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Interannual fluctuations in average summertime temperatures across the western United States are captured by a leading empirical orthogonal function that explains over 50% of the total observed variance. In this paper, we explain the origins of this pattern of interannual temperature variability by examining soil moisture–temperature coupling that acts across seasons in observations and climate models. We find that a characteristic pattern of coupled temperature–soil moisture climate variability accounts for 34% of the total observed variance in summertime temperature across the region. This pattern is reproduced in state-of-the-art global climate models, where experiments that eliminate soil moisture variability reduce summertime average temperature variance by a factor of 3 on average. We use an idealized model of the coupled atmospheric boundary layer and underlying land surface to demonstrate that feedbacks between soil moisture, boundary layer relative humidity, and precipitation can explain the observed relations between springtime soil moisture and summertime temperature. Our results suggest that antecedent soil moisture conditions and subsequent land–atmosphere interactions play an important role in interannual summertime temperature variability in the western United States; soil moisture variations cause distal temperature anomalies and impart predictability at time scales longer than one season. Our results indicate that 40% of the observed warming trend across the western United States since 1981 has been driven by wintertime precipitation trends in the U.S. southwest. Significance Statement: Year-to-year fluctuations in summertime temperatures have a large impact on drought, wildfire, and extreme heat across the Western United States. We find strong evidence that soil moisture deficits in the preceding spring may be the primary driver of higher-than-average summer temperatures in this region. Our results suggest that memory in the water cycle may lead to greater predictability in the climate system from season to season and that trends in southwest precipitation have exerted a considerable influence on observed warming over the past 40 years. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

The MERRA-2 atmospheric reanalysis product provides global, 1-hourly estimates of land surface conditions for 1980–present at ;50-km resolution. MERRA-2 uses observations-based precipitation to force the land (unlike its predecessor, MERRA). This paper evaluates MERRA-2 and MERRA land hydrology estimates, along with those of the land-only MERRA-Land and ERA-Interim/Land products, which also use observations-based precipitation. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. Validation against in situ measurements from 220–320 stations in North America, Europe, and Australia shows that MERRA-2 and MERRA-Land have the highest surface and root zone soil moisture skill, slightly higher than that of ERA-Interim/Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data from the Canadian Meteorological Centre than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim/Land. Validation with MODIS satellite observations shows that MERRA-2 has a lower snow cover probability of detection and probability of false detection than MERRA, owing partly to MERRA-2's lower midwinter, midlatitude snow amounts and partly to MERRA-2's revised snow depletion curve parameter compared to MERRA. Finally, seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim/Land, somewhat lower for MERRA-Land, and lower still for MERRA (significantly in four basins). [ABSTRACT FROM AUTHOR]

While low-frequency variations in precipitation amount, occurrence counts (hereafter "occurrence"), and intensity can take place on seasonal to multidecadal time scales, it is often unclear at which time scales these precipitation variations can be ascribed to potentially predictable, climate-induced changes versus simple, stochastic (i.e., random) precipitation event evolutions. This paper seeks to isolate the dominant time scales at which potentially predictable changes in observed precipitation characteristics occur over the continental United States and analyze sources of revealed potentially predictable precipitation variations for particular regions. The results highlight that at interannual time scales (here defined as those shorter than 7 years), the potential for predicting annual precipitation amounts tends to be higher than for annual event occurrence or intensity, with interannual potential predictability highest in both relatively dry and wet locations and lowest in transition regions. By contrast, at time scales greater than 7 years the potential for predicting annual event occurrence tends to be higher than amount or intensity, with >20-yr time scale potential predictability highest in relatively wet locations and lowest in relatively dry locations. To highlight the utility of this type of analysis, two robust signals are selected for further investigation, including 1) approximately 10-yr time scale variations in potentially predictable annual amounts over the northwestern United States and 2) 20-60-yr time scale variations in potentially predictable annual event occurrence over the southwestern United States. While mechanistic drivers for these observed variations are still being investigated, concurrent and precursor climate-slate estimates in the atmosphere and ocean—principally over the Pacific sector—are provided, the monitoring of which may help realize the potential for predicting precipitation variations in these regions. [ABSTRACT FROM AUTHOR]

There is no simple explanation for the spatial structure of near-surface relative humidity over land. We present a diagnostic theory for zonally and temporally averaged near-surface relative humidity (RH) over land based on energy budgets of an atmospheric column in radiative–convective equilibrium. The theory analytically relates RH to the surface evaporative fraction (EF), has no calibrated parameters, and is quantitatively accurate when compared with RH from a reanalysis, and with cloud-permitting simulations over an idealized land surface. The theory is used to answer two basic questions. First, why is RH never especially low (e.g., 1%)? The theory shows that established lower bounds on EF over land and ocean are equivalent to lower bounds on RH that preclude particularly low values, at least for conditions typical of the modern Earth. Second, why is the latitudinal profile of RH over land shaped like the letter W, when both specific humidity and saturation specific humidity essentially decline monotonically from the equator to the poles? The theory predicts that the latitudinal profile of RH should look more like that of water stored in the soil (which also exhibits a W-shaped profile) than in the air (which does not). [ABSTRACT FROM AUTHOR]

The coupling of the land with the planetary boundary layer (PBL) on diurnal time scales is critical to regulating the strength of the connection between soil moisture and precipitation. To improve understanding of land-atmosphere (L-A) interactions, recent studies have focused on the development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process level. In this paper, the authors apply a suite of local land-atmosphere coupling (LoCo) metrics to modern reanalysis (RA) products and observations during a 17-yr period over the U.S. southern Great Plains. Specifically, a range of diagnostics exploring the links between soil moisture, evaporation, PBL height, temperature, humidity, and precipitation is applied to the summertime monthly mean diurnal cycles of the North American Regional Reanalysis (NARR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR). Results show that CFSR is the driest and MERRA the wettest of the three RAs in terms of overall surface-PBL coupling. When compared against observations, CFSR has a significant dry bias that impacts all components of the land-PBL system. CFSR and NARR are more similar in terms of PBL dynamics and response to dry and wet extremes, while MERRA is more constrained in terms of evaporation and PBL variability. Each RA has a unique land-PBL coupling that has implications for downstream impacts on the diurnal cycle of PBL evolution, clouds, convection, and precipitation as well as representation of extremes and drought. As a result, caution should be used when treating RAs as truth in terms of their water and energy cycle processes. [ABSTRACT FROM AUTHOR]

Human heat stress depends jointly on atmospheric temperature and humidity. Wetter soils reduce temperature but also raise humidity, making the collective impact on heat stress unclear. To better understand these interactions, we use ERA5 to examine the coupling between daily average soil moisture and wet-bulb temperature (Tw) and its seasonal and diurnal cycle at global scale. We identify a global soil moisture–Tw coupling pattern with both widespread negative and positive correlations in contrast to the well-established cooling effect of wet soil on dry-bulb temperature. Regions showing positive correlations closely resemble previously identified land–atmosphere coupling hotspots where soil moisture effectively controls surface energy partition. Soil moisture–Tw coupling varies seasonally closely tied to monsoon development, and the positive coupling is slightly stronger and more widespread during nighttime. Local-scale analysis demonstrates a nonlinear structure of soil moisture–Tw coupling with stronger coupling under relatively dry soils. Hot days with high Tw values show wetter-than-normal soil, anomalous high latent and low sensible heat flux from a cooler surface, and a shallower boundary layer. This supports the hypothesis that wetter soil increases Tw by concentrating surface moist enthalpy flux within a shallower boundary layer and reducing free-troposphere-air entrainment. We identify areas of particular interest for future studies on the physical mechanisms of soil moisture–heat stress coupling. Our findings suggest that increasing soil moisture might amplify heat stress over large portions of the world including several densely populated areas. These results also raise questions about the effectiveness of evaporative cooling strategies in ameliorating urban heat stress. Significance Statement: The purpose of this study is to provide a global picture of the relationship between soil moisture anomalies and a heat stress metric that includes the joint effects of temperature and humidity. This is important because a better understanding of this relationship will help improve the prediction of extreme heat stress events and inform strategies for ameliorating heat stress. We find a widespread positive correlation between soil moisture and heat stress, in contrast to studies relying on temperature alone. This raises the possibility that, over much of the world, and in the most populous regions, strategies like irrigation or "greening" that can reduce temperature might be ineffective or even harmful in reducing heat stress with humidity incorporated. [ABSTRACT FROM AUTHOR]

