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Agnès Ducharne and Katia Laval

Abstract

The sensitivity of the hydrological cycle to soil water-holding capacity (WHC) is investigated using the Laboratoire de Meteorologie Dynamique General Circulation Model (LMD GCM) coupled to a land surface model (LSM). A reference simulation (REF), with WHCs equal to 150 mm globally (except in deserts where it is set to 30 mm), is compared to two perturbation simulations using datasets with realistic WHC distributions:the “available WHC” (AWC) dataset is physically consistent with the definition of WHC in the LSM and has a global average close to 150 mm; the “total WHC” (TWC) dataset is used as a secondary reference for a large WHC increase (more than a doubling from 150 mm). The average impact over land of the increase in WHC (from REF to both AWC and TWC) is an increase in annual mean evaporation, split between increased annual precipitation and decreased annual mean moisture convergence. The regional responses, however, are more complex: precipitation increases in summer over the midlatitude landmasses through the recycling of increased evaporation; in the Tropics, moisture convergence and precipitation decrease in the intertropical convergence zone and precipitation increases in the surrounding areas, both behaviors being related to the sensitivity of tropical convection to surface energy fluxes in the LMD GCM.

Two important conclusions arise from these numerical results: first, the changes in the hydrological cycle are driven through evaporation by the WHC changes realized in the hydrologically active regions (continental midlatitude and tropical rainbelts); second, WHC increase of 10% to 20% in the rainbelts induces changes in the hydrologic cycle with similar patterns and almost the same amplitude as changes resulting from an increase greater than 100%. These results are strongly conditioned to the land–atmosphere feedbacks, which can only be allowed in a GCM environment.

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Claire Magand, Agnès Ducharne, Nicolas Le Moine, and Simon Gascoin

Abstract

The Durance watershed (14 000 km2), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km2, into elementary catchments with an average area of 500 km2. The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

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Marc Stieglitz, Agnès Ducharne, Randy Koster, and Max Suarez

Abstract

The three-layer snow model of Lynch-Stieglitz is coupled to the global catchment-based land surface model of the National Aeronautics and Space Administration’s Seasonal to Interannual Prediction Project, and the combined models are used to simulate the growth and ablation of snow cover over the North American continent for the period of 1987–88. The various snow processes included in the three-layer model, such as snow melting and refreezing, dynamic changes in snow density, and snow insulating properties, are shown (through a comparison with the corresponding simulation using a much simpler snow model) to lead to an improved simulation of ground thermodynamics on the continental scale. This comparison indicates that the three-layer model, originally developed and validated at small experimental catchments, does indeed capture the important snow processes that control the growth and the ablation of continental-scale snowpack and its snow insulation capabilities.

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Paul A. Dirmeyer, Fanrong J. Zeng, Agnès Ducharne, Jean C. Morrill, and Randal D. Koster

Abstract

Evaporative fraction (EF; the ratio of latent heat flux to the sum of the latent plus sensible heat fluxes) can be measured in the field to an accuracy of about 10%. In this modeling study, the authors try to determine to what accuracy soil moisture must be known in order to simulate surface energy fluxes within this observational uncertainty and whether there is a firm relationship between the variabilities of soil moisture and surface turbulent energy fluxes. A relationship would provide information for planning the future measurement of soil moisture, the design of field experiments, and points of focus for soil model development. The authors look for relationships in three different land surface schemes using results and ancillary integrations in the Global Soil Wetness Project.

It is found that the variation of evaporative fraction as a function of soil moisture is consistent among the models and within subsets of vegetation type. In forested areas, there is high sensitivity of EF to soil moisture variations when soils are dry and there is little sensitivity in moderate to wet soils. Where vegetation is sparser, there is a more gradual decrease of EF sensitivity with a decrease in soil moisture. Bare soil desert areas behave similarly to sparsely vegetated areas but with lower peak EF. Tundra regions have a unique behavior, probably because evaporation is limited more by a lack of radiant energy at high latitudes. The results suggest that accuracy in the measurement or model simulation of soil moisture is most critical within the drier portion of the range of variability of soil moisture. It also is more important over sparsely vegetated areas, for which evapotranspiration is dependent on moisture in a shallower column of soil.

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Mehnaz Rashid, Rong-You Chien, Agnès Ducharne, Hyungjun Kim, Pat J.-F. Yeh, Christophe Peugeot, Aaron Boone, Xiaogang He, Luc Séguis, Yutaro Yabu, Moussa Boukari, and Min-Hui Lo

Abstract

A comprehensive estimation of water budget components, particularly groundwater storage (GWS) and fluxes, is crucial. In this study, we evaluate the terrestrial water budget of the Donga basin (Benin, West Africa), as simulated by three land surface models (LSMs) used in the African Monsoon Multidisciplinary Analysis Land Surface Model Intercomparison Project, phase 2 (ALMIP2): CLM4, Catchment LSM (CLSM), and Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO). All three models include an unconfined groundwater component and are driven by the same ALMIP2 atmospheric forcing from 2005 to 2008. Results show that all three models simulate substantially shallower water table depth (WTD) with smaller seasonal variations, approximately 1–1.5 m compared to the observed values that range between 4 and 9.6 m, while the seasonal variations of GWS are overestimated by all the models. These seemingly contradictory simulation results can be explained by the overly high specific yield prescribed in all models. All models achieve similar GWS simulations but with different fractions of precipitation partitioning into surface runoff, base flow, and evapotranspiration (ET), suggesting high uncertainty and errors in the terrestrial and groundwater budgets among models. The poor performances of models can be attributed to bias in the hydrological partitioning (base flow vs surface runoff) and sparse subsurface data. This analysis confirms the importance of subsurface hydrological processes in the current generation of LSMs and calls for substantial improvement in both surface water budget (which controls groundwater recharge) and the groundwater system (hydrodynamic parameters, vertical geometry).

