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https://hdl.handle.net/11681/43582| Title: | The Blowing Snow Hazard Assessment and Risk Prediction model : a Python based downscaling and risk prediction for snow surface erodibility and probability of blowing snow |
| Authors: | Letcher, Theodore W. LeGrand, Sandra L. Polashenski, Christopher M. |
| Keywords: | Visibility Extreme cold Weather prediction Cold regions--Weather Blizzards--Visibility Snow Wind-snow interaction Snow erosion Winter storms--Visibility |
| Publisher: | Engineer Research and Development Center (U.S.) |
| Series/Report no.: | Special Report (Engineer Research and Development Center (U.S.)) ; no. ERDC/CRREL SR-22-1 |
| Abstract: | Blowing snow is an extreme terrain hazard causing intermittent severe reductions in ground visibility and snow drifting. These hazards pose significant risk to operations in snow-covered regions. While many ingredients-based forecasting methods can be employed to predict where blowing snow is likely to occur, there are currently no physically based tools to predict blowing snow from a weather forecast. However, there are several different process models that simulate the transport of snow over short distances that can be adapted into a terrain forecasting tool. This report documents a downscaling and blowing-snow prediction tool that leverages existing frameworks for snow erodibility, lateral snow transport, and visibility, and applies these frameworks for terrain prediction. This tool is designed to work with standard numerical weather model output and user-specified geographic models to generate spatially variable forecasts of snow erodibility, blowing snow probability, and deterministic blowing-snow visibility near the ground. Critically, this tool aims to account for the history of the snow surface as it relates to erodibility, which further refines the blowing-snow risk output. Qualitative evaluations of this tool suggest that it can provide more precise forecasts of blowing snow. Critically, this tool can aid in mission planning by downscaling high-resolution gridded weather forecast data using even higher resolution terrain dataset, to make physically based predictions of blowing snow. |
| Description: | Special Report |
| Gov't Doc #: | ERDC/CRREL SR-22-1 |
| Rights: | Approved for Public Release; Distribution is Unlimited |
| URI: | https://hdl.handle.net/11681/43582 http://dx.doi.org/10.21079/11681/43582 |
| Appears in Collections: | Special Report |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ERDC-CRREL SR-22-1.pdf | 4.68 MB | Adobe PDF |  View/Open |