Trends in mean and extreme precipitation in the Mount Kenya region from observations and reanalyses

ABSTRACT Land and water management in semi‐arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya...

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Published inInternational journal of climatology Vol. 36; no. 3; pp. 1500 - 1514
Main Authors Schmocker, J., Liniger, H. P., Ngeru, J. N., Brugnara, Y., Auchmann, R., Brönnimann, S.
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 15.03.2016
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Summary:ABSTRACT Land and water management in semi‐arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya region, encompassing around 50 stations with at least 30 years of data. We describe the data set, including quality control procedures and statistical break detection. Trends in mean precipitation and extreme indices calculated from these data for individual rainy seasons are compared with corresponding trends in reanalysis products. From 1979 to 2011, mean precipitation decreased at 75% of the stations during the ‘long rains’ (March to May) and increased at 70% of the stations during the ‘short rains’ (October to December). Corresponding trends are found in the number of heavy precipitation days, and maximum of consecutive 5‐day precipitation. Conversely, an increase in consecutive dry days within both main rainy seasons is found. However, trends are only statistically significant in very few cases. Reanalysis data sets agree with observations with respect to interannual variability, while correlations are considerably lower for monthly deviations (ratios) from the mean annual cycle. While some products well reproduce the rainfall climatology and some the spatial trend pattern, no product reproduces both.
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ISSN:0899-8418
1097-0088
DOI:10.1002/joc.4438