Relationship between Synoptic Weather Patterns and Topography on Snowfall in the Idaho Mountainous Regions during the SNOWIE Project

Zhixing Xie aDepartment of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

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Katja Friedrich aDepartment of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

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Sarah A. Tessendorf bResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Lulin Xue bResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Sisi Chen bResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Theodore Whittock aDepartment of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

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Bart Geerts cDepartment of Atmospheric Science, University of Wyoming, Laramie, Wyoming

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Kyoko Ikeda bResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Abstract

Snowpack melting is a crucial water resource for local ecosystems, agriculture, and hydropower in the intermountain west of the U.S. Glaciogenic seeding, a method widely used in mountain regions to enhance precipitation, has been subject to numerous field studies aiming to understand and validate this mechanism. However, investigating precipitation distribution and amounts in mountainous areas is complicated due to the intricate interplay of synoptic circulation patterns and local complex topography. These interactions significantly influence microphysical processes, ultimately affecting the amount and distribution of surface precipitation. To address these challenges, this study leverages Weather Research and Forecasting (WRF) model simulations, providing high-resolution (900 m), hourly data, spanning the Payette region of Idaho from January to March 2017. We applied the self-organizing map approach to categorize the most representative synoptic circulation patterns and conducted a multi-scale analysis to explore their associated environmental conditions and microphysical processes, aiming to assess the cloud seeding potential. The analysis identified four primary synoptic patterns: cold zonal flow (CZF), cold southwesterly flow (CSWF), warm zonal flow (WZF), and warm southwesterly flow (WSWF), constituting 21.3%, 23.1%, 30.0%, and 25.5%, respectively. CSWF and WSWF demonstrated efficiency in generating natural precipitation. These patterns were characterized by abundant supercooled liquid water (SLW) and ice particles, facilitating cloud droplet growth through seeder-feeder processes. On the other hand, CZF exhibited the least SLW and limited potential for cloud seeding, while WZF displayed a lower ice water content but substantial SLW in the diffusion/dendritic growth layer, suggesting a favorable scenario for cloud seeding.

© 2024 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Zhixing Xie, Zhixing.Xie@colorado.edu

Abstract

Snowpack melting is a crucial water resource for local ecosystems, agriculture, and hydropower in the intermountain west of the U.S. Glaciogenic seeding, a method widely used in mountain regions to enhance precipitation, has been subject to numerous field studies aiming to understand and validate this mechanism. However, investigating precipitation distribution and amounts in mountainous areas is complicated due to the intricate interplay of synoptic circulation patterns and local complex topography. These interactions significantly influence microphysical processes, ultimately affecting the amount and distribution of surface precipitation. To address these challenges, this study leverages Weather Research and Forecasting (WRF) model simulations, providing high-resolution (900 m), hourly data, spanning the Payette region of Idaho from January to March 2017. We applied the self-organizing map approach to categorize the most representative synoptic circulation patterns and conducted a multi-scale analysis to explore their associated environmental conditions and microphysical processes, aiming to assess the cloud seeding potential. The analysis identified four primary synoptic patterns: cold zonal flow (CZF), cold southwesterly flow (CSWF), warm zonal flow (WZF), and warm southwesterly flow (WSWF), constituting 21.3%, 23.1%, 30.0%, and 25.5%, respectively. CSWF and WSWF demonstrated efficiency in generating natural precipitation. These patterns were characterized by abundant supercooled liquid water (SLW) and ice particles, facilitating cloud droplet growth through seeder-feeder processes. On the other hand, CZF exhibited the least SLW and limited potential for cloud seeding, while WZF displayed a lower ice water content but substantial SLW in the diffusion/dendritic growth layer, suggesting a favorable scenario for cloud seeding.

© 2024 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Zhixing Xie, Zhixing.Xie@colorado.edu
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