Groundwater and climate interact in a two-way manner. Precipitation ultimately controls groundwater recharge and, conversely, groundwater may influence climate through evapotranspiration. Yet very few global climate models or Earth system models actually simulate groundwater flows. And while the expected impacts of climate change on groundwater resources are the subject of a growing concern, global-scale groundwater–climate feedbacks have received very little attention so far. Here we show that the integration of unconfined aquifers in a global climate model can regionally affect the climate change signal on temperatures and precipitation. We assess the impact of groundwater under preindustrial and 4xCO2 conditions (after climate stabilization). In both cases, we find that groundwater has a cooling and a wetting effect in certain regions of the world. In eastern Europe, both these impacts are stronger in the warmer climate (4xCO2 forcing) where the presence of groundwater reduces the frequency of summer heatwaves by 40%, compared to a 15% reduction in the preindustrial world. This work constitutes one of the very first global assessments of the potential feedbacks of groundwater on climate change. Our results support the idea that groundwater should be represented in global climate models and Earth system models, as it does indeed play an active role in the climate system. [ABSTRACT FROM AUTHOR]

Thresholds of soil moisture exist below which the atmosphere becomes hypersensitive to land surface drying, inducing thermal feedbacks that can exacerbate heatwaves. Realistic representation of threshold transitions in forecast models could improve extreme heat predictability and understanding of the role of land–atmosphere coupling. This study evaluates the performance of several forecast models from the Subseasonal Experiment (SubX) and several prototype versions of the Unified Forecast System (UFS) in their representation of threshold transitions by validation against reanalysis data. A metric of skill (true skill score) is applied to soil moisture breakpoint values, which mark the transition to heatwave hypersensitivity for drying soils. Forecast models have poor skill at being initialized on the correct side of the breakpoint, but show improvement when normalized to account for deficiencies in their soil moisture climatologies. Regionally, models performed best in the U.S. Northwest and worst in the Southwest. They effectively capture the tendency of western regions to spend more summer days in the hypersensitive regime than the eastern United States. Models represent well extreme heat as a consequence of atmospheric initial state for the first week of the forecast, but struggle to represent the soil moisture feedback regime. Forecast models generally perform better at extreme heat prediction when they are already dry and in the hypersensitive regime, even when erroneously so, implying that errors or biases exist in model parameterizations. Nevertheless, composite analysis shows encouraging model performance of the "hit" category, suggesting that an improvement in soil moisture initialization could further improve extreme heat forecast skill. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) is the strongest interannual signature in the tropical air–sea system and can affect global atmospheric variables, but ENSO's climatic impact on land surface variables such as skin temperature, snow cover, and soil moisture that can serve as seasonal climate predictors remains relatively little known. Here we examine ENSO's impact on the three land surface variables in Northern Hemisphere extratropics by regression analysis, using a combination of ERA5 reanalysis, GLDAS, satellite-based observations, and CESM2 simulations. Our results show that during El Niño winters anomalous land surface warming occurs in Northern Hemisphere midlatitudes, accompanied by snow cover reduction, especially in northern North America and eastern Europe, while anomalous cooling occurs in southern North America and the Tibetan Plateau, accompanied by increased snow cover. Meanwhile, increased soil moisture is observed in southern North America, central Asia, and southeast China. Further analysis indicates that atmospheric moisture processes dominate the formation of the land surface anomalies, for which the changes in water vapor and precipitation induced by the ENSO-related large-scale atmospheric teleconnection are critical. The anomalous land surface warming in midlatitudes mainly results from the increased downward longwave radiation due to the increase of water vapor, whereas the physical pathway causing water vapor anomalies is different over North America and Eurasia. Controlled by ENSO-induced changes in atmospheric circulation and moisture transport, anomalous precipitation explains most of the snow cover and soil moisture anomalies, which play a certain role in shaping the skin temperature anomalies in some regions through snow–albedo feedback and evaporation, respectively. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) exerts strong powerful thermal forcing, which plays a vital role in influencing weather–climate variations in Asia and even the Northern Hemisphere. However, the causes of thermal variation over the TP have not been fully revealed. Here, the role of winter soil moisture (SM) in subsequent summer thermal anomalies on the TP was investigated through multisource datasets for the period 1979–2014. Results indicate a significant positive relationship (r = 0.52) between winter SM and subsequent summer-mean surface air temperature (SAT). Further investigations show that more (less) winter SM results in abundant (deficient) atmospheric water vapor in subsequent summer owing to its persistence. Furthermore, Earth’s surface energy budget equation confirms that strengthened (weakened) surface downward longwave radiation caused by increased (decreased) water vapor is the dominant factor leading to SAT variations, even more significant for nocturnal SAT. The winter SM–atmospheric temperature positive relationship can extend from the surface to 200 hPa over the TP. In addition, the enhanced (weakened) atmospheric latent heat release associated with increased (decreased) water vapor content may be another important factor contributing to changes in atmospheric temperatures over the TP. Therefore, our results contribute to a better understanding of the effect of land–surface processes on thermal anomalies over the TP. Significance Statement Understanding the causes of thermal anomalies over the Tibetan Plateau (TP) is crucial for weather and climate variations, but the role of winter soil moisture (SM) in subsequent summer thermal effects is largely unknown. This study investigated the relationship between winter SM and thermal anomalies in subsequent summers on the TP. Results show that the above (below)-normal winter SM will cause warm (cold) atmospheric temperatures in the subsequent summer. The above (below)-normal winter SM anomalies bring increased (decreased) atmospheric water vapor in summer owing to its persistence, resulting in strengthened (weakened) downward longwave radiation and atmospheric latent heat release to heat (cool) the atmosphere. [ABSTRACT FROM AUTHOR]

In North China (NC), heat stress, which can be quantitatively characterized by wet-bulb globe temperature (WBGT), is closely related to specific humidity. This study focuses on the total days for NC average daily maximum WBGT exceeding 26°C (WGBT26) per summer (June–August) from 1979 to 2017. Rather than local precipitation or evaporation in NC, the NC WBGT26 is significantly related to the nonlocal evaporation around the Yangtze River valley (YR). The abnormal positive evaporated water vapor in YR, associated with anomalously high water vapor flux from south to north at 925 hPa, is continuously transported to NC in the above-normal WBGT26 years. Such an abnormal "evaporation and transportation" process can significantly increase the water vapor in NC and therefore enhance WBGT26. The evaporation in YR peaks in mid- to late July and is closely associated with the occurrence days for daily maximum WBGT exceeding 26°C and maximum daily mean specific humidity at 925 hPa in summer. The main driver for the strongest YR evaporation anomaly from 15 July to 15 August is the simultaneous surface air temperature rather than the simultaneous or earlier soil moisture, precipitation, and vapor pressure deficit (VPD) anomaly. This condition is due to the continuously abundant soil moisture in the YR from April to September. The results of this study provide new ideas for studying heat stress in NC, indicating that nonlocal land–atmosphere interactions are crucial. [ABSTRACT FROM AUTHOR]

Normalized mutual information (NMI) is a nonparametric measure of the dependence between two variables without assumptions about the shape of their bivariate data distributions, but the implementation and interpretation of NMI in the coupled climate system is more complicated than for linear correlations. This study presents a joint approach combining correlation and NMI to examine land and ocean surface forcing of U.S. drought at varying lead times. Based on the distribution of correlation versus NMI between a source variable (local or remote forcing) and target variable [e.g., summer precipitation in the southern Great Plains (SGP)], newly proposed one-tail significance levels for NMI combined with two-tailed significance levels of correlation enable us to discern linearity and nonlinearity dominant regimes in a more intuitive way. Our analysis finds that NMI can detect strong linear relationships like correlations, but it is not exclusively tuned to linear relationships as correlations are. Also, NMI can further identify nonlinear relationships, particularly when there are clusters and blank areas (high density and low density) in joint probability distributions between source and target variables (e.g., detected between soil moisture conditions in eastern Montana from mid-February to mid-August and summer precipitation in the SGP). The linear and nonlinear information are found to be sometimes mixed and rather convoluted with time, for instance, in the subtropical Pacific of the Southern Hemisphere, revealing relationships that cannot be fully detected by either NMI or correlation alone. Therefore, this joint approach is a potentially powerful tool to reveal complex and heretofore undetected relationships. [ABSTRACT FROM AUTHOR]