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Manuela Grippa, Laurent Kergoat, Aaron Boone, Christophe Peugeot, Jérôme Demarty, Bernard Cappelaere, Laetitia Gal, Pierre Hiernaux, Eric Mougin, Agnès Ducharne, Emanuel Dutra, Martha Anderson, Christopher Hain, and ALMIP2 Working Group

Abstract

Land surface processes play an important role in the West African monsoon variability. In addition, the evolution of hydrological systems in this region, and particularly the increase of surface water and runoff coefficients observed since the 1950s, has had a strong impact on water resources and on the occurrence of floods events. This study addresses results from phase 2 of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project (ALMIP2), carried out to evaluate the capability of different state-of-the-art land surface models to reproduce surface processes at the mesoscale. Evaluation of runoff and water fluxes over the Mali site is carried out through comparison with runoff estimations over endorheic watersheds as well as evapotranspiration (ET) measurements. Three remote-sensing-based ET products [ALEXI, MODIS, and Global Land Evaporation Amsterdam Model (GLEAM)] are also analyzed. It is found that, over deep sandy soils, surface runoff is generally overestimated, but the ALMIP2 multimodel mean reproduces in situ measurements of ET and water stress events rather well. However, ALMIP2 models are generally unable to distinguish among the two contrasted hydrological systems typical of the study area. Employing as input a soil map that explicitly represents shallow soils improves the representation of water fluxes for the models that can account for their representation. Shallow soils are shown to be also quite challenging for remote-sensing-based ET products, even if their effect on evaporative loss was captured by the diagnostic thermal-based ALEXI. A better representation of these soils, in soil databases, model parameterizations, and remote sensing algorithms, is fundamental to improve the estimation of water fluxes in this part of the Sahel.

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Alexis Berg, Benjamin R. Lintner, Kirsten Findell, Sonia I. Seneviratne, Bart van den Hurk, Agnès Ducharne, Frédérique Chéruy, Stefan Hagemann, David M. Lawrence, Sergey Malyshev, Arndt Meier, and Pierre Gentine

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.

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Aaron Boone, Patricia de Rosnay, Gianpaolo Balsamo, Anton Beljaars, Franck Chopin, Bertrand Decharme, Christine Delire, Agnes Ducharne, Simon Gascoin, Manuela Grippa, Françoise Guichard, Yeugeniy Gusev, Phil Harris, Lionel Jarlan, Laurent Kergoat, Eric Mougin, Olga Nasonova, Anette Norgaard, Tristan Orgeval, Catherine Ottlé, Isabelle Poccard-Leclercq, Jan Polcher, Inge Sandholt, Stephane Saux-Picart, Christopher Taylor, and Yongkang Xue

The rainfall over West Africa has been characterized by extreme variability in the last half-century, with prolonged droughts resulting in humanitarian crises. There is, therefore, an urgent need to better understand and predict the West African monsoon (WAM), because social stability in this region depends to a large degree on water resources. The economies are primarily agrarian, and there are issues related to food security and health. In particular, there is a need to better understand land-atmosphere and hydrological processes over West Africa because of their potential feedbacks with the WAM. This is being addressed through a multiscale modeling approach using an ensemble of land surface models that rely on dedicated satellite-based forcing and land surface parameter products, and data from the African Multidisciplinary Monsoon Analysis (AMMA) observational field campaigns. The AMMA land surface model (LSM) Intercomparison Project (ALMIP) offline, multimodel simulations comprise the equivalent of a multimodel reanalysis product. They currently represent the best estimate of the land surface processes over West Africa from 2004 to 2007. An overview of model intercomparison and evaluation is presented. The far-reaching goal of this effort is to obtain better understanding and prediction of the WAM and the feedbacks with the surface. This can be used to improve water management and agricultural practices over this region.

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Augusto C. V. Getirana, Emanuel Dutra, Matthieu Guimberteau, Jonghun Kam, Hong-Yi Li, Bertrand Decharme, Zhengqiu Zhang, Agnes Ducharne, Aaron Boone, Gianpaolo Balsamo, Matthew Rodell, Ally M. Toure, Yongkang Xue, Christa D. Peters-Lidard, Sujay V. Kumar, Kristi Arsenault, Guillaume Drapeau, L. Ruby Leung, Josyane Ronchail, and Justin Sheffield

Abstract

Despite recent advances in land surface modeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-of-the-art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 1° spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to match monthly Global Precipitation Climatology Project (GPCP) and Global Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l’Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets and Gravity Recovery and Climate Experiment (GRACE) TWS estimates in two subcatchments of main tributaries (Madeira and Negro Rivers). At the basin scale, simulated ET ranges from 2.39 to 3.26 mm day−1 and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.

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