Development of a New Land Data Assimilation System for Improvement of Forecasting both Soil Moisture and Vegetation Dynamics

Abstract:

To improve the skill of reproducing land-atmosphere interactions in weather, seasonal, and climate prediction systems, it is necessary to simulate correctly and simultaneously the soil moisture and terrestrial biomass in land surface models. Despite the importance of the interactions between subsurface soil moisture and vegetation dynamics on the climate system both in global and regional scales, a land data assimilation approach that can effectively address these water and vegetation growth interactions has yet to be established. We develop a new land data assimilation system that can improve to simultaneously simulate surface and subsurface soil moisture and vegetation growth by assimilating a microwave observation that is sensitive to both surface soil moisture and terrestrial biomass. Our new system, Coupled Land and Vegetation Data Assimilation System (CLVDAS) comprises an eco-hydrological model that has a physically-based and sophisticated soil hydrology scheme and dynamic vegetation model that can estimate vegetation growth and senescence, and radiative transfer model that can convert land surface conditions into brightness temperatures in the microwave region. The CLVDAS firstly optimizes hydrological and ecological unknown parameters in the model at the same time by using the shuffled complex evolution method. Secondly, the model states of surface soil moisture, root-zone soil moisture, and leaf area index are adjusted by using genetic particle filter. We can justify to adjust the root-zone soil moisture from a microwave observation of the earth surface since we explicitly model subsurface water – vegetation dynamics interactions. From the point-scale evaluation at the in-situ observation sites in Mali, Mongolia, the United States, and Australia, we confirm the CLVDAS significantly improve the skill of simulating vertical soil moisture distribution and vegetation dynamics by assimilating microwave brightness temperatures from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and its successor (AMSR2).