159 research outputs found

    Land-Atmosphere Interactions: The LoCo Perspective

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    Land-atmosphere (L-A) interactions are a main driver of Earth's surface water and energy budgets; as such, they modulate near-surface climate, including clouds and precipitation, and can influence the persistence of extremes such as drought. Despite their importance, the representation of L-A interactions in weather and climate models remains poorly constrained, as they involve a complex set of processes that are difficult to observe in nature. In addition, a complete understanding of L-A processes requires interdisciplinary expertise and approaches that transcend traditional research paradigms and communities. To address these issues, the international Global Energy and Water Exchanges project (GEWEX) Global Land-Atmosphere System Study (GLASS) panel has supported 'L-A coupling' as one of its core themes for well over a decade. Under this initiative, several successful land surface and global climate modeling projects have identified hotspots of L-A coupling and helped quantify the role of land surface states in weather and climate predictability. GLASS formed the Local L-A Coupling ('LoCo') project and working group to examine L-A interactions at the process level, focusing on understanding and quantifying these processes in nature and evaluating them in models. LoCo has produced an array of L-A coupling metrics for different applications and scales, and has motivated a growing number of young scientists from around the world. This article provides an overview of the LoCo effort, including metric and model applications, along with scientific and programmatic developments and challenges

    A Study of Land Surface Processes Using Land Surface Models Over the Little River Experimental Watershed

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    Three different land surface models (Hydrological improvements to the Simplified version of the Simple Biosphere model (HySSiB), Noah model, and Community Land Model (CLM)) were simulated on the NASA Goddard Space Flight Center’s Land Information System platform at 1-km resolution over the Little River Experimental Watershed, Georgia, and the simulated results were analyzed to address the local-scale land-atmosphere processes. All the three models simulated the soil moisture in space and time realistically. The Noah model produced higher soil moisture whereas the CLM got lower soil moisture with many dry down phases. CLM and HySSiB models were oversensitive to the atmospheric events. Different vertical discretizations of the model layers affected the soil moisture results in all the three models. The arithmetic model ensemble mean soil moisture performed reasonably well even at individual in-situ measurement sites. We found that different model schemes partitioned the incoming water and energy differently and hence produced different results for the water and energy budget parameters. In CLM, the energy and water budget parameters were very closely connected to the soil moisture (e.g., evaporation, latent, and sensible heat) change. HySSiB produced very high surface runoff and very low subsurface runoff. The Noah model did not produce much surface and subsurface runoff resulting in high surface soil moisture. We did not find much variability in Noah latent heat, sensible heat, and ground heat fluxes. From soil moisture data assimilation point of view, the mean bias removed Noah soil moisture was found to be better than other data sets

    Hydroclimatic Variability and Predictability: A Survey of Recent Research

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    Recent research in large-scale hydroclimatic variability is surveyed, focusing on five topics: (i) variability in general, (ii) droughts, (iii) floods, (iv) land-atmosphere coupling, and (v) hydroclimatic prediction. Each surveyed topic is supplemented by illustrative examples of recent research, as presented at a 2016 symposium honoring the career of Professor Eric Wood. Taken together, the recent literature and the illustrative examples clearly show that current research into hydroclimatic variability is strong, vibrant, and multifaceted

    Improved representation of the diurnal variation of warm season precipitation by an atmospheric general circulation model at a 10 km horizontal resolution

