Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Abstract

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (TB) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.

Frequency and distribution of winter melt events from passive microwave satellite data in the pan-Arctic, 1988–2013

“…The PMW series is also consistent over time unlike some reanalysis datasets. Several studies have focused on the development of ROS detection methods using PMW data and encouraging results were obtained at some field sites (e.g., Dolant et al, 2016;Grenfell and Putkonen, 2008;Langlois et al, 2016). Future work will focus on the detection of pan-Arctic ice lenses (from both melt-refreeze and ROS events) by integrating PMW techniques.…”

“…Satellite active and passive microwave measurements have been widely used for snowmelt detection over various components of the Arctic cryosphere during the spring melt period (e.g., Kim et al, 2011;Markus et al, 2009;Tedesco, 2007;Wang et al, 2011). Only a few satellite studies have focused on winter melt or ROS detection, and are mainly for specific regions or limited time periods (Bartsch, 2010;Bartsch et al, 2010;Dolant et al, 2016;Grenfell and Putkonen, 2008;Semmens et al, 2013;Wilson et al, 2013). Here we develop an algorithm to detect winter melt from satellite passive microwave (PMW) data over panArctic snow-covered land areas north of 50 • N for the period 1988-2013.…”

Assessment of the Barren Ground Caribou Die‐off During Winter 2015–2016 Using Passive Microwave Observations

“…We used previously defined brightness temperature indexes for ice crust detection within the snowpack (Montpetit, 2015) and DOLANT ) suggest poor foraging conditions combined with low mobility for caribou rain-on-snow event detection (Dolant et al, 2016(Dolant et al, , 2017. We used previously defined brightness temperature indexes for ice crust detection within the snowpack (Montpetit, 2015) and DOLANT ) suggest poor foraging conditions combined with low mobility for caribou rain-on-snow event detection (Dolant et al, 2016(Dolant et al, , 2017.…”

“…Strong winds and rain-on-snow events are the main meteorological events leading to a denser snowpack and ice crust formation. Therefore, an unusual number of storm occurrence, or rain-on-snow events (e.g., Dolant et al, 2016Dolant et al, , 2017, during a winter season represents a serious threat to caribou survival in the Arctic. Hence, the objective of this study is to investigate the possible causes of the PCI's caribou die-off by analyzing anomalies in weather events that could generate significant changes in snow conditions.…”

“…Here we propose an approach for wind slab detection using microwave satellite data. We used previously defined brightness temperature indexes for ice crust detection within the snowpack (Montpetit, 2015) ) suggest poor foraging conditions combined with low mobility for caribou rain-on-snow event detection (Dolant et al, 2016(Dolant et al, , 2017. A new sensitivity analysis based on a modeling approach shows the usefulness of these indexes for wind slab detection for arctic snow type.…”