model, where HadISST1 and NOAA OI2 data set were used (Hurrell et al. 2008 ). EC-Earth3 was run with model version 3.3.1 with CMIP6 scenario SSP3-7.0 for all the experiments. 2.2 Experiment set-up There are four sets of ensemble experiments included in this study. An overview of the experiments is presented in Table 1 . All experiments have the same prescribed SSTs, sea ice cover fraction, and land cover. They differ in atmospheric nudging, soil moisture climatology states, and soil moisture prescription. All the experiments consist of 100 ensemble members for the period of 2009 to 2016. Table 1 EC-Earth3 model Experiments description. Experiment Period Ensemble Description SMI 2009–2016 100 atmosphere and soil moisture interactive SME 2009–2016 100 atmosphere interactive, EC-Earth ensemble climatological soil moisture prescribed SMF 2009–2016 100 atmosphere interactive and reanalyses soil moisture prescribed (6 hourly) SMC 2009–2016 100 atmosphere interactive and soil moisture climatology from reanalyses prescribed 2.3 Soil moisture data All four soil layers were prescribed for SME, SMF, and SMC experiments. The experiments prescribe three sets of soil moisture: ERA-Land (Balsamo et al. 2015 ) prescribed on a 6-hrly timescale, ERA-Land climatology soil moisture that is calculated, and the soil moisture ensemble mean climatology from SMI runs. The soil moisture ensemble mean climatology (Fig. A1 ) is the prescribed soil moisture for SME simulations. It was calculated based on all the 100 SMI ensemble member soil moisture values. First, the median ensemble soil moisture values were computed, then a 15-day running mean process was carried out, followed by a multi-year (2009–2016) daily mean calculation. Soil moisture standard deviation plots for SMI and SMF were calculated based on the data described in Table.1 (Fig. A2 ). For SMF experiments, the ERA-Land soil moisture was prescribed every six hours from 2009 to 2016. ERA-Land soil moisture climatology for SMC experiments was computed from the ERA_land daily soil moisture data from 1982–2008. The median value of that day in a year (1982–2008) was first calculated, and then a 15-day running mean was applied. Since the model outputs 6-hourly timescale, the same soil moisture climatology data was prescribed four times daily. 2.4 Summer season month July climatology plots Climatology plots are computed as the ensemble monthly mean from 100 ensemble members from 2009 to 2016 and month July. All the ensemble members were initially outputted on six hourly time scale, then climatological means are calculated based on these data to monthly means. We restrict our study domain from 20S to 90N and 180W to 180E to cover the Northern Hemisphere and Southern tropics. 3. Results 3.1 Jet stream response to Soil Moisture-Atmosphere interaction First, we focus on the question of whether the two-way interaction between soil moisture and the atmosphere influences the climatological state of the jet streams. To do so, we compare the July climatology of the experiment with interactive soil moisture (SMI) and without (SME). Figure 1 shows the climatology for thermodynamic variables for SMI in the left column. The impact of interactive soil moisture is in the right column, as it is the difference in the climatology between SMI and SME. Dynamical variables are shown in Fig. 2 . Stippled areas outline the regions where the difference is significant at 99% confidence (determined from bootstrapping 1000 times of random samples from 800 July months). The mean surface air temperature is generally much higher with interactive soil moisture (Fig. 1 b). Largest impact (0.5–1.5 k) occurs in E. Siberia, Russia, Europe, and central to East North America. In these areas, we see enhanced net short-wave radiation (Fig. 1 (h)) and increased stream function values at 250 hPa (Fig. 2 (h)). These changes suggest that in these areas, on average soil moisture more often limits evaporation in SMI, leading to reduced evaporative cooling of the surface, increased surface temperature and sensible heat flux, fewer clouds, more solar radiation and a warmer air column beneath 250 hPa leading to the positive stream function anomalies aloft. The increase in solar radiation is larger than the reduction in evaporative cooling and increase in sensible heat flux (Fig. 1 (d)). In the areas of increased radiation, we find significantly reduced precipitation (Fig. 2 (j)) . The mean position and strength of the jet streams are affected by interactive soil moisture. (Fig. 2 (e) and (f)). Over North America and Eurasia the jet stream is weaker and slightly northward shifted with interactive soil moisture. The polar front jet above the northern coast of Eurasia is enhanced and above the North-Atlantic there is a clear northward shift of the jet stream leading to a more south-west to north-east tilting of the jet stream. Also the stationary waves are affected. A circumglobal wave response is visible in the meridional wind response at 250 hPa as well as in the azonal part of geopotential height at 500 hPa (Fig. 2 (b) and (d)). The positive geopotential height changes match as expected the positive streamfunction changes over Canada, East Europe, and Northeast Asia. The stationary wave response has a clear circumglobal wave number 5 signature. The monsoon is strengthened in SMI runs as shown in Fig. 2 (j). There is more precipitation in Indian monsoon belt regions in SMI than in SME runs. This corresponds well with the more latent heating fluxes in SMI (Fig. 1 (f)). 3.2 Jet stream response to prescribed soil moisture variability Furthermore, since both SMF and SMC are from the same soil moisture dataset, ERA-Land, and none have two-way land-atmosphere interaction, comparing these two experiments will shed light on the variability in soil moisture implying for the atmosphere. In SMF, the day-to-day soil moisture variability is the same as in ERA-Land. In contrast, in SMC, the variability is gone because of the prescription of soil moisture climatology. Figure 3 shows the surface thermodynamic variables fields for both climatology from SMF (left column) and the differences between SMF and SMC ensemble mean climatology (right column). Although with the same soil moisture climatology prescribed, SMF exhibits warmer near-surface temperatures than SMC (Fig. 3 (b)). For the land region, SMF is warmer than SMC everywhere except for a region in the Sahara. The hotspots for strong temperature warm anomalies can be seen in the central U.S., Russia, East Siberia, and North East China. Those regions show negative anomalies in latent heating and positive anomalies in sensible heating in SMF experiments compared to SMC. This implies that in those regions, the observed variability in soil moisture leads to land warming due to increased sensible heating and decreased latent heating. The soil moisture differences plot (Fig. 3 (d)) pinpoints in Central America, SMF is dryer than SMC, which relates to the high sensible heating (Fig. 3 (f)) and low latent heating (Fig. 3 (h)) fluxes of SMF compared to SMC experiments. As for precipitation patterns (Fig. 3 (j)), at the exact location in Central America, SMF precipates less than SMC. A jet shift is observed as well (Fig. 4 (e) and (f)) between SMF and SMC experiments. The differences plots for both 500 hPa azonal geopotential heights and 250 hPa meridional winds (Fig. 4 (b) and (d)) show a circumglobal wave pattern in the northern hemisphere mid-latitudes. The most pronounced patterns can be seen over North America. This differs from the results of the SMI and SME experiments, where the anomalous patterns are more evident over the Eurasian continent for meridional winds, and the azonal geopotential heights shift northward. Anomalies in stream function at 250 hPa (Fig. 4 (h)) also overlapped with geopotential heights (Fig. 4 (b)) in Central America and North East China. 3.3 Differences in Jet stream response to two-way Interaction and soil moisture variability By comparing the two sets of experiments: SMI and SME vs. SMF and SMC. As the soil moisture climatology means, the state is kept the same between SMI and SME, as well as SMF and SMC. We suspect the responses from the atmospheric circulations come from land-atmosphere interaction and soil moisture variability. Figure 2 (b) and Fig. 4 (b) show that the positions of the jets are different in these two sets of experiments. In the SMI-SME set, azonal geopotential height anomalies position more poleward, and the centers of each hot spot are around 70N. Thus, with interactive soil moisture, the quasi-stationary planetary wave is positioned more northwards, together with a northward shift of the jet stream. Whereas in the SMF-SMC set, they are centred around 50N. Additionally, the wave response in SMI-SME is located primarily over Eurasia (Fig. 2 (d)), whereas it is most pronounced over North America in the SMF-SMC set (Fig. 4 (d)). The stream function difference plots (Fig. 2 (h) and Fig. 4 (h)) show different locations for anomalous hotspots in North America. In the SMI-SME set, the core is in North Canada, whereas in the SMF-SMC set, it is more in Central America. 4. Discussions 4.1 Land-atmosphere two-way interaction induces circulation changes In our study, we compared the July ensemble climatological mean fields for surface thermodynamically controlled variables and variables of the upper-level atmospheric circulation between large-ensemble simulations with different soil moisture and land-atmosphere interactions. Interestingly, panel Fig. 1 (b) patterns identified similar regions that have seen the strongest warming over recent decades by the study of Coumou et al. (2018) in Fig. 1 a to c, suggesting a potential role of soil moisture in amplifying the warming trends. Additionally, the observed linear trend from 1979 to 2020 for near-surface temperature anomalies during JJA seasonal mean during selected extreme events (Teng et al., 2022 ) also coincides with our hotspots in Fig. 1 (b) such as E. Siberia, Russia, Europe, and Northern Canada. When two-way land-atmosphere interaction is turned on (e.g. SMI versus SME), we observe a poleward migration of jet and a more pronounced Arctic font jet state. Additionally, we found an anomalous wave 5 circumglobal wave pattern (Fig. 2 (b, d. This implies that the two-way dynamic interaction between land (soil moisture) and atmosphere affects the position and waves in the jet stream. This anomalous circumglobal wave 5 patterns and/or its resemblance is associated with surface heat extremes were also found in a recent study by Teng et. Al ( 2022 ). Overall, the SMI experiments are warmer than SME runs, suggesting the two-way interaction also introduces more potential extreme events (Fig. A3 ). From the 90th-percentile of near-surface temperature comparisons between SMI and SME, A possible explanation of the observed northward jet shift could be that the atmospheric response to local surface energy fluxes changes is not always in situ, as changes in soil moisture conditions locally induce both local and remote changes in forcings. As the soil dries out, initially, latent heating is reduced, and sensible heating is increased, but later, the atmosphere starts to respond. There will be cloud formation and precipitation processes, then divergence in the air and thus wind changes. As a result, the jets shift their positions. The persistent anomalies in soil moisture can also act as forcing for Circumglobal Wave Trains (CGWTs), specifically amplifying the wave 5 pattern in the mid-latitudes. This results from the influence of soil moisture on surface heat flux, which further modulates atmospheric baroclinicity and wave activity (Teng et al., 2019 ). A few other studies have highlighted the emerging climate signals, based on decades of reanalysis data and modelling data, such as the poleward shift of jet streams in the Northern Hemisphere and attributed that to global warming-induced changes in atmospheric circulation, notably enhanced upper-tropospheric baroclinicity and alterations in stratospheric winds that impact tropospheric eddies and momentum flux (Rivière, 2011 ; Woollings et al., 2023 ; Shaw et al., 2024 ). 