Abstract
The use of Special Sensor Microwave Imager (SSM/I) data for snow cover detection has been well documented since the launch of the first Defence Meteorological Satellite Program (DMSP) platform in 1987. One of the major problems yet to be resolved is the successful discrimination and subsequent removal of precipitation areas from snow cover estimates at high latitudes: this can have a significant impact on the ability to detect snow cover. Both snow cover and precipitation can exhibit similar responses at SSM/I microwave frequencies. The majority of snow cover algorithms eliminate precipitation using a single brightness temperature threshold at either 19 or 22GHz and perform adequately under most conditions. It has been observed that this threshold must be varied under given surface and atmospheric conditions by as much as 5-10 K. This can result in large errors in both snow cover and precipitation estimates when climatically aggregated, but is also evident in some individual case study events. By using additional thermal infrared (IR) data from the DMSP Operational Line Scanner (OLS) a synergistic approach has been applied. In theory a snow cover will have a much warmer OLS IR temperature than the type of precipitating clouds that give a similar response at microwave frequencies to the snow cover. The IR data can be used to identify more accurately the snow cover. The OLS has the advantage also of an improved spatial resolution over the SSM/I, and a synergistic approach will not deteriorate the spatial resolution of the SSM/I estimate. A synergistic algorithm has been developed and tested over three case study areas and demonstrates a qualitative improvement in the detection of snow cover under difficult conditions.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call