A sensitivity study of MATSIRO land surface model with a simple wetland scheme for improvements in the representation of surface hydrology and surface air temperature bias

Monday, 15 December 2014
Tomoko Nitta, Atmosphere and Ocean Research Institute University of Tokyo, Tokyo, Japan, Kei Yoshimura, AORI, Univ Tokyo, Chiba, Japan and Ayako Abe-Ouchi, University of Tokyo, Bunkyo-ku, Japan
Many lakes and wetlands exist in the Arctic. They store a part of snowmelt, and influence the surface water and energy budget and surface hydrology including soil moisture and river flow. The storage effects of wetlands have a possibility to improve the surface hydrology simulation and to reduce the surface air temperature bias that exists in the current generation climate model. There are, however, only few global land surface models that incorporate wetlands and the effects upon climate are not yet well investigated. Here, in the present study, we examine a simple wetland scheme that stores part of snowmelt with MATSIRO land surface model in a climate model, MIROC5. First, we conduct offline global land simulations with and without the wetland scheme using meteorological forcing that combines the reanalysis and the observed precipitation dataset. We evaluate the results using satellite based soil moisture dataset, evapotranspiration reference dataset and observed river discharge. Using the offline land model, we show that the wetland scheme improves the underestimation of evapotranspiration in the control simulation. The simulated sensible heat flux decreases corresponding to the increasing latent heat flux. The bias of river discharge simulation is reduced in major Arctic river basins. Further, we conduct a series of on-line AGCM experiment using MIROC5 with climatological monthly SST and sea ice boundary conditions in order to examine the effects of the wetland on the near surface air temperature. The result shows that the impact of wetland scheme upon the reduction of near surface air temperature in summer is significant.