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

This paper presents the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Models Intercomparison Project (ALMIP) for Microwave Emission Models (ALMIP-MEM). ALMIP-MEM consists in an ensemble of simulations of C-band brightness temperatures over West Africa for a one-year annual cycle in 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 the soil dielectric models. ALMIP-MEM provides the first inter-comparison 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. Results show that when the best microwave modeling configuration is used, all the LSMs are able to reproduce the main temporal and spatial variability of measured brightness temperature. Statistical results show a scatter in the model performances, and different LSMs provide best correlation, best standard deviation and best root mean square errors. Averaged among the LSMs, correlation is 0.67 and averaged normalized standard deviation is 0.98, both indicating good performances of the ensemble LSMs simulation. The scatter in simulated Top Of Atmosphere (TOA) brightness temperatures due to the LSMs is lower than the scatter due the choice of the microwave emission model. It is shown that 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.