Soil Moisture-temperature Coupling Research Articles

How Much Does Land–Atmosphere Coupling Influence Summertime Temperature Variability in the Western United States?

Abstract 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.

The role of soil moisture-temperature coupling for the 2018 Northern European heatwave in a subseasonal forecast

This study investigates the predictability of the 2018 Northern Europe heatwave using the GloSea5 forecast model from the perspective of land-atmosphere interactions. We focus on an inverse relationship wherein soil drying leads to increased temperatures and the model's ability to simulate this hypersensitivity in the soil moisture-temperature coupling on the dry side of a breakpoint defined as the soil moisture threshold below which land feedbacks nonlinearly amplify extreme heat. When evaluating forecast model performance in predicting this heatwave, we compare deterministic forecast scores (Hit Rate (HR) and True Skill Score (TSS)) for whether model Surface Soil Moisture (SSM) falls within the hypersensitive regime. GloSea5 exhibits enhanced prediction skill for the extreme heat event when the modelled soil moisture is within the hypersensitive regime. To understand the skill of the heatwave forecast for hit and missed cases of capturing SSM below the breakpoint, we first evaluate the climatological model performance for the water- and energy-limited processes, and then perform a comparison classified by whether SSM verifies on the dry side of the wilting point. The composite analysis demonstrates that the reproducibility of the breakpoint is tied to an improvement in climatological land coupling processes, mainly for classification in the water-limited coupling regime. Therefore, the results suggest that the process-based connection between soil moisture and temperature is a potential source for improving heatwave forecasts on subseasonal to seasonal (S2S) time scales.

Soil moisture–temperature coupling over India through multi-scale observations

ABSTRACT Soil moisture–temperature coupling has been shown to affect the severity and occurrences of extreme temperature events like heatwaves and droughts. In this study, we quantify the soil moisture–temperature coupling over India at daily and climatological scales. Our results show maximum climatological coupling over north and central India during pre-monsoon months. The coupling strength is related to soil moisture content. Daily coupling is calculated for two heatwave events (2009 and 2015) to determine whether land–atmosphere coupling enhances the heatwave event. We observed strong soil moisture–temperature coupling during the 2009 heatwave, whereas weak coupling is observed in the 2015 heatwave. Our results suggest that soil moisture anomalies could enhance heat anomalies and temperature anomalies through the reduction in latent heat flux, leading to enhanced soil moisture–temperature coupling. Thus our study highlights the importance of soil moisture and associated coupling in understanding and predicting heatwave events.

Shift of soil moisture-temperature coupling exacerbated 2022 compound hot-dry event in eastern China

Compound hot-dry events (CHDEs) are among the deadliest climate hazards and are occurring with increasing frequency under global warming. The Yangtze River Basin in China experienced a record-breaking CHDE in the summer of 2022, causing severe damage to human societies and ecosystems. Recent studies have emphasized the role of atmospheric circulation anomalies in driving this event. However, the contribution of land–atmosphere feedback to the development of this event remains unclear. Here, we investigated the impacts of soil moisture-temperature coupling on the development of this concurrent heatwave and drought. We showed that large amounts of surface net radiation were partitioned to sensible heat instead of latent heat as the soil moisture-temperature coupling pattern shifted from energy-limited to water-limited under low soil moisture conditions, forming positive land–atmosphere feedback and leading to unprecedented hot extremes in August. The spatial heterogeneity of hot extremes was also largely modulated by the land–atmosphere coupling strength. Furthermore, enhanced land–atmosphere feedback has played an important role in intensifying CHDEs in this traditional humid region. This study improves the understanding of the development of CHDEs from three aspects, including timing, intensity, and spatial distribution, and enables more effective early warning of CHDEs.

