Numerical Study On Split-window Differential Algorithm To Retrieve AMVs In Cloud-free Regions And Case Applications

It’s crucial to obtain the wind field data which has a higher spatial resolution and temporal resolution as that plays an important role in the meteorological services and scientific research. In the cloud-free regions, the wind cannot be retrieved by the traditional cloud motion technique. Thus it’s very necessary to retrieve winds to make up for the lack of winds in cloud-free regions and provide better information for the meteorological services and scientific research. The infrared channel of geostationary satellite can detect the weak texture information which is generated by the uneven distribution of atmospheric water vapor and dust aerosol in cloud-free regions. And the atmospheric motion vectors (AMVs) for clear-sky regions can be retrieved by tracking water vapor motion or dust aerosol motion. However, as the weak information is easily affected by the change of surface temperature, a suited algorithm is needed to decrease the interference of surface temperature and to extract the weak information.) Therefore, this paper carried out the following research:Based on the split-window infrared theory, this paper gives the detailed description about the split-window difference method which provides a theoretical basis for the further conduct of the retrieval of atmospheric motion vectors with satellite in cloud-free areas. This theory shows that the satellite at-sensor radiance is composed of two parts. One is the at-sensor radiance by the atmospheric attenuation of the surface emitted and the other is the infrared radiance emitted by the atmosphere. As the emission of atmospheric absorbing material is feeblish at the atmospheric window channel, what the satellite sensor accept is mainly the radiance by the atmospheric attenuation of the surface emitted, and that largely reflects surface information. While the split-window brightness temperature difference (BTD) is decided in the surface temperature, the atmospheric temperature profile, the density of atmospheric absorbing material and the difference between the absorption coefficients the split-window channels. And thus the BTD image texture mainly expresses the content distribution characteristics of the absorbing gas.Combined with the spectral response function of the FY-2E, the quantitative analysis on the influence of the observed brightness temperature caused by the factors such as the surface characteristic and the content of the absorbing gas and the main influencing height under different atmospheric conditions have been done. And this paper also has analyzed numerical simulation of extracting the weak information by using the split-window brightness temperature difference (BTD) algorithm and has applied this algorithm to instance analysis. The numerical study indicates that using the BTD images can weaken the influence of the surface temperature and highlight the distribution characteristics of water vapor and aerosol. And it also explains the feasibility and the superiority of this algorithm. Under different atmospheric conditions the main influencing heights of the water vapor content are all at about800hPa, and the dust aerosol has bigger influence on the lower atmosphere.Based on the split-window infrared theory and simulation,the instance analysis has been conducted which also shows that using the BTD images can get low-level wind in clear-sky regions which is hard to get by only using IR1or IR2images. And the results of the cases have a good consistency with the wind field of the NCEP reanalysis data.