Understanding the roles of land surface conditions and atmospheric circulation on continental daily temperature variance is key to improving predictions of temperature extremes. Evaporative resistance (rs, hereafter), a function of the land cover type, reflects the ease with which water can be evaporated or transpired and is a strong control on land–atmosphere interactions. This study explores the effects of rs perturbations on summer daily temperature variance using the Simple Land Interface Model (SLIM) by mimicking, for rs only, a global land cover conversion from forest to crop/grassland. Decreasing rs causes a global cooling. The cooling is larger in wetter areas and weaker in drier areas, and primarily results from perturbations in shortwave radiation (SW) and latent heat flux (LH). Decreasing rs enhances cloud cover due to greater land surface evaporation and thus reduces incoming SW over most land areas. When rs decreases, wetter areas experience strong evaporative cooling, while drier areas become more moisture-limited and thus experience less cooling. Thermal advection further shapes the temperature response by damping the combined impacts of SW and LH. Temperature variance increases in drier areas and decreases in wetter areas as rs decreases. The temperature variance changes can be largely explained from changes in the combined variance of SW and LH, including an important contribution of changes in the covariance of SW and LH. In contrast, the effects of changes in thermal advection variance mainly affect the Northern Hemisphere midlatitudes. Significance Statement: This study aims to better understand processes governing daily near-surface air temperature variance over land. We use an idealized modeling framework to explore the effects of land surface evaporative resistance (a parameter that controls how hard it is to evaporate water from the surface) on summer daily temperature variance. We find that a uniform decrease of evaporative resistance across the global land surface causes changes in the temperature variance that can be predicted from changes in the combined variance of shortwave radiation and latent heat flux. The variance of horizontal advection is important in altering the temperature variance in the Northern Hemisphere midlatitudes. Our findings shed light on predicting the characteristics of temperature variability as a function of surface conditions. [ABSTRACT FROM AUTHOR]

In northern Australia (NAUS), mean rainfall during the Australian summer monsoon (AUSM) season exhibits distinct interannual variability despite weak influence from tropical sea surface temperature (SST) variability. The present study investigates mechanisms for the strong and persistent rainfall anomalies throughout the AUSM season. When the AUSM is stronger than normal, the low-level monsoonal circulation intensifies in response to the stronger convective activity over NAUS. The intensified surface westerlies over the tropical southeastern Indian Ocean (SEIO) enhance oceanic evaporation locally and downstream moisture transport into NAUS. This wind–evaporation feedback is verified through a moist static energy budget analysis. For this feedback to work effectively, SST cooling due to the stronger AUSM should be weak enough not to suppress the oceanic evaporation in the tropical SEIO. Our mixed layer heat budget analysis based on an ocean model hindcast experiment reveals that anomalous downwelling in the subsurface SEIO, which is induced dynamically by the intensified monsoon westerlies, partially offsets the SST cooling. The land surface evaporation over the continental inland area is also enhanced significantly in the middle and later portions of the monsoon season associated with increased soil moisture, suggesting its memory effect for the persistence of rainfall anomalies. The AUSM variability can therefore be regarded as a self-sustaining internal variability in the atmosphere–ocean–land surface coupled system, rather than just an atmospheric internal variability. Significance Statement: We aim to understand why summer monsoon rainfall in northern Australia varies markedly from one year to another even under the weak influence of large-scale sea surface temperature fluctuations, such as El Niño/La Niña. Our analyses based mainly on observational datasets reveal that wind-induced changes in oceanic evaporation south of Java significantly modulates the water vapor transport into northern Australia. We also find that ocean dynamics helps this wind–evaporation feedback process and continental soil moisture may act to prolong anomalous rainfall by its memory effect. This study shows the self-sustaining nature of the Australian summer monsoon variability under the atmosphere–ocean–land surface interactions, which deepens our understandings of the monsoon system. [ABSTRACT FROM AUTHOR]

The land–atmosphere interactions play an important role in modulating climate variability at different spatial and temporal scales. In South America, two recognized hot spots of soil moisture–atmosphere coupling are located in southeastern South America (SESA) and eastern Brazil. Soil moisture variability may not only alter the climate locally but may also have nonlocal impacts through changes in the regional circulation. Here we explore how these two local coupling hot spots interact with each other, how soil moisture variability modulates the regional circulation, and what is the consequent nonlocal impact on precipitation. To this end, we analyze numerical experiments, performed with a regional climate model for the period October–March of 1983–2012, that allow us to isolate the influence of the soil moisture interannual variability on the regional climate. When the soil moisture–atmosphere interaction is enabled, we find a nonlocal coupling mechanism that links both hot spots at different temporal scales, favoring precipitation in eastern Brazil to the detriment of the precipitation in SESA through shifts in the regional circulation, when compared with a simulation with constrained soil moisture–atmosphere interaction. In northeastern Argentina, a subregion of SESA located at the exit of the South American low-level jet, it was found that the amount of nighttime precipitation is modulated by the proposed nonlocal coupling mechanism. A better understanding of the variability of precipitation due to the influence of land–atmosphere interaction processes may contribute to improving the predictability of precipitation and the interpretation of climate projections. [ABSTRACT FROM AUTHOR]

California is one of the nation's top agriculture producers and is vulnerable to extreme events such as droughts and heat waves. Concurrent extreme events may further stress water and energy resources, exerting greater adverse socioeconomic, environmental, and health impacts than individual events. Here we examine the features of compound drought, heat wave, and dust events in California during spring and summer. From 2003 to 2020, 16 compound events are found in warm seasons, with a mean duration of ∼4 days. Compound events are characterized by enhanced surface temperature up to 4.5°C over northern and western California, reduced soil moisture and vegetation density, and an increase in dust optical depth (DOD) by 0.05–0.1 over central and southern California. The enhanced DOD is largely associated with severe vegetation dieback that favors dust emissions and southeasterly wind anomalies that support northward transport of dust from source regions in southern California. Surface fine dust and PM2.5 concentrations also increase by more than 0.5 and 5 μg m−3, respectively, during compound events associated with both enhanced dust emissions and a relatively stable atmosphere that traps pollutants. The development of the compound events is related to an anomalous high over the west coast in the lower to middle troposphere, which is a pattern favoring sinking motion and dry conditions in California. The anomalous high is embedded in a wave train that develops up to 7 days before the events. In comparison with heat wave extremes alone, compound events show significantly higher DOD and lower vegetation density associated with droughts. [ABSTRACT FROM AUTHOR]

Extreme heat events are a threat to human health, productivity, and food supply, so understanding their drivers is critical to adaptation and resilience. Anticyclonic circulation and certain quasi-stationary Rossby wave patterns are well known to coincide with heatwaves, and soil moisture deficits amplify extreme heat in some regions. However, the relative roles of these two factors in causing heatwaves is still unclear. Here we use constructed circulation analogs to estimate the contribution of atmospheric circulation to heatwaves in the United States in the Community Earth System Model version 1 (CESM1) preindustrial control simulations. After accounting for the component of the heatwaves explained by circulation, we explore the relationship between the residual temperature anomalies and soil moisture. We find that circulation explains over 85% of heatwave temperature anomalies in the eastern and western United States but only 75%–85% in the central United States. In this region, there is a significant negative correlation between soil moisture the week before the heatwave and the strength of the heatwave that explains additional variance. Further, for the hottest central U.S. heatwaves, positive temperature anomalies and negative soil moisture anomalies are evident over a month before heatwave onset. These results provide evidence that positive land–atmosphere feedbacks may be amplifying heatwaves in the central United States and demonstrate the geographic heterogeneity in the relative importance of the land and atmosphere for heatwave development. Analysis of future circulation and soil moisture in the CESM1 Large Ensemble indicates that, over parts of the United States, both may be trending toward greater heatwave likelihood. [ABSTRACT FROM AUTHOR]

Drought is a major natural hazard with far-reaching social, economic, and environmental impacts whose characteristics are highly interdependent across different spatial and temporal scales. Traditional global warming impact assessments on drought at the global scale have, however, taken into account only one drought characteristic at a time, likely leading to an underestimation of the overall impact. Here, we perform a trivariate analysis of changes in drought conditions at 1.5°, 2°, and 3°C global warming levels using 25 CMIP6 GCMs. Drought properties are characterized by the Standardized Soil Moisture Index (SSI). The future joint return periods of droughts historically associated with 10-, 20-, and 30-yr return periods are computed under the warming levels using copula functions considering drought duration, peak, and severity. Our comparative assessments of global warming impact on drought properties between univariate and trivariate analyses corroborate the substantial underestimation of the impact by the univariate analysis. The trivariate analysis shows that around 63%–91% of the global land will be subject to more recurrent droughts, while the percentage of the land reduces to 41%–56% for the univariate analysis. The difference between the univariate and trivariate analyses enlarges with global warming levels and the extremity of drought events. Based on the trivariate analysis, a 30-yr drought would become at least threefold more recurrent in 11%, 15%, and 20% of the global land at 1.5°, 2°, and 3°C warming levels, respectively, but the univariate analysis could not reach such large increases in drought conditions. [ABSTRACT FROM AUTHOR]