Changes in land-atmosphere coupling increase compound drought and heatwaves over northern East Asia

Compound drought and heatwaves (DHW) events have much attention due to their notable impacts on socio-ecological systems. However, studies on the mechanisms of DHW related to land-atmosphere interaction are not still fully understood in regional aspects. Here, we investigate drastic increases in DHW from 1980 to 2019 over northern East Asia, one of the strong land-atmosphere interaction regions. Heatwaves occurring in severely dry conditions have increased after the late 1990s, suggesting that the heatwaves in northern East Asia are highly likely to be compound heatwaves closely related to drought. Moreover, the soil moisture–temperature coupling strength increased in regions with strong increases in DHW through phase transitions of both temperature and heat anomalies that determine the coupling strength. As the soil moisture decreases, the probability density of low evapotranspiration increases through evaporative heat absorption. This leads to increase evaporative stress and eventually amplify DHW since the late 1990s. In particular, seasonal changes in soil moisture and evapotranspiration between spring and summer contributed to the amplification of DHW by enhancing land-atmosphere interaction.

The influence of soil dry-out on the record-breaking hot 2013/2014 summer in Southeast Brazil

The 2013/2014 summer in Southeast Brazil was marked by historical unprecedented compound dry and hot (CDH) conditions with profound socio-economic impacts. The synoptic drivers for this event have already been analyzed, and its occurrence within the context of the increasing trend of CDH conditions in the area evaluated. However, so far, the causes for these record temperatures remain poorly understood. Here, a detailed characterization of the 2013/2014 austral summer season over Southeast Brazil is proposed, emphasizing the role played by land–atmosphere interactions in temperature escalation. We demonstrate that a strong soil moisture–temperature coupling regime promoted record-breaking temperatures levels exceeding almost 5 °C over the previous highest record, and played a key role in triggering an outstanding ‘mega-heatwave’ that lasted for a period of around 20 days. This pronounced soil desiccation occurred within a current climate change trend defined by drier and hotter conditions in the region. The soil dry-out, coupled with strong radiative processes and low entrainment of cooler air masses through mesoscale sea-breeze circulation processes, led to a water-limited regime and to an enhancement of sensible heat fluxes that, ultimately, resulted in a sharp increase of surface temperatures.

Contribution of soil moisture variations to high temperatures over different climatic regimes

The coupling of soil moisture to climatic variables highly depends on soil moisture variability. Therefore, the activities affecting the soil moisture availability and dynamics such as land use/cover change and agricultural practices influence land-atmosphere interactions. Using soil moisture proxies, modeling studies have proven significant coupling of soil water variations to near-surface atmospheric temperature in some regions. However, these works have mostly applied the precipitation-based indices at a specific time scale. In the present study, the concurrent and lagged associations of the soil wetness variations and the high temperature index (HTI) across different climates in Iran were evaluated using Spearman’s rank test. Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) calculated at one-month and six-month scales were employed as soil moisture surrogates. When seasonal aridity index (AI) range was from 0.2 to 1.0 (transitional condition), SPEI1 and SPI1 were correlated significantly (p < 0.05) with HTI at 83.0 and 42.4 % of cases, respectively. However, when AI was below 0.2 (water-limited condition) or over 2.0 (energy-limited condition), the topsoil moisture indices showed an insignificant association with HTI at the majority of cases. A significant negative association existed between SPEI6 and HTI at most dry cases in which soil surface is dry but subsoil appears not to be fully depleted. Therefore, the topsoil and subsoil moisture variations are likely to affect high temperature occurrence under transitional and dry conditions, respectively. The insignificant lagged correlations found for most areas indicate poor linear relationship between high temperature occurrence and soil water dynamics in the preceding month over the study area. Furthermore, when AI exceed 0.2, ENSO-related soil drought is likely to cause a stronger soil moisture-temperature coupling. Overall, the role of evapotranspiration and soil moisture depth should be considered for assessing soil moisture dynamics and land-atmosphere interactions. Our findings may be helpful for adopting soil moisture-based adaptive measures to negate the impacts of high temperatures on agricultural products.

