1. Improving Land Surface Energy and Water Fluxes Simulation over the Tibetan Plateau with Using a Land Data Assimilation System Hui Lu ( Tsinghua University ) Toshio Koike, Hiroyuki Tsutsui, Katsunori Tamagawa ( The University of Tokyo ) Kun Yang, Xin Li ( Chinese Academy of Science ) Xiangde Xu ( Chinese Meteorological Admistration )

5. Minimization scheme F(Tb obs -Tb sim ) TMI/AMSR/AMSR-E (6.9/10.6 and 18.7 GHz) SiB2/New SiB DMRT-AIEM Shuffled Complex Evolution Optimization + Assimilation LDAS LSM Tg, Tc, Mv Tb sim Mv Vegetation layer Surface Surface radiation Vegetation emission RTM Tb obs Microwave

6. Introduction of LDAS-UT: Input and Output LDAS-UT Meteorological Forcing : Wind, Temp., Humidity, Pressure, Precipitation, Radiation In situ observation, Satellite Products, model outputs, Default Parameters: Land Cover Type, Soil Type, …… ISLSCP Output Status Variables : Energy fluxes Soil Moisture profile Soil Temp. profile Canopy Temperature …… Semi-dynamic Vegetation information : MODIS, LAI  VWC MODIS, NDVI  Vegetation Fractional coverage : Observation: Microwave TB TMI/AMSR/AMSR-E

9. Results Soil Moisture

10. Result: Soil moisture at Gaize 0.442 26.13 25.28 NCEP 0.601 6.13 -3.01 AMSR-E 0.361 8.46 2.74 LDAS R RMSE MBE

11. Result: Soil moisture at Naqu 0.417 12.15 10.02 NCEP 0.562 21.25 10.16 AMSR-E 0.853 3.88 -0.17 LDAS R RMSE MBE

12. Result: Energy flux:Bowen Ratio Clean wet/dry division is showed by LDAS result, while NCEP failed to represent such a feature.

13. Result: energy fluxes at Gaize 0.949 77.19 -15.09 G0 0.878 31.05 12.88 lE 0.879 54.21 43.38 Hs R RMSE MBE

14. Result: energy fluxes at Naqu 0.967 68.85 3.72 G0 0.975 35.14 6.93 lE 0.934 42.36 35.64 Hs R RMSE MBE

15. Result: Dynamic variation Cyclonic brings moisture from the Bay of Bengal to the SE of T-P, and brings dry air mass from Taklamagan desert LDAS-UT is able to provide more realistic land surface status for research in other principles LDAS-UT NCEP

18. Thank you for your attention!