This study shows that the frequency of North American summertime (June–August) heat extremes is skillfully predicted several months in advance in the newly developed Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR) seasonal forecast system. Using a statistical optimization method, the average predictability time, we identify three large-scale components of the frequency of North American summer heat extremes that are predictable with significant correlation skill. One component, which is related to a secular warming trend, shows a continent-wide increase in the frequency of summer heat extremes and is highly predictable at least 9 months in advance. This trend component is likely a response to external radiative forcing. The second component is largely driven by the sea surface temperatures in the North Pacific and North Atlantic and is significantly correlated with the central U.S. soil moisture. The second component shows largest loadings over the central United States and is significantly predictable 9 months in advance. The third component, which is related to the central Pacific El Niño, displays a dipole structure over North America and is predictable up to 4 months in advance. Potential implications for advancing seasonal predictions of North American summertime heat extremes are discussed. [ABSTRACT FROM AUTHOR]

Diagnosis of rapidly developing springtime droughts in the central United States has mostly been made via numerous individual case studies rather than in an aggregate sense. This study investigates common aspects of subseasonal "meteorological drought" evolution, here defined as persistent precipitation minus evapotranspiration (P − ET) deficits, revealed in early (1 April–15 May) and late (16 May–30 June) spring composites of 5-day running mean JRA-55 reanalysis data for three different central U.S. regions during 1958–2018. On average, these droughts are initiated by a quasi-stationary Rossby wave packet (RWP), propagating from the western North Pacific, which arises about a week prior to drought onset. The RWP is related to a persistent ridge west of the incipient drought region and strong subsidence over it. This subsidence is associated with low-level divergent flow that dries the atmosphere and suppresses precipitation for roughly 1–2 weeks, and generally has a greater impact on the local moisture budget than does reduced poleward moisture transport. The resulting "dynamically driven" evaporative demand corresponds to a rapid drying of the root-zone soil moisture, which decreases around 40 percentiles within about 10 days. Anomalous near-surface warmth develops only after the P − ET deficit onset, as does anomalously low soil moisture that then lingers a month or more, especially in late spring. The horizontal scale of the RWPs, and of the related drought anomalies, decreases from early to late spring, consistent with the climatological change in the Pacific Rossby waveguide. Finally, while this composite analysis is based upon strong, persistent P − ET deficits, it still appears to capture much of the springtime development of "flash droughts" as well. [ABSTRACT FROM AUTHOR]

We analyze observations and develop a hierarchy of models to understand heat waves—long-lived, high temperature anomalies—and extremely high daily temperatures during summertime in the continental extratropics. Throughout the extratropics, the number of extremely hot days found in the three hottest months is much greater than expected from a random, single-process model. Furthermore, in many locations the temperature skewness switches from negative on daily time scales to positive on monthly time scales (or shifts from positive on daily time scales to higher positive values on monthly time scales) in ways that cannot be explained by averaging alone. These observations motivate a hierarchy of models of the surface energy and moisture budgets that we use to illuminate the physics responsible for daily and monthly averaged temperature variability. Shortwave radiation fluctuations drive much of the variance and the negative skewness found in daily temperature observations. On longer time scales, precipitation-induced soil moisture anomalies are important for temperature variability and account for the shift toward positive skewness in monthly averaged temperature. Our results demonstrate that long-lived heat waves are due to (i) the residence time of soil moisture anomalies and (ii) a nonlinear feedback between temperature and evapotranspiration via the impact of temperature on vapor pressure deficit. For most climates, these two processes give rise to infrequent, long-lived heat waves in response to randomly distributed precipitation forcing. Combined with our results concerning high-frequency variability, extremely hot days are seen to be state-independent filigree driven by shortwave variability acting on top of longer-lived, moisture-driven heat waves. [ABSTRACT FROM AUTHOR]

Drought is projected to become more severe and widespread as global warming continues in the twenty-first century, but hydroclimatic changes and their drivers are not well examined in the latest projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Here, precipitation (P), evapotranspiration (E), soil moisture (SM), and runoff (R) from 25 CMIP6 models, together with self-calibrated Palmer drought severity index with Penman–Monteith potential evapotranspiration (scPDSIpm), are analyzed to quantify hydroclimatic and drought changes in the twenty-first century and the underlying causes. Results confirm consistent drying in these hydroclimatic metrics across most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, and Australia, although the drying magnitude differs, with the drying being more severe and widespread in surface SM than in total SM. Global drought frequency based on surface SM and scPDSIpm increases by ∼25%–100% (50%–200%) under the SSP2-4.5 (SSP5-8.5) scenario in the twenty-first century together with large increases in drought duration and areas, which result from a decrease in the mean and flattening of the probability distribution functions of SM and scPDSIpm, while the R-based drought changes are relatively small. Changes in both P and E contribute to the SM change, whereas scPDSIpm decreases result from ubiquitous PET increases and P decreases over subtropical areas. The R changes are determined primarily by P changes, while the PET change explains most of the E increase. Intermodel spreads in surface SM and R changes are large, leading to large uncertainties in the drought projections. SIGNIFICANCE STATEMENT: Drought may become more severe and widespread under greenhouse gas (GHG)-induced global warming in the twenty-first century based on model projections. However, there are still large uncertainties in projected future drought changes, especially regarding the extent to which drought changes depend on drought indices and the future emissions scenarios analyzed. The latest projections from CMIP6 models reaffirm the widespread drying and increases in agricultural drought by up to 200% over most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, Southeast Asia, and Australia under moderate-to-high emissions scenarios in the twenty-first century, despite large uncertainties in individual projections partly due to internal variability. Ubiquitous increases in atmospheric demand for moisture under rising temperatures and precipitation decreases over many subtropical regions are the main driver of the projected drying and drought increases. [ABSTRACT FROM AUTHOR]

Future projections of precipitation change over tropical land are often enhanced by vegetation responses to CO2 forcing in Earth system models. Projected decreases in rainfall over the Amazon basin and increases over the Maritime Continent are both stronger when plant physiological changes are modeled than if these changes are neglected, but the reasons for this amplification remain unclear. The responses of vegetation to increasing CO2 levels are complex and uncertain, including possible decreases in stomatal conductance and increases in leaf area index due to CO2 fertilization. Our results from an idealized atmospheric general circulation model show that the amplification of rainfall changes occurs even when we use a simplified vegetation parameterization based solely on CO2-driven decreases in stomatal conductance, indicating that this mechanism plays a key role in complex model projections. Based on simulations with rectangular continents we find that reducing terrestrial evaporation to zero with increasing CO2 notably leads to enhanced rainfall over a narrow island. Strong heating and ascent over the island trigger moisture advection from the surrounding ocean. In contrast, over larger continents rainfall depends on continental evaporation. Simulations with two rectangular continents representing South America and Africa reveal that the stronger decrease in rainfall over the Amazon basin seen in Earth system models is due to a combination of local and remote effects, which are fundamentally connected to South America's size and its location with respect to Africa. The response of tropical rainfall to changes in evapotranspiration is thus connected to size and configuration of the continents. [ABSTRACT FROM AUTHOR]

Three sets of model experiments are performed with the Community Earth System Model to study the role of soil moisture anomalies as a boundary forcing for the formation of upper-level Rossby wave patterns during the Southern Hemisphere summer. In the experiments, soil moisture over Australia is set to ±1 standard deviation (STD) of an ERA-Interim-derived soil moisture reconstruction for the years 2009–16 and 50 ensemble members are run. The local response is a positive heating anomaly in the dry simulations that results in a thermal low–like circulation anomaly with an anomalous surface low and upper-level anticyclone. Significant differences in convective rainfall over Australia are related to differences in convective instability and associated with changes in near-surface moisture and moisture advection patterns. A circum-hemispheric flow response is identified both in the upper-level flow and in the surface storm tracks that overall resembles a positive southern annular mode–like flow anomaly in the dry simulations. The structure of this atmospheric response strongly depends on the background flow. The results point to a modulation of the hemispheric flow response to the forcing over Australia by El Niño–Southern Oscillation. Significant changes of precipitation over the Maritime Continent and South Africa are found and significant differences in the frequency of surface cyclones are present all along the storm tracks. SIGNIFICANCE STATEMENT: We demonstrate significant effects of soil moisture anomalies in Australia on local and remote atmospheric conditions in the Community Earth System Model. For this, we run three experiments with soil moisture set to dry, climatological, and wet conditions in Australia. In the dry experiment, near-surface temperature is significantly warmer and surface pressure is significantly lower over Australia. Convective precipitation changes as well and the spatial pattern of the precipitation response is influenced by changes in moisture transport. Significant anomalies in the upper-level height field are present around the hemisphere along the upper-level jet waveguides and storm-track position and strength are modulated. The results have potential applications in seasonal forecasting and implications for the interpretation of climate change simulations. [ABSTRACT FROM AUTHOR]