Coupling of Soil Moisture and Air Temperature from Multiyear Data During 1980–2013 over China

Soil moisture is an important parameter in land surface processes, which can control the surface energy and water budgets and thus affect the air temperature. Studying the coupling between soil moisture and air temperature is of vital importance for forecasting climate change. This study evaluates this coupling over China from 1980–2013 by using an energy-based diagnostic method, which represents the momentum, heat, and water conservation equations in the atmosphere, while the contributions of soil moisture are treated as external forcing. The results showed that the soil moisture–temperature coupling is strongest in the transitional climate zones between wet and dry climates, which here includes Northeast China and part of the Tibetan Plateau from a viewpoint of annual average. Furthermore, the soil moisture–temperature coupling was found to be stronger in spring than in the other seasons over China, and over different typical climatic zones, it also varied greatly in different seasons. We conducted two case studies (the heatwaves of 2013 in Southeast China and 2009 in North China) to understand the impact of soil moisture–temperature coupling during heatwaves. The results indicated that over areas with soil moisture deficit and temperature anomalies, the coupling strength intensified. This suggests that soil moisture deficits could lead to enhanced heat anomalies, and thus, result in enhanced soil moisture coupling with temperature. This demonstrates the importance of soil moisture and the need to thoroughly study it and its role within the land–atmosphere interaction and the climate on the whole.

Physical Understanding of Human-Induced Changes in U.S. Hot Droughts Using Equilibrium Climate Simulations

AbstractAlthough the link between droughts and heat waves is widely recognized, how climate change affects this link remains uncertain. Here we assess how, and by how much, human-induced climate change affects summertime hot drought compound events over the contiguous United States. Results are derived by comparing hot drought statistics in long simulations of a coupled climate model (CESM1) subjected to year-1850 and year-2000 radiative forcings. Within each climate state, a strong and nonlinear dependency of heat-wave intensity on drought severity is found in water-limited regions of the southern Great Plains and southwestern United States whereas heat-wave intensity is found to be insensitive to drought severity in energy-limited regions of the northern and/or northeastern United States. Applying a statistical model that is based on pair-copula constructions, we find that anthropogenic warming leads to enhanced soil moisture–temperature coupling in water-limited areas of the southern Great Plains and/or southwestern United States and consequently amplifies the intensity of extreme heat waves during severe droughts. This strengthened coupling accounts for a substantial fraction of rising temperature extremes related to the long-term climate change in CESM1, highlighting the importance of changes in land–atmosphere feedback in a warmer climate. In contrast, coupling effects remain weak and largely unchanged in energy-limited regions, thereby yielding no appreciable contribution to heat-wave intensification over the northern and/or northeastern United States apart from the long-term warming effects.

Mesoclimate regulation induced by landscape restoration and water harvesting in agroecosystems of the horn of Africa

When changes are made in a landscape, these changes may impact on the local climate. In arid and semi-arid agroecosystems, measures such as Landscape Restoration and Water Harvesting (LRWH) are implemented in order to revert land degradation and increase agricultural yields, by means of reducing runoff losses and increasing soil moisture. The present work analyses to what extent storing soil moisture, with adequate land and water management practices, can reduce temperatures in the hot months after the rainy season in a semi-arid climate. Since it is reported that Soil Moisture (SM) deficit can enhance heatwaves in diverse regions of the world because of Soil Moisture-Temperature Coupling (SMTC), it is hypothesized that increasing soil water availability, during the dry and hot periods, can mitigate hot temperatures. The analysis was carried for Enabered catchment, in Tigray Region, Ethiopia, where the rainy season runs from June to September. Here, large scale LRWH implementation ended in 2008. Using remote sensing data, the present study evaluates (1) to what extent LRWH implementation can enhance SM conservation at agroecosystem scale; (2) to what extent LRWH implementation can mitigate temperatures in the dry season at agroecosystem scale; and (3) the evidence of SMTC effects. Results show an increased capacity of the catchment to maintain SM accumulated in the rainy season and consequent reduced temperatures. Increase of SM was especially significant for September (P < 0.01), while temperature decrease was evident in October (P < 0.01) and November (P < 0.05), with decreases of Land Surface Temperatures (LST) up to 1.74 °C A simple, parsimonious linear regression model demonstrates that SMTC is evident at catchment scale and that the implementation of LRWH measures provides a climate regulation effect in the watershed. The present work can reinforce the call for an increased adoption of water harvesting, land restoration and green water management, in order to increase the resilience of agricultural ecosystem and food security in arid and semi-arid areas.

