Spatiotemporal geostatistical analysis of precipitation combining ground and satellite observations

Abstract Precipitation data are useful for the management of water resources as well flood and drought events. However, precipitation monitoring is sparse often unreliable in regions with complicated geomorphology. Subsequently, spatial variability distribution frequently represented incorrectly. Satellite provide an attractive supplement to ground observations. satellite involve errors due complexity retrieval algorithms and/or presence obstacles that affect infrared observation capability. This work presents a methodology combines observations leading improved spatiotemporal mapping analysis precipitation. The applied based on space–time regression kriging. case study refers island Crete, Greece, time period 2010–2018. from 53 stations used combination images reference period. introduces approach mapping.