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Moist Potential Vorticity Vector for Diagnosis of Heavy Rainfall Events in Tanzania

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dc.contributor.author Luhunga, Modest Luhunga
dc.contributor.author Mutayoba, Edmund
dc.date.accessioned 2017-08-15T08:15:09Z
dc.date.available 2017-08-15T08:15:09Z
dc.date.issued 206-09-29
dc.identifier.citation Luhunga, P.M. and Mutayoba, E. (2016) Moist Potential Vortic- ity Vector for Diagnosis of Heavy Rainfall Events in Tanzania. Journal of Geoscience and Environment Protection, 4, 128-145. http://dx.doi.org/10.4236/gep.2016.49010 en_GB
dc.identifier.issn 2327-4344
dc.identifier.uri http://www.taccire.sua.ac.tz/handle/123456789/513
dc.description.abstract In this paper, we modify the convective vorticity vector ( CVV ) defined as a cross product of absolute vorticity and gradient of equivalent potential temperature to moist potential vorticity vector (MPVV) defined as a cross product of absolute vorticity (ζa ) and the gradient of the moist-air entropy potential temperature (θs ). The patterns of (MPVV ) are compared with the patterns of heavy rainfall events that occurred over different regions in Tanzania on 20th to 22nd December, 2011 and on 5th to 8th May, 2015. Moreover, the article aimed at assessing the relative contribu- tions of the magnitude, horizontal and vertical components of (MPVV ) detecting on the observed patterns of rainfall events. Dynamic and thermodynamic variables: wind speed, temperature, atmospheric pressure and relative humidity from numeri- cal output generated by the Weather Research and Forecasting (WRF) model run- ning at Tanzania Meteorological Agency (TMA) were used to compute MPVV. It is found that MPVV provide accurate tracking of locations received heavy rainfall, suggesting its potential use as a dynamic tracer for heavy rainfall events in Tanzania. Finally it is found that the first and second components of MPVV contribute al- most equally in tracing locations received heavy rainfall events. The magnitude of MPVV described the locations received heavy rainfall events better than the com- ponents. en_GB
dc.description.sponsorship Authors are grateful to the Tanzania Meteorological Agency for provision of observed meteorological data, and the output from WRF model which have been used in this study. Special thanks to Pascal Marquet from the Météo-France, CNRM/GMAP/PROC for the useful discussion on computation of his new novelty moist air entropic potential temperature. en_GB
dc.language.iso en en_GB
dc.publisher Scientific Research Publishing en_GB
dc.subject Moist Potential Vorticity Vector en_GB
dc.subject Moist-Air Entropic Potential Temperature en_GB
dc.subject Heavy Rainfall Events en_GB
dc.title Moist Potential Vorticity Vector for Diagnosis of Heavy Rainfall Events in Tanzania en_GB
dc.type Article en_GB

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