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Correction of Humidity Bias for Vaisala RS80-A Sondes during the AMMA 2006 Observing Period

Mathieu NuretCNRM-GAME, Météo-France, and CNRS, Toulouse, France

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Jean-Philippe LaforeCNRM-GAME, Météo-France, and CNRS, Toulouse, France

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Françoise GuichardCNRM-GAME, Météo-France, and CNRS, Toulouse, France

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Jean-Luc RedelspergerCNRM-GAME, Météo-France, and CNRS, Toulouse, France

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Olivier BockLAREG/IGN, Marne La Vallée, France

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Anna Agusti-PanaredaLAREG/IGN, Marne La Vallée, France

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Jean-Blaise N’GaminiASECNA, Dakar, Senegal

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Abstract

During the African Monsoon Multidisciplinary Analyses (AMMA) program, which included a special observing period that took place over West Africa in 2006, a major effort was devoted to monitor the atmosphere and its water cycle. The radiosonde network was upgraded and enhanced, and GPS receivers deployed. Among all sondes released in the atmosphere, a significant number were Vaisala RS80-A sondes, which revealed a significant dry bias relative to Vaisala RS92 (a maximum of 14% in the lower atmosphere, reaching 20% in the upper levels). This paper makes use of a simple but robust statistical approach to correct the bias. Comparisons against independent GPS data show that the bias is almost removed at night, whereas for daytime conditions, a weak dry bias (5%) still remains. The correction enhances CAPE by a factor of about 4 and, thus, becomes much more in line with expected values over the region.

Corresponding author address: Mathieu Nuret, Météo-France and CNRS, CNRM/GMME/MOANA, 42 Avenue G. Coriolis, F-31057 Toulouse, France. Email: mathieu.nuret@meteo.fr

Abstract

During the African Monsoon Multidisciplinary Analyses (AMMA) program, which included a special observing period that took place over West Africa in 2006, a major effort was devoted to monitor the atmosphere and its water cycle. The radiosonde network was upgraded and enhanced, and GPS receivers deployed. Among all sondes released in the atmosphere, a significant number were Vaisala RS80-A sondes, which revealed a significant dry bias relative to Vaisala RS92 (a maximum of 14% in the lower atmosphere, reaching 20% in the upper levels). This paper makes use of a simple but robust statistical approach to correct the bias. Comparisons against independent GPS data show that the bias is almost removed at night, whereas for daytime conditions, a weak dry bias (5%) still remains. The correction enhances CAPE by a factor of about 4 and, thus, becomes much more in line with expected values over the region.

Corresponding author address: Mathieu Nuret, Météo-France and CNRS, CNRM/GMME/MOANA, 42 Avenue G. Coriolis, F-31057 Toulouse, France. Email: mathieu.nuret@meteo.fr

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