A New Methodology for Detection of Fog over the Indian Region using INSAT-3D Data

Fog estimation from the satellite is crucial as the fog has a significant impact on the road, rail, and air traffic, thereby influencing the economy and human life. To understand and deal with several influence factors, spatially and temporally high-resolution fog information is required. This study has attempted to develop an algorithm for daytime fog retrieval from INSAT-3D Imager data over the Indian region. The operational algorithm for detecting fog using INSAT-3D data provides low stratus cloud and fog as its product. The operational product does not provide any distinction between low stratus clouds and fog. The segregation of fog from low-level stratus clouds is still an open area. This work proposes a methodology to segregate low stratus clouds from fog. The work presents a two-step approach. In the first step, it implements the methodology proposed by Chaurasia and Gohil (2015), for the detection of daytime low stratus clouds/fog using INSAT-3D data, and in the second step, it proposes a methodology to segregate fog from low stratus clouds. The daytime fog retrieval methodology primarily makes use of visible and thermal channels to distinguish fog from high/mid-level clouds, snow, and bright land area. However, the fog and low-level stratus clouds cannot be segregated using only visible and thermal channels, as the top of both fog and low-level stratus appears similar in these two channels. In the present study, an attempt has been made to separate fog from low stratus clouds using a wind threshold. The final segregated fog product from the proposed methodology has been validated with ground observation. The percentage of detection is observed to be 86% with a false alarm of 4% for the season December 2018-January 2019. The fog products with and without wind threshold have also been compared with INSAT-3D operational fog products and MODIS true color composite images. The comparison has shown the robustness of the algorithm in segregating the fog and low-level stratus clouds.