DATE2018-05-10 10:56:03
IDABSTRACT20180510105603-0158
CONTACTdhib_saoussen@hotmail.fr
PRESENTATIONORAL
INVITED0
IDSESSION3
TITLERAINFALL ESTIMATION OVER NORTHERN TUNISIA BY COMBINING MSG CLOUD TOP TEMPERATURE AND TRMM-TMI RAIN RATES
AUTHORSS Dhib (1), CM Mannaerts (2), Z Bargaoui (1), BHP Maathuis (2), P Budde (2)
AFFILIATIONS
  1. Université de Tunis El Manar, ENIT, Tunis, Tunisia
  2. University of Twente, ITC, Enschede, Netherlands
ABSTRACTIn this study, a new method to delineate rain areas in northern Tunisia is presented. The proposed approach is based on blending geostationary Meteosat Second Generation (MSG) infrared channel (IR) with the passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The correlation coefficient of these two variables has a negative tendency, meaning that with decreasing temperature there is an increase in rainfall intensity. To blend this two products, we adopt two main steps. Firstly, we identify the rainy pixels based on a classification using MSG channel IR 10.8 and the water vapor WV 0.62. A threshold on the temperature difference of 11 K is adapted to identify the clouds that have a high likelihood of precipitation. The second step consists of fitting a statistical relation between IR cloud top temperatures with the TMI rain rates. The fitted equation is then applied to the MSG 15 minutes interval images of the whole day. To evaluate this combined product, we analyze a sample of daily extreme rainfall occurred during the period 2007-2009 in Northern Tunisia. A threshold is assumed for large rainfall depths (50 mm/day). The date is selected if at least one rainfall station of the studied network has a rainfall greater than the threshold. Inverse distance interpolation method is applied to draw rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). The results were found very encouraging where all the events are detected rainy and the correlation coefficients between observed and calculated maps are much better than those obtained for MSGMPE and PERSIANN products. Moreover, during the wet season.
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