|Title||Assimilation of MODIS cloud optical depths in the ECMWF model|
|Year of Publication||2007|
|Authors||Benedetti, A, Janiskova, M|
|Secondary Title||Technical Memorandum|
At the European Centre for Medium-Range Weather Forecasts (ECMWF), a large effort has recently been devoted to define and implement moist physics schemes for variational assimilation of rain and cloud-affected brightness temperatures. In this study we expand on the current application of the new linearized moist physics schemes to assimilate cloud optical depths retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board of the Aqua platform, for the first time in the ECMWF operational four-dimensional assimilation system (4D-Var). Model optical depths are functions of ice water and liquid water contents through established parametrizations. Linearized cloud schemes in turn link these cloud variables with temperature and humidity. A bias correction is applied to the optical depths to allow for a better agreement of the differences between model and observations. The control variables in the assimilation are temperature, humidity, winds and surface pressure. One month assimilation experiments for April 2006 demonstrated an impact of the assimilated MODIS cloud optical depths on the model fields, particularly temperature and humidity. Comparison with independent observations indicate a positive effect of the cloud information assimilated into the model especially on the amount and distribution of the Ice Water Content. The impact of the cloud assimilation on the medium-range forecast is neutral-to-positive. Most importantly, this study demonstrate the feasibility of global assimilation of cloud observations in the context of a Numerical Weather Prediction system.