Mapping weather risk – A multi-indicator analysis of satellite-based weather data for agricultural index insurance development in semi-arid and arid zones of Central Asia

Index insurance has been introduced as a solution to tackle several challenges that prevail in the agricultural sector of developing countries. One main implementation these countries is lack reliable weather data for index development and implementation. The increasing availability satellite could ease constraints access. Meanwhile, suitability various products yield estimation across world regions undergo thorough assessment. This study contributes literature by systematically analyzing accuracy some globally available data, namely Global Satellite Mapping Precipitation (GSMaP), Climate Hazards Group InfraRed with Station (CHIRPS), Land Data Assimilation System (GLDAS) compared ground-level information 14 different indicators case Uzbekistan. Our analysis indicates those sources may provide necessary an accessible adequate climate service. However, considerable risk overestimation underestimation depending on source exist, especially precipitation conditions Central Asia. Among tested datasets, GSMaP showed relatively better performance than CHIRPS drought flood detection. In order reduce detection inaccuracy, application possible when temporal aggregation (e.g., monthly, seasonal) considered. Globally serve good establish Asia; however, careful selection required.