Wondie Megbar
Atmospheric Physics Research Division, Department of Physics, College of Natural and Computational Science, Debre Markos University, Debre Markos, Ethiopia.
Heliyon. 2023 Mar 29;9(4):e14974. doi: 10.1016/j.heliyon.2023.e14974. eCollection 2023 Apr.
The government of Ethiopia has started exploring different innovative approaches to tackle the scarcity of water in arid and semi-arid regions of the country. In line with this strategy, precipitation enhancement through weather modification technology is getting strong attention and some initial attempts have been made to assess its feasibility. Therefore, this paper aims to model cloud-seeding technology for rain enhancement and check its effectiveness in arid and semiarid regions of Ethiopia. Different relevant measurements including ground-based as well as reanalysis data from 2021 to 2022 are used to improve relevant cloud-seeded models. Reanalysis data are validated with ground-based data using different error metrics. The improved cloud-seeded modeling is developed for precipitation enhancement for the arid and semiarid regions of Ethiopia. An atmospheric moisture budget is used for improving the cloud-seeded model. The results indicated that the developed model and the direct operation are well agreed upon. The relative precipitation (RP) (after the application of cloud-seeded per before the application of cloud-seeded during spring, summer, and autumn is found 1.31, 0.98, and 1.03 respectively. The changing precipitation between cloud seeded and before seeded for spring, summer, and autumn is found at 1.38, -0.19, and 0.11 mm respectively; whereas changing temperature is found at 1.08, 1.78, and -1.06 k respectively. In general, the model result indicated that cloud-seeded technology is effective over Ethiopia when the daily resultant wind speed is less than 1.5 m/s and cloud base height (CBH) is less than 1700 m. Furthermore, by observing RP from the improved cloud-seeded model results, rain enhancement science is applicable for Ethiopia during the spring and slightly autumn seasons. Hence, before artificial aerosol is seeded into the cloud, the operators should be nowcast and forecast the daily wind speed and CBH of the target area unless an economic crisis will have happened.
埃塞俄比亚政府已开始探索不同的创新方法,以应对该国干旱和半干旱地区的缺水问题。按照这一战略,通过人工影响天气技术增加降水受到了高度关注,并已进行了一些初步尝试来评估其可行性。因此,本文旨在对人工增雨的云催化技术进行建模,并检验其在埃塞俄比亚干旱和半干旱地区的有效性。使用了包括2021年至2022年的地面测量数据以及再分析数据等不同相关测量数据,以改进相关的云催化模型。再分析数据使用不同的误差指标与地面数据进行验证。针对埃塞俄比亚干旱和半干旱地区的降水增强,开发了改进的云催化模型。利用大气水分收支来改进云催化模型。结果表明,所开发的模型与直接操作结果吻合良好。春季、夏季和秋季人工增雨前后的相对降水量(RP)分别为1.31、0.98和1.03。春季、夏季和秋季人工增雨前后的降水量变化分别为1.38毫米、-0.19毫米和0.11毫米;而温度变化分别为1.08开尔文、1.78开尔文和-1.06开尔文。总体而言,模型结果表明,当日合成风速小于1.5米/秒且云底高度(CBH)小于1700米时,云催化技术在埃塞俄比亚是有效的。此外,通过观察改进后的云催化模型结果中的RP,人工增雨科学在春季和略偏秋季适用于埃塞俄比亚。因此,在将人工气溶胶播撒到云中之前,除非发生经济危机,操作人员现在应该对目标区域的每日风速和CBH进行临近预报和预报。