Event date:
Apr 18 2022 8:00 pm

Data Assimilation of the Terrestrial Water Cycle: Applications

Speaker(s)
Dr. Manuela Girotto
Abstract
The goal of Data assimilation is to provide a better estimate of the environmental states than either models or observations could individually do. This presentation will focus on benefits, challenges and applications of recent land surface data assimilation research efforts targeted at improving snow, soil moisture, groundwater, and terrestrial water storage hydrological states.

Dr. Manuela Girotto is an Assistant Professor in the department of Environmental Science and Policy Management at UC Berkeley. Her research merges cutting-edge space technology and remotely-sensed observations of the earth with state-of-the-art models for the purpose of improving our scientific knowledge about variability and change in hydrologic cycles. Her research focuses on snow, soil moisture, and groundwater hydrology. After earning her PhD in civil and environmental engineering at the University of California, Los Angeles, Dr Manuela have worked as a research scientist in the earth science division of the NASA Goddard Space Flight Center in Greenbelt, MD.  


The MLSH 2022 seminars are targeted towards individuals engaged in research-based activities in the hydrological sciences and will be delivered by scientists who have produced acclaimed research in the field. The concurrent emergence of new technologies, advancements in data-science and new approaches to modelling have expanded the possibility frontier for effective management of our water resources. Not only this, but these developments are uncovering new insights and spawning new discoveries that change our fundamental understanding of the Earth's hydrosphere. "Models, Learning and Sensing in Hydrology" is aimed at propagating the science and techniques of exactly this field of research. The full schedule for the webinars can be found here, which also includes recordings of past sessions. A link for attending will be sent via email to registered individuals. Colleagues who register once can attend all future talks without the need to register again.