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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]

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]

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]

Soil moisture anomalies within the root zone (roughly, soil depths down to ~0.4 m) typically persist only a few months. Consequently, land surface–related climate predictability research has often focused on subseasonal to seasonal time scales. However, in this study of multidecadal in situ datasets and land data assimilation products, we find that root zone soil moisture anomalies can recur several or more seasons after they were initiated, indicating potential interannual predictability. Lead–lag correlations show that this recurrence often happens during one fixed season and also seems related to the greater memory of soil moisture anomalies within the layer beneath the root zone, with memory on the order of several months to over a year. That is, in some seasons, notably spring and summer when the vertical soil water potential gradient reverses sign throughout much of North America, deeper soil moisture anomalies appear to return to the surface, thereby restoring an earlier root zone anomaly that had decayed. We call this process "reemergence," in analogy with a similar seasonally varying process (with different underlying physics) providing winter-to-winter memory to the extratropical ocean surface layer. Pronounced spatial and seasonal dependence of soil moisture reemergence is found that is frequently, but not always, robust across datasets. Also, some of its aspects appear sensitive to spatial and temporal sampling, especially within the shorter available in situ datasets, and to precipitation variability. Like its namesake, soil moisture reemergence may enhance interannual-to-decadal variability, notably of droughts. Its detailed physics and role within the climate system, however, remain to be understood. [ABSTRACT FROM AUTHOR]

The climate system model of the National Center for Atmospheric Research is used to examine the predictability arising from the land surface initialization of seasonal climate ensemble forecasts in current, preindustrial, and projected future settings. Predictability is defined in terms of the model's ability to predict its own interannual variability. Predictability from the land surface in this model is relatively weak compared to estimates from other climate models but has much of the same spatial and temporal structure found in previous studies. Several factors appear to contribute to the weakness, including a low correlation between surface fluxes and subsurface soil moisture, less soil moisture memory (lagged autocorrelation) than other models or observations, and relative insensitivity of the atmospheric boundary layer to surface flux variations. Furthermore, subseasonal cyclical behavior in plant phenology for tropical grasses introduces spurious unrealistic predictability at low latitudes during dry seasons. Despite these shortcomings, intriguing changes in predictability are found. Areas of historical land use change appear to have experienced changes in predictability, particularly where agriculture expanded dramatically into the Great Plains of North America, increasing land-driven predictability there. In a warming future climate, land-atmosphere coupling strength generally increases, but added predictability does not always follow; many other factors modulate land-driven predictability. [ABSTRACT FROM AUTHOR]

A process-based, semianalytic prototype model for understanding large-scale land-atmosphere coupling is developed here. The metric for quantifying the coupling is the sensitivity of precipitation P to soil moisture W, . For a range of prototype parameters typical of conditions found over tropical or summertime continents, the sensitivity measure exhibits a broad minimum at intermediate soil moisture values. This minimum is attributed to a trade-off between evaporation (or evapotranspiration) E and large-scale moisture convergence across the range of soil moisture states. For water-limited, low soil moisture conditions, is dominated by evaporative sensitivity , reflecting high potential evaporation Ep arising from relatively warm surface conditions and a moisture-deficient atmospheric column under dry surface conditions. By contrast, under high soil moisture (or energy limited) conditions, becomes slightly negative as Ep decreases. However, because convergence and precipitation increase strongly with decreasing (drying) moisture advection, while soil moisture slowly saturates, is large. Variation of key parameters is shown to impact the magnitude of , for example, increasing the time scale for deep convective adjustment lowers at a given W, especially on the moist side of the profile where convergence dominates. While the prototype's applicability for direct quantitative comparison with either observations or models is clearly limited, it nonetheless demonstrates how the complex interplay of surface turbulent and column radiative fluxes, deep convection, and horizontal and vertical moisture transport influences the coupling of the land surface and atmosphere that may be expected to occur in either more realistic models or observations. [ABSTRACT FROM AUTHOR]

This study examines the sensitivity of the global climate to land surface processes (LSP) using an atmospheric general circulation model both uncoupled (with prescribed SSTs) and coupled to an oceanic general circulation model. The emphasis is on the interactive soil moisture and vegetation biophysical processes, which have first-order influence on the surface energy and water budgets. The sensitivity to those processes is represented by the differences between model simulations, in which two land surface schemes are considered: 1) a simple land scheme that specifies surface albedo and soil moisture availability and 2) the Simplified Simple Biosphere Model (SSiB), which allows for consideration of interactive soil moisture and vegetation biophysical process. Observational datasets are also employed to assess the extent to which results are realistic. The mean state sensitivity to different LSP is stronger in the coupled mode, especially in the tropical Pacific. Furthermore, the seasonal cycle of SSTs in the equatorial Pacific, as well as the ENSO frequency, amplitude, and locking to the seasonal cycle of SSTs, is significantly modified and more realistic with SSiB. This outstanding sensitivity of the atmosphere-ocean system develops through changes in the intensity of equatorial Pacific trades modified by convection over land. The results further demonstrate that the direct impact of land-atmosphere interactions on the tropical climate is modified by feedbacks associated with perturbed oceanic conditions ('indirect effect' of LSP). The magnitude of such an indirect effect is strong enough to suggest that comprehensive studies on the importance of LSP on the global climate have to be made in a system that allows for atmosphere-ocean interactions. [ABSTRACT FROM AUTHOR]

The Global Land–Atmosphere Coupling Experiment (GLACE) built a framework to estimate the strength of the land–atmosphere interaction across many weather and climate models. Within this framework, GLACE-type experiments are performed with a single atmospheric model coupled to three different land models. The precipitation time series is decomposed into three frequency bands to investigate the large-scale connection between external forcing, precipitation variability and predictability, and land–atmosphere coupling strength. It is found that coupling to different land models or prescribing subsurface soil moisture does not change the global pattern of precipitation predictability and variability too much. However, the regional impact of soil moisture can be highlighted by calculating the land–atmosphere coupling strength, which shows very different patterns for the three models. The estimated precipitation predictability and land–atmosphere coupling strength is mainly associated with the low-frequency component of precipitation (periods beyond 3 weeks). Based on these findings, the land–atmosphere coupling strength is conceptually decomposed into the impact of low-frequency external forcing and the impact of soil moisture. Because most models participating in GLACE have overestimated the low-frequency component of precipitation, a calibration to the GLACE-estimated land–atmosphere coupling strength is performed. The calibrated coupling strength is generally weaker, but the global pattern does not change much. This study provides an important clarification of land–atmosphere coupling strength and increases the understanding of the land–atmosphere interaction. [ABSTRACT FROM AUTHOR]