Global Land Atmosphere Coupling Experiment Research Articles

Reassessment of land–atmosphere interactions over India during summer monsoon using state-of-the-art regional climate models

The evaluation and characteristics of land-surface processes over the Indian Summer Monsoon (ISM) region are studied using Dirmeyer's two-legged land-atmosphere coupling metrics in regional climate modelling system. Different land-atmosphere coupling metrics are used for assessing the “hot-spots” of land atmosphere feedback over the Indian subcontinent. The model simulations are performed using regional climate model (RCM)—RegCMv4.0, 4.2 and 4.4.5.10 at different horizontal resolutions. The monthly soil wetness climatology over India is calculated using European Space Agency (ESA) datasets. Maximum soil moisture(SM) is found over the western part of central India during June–September. The results from RCM simulations (RegCMv4.0, 4.2 and 4.4.5.10) indicate more soil wetness, systematically (over-predicted) over North India, Indo-Gangetic plains and central India during June, July, August and September, implying that model soil wetness is driven by precipitation minus evapotranspiration (P-E). The role of aerosols in land–atmosphere interactions along with the impact of mixed convective parameterization schemes over ocean and land on modelling SM and land–atmosphere interactions is also addressed. The spatial and temporal variation of atmospheric and terrestrial coupling indices during ISM regime concludes that May, June, July and August are the prime months of land–atmosphere interactions over central and north-west India reiterating results from previous GLACE (The Global Land–Atmosphere Coupling Experiment) studies. Model simulations also indicate that during the ISM season the terrestrial segment of land–atmosphere coupling (i.e. terrestrial coupling index of soil moisture, SM) from SM to latent heat flux varies around 35–40 W m−2, while the atmospheric segment of coupling (i.e. atmospheric coupling index of precipitation) from latent heat flux to precipitation modulates around 4–6 mm/day. Aerosols are found to influence land-atmosphere interactions over north-west India by modulating net radiation. More in-situ observations of land surface variables are required for verification of land-atmospheric interactions (along with impact of aerosols) using RCMs.

Land–atmosphere feedbacks exacerbate concurrent soil drought and atmospheric aridity

Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land-atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture-precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land-atmosphere feedbacks is projected to increase in the 21st century. Importantly, land-atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.

A theoretical approach to assess soil moisture–climate coupling across CMIP5 and GLACE-CMIP5 experiments

Abstract. Terrestrial climate is influenced by various land–atmosphere interactions that involve numerous land surface state variables. In several regions on Earth, soil moisture plays an important role for climate via its control on the partitioning of net radiation into sensible and latent heat fluxes; consequently, soil moisture also impacts on temperature and precipitation. The Global Land–Atmosphere Coupling Experiment–Coupled Model Intercomparison Project phase 5 (GLACE-CMIP5) aims to quantify the impact of soil moisture on these important climate variables and to trace the individual coupling mechanisms. GLACE-CMIP5 provides experiments with different soil moisture prescriptions that can be used to isolate the effect of soil moisture on climate. Using a theoretical framework that relies on the distinct relation of soil moisture with evaporative fraction (the ratio of latent heat flux over net radiation) in different soil moisture regimes, the climate impact of the soil moisture prescriptions in the GLACE-CMIP5 experiments can be emulated and quantified. The framework-based estimation of the soil moisture effect on the evaporative fraction agrees very well with estimations obtained directly from the GLACE-CMIP5 experiments (pattern correlation of 0.85). Moreover, the soil moisture effect on the daily maximum temperature is well captured in regions where soil moisture exerts a strong control on latent heat fluxes. The theoretical approach is further applied to quantify the soil moisture contribution to the projected change of the temperature on the hottest day of the year, confirming recent estimations by other studies. Finally, GLACE-style soil moisture prescriptions are emulated in an extended set of CMIP5 models. The results indicate consistency between the soil moisture–climate coupling strength estimated with the GLACE-CMIP5 and the CMIP5 models. Although the theoretical approach is only designed to capture the local soil moisture–climate coupling strength, it can also help to distinguish non-local from local soil moisture–atmosphere feedbacks where sensitivity experiments (such as GLACE-CMIP5) are available. Overall, the theoretical framework-based approach presented here constitutes a simple and powerful tool to quantify local soil moisture–climate coupling in both the GLACE-CMIP5 and CMIP5 models that can be applied in the absence of dedicated sensitivity experiments.

