AMMA Land Surface Model Intercomparison experiment coupled to the Community Microwave Emission Model: ALMIP-MEM

International audienceThis paper presents the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Models Intercomparison Project (ALMIP) for Microwave Emission Models (ALMIP-MEM). ALMIP-MEM comprises an ensemble of simulations of C-band brightness temperatures over West Africa for 2006. Simulations have been performed for an incidence angle of 55°, and results are evaluated against C-band satellite data from the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E). The ensemble encompasses 96 simulations, for 8 Land Surface Models (LSMs) coupled to 12 configurations of the Community Microwave Emission Model (CMEM). CMEM has a modular structure which permits combination of several parameterizations with different vegetation opacity and soil dielectric models. ALMIP-MEM provides the first intercomparison of state-of-the-art land surface and microwave emission models at regional scale. Quantitative estimates of the relative importance of land surface modeling and radiative transfer modeling for the monitoring of low-frequency passive microwave emission on land surfaces are obtained. This is of high interest for the various users of coupled land surface microwave emission models. Results show that both LSMs and microwave model components strongly influence the simulated top of atmosphere (TOA) brightness temperatures. For most of the LSMs, the Kirdyashev opacity model is the most suitable to simulate TOA brightness temperature in best agreement with the AMSR-E data. When this best microwave modeling configuration is used, all the LSMs are able to reproduce the main temporal and spatial variability of measured brightness temperature. Averaged among the LSMs, correlation is 0.67 and averaged normalized standard deviation is 0.98

Land water storage variability over West Africa estimated by GRACE and land surface models

International audienceLand water storage plays a fundamental role on the West African water cycle and has an important impact on climate and on the natural resources of this region. However, measurements of land water storage are scarcely available at regional and global scale and, especially, in poorly instrumented endhoreic regions, such as most part of the Sahel, where little useful information can be derived from river flow measurements and basins water budgets. The GRACE satellite mission provides an accurate measurement of the terrestrial gravity field variations from which land water storage variations can be derived. However, its retrieval is not straightforward and different methods are employed to do this, resulting in different water storage GRACE products. On the other hand, water storage can be estimated by land surface modelling but, again, significantly different results can be reached by using different models. In this study, land water storage by six GRACE products and soil moisture estimations by nine land surface models (run in the framework of the AMMA Land Surface Intercomparison Project, ALMIP) are evaluated over West Africa, with a particular focus on the Sahelian area. The water storage spatial distribution, including the zonal transects, its seasonal cycle and its interannual variability are analysed between 2003 and 2007. Despite the not negligible differences within the different GRACE products and within the different models' results, a general good agreement between satellite and model estimates is found over the West Africa study region. In particular, GRACE data are shown to well reproduce the water storage interannual variability over the Sahel for the 5-years study period. The comparison between satellite estimates and ALMIP results allowed the identification of processes needing improvement in the land surface models. In particular, our results point out the importance of well simulating slow water reservoirs as well as evapotraspiration during the dry season for accurate soil moisture modelling over West Africa

Variance Based Sensitivity Analysis of FLake Lake Model for Global Land Surface Modeling

International audienceGiven the ever increasing spatial resolution of climate models and the significant role of lakes on the regional climate, it becomes important to represent water bodies in climate models. Such developments have started in the IPSL (Institut Pierre Simon Laplace) climate model and its land surface component, ORganizing Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE), with the Freshwater Lake model, FLake. To answer the questions raised by these new developments, such as the lake differentiation and related model parameters, we analyze spatial distributions of lake characteristics in the whole world to perform a global sensitivity analysis of the FLake parameters. As a result, three different climates and four lake depth configurations were selected as test cases. The Sobol method as sensitivity analysis based on variance decomposition was chosen to rank parameters impact on the model output, that is, lake surface water temperature, latent and sensible heat fluxes. We focus on the 11 parameters of the FLake model, which are the lake depth, the albedo and light extinction coefficient of water, snow, and ice respectively, the fetch, and the relaxation coefficient of the thermocline shape factor. The results show different sensitivity features according to the lake type and climate. The dominant role and time varying contribution of the lake depth, radiative parameters (albedo, light extinction coefficient) and thermocline relaxation coefficient linked to the atmospheric conditions, were clearly highlighted. These findings will lead us to distinguish between different lake categories in each grid cell of ORCHIDEE in the future implementation

Land clearing, climate variability, and water resources increase in semiarid southwest Niger: a review

The water table in southwestern Niger has been rising continuously for the past decades (4 m rise from 1963 to 2007), despite a ~23% deficit in monsoonal rainfall from 1970 to 1998. This paradoxical phenomenon has been linked with a change in land use from natural savannah to millet crops that have expanded in area sixfold since 1950 and have caused soil crusting on slopes that has, in turn, enhanced Hortonian runoff. Runoff concentrates in closed ponds and then recharges the aquifer; therefore, higher runoff increases aquifer recharge. At the local scale (2 km2), a physically based, distributed hydrological model showed that land clearing increased runoff threefold, whereas the rainfall deficit decreased runoff by a factor of 2. At a larger scale (500 km2, 1950–1992 period), historical aerial photographs showed a 2.5-fold increase in the density of gullies, in response to an 80% decrease in perennial vegetation. At the scale of the entire study area (5000 km2), analytical modeling of groundwater radioisotope data (3H and 14C) showed that the recharge rate prior to land clearing (1950s) was about 2 mm a−1; postclearing recharge, estimated from groundwater level fluctuations and constrained by subsurface geophysical surveys, was estimated to be 25 ± 7 mm a−1. This order of magnitude increase in groundwater fluxes has also impacted groundwater quality near ponds, as shown by a rising trend in groundwater nitrate concentrations of natural origin (75% of δ15N values in the range +4 to +8‰). In this well-documented region of semiarid Africa, the indirect impacts of land use change on water quantity and quality are much greater than the direct influence of climate variability