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Eastern China experienced persistent regional extreme heatwaves in the summer of 2022, with disparate spatial features and formation mechanisms in different months. We quantitatively assessed the relative contributions of three oceans, i.e. tropical Indian Ocean and Pacific and North Atlantic, and the local soil moisture–temperature feedback using linear regression. The results showed that the monthly mean atmospheric circulation anomalies failed to explain the extreme heatwave in June 2022. The combined contribution of the tropical Indo-Pacific and North Atlantic sea surface temperature anomalies (SSTAs), together with the local soil moisture–temperature feedback, explaining approximately 10% of the temperature anomalies. In July, the tropical Indo-Pacific SSTAs promoted anomalous atmospheric circulation and extreme heat via meridional circulation originating in the Maritime Continent, accounting for approximately 10% of the temperature anomalies, with North Atlantic SSTAs contributing the same percentage by a mid-latitude steady Rossby wave. Local soil moisture–temperature feedback accounted for 42% of the anomalies. The tropical Indo-Pacific SSTAs produced a strong western North Pacific anticyclone in August, but their direct contribution to the temperature anomalies was negligible. The North Atlantic SSTAs contributed 9% of the total via the mid-latitude steady Rossby wave. Local soil moisture–temperature feedback contributed 66%, suggesting that the July heatwave and drought exerted a significant impact on the subsequent August extreme heatwave. Global warming has greatly facilitated extreme heatwaves, accounting for about 30%–40% of these events in summer 2022. These results also suggest that the climatic effects of tropical Indo-Pacific and North Atlantic SSTAs on Eastern China are evident in the month-to-month variation in summer. Our results thus contribute to the understanding and prediction of extreme heatwaves in Eastern China.

The South American low‐level jet (SALLJ) is a major source of moisture transport to southeastern South America, influencing rainfall, agriculture, and hydropower. While past research emphasized atmospheric controls, we examine the role of antecedent soil moisture in modulating jet dynamics. We focus on strong Chaco jets, a southward‐extended branch of the SALLJ that transport 37.9 Gt of water daily—twice the Amazon River's discharge. Using reanalysis data, we identify 54 Chaco jet events and categorize them based on antecedent soil moisture over northern Argentina; 63% occur under drier‐than‐normal conditions. Dry soils are associated with enhanced surface sensible heating, lower‐tropospheric warming, and a deepened thermal low, which intensifies the Chaco jet (2.8 times stronger than in wet cases) during the 5 days before its peak. These results highlight the importance of land‐atmosphere interactions in modulating SALLJ dynamics and suggest that antecedent soil moisture information could improve jet forecasts in the region.

Southeastern South America (SESA) is a highly productive agricultural region and a hot spot for land‐atmosphere interactions. To evaluate the impact of dry soil moisture anomalies (SMAs) on SESA climate and the sensitivity of the regional climate response to the location of SMAs, we perform three experimental simulations using the Community Earth System Model (CESM) with prescribed dry SMAs over (a) SESA, (b) western SESA, and (c) eastern SESA. The dry SESA and eastern SESA simulations show widespread negative precipitation anomalies. In contrast, the dry western SESA simulation shows positive precipitation anomalies over northeastern Argentina, which are associated with the enhanced southward moisture flux co‐located with the South American low‐level jet exit region. A composite analysis of extremely dry cases over western SESA using reanalysis data agrees with the findings from our CESM experiment. These findings have potential implications for subseasonal forecasting in this region. Plain Language Summary Large‐scale soil moisture anomalies evolve slowly and can provide an opportunity for better weather forecasting at timescales longer than 2 weeks. Therefore, it is critical to understand the causal physical mechanism and evaluate whether the regional climate response is sensitive to the location of soil moisture anomalies, especially in a productive agricultural region like southeastern South America (SESA). Using a numerical climate model, we simulate the impacts of dry soil over (a) SESA, (b) western SESA, and (c) eastern SESA. The simulations show that dry soil over western SESA can alter regional atmospheric circulation in the proximity of the existing corridor of poleward moisture transport, hence enhancing rainfall over northeastern Argentina. Conversely, dry soil over eastern SESA or the entire SESA region results in less precipitation because enhanced northerly transport is not co‐located with the low‐level wind corridor. Analysis of a dataset that incorporates observations supports our findings from numerical simulations. Key Points The impact of dry soil moisture anomalies (SMAs) on southeastern South America (SESA) regional climate is sensitive to the location of SMAs This study provides a causal mechanism linking soil moisture to precipitation via atmospheric circulation When western SESA has dry soil, it generates anomalous geostrophic wind, which is co‐located with the low‐level jet exit region

Inconsistent findings in soil moisture (SM)‐precipitation feedback literature motivate further research into the role of the boundary layer in these feedbacks. The present study explores mechanisms that can explain the spatial patterns found in a previous analysis employing satellite measured SM: positive feedback in the semi‐arid western U.S. (higher morning SM predicting greater likelihood of afternoon rainfall), and negative feedback in the humid east. Using a cloud–topped boundary layer model, we examine how evaporative fraction (EF, a proxy for SM) influences cloud mass flux (CMF). We then use logistic regression to relate CMF to precipitation. The results are consistent with the previous analysis: in semi‐arid areas, increased humidification with increased EF dominates CMF strength, yielding net positive feedbacks; in humid areas, reductions in convective velocity with increasing EF dominate the CMF, yielding net negative feedbacks. Such offsetting feedbacks may contribute to inconsistencies reported in the literature.

