Sensitivity of L-Band NWP forward modelling to soil roughness

TitleSensitivity of L-Band NWP forward modelling to soil roughness
Publication TypeMiscellaneous
Year of Publication2010
AuthorsSabater, JM, de Rosnay, P, Balsamo, G
Secondary TitleTechnical Memorandum
Date PublishedApril
Type of WorkTechnical Memorandum

This paper investigates the sensitivity of the EuropeanCentre forMedium-RangeWeather Forecasts (ECMWF) simulated L-band brightness temperatures (TB) in response to different soil roughness parameterisations. To this end, the ECMWF operational conditions during the year 2004 have been used to force the Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (HTESSEL) coupled to the Community Microwave Emission Model (CMEM). The coupled HTESSEL-CMEM system is then run at five different incident angles (20◦,30◦,40◦,50◦ and 60◦) and for five soil roughness parameterisations available in CMEM. The performance of the simulated TB are analysed at ground point scale over the SurfaceMonitoring Of Soil Reservoir EXperiment (SMOSREX) site in South West of France. For this particular data set, both ground-based vertical profile of soil moisture and L-band radiometric observations are available for evaluation of the ECMWF forecast system nearest grid box. In particular, the results show that the simple Choudhury parameterisation best fits the observations for both horizontal (H-pol) and vertical polarization (V-pol) and for most of the incidence angles tested. The best forward modelling configuration is at 50◦ for the V-pol, with coefficient of determination between modelled and observed TB of 82.9% and root mean squared error of 7.9 K. The sensitivity of the L-band TB errors to the empirical soil roughness parameter is also investigated. Strong sensitivity to this parameter is shown, mainly at H-pol for the least rough surfaces. The investigation carried out in this paper gives an insight into the soil roughness model to be used in the operational configuration of the CMEM L-band forward operator, for the future assimilation of the Soil Moisture and Ocean Salinity satellite data of the European Space Agency.