During the summer, the midwestern United States, which covers the main U.S. corn belt, has a net loss of surface water as evapotranspiration exceeds precipitation. The net moisture gain into the atmosphere is transported out of the region to the northern high latitudes through transient eddy moisture fluxes. How this process may change in the future is not entirely clear despite the fact that the corn-belt region is responsible for a large portion of the global supply of corn and soybeans. We find that increased CO2 and the associated warming increase evapotranspiration while precipitation reduces in the region, leading to further reduction in precipitation minus evaporation in the future. At the same time, the poleward transient moisture flux increases, leading to enhanced atmospheric moisture export from the corn-belt region. However, storm-track intensity is generally weakened in the summer because of a reduced north–south temperature gradient associated with amplified warming in the midlatitudes. The intensified transient eddy moisture transport as the storm track weakens can be reconciled by the stronger mean moisture gradient in the future. This is found to be caused by the climatological low-level jet transporting more moisture into the Great Plains region as a result of the thermodynamic mechanism under warmer conditions. Our results, for the first time, show that in the future the U.S. Midwest corn belt will experience more hydrological stress due to intensified transient eddy moisture export, leading to drier soils in the region. Significance Statement: The U.S. corn belt has dominated corn production in the United States since the 1850s, accounting for more than one-third of the global supply of corn, and is the world's largest source of soybeans. Yet how the region's hydroclimate responds to future climate change is still unclear. Here we found that increased CO2 and the associated warming increase evapotranspiration that takes more moisture out of the soil, thus leading to a drying effect. At the same time, the storms are becoming weaker and are shifted northward, leading to less precipitation in the corn-belt region. The excess moisture from the evapotranspiration is transported out of the corn-belt region by eddies. These processes together contribute to the corn belt's increased hydrological stress in the future. [ABSTRACT FROM AUTHOR]

Fire-emitted aerosols play an important role in influencing Earth’s climate, directly by scattering and absorbing radiation and indirectly by influencing cloud microphysics. The quantification of fire–aerosol interactions, however, remains challenging and subject to uncertainties in emissions, plume parameterizations, and aerosol properties. Here we optimized fire-associated aerosol emissions in the Energy Exascale Earth System Model (E3SM) using the Global Fire Emissions Database (GFED) and AERONET aerosol optical depth (AOD) observations during 1997–2016. We distributed fire emissions vertically using smoke plume heights from Multiangle Imaging SpectroRadiometer (MISR) satellite observations. From the optimization, we estimate that global fires emit 45.5 Tg yr-1 of primary particulate organic matter and 3.9 Tg yr-1 of black carbon. We then performed two climate simulations with and without the optimized fire emissions. We find that fire aerosols significantly increase global AOD by 14% ± 7% and contribute to a reduction in net shortwave radiation at the surface (-2.3 ± 0.5 Wm-2). Together, fire-induced direct and indirect aerosol effects cause annual mean global land surface air temperature to decrease by 0.17° ± 0.15°C, relative humidity to increase by 0.4% ± 0.3%, and diffuse light fraction to increase by 0.5% ± 0.3%. In response, GPP declines by 2.8 Pg C yr-1 as a result of large positive drivers (decreases in temperature and increases in humidity and diffuse light), nearly cancelling out large negative drivers (decreases in shortwave radiation and soil moisture). Our analysis highlights the importance of fire aerosols in modifying surface climate and photosynthesis across the tropics. [ABSTRACT FROM AUTHOR]

Heat waves such as the one in Europe 2003 have severe consequences for the economy, society, and ecosystems. It is unclear whether temperatures could have exceeded these anomalies even without further climate change. Developing storylines and quantifying the highest possible temperature levels is challenging given the lack of a long homogeneous time series and methodological framework to assess them. Here, we address this challenge by analyzing summer temperatures in a nearly 5000-yr preindustrial climate model simulation, performed with the Community Earth System Model CESM1. To assess how anomalous temperatures could get, we compare storylines generated by three different methods: 1) a return-level estimate, deduced from a generalized extreme value distribution; 2) a regression model, based on dynamic and thermodynamic heat wave drivers; and 3) a novel ensemble boosting method, generating large samples of reinitialized extreme heat waves in the long climate simulation. All methods provide consistent temperature estimates, suggesting that historical exceptional heat waves such as those in Chicago in 1995, Europe in 2003, and Russia in 2010 could have been substantially exceeded even in the absence of further global warming. These estimated unseen heat waves are caused by the same drivers as moderate observed events, but with more anomalous patterns. Moreover, altered contributions of circulation and soil moisture to temperature anomalies include amplified feedbacks in the surface energy budget. The methodological framework of combining different storyline approaches of heat waves with magnitudes beyond the observational record may ultimately contribute to adaptation and to the stress testing of ecosystems or socioeconomic systems to increase resilience to extreme climate stressors. [ABSTRACT FROM AUTHOR]

El Niño is a dominant source of interannual climate variability around the world. Based on the observed and reanalyzed datasets for the period of 1958–2019, this study explores the influence of El Niño on the spring precipitation over the Indochina Peninsula (ICP). The results show that El Niño has a significant negative correlation with the following spring precipitation over the ICP. However, this climatic teleconnection of El Niño was unstable, with an obvious interdecadal strengthening since the early 1990s. During the decaying spring, the El Niño–related sea surface temperature (SST) anomalies would induce an abnormal downward motion along with an anomalous low-level anticyclone over the western North Pacific. Before the early 1990s, such El Niño–induced atmospheric circulation anomalies were located to the east of the ICP, exerting little influence on the spring ICP precipitation. In contrast, since the early 1990s, the abnormal downward motion and anomalous low-level anticyclone extended westward covering the whole ICP, hampering local spring precipitation. This interdecadal change is owing to a relatively stronger intensity and longer duration of the El Niño–related warm SST anomalies over the tropical central Pacific in the epoch after the early 1990s (1992–2019) than in the previous decades (1958–91). Our findings highlight a strengthening effect of El Niño on the following spring climate over the ICP since the early 1990s, which has great implications for the regional climate prediction. Significance Statement: Spring precipitation variation has profound economic and societal influences for the Indochina Peninsula (ICP) that consists of several agriculture-based countries. Moreover, the local soil moisture anomaly induced by the ICP spring precipitation is an important seasonal predictor for the East Asian summer monsoon and extreme climate. Here this study identifies a strengthening influence of El Niño on the following spring precipitation over the ICP, due to a relatively stronger intensity and longer duration of the El Niño–related warm SST anomalies over the tropical central Pacific since the early 1990s. This may provide an important implication for the seasonal predictions of summer monsoon and extreme climate over East Asia and thus potentially enhance the predictability of regional climate. [ABSTRACT FROM AUTHOR]

Skillful subseasonal prediction of extreme heat and precipitation greatly benefits multiple sectors, including water management, public health, and agriculture, in mitigating the impact of extreme events. A statistical model is developed to predict the weekly frequency of extreme warm days and 14-day standardized precipitation index (SPI) during boreal summer in the United States. We use a leading principal component of U.S. soil moisture and an index based on the North Pacific sea surface temperature (SST) as predictors. The model outperforms the NCEP Climate Forecast System, version 2 (CFSv2), at weeks 3–4 in the eastern United States. It is found that the North Pacific SST anomalies persist for several weeks and are associated with a persistent wave train pattern, which leads to increased occurrences of blocking and extreme temperature over the eastern United States. Extreme dry soil moisture conditions persist into week 4 and are associated with an increase in sensible heat flux and a decrease in latent heat flux, which may help to maintain the overlying anticyclone. The clear-sky conditions associated with blocking anticyclones further decrease soil moisture and increase the frequency of extreme warm days. This skillful statistical model has the potential to aid in irrigation scheduling, crop planning, and reservoir operation and to provide mitigation of impacts from extreme heat events. [ABSTRACT FROM AUTHOR]