4.2 Asymmetrical response from soil moisture prescription One special experimental set-up of our soil moisture prescription experiments is that the soil moisture prescription is applied at every grid point, every soil level, and every time step. This separates our simulations from previous studies which used location-specific soil moisture prescription experiments (Koster et al., 2016 ; Teng et al., 2019 ). Our analyses thereby shed light on the global effect of soil moisture – atmosphere interactions on large-scale circulation but also make it more challenging to interpret in terms of physics. From our analysis, the response from drying vs. wetting soil moisture is asymmetric. This is due to the effect of soil moisture depletion on near-surface temperature (Seneviratne et al. 2010 ) since as long as there is water in the soil (Fig. 5 wet regime), it is an energy-limited regime, and sensible heat fluxes would be small. However, warming has more effect when the soil water content is entirely evaporated in SMF runs (Fig. 5 dry regime). This soil moisture asymmetry effect is especially at play for regions where soil moisture is a global limiting factor. Such as the borders of deserts and dry regions. Thus, the soil moisture drying effect is more pronounced because there is almost always soil moisture as its soil moisture climatology. However, for SMF, there could be locations where the soil is arid; thus, it cannot give feedback on the atmosphere above. Thus, one must consider this asymmetrical effect when studying soil moisture and its relationship to surface energy balance and fluxes and the influence on upper atmospheric level jets. In our results, for instance, in SMC, the soil moisture is not so dry since its soil moisture climatology values, where the dry years would be compensated by wet years. When there is dry soil moisture in SMF (Fig. 3 (d)), take Northeast China as an example; the climatology of warmer near-surface temperature (Fig. 3 (b)), high sensible heating (Fig. 3 (f)) and low latent heating (Fig. 3 (h)) in SMF are also reflected in the exact location. As the surface temperature warms up, there is high pressure, which means it is a clear sky, and evaporation will reduce. Furthermore, reduced soil moisture will, in turn, limit the evaporation from the surface, causing the near-surface temperature to be hotter than the climatology temperature (Fig. 3 (b)). 4.3 Differences between two sets of experiments As described in previous section 3.3 , there are a few differences between the SMI-SME and SMF-SMC sets. The most obvious one is the poleward shifts of the jets in SMI-SME (Fig. 2 (d)) compared to SMF-SMC (Fig. 4 (d)). It could be linked to the variability in soil moisture states (Fig. A2 ). If the variability (standard deviations) of soil moisture is high, the soil moisture could have more influence on the atmosphere above via energy exchanges. However, if the variability is small, assume a region that is always wet or dry. Take the Sahara as an example; the influences of soil moisture variability on the atmosphere will be small. Fig. A1 shows more variability in soil moisture in SMI in mid to high latitudes in the Northern Hemisphere. This is where the jets are presented in the atmosphere above. 4.4 Limitations and Outlook One strength in our approach and results, which echoed the study from Koster et al. ( 2016 ), is that the large ensemble number simulations (in our case 100, and theirs 96–192) were carried out for detecting some specific spatial anomalous patterns in anomalous atmospheric circulation and near-surface temperature. However, at the same time, we have only conducted experiments with EC-Earth3; more models can be added to make more confident and general statements. Although the large ensemble size could compensate for the lack of model diversity, results may be model-dependent, as they ultimately depend on how accurately the model represents land-atmosphere interaction, surface fluxes, and soil moisture. In our study, we compared the large ensemble simulations’ climatological means for various variables. This allowed us to capture the signal of circulation change induced by land-atmosphere interaction. Despite the overall robustness of our results, we still lack confidence in explaining the physical process in detail. The changes we observe are a combination of local and remote effects, which is also outside this study’s scope. Future work can be done on the amplified circumglobal wave characters and associated extreme events. It is also possible to check the early spring soil moisture conditions in each experiment set and the corresponding summer extreme heat events to analyze the seasonal predictability of summer heat waves based on the information on early spring soil moisture conditions. Another aspect is further research on the role of land-atmosphere interactions for extremes, tails of the distribution of the extremes rather than focusing on the mean states. 5. Concluding Remarks Our results show that the two-way interaction between land and atmosphere is critical in driving circulation changes, such as poleward shifts and strengthening of jet stream patterns. This land-atmosphere interaction amplifies the potential for extreme events, as shown by the 90th percentile temperature anomalies increase when SME is compared to SMI (Fig. A3 ). Comparisons between soil moisture experiments reveal that SMI and SMF scenarios exhibit warmer conditions than SME and SMC experiments, also highlighting the sensitivity of temperature patterns to soil moisture variability. Notably, soil moisture variability induces circulation changes that differ from those resulting from prescribed soil moisture, leading to asymmetric responses. Moreover, the wave amplitudes over land are strengthened by approximately 24% from SME to SMI experiments (Fig. A4 ), which implies the key role of land-atmosphere coupling in modulating atmospheric wave dynamics. This has important implications, especially for certain amplified waves that trigger and maintain more extremes in the mid-latitudes. Declarations Acknowledgments. Fei Luo, Frank Selten, and Dim Coumou acknowledge a VIDI award from the Netherlands Organisation for Scientific Research (NWO) (project PERSIST: Persistent Summer Extremes, grant 016.Vidi.171.011). Data Availability Statement. The code and data can be made available by the first author upon reasonable request. Competing Interests. The contact author has declared that neither they nor their co-authors have any competing interests. Author Contribution All authors designed the research. F.L. performed the analysis and drafted the paper. All authors participated in manuscript editing. References Ali, S. Mubashshir, Olivia Martius, and Matthias Röthlisberger. 2021. “Recurrent Rossby Wave Packets Modulate the Persistence of Dry and Wet Spells Across the Globe.” Geophysical Research Letters 48 (5): e2020GL091452. https://doi.org/10.1029/2020GL091452 . Balsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H., … Vitart, F. (2015). “ERA-Interim/Land: a global land surface reanalysis data set. ” Hydrology and Earth System Sciences, 19 (1), 389–407. https://doi.org/10.5194/hess-19-389-2015 Capua, G. Di, S. Sparrow, K. Kornhuber, E. Rousi, S. Osprey, D. Wallom, B. van den Hurk, and D. Coumou. 2021. “Drivers behind the Summer 2010 Wave Train Leading to Russian Heatwave and Pakistan Flooding.” Npj Climate and Atmospheric Science 2021 4:1 4 (1): 1–14. https://doi.org/10.1038/s41612-021-00211-9 . Döscher, Ralf, Mario Acosta, Andrea Alessandri, Peter Anthoni, Almut Arneth, Thomas Arsouze, Tommi Bergmann, et al. 2021. “The EC-Earth3 Earth System Model for the Climate Model Intercomparison Project 6.” Geoscientific Model Development Discussions , no. February: 1–90. https://doi.org/10.5194/gmd-2020-446 . Fischer, E. M., S. I. Seneviratne, P. L. Vidale, D. Lüthi, and C. Schär. 2007. “Soil Moisture-Atmosphere Interactions during the 2003 European Summer Heat Wave.” Journal of Climate 20 (20): 5081–99. https://doi.org/10.1175/JCLI4288.1 . Gloege, L., Kornhuber, K., Skulovich, O., Pal, I., Zhou, S., Ciais, P., & Gentine, P. 2022. “Land-atmosphere cascade fueled the 2020 Siberian heatwave.” AGU Advances , 3 (6), https://doi.org/0.1029/2021AV000619. Haghighi, Erfan, Daniel J. Short Gianotti, Ruzbeh Akbar, Guido D. Salvucci, and Dara Entekhabi. 2018. “Soil and Atmospheric Controls on the Land Surface Energy Balance: A Generalized Framework for Distinguishing Moisture-limited and Energy‐limited Evaporation Regimes.” Water Resour. Res. 54 (3): 1831–51. https://doi.org/10.1002/2017wr021729 . Hsu, Hsin, and Paul A. Dirmeyer. 2023. “Soil Moisture-Evaporation Coupling Shifts into New Gears under Increasing CO2.” Nature Communications 2023 14:1 14 (1): 1–9. https://doi.org/10.1038/s41467-023-36794-5 . Hurrell, James W., James J. Hack, Dennis Shea, Julie M. Caron, and James Rosinski. 2008. “A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model.” Journal of Climate 21 (19): 5145–53. https://doi.org/10.1175/2008JCLI2292.1 . Kornhuber, Kai, Dim Coumou, Elisabeth Vogel, Corey Lesk, Jonathan F. Donges, Jascha Lehmann, and Radley M. Horton. 2020. “Amplified Rossby Waves Enhance Risk of Concurrent Heatwaves in Major Breadbasket Regions.” Nature Climate Change 10 (1): 48–53. https://doi.org/10.1038/s41558-019-0637-z . Koster, R. D., Chang, Y., Wang, H., & Schubert, S. D. 2016. Impacts of local soil moisture anomalies on the atmospheric circulation and on remote surface meteorological fields during boreal summer: A comprehensive analysis over North America. Journal of Climate, 29 (20), 7345–7364. https://doi.org/10.1175/JCLI-D-16-0192.1 Lorenz, Ruth, Eric B. Jaeger, and Sonia I. Seneviratne. 