Evaluation of Ensemble Mapping of Snow Water Equivalent in Utah Combining Land-Based Models and Gridded Products for Bias Correction
Location
Logan, UT
Start Date
3-29-2022 4:15 PM
End Date
3-29-2022 7:00 PM
Description
April 1st snow water equivalent (SWE) is used by many western states to determine snowpack conditions as part of water management planning. Land-based weather stations provide accurate measures of local snowpack characteristics but, due to spatial sparsity, struggle to characterize state or regional landscapes with consistent accuracy. On the other hand, several organizations provide daily gridded climate products, including SWE estimates, at high resolution but may struggle to appropriately characterize local snowpack conditions in mountainous terrain. This study investigates the accuracy and bias of SWE predictions throughout Utah and proposes a bias correction approach based on the deviations of the gridded products from direct measurements of the snowpack. In addition, an adaptive ensemble modeling approach is proposed that adjusts the gridded climate products in locations with a high density of direct measurements of the snowpack. The paper concludes with a comparison of the results of ensemble method and gridded products and discusses potential improvements to currently available SWE maps.
Evaluation of Ensemble Mapping of Snow Water Equivalent in Utah Combining Land-Based Models and Gridded Products for Bias Correction
Logan, UT
April 1st snow water equivalent (SWE) is used by many western states to determine snowpack conditions as part of water management planning. Land-based weather stations provide accurate measures of local snowpack characteristics but, due to spatial sparsity, struggle to characterize state or regional landscapes with consistent accuracy. On the other hand, several organizations provide daily gridded climate products, including SWE estimates, at high resolution but may struggle to appropriately characterize local snowpack conditions in mountainous terrain. This study investigates the accuracy and bias of SWE predictions throughout Utah and proposes a bias correction approach based on the deviations of the gridded products from direct measurements of the snowpack. In addition, an adaptive ensemble modeling approach is proposed that adjusts the gridded climate products in locations with a high density of direct measurements of the snowpack. The paper concludes with a comparison of the results of ensemble method and gridded products and discusses potential improvements to currently available SWE maps.