论文推荐|西安科技大学赵庆志教授：GNSS协同遥感卫星的大气可降水量普适反演方法

The use of remote sensing technique to monitor atmospheric water vapor is significant for weather and climate studies. However, the general methods of retrieving precipitable water vapor (PWV) with high precision and high resolution using remote sensing satellite has hardly been investigated, which becomes the focus of this paper. A general remote sensing PWV retrieval (GRPR) method that uses level-1 near-infrared (NIR) data sympathized by a global navigation satellite system (GNSS) is proposed. In this method, the atmospheric transmittance coefficients are determined by combining the radiative transmission model and the central wavelength interpolation method instead of directly using the traditional empirical values. Next, the PWV derived from remote sensing NIR data is obtained using the adaptive seasonal exponent model rather than the traditional transmittance–water vapor lookup table method. Furthermore, the accuracy of remote sensing NIR PWV is further calibrated by establishing the seasonal relationship between PWV residual and elevation. The corresponding NIR data from the Fengyun-3A (FY3A) satellite over the period of 2013–2015 in China are selected to validate the proposed method. Statistical results show the good performance of GRPR method for internal and external accuracies with root mean square (RMS) improvement rates of 76.8% and 72.4%, respectively, compared with the FY3A level-2 PWV products. In addition, the proposed method has good robustness and is almost unaffected by the PWV magnitude at different seasons. Proposed GRPR method is also applied for PWV retrieval at different time scales, further showing its superiority of retrieving PWV with high precision and high resolution. These results indicate the good application prospect of the GRPR method proposed in this study for generating remote sensing PWV products.