Prediction of summer hot extremes over the middle and lower reaches of the Yangtze River valley

Substantial efforts have been made in recent decades to understand the characteristics and variations of summer hot extremes and the underlying physical processes involved. However, the seasonal prediction of summer hot extremes remains challenging. The populous middle and lower reaches of the Yangtze River valley (MLYR) in China are severely influenced by hot extremes during summer. This study presents seasonal predictions of summer hot extremes over the MLYR for the period 1979–2016 based on three preceding predictors that are closely linked to hot extremes over this region: spring soil moisture over the southeastern Indochina Peninsula (SIP); spring sea surface temperature (SST) over the western tropical Pacific (WTP); and the difference of Nino 3.4 SST data in May and the previous December. The soil moisture deficit over the SIP and warm SST over the WTP in spring, as well as the difference of Nino 3.4 SST data in May and the previous December, tend to result in positive geopotential height anomalies over the MLYR, which may favor hot extremes by enhancing downward solar radiation, subsidence warming and local soil moisture–temperature coupling associated with precipitation reduction. Using these three predictors, we demonstrate with cross validation that the temporal variations of hot extremes over the MLYR can be skillfully predicted for the study period (i.e., 1979–2016), while biases exist in the magnitude. Hindcast experiments for 2012–2016 show that high prediction skill can be achieved for the spatial patterns of hot extremes, with pattern correlation coefficients of 0.83–0.99. Our findings are expected to facilitate the practical prediction of hot extremes over the MLYR.

Soil Moisture-Temperature Coupling in a Set of Land Surface Models.

The land surface controls the partitioning of water and energy fluxes and therefore plays a crucial role in the climate system. The coupling between soil moisture and air temperature, in particular, has been shown to affect the severity and occurrence of temperature extremes and heat waves. Here we study soil moisture‐temperature coupling in five land surface models, focusing on the terrestrial segment of the coupling in the warm season. All models are run off‐line over a common period with identical atmospheric forcing data, in order to allow differences in the results to be attributed to the models' partitioning of energy and water fluxes. Coupling is calculated according to two semiempirical metrics, and results are compared to observational flux tower data. Results show that the locations of the global hot spots of soil moisture‐temperature coupling are similar across all models and for both metrics. In agreement with previous studies, these areas are located in transitional climate regimes. The magnitude and local patterns of model coupling, however, can vary considerably. Model coupling fields are compared to tower data, bearing in mind the limitations in the geographical distribution of flux towers and the differences in representative area of models and in situ data. Nevertheless, model coupling correlates in space with the tower‐based results (r = 0.5–0.7), with the multimodel mean performing similarly to the best‐performing model. Intermodel differences are also found in the evaporative fractions and may relate to errors in model parameterizations and ancillary data of soil and vegetation characteristics.