Soil moisture‐precipitation feedbacks are influenced by both small‐scale land‐atmosphere coupling and large‐scale atmospheric circulations, and their sign has important implications for the stability of regional hydroclimate. However, the importance of both local and non‐local processes makes it difficult to model soil moisture‐precipitation feedbacks with high fidelity, limiting our ability to use models to understand controls on their sign. Here, we address this challenge by exploring a promising but seldom‐used approach to studying soil moisture‐precipitation feedbacks over tropical land: coupling small‐domain convection‐permitting simulations to a land‐like surface and a parameterization of large‐scale dynamics. The large‐scale dynamics parameterization, based on the weak temperature gradient (WTG) approximation, is a key component that produces an open hydrological cycle with interactive moisture convergence. We first show that WTG‐constrained simulations coupled to a freely‐evaporating land surface support both precipitating and non‐precipitating equilibria across a wide range of insolation. We then leverage this bistability to probe the influence of soil moisture feedbacks on dry spells by asking whether non‐precipitating equilibria remain stable as the underlying surface dries out. We find that surface drying can trigger transitions from dry equilibria back to precipitating equilibria—a negative soil moisture‐precipitation feedback—and attribute this transition to increasingly inefficient boundary layer ventilation by the parameterized large‐scale circulation. In sensitivity experiments, alternative versions of the WTG scheme modify the parameter space where the negative feedback occurs, but none eliminate it entirely. Our results provide a foundation for leveraging the rich behavior of WTG‐constrained simulations to probe controls on soil moisture‐precipitation feedbacks over tropical land. Plain Language Summary Land surfaces constantly lose moisture through evaporation, and without rain will eventually become very dry. A key question for researchers interested in understanding drought is whether a drier land surface makes rain less likely (a “positive feedback” that favors intense drought) or more likely (a “negative feedback” that opposes intense drought). However, these feedbacks are difficult to study using computer models, in part because limited computer power makes it difficult to simulate interactions between land and the atmosphere in sufficient detail without neglecting the effects of large‐scale winds. We explore a new solution to this dilemma by describing computer simulations that take a novel approach to simulating feedbacks between rain and surface wetness: we devote most of our computational power to simulating land‐atmosphere interactions in great detail over a small region, and represent winds that carry moisture into and out of that region using a simple model most appropriate for the tropics. We show that these simulations can model both rainy and drought‐like conditions, and show that surface drying under drought conditions can trigger the return of rain—a negative anti‐drought feedback. These results provide a foundation for using a new modeling approach to improve our understanding of controls on drought. Key Points Cloud‐resolving simulations with parameterized moisture convergence support multiple equilibria in precipitation over a wet land surface Allowing the surface to dry out can trigger transitions from non‐precipitating equilibria back to a precipitating states The onset of precipitation is linked to less efficient boundary layer ventilation by large‐scale subsidence over a drier surface

Conventional global climate models are prone to producing unrealistic land‐atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land‐atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land‐atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the land‐atmosphere feedback loop. At daily timescales, SPCAM produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis‐forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM. Key Points: Superparameterization improves the global distribution of the strong terrestrial coupling signals Superparameterization reduces TFS (rainfall triggering signal) but enhances AFS (rainfall amount signal) globally Superparameterization tightens the connection between the responses of PBL properties and rainfall triggering to surface turbulent fluxes

With the aim of developing a fully coupled atmosphere‐hydrology model system, the Weather Research and Forecasting (WRF) model was enhanced by integrating a new set of hydrologic physics parameterizations accounting for lateral water flow occurring at the land surface. The WRF‐Hydro modeling system was applied for a 3 year long simulation in the Crati River Basin (Southern Italy), where output from the fully coupled WRF/WRF‐Hydro was compared to that provided by original WRF model. Prior to performing coupled land‐atmosphere simulations, the stand‐alone hydrological model (“uncoupled” WRF‐Hydro) was calibrated through an automated procedure and validated using observed meteorological forcing and streamflow data, achieving a Nash‐Sutcliffe Efficiency value of 0.80 for 1 year of simulation. Precipitation, runoff, soil moisture, deep drainage, and land surface heat fluxes were compared between WRF‐only and WRF/WRF‐Hydro simulations and validated additionally with ground‐based observations, a FLUXNET site, and MODIS‐derived LST. Since the main rain events in the study area are mostly dependent on the interactions between the atmosphere and the surrounding Mediterranean Sea, changes in precipitation between modeling experiments were modest. However, redistribution and reinfiltration of local infiltration excess produced higher soil moisture content, lower overall surface runoff, and higher drainage in the fully coupled model. Higher soil moisture values in WRF/WRF‐Hydro slightly influenced precipitation and also increased latent heat fluxes. Overall, the fully coupled model tended to show better performance with respect to observed precipitation while allowing more water to circulate in the modeled regional water cycle thus, ultimately, modifying long‐term hydrological processes at the land surface. Key Points: Fully coupled model includes lateral surface and subsurface water fluxes Lateral redistribution increases soil moisture content compared to control run Precipitation and long‐term land surface hydrological processes are influenced