Global Effects of Superparameterization on Hydrothermal Land‐Atmosphere Coupling on Multiple Timescales

AbstractMany conventional General Circulation Models (GCMs) in the Global Land‐Atmosphere Coupling Experiment (GLACE) tend to produce what is now recognized as overly strong land‐atmosphere (L‐A) coupling. We investigate the effects of cloud Superparameterization (SP) on L‐A coupling on timescales beyond diurnal where it has been recently shown to have a favorable muting effect hydrologically. Using the Community Atmosphere Model v3.5 (CAM3.5) and its Superparameterized counterpart SPCAM3.5, we conducted soil moisture interference experiments following the GLACE and Atmospheric Model Intercomparison Project (AMIP) protocols. The results show that, on weekly‐to‐subseasonal timescales, SP also mutes hydrologic L‐A coupling. This is detectable globally, and happens through the evapotranspiration‐precipitation segment. But on seasonal timescales, SP does not exhibit detectable effects on hydrologic L‐A coupling. Two robust regional effects of SP on thermal L‐A coupling have also been explored. Over the Arabian Peninsula, SP reduces thermal L‐A coupling through a straightforward control by mean rainfall reduction. More counterintuitively, over the Southwestern US and Northern Mexico, SP enhances the thermal L‐A coupling in a way that is independent of rainfall and soil moisture. This signal is associated with a systematic and previously unrecognized effect of SP that produces an amplified Bowen ratio, and is detectable in multiple SP model versions and experiment designs. In addition to amplifying the present‐day Bowen ratio, SP is found to amplify the climate sensitivity of Bowen ratio as well, which likely plays a role in influencing climate change predictions at the L‐A interface.

Soil Moisture Influence on Seasonality and Large-Scale Circulation in Simulations of the West African Monsoon

Prior studies have highlighted West Africa as a regional hotspot of land–atmosphere coupling. This study focuses on the large-scale influence of soil moisture variability on the mean circulation and precipitation in the West African monsoon. A suite of six models from the Global Land–Atmosphere Coupling Experiment (GLACE)-CMIP5 is analyzed. In this experiment, model integrations were performed with soil moisture prescribed to a specified climatological seasonal cycle throughout the simulation, which severs the two-way coupling between soil moisture and the atmosphere. Comparison with the control (interactive soil moisture) simulations indicates that mean June–September monsoon precipitation is enhanced when soil moisture is prescribed. However, contrasting behavior is evident over the seasonal cycle of the monsoon, with core monsoon precipitation enhanced with prescribed soil moisture but early-season precipitation reduced, at least in some models. These impacts stem from the enhancement of evapotranspiration at the dry poleward edge of the monsoon throughout the monsoon season, when soil moisture interactivity is suppressed. The early-season decrease in rainfall with prescribed soil moisture is associated with a delayed poleward advancement of the monsoon, which reflects the relative cooling of the continent from enhanced evapotranspiration, and thus a reduced land–ocean thermal contrast, prior to monsoon onset. On the other hand, during the core/late monsoon season, surface evaporative cooling modifies meridional temperature gradients and, through these gradients, alters the large-scale circulation: the midlevel African easterly jet is displaced poleward while the low-level westerlies are enhanced; this enhances precipitation. These results highlight the remote impacts of soil moisture variability on atmospheric circulation and precipitation in West Africa.

Land–Atmosphere Coupling at the Southern Great Plains Atmospheric Radiation Measurement (ARM) Field Site and Its Role in Anomalous Afternoon Peak Precipitation

Abstract The multimodel Global Land–Atmosphere Coupling Experiment (GLACE) identified the semiarid Southern Great Plains (SGP) as a hotspot for land–atmosphere (LA) coupling and, consequently, land-derived temperature and precipitation predictability. The area including and surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) SGP Climate Research Facility has in particular been well studied in the context of LA coupling. Observation-based studies suggest a coupling signal that is much weaker than modeled, if not elusive. Using North American Regional Reanalysis and North American Land Data Assimilation System data, this study provides a 36-yr (1979–2014) climatology of coupling for ARM-SGP that 1) unifies prior interdisciplinary efforts and 2) isolates the origin of the (weak) coupling signal. Specifically, the climatology of a prominent convective triggering potential–low-level humidity index (CTP–HIlow) coupling classification is linked to corresponding synoptic–mesoscale weather and atmospheric moisture budget analyses. The CTP–HIlow classification defines a dry-advantage regime for which convective triggering is preferentially favored over drier-than-average soils as well as a wet-advantage regime for which convective triggering is preferentially favored over wetter-than-average soils. This study shows that wet-advantage days are a result of horizontal moisture flux convergence over the region, and conversely, dry-advantage days are a result of zonal and vertical moisture flux divergence. In this context, the role of the land is nominal relative to that of atmospheric forcing. Surface flux partitioning, however, can play an important role in modulating diurnal precipitation cycle phase and amplitude and it is shown that soil moisture and sensible heat flux are significantly correlated with both occurrence and intensity of afternoon peak precipitation.