The Role of Soil Moisture–Atmosphere Interaction on Future Hot Spells over North America as Simulated by the Canadian Regional Climate Model (CRCM5)

Soil moisture–atmosphere interactions play a key role in modulating climate variability and extremes. This study investigates how soil moisture–atmosphere coupling may affect future extreme events, particularly the role of projected soil moisture in modulating the frequency and maximum duration of hot spells over North America, using the fifth-generation Canadian Regional Climate Model (CRCM5). With this objective, CRCM5 simulations, driven by two coupled general circulation models (MPI-ESM and CanESM2), are performed with and without soil moisture–atmosphere interactions for current (1981–2010) and future (2071–2100) climates over North America, for representative concentration pathways (RCPs) 4.5 and 8.5. Analysis indicates that, in future climate, the soil moisture–temperature coupling regions, located over the Great Plains in the current climate, will expand farther north, including large parts of central Canada. Results also indicate that soil moisture–atmosphere interactions will play an important role in modulating temperature extremes in the future by contributing more than 50% to the projected increase in hot-spell days over the southern Great Plains and parts of central Canada, especially for the RCP4.5 scenario. This higher contribution of soil moisture–atmosphere interactions to the future increases in hot-spell days for RCP4.5 is related to the fact that the projected decrease in soil moisture caused the soil to remain in a transitional regime between wet and dry state that is conducive to soil moisture–atmosphere coupling. For the RCP8.5 scenario, on the other hand, the future projected soil state over the southern United States and northern Mexico is too dry to have an impact on evapotranspiration and therefore on temperature.

Multi‐decadal variability of soil moisture–temperature coupling over the contiguous United States modulated by Pacific and Atlantic sea surface temperatures

ABSTRACTRegions of strong land–atmosphere coupling are often depicted as static in time. However, the mechanisms through which the land surface impacts atmospheric conditions vary on sub‐daily to multi‐decadal timescales. Therefore, characterizing the long‐term variability of land–atmosphere interactions may provide a means of predicting when surface‐induced extreme temperature events will be more or less likely to occur. We evaluate the coupling strength between soil moisture, as represented by in situ observations and 1‐month Standardized Precipitation Index (SPI), and subsequent monthly maximum temperature (TMAX) over the contiguous United States. We find that the utility of SPI as a proxy for soil moisture anomalies is limited to the summer, as the correlations between SPI and TMAX are not significantly related in the other seasons. We examine the variability in summer SPI–TMAX coupling in four regions of the United States. In general, we find the strongest relationships between SPI and TMAX in the Southern Great Plains. However, our results demonstrate that the coupling strength varies considerably over time in most regions of the United States. The long‐term variability in SPI–TMAX coupling strength is strongly related to the Pacific Decadal Oscillation in the northwest and midwest United States, and the Atlantic Multidecadal Oscillation in the southeast United States The results of this study suggest that land–atmosphere coupling in the contiguous United States is modulated by multi‐decadal oscillations in Pacific and Atlantic sea surface temperatures.

Modulation of summer monsoon sub-seasonal surface air temperature over India by soil moisture-temperature coupling

The influence of soil moisture on the sub-seasonal warmer surface air temperature anomalies during drier soil conditions associated with break spells in the Indian summer monsoon precipitation is explored using observations. The multi-model analysis of land surface states and fluxes available from the Second Global Soil Wetness Project (GSWP-2) are found useful in understanding the mechanism for this soil moisture-temperature coupling on sub-seasonal timescales. The analysis uses a soil moisture-temperature coupling diagnostic computed based on linear correlations of daily fields. It is shown that the summer surface air temperature variations are linked to intraseasonal variations of the Indian monsoon precipitation, which control the land-climate coupling by modulating the soil moisture variations. Strong coupling mainly occurs during dry soil states within the summer monsoon season over the transition zones between wet and dry climates of central to north-west India. In contrast, the coupling is weak for constantly wet and energy-limited evaporative regimes over eastern India during the entire summer monsoon season. This observational based analysis provided a better understanding of the linkages between the sub-seasonal dry soil states and warm conditions during the Indian summer monsoon season. A proper representation of these aspects of land-atmosphere interactions in weather and climate models used for sub-seasonal and seasonal monsoon forecasting could be critical for several applications, in particular agriculture. The soil moisture-temperature coupling diagnostic used in this study will be a useful metric for evaluating the performance of weather and climate models.

