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Enhancing Snow Data for Efficient Snowmelt Forecasting

Learn strategies to optimize SWE data, gauge accuracy, and utilize SNODAS for hazard alerts. Address limitations in current snow models and leverage innovative computational schemes for better predictions. Explore ways to forecast diurnal flow fluctuations and integrate snow depth observations effectively.

uriah-hood
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Enhancing Snow Data for Efficient Snowmelt Forecasting

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  1. Snow Data and Snowmelt Issues Basis of presentations Wednesday afternoon and all day Thursday

  2. Snow Data and Snowmelt Issues • How to maximize SWE data available to forecasters • Collection of accurate SWE data • Use of wind shields on NWS precipitation gauges • MAT computational scheme in NWSRFS • Lack of high elevation temperature data • Forecasting diurnal fluctuation in flow/stage+ • Use of snow depth observations in NWSRFS • Use of SNODAS information in NWSRFS • Use of SNODAS output as a snowmelt hazard alert tool • Limitations of SNOW-17 to account for variability in energy balance • IFP displays of more snow parameters

  3. Forecasting diurnal fluctuation in flow/stage

  4. Snow Data and Snowmelt Issues • How to maximize SWE data available to forecasters • Collection of accurate SWE data • Use of wind shields on NWS precipitation gauges • MAT computational scheme in NWSRFS • Lack of high elevation temperature data • Forecasting diurnal fluctuation in flow/stage+ • Use of snow depth observations in NWSRFS • Use of SNODAS information in NWSRFS • Use of SNODAS output as a snowmelt hazard alert tool • Limitations of SNOW-17 to account for variability in energy balance • IFP displays of more snow parameters

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