Reducing Uncertainties in Land Surface Modeling through Parameterization Scheme Development and Optimal Parameter Estimation

Seminar by Prof. Seon-Ki Park from Ewha Womans University

04 December 2020
KST 10:00 – 11:00

The Seminar is being held in Room 1010 (Jasmin) – Integrated mechanical engineering building. Click here for the campus map.

Land surface is the interface between atmosphere and land, which is composed of various soils, vegetations, surface water bodies, snow/ice etc.; thus, it represents various components of the Earth’s environment/climate system, including biosphere, hydrosphere, cryosphere, and pedosphere. It also plays a vital role in interacting with the atmosphere through the energy/water/carbon cycles and many feedback processes among diverse components of the cycles. The land surface models (LSMs) serve as the bottom condition of the numerical weather/climate models, and most of them include soil layer(s) as well. As many land surface processes occur in the scales smaller than the grid point system (i.e., subgrid scale), the LSMs employs many subgrid-scale parameterization schemes. These parameterized processes inherently include uncertainties that are expressed in the ranges of parameter values. One of the major issues in contemporary numerical weather/climate predictions is to obtain more accurate parameterization schemes and/or parameter values in LSMs. This seminar introduces recent efforts to improve the LSM performances by developing new parameterization schemes and by estimating the optimal parameter values of the given schemes in the Noah LSM and the Noah-MP, especially focusing on the snow albedo processes and the vegetation effect.