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    This study investigates the diurnal variation of the warm season precipitation simulated by the Goddard Earth Observing System version 5 atmospheric general circulation model for 2??years (2005???2006) at a horizontal resolution of 10??km. The simulation was validated with the satellite-derived Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation data and the Modern-Era Retrospective analysis for Research and Applications atmospheric reanalysis for atmospheric winds and moisture. The simulation is compared with the coarse-resolution run in 50??km to examine the impacts driven by resolution change. Overall, the 10??km model tends to reproduce the important features of the observed diurnal variation, such as the amplitude and phase at which precipitation peaks in the evening on land and in the morning over the ocean, despite an excessive amplitude bias over land. The model also reproduces the realistic propagation patterns of precipitation in the vicinity of ocean coasts and major mountains. The regional characteristics of the diurnal precipitation over two regions, the Bay of Bengal and the Great Plains in North America, are examined in detail, where the observed diurnal cycle exhibits a systematic transition in the peak phase due to the development and propagation of regional-scale convective systems. The model is able to reproduce this pattern as well as the diurnal variation of low-level wind and moisture convergence; however, it is less effective at representing the nocturnal peak of precipitation over the Great Plains. The model results suggest that increasing the horizontal resolution of the model to 10??km substantially improves the representation of the diurnal precipitation cycle. However, intrinsic model deficiencies in topographical precipitation and the accurate representation of mesoscale convective systems remain a challenge

    The role of the land-surface model for climate change projections over the Iberian Peninsula

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    The importance of land-surface processes within Regional Climate Models for accurately reproducing the present-day climate is well known. However, their role when projecting future climate is still poorly reported. Hence, this work assesses the influence of the land-surface processes, particularly the contribution of soil moisture, when projecting future changes for temperature, precipitation and wind over a complex area as the Iberian Peninsula, which, in addition, shows great sensitivity to climate change. The main signals are found for the summer season, when the results indicate a strengthening in the increases projected for both mean temperature and temperature variability as a consequence of the future intensification of the positive soil moisture-temperature feedback. The more severe warming over the inner dry Iberian Peninsula further implies an intensification of the Iberian thermal low and, thus, of the cyclonic circulation. Furthermore, the land-atmosphere coupling leads to the projection of a wider future daily temperature range, since maximum temperatures are more affected than minima, a feature absent in non-coupled simulations. Regarding variability, the areas where the land-atmosphere coupling introduces larger changes are those where the reduction in the soil moisture content is more dramatic in future simulations, i.e., the so-called transitional zones. As regards precipitation, weaker positive signals for convective precipitation and more intense negative signals for non-convective precipitation are obtained as a result of the soil moisture-atmosphere interactions. These results highlight the crucial contribution of soil moisture to climate change projections and suggest its plausible key role for future projections of extreme events

    West African Monsoon water cycle: 1. A hybrid water budget data set

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    International audienceThis study investigates the West African Monsoon water cycle with the help of a new hybrid water budget data set developed within the framework of the African Monsoon Multidisciplinary Analyses. Surface water and energy fluxes are estimated from an ensemble of land surface model simulations forced with elaborate precipitation and radiation products derived from satellite observations, while precipitable water tendencies are estimated from numerical weather prediction analyses. Vertically integrated atmospheric moisture flux convergence is estimated as a residual. This approach provides an advanced, comprehensive atmospheric water budget, including evapotranspiration, rainfall, and atmospheric moisture flux convergence, together with other surface fluxes such as runoff and net radiation. The annual mean and the seasonal cycle of the atmospheric water budget are presented and the couplings between budget terms are discussed for three climatologically distinct latitudinal bands between 6°N and 20°N. West Africa is shown to be alternatively a net source and sink region of atmospheric moisture, depending on the season (a source during the dry season and a sink during the wet season). Several limiting and controlling factors of the regional water cycle are highlighted, suggesting strong sensitivity to atmospheric dynamics and surface radiation. Some insight is also given into the underlying smaller-scale processes. The relationship between evapotranspiration and precipitation is shown to be very different between the Sahel and the regions more to the south and partly controlled by net surface radiation. Strong correlations are found between precipitation and moisture flux convergence over the whole region from daily to interannual time scales. Causality is also established between monthly mean anomalies. Hence, precipitation anomalies are preceded by moisture flux convergence anomalies and followed by moisture flux divergence and evapotranspiration anomalies. The results are discussed in comparison to other studies
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