When the background model is changed from the RG96 model, to the most recent TS18 model, the CPCP tends to decrease for lower values, but tends to increase for higher values. We find that the CPCP is reduced when the PolarDARN radars are introduced, but then increases again when the StormDARN radars are added.
We study changes in the Heppner-Maynard boundary (HMB), the cross polar cap potential (CPCP), the number of backscatter echoes ( n) and the χ 2/ n statistic which is a measure of the global agreement between the measured and fitted velocities. This enables us to simulate how much information was missing from older SuperDARN research. Using data from 2012 to 2018, we produce five different versions of the widely used convection maps, using limited backscatter ranges, background models and the exclusion/inclusion of data from specific radar groups such as the StormDARN radars.
#NETWORK RADAR REVIEW SOFTWARE#
Alongside software developments, this has resulted in many different versions of the convection maps data set being available. Keywords: radar, snow water equivalent, wet snow, snow remote sensing.The Super Dual Auroral Radar Network (SuperDARN) was built to study ionospheric convection and has in recent years been expanded geographically. This presentation will review the current state-of-the-art of radar remote sensing of snow from ground-based, airborne, and satellite-based platforms, in the context of snow products that will be available and useful to avalanche forecasters in the near future. Recent results from our network of tower-based radar systems, as well as results from the recent intensive NASA SnowEx airborne snow remote sensing campaign will be presented. Recent airborne snow radar missions, and preliminary results from recently launched satellitebased radar sensors, have indicated that operational monitoring of changes in snow water equivalent and depth, as well as recent avalanche activity, will likely be possible at high resolution in the near future from space. Ground-based radar systems can track snow water equivalent, estimate snow density and liquid water content, are used to measure falling snow, and for avalanche detection. Changes in snowpack mass cause changes in microwave radar amplitude and phase, and radar is also being used to monitor snowfall rates. Microwave radar is highly sensitive to liquid water, providing both a challenge to estimating snow mass, as well as an opportunity for monitoring the spatial extent of melt and rain-on-snow events.
Satellite radar with spatial resolutions on the order of meters, and repeat intervals on the order of days, have just recently removed some of the major limitations for radar remote sensing in the mountains. Snow radar remote sensing is just now reaching a maturity level where sensors and data are becoming available at the necessary spatial and temporal resolutions, and at the appropriate frequencies, that are relevant for avalanche forecasting. Although research over the past decade has demonstrated the potential for monitoring snow using remote sensing, current operational snow remote sensing products are limited to snow covered area, which is of little direct use to avalanche forecasters. While these remote sensing products provide valuable information about approaching storms, and have been part of an avalanche forecaster’s daily routine for decades, we still do not have remote sensing products which provide information about snowfall amounts, nor total snow on the ground.
Title: Radar remote sensing of mountain snow: a review of current ground-based, airborne and satellite-based approaches to monitoring snow properties Item: Radar remote sensing of mountain snow: a review of current ground-based, airborne and satellite-based approaches to monitoring snow properties
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