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About the speaker:

Dr. Seon Ki Park is Professor of Climate and Energy Systems Engineering at the Ewha Womans University (EWU), Seoul, Korea; he established and served as the Founding Directors of two research centers at EWU ― the Severe Storm Research Center (SSRC) and the Center for Climate/Environment Change Prediction Research (CCCPR). His research focuses on storm- and meso-scale meteorology, coupled modeling of land surface-atmosphere-chemistry, and numerical prediction of high-impact weather/climate/environment, including data assimilation and parameter optimization. He obtained a Ph.D. in Meteorology from the U. of Oklahoma (OU) in 1996, then worked as a research scientist at OU, U. of Maryland and NASA/GSFC before he joined EWU in 2001. He has served as the President of Atmospheric Sciences Section of the Asia Oceania Geosciences Society (AOGS) in 2012-2014, and currently serves as the President of the Korean Meteorological Society (2024-2025). He co-edited a series of editorial volumes, Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (2009, 2013, 2017, 2022; Springer); he co-authored a textbook, Principles of Data Assimilation (2022; Cambridge University Press); he also edited a book, Numerical Weather Prediction: East Asian Perspectives (2023; Springer). He has been the main host and organizer of the Ewha International School on Data Assimilation (EISDA) since 2012.

About the seminar:

Land surface processes play a significant role in the integrated climate/environment modeling through interactions with atmosphere, chemistry, biosphere, etc., thus constituting a core component of the global/regional climate models. Uncertainties in the land surface modeling can deteriorate numerical prediction of climate/weather/environment, which is an important source for adequate policy making in an era of changing climate. The performance of land surface models can be improved through better estimation of parameters and initial conditions. Some recent efforts to improve the land surface modeling will be introduced as an integrated approach, such as developing/improving parameterizations of subgrid-scale phenomena, estimating optimal parameter values, seeking an optimized set of parameterization schemes, and applying a hybrid ensemble-variational data assimilation.

Kindly note, Professor Park will be available for one-on-one discussions after the seminar and on 24th July; please let us know in advance if you'd like to book a slot.

You can also join via Zoom:
https://anu.zoom.us/j/6633934183?pwd=ZnJnelcxUDZJcXNSOTBraTU2d0kwUT09&omn=83104926636

Meeting ID: 663 393 4183
Password: 462534