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- Author or Editor: Olivier Bock x
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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.
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.