Two long‐term simulations with the weather research and forecasting model are conducted to assess the contribution of land‐atmosphere coupling to interannual variability of summer climate over East Asia. The control experiment (CTL) uses a fully coupled land surface model, while an additional experiment replaces soil moisture evolution at each time step with the climatology of CTL and thus removes the interannual variability of soil moisture. CTL is able to reproduce relatively well climatic means and interannual variability of summer climate over East Asia though some biases exist. It is found that land‐atmosphere coupling plays a critical role in influencing summer climate variability, in particular over the climatic and ecological transition zones. Interactive soil moisture strongly amplifies daily mean temperature variability over the southern Siberia–northern Mongolia region, the region from northeast China to central China, and the eastern part of South Asia, accounting for half or more of the total variance. Soil moisture is found to exert substantially stronger impacts on daily maximum temperature variability than on daily mean temperature variability but generally has small effects on daily minimum temperature except for the eastern Tibetan Plateau and some other areas. Soil moisture makes a dominant contribution to precipitation variability over the climatic and ecological transition zones of the southern Siberia–northern Mongolia region and northern China and many areas of western China. While soil moisture‐temperature coupling is largely determined by the ability of soil moisture to affect surface fluxes, soil moisture–precipitation coupling also depends on other physical processes, particularly moisture convection.

This study examines the role of terrestrial forcings on the regional climate of sub-Saharan Africa through the application of a multivariate statistical method, stepwise generalized equilibrium feedback assessment, to an array of observational, reanalysis, and remote sensing data products. By applying multiple datasets, data uncertainty and the robustness of assessed land surface feedbacks are considered. The approach from our 2017 study is expanded to decompose the relative contribution of vegetation, soil moisture, and oceanic forcings; investigate the role of evapotranspiration (ET) partitioning in terrestrial feedbacks; and compare land surface feedbacks among four key regions, namely the Sahel, Greater Horn of Africa, West African monsoon region, and Congo. ET partitioning differs notably among sub-Saharan regions and between available observational datasets. Across sub-Saharan Africa as a whole, oceanic and terrestrial forcings impose a relatively comparable impact on year-round atmospheric conditions. The land surface feedbacks are most pronounced across the semi-arid Sahel and Greater Horn of Africa, although with unique seasonality of such feedbacks between regions. Moisture recycling is the dominant mechanism in these regions, with positive soil moisture–vegetation–rainfall feedbacks. The direct feedback of soil moisture anomalies on atmospheric conditions outweighed that of leaf area index anomalies. There is a clear need for more extensive observations of ET, its partitioning, and soil moisture across sub-Saharan Africa, as these data uncertainties propagate into the reliability of assessed soil moisture–ET feedbacks, particularly across the Sahel.

Soil moisture plays an important role in modulating regional climate from sub-seasonal to seasonal timescales. Particularly important, soil moisture deficits can amplify summer heatwaves (HWs) through soil moisture-temperature feedback which has critical impacts on society, economy and human health. In this study, we evaluate decade-long convection-permitting Weather Research and Forecast (WRF) model simulations over the contiguous US on simulating heatwaves and their relationship with antecedent soil moisture using a dense observational network. We showed that the WRF model is capable of capturing the spatial patten of temperature threshold to define HWs, though the simulation shows a warm bias in the Midwest and cold bias in western mountainous regions. Two HW indices, based on frequency (HWF) and magnitude (HWM), are evaluated. Significant anti-correlations between antecedent soil moisture and both HW indices have been found in most parts of the domain except the South Pacific Coast. A detailed study has been conducted for the Midwest and South Great Plains regions, where two heatwaves had occurred in the last decade. In both regions, the high quantile of the HWF distribution shows a strong dependence on antecedent soil moisture: drier soil leads to much larger increase on the upper quantile of HWF than it does on the lower quantile. Soil moisture effects on the higher end of HWM are not as strong as on the lower end: wetter antecedent soil corresponds to a larger decrease on the lower quantile of HWM. WRF captures the heterogeneous responses to dry soil on HWF distribution in both regions, but overestimates these HWM responses in the Midwest and underestimates them in the South Great Plains. Our results show confidence in WRF’s ability to simulate HW characteristics and the impacts of antecedent soil moisture on HWs. These are also important implications for using high-resolution convection-permitting mode to study the coupling between land and atmosphere.