Study Of The Microwave Brightness Temperature Data Quality Control In Land Data Assimilation

Soil moisture is one of the most important physical quantity for land surface process. It actually affects between land and atmosphere of material, energy balance through the impact between land surface and atmospheric moisture,sensible heat and latent heat flux and finally have an important influence on the climate.Using satellite observation data into land data assimilation system to access optimal estimate of soil moisture,has important significance on numerical weather prediction and short-term climate prediction. This paper’s research objective is according to Land Data Assimilation System of Institute of Atmospheric Physics, Chinese Academy of sciences (LDAS-IAP/CAS),on the basis of sensitivity to land surface and cloud parameters of observation operator,build a relatively perfect satellite microwave brightness temperature quality control solution.Based on the FY2C atmosphere forcing data which has high space and time resolution,make soil moisture assimilation and simulation test separately by LDAS-IAP/CAS and CLM3.0.Contrast assimilated results pre and after this quality control and simulated result,and take advantage of agriculture meteorologic soil moisture observed station to validation,so as to assess improvement of assimilation results by quality control solution in this paper,also can provide a preliminary of making a better quality control methods.Main conclusions are as follows.(1)Through the AMRE-E microwave brightness temperature (TB) simulating test of radiative transfer model CRTM,10.65GHz vertical polarization channel has the minimum error between simulated TB and satellite observed TB, which within0.5K.Channel10.65V is sensitive to soil moisture, and influenced by cloud and rainy atmosphere within0.5K.(2)According to land data assimilation system’s character, put forward a satellite observed microwave brightness temperature quality control solution,which could remove data that not well simulated by observation operator and has large observation error.Making five years AMSR-E channel10.65V TB data between July2005and June2010at last.(3)By contrast with China soil moisture assimilation and simulation results,we can see the assimilation result which by means of observation data quality control can describe soil moisture distribution features of China. On the one hand,it can reflect dry center in the Northwest China,which not be described by CLM3.0.On the other hand,it is closer to station observed data than assimilation results by old quality control.Statistics analysis also shows assimilation result is improved by the observation data quality control solution in this paper.