Soil moisture–atmosphere interactions are key elements of the regional climate system. There is a well-founded hope that a more accurate representation of the soil moisture–precipitation feedback would improve the simulation of summer precipitation on daily to seasonal, to climate time scales. However, uncertainties have persistently remained as the simulated feedback is strongly sensitive to the model representation of deep convection. Here we assess the feedback representation using a GPU-accelerated version of the regional climate model COSMO. We simulate and compare the impact of continental-scale springtime soil moisture anomalies on summer precipitation at convection-resolving (2.2 km) and convection-parameterizing resolution (12 km). We conduct reanalysis-driven simulations of 10 summer seasons (1999–2008) in continental Europe. While both simulations qualitatively agree on a positive sign of soil moisture–induced precipitation, they strongly differ in precipitation frequency: when convection is parameterized, wetter soil predominantly leads to more frequent precipitation events, and when convection is treated explicitly, they primarily become more intense. The results indicate that the sensitivity to soil moisture is stronger with parameterized convection, suggesting that the land surface–atmosphere coupling may be overestimated. In addition, the feedback's sensitivity in complex terrain is assessed for soil perturbations of different horizontal scales. The convection-resolving simulations confirm a negative feedback for subcontinental soil moisture anomalies, which manifests itself in a local decrease of wet-hour frequency. However, the intensity feedback reinforces precipitation events at the same time (positive feedback). The two processes are represented differently in simulations with explicit and parameterized convection, explaining much of the difference between the two simulations. [ABSTRACT FROM AUTHOR]

Persistent drought events that cause serious damage to the economy and environment are usually intensified by the feedback between the land surface and atmosphere. Therefore, reasonably modeling land–atmosphere coupling is critical for skillful prediction of persistent droughts. However, most high-resolution regional climate modeling has focused on the amplification effect of land–atmosphere coupling on local anticyclonic circulation anomalies, while less attention has been paid to the nonlocal influence through altering large-scale atmospheric circulation. Here we investigate how the antecedent land–atmosphere coupling over the area south of Lake Baikal (ASLB) influences the drought events occurring over its downstream region [i.e., Northeast China (NEC)] by using the Weather Research and Forecasting (WRF) Model and a linear baroclinic model (LBM). When the ASLB region is artificially forced to be wet in the WRF simulations during March–May, the surface sensible heating is weakened and results in a cooling anomaly in low level atmosphere during May–July. Consequently, the anticyclonic circulation anomalies over ASLB and NEC are weakened, and the severity of NEC drought during May–July cannot be captured due to the upstream wetting in March–May. In the LBM experiments, idealized atmospheric heating anomaly that mimics the diabatic heating associated with surface wetness is imposed over ASLB, and the quasi-steady response pattern of 500-hPa geopotential height to the upstream wetting is highly consistent with that in the WRF simulation. In addition, the lower-level heating instead of the upper-level cooling makes a major contribution to the high pressure anomaly over NEC. This study implies the critical role of modeling upstream land–atmosphere coupling in capturing downstream persistent droughts. [ABSTRACT FROM AUTHOR]

This study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December–February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS of prior seasons and DJF rainfall, we note that SSS of the Indo-Pacific warm pool region [SSSP (150°E–165°W and 10°S–10°N) and SSSI (50°–95°E and 10°S–10°N)] covaries with Australian rainfall, particularly in the northeast region. Composite analysis that is based on high or low SSS events in the SSSP and SSSI regions is performed to understand the physical links between the SSS and the atmospheric moisture originating from the regions of anomalously high or low, respectively, SSS and precipitation over Australia. The composites show the signature of co-occurring La Niña and negative Indian Ocean dipole with anomalously wet conditions over Australia and conversely show the signature of co-occurring El Niño and positive Indian Ocean dipole with anomalously dry conditions there. During the high SSS events of the SSSP and SSSI regions, the convergence of incoming moisture flux results in anomalously wet conditions over Australia with a positive soil moisture anomaly. Conversely, during the low SSS events of the SSSP and SSSI regions, the divergence of incoming moisture flux results in anomalously dry conditions over Australia with a negative soil moisture anomaly. We show from the random-forest regression analysis that the local soil moisture, El Niño–Southern Oscillation (ENSO), and SSSP are the most important precursors for the northeast Australian rainfall whereas for the Brisbane region ENSO, SSSP, and the Indian Ocean dipole are the most important. The prediction of Australian rainfall using random-forest regression shows an improvement by including SSS from the prior season. This evidence suggests that sustained observations of SSS can improve the monitoring of the Australian regional hydrological cycle. [ABSTRACT FROM AUTHOR]

Increased heat-wave frequency across the United States has led to the need for improved predictability of heat-wave events. A detailed understanding of land–atmosphere interactions and the relationship between soil moisture and temperature extremes could provide useful information for prediction. This study identifies, for many locations, a threshold of soil moisture below which there is an increase in the sensitivity of atmospheric temperature to declining soil moisture. This shift to a hypersensitive regime causes the atmosphere to be more susceptible to atmospherically driven heat-wave conditions. The soil moisture breakpoint where the regime shift occurs is estimated using segmented regression applied to observations and reanalysis data. It is shown that as the soil gets drier, there is a concomitant change in the rate of decrease in latent heat flux and increase in sensible heat flux leading to a strong positive feedback of increased air temperature near the surface, which further dries out the soil. Central, southwestern, and southeastern parts of the United States seem to have regions of clear regime shifts, while the eastern part of the United States generally does not get dry enough to reveal significant breakpoints. Sensible heat flux is seen to be a primary driver of this increased temperature sensitivity aided by the drop in latent heat flux. An investigation of flux tower sites verifies the breakpoint–flux relationships found in reanalysis data. Accurate estimation of these breakpoints can contribute to improved heat-wave prediction. [ABSTRACT FROM AUTHOR]

One of the critical components in understanding the climate system is the interaction between the land and the atmosphere. Whereas previous studies on land–atmosphere coupling mostly focus on its spatial hotspots, we explore the temporal evolution of land surface coupling strength (LCS) during a large-scale flood event in a semiarid region in northern Australia. The LCS indicates the relationship between soil moisture and latent heat flux, and the spatiotemporal variability in precipitation and soil water strongly affects the variability of LCS. The LCS is usually positive in the semiarid climate, where evapotranspiration (ET) occurs under the soil moisture–limited regime and thus increases with soil moisture. However, our analyses of combined land surface modeling and observational datasets show high temporal variability of LCS in the course of the extreme flood event followed by a drying period. The wet regions transferred the ET regime from the soil moisture–limited to the transition section, weakening the linear growth of ET with soil moisture, which resulted in the decline of LCS. The LCS remained weak until the flood retreated and the soil water approached the prestorm average state. Such temporal variation of the LCS has important implications for realistic parameterization of the land–atmosphere coupling and consequently improving subseasonal to seasonal climate forecast. [ABSTRACT FROM AUTHOR]

Understanding the Tibetan Plateau (TP) thermal processes is of utmost significance in changing climate. This study investigates the effect of soil moisture in changing the TP thermal profile and consequently summer precipitation in South Asia (SA). Soil moisture from Special Sensor Microwave Imager (SSM/I) developed from the F-08, F-11, and F-13 fundamental climate data record and atmospheric reanalysis from ERA-Interim, MERRA-2, and NCEP/CFSR during 1988–2008 are used. A generalized linear method that assesses the reciprocal forcing between two connected fields, named the coupled manifold technique (CMT), is applied to TP soil moisture and SA summer precipitation. It is revealed that interannual variations of SA precipitation are significantly (confidence level = 99%) impacted by TP soil moisture and the explained ratio of variance in SA is 0.3–0.4. Composite analysis indicates that SA summer precipitation has positive anomalies in response to dry TP soil moisture in the previous spring and vice versa. For understanding the possible mechanism, thermal processes, relative humidity, wind components, and moisture flux anomalies were calculated for dry and wet TP soil moisture and summer precipitation. The results suggested that TP soil moisture is likely to regulate near-surface energy balance and diabatic heating profile over TP. As a result, the surrounding lower-level westerlies (easterlies) (at 850 hPa) converge (diverge), associated with divergence (convergence) at the upper troposphere (200 hPa). The westerlies (easterlies) are usually moisture-rich (moisture-deficient) and thus cause more (less) precipitation in western (eastern) SA. It is thus suggested that the spring soil moisture may affect the thermal profile of TP, affecting the summer precipitation in SA as a consequence. [ABSTRACT FROM AUTHOR]

