Radiosonde humidity bias correction over the West African region for special AMMA reanalysis at ECMWF

Correction de biais des mesures d'humidité réalisées par radiosonde au-dessus de l'Afrique de l'Ouest en vue des réanalyses effectuées au CEPMMT spécialement pour la campagne AMMA

Agustí-Panareda, A. ; Vasiljevic, D. ; Beljaars, A. ; Bock, O. ; Guichard, F. ; Nuret, M. ; Garcia Mendez, A. ; Andersson, E. ; Bechtold, P. ; Fink, A. ; Hersbach, H. ; Lafore, J.-P. ; Ngamini, J.-B. ; Parker, D. J. ; Redelsperger, J.-L. ; Tompkins, A. M.

Année de publication
2009

During the African Monsoon Multidisciplinary Analysis (AMMA) field experiment in 2006 there was a large increase in the number of radiosonde data over West Africa. This has the potential of improving the numerical weather prediction (NWP) analysis/forecast and the water budget studies over that region. However, it is well known that the humidity from radiosondes can have some errors depending on sonde type, relative humidity (RH), temperature and the age of the sensor and can give rise to dry biases that are typically between 5% and 30% for RH. Three main sonde types were used in the AMMA field experiment: Vaisala RS80A, Vaisala RS92 and MODEM. In this article, a new empirical method is presented by using the operational European Centre for Medium-Range Weather Forecasts (ECMWF) short-range forecast as an intermediary dataset for computing biases. The validation of the correction method using global positioning system (GPS) total columnar water vapour (TCWV) confirms that the method is able to correct for a large part of the dry biases associated with the different sonde types. Results from analysis experiments show how the correction of humidity is particularly important in the West African region due to its impact on the development of convection in NWP models. The proposed radiosonde humidity bias correction has been applied to the special AMMA reanalysis experiment performed at ECMWF for the 2006 West African wet monsoon season. This is expected to benefit a wide number of AMMA-related studies that make use of the reanalysis, in particular those focusing on the water cycle. Copyright g 2009 Royal Meteorological Society.

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