LAUSR

The main objective of this study is to develop two indices capable to identify areas where rain showers are possible over Egypt and the Eastern Mediterranean Region (EEMR). This is done by adding a coefficient to each K index variable. The coefficients are obtained from a multiple linear regression that is constructed between rainfall as predictant and K index variables as predictors. This is the case of the first Egypt and Eastern Mediterranean Index (EEM1). The other developed index (EEM2) differs from EEM1 by adding dew point at 500 hPa as other predictor. Six hourly dataset from European Centre for Medium-Range Weather Forecasts (ECMWF) for three wet events with heavy rainfall during January, March and November are used to construct the new regression equations. On the other hand, the validation of this technique is applied to different six wet events with heavy rain showers (two events for each of winter, spring and autumn season). The category scale of the two developed indices is adjusted to be compatible with the K index. The results show that rainfall occurs only over EEMR when K and EEM indices are ≥ 20, respectively. The result of estimating spatial and temporal distribution of rain showers shows that EEM2 is more accurate than EEM1 and K index due to including dew point temperature at 500 hPa. The average EEM2 (EEM1) Rain Area Relative Error (RARE) in November, January and March reaches 31.84% (47.61%), 43.82% (50.43%) and 49.72% (55.22%), respectively. On the other hand, the corresponding average K index RARE is 164.97%, 74.43% and 163.09%, respectively.