2010. “Persistence of Heat Waves and Its Link to Soil Moisture Memory.” Geophysical Research Letters 37 (9). https://doi.org/10.1029/2010GL042764 . Luo, Fei, Frank Selten, Kathrin Wehrli, Kai Kornhuber, Philippe Le Sager, Wilhelm May, Thomas Reerink, et al. 2022. “Summertime Rossby Waves in Climate Models: Substantial Biases in Surface Imprint Associated with Small Biases in Upper-Level Circulation.” Weather and Climate Dynamics 3 (3): 905–35. https://doi.org/10.5194/WCD-3-905-2022 . Mann, M, S. Rahmstorf, K. Kornhuber, Byron A. Steinman, S K Miller, S. Petri, and D. Coumou. 2018. “Projected Changes in Persistent Extreme Summer Weather Events: The Role of Quasi-Resonant Amplification.” Science Advances 4 (eaat3272): 1–9. https://doi-org.vu-nl.idm.oclc .org/10.1126/sciadv.aat3272 Martius, Olivia, Kathrin Wehrli, and Marco Rohrer. 2021. “Local and Remote Atmospheric Responses to Soil Moisture Anomalies in Australia.” Journal of Climate 34 (22): 9115–31. https://doi.org/10.1175/JCLI-D-21-0130.1 . Miralles, Diego G., Pierre Gentine, Sonia I. Seneviratne, and Adriaan J. Teuling. 2019. “Land–Atmospheric Feedbacks during Droughts and Heatwaves: State of the Science and Current Challenges.” Annals of the New York Academy of Sciences 1436 (1): 19–35. https://doi.org/10.1111/nyas.13912 . Miralles, Diego G., Adriaan J. Teuling, Chiel C. Van Heerwaarden, and Jordi Vilà Guerau De Arellano. 2014. “Mega-Heatwave Temperatures Due to Combined Soil Desiccation and Atmospheric Heat Accumulation.” Nature Geoscience 2014 7:5 7 (5): 345–49. https://doi.org/10.1038/NGEO2141 . Petoukhov, Vladimir, Stefan Rahmstorf, Stefan Petri, and Hans Joachim Schellnhuber. 2013. “Quasiresonant Amplification of Planetary Waves and Recent Northern Hemisphere Weather Extremes.” Proceedings of the National Academy of Sciences of the United States of America 110 (14): 5336–41. https://doi.org/10.1073/pnas.1222000110 . Rivière, G. 2011. “A dynamical interpretation of the poleward shift of the jet streams in global warming scenarios.” Journal of the Atmospheric Sciences, 68 (6), 1253–1272. https://doi.org/10.1175/2011JAS3641.1 Röthlisberger, Matthias, Stephan Pfahl, and Olivia Martius. 2016.“Regional-Scale Jet Waviness Modulates the Occurrence of Midlatitude Weather Extremes.” Geophysical Research Letters 43 (20), 10–989. https://doi.org/10.1002/2016GL070944 . Röthlisberger, Matthias, Linda Frossard, Lance F. Bosart, Daniel Keyser, and Olivia Martius. 2019. “Recurrent Synoptic-Scale Rossby Wave Patterns and Their Effect on the Persistence of Cold and Hot Spells.” Journal of Climate 32 (11): 3207–26. https://doi.org/10.1175/JCLI-D-18-0664.1 . Seneviratne, Sonia I., Thierry Corti, Edouard L. Davin, Martin Hirschi, Eric B. Jaeger, Irene Lehner, Boris Orlowsky, and Adriaan J. Teuling. 2010. “Investigating Soil Moisture-Climate Interactions in a Changing Climate: A Review.” Earth-Science Reviews. https://doi.org/10.1016/j.earscirev.2010.02.004 . Seneviratne, Sonia I., Daniel Lüthi, Michael Litschi, and Christoph Schär. 2006. “Land–Atmosphere Coupling and Climate Change in Europe.” Nature 2006 443:7108 443 (7108): 205–9. https://doi.org/10.1038/nature05095 . Shaw, T. A., Arblaster, J. M., Birner, T., Butler, A. H., Domeisen, D. I. V., Garfinkel, C. I., … & Karpechko, A. Y. 2024. Emerging climate change signals in atmospheric circulation. AGU Advances, 5 (6), https://doi.org/10.1029/2024AV001297 . Teng, H., Leung, R., Branstator, G., Lu, J., & Ding, Q. (2022). "Warming pattern over the Northern Hemisphere midlatitudes in boreal summer 1979–2020". Journal of Climate, 35 (11), 3479–3494. https://doi.org/10.1175/JCLI-D-21-0437.1 Teng, Haiyan, and Grant Branstator. 2019. “Amplification of Waveguide Teleconnections in the Boreal Summer.” Current Climate Change Reports 5 (4): 421–32. https://doi.org/10.1007/s40641-019-00150-x . Teng, Haiyan, Grant Branstator, Ahmed B. Tawfik, and Patrick Callaghan. 2019. “Circumglobal Response to Prescribed Soil Moisture over North America.” Journal of Climate 32 (14): 4525–45. https://doi.org/10.1175/JCLI-D-18-0823.1 . Wehrli, K., Luo, F., Hauser, M., Shiogama, H., Tokuda, D., Kim, H., … & Seneviratne, S. I. (2022). The ExtremeX global climate model experiment: investigating thermodynamic and dynamic processes contributing to weather and climate extremes. Earth System Dynamics, 1–31. https://doi.org/10.5194/esd-13-1167-2022 White, Rachel H., Kai Kornhuber, Olivia Martius, and Volkmar Wirth. 2022. “From Atmospheric Waves to Heatwaves: A Waveguide Perspective for Understanding and Predicting Concurrent, Persistent, and Extreme Extratropical Weather.” Bulletin of the American Meteorological Society 103 (3): E923–35. https://doi.org/10.1175/BAMS-D-21-0170.1 . Woollings, T., Drouard, M., O’Reilly, C. H., Sexton, D. M., & McSweeney, C. 2023. “Trends in the atmospheric jet streams are emerging in observations and could be linked to tropical warming. ”Communications Earth & Environment, 4 (1), 125. https://doi.org/10.1038/s43247-023-00792-8 Additional Declarations No competing interests reported. Supplementary Files Appendix.docx Cite Share Download PDF Status: Published Journal Publication published 06 Feb, 2026 Read the published version in npj Climate and Atmospheric Science → Version 1 posted Editorial decision: Revision requested 03 Jun, 2025 Reviews received at journal 01 Jun, 2025 Reviewers agreed at journal 27 May, 2025 Reviews received at journal 05 May, 2025 Reviewers agreed at journal 30 Apr, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers invited by journal 28 Apr, 2025 Editor assigned by journal 11 Apr, 2025 Submission checks completed at journal 11 Apr, 2025 First submitted to journal 10 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6420148","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":441895308,"identity":"d5c20f6c-fb2e-432c-bcee-4a34de4422a3","order_by":0,"name":"Fei Luo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAn0lEQVRIiWNgGAWjYBAC9gbGBoYHDAxyYN4DYrTwHABqSWBgMAbzEojTAlGZ2EC8FvbmBobENpv0DTcS2B4Qp4XnIEhLWi5QC7sBUVrsJRJBWg7nzpyRwCZBnC3yD8Fa0iWJ1yLBCNaSwC9BtBaexIYDCefSDPt5HrYRqYX9+MMHH8ps5NnYk49JfCBGCwgcgFBAF46CUTAKRsEooBIAACAkLwUftlIKAAAAAElFTkSuQmCC","orcid":"","institution":"Vrije Universiteit Amsterdam","correspondingAuthor":true,"prefix":"","firstName":"Fei","middleName":"","lastName":"Luo","suffix":""},{"id":441895309,"identity":"c1eb72ec-e4f4-47d5-b57b-6f2ce25ecf81","order_by":1,"name":"Frank Selten","email":"","orcid":"","institution":"Royal Netherlands Meteorological Institute","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"","lastName":"Selten","suffix":""},{"id":441895310,"identity":"4e4fe13e-7259-4673-9511-f6a173db29d3","order_by":2,"name":"Dim Coumou","email":"","orcid":"","institution":"Vrije Universiteit Amsterdam","correspondingAuthor":false,"prefix":"","firstName":"Dim","middleName":"","lastName":"Coumou","suffix":""}],"badges":[],"createdAt":"2025-04-10 12:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6420148/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6420148/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41612-025-01294-4","type":"published","date":"2026-02-06T15:59:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80721189,"identity":"927360f2-3f94-4765-946d-faec3b712add","added_by":"auto","created_at":"2025-04-16 11:01:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":209365,"visible":true,"origin":"","legend":"\u003cp\u003eDifference plots between SMI and SME surface thermodynamic variables for ensemble climatology means in July for simulated years 2009-2016: the left column is the SMI climatology mean, and the right column is the difference between SMI and SME.(a) to (b) near-surface temperature [k], (c) to (d) sensible heating [W m\u003csup\u003e-2\u003c/sup\u003e], (e) to (f) latent heating [W m\u003csup\u003e-2\u003c/sup\u003e], (g) to (h) net short-wave radiation [W m\u003csup\u003e-2\u003c/sup\u003e]. Stippled areas show significant (a = 0.01, two-sided) differences between SMI and SME climatology means obtained from 1000 bootstraps based on 800 ensemble monthly means.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6420148/v1/a2cb7399c4b6960f200a3c13.jpg"},{"id":80721192,"identity":"2677a06e-1d28-4d30-860a-ade5c20f4aeb","added_by":"auto","created_at":"2025-04-16 11:01:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":243243,"visible":true,"origin":"","legend":"\u003cp\u003eDifference plots between SMI and SME atmospheric dynamic variables for ensemble climatology means in July for simulated years 2009-2016: the left column is the SMI climatology means, and the right column is the difference between SMI and SME. \u0026nbsp;(a) to (b) azonal plots for geopotential height at 500 hPa [m], (c) to (d) meridional wind at 250 hPa [m s\u003csup\u003e-1\u003c/sup\u003e], (e) to (f) zonal wind at 250 hPa [m], (g) to (h) stream function at 250 hPa [m\u003csup\u003e2\u003c/sup\u003e s\u003csup\u003e-1\u003c/sup\u003e], (g) to (h) precipitation pr [mm]. Stippled areas show significant (a = 0.01, two-sided) differences between SMI and SME climatology means obtained from 1000 bootstraps based on 800 ensemble monthly means.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6420148/v1/e5887d6805c63e644de567e2.jpg"},{"id":80721190,"identity":"1dff6f10-a893-4cbd-9519-ceb738894321","added_by":"auto","created_at":"2025-04-16 11:01:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":269896,"visible":true,"origin":"","legend":"\u003cp\u003eDifference plots between SMF and SMC surface thermodynamic variables for ensemble climatology means in July for simulated years 2009-2016: the left column is the SMF climatology mean, and the right column is the difference between SMF and SMC.\u0026nbsp; (a) to (b) near-surface temperature [k], (c) to (d) soil moisture content (kg m\u003csup\u003e-2\u003c/sup\u003e), (e) to (f) sensible heating [W m\u003csup\u003e-2\u003c/sup\u003e], (g) to (h) latent heating [W m\u003csup\u003e-2\u003c/sup\u003e], (i) to (j) net short-wave radiation [W m\u003csup\u003e-2\u003c/sup\u003e]. Stippled areas show significant (a = 0.01, two-sided) differences between SMF and SMC climatology means obtained from 1000 bootstraps based on 800 ensemble monthly means.