Impact of Convective Parameterization Schemes on the Quality of Rainfall Forecast over Tanzania Using WRF-Model - Natural Science

NS > Vol.6 No.10, June 2014

Impact of Convective Parameterization Schemes on the Quality of Rainfall Forecast over Tanzania Using WRF-Model ()

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Download as PDF (Size: 2216KB) PP. 691-699

DOI: 10.4236/ns.2014.610069 3,866 Downloads 5,321 Views Citations

Author(s)

Alfred L. Kondowe

Affiliation(s)

Department of Weather Forecast and Numerical Weather Prediction, Faculty of Meteorology, Russian State Hydrometeorological University (RSHU), St. Petersburg, Russia.

ABSTRACT

To describe the evolution of atmospheric processes and rainfall forecast in Tanzania, the Advanced Weather Research and Forecasting (WRF-ARW) model was used. The principal objectives of this study were 1) the understanding of mesoscale WRF model and adapting the model for Tanzania; 2) to conduct numerical experiments using WRF model with different convective parameterization schemes (CP’s) and investigate the impact of each scheme on the quality of rainfall forecast; and 3) the investigation of the capability of WRF model to successfully simulate rainfall amount during strong downpour. The impact on the quality of rainfall forecast of six CP’s was investigated. Two rainy seasons, short season “Vuli” from October to December (OND) and long season “Masika” from March to May (MAM) were targeted. The results of numerical experiments showed that for rainfall prediction in Dar es Salaam and (the entire coast of the Indian Ocean), GD scheme performed better during OND and BMJ scheme during MAM. Results also showed that NC scheme should not be used, which is in agreement to the fact that in tropics rainfall is from convective activities. WRF model to some extent performs better in the cases of extreme rainfall.

KEYWORDS

Tanzania, WRF-ARW, Convective Parameterization Scheme (CP’s)

Share and Cite:

Kondowe, A. (2014) Impact of Convective Parameterization Schemes on the Quality of Rainfall Forecast over Tanzania Using WRF-Model. Natural Science, 6, 691-699. doi: 10.4236/ns.2014.610069.

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