The diverse and varied climate of Eastern Africa’s Kenya is home to an agriculturally dependent populace, in which farmers and other related economic sectors make up the majority of livelihoods and gross domestic product. Recurring droughts and severe flooding are major concerns for local farmers and governmental entities. The purpose of this study is to identify and categorize differences in rainfall trends over Kenya and to examine relationships between seasonal rainfall anomalies of sea surface temperature (SST), with an ultimate goal to improve predictions of wet season rainfall amounts. The analysis began with data from 27 national and cooperative weather stations. Several of these records were short and incomplete; therefore, a gridded and complete alternative data set was obtained with data dating back to 1901. Graphical comparisons of seasonal cycles within the country presented two distinct climate regions: Rift Valley and Eastern Kenya. The gridded data for each region was used to observe correlations with SST values in the Indian and Pacific Ocean. During March – May, there are weak positive correlations in the equatorial western Pacific that are unlikely to be of much value to forecasters, while a strong relationship exists during the short wet season. Interannual trends show a decrease in rainfall during the long rainy season (March-May) in both regions, while an increase in rainfall is observed during the short rainy season (October-November). These results ultimately confirm a large drying trend for the long wet season in both climate regions, a problematic result for an agriculturally dependent nation.


Atmospheric Sciences | Climate | Geology | Oceanography


Brant Liebmann, Ph.D

Lab site

National Oceanic Atmospheric Administration Earth Systems Research Laboratory (NOAA ESRL)

Funding Acknowledgement

This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation. This project has also been made possible with support of the National Marine Sanctuary Foundation. The STAR program is administered by the Cal Poly Center for Excellence in Science and Mathematics Education (CESaME) on behalf of the California State University (CSU).



URL: https://digitalcommons.calpoly.edu/star/250


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