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6420148/v1/ba9f6ba4249c582a856e3615.jpg"},{"id":80722422,"identity":"dfedcf61-6da3-4be3-9361-ab94bbacafba","added_by":"auto","created_at":"2025-04-16 11:17:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":251949,"visible":true,"origin":"","legend":"\u003cp\u003eDifference plots between SMF and SMC atmospheric dynamic variables for ensemble climatology means in July for simulated years 2009-2016: the left column is the SMF climatology mean, and the right column is the difference between SMF and SMC. \u0026nbsp;(a) to (b) azonal plots for geopotential height at 500 hPa [m], (c) to (d) meridional wind at 250 hPa [m s\u003csup\u003e-1\u003c/sup\u003e], (e) to (f) zonal wind at 250 hPa [m], (g) to (h) stream function at 250 hPa [m\u003csup\u003e2\u003c/sup\u003e.s\u003csup\u003e-1\u003c/sup\u003e], (i) to (j) precipitation pr [mm]. Stippled areas show significant (a = 0.01, two-sided) differences between SMF and SMC climatology means obtained from 1000 bootstraps based on 800 ensemble monthly means.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6420148/v1/bc19a74fbff03ec063ea6c76.jpg"},{"id":80721193,"identity":"f8e2fd2f-d904-4a1d-b940-a53bc9759529","added_by":"auto","created_at":"2025-04-16 11:01:22","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":25623,"visible":true,"origin":"","legend":"\u003cp\u003eDifferent soil moisture and their corresponding evapotranspiration regimes and definitions. EF represents the evaporative fraction, and EF\u003csub\u003emax\u003c/sub\u003e is its maximal value. θ is the soil moisture content, \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003eWILT \u003c/em\u003e\u003c/sub\u003edenotes the wilting point, and \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003eCRIT \u003c/em\u003e\u003c/sub\u003edenotes the critical point, figure adapted from Seneviratne et al. (2010). \u0026nbsp;\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6420148/v1/8e3195441176a520dfea21f9.jpg"},{"id":102234992,"identity":"8b603932-cb86-4d0a-ae32-86243e2736e0","added_by":"auto","created_at":"2026-02-09 16:14:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1680814,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6420148/v1/30b6523a-d31f-400f-a578-2ffdfb221a0a.pdf"},{"id":80721218,"identity":"ef0958fb-40a1-4692-851b-618e99a5356a","added_by":"auto","created_at":"2025-04-16 11:01:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2579202,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-6420148/v1/8dd2ebfe8b066f40b61ff649.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The role of soil moisture on summer atmospheric circulation climatology in the Northern Hemisphere","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSoil moisture plays a vital role in the climate system. The exchange of water and heat between land and atmosphere depends on the amount of soil moisture. Soil moisture impacts the surface energy balance and the hydrological cycle by directly affecting evaporation. Two major feedback loops are described in the literature soil moisture and temperature and soil moisture and precipitation (Seneviratne et al. 2010). The soil moisture-temperature feedback works as follows. When the surface air temperature rises, more water evaporates from the soil, reducing the soil moisture content. At some point, a lack of soil moisture limits evaporation and the associated evaporative cooling. As a result, the ground heats, and the sensible heat flux increases, leading to higher surface air temperatures. Reduced evaporation and higher air temperatures lead to reduced cloud cover and enhanced solar radiation at the surface. This further amplifies the drying and the surface warming. The soil moisture-precipitation feedback works as follows. Precipitation increases soil moisture. Wetter soils lead to more evaporation and moistening of the planetary boundary layer, favouring cloud formation. More clouds lead to enhanced precipitation. The drying and wetting of the soil takes time and introduces a memory into the climate system. Therefore, knowledge of the soil moisture state can lead to skillful forecasts on sub-seasonal to seasonal time scales (Lorenz, Jaeger, and Seneviratne 2010).\u003c/p\u003e\n\u003cp\u003ePrevious studies have shown the significance of soil moisture in promoting and maintaining extreme events such as heat waves and droughts, both as local and remote drivers. Locally, there are various pathways in which dry soils trigger and amplify heat waves. These processes and mechanisms are mainly land-atmosphere coupling (Seneviratne et al. 2006; Miralles et al. 2014), evapotranspiration (Fischer et al. 2007), feedback mechanisms (Seneviratne et al. 2010), and surface energy balance (Lorenz, Jaeger, and Seneviratne 2010; Haghighi et al. 2018; Hsu and Dirmeyer 2023). Miralles et al. (2014) demonstrated that the mega-heatwave in Europe in 2003 and 2010 summers would not have been possible without the soil desiccation conditions, emphasizing the land-atmosphere coupling. When soil drying enhances the diurnal warm air entrainment, it accumulates atmospheric heat that lasts (Miralles et al. 2014). Usually, the evapotranspiration process from soil and plants regulates the land surface temperature as it has a cooling effect. However, when the soil moisture becomes limited, the evapotranspiration rate reduces, which induces heat wave conditions, if prolonged, even drought conditions (Miralles et al. 2019). Soil moisture temperature and soil moisture precipitation are two dominating feedback mechanisms; for soil moisture-temperature feedback, surface drying is induced by reduced soil moisture, enhancing surface heating during heat waves. The heated surface again dries the soil moisture below (Seneviratne et al. 2010). Various studies, including a generalized framework (Haghighi et al. 2018) and both regional (Lorenz, Jaeger, and Seneviratne 2010) and global climate models (Hsu and Dirmeyer 2023), show that the partitioning of land surface energy is strongly affected by soil moisture as it affects the balance between sensible and latent heat fluxes; the dry soil moisture contributes to increased sensible heat flux and, thus, persistent heat waves.\u003c/p\u003e\n\u003cp\u003eAdditionally, apart from the role of soil moisture in heat waves, circulation and atmospheric dynamics are indispensable. The recent ExtremeX global climate model experiment study from Wehrli et al. (2022), where the different multi-model experiments covered free atmospheric and land interaction, atmospheric nudging, and soil moisture prescription, showed the results from recent heatwave case studies demonstrated that atmospheric circulation patterns and soil moisture anomalies play key roles in extreme heat occurrences. While soil moisture effects are essential for the US Great Plains, tropics and monsoon regions, the circulation anomaly pattern overrides the rest of the extratropic and high latitudes areas.\u003c/p\u003e\n\u003cp\u003eFurthermore, a critical aspect of extreme events study is atmospheric dynamics. In middle latitudes, large-scale atmospheric circulation, namely jet streams, affects the day-to-day weather systems and governs the land surface conditions. Previous studies showed that high-amplitude quasi-stationary Rossby waves can trigger extreme events (Petoukhov et al. 2013; Mann et al. 2018; Teng and Branstator 2019). Both observational (reanalysis) and model studies have illustrated the importance of specific Rossby wave patterns, especially amplified circumglobal waves 5 and 7 in boreal summer, in promoting stagnating weather systems and, therefore, also responsible for global simultaneous extremes (Kornhuber et al. 2020; Luo et al. 2022). Regionally, the waviness of jets can impact the numbers and locations of weather extremes at mid-latitudes (R\u0026ouml;thlisberger, Pfahl, and Martius, 2016). A \u0026ldquo;recurrent synoptic-scale Rossby wave pattern\u0026rdquo; (RRWP) was identified based on reanalysis data that showed it to be responsible for persistent hot spells (R\u0026ouml;thlisberger et al. 2019). An overview of Waveguide theory and its association with surface extremes weather was summarised in a recent study (White et al. 2022).\u003c/p\u003e\n\u003cp\u003eLinking soil moisture to upper-level atmospheric circulation, a few studies have looked at the soil moisture-atmosphere interaction in one way: dry soils affect large-scale circulation in the Northern Hemisphere (Teng and Branstator 2019; Teng et al. 2019) and Southern Hemisphere (Ali, Martius, and R\u0026ouml;thlisberger 2021; Martius, Wehrli, and Rohrer 2021). For example, during mega heat waves, dry soils can influence local circulation (Miralles et al. 2014), and dry soil conditions can even affect remote circulation (Di Capua et al. 2021). Di Capua et al. (2021) showed that the dry soil moisture in western Russia enhances flood risks in Pakistan via a Rossby wave response. Gloege et al. (2022) also looked into spring but focused on the case study of the 2020 Siberian Heatwave.\u003c/p\u003e\n\u003cp\u003eThe study from Koster et al. (2016) supported the positive feedback loop idea that drying various interior regions in North America leads to atmospheric circulation changes that reinforce the heating on the continental interior. In their experiments, drying soil moisture simulations were performed with a stationary wave model (SWM) and an atmospheric general circulation model (AGCM). In the SWM experiments, the model was forced to use idealized diabatic heating at a few locations in the continental United States. Whereas in the AGCM experiments, soil moisture dryness was imposed in several places in the US interior. Despite the different models used and locations chosen, the atmospheric circulation anomaly shows similar patterns: a high-pressure anomaly in West-Central North America and a low-pressure anomaly to the east. The proposed potential positive feedback loop suggests that drying in soil moisture imposed in the US interior triggers a specific atmospheric circulation pattern which warms up the central US with increased surface sensible heating that reinforces the original atmospheric circulation anomalies (Koster et al., 2016). The need for large ensembles (96\u0026ndash;192) was also emphasized for detecting the spatial patterns of the induced stream function, precipitation, and 2-m temperature anomalies in their results.\u003c/p\u003e\n\u003cp\u003eIn this paper we build upon this earlier work and try to understand the role of soil-moisture-atmosphere interactions on the hemispheric-scale boreal summer circulation. We cover the analysis of the summer season, mainly using the month of July as an example to understand the soil moisture conditions and, hence, their implications for surface variables. Furthermore, we analyze jet stream patterns and planetary wave changes induced by different soil moisture experiments.\u003c/p\u003e\n\u003cp\u003eThis is the first study to examine the role of two-way soil moisture interaction between land and atmosphere on the climatological summer circulation employing large ensemble global climate model experiments.\u003c/p\u003e\n\u003cp\u003eThis paper aims to answer the following research questions:\u003c/p\u003e\n\u003cp\u003e- How does the two-way interaction between soil moisture and atmosphere dynamics influence the climatological mean state of the jet stream and planetary wave in boreal summer?