The seasonal prediction of precipitation extremes over the Yangtze River basin (YRB) has always been a great challenge. This study investigated the effects of spring soil moisture over the Indo-China Peninsula (ICP) on the following summer mei-yu front and YRB precipitation extremes during 1961-2010. The results indicated that the frequency of summer YRB precipitation extremes was closely associated with the mei-yu front intensity, which exhibited a strong negative correlation with the preceding spring ICP soil moisture. However, the lingering climate influence of the ICP soil moisture was unstable, with an obvious weakening since the early 1990s. Due to its strong memory, an abnormally lower spring soil moisture over the ICP would increase local temperature until the summer by inducing less evapotranspiration. Before the early 1990s, the geopotential height elevation associated with the ICP heating affected the western Pacific subtropical high (WPSH), strengthening the southwesterly summer monsoon. Consequently, the mei-yu front was intensified as more warm, wet air was transported to the YRB, and local precipitation extremes also occurred more frequently associated with abnormal ascending motion mainly maintained by the warm temperature advection. In the early 1990s, the Asian summer monsoon underwent an abrupt shift, with the changing climatological states of the large-scale circulations. Therefore, the similar ICP heating induced by the anomalous soil moisture had different effects on the monsoonal circulation, resulting in weakened responses of the mei-yu front and YRB precipitation extremes since the early 1990s. [ABSTRACT FROM AUTHOR]

The evaluation of decadal climate predictions against observations is crucial for their benefit to stakeholders. While the skill of such forecasts has been verified for several atmospheric variables, land hydrological states such as terrestrial water storage (TWS) have not been extensively investigated yet due to a lack of long observational records. Anomalies ofTWSare globally observed with the satellite missionsGRACE(2002-2017) andGRACE-FO(since 2018). By means of a GRACE-like reconstruction of TWS available over 41 years, we demonstrate that this data type can be used to evaluate the skill of decadal prediction experiments made available from different Earth system models as part of both CMIP5 and CMIP6. Analysis of correlation and root-mean-square deviation (RMSD) reveals that for the global land average the initialized simulations outperform the historical experiments in the first three forecast years. This predominance originates mainly from equatorial regions where we assume a longer influence of initialization due to longer soil memory times. Evaluated for individual grid cells, the initialization has a largely positive effect on the forecast year 1 TWS states; however, a general grid-scale prediction skill for TWS of more than 2 years could not be identified in this study for CMIP5. First results from decadal hindcasts of three CMIP6 models indicate a predictive skill comparable to CMIP5 for the multimodel mean in general, and a distinct positive influence of the improved soil-hydrology scheme implemented in the MPIESM for CMIP6 in particular. [ABSTRACT FROM AUTHOR]

We analyze the observed relationship between sea surface temperatures (SSTs) over the Atlantic Ocean and the normalized difference vegetation index (NDVI) in the Orinoco and Amazon basins. Monthly correlations between anomalies of NDVI and SSTs are computed for different regions of the Atlantic Ocean.We also use a mixture of observations and reanalysis products to analyze lagged correlations. Our results show that during August-September (i.e., the dry-to-wet transition season), changes in NDVI in the central Amazon and the so-called Arc of Deforestation are associated with precedent changes in the SSTs of the tropical North Atlantic (TNA) and the Caribbean (CABN) during March-June. Anomalous warming of the CABN and TNA generates changes in surface winds and atmospheric moisture transport in the region, decreasing precipitation, with consequent decreases of soil moisture, moisture recycling, and NDVI. An increase in TNA and CABN SSTs during March-June is also associated with an increase of NDVI over the northern Orinoco during June (i.e., the wet season). Unlike in the southern Amazon, precipitation and soil moisture in the Orinoco basin do not exhibit significant changes associated with SSTs. By contrast, atmospheric moisture recycling and transport increase with warmer SSTs in the TNA. Therefore, for the Orinoco, the link between SSTs and NDVI appears to be related not to changes in precipitation but to changes in moisture recycling. However, the causality between these changes needs to be further explored. These findings highlight the contrasting responses of the Amazon and Orinoco basins to Atlantic temperatures and the dominant role of atmospheric moisture transport linking these responses. [ABSTRACT FROM AUTHOR]

The land surface energy exchange over the Indo-China Peninsula (ICP) is important for regulating regional weather and climate. This work investigates the effect of spring soil moisture (SM) over the ICP on the following summer precipitation over the Yangtze River basin (YRB) during 1961–2010. The results show that the spring SM over the ICP has a significant negative correlation with the following summer YRB precipitation. However, this relationship experiences an obvious interdecadal change with a much stronger correlation in the epoch before the early 1990s (1961–91) than in the later decades (1992–2010). In spring, an abnormally lower SM over the ICP could induce less surface evapotranspiration, increasing local temperature until the summer. Before the 1990s, the resultant anomalous ICP heating raises the local geopotential height, resulting in an excessive westward extension of the western Pacific subtropical high (WPSH). Accordingly, the enhanced southwesterly summer monsoon would transport more moisture to the YRB, intensifying the meiyu front and local precipitation. In the early 1990s, the East Asian summer monsoon underwent an abrupt change with an interdecadal westward extension of the climatic WPSH. Consequently, the similar abnormal ICP surface heating induced by the anomalous SM would have different influences on the monsoonal circulation, causing a much weaker effect on the YRB precipitation in the recent decades. [ABSTRACT FROM AUTHOR]

The impact of land–atmosphere anomaly coupling on land variability is investigated using a new two-stage climate model experimental design called the ‘‘GLACE-Hydrology’’ experiment. First, as in the GLACECMIP5 experiment, twin sets of coupled land–atmosphere climate model (CAM5-CLM4.5) ensembles are performed, with each simulation using the same prescribed observed sea surface temperatures and radiative forcing for the years 1971–2014. In one set, land–atmosphere anomaly coupling is removed by prescribing soil moisture to follow the control model’s seasonally evolving soil moisture climatology (‘‘land–atmosphere uncoupled’’), enabling a contrast with the original control set (‘‘land–atmosphere coupled’’). Then, the atmospheric outputs from both sets of simulations are used to force land-only ensemble simulations, allowing investigation of the resulting soil moisture variability and memory under both the coupled and uncoupled scenarios. This study finds that in midlatitudes during boreal summer, land–atmosphere anomaly coupling significantly strengthens the relationship between soil moisture and evapotranspiration anomalies, both in amplitude and phase. This allows for decreased moisture exchange between the land surface and atmosphere, increasing soilmoisturememory and often its variability as well. Additionally, land–atmosphere anomaly coupling impacts runoff variability, especially in wet and transition regions, and precipitation variability, although the latter has surprisingly localized impacts on soilmoisture variability. As a result of these changes, there is an increase in the signal-to-noise ratio, and thereby the potential seasonal predictability, of SST-forced hydroclimate anomalies in many areas of the globe, especially in the midlatitudes. This predictability increase is greater for soil moisture than precipitation and has important implications for the prediction of drought. [ABSTRACT FROM AUTHOR]

Rapid-onset droughts, known as flash droughts, can have devastating impacts on agriculture, water resources, and ecosystems. The ability to predict flash droughts in advance would greatly enhance our preparation for them and potentially mitigate their impacts. Here, we investigate the prediction skill of the extreme 2012 flash drought over the U.S. Great Plains at subseasonal lead times (3 weeks or more in advance) in global forecast systems participating in the Subseasonal Experiment (SubX). An additional comprehensive set of subseasonal hindcasts with NASA’s GEOS model, a SubX model with relatively high prediction skill, was performed to investigate the separate contributions of atmospheric and land initial conditions to flash drought prediction skill. The results show that the prediction skill of the SubX models is quite variable.While skillful predictions are restricted to within the first two forecast weeks in most models, skill is considerably better (3–4 weeks or more) for certain models and initialization dates. The enhanced prediction skill is found to originate from two robust sources: 1) accurate soil moisture initialization once dry soil conditions are established, and 2) the satisfactory representation of quasi-stationary cross-Pacific Rossby wave trains that lead to the rapid intensification of flash droughts. Evidence is provided that the importance of soil moisture initialization applies more generally to central U.S. summer flash droughts. Our results corroborate earlier findings that accurate soil moisture initialization is important for skillful subseasonal forecasts and highlight the need for additional research on the sources and predictability of drought-inducing quasi-stationary atmospheric circulation anomalies. [ABSTRACT FROM AUTHOR]

The increasing frequency of very high summertime temperatures has motivated growing interest in the processes determining the probability distribution of surface temperature over land. Here, we show that on monthly time scales, temperature anomalies can be modeled as linear responses to fluctuations in shortwave radiation and precipitation. Our model contains only three adjustable parameters, and, surprisingly, these can be taken as constant across the globe, notwithstanding large spatial variability in topography, vegetation, and hydrological processes. Using observations of shortwave radiation and precipitation from 2000 to 2017, the model accurately reproduces the observed pattern of temperature variance throughout the Northern Hemisphere midlatitudes. In addition, the variance in latent heat flux estimated by the model agrees well with the few long-term records that are available in the central United States. As an application of the model, we investigate the changes in the variance of monthly averaged surface temperature that might be expected due to anthropogenic climate change. We find that a climatic warming of 4°C causes a 10% increase in temperature variance in parts of North America. [ABSTRACT FROM AUTHOR]