Modulation of Land-Use Change Impacts on Temperature Extremes via Land–Atmosphere Coupling over Australia

Abstract The role of land–atmosphere coupling in modulating the impact of land-use change (LUC) on regional climate extremes remains uncertain. Using the Weather and Research Forecasting Model, this study combines the Global Land–Atmosphere Coupling Experiment with regional LUC to assess the combined impact of land–atmosphere coupling and LUC on simulated temperature extremes. The experiment is applied to an ensemble of planetary boundary layer (PBL) and cumulus parameterizations to determine the sensitivity of the results to model physics. Results show a consistent weakening in the soil moisture–maximum temperature coupling strength with LUC irrespective of the model physics. In contrast, temperature extremes show an asymmetric response to LUC dependent on the choice of PBL scheme, which is linked to differences in the parameterization of vertical transport. This influences convective precipitation, contributing a positive feedback on soil moisture and consequently on the partitioning of the surface turbulent fluxes. The results suggest that the impact of LUC on temperature extremes depends on the land–atmosphere coupling that in turn depends on the choice of PBL. Indeed, the sign of the temperature change in hot extremes resulting from LUC can be changed simply by altering the choice of PBL. The authors also note concerns over the metrics used to measure coupling strength that reflect changes in variance but may not respond to LUC-type perturbations.

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.

Interannual Coupling between Summertime Surface Temperature and Precipitation over Land: Processes and Implications for Climate Change*

Abstract Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture–atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature–precipitation correlations using simulations from the Global Land–Atmosphere Coupling Experiment–phase 5 of the Coupled Model Intercomparison Project (GLACE-CMIP5) multimodel experiment. The analyses are based on simulations with five climate models, which were integrated with prescribed (noninteractive) and with interactive soil moisture over the period 1950–2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture–atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature–precipitation correlation. On longer time scales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near-surface climate: in all models, in the regions of strongest temperature–precipitation anticorrelation on interannual time scales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil moisture–atmosphere interactions.

The role of land cover change in modulating the soil moisture‐temperature land‐atmosphere coupling strength over Australia

AbstractThe severity of recent droughts and heat waves have been linked to land‐atmosphere feedbacks. However, investigations of how these feedbacks are influenced by land use and land cover change (LULCC) are limited. Using the Weather and Research Forecasting model with an ensemble framework of planetary boundary layer and cumulus parameterization schemes, we combine the Global Land Atmosphere Coupling Experiment methodology with LULCC to assess how LULCC affects land‐atmosphere coupling strength for maximum temperature over Australia. We find a statistically significant decrease in soil moisture‐temperature coupling over regions where forest changes to crops, which was consistent across the implemented model physics and background climate. This was associated with a decrease in the ensemble mean variance suggesting that LULCC influences regional climate variability via changes in the regional scale hydrology and surface energy balance. Our results highlight the need to consider land surface changes and coupling strength in combination, rather than in isolation.

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.

Interannual Variability of Land–Atmosphere Coupling Strength

Abstract Recent studies in the Global Land–Atmosphere Coupling Experiment (GLACE) established a framework to estimate the extent to which anomalies in the land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. Within this framework, a multiyear GLACE-type experiment is carried out with a coupled land–atmosphere general circulation model to examine the interannual variability of land–atmosphere coupling strength. Soil wetness with intermediate values are in the range at which rainfall generation, near-surface air temperature, and surface turbulent fluxes are most sensitive to soil moisture anomalies, and thus, land–atmosphere coupling strength peaks in this range. As a result, the “hot spots” with strong land–atmosphere coupling strength appear in regions with intermediate climatological soil wetness (e.g., transition zones between dry and wet climates), consistent with previous studies. Land–atmosphere coupling strength experiences significant year-to-year variation because of interannual variability of soil moisture and the local spatiotemporal evolution of hydrologic regime. Coupling strength over areas with dry (wet) climate is enhanced during wet (dry) years since the resultant soil wetness enters into the sensitive range from a relatively insensitive range, and soil moisture can have stronger potential impact on surface turbulent fluxes and convection. On the other hand, land–atmosphere coupling strength over areas with wet (dry) climate is weakened during wet (dry) years since the soil wetness moves further away from the sensitive range. This results in a positive correlation between the land–atmosphere coupling strength and soil moisture anomalies over areas with dry climate and a negative correlation over areas with wet climate.