\u003c/p\u003e\n\u003cp\u003e- What is the circulation\u0026rsquo;s response to variability in soil moisture?\u003c/p\u003e"},{"header":"2. Data and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 European Community Earth System Model version 3 (EC-Earth3)\u003c/h2\u003e \u003cp\u003eThe model output from the European Community Earth System Model (EC-Earth3) (D\u0026ouml;scher et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) is used in this study. The atmosphere component from EC-Earth is based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System IFS cycle cy36r4. There are 91 vertical model levels; the horizontal model resolution is T255 (ca. 80km). IFS also has a land component H-TESSEL land surface model (Balsamo et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) that consists of four soil layers: 0\u0026ndash;7, 7\u0026ndash;28, 28\u0026ndash;100, and 100\u0026ndash;255 cm. The monthly sea surface temperature and sea ice is prescribed in the model, where HadISST1 and NOAA OI2 data set were used (Hurrell et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). EC-Earth3 was run with model version 3.3.1 with CMIP6 scenario SSP3-7.0 for all the experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Experiment set-up\u003c/h2\u003e \u003cp\u003eThere are four sets of ensemble experiments included in this study. An overview of the experiments is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All experiments have the same prescribed SSTs, sea ice cover fraction, and land cover. They differ in atmospheric nudging, soil moisture climatology states, and soil moisture prescription. All the experiments consist of 100 ensemble members for the period of 2009 to 2016.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEC-Earth3 model Experiments description.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExperiment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnsemble\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eatmosphere and soil moisture interactive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eatmosphere interactive, EC-Earth ensemble climatological soil moisture prescribed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eatmosphere interactive and reanalyses soil moisture prescribed (6 hourly)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eatmosphere interactive and soil moisture climatology from reanalyses prescribed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Soil moisture data\u003c/h2\u003e \u003cp\u003eAll four soil layers were prescribed for SME, SMF, and SMC experiments. The experiments prescribe three sets of soil moisture: ERA-Land (Balsamo et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) prescribed on a 6-hrly timescale, ERA-Land climatology soil moisture that is calculated, and the soil moisture ensemble mean climatology from SMI runs.\u003c/p\u003e \u003cp\u003eThe soil moisture ensemble mean climatology (Fig. \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003eA1\u003c/span\u003e) is the prescribed soil moisture for SME simulations. It was calculated based on all the 100 SMI ensemble member soil moisture values. First, the median ensemble soil moisture values were computed, then a 15-day running mean process was carried out, followed by a multi-year (2009\u0026ndash;2016) daily mean calculation. Soil moisture standard deviation plots for SMI and SMF were calculated based on the data described in Table.1 (Fig. \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003eA2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor SMF experiments, the ERA-Land soil moisture was prescribed every six hours from 2009 to 2016.\u003c/p\u003e \u003cp\u003eERA-Land soil moisture climatology for SMC experiments was computed from the ERA_land daily soil moisture data from 1982\u0026ndash;2008. The median value of that day in a year (1982\u0026ndash;2008) was first calculated, and then a 15-day running mean was applied. Since the model outputs 6-hourly timescale, the same soil moisture climatology data was prescribed four times daily.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Summer season month July climatology plots\u003c/h2\u003e \u003cp\u003eClimatology plots are computed as the ensemble monthly mean from 100 ensemble members from 2009 to 2016 and month July. All the ensemble members were initially outputted on six hourly time scale, then climatological means are calculated based on these data to monthly means. We restrict our study domain from 20S to 90N and 180W to 180E to cover the Northern Hemisphere and Southern tropics.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Jet stream response to Soil Moisture-Atmosphere interaction\u003c/h2\u003e \u003cp\u003eFirst, we focus on the question of whether the two-way interaction between soil moisture and the atmosphere influences the climatological state of the jet streams. To do so, we compare the July climatology of the experiment with interactive soil moisture (SMI) and without (SME). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the climatology for thermodynamic variables for SMI in the left column. The impact of interactive soil moisture is in the right column, as it is the difference in the climatology between SMI and SME. Dynamical variables are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Stippled areas outline the regions where the difference is significant at 99% confidence (determined from bootstrapping 1000 times of random samples from 800 July months).\u003c/p\u003e \u003cp\u003eThe mean surface air temperature is generally much higher with interactive soil moisture (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Largest impact (0.5\u0026ndash;1.5 k) occurs in E. Siberia, Russia, Europe, and central to East North America. In these areas, we see enhanced net short-wave radiation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (h)) and increased stream function values at 250 hPa (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (h)). These changes suggest that in these areas, on average soil moisture more often limits evaporation in SMI, leading to reduced evaporative cooling of the surface, increased surface temperature and sensible heat flux, fewer clouds, more solar radiation and a warmer air column beneath 250 hPa leading to the positive stream function anomalies aloft. The increase in solar radiation is larger than the reduction in evaporative cooling and increase in sensible heat flux (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (d)). In the areas of increased radiation, we find significantly reduced precipitation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (j)) .\u003c/p\u003e \u003cp\u003eThe mean position and strength of the jet streams are affected by interactive soil moisture. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (e) and (f)). Over North America and Eurasia the jet stream is weaker and slightly northward shifted with interactive soil moisture. The polar front jet above the northern coast of Eurasia is enhanced and above the North-Atlantic there is a clear northward shift of the jet stream leading to a more south-west to north-east tilting of the jet stream. Also the stationary waves are affected. A circumglobal wave response is visible in the meridional wind response at 250 hPa as well as in the azonal part of geopotential height at 500 hPa (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (b) and (d)). The positive geopotential height changes match as expected the positive streamfunction changes over Canada, East Europe, and Northeast Asia. The stationary wave response has a clear circumglobal wave number 5 signature.\u003c/p\u003e \u003cp\u003eThe monsoon is strengthened in SMI runs as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (j). There is more precipitation in Indian monsoon belt regions in SMI than in SME runs. This corresponds well with the more latent heating fluxes in SMI (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (f)).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Jet stream response to prescribed soil moisture variability\u003c/h2\u003e \u003cp\u003eFurthermore, since both SMF and SMC are from the same soil moisture dataset, ERA-Land, and none have two-way land-atmosphere interaction, comparing these two experiments will shed light on the variability in soil moisture implying for the atmosphere. In SMF, the day-to-day soil moisture variability is the same as in ERA-Land. In contrast, in SMC, the variability is gone because of the prescription of soil moisture climatology. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the surface thermodynamic variables fields for both climatology from SMF (left column) and the differences between SMF and SMC ensemble mean climatology (right column). Although with the same soil moisture climatology prescribed, SMF exhibits warmer near-surface temperatures than SMC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (b)). For the land region, SMF is warmer than SMC everywhere except for a region in the Sahara. The hotspots for strong temperature warm anomalies can be seen in the central U.S., Russia, East Siberia, and North East China. Those regions show negative anomalies in latent heating and positive anomalies in sensible heating in SMF experiments compared to SMC. This implies that in those regions, the observed variability in soil moisture leads to land warming due to increased sensible heating and decreased latent heating.\u003c/p\u003e \u003cp\u003eThe soil moisture differences plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (d)) pinpoints in Central America, SMF is dryer than SMC, which relates to the high sensible heating (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (f)) and low latent heating (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (h)) fluxes of SMF compared to SMC experiments. As for precipitation patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (j)), at the exact location in Central America, SMF precipates less than SMC.\u003c/p\u003e \u003cp\u003eA jet shift is observed as well (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (e) and (f)) between SMF and SMC experiments. The differences plots for both 500 hPa azonal geopotential heights and 250 hPa meridional winds (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (b) and (d)) show a circumglobal wave pattern in the northern hemisphere mid-latitudes. The most pronounced patterns can be seen over North America. This differs from the results of the SMI and SME experiments, where the anomalous patterns are more evident over the Eurasian continent for meridional winds, and the azonal geopotential heights shift northward. Anomalies in stream function at 250 hPa (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (h)) also overlapped with geopotential heights (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (b)) in Central America and North East China.