Detecting Snowfall Events over Mountainous Areas Using Optical Imagery

Abstract

Snowfall over mountainous areas not only has important implications on the water cycle and the Earth’s radiation balance, but also causes potentially hazardous weather. However, snowfall detection remains one of the most difficult problems in modern hydrometeorology. We present a method for detecting snowfall events from optical satellite data for seasonal snow in mountainous areas. The proposed methodology is based on identifying expanded snow cover or suddenly declined snow grain size using time series images, from which it is possible to detect the location and time of snowfall events. The methodology was tested with Moderate Resolution Imaging Spectroradiometer (MODIS) daily radiance data for an entire hydrologic year from July 2014 to June 2015 in the mountainous area of the Manas River Basin, Northwest China. The study evaluated the recordings of precipitation events at eighteen meteorological stations in the study area prove the effectiveness of the proposed method, showing that there was more liquid precipitation in the second and third quarter, and more solid precipitation in the first and fourth quarter.

Downscaling Snow Depth Mapping by Fusion of Microwave and Optical Remote-Sensing Data Based on Deep Learning

“…Air temperature has a significant influence on snow freezing and melting. The change of temperature will influence the content of liquid water in snow, then changes the grain size and density of snow, which will affect the detection of snow depth by satellite microwave data [53]. The air temperature used in the downscaling snow depth retrieval model was from the Global Land Data Assimilation System (GLDAS) data [54,55], GLDAS-Noah is the Noah model driven by the Global Land Data Assimilation System, version 2.1 (GLDAS-2.1) (https://disc.gsfc.nasa.gov/datasets/ (accessed on 1 November 2020)), which was developed jointly by scientists at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) and the National Oceanic and Atmospheric Administration (NOAA) NCEP [56].…”