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.

Revisiting GLACE: Understanding the Role of the Land Surface in Land–Atmosphere Coupling

Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) established a method for quantifying and comparing the influence of soil moisture on the atmosphere in AGCMs. The models included in the GLACE intercomparison displayed a wide range in the strength of this influence, with the Met Office Hadley Centre (MOHC) Atmosphere Model, version 3 (HadAM3), being one of the weakest. Applying the GLACE method to a much developed version of the MOHC model, the atmospheric component of the Hadley Centre Global Environmental Model version 3 (HadGEM3-A), it is demonstrated that this new model has a stronger coupling signal than its predecessor. Although this increase in the coupling strength cannot be attributed to changes in the land surface representation, the existence of the stronger signal enables an investigation of the signal’s dependence on key land surface parameters. The GLACE method is applied to four HadGEM3-A experiment cases, with soil hydraulic parameters specified using two methods of calculation from two different underlying soil texture datasets. These cases show differences in their volumetric soil moisture and their level of moisture availability for transpiration. A change in moisture availability produces a change in evaporation variability in the same direction, which is a key factor affecting the overall land–atmosphere coupling strength. For HadGEM3-A the parameter changes therefore produce a clear change in the GLACE diagnostic.

A coupled soil moisture initialization scheme for the FSU/COAPS climate model

We developed a coupled soil initialization scheme for the Florida State University/Center for Ocean-Atmosphere Prediction Studies (FSU/COAPS) climate model, which is coupled to the Community Land Model version 2. This method indirectly initializes the land surface component of the climate model by assimilating precipitation in the atmospheric component. A continuous assimilation is performed while the land and atmosphere components exchange fluxes, thus keeping the coupled model in a physically consistent state, obviating the need for any correction. Comparison with in situ observations in Illinois and Oklahoma shows very good agreement with the initialized soil moisture profile. A global comparison of the initialized land surface model with the Global Soil Wetness Project 2 multi-model analysis also shows very good agreement. Short-term climate forecasts (2 weeks to 2 months), performed in conjunction with the Global Land Atmosphere Coupling Experiment, Part 2, show that initialized soil moisture conditions improve surface temperature forecasts.

A Global Intercomparison of Modeled and Observed Land–Atmosphere Coupling*

Abstract Land–atmosphere coupling strength or the degree to which land surface anomalies influence boundary layer development—and in extreme cases, rainfall—is arguably the single most fundamental criterion for evaluating hydrological model performance. The Global Land–Atmosphere Coupling Experiment (GLACE) showed that strength of coupling and its representation can affect a model’s ability to simulate climate predictability at the seasonal time scale. And yet, the lack of sufficient observations of coupling at appropriate temporal and spatial scales has made achieving “true” coupling in models an elusive goal. This study uses Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) soil moisture (SM), multisensor remote sensing (RS) evaporative fraction (EF), and Atmospheric Infrared Sounder (AIRS) lifting condensation level (LCL) to evaluate the realism of coupling in the Global Land Data Assimilation System (GLDAS) suite of land surface models (LSMs), Princeton Global Forcing Variable Infiltration Capacity model (PGF–VIC), seven global reanalyses, and the North American Regional Reanalysis (NARR) over a 5-yr period (2003–07). First, RS and modeled estimates of SM, EF, and LCL are intercompared. Then, emphasis is placed on quantifying RS and modeled differences in convective-season daily correlations between SM–LCL, SM–EF, and EF–LCL for global, regional, and conditional samples. RS is found to yield a substantially weaker state of coupling than model products. However, the rank order of basins by coupling strength calculated from RS and models do roughly agree. Using a mixture of satellite and modeled variables, a map of hybrid coupling strength was produced, which supports the findings of GLACE that transitional zones tend to have the strongest coupling.