This study investigates the trend in destructive potential of landfalling tropical cyclones (TCs) in terms of power dissipation index (PDI) over mainland China in the period of 1980–2018. Results show that both the accumulated PDI and averaged PDI after landfall show significant increasing trends. The increasing trends are found to be contributed primarily by the increasing mean duration of TCs over land and the increasing TC intensity at landfall. Further analyses indicate that the increase in landfalling TC intensity prior to and at landfall, the decrease in intensity weakening rate after landfall, and the northward shift of landfalling TC track density all contribute to the longer duration of TCs after landfall. Moreover, the conducive large-scale conditions, such as the increases in coastal sea surface temperature and land surface temperature and soil moisture, the decrease in low-level vertical wind shear, and the increase in upper-level divergence, are all favorable for intense landfalling TCs and their survival after landfall, thus contributing to the increasing destructive potential of landfalling TCs over China. [ABSTRACT FROM AUTHOR]

Climate models show that soil moisture and its subseasonal fluctuations have important impacts on the surface latent heat flux, thus regulating surface temperature variations. Using correlations between monthly anomalies in net absorbed radiative fluxes, precipitation, 2-m air temperature, and soil moisture in the ERA-Interim reanalysis and the HadCM3 climate model, we develop a linear diagnostic model to quantify the major effects of land–atmosphere interactions on summertime surface temperature variability. The spatial patterns in 2-m air temperature and soil moisture variance from the diagnostic model are consistent with those from the products from which it was derived, although the diagnostic model generally underpredicts soil moisture variance. We use the diagnostic model to quantify the impact of soil moisture, shortwave radiation, and precipitation anomalies on temperature variance in wet and dry regions. Consistent with other studies, we find that fluctuations in soil moisture amplify temperature variance in dry regions through their impact on latent heat flux, whereas in wet regions temperature variability is muted because of high mean evapotranspiration rates afforded by plentiful surface soil moisture. We demonstrate how the diagnostic model can be used to identify sources of temperature variance bias in climate models. [ABSTRACT FROM AUTHOR]

Understanding vulnerabilities of continental precipitation to changing climatic conditions is of critical importance to society at large. Terrestrial precipitation is fed by moisture originating as evaporation from oceans and from recycling of water evaporated from continental sources. In this study, continental precipitation and evaporation recycling processes in the Earth system model GFDL-ESM2G are shown to be consistent with estimates from two different reanalysis products. The GFDL-ESM2G simulations of historical and future climate also show that values of continental moisture recycling ratios were systematically higher in the past and will be lower in the future. Global mean recycling ratios decrease 2%–3% with each degree of temperature increase, indicating the increased importance of oceanic evaporation for continental precipitation. Theoretical arguments for recycling changes stem from increasing atmospheric temperatures and evaporative demand that drive increases in evaporation over oceans that are more rapid than those over land as a result of terrestrial soil moisture limitations. Simulated recycling changes are demonstrated to be consistent with these theoretical arguments. A simple prototype describing this theory effectively captures the zonal mean behavior of GFDL-ESM2G. Implications of such behavior are particularly serious in rain-fed agricultural regions where crop yields will become increasingly soil moisture limited. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) suffered a severe drought that persisted from March to July of 2017 with profound impacts on agriculture and society, raising an urgent need to understand the mechanism for persistent droughts over midlatitudes. Previous drought mechanism studies focused on either large-scale teleconnections or local land–atmosphere coupling, while less attention was paid to their synergistic effects on drought persistence. Here we show that the 2017 NEC drought was triggered by a strong positive phase of the Arctic Oscillation in March, and maintained by the anticyclone over the area south to Lake Baikal (ASLB) through a quasi-stationary Rossby wave in April–July, accompanied by sinking motion and north wind anomaly. By using a land–atmosphere coupling index based on the persistence of positive feedbacks between the boundary layer and land surface, we find that the coupling states over NEC and ASLB shifted from a wet coupling in March to a persistently strengthened dry coupling in April–July. Over ASLB, the dry coupling and sinking motion increased surface sensible heat, decreased cloud cover, and weakened longwave absorption, resulting in a diabatic heating anomaly in the lower atmosphere and a diabatic cooling anomaly in the upper atmosphere. This anomalous vertical heating profile led to a negative anomaly of potential vorticity at low levels, indicating that the land–atmosphere coupling had a phase-lock effect on the Rossby wave train originating from upstream areas, and therefore maintained the NEC drought over downstream regions. Our study suggests that an upstream quasi-stationary wave pattern strengthened by land–atmosphere coupling should be considered in diagnosing persistent droughts, especially over northern midlatitudes. [ABSTRACT FROM AUTHOR]

The interaction between the land surface and the atmosphere is of significant importance in the climate system because it is a key driver of the exchanges of energy and water. Several important relations to heat waves, floods, and droughts exist that are based on the interaction of soil moisture and, for instance, air temperature and humidity. Our ability to separate the elements of this coupling, identify the exact locations where they are strongest, and quantify their strengths is, therefore, of paramount importance to their predictability. A recent rigorous causality formalism based on the Liang–Kleeman (LK) information flow theory has been shown, both theoretically and in real-world applications, to have the necessary asymmetry to infer the directionality and magnitude within geophysical interactions. However, the formalism assumes stationarity in time, whereas the interactions within the land surface and atmosphere are generally nonstationary; furthermore, it requires a sufficiently long time series to ensure statistical sufficiency. In this study, we remedy this difficulty by using the square root Kalman filter to estimate the causality based on the LK formalism to derive a time-varying form. Results show that the new formalism has similar properties compared to its time-invariant form. It is shown that it is also able to capture the time-varying causality structure within soil moisture–air temperature coupling. An advantage is that it does not require very long time series to make an accurate estimation. Applying a wavelet transform to the results also reveals the full range of temporal scales of the interactions. [ABSTRACT FROM AUTHOR]

Evaporation plays an extremely important role in determining summertime surface temperature variability over land. Observations show the relationship between evaporation and soil moisture generally conforms to the Budyko "two regime" framework; namely, that evaporation is limited by available soil moisture in dry climates and by radiation in wet climates. This framework has led climate models to different parameterizations of the relationship between evaporation and soil moisture in wet and dry regions. We have developed the Simple Land–Atmosphere Model (SLAM) as a tool for studying land–atmosphere interaction in general, and summertime temperature variability in particular. We use the SLAM to show that a negative feedback between evaporation and surface temperature gives rise to the two apparent evaporation "regimes" and provide analytic solutions for evaporative cooling anomalies that demonstrate the nonlinear impact of soil moisture perturbations. Stemming from the temperature dependence of vapor pressure deficit, the feedback we identify has important implications for how transitions between wet and dry land surfaces may impact temperature variability as the climate warms. We also elucidate the impacts of surface moisture and insolation perturbations on latent and sensible heat fluxes and on surface temperature variability. [ABSTRACT FROM AUTHOR]

In the mid-twentieth century (1948–57), North America experienced a severe drought forced by cold tropical Pacific sea surface temperatures (SSTs). If these SSTs recurred, it would likely cause another drought, but in a world substantially warmer than the one in which the original event took place. We use a 20-member ensemble of the GISS climate model to investigate the drought impacts of a repetition of the mid-twentieth-century SST anomalies in a significantly warmer world. Using observed SSTs and mid-twentieth-century forcings (Hist-DRGHT), the ensemble reproduces the observed precipitation deficits during the cold season (October–March) across the Southwest, southern plains, and Mexico and during the warm season (April–September) in the southern plains and the Southeast. Under analogous SST forcing and enhanced warming (Fut-DRGHT, ≈3 K above preindustrial), cold season precipitation deficits are ameliorated in the Southwest and southern plains and intensified in the Southeast, whereas during the warm season precipitation deficits are enhanced across North America. This occurs primarily from greenhouse gas–forced trends in mean precipitation, rather than changes in SST teleconnections. Cold season runoff deficits in Fut-DRGHT are significantly amplified over the Southeast, but otherwise similar to Hist-DRGHT over the Southwest and southern plains. In the warm season, however, runoff and soil moisture deficits during Fut-DRGHT are significantly amplified across the southern United States, a consequence of enhanced precipitation deficits and increased evaporative losses due to warming. Our study highlights how internal variability and greenhouse gas–forced trends in hydroclimate are likely to interact over North America, including how changes in both precipitation and evaporative demand will affect future drought. [ABSTRACT FROM AUTHOR]