The retrieval of water vapor path and liquid waterpath from the NOAA/AMSU data

The atmospheric water plays an important role in the climate system. In this paper, we use a linear regression method to retrieve the water vapor path and liquid water path over water surfaces. The retrieval is based on data obtained from the Advanced Microwave Sounding Unit (AMSU) onboard NOAA-16 and the wind speed data obtained from the Global Forecast System (GFS). Brightness temperatures measured at 23.8 GHz are strongly related to the water vapor content in the atmosphere whereas the 31.4 GHz respond more strongly to the liquid water. For the initial validation of the method, we use the radio sounding data. Comparisons are also made between monthly mean water vapor path and the data from GFS. It is shown that the obtained results are in qualitative agreement on a large geographic region (70°S-70°N) during summer and fall.