An Application Study On Near Surface Channels Of Hyper-spectral Atmospheric Infrared Sounder

The main reason that the radiation data of near surface channels are not effectively used is the complexity of the underlying, especially the surface temperature and the surface emissivity as two important characteristic physical quantities of the underlying are difficult to estimate. In order to solve this problem, this paper uses actual satellite observation data to adjust the surface temperature through one dimensional variational(1DVar) analysis system. According to the characteristics of atmospheric infrared wave band, we choose the channels near11microns where the change of the surface emissivity is small to do experiments. First of all, we use1DVar method to do simulated experiment to test the capacity of adjusting the background surface temperature, and the scheme that adjusting the surface temperature alone is chose as1DVar temperature adjustment scheme. Secondly, the surface of the ocean underlying is relatively simple, so this paper uses1DVar method and the AIRS observed data to adjust the background sea surface temperature if the FOV(field of view) is clear. Finally, we utilize the GRAPES model to do cycle assimilation, then research the influence of the analytic fields after adjusting the sea surface temperature. The test results are as follows:1. Using1DVar and satellite observation data to adjust the surface temperature, if the estimate of the surface emissivity is accurate, the surface temperature will be adjusted very effectively. With the increasing of the surface emissivity error, the adjustment effect is fallen, but the impact caused by the surface emissivity error is limited; In consideration of the temperature profile error, the humidity profile error and satellite observation error comprehensively,1DVar still able to adjust the surface temperature effectively.2. After using1DVar and satellite observation data of AIRS to adjust the background surface temperature if the FOV is clear, not only makes the deviation between simulation brightness temperature and observation brightness temperature of lower channels close to0, but also the distribution of the deviation is more concentrated. The simulation brightness temperature and the observation brightness temperature of lower channels are more matched after adjusting the surface temperature. 3. Using GRAPES model to do the ten-day assimilation test. The results show that the temperature after adjusting effectively improves the analytic fields. The height fields of the lower atmosphere, the middle atmosphere and the upper atmosphere are all good improved. The humidity fields and the wind fields are also obviously improved in the lower atmosphere.