Abstract
This paper analyses for the first time in tropical area, the relationship between lightning and DSD (Drop Size Distribution) parameters on rainy events that occurred during the monsoon period. The Lightning data used are collected by the LINET (Lightning Detection Network) while the DSD data were recorded by a distrometer. The correlation was computed within five circles of radius varying between to with a step of . These consecutive areas are centered on the position of the disdrometer. By taking into account only the convective spectra and remove out of the data the cases where there is rain without any lightning and vice versa, all data was computed with a time scale of one minute during each of the rainy events .The results showed that the exponential and polynomial laws fit better our data than the power and linear laws. The highest correlation coefficients are obtained within a radius of about 20 km around the distrometer location. The correlation between the parameter and is the most stable with a correlation coefficient equal to .
Highlights
Most hydrological simulation models use rainfall data
We investigate for the first time, the relationship between lightning and the Drop Size Distribution parameters (DSD) parameters using the case-to-case approach in tropical West Africa area known for its climate strong variability
The analysis performed in this work aims to explore for the first time the correlation between drop size distribution and lightning characteristics in African Monsoon Multidisciplinary Analysis (AMMA)-CATCH area in Benin republic
Summary
Most hydrological simulation models use rainfall data. A good description of precipitation in time and space is essential to improve hydrological modeling and design [1]. The estimation of rainfall data is mainly done today using rain gauges and weather radars. When the observation area becomes large, it is often necessary to use many rain gauges and interpolate methods with consequence of a loss of spatial resolution [2]. To avoid this problem, radars are identified as the best possible alternative. The problem of spatial resolution seems to be solved for regions well covered by radars, it will be necessary to find another alternative method for measuring rain remotely in other locations radar coverage is poor. According to several authors, lightning data could be considered as additional information that can be used for input to distributed parameter hydrologic models
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