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East African Rainfall Variability Associated with the Madden-Julian Oscillation

Journal of Kenya Meteorological Society

(JKMS)

Volume 2:2:4


East African Rainfall Variability Associated with the Madden-Julian Oscillation

Peter A. Omeny*, Laban Ogallo**, Raphael Okoola***, Harry Hendon**** and Mathew Wheeler****

*Kenya Meteorological Department, **IGAD Climate Prediction and Applications Center, Nairobi, ***University of Nairobi, ****BMRC (Bureau of Meteorological Research Centre, Australia)

Corresponding Author

Peter A. Omeny

Kenya Meteorological Department

P.O. Box 30329 00100 Nairobi

(Manuscript received 15 July 2007, in final form 13 October 2008)

Abstract

The main objective of this study is to diagnose the relationship between the Madden-Julian Oscillation (MJO) and rainfall over East Africa. The data used include daily rainfall obtained from the National Meteorological and Hydrological Services (NMHSs) of Uganda, Tanzania and Kenya, daily Madden-Julian (MJO) indices from the Bureau of Meteorology Research Center (BMRC), daily Outgoing Longwave Radiation (OLR) from Climate Diagnostics Center (CDC) and wind data obtained from NCEP-NCAR.. Correlation and composite analyses are used to establish the association and the relationship between the MJO and rainfall over East Africa. The skill of forecast is verified using cross validation method. Results reveal strong association between East African rainfall and the MJO to the west of the region especially around the Lake Victoria. Out of phase (opposite) relationship between the west and the east is also revealed indicating different rain causing mechanisms for the two regions. The rainfall is also shown to depend on the configuration of the winds at low and upper levels. Based on composite analysis extreme rainfall events are shown to occur during preferential phases of the MJO. Phase 2 coincides with enhanced rainfall, high negative anomaly OLR values as well as westerly and easterly winds configuration at 700hpa and 200hpa while phase 5 and 6 are associated with depressed rainfall. The study also reveals that skillful prediction of rainfall at intraseasonal time scale is possible up to 10 days. The eastern parts of East Africa showed no prediction skills at intraseasonal time scales. The study provides evidence of the potential predictability of intraseasonal rainfall over East Africa using the MJO indices up to 10 days. However, the MJO indices only explain 18% of the variance over the Lake Victoria basin. The inclusion of other modes of variability such as Sea surface Temperatures (SSTs) and the Indian Ocean Dipole (IOD), as predictors are recommended in predicting intraseasonal rainfall.

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