Contributions of soil moisture interactions to climate change in the tropics in the GLACE–CMIP5 experiment

Contributions of changes in soil moisture to the projected climate change in the tropics at the end of the twenty first century are quantified using the simulations from five different global climate models, which contributed to the GLACE–CMIP5 experiment. “GLACE” refers to the Global Land Atmosphere Coupling Experiment and “CMIP5” to the fifth phase of the Coupled Model Intercomparison Project. This is done by relating the overall projected changes in climate to those changes in climate that are related to the projected changes in soil moisture. The study focusses on two particular aspects of the interactions of the soil moisture with climate, the soil moisture–temperature coupling and the soil moisture–precipitation coupling. The simulations show distinct future changes in soil moisture content in the tropics, with a general tendency of increases in the central parts of the tropics and decreases in the subtropics. These changes are associated with corresponding changes in precipitation, with an overall tendency of an approximate 5 % change in soil moisture in response to a precipitation change of 1 mm/day. All five individual models are characterized by the same qualitative behaviour, despite differences in the strength and in the robustness of the coupling between soil moisture and precipitation. The changes in soil moisture content are found to give important contributions to the overall climate change in the tropics. This is in particularly the case for latent and sensible heat flux, for which about 80 % of the overall changes are related to soil moisture changes. Similarly, about 80 % of the overall near-surface temperature changes (with the mean temperature changes in the tropics removed) are associated with soil moisture changes. For precipitation, on the other hand, about 30–40 % of the overall change can be attributed to soil moisture changes. The robustness of the contributions of the soil moisture changes to the overall climate change varies between the different meteorological variables, with a high degree of robustness for the surface energy fluxes, a fair degree for near-surface temperature and a low degree for precipitation. Similar to the coupling between soil moisture and precipitation, the five individual models are characterized by the same qualitative behaviour, albeit differences in the strength and the robustness of the contributions of the soil moisture change. This suggests that despite the regional differences in the projected climate changes between the individual models, the basic physical mechanisms governing the soil moisture–temperature coupling and the soil moisture–precipitation coupling work similarly in these models. The experiment confirms the conceptual models of the soil moisture–temperature coupling and the soil moisture–precipitation coupling described Seneviratne et al. (Earth-Sci Rev 99:125–161, 2010). For the soil moisture–temperature coupling, decreases (increases) in soil moisture lead to increasing (decreasing) sensible heat fluxes and near-surface temperatures. The soil moisture–precipitation coupling is part of a positive feedback loop, where increases (decreases) in precipitation cause increases (decreases) in soil moisture content, which, in turn, lead to increasing (decreasing) latent heat fluxes and precipitation.

Using remotely sensed soil moisture for land–atmosphere coupling diagnostics: The role of surface vs. root-zone soil moisture variability

Hot extremes have been shown to be induced by antecedent surface moisture deficits in several regions. While most previous studies on this topic relied on modeling results or precipitation-based surface moisture information (particularly the standardized precipitation index, SPI), we use here a new merged remote sensing soil moisture product that combines active and passive microwave sensors to investigate the relation between the number of hot days (NHD) and preceding soil moisture deficits. Along with analyses of temporal variabilities of surface vs. root-zone soil moisture, this sheds light on the role of different soil depths for soil moisture–temperature coupling.The global patterns of soil moisture–NHD correlations from remote sensing data and from SPI as used in previous studies are comparable. Nonetheless, the strength of the relationship appears underestimated with remote sensing-based soil moisture compared to SPI-based estimates, particularly in regions of strong soil moisture–temperature coupling. This is mainly due to the fact that the temporal hydrological variability is less pronounced in the remote sensing data than in the SPI estimates in these regions, and large dry/wet anomalies appear underestimated. Comparing temporal variabilities of surface and root-zone soil moisture in in-situ observations reveals a drop of surface-layer variability below that of root-zone when dry conditions are considered. This feature is a plausible explanation for the observed weaker relationship of remote sensing-based soil moisture (representing the surface layer) with NHD as it leads to a gradual decoupling of the surface layer from temperature under dry conditions, while root-zone soil moisture sustains more of its temporal variability.

Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We find a negative relationship between these controls that weakens the forecast skills, nevertheless there is a middle ground between both controls in several catchments, as shown by our results.

Diagnosing the Strength of Land–Atmosphere Coupling at Subseasonal to Seasonal Time Scales in Asia

Abstract This paper focuses on diagnosing the strength of soil moisture–atmosphere coupling at subseasonal to seasonal time scales over Asia using two different approaches: the conditional correlation approach [applied to the Global Land Data Assimilation System (GLDAS) data, the Climate Forecast System Reanalysis (CFSR) data, and output from the regional climate model, version 4 (RegCM4)] and the Global Land–Atmosphere Coupling Experiment (GLACE) approach applied to the RegCM4. The conditional correlation indicators derived from the model output and the two observational/reanalysis datasets agree fairly well with each other in the spatial pattern of the land–atmosphere coupling signal, although the signal in CFSR data is stronger and spatially more extensive than the GLDAS data and the RegCM4 output. Based on the impact of soil moisture on 2-m air temperature, the land–atmosphere coupling hotspots common to all three data sources include the Indochina region in spring and summer, the India region in summer and fall, and north-northeastern China and southwestern Siberia in summer. For precipitation, all data sources produce a weak and spatially scattered signal, indicating the lack of any strong coupling between soil moisture and precipitation, for both precipitation amount and frequency. Both the GLACE approach and the conditional correlation approach (applied to all three data sources) identify evaporation and evaporative fraction as important links for the coupling between soil moisture and precipitation/temperature. Results on soil moisture–temperature coupling strength from the GLACE-type experiment using RegCM4 are in good agreement with those from the conditional correlation analysis applied to output from the same model, despite substantial differences between the two approaches in the terrestrial segment of the land–atmosphere coupling.

Summer Land–Atmosphere Coupling Strength over the United States: Results from the Regional Climate Model RegCM4–CLM3.5

Abstract This study investigates the land–atmosphere coupling strength during summer over the United States using the Regional Climate Model version 4 (RegCM4)–Community Land Model version 3.5 (CLM3.5). First, a 10-yr simulation driven with reanalysis lateral boundary conditions (LBCs) is conducted to evaluate the model performance. The model is then used to quantify the land–atmosphere coupling strength, predictability, and added forecast skill (for precipitation and 2-m air temperature) attributed to realistic land surface initialization following the Global Land–Atmosphere Coupling Experiment (GLACE) approaches. Similar to previous GLACE results using global climate models (GCMs), GLACE-type experiments with RegCM4 identify the central United States as a region of strong land–atmosphere coupling, with soil moisture–temperature coupling being stronger than soil moisture–precipitation coupling, and confirm that realistic soil moisture initialization is more promising in improving temperature forecasts than precipitation forecasts. At a 1–15-day lead, the added forecast skill reflects predictability (or land–atmosphere coupling strength) indicating that that model can capture the realistic land–atmosphere coupling at a short time scale. However, at a 16–30-day lead, predictability cannot translate to added forecast skill, implying that the coupling at the longer time scale may not be represented well in the model. In addition, comparison of results from GLACE2-type experiments with RegCM4 driven by reanalysis LBCs and those driven by GCM LBCs suggest that the intrinsic land–atmosphere coupling strength within the regional model is the dominant factor for the added forecast skill at a 1–15-day lead, while the impact of LBCs from the GCM may play a dominant role in determining the signal of added forecast skill in the regional model at a 16–30-day lead. It demonstrates the complexities of using regional climate model for GLACE-type studies.