During the last decade substantial improvements have been accomplished in many remote sensing systems. However, the uncertainty in precipitation estimation still persists, since it manifests (a) as measurement error, (b) in the space/time interpolation of a naturally discontinuous and erratic field and (c) in the assumptions made to transform the satellite measurements into a precipitation amounts. While several methodologies have been developed for data comparison and validation, all these efforts, to date, focus mainly on individual variables and spatiotemporal scales. The challenge is thus how to achieve a better coupling between station-derived datasets and remote sensing records, in order to scrutinize observational limitations and/or deficiencies across different spatiotemporal scales.
Our research team will contribute to the development of a validation scheme between station-derived datasets and the satellite observations. Our goal is to scrutinize observational limitations and/or deficiencies across different spatiotemporal scales, in order to improve the efficiency of the satellite performance. The robust estimation of precipitation is crucial for understanding how the hydrological cycle fluctuates, as well as for anticipating meteorological and hydroclimatic extremes, such as floods and droughts.
EarthCARE is a joint European/Japanese satellite, the sixth of ESA’s Living Planet Program, and is scheduled to be launched in August 2019. Among the scientific objectives of the mission is to observe vertical distributions of atmospheric liquid water and ice on a global scale, to estimate their transport by clouds and to highlight cloud-precipitation interactions.