Evaluation of a Numerical Weather Forecast Model Using Boundary Layer Cloud-Top Temperature Retrieved from AVHRR

Abstract This study concerns the evaluation of the boundary layer (BL) subgrid parameterization of a numerical weather forecast model on the synoptic scale. The method presented aims at separating the two possible origins of model defficiencies in representing a cloud-topped boundary layer: (i) large-scale data assimilation issues, and (ii) BL parameterization. The method combines two sources of data: model analyzed fields from the SEMAPHORE field experiment, and the Advanced Very High Resolution Radiometer (AVHRR) dataset from the NOAA-11 and -12 Satellite. The application focuses on an anticyclonic period during field experiment (10–17 November 1993), for which a special version of ARPEGE—The Meteo-France Numerical Weather Prediction model—is used to analyze the data from the field experiment. In the proposed method, the boundary layer is globally characterized by its height which is converted to an inversion layer temperature in the model. Low-level cloud-top temperatures of optically thick clouds are ...

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