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Differences in Jet stream response to two-way Interaction and soil moisture variability\u003c/h2\u003e \u003cp\u003eBy comparing the two sets of experiments: SMI and SME vs. SMF and SMC. As the soil moisture climatology means, the state is kept the same between SMI and SME, as well as SMF and SMC. We suspect the responses from the atmospheric circulations come from land-atmosphere interaction and soil moisture variability. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (b) and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (b) show that the positions of the jets are different in these two sets of experiments. In the SMI-SME set, azonal geopotential height anomalies position more poleward, and the centers of each hot spot are around 70N. Thus, with interactive soil moisture, the quasi-stationary planetary wave is positioned more northwards, together with a northward shift of the jet stream. Whereas in the SMF-SMC set, they are centred around 50N. Additionally, the wave response in SMI-SME is located primarily over Eurasia (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (d)), whereas it is most pronounced over North America in the SMF-SMC set (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (d)).\u003c/p\u003e \u003cp\u003eThe stream function difference plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (h) and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (h)) show different locations for anomalous hotspots in North America. In the SMI-SME set, the core is in North Canada, whereas in the SMF-SMC set, it is more in Central America.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussions","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Land-atmosphere two-way interaction induces circulation changes\u003c/h2\u003e \u003cp\u003eIn our study, we compared the July ensemble climatological mean fields for surface thermodynamically controlled variables and variables of the upper-level atmospheric circulation between large-ensemble simulations with different soil moisture and land-atmosphere interactions. Interestingly, panel Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (b) patterns identified similar regions that have seen the strongest warming over recent decades by the study of Coumou et al. (2018) in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea to c, suggesting a potential role of soil moisture in amplifying the warming trends. Additionally, the observed linear trend from 1979 to 2020 for near-surface temperature anomalies during JJA seasonal mean during selected extreme events (Teng et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) also coincides with our hotspots in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(b) such as E. Siberia, Russia, Europe, and Northern Canada.\u003c/p\u003e \u003cp\u003eWhen two-way land-atmosphere interaction is turned on (e.g. SMI versus SME), we observe a poleward migration of jet and a more pronounced Arctic font jet state. Additionally, we found an anomalous wave 5 circumglobal wave pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (b, d. This implies that the two-way dynamic interaction between land (soil moisture) and atmosphere affects the position and waves in the jet stream. This anomalous circumglobal wave 5 patterns and/or its resemblance is associated with surface heat extremes were also found in a recent study by Teng et. Al (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Overall, the SMI experiments are warmer than SME runs, suggesting the two-way interaction also introduces more potential extreme events (Fig. \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003eA3\u003c/span\u003e). From the 90th-percentile of near-surface temperature comparisons between SMI and SME,\u003c/p\u003e \u003cp\u003eA possible explanation of the observed northward jet shift could be that the atmospheric response to local surface energy fluxes changes is not always in situ, as changes in soil moisture conditions locally induce both local and remote changes in forcings. As the soil dries out, initially, latent heating is reduced, and sensible heating is increased, but later, the atmosphere starts to respond. There will be cloud formation and precipitation processes, then divergence in the air and thus wind changes. As a result, the jets shift their positions. The persistent anomalies in soil moisture can also act as forcing for Circumglobal Wave Trains (CGWTs), specifically amplifying the wave 5 pattern in the mid-latitudes. This results from the influence of soil moisture on surface heat flux, which further modulates atmospheric baroclinicity and wave activity (Teng et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA few other studies have highlighted the emerging climate signals, based on decades of reanalysis data and modelling data, such as the poleward shift of jet streams in the Northern Hemisphere and attributed that to global warming-induced changes in atmospheric circulation, notably enhanced upper-tropospheric baroclinicity and alterations in stratospheric winds that impact tropospheric eddies and momentum flux (Rivi\u0026egrave;re, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Woollings et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shaw et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Asymmetrical response from soil moisture prescription\u003c/h2\u003e \u003cp\u003eOne special experimental set-up of our soil moisture prescription experiments is that the soil moisture prescription is applied at every grid point, every soil level, and every time step. This separates our simulations from previous studies which used location-specific soil moisture prescription experiments (Koster et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Teng et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our analyses thereby shed light on the global effect of soil moisture \u0026ndash; atmosphere interactions on large-scale circulation but also make it more challenging to interpret in terms of physics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFrom our analysis, the response from drying vs. wetting soil moisture is asymmetric. This is due to the effect of soil moisture depletion on near-surface temperature (Seneviratne et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) since as long as there is water in the soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e wet regime), it is an energy-limited regime, and sensible heat fluxes would be small. However, warming has more effect when the soil water content is entirely evaporated in SMF runs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e dry regime).\u003c/p\u003e \u003cp\u003eThis soil moisture asymmetry effect is especially at play for regions where soil moisture is a global limiting factor. Such as the borders of deserts and dry regions. Thus, the soil moisture drying effect is more pronounced because there is almost always soil moisture as its soil moisture climatology. However, for SMF, there could be locations where the soil is arid; thus, it cannot give feedback on the atmosphere above. Thus, one must consider this asymmetrical effect when studying soil moisture and its relationship to surface energy balance and fluxes and the influence on upper atmospheric level jets.\u003c/p\u003e \u003cp\u003eIn our results, for instance, in SMC, the soil moisture is not so dry since its soil moisture climatology values, where the dry years would be compensated by wet years. When there is dry soil moisture in SMF (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (d)), take Northeast China as an example; the climatology of warmer near-surface temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (b)), high sensible heating (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (f)) and low latent heating (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (h)) in SMF are also reflected in the exact location. As the surface temperature warms up, there is high pressure, which means it is a clear sky, and evaporation will reduce. Furthermore, reduced soil moisture will, in turn, limit the evaporation from the surface, causing the near-surface temperature to be hotter than the climatology temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (b)).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Differences between two sets of experiments\u003c/h2\u003e \u003cp\u003eAs described in previous section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e, there are a few differences between the SMI-SME and SMF-SMC sets. The most obvious one is the poleward shifts of the jets in SMI-SME (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (d)) compared to SMF-SMC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (d)). It could be linked to the variability in soil moisture states (Fig. \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003eA2\u003c/span\u003e). If the variability (standard deviations) of soil moisture is high, the soil moisture could have more influence on the atmosphere above via energy exchanges. However, if the variability is small, assume a region that is always wet or dry. Take the Sahara as an example; the influences of soil moisture variability on the atmosphere will be small. Fig. \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003eA1\u003c/span\u003e shows more variability in soil moisture in SMI in mid to high latitudes in the Northern Hemisphere. This is where the jets are presented in the atmosphere above.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Limitations and Outlook\u003c/h2\u003e \u003cp\u003eOne strength in our approach and results, which echoed the study from Koster et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), is that the large ensemble number simulations (in our case 100, and theirs 96\u0026ndash;192) were carried out for detecting some specific spatial anomalous patterns in anomalous atmospheric circulation and near-surface temperature. However, at the same time, we have only conducted experiments with EC-Earth3; more models can be added to make more confident and general statements. Although the large ensemble size could compensate for the lack of model diversity, results may be model-dependent, as they ultimately depend on how accurately the model represents land-atmosphere interaction, surface fluxes, and soil moisture.\u003c/p\u003e \u003cp\u003eIn our study, we compared the large ensemble simulations\u0026rsquo; climatological means for various variables. This allowed us to capture the signal of circulation change induced by land-atmosphere interaction. Despite the overall robustness of our results, we still lack confidence in explaining the physical process in detail. The changes we observe are a combination of local and remote effects, which is also outside this study\u0026rsquo;s scope.