The Merging Of CLDAS Long Term Precipitation Forcing Data And Land Surface Data Assimilation Of ASCAT Soil Moisture

As an important physical quantity on the land surface,soil moisture is important to climate,agriculture and ecology.At present,soil moisture is obtained mainly by site observation,remote sensing inversion,and land model simulation.The land surface assimilation of soil moisture can make use of multiple data sources and adjust the operation of the land surface model with observation or remote sensing inversion of soil moisture,which allows the model accumulated error to be released and improve soil moisture simulation.Therefore,this paper carry out ASCAT soil moisture assimilation studies based on the China Meteorological Administration Land Surface Data Assimilation System(CLDAS),mainly including long Term precipitation driving data merging,simulation based on Noah-MP land surface model and ASCAT soil moisture assimilation.The main conclusions of this paper are as follows:(1)Long Term precipitation driving data merging:From the average years precipitation and seasons of precipitation,the CLDAS long term integrated precipitation in this paper is more close to the site observation on the scale,consistent with the climate spatial distribution of Chinese precipitation,and it can be found from the independence test that the CLDAS long term integrated precipitation is superior to the cmorph precipitation and MERRA2 precipitation in error time series,spatial distribution,different Chinese region,the monitoring of the regional automatic station and the different precipitation level.In the monitoring of"Saudel" typhoon,the CLDAS long term integrated precipitation can show the heavy rainfall process of typhoon crossing,which is better than CMORPH precipitation,MERRA2 precipitation and EMSIP precipitation,but this precipitation only integrates the the China Meteorological Administration national-station data,which is slightly lower than the site observation in magnitude and slightly less than the CMPA three-source precipitation,which combines national-automatic station,regional-station observation,satellite and radar precipitation.CLDAS long term precipitation time is more longer and considering the problem of solid precipitation,but integrating more observational data is also the future improvement of this precipitation.(2)Simulation test based on Noah-MP land surface model:The soil moistre and snow deep data are simulated by the Noah-MP land surface model respectively drived by the CLDAS long term precipitation and CLDAS2.0 precipitation.Soil moisture obtained by CLDAS long term precipitation is greater in bias but is better in the correlation coefficient compared whith the soil moisture obtained by CLDAS2.0 precipitation.Snow deep obtained by CLDAS long term precipitation is close to snow deep observation and is obviously better than snow deep obtained by CLDAS2.0,mainly because of the CLDAS long term merging precipitation adding solid precipitation information.So it can be seen that CLDAS long series precipitation can be used in land surface model simulation and has an excellent effcet;(3)ASCAT Soil Moisture Assimilation Test:By selecting different ensemble to experimented ASCAT soil moisture assimilation test after bias correction and quality control,the result show the number of different sets has little influence on assimilation from error time series,error space distribution and so on.Perturbating respectively the radiation and precipitation data to assimilate soil moisture,the results show that these have little difference.(4)Analysis of ASCAT Soil Moisture Assimilation:The ASCAT soil moisture is assmilated to Noah-MP land model,the results show that the assimilation soil moisture is more close to the observational data than the model simulation(openloop)on the national average in the time series.From the spatial distribution,assimilation improved soil moisture simulation in some areas,but for some areas,assimilation also made soil moisture simulation decreased;Assimilation of soil moisture also has a certain improvement to soil temperature simulation,but the value of the improvement is not very large because soil temperature of the model simulation has a good effect;In the case of drought monitoring,compared with the meteorological drought comprehensive monitoring map published by the National Climate Center of July 12 in 2014,results show that the effect of assimilation soil moisture is better than model simulation(openloop)in drought monitoring.