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.

中文翻译：

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埃及和东地中海强降雨事件的不稳定指数发展

本研究的主要目标是制定两个指数，能够确定埃及和东地中海地区 (EEMR) 可能出现阵雨的地区。这是通过向每个 K 索引变量添加一个系数来完成的。这些系数是从作为预测变量的降雨量和作为预测变量的 K 指数变量之间构建的多元线性回归中获得的。第一个埃及和东地中海指数 (EEM1) 就是这种情况。另一个开发的指数 (EEM2) 与 EEM1 不同，它添加了 500 hPa 的露点作为其他预测指标。来自欧洲中期天气预报中心 (ECMWF) 的 6 小时数据集用于构建新的回归方程，其中包括 1 月、3 月和 11 月期间发生强降雨的三个潮湿事件。另一方面，该技术的验证应用于具有大雨的不同的六个潮湿事件（冬季、春季和秋季各有两个事件）。两个开发指数的类别尺度进行了调整，以与K指数兼容。结果表明，只有当 K 和 EEM 指数分别≥ 20 时，降雨才会发生在 EEMR 上。估计阵雨时空分布的结果表明，EEM2 比 EEM1 和 K 指数更准确，因为它包括了 500 hPa 的露点温度。11月、1月和3月平均EEM2（EEM1）雨区相对误差（RARE）分别达到31.84%（47.61%）、43.82%（50.43%）和49.72%（55.22%）。另一方面，对应的平均K指数RARE分别为164.97%、74.43%和163.09%。