\u003c/p\u003e \u003cp\u003eFuture work can be done on the amplified circumglobal wave characters and associated extreme events. It is also possible to check the early spring soil moisture conditions in each experiment set and the corresponding summer extreme heat events to analyze the seasonal predictability of summer heat waves based on the information on early spring soil moisture conditions. Another aspect is further research on the role of land-atmosphere interactions for extremes, tails of the distribution of the extremes rather than focusing on the mean states.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Concluding Remarks","content":"\u003cp\u003eOur results show that the two-way interaction between land and atmosphere is critical in driving circulation changes, such as poleward shifts and strengthening of jet stream patterns. This land-atmosphere interaction amplifies the potential for extreme events, as shown by the 90th percentile temperature anomalies increase when SME is compared to SMI (Fig. \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003eA3\u003c/span\u003e). Comparisons between soil moisture experiments reveal that SMI and SMF scenarios exhibit warmer conditions than SME and SMC experiments, also highlighting the sensitivity of temperature patterns to soil moisture variability. Notably, soil moisture variability induces circulation changes that differ from those resulting from prescribed soil moisture, leading to asymmetric responses. Moreover, the wave amplitudes over land are strengthened by approximately 24% from SME to SMI experiments (Fig. \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003eA4\u003c/span\u003e), which implies the key role of land-atmosphere coupling in modulating atmospheric wave dynamics. This has important implications, especially for certain amplified waves that trigger and maintain more extremes in the mid-latitudes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments.\u003c/p\u003e\n\u003cp\u003eFei Luo, Frank Selten, and Dim Coumou acknowledge a VIDI award from the Netherlands Organisation for Scientific Research (NWO) (project PERSIST: Persistent Summer Extremes, grant 016.Vidi.171.011).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData Availability Statement.\u003c/p\u003e\n\u003cp\u003eThe code and data can be made available by the first author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting Interests.\u003c/p\u003e\n\u003cp\u003eThe contact author has declared that neither they nor their co-authors have any competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors designed the research. F.L. performed the analysis and drafted the paper. All authors participated in manuscript editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAli, S. Mubashshir, Olivia Martius, and Matthias R\u0026ouml;thlisberger. 2021. \u0026ldquo;Recurrent Rossby Wave Packets Modulate the Persistence of Dry and Wet Spells Across the Globe.\u0026rdquo; Geophysical Research Letters 48 (5): e2020GL091452. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1029/2020GL091452\u003c/span\u003e\u003cspan address=\"10.1029/2020GL091452\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H., \u0026hellip; Vitart, F. (2015). \u0026ldquo;ERA-Interim/Land: a global land surface reanalysis data set. \u0026rdquo; Hydrology and Earth System Sciences, \u003cem\u003e19\u003c/em\u003e(1), 389\u0026ndash;407. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/hess-19-389-2015\u003c/span\u003e\u003cspan address=\"10.5194/hess-19-389-2015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCapua, G. Di, S. Sparrow, K. Kornhuber, E. Rousi, S. Osprey, D. Wallom, B. van den Hurk, and D. Coumou. 2021. \u0026ldquo;Drivers behind the Summer 2010 Wave Train Leading to Russian Heatwave and Pakistan Flooding.\u0026rdquo; \u003cem\u003eNpj Climate and Atmospheric Science 2021 4:1\u003c/em\u003e 4 (1): 1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41612-021-00211-9\u003c/span\u003e\u003cspan address=\"10.1038/s41612-021-00211-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD\u0026ouml;scher, Ralf, Mario Acosta, Andrea Alessandri, Peter Anthoni, Almut Arneth, Thomas Arsouze, Tommi Bergmann, et al. 2021. \u0026ldquo;The EC-Earth3 Earth System Model for the Climate Model Intercomparison Project 6.\u0026rdquo; \u003cem\u003eGeoscientific Model Development Discussions\u003c/em\u003e, no. February: 1\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/gmd-2020-446\u003c/span\u003e\u003cspan address=\"10.5194/gmd-2020-446\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFischer, E. M., S. I. Seneviratne, P. L. Vidale, D. L\u0026uuml;thi, and C. Sch\u0026auml;r. 2007. \u0026ldquo;Soil Moisture-Atmosphere Interactions during the 2003 European Summer Heat Wave.\u0026rdquo; Journal of Climate 20 (20): 5081\u0026ndash;99. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/JCLI4288.1\u003c/span\u003e\u003cspan address=\"10.1175/JCLI4288.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGloege, L., Kornhuber, K., Skulovich, O., Pal, I., Zhou, S., Ciais, P., \u0026amp; Gentine, P. 2022. \u0026ldquo;Land-atmosphere cascade fueled the 2020 Siberian heatwave.\u0026rdquo; \u003cem\u003eAGU Advances\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(6), https://doi.org/0.1029/2021AV000619.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaghighi, Erfan, Daniel J. Short Gianotti, Ruzbeh Akbar, Guido D. Salvucci, and Dara Entekhabi. 2018. \u0026ldquo;Soil and Atmospheric Controls on the Land Surface Energy Balance: A Generalized Framework for Distinguishing Moisture-limited and Energy‐limited Evaporation Regimes.\u0026rdquo; Water Resour. Res. 54 (3): 1831\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/2017wr021729\u003c/span\u003e\u003cspan address=\"10.1002/2017wr021729\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsu, Hsin, and Paul A. Dirmeyer. 2023. \u0026ldquo;Soil Moisture-Evaporation Coupling Shifts into New Gears under Increasing CO2.\u0026rdquo; \u003cem\u003eNature Communications 2023 14:1\u003c/em\u003e 14 (1): 1\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41467-023-36794-5\u003c/span\u003e\u003cspan address=\"10.1038/s41467-023-36794-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHurrell, James W., James J. Hack, Dennis Shea, Julie M. Caron, and James Rosinski. 2008. \u0026ldquo;A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model.\u0026rdquo; Journal of Climate 21 (19): 5145\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/2008JCLI2292.1\u003c/span\u003e\u003cspan address=\"10.1175/2008JCLI2292.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKornhuber, Kai, Dim Coumou, Elisabeth Vogel, Corey Lesk, Jonathan F. Donges, Jascha Lehmann, and Radley M. Horton. 2020. \u0026ldquo;Amplified Rossby Waves Enhance Risk of Concurrent Heatwaves in Major Breadbasket Regions.\u0026rdquo; Nature Climate Change 10 (1): 48\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41558-019-0637-z\u003c/span\u003e\u003cspan address=\"10.1038/s41558-019-0637-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoster, R. D., Chang, Y., Wang, H., \u0026amp; Schubert, S. D. 2016. Impacts of local soil moisture anomalies on the atmospheric circulation and on remote surface meteorological fields during boreal summer: A comprehensive analysis over North America. Journal of Climate, \u003cem\u003e29\u003c/em\u003e(20), 7345\u0026ndash;7364. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/JCLI-D-16-0192.1\u003c/span\u003e\u003cspan address=\"10.1175/JCLI-D-16-0192.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLorenz, Ruth, Eric B. Jaeger, and Sonia I. Seneviratne. 2010. \u0026ldquo;Persistence of Heat Waves and Its Link to Soil Moisture Memory.\u0026rdquo; Geophysical Research Letters 37 (9). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1029/2010GL042764\u003c/span\u003e\u003cspan address=\"10.1029/2010GL042764\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo, Fei, Frank Selten, Kathrin Wehrli, Kai Kornhuber, Philippe Le Sager, Wilhelm May, Thomas Reerink, et al. 2022. \u0026ldquo;Summertime Rossby Waves in Climate Models: Substantial Biases in Surface Imprint Associated with Small Biases in Upper-Level Circulation.\u0026rdquo; Weather and Climate Dynamics 3 (3): 905\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/WCD-3-905-2022\u003c/span\u003e\u003cspan address=\"10.5194/WCD-3-905-2022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMann, M, S. Rahmstorf, K. Kornhuber, Byron A. Steinman, S K Miller, S. Petri, and D. Coumou. 2018. \u0026ldquo;Projected Changes in Persistent Extreme Summer Weather Events: The Role of Quasi-Resonant Amplification.\u0026rdquo; Science Advances 4 (eaat3272): 1\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi-org.vu-nl.idm.oclc\u003c/span\u003e\u003cspan address=\"https://doi-org.vu-nl.idm.oclc\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e.org/10.1126/sciadv.aat3272\u003c/span\u003e\u003cspan address=\".10.1126/sciadv.aat3272\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartius, Olivia, Kathrin Wehrli, and Marco Rohrer. 2021. \u0026ldquo;Local and Remote Atmospheric Responses to Soil Moisture Anomalies in Australia.\u0026rdquo; Journal of Climate 34 (22): 9115\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/JCLI-D-21-0130.1\u003c/span\u003e\u003cspan address=\"10.1175/JCLI-D-21-0130.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiralles, Diego G., Pierre Gentine, Sonia I. Seneviratne, and Adriaan J. Teuling. 2019. \u0026ldquo;Land\u0026ndash;Atmospheric Feedbacks during Droughts and Heatwaves: State of the Science and Current Challenges.\u0026rdquo; Annals of the New York Academy of Sciences 1436 (1): 19\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/nyas.13912\u003c/span\u003e\u003cspan address=\"10.1111/nyas.13912\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiralles, Diego G., Adriaan J. Teuling, Chiel C. Van Heerwaarden, and Jordi Vil\u0026agrave; Guerau De Arellano. 2014. \u0026ldquo;Mega-Heatwave Temperatures Due to Combined Soil Desiccation and Atmospheric Heat Accumulation.\u0026rdquo; \u003cem\u003eNature Geoscience 2014 7:5\u003c/em\u003e 7 (5): 345\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/NGEO2141\u003c/span\u003e\u003cspan address=\"10.1038/NGEO2141\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetoukhov, Vladimir, Stefan Rahmstorf, Stefan Petri, and Hans Joachim Schellnhuber. 2013. \u0026ldquo;Quasiresonant Amplification of Planetary Waves and Recent Northern Hemisphere Weather Extremes.