A Revised Framework for Analyzing Soil Moisture Memory in Climate Data: Derivation and Interpretation

Abstract A revised framework for the analysis of soil moisture memory characteristics of climate models and observational data is derived from the approach proposed by Koster and Suarez. The resulting equation allows the expression of the month-to-month soil moisture autocorrelation as a function of 1) the initial soil moisture variability, 2) the (atmospheric) forcing variability over the considered time period, 3) the correlation between initial soil moisture and subsequent forcing, 4) the sensitivity of evaporation to soil moisture, and 5) the sensitivity of runoff to soil moisture. A specific new feature is the disentangling of the roles of initial soil moisture variability and forcing variability, which were both (for the latter indirectly) contributing to the seasonality term of the original formulation. In addition, a version of the framework entirely based on explicit equations for the underlying relationships (i.e., independent of soil moisture statistics at the following time step) is proposed. The validity of the derived equation is exemplified with atmospheric general circulation model (AGCM) simulations from the Global Land–Atmosphere Coupling Experiment (GLACE).

Observed Land–Atmosphere Coupling from Satellite Remote Sensing and Reanalysis

Abstract The lack of observational data for use in evaluating the realism of model-based land–atmosphere feedback signal and strength has been deemed a major obstacle to future improvements to seasonal weather prediction by the Global Land–Atmosphere Coupling Experiment (GLACE). To address this need, a 7-yr (2002–09) satellite remote sensing data record is exploited to produce for the first time global maps of predominant coupling signals. Specifically, a previously implemented convective triggering potential (CTP)–humidity index (HI) framework for describing atmospheric controls on soil moisture–rainfall feedbacks is revisited and generalized for global application using CTP and HI from the Atmospheric Infrared Sounder (AIRS), soil moisture from the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E), and the U.S. Climate Prediction Center (CPC) merged satellite rainfall product (CMORPH). Based on observations taken during an AMSR-E-derived convective rainfall season, the global land area is categorized into four convective regimes: 1) those with atmospheric conditions favoring deep convection over wet soils, 2) those with atmospheric conditions favoring deep convection over dry soils, 3) those with atmospheric conditions that suppress convection over any land surface, and 4) those with atmospheric conditions that support convection over any land surface. Classification maps are produced using both the original and modified frameworks, and later contrasted with similarly derived maps using inputs from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective Analysis for Research and Applications (MERRA). Both AIRS and MERRA datasets of CTP and HI are validated using radiosonde observations. The combinations of methods and data sources employed in this study enable evaluation of not only the sensitivity of the classification schemes themselves to their inputs, but also the uncertainty in the resultant classification maps. The findings are summarized for 20 climatic regions and three GLACE coupling hot spots, as well as zonally and globally. Globally, of the four-class scheme, regions for which convection is favored over wet and dry soils accounted for the greatest and least extent, respectively. Despite vast differences among the maps, many geographically large regions of concurrence exist. Through its ability to compensate for the latitudinally varying CTP–HI–rainfall tendency characteristics observed in this study, the revised classification framework overcomes limitations of the original framework. By identifying regions where coupling persists using satellite remote sensing this study provides the first observationally based guidance for future spatially and temporally focused studies of land–atmosphere interactions. Joint distributions of CTP and HI and soil moisture, rainfall occurrence, and depth demonstrate the relevance of CTP and HI in coupling studies and their potential value in future model evaluation, rainfall forecast, and/or hydrologic consistency applications.

The Second Phase of the Global Land–Atmosphere Coupling Experiment: Soil Moisture Contributions to Subseasonal Forecast Skill

AbstractThe second phase of the Global Land–Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multimodel “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

Land–Atmosphere Coupling Strength in the Global Forecast System

Abstract The operational coupled land–atmosphere forecast model from the National Centers for Environmental Prediction (NCEP) is evaluated for the strength and characteristics of its coupling in the water cycle between land and atmosphere. Following the protocols of the Global Land–Atmosphere Coupling Experiment (GLACE) it is found that the Global Forecast System (GFS) atmospheric model coupled to the Noah land surface model exhibits extraordinarily weak land–atmosphere coupling, much as its predecessor, the GFS–Oregon State University (OSU) coupled system. The coupling strength is evaluated by the ability of subsurface soil wetness to affect locally the time series of precipitation. The surface fluxes in Noah are also found to be rather insensitive to subsurface soil wetness. Comparison to another atmospheric model coupled to Noah as well as a different land surface model show that Noah is responsible for some of the lack of sensitivity, primarily because its thick (10 cm) surface layer dominates the variability in surface latent heat fluxes. Noah is found to be as responsive as other land surface models to surface soil wetness and temperature variations, suggesting the design of the GLACE sensitivity experiment (based only on subsurface soil wetness) handicapped the Noah model. Additional experiments, in which the parameterization of evapotranspiration is altered, as well as experiments where surface soil wetness is also constrained, isolate the GFS atmospheric model as the principal source of the weak sensitivity of precipitation to land surface states.