Dear Cryolist,
We would like to encourage abstract submissions to the snow processes session at the January 2021 AMS meeting in New Orleans -- Linking Snow Hydrology and Society through Remote Sensing, Modeling, and Data Assimilation. The abstract deadline is Monday, August 3rd.
To submit: https://ams.confex.com/ams/101ANNUAL/webprogrampreliminary/Session56734.html
Please note that AMS has not yet decided whether the Annual Meeting will be help in person or remotely. We anticipate a decision will be made prior to the submission deadline.
Session chairs:
Melissa Wrzesien (melissa.l.wrzesien@nasa.gov)
Eli Deeb (Elias.J.Deeb@erdc.dren.mil)
Carrie Vuyovich (carrie.m.vuyovich@nasa.gov)
Feel free to reach out if you have any questions.
Best,
Melissa Wrzesien
Linking Snow Hydrology and Society through Remote Sensing, Modeling, and Data Assimilation
In snow-dominated basins across the globe, efficient water resource management requires accurate, timely estimates of snow water equivalent (SWE), snow melt onset, and other key snow and hydrologic variables. Melting snow provides a reliable water supply and can also produce wide-scale flooding hazards, particularly when combined with rainfall. Accurate estimates of snow volume, melt timing, and other heterogeneous properties of the snow and landscape are critical in accurately predicting runoff response for water resource and hydropower management. Remote sensing and modeling techniques provide methods for observing and detecting snow evolution, onset of snowmelt, spatial extent of melt processes, and vulnerability to extreme flood hazards that may result. Local and regional snow models have shown the ability to estimate snow properties, such as snow mass, density, and albedo. Observational, in-situ datasets that drive these models with meteorological inputs and modify the model through data assimilation techniques are critical in accurately portraying the natural phenomena of snow evolution. This session invites research on existing and novel methods for remote sensing, modeling, and data assimilation of snow hydrology, particularly efforts that identify and overcome gaps in the current knowledge of snow observation and modeling. We encourage submissions that connect snow accumulation and melt with human impacts, such as data assimilation to improve streamflow forecasting or operational modeling of snowmelt-derived flooding.