\u0026rdquo; Proceedings of the National Academy of Sciences of the United States of America 110 (14): 5336\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1222000110\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1222000110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRivi\u0026egrave;re, G. 2011. \u0026ldquo;A dynamical interpretation of the poleward shift of the jet streams in global warming scenarios.\u0026rdquo; Journal of the Atmospheric Sciences, \u003cem\u003e68\u003c/em\u003e(6), 1253\u0026ndash;1272. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/2011JAS3641.1\u003c/span\u003e\u003cspan address=\"10.1175/2011JAS3641.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR\u0026ouml;thlisberger, Matthias, Stephan Pfahl, and Olivia Martius. 2016.\u0026ldquo;Regional-Scale Jet Waviness Modulates the Occurrence of Midlatitude Weather Extremes.\u0026rdquo; Geophysical Research Letters \u003cem\u003e43\u003c/em\u003e(20), 10\u0026ndash;989. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/2016GL070944\u003c/span\u003e\u003cspan address=\"10.1002/2016GL070944\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR\u0026ouml;thlisberger, Matthias, Linda Frossard, Lance F. Bosart, Daniel Keyser, and Olivia Martius. 2019. \u0026ldquo;Recurrent Synoptic-Scale Rossby Wave Patterns and Their Effect on the Persistence of Cold and Hot Spells.\u0026rdquo; Journal of Climate 32 (11): 3207\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/JCLI-D-18-0664.1\u003c/span\u003e\u003cspan address=\"10.1175/JCLI-D-18-0664.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeneviratne, Sonia I., Thierry Corti, Edouard L. Davin, Martin Hirschi, Eric B. Jaeger, Irene Lehner, Boris Orlowsky, and Adriaan J. Teuling. 2010. \u0026ldquo;Investigating Soil Moisture-Climate Interactions in a Changing Climate: A Review.\u0026rdquo; Earth-Science Reviews. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.earscirev.2010.02.004\u003c/span\u003e\u003cspan address=\"10.1016/j.earscirev.2010.02.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeneviratne, Sonia I., Daniel L\u0026uuml;thi, Michael Litschi, and Christoph Sch\u0026auml;r. 2006. \u0026ldquo;Land\u0026ndash;Atmosphere Coupling and Climate Change in Europe.\u0026rdquo; \u003cem\u003eNature 2006 443:7108\u003c/em\u003e 443 (7108): 205\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nature05095\u003c/span\u003e\u003cspan address=\"10.1038/nature05095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaw, T. A., Arblaster, J. M., Birner, T., Butler, A. H., Domeisen, D. I. V., Garfinkel, C. I., \u0026hellip; \u0026amp; Karpechko, A. Y. 2024. Emerging climate change signals in atmospheric circulation. AGU Advances, \u003cem\u003e5\u003c/em\u003e(6), \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1029/2024AV001297\u003c/span\u003e\u003cspan address=\"10.1029/2024AV001297\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeng, H., Leung, R., Branstator, G., Lu, J., \u0026amp; Ding, Q. (2022). \"Warming pattern over the Northern Hemisphere midlatitudes in boreal summer 1979\u0026ndash;2020\". Journal of Climate, \u003cem\u003e35\u003c/em\u003e(11), 3479\u0026ndash;3494. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/JCLI-D-21-0437.1\u003c/span\u003e\u003cspan address=\"10.1175/JCLI-D-21-0437.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeng, Haiyan, and Grant Branstator. 2019. \u0026ldquo;Amplification of Waveguide Teleconnections in the Boreal Summer.\u0026rdquo; Current Climate Change Reports 5 (4): 421\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40641-019-00150-x\u003c/span\u003e\u003cspan address=\"10.1007/s40641-019-00150-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeng, Haiyan, Grant Branstator, Ahmed B. Tawfik, and Patrick Callaghan. 2019. \u0026ldquo;Circumglobal Response to Prescribed Soil Moisture over North America.\u0026rdquo; Journal of Climate 32 (14): 4525\u0026ndash;45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/JCLI-D-18-0823.1\u003c/span\u003e\u003cspan address=\"10.1175/JCLI-D-18-0823.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWehrli, K., Luo, F., Hauser, M., Shiogama, H., Tokuda, D., Kim, H., \u0026hellip; \u0026amp; Seneviratne, S. I. (2022). The ExtremeX global climate model experiment: investigating thermodynamic and dynamic processes contributing to weather and climate extremes. Earth System Dynamics, 1\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/esd-13-1167-2022\u003c/span\u003e\u003cspan address=\"10.5194/esd-13-1167-2022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhite, Rachel H., Kai Kornhuber, Olivia Martius, and Volkmar Wirth. 2022. \u0026ldquo;From Atmospheric Waves to Heatwaves: A Waveguide Perspective for Understanding and Predicting Concurrent, Persistent, and Extreme Extratropical Weather.\u0026rdquo; Bulletin of the American Meteorological Society 103 (3): E923\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/BAMS-D-21-0170.1\u003c/span\u003e\u003cspan address=\"10.1175/BAMS-D-21-0170.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoollings, T., Drouard, M., O\u0026rsquo;Reilly, C. H., Sexton, D. M., \u0026amp; McSweeney, C. 2023. \u0026ldquo;Trends in the atmospheric jet streams are emerging in observations and could be linked to tropical warming. \u0026rdquo;Communications Earth \u0026amp; Environment, \u003cem\u003e4\u003c/em\u003e(1), 125. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s43247-023-00792-8\u003c/span\u003e\u003cspan address=\"10.1038/s43247-023-00792-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-climate-and-atmospheric-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjclimatsci","sideBox":"Learn more about [npj Climate and Atmospheric Science](http://www.nature.com/npjclimatsci/)","snPcode":"41612","submissionUrl":"https://submission.springernature.com/new-submission/41612/3","title":"npj Climate and Atmospheric Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6420148/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6420148/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSoil moisture\u0026ndash;atmosphere interactions intensify extremes like heat waves and droughts. Atmospheric circulation and soil moisture are key drivers for both local and remote extreme events via dynamical and thermodynamical mechanisms. Understanding the interaction between soil moisture and atmosphere dynamics, including potential feedback loops, is crucial for both climate attribution studies and sub-seasonal to seasonal forecasts. Here, we study the effect of soil moisture on large-scale atmospheric circulation using large ensemble simulations from the fully coupled climate model EC-Earth 3 from 2009 to 2016. The atmosphere evolves freely in all the experiments. Four sets of experiments are carried out with one control run in which the interaction between the atmosphere and the land is fully interactive. In contrast, in the other three experiments soil moisture is prescribed. The main finding of this study is that soil moisture impacts the climatological mean state of the atmospheric circulation in the Northern Hemisphere during the summer season (June to August) and especially in July.\u003c/p\u003e \u003cp\u003eSpecifically, we observe poleward shifts of subtropical jets and a stronger polar front jet in the experiment with the prescribed soil moisture climatology of the control experiment with interactive soil moisture. Additionally, by allowing the two-way interaction between land and atmosphere (control experiment), the wave amplitudes over land are strengthened by approximately 24% (compared to soil moisture prescribed), which implies the key role of land-atmosphere coupling in modulating atmospheric wave dynamics. The Stationary wave patterns over North America are triggered in the experiment with prescribed climatological soil moisture of the ERA land reanalysis. In addition, we find that interactive soil moisture leads to higher mean summer surface temperatures for most land areas up to +\u0026thinsp;1.5 k and even higher (+\u0026thinsp;3 k) for temperature extremes (90th near-surface daily temperature). We conclude that soil moisture impacts the atmospheric circulation. Therefore, we expect circulation changes triggered by drying soils in large areas of the summer continents in projections of our future climate.\u003c/p\u003e","manuscriptTitle":"The role of soil moisture on summer atmospheric circulation climatology in the Northern Hemisphere","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-16 11:01:17","doi":"10.21203/rs.3.rs-6420148/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-04T00:40:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-02T01:09:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150214368673610102247970566152596554276","date":"2025-05-27T08:15:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-06T02:30:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39940756159362632659547836306513038910","date":"2025-05-01T03:20:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306563210000320342067352762506534172800","date":"2025-04-29T00:13:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-29T00:00:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-12T01:40:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-11T17:59:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Climate and Atmospheric Science","date":"2025-04-10T12:21:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-climate-and-atmospheric-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjclimatsci","sideBox":"Learn more about [npj Climate and Atmospheric Science](http://www.nature.com/npjclimatsci/)","snPcode":"41612","submissionUrl":"https://submission.springernature.com/new-submission/41612/3","title":"npj Climate and Atmospheric Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8be95bcf-4913-421f-8c56-a9c9f8759f98","owner":[],"postedDate":"April 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47055299,"name":"Earth and environmental sciences/Climate sciences/Atmospheric science/Atmospheric dynamics"},{"id":47055300,"name":"Earth and environmental sciences/Climate sciences"},{"id":47055301,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate and earth system modelling"}],"tags":[],"updatedAt":"2026-02-09T16:09:30+00:00","versionOfRecord":{"articleIdentity":"rs-6420148","link":"https://doi.org/10.1038/s41612-025-01294-4","journal":{"identity":"npj-climate-and-atmospheric-science","isVorOnly":false,"title":"npj Climate and Atmospheric Science"},"publishedOn":"2026-02-06 15:59:55","publishedOnDateReadable":"February 6th, 2026"},"versionCreatedAt":"2025-04-16 11:01:17","video":"","vorDoi":"10.1038/s41612-025-01294-4","vorDoiUrl":"https://doi.org/10.1038/s41612-025-01294-4","workflowStages":[]},"version":"v1","identity":"rs-6420148","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6420148","identity":"rs-6420148","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}