2013 Interdisciplinary Summer School: Data Assimilation in Geoscience

University Of Maryland, College Park, College Park MD

Investigators

Abstract

The "2013 Interdisciplinary Summer School: Data Assimilation in Geosciences" to be held June 3-14, 2013, at the Center of Scientific Computing and Mathematical Modeling (CSCAMM), University of Maryland (UMD), College Park, MD, targets graduate students and scientists at an early stage of their career. The mathematical problem of data assimilation is both fundamental and challenging in that it aims at the monitoring and prediction of unknown true state of time-evolving system. This two-week intensive summer school is designed to build a solid foundation for data assimilation through the tutorial lectures and the computational laboratory, while providing an exposure to the current state-of-the-art of the US operational Numerical Weather Prediction (NWP), advanced methods, and new ideas. It is organized and taught by the leading scientists in the field, who are experienced with data assimilation schools for young researchers as well as workshops for specialists. Geographical proximity of UMD to the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and NASA Goddard Space and Flight Center (GSFC) provides a unique one-of-the-kind experience to visit these centers. CSCAMM at UMD has a track record for successful summer schools and workshops. Entire summer school is carefully structured to take advantages of all these features. Lecture notes and presentations of the summer school will be disseminated through the CSCAMM website for the broader impact. In essence, data assimilation is a complex interdisciplinary subject that involves scientific prediction using computational models and observations. The most familiar practice of data assimilation may the weather forecast, performed and provided to public by NOAA and other operational NWP centers in the world. To forecast the weather by the NWP, data assimilation adjusts the current condition of the atmosphere represented in the sophisticated computational model by fusing the contemporary atmospheric observations. Quality of the forecast largely depends on that of the data assimilation system in use. Data assimilation is thus at the very interface of science and operational technology that has significant societal impact. Improving the prediction of extreme weather events can help better support the decision making processes and lead to the positive socio-economic impact. Moreover, data assimilation has a wide range of important application areas within and beyond geosciences. One such area is the climate change projection and monitoring. Another is the design of the future observing systems and networks. This summer school aims to provide an ideal venue for young scientists to brainstorm and initiate their future career.