Emmanouil N. Anagnostou
The 2002 Plinius Medal is awarded to Emmanouil N. Anagnostou for his outstanding achievements in combining meteorology and hydrology to improve our knowledge and understaning of natural hazards.
Dr. Emmanouil N. Anagnostou, was born in Athens, Greece, in 1968. He has degrees from the University of Iowa, USA, and the Iowa Institute of Hydraulic Research, USA. He is currently Assistant Professor in the Department of Civil and Environmental Engineering of the University of Connecticut, and holds Adjunct Research Scientist appointment with the National Observatory of Athens. He has been Visiting Scientist at the Laboratory of Atmospheres of NASA Goddard Space Flight Center. His research experience and expertise is on remote sensing applications in hydrometeorology and the prediction of natural hazards (floods, hurricanes, severe weather, lightning, etc.). In the past six years he has focused his work on the advancement of our knowledge on precipitation estimation from both space and ground based sensors, and the optimum assimilation of remote sensing data in atmospheric and hydrologic models for the prediction of hazardous floods and flash floods. He is recipient of three prestigious awards in support of his Natural Hazards interdisciplinary research: (1) the NSF CAREER award for research on improving the knowledge on precipitation microphysics for advancing radar rainfall estimation and quantitative precipitation forecasting; (2) the NASA’s New Investigator Program Award for research on the quantification of uncertainties associated with satellite remote sensing of rainfall; and (3) the European Union Marie Curie award for studying the propagation of radar rainfall estimation error in runoff forecasting. He is the Primary Investigator of several research projects in the area of Earth Sciences and Natural Hazards funded by NASA and the US National Science Foundation. He is member of NASAs Tropical Rainfall Measuring Mission science team. He is the author or co-author of 29 journal paper in areas of precipitation remote sensing and hydro-meteorological prediction.