Drivers of Snowfall Accumulation in the Central Idaho Mountains Using Long-Term High-Resolution WRF Simulations.
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| Title: | Drivers of Snowfall Accumulation in the Central Idaho Mountains Using Long-Term High-Resolution WRF Simulations. |
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| Authors: | Warms, Mikell1 (AUTHOR) mikell.warms@colorado.edu, Friedrich, Katja1 (AUTHOR), Xue, Lulin2 (AUTHOR), Tessendorf, Sarah2 (AUTHOR), Ikeda, Kyoko2 (AUTHOR) |
| Source: | Journal of Applied Meteorology & Climatology. Sep2023, Vol. 62 Issue 9, p1279-1295. 17p. 1 Chart, 14 Graphs. |
| Subjects: | Snowpack augmentation, Supercooled liquids, Rain-making, Electric power consumption, Topography, Ice clouds, Renewable energy sources |
| Geographic Terms: | Idaho |
| Abstract: | The western United States region, an economic and agricultural powerhouse, is highly dependent on winter snowpack from the mountain west. Coupled with increasing water and renewable electricity demands, the predictability and viability of snowpack resources in a changing climate are becoming increasingly important. In Idaho, specifically, up to 75% of the state's electricity production comes from hydropower, which is dependent on the timing and volume of spring snowmelt. While we know that 1 April snowpack is declining from SNOTEL observations and is expected to continue to decline as indicated by GCM predictions, our ability to understand the variability of snowfall accumulation and distribution at the regional level is less robust. In this paper, we analyze snowfall events using 0.9-km-resolution WRF simulations to understand the variability of snowfall accumulation and distribution in the mountains of Idaho between 1 October 2016 and 31 April 2017. Various characteristics of snowfall events throughout the season are evaluated, including the spatial coverage, event durations, and snowfall rates, along with the relationship between cloud microphysical variables—particularly liquid and ice water content—on snowfall amounts. Our findings suggest that efficient snowfall conditions—for example, higher levels of elevated supercooled liquid water—can exist throughout the winter season but are more impactful when surface temperatures are near or below freezing. Inefficient snowfall events are common, exceeding 50% of the total snowfall events for the year, with some of those occurring in peak winter. For such events, glaciogenic cloud seeding could make a significant impact on snowpack development and viability in the region. Significance Statement: The purpose and significance of this study is to better understand the variability of snowfall event accumulation and distribution in the Payette Mountains region of Idaho as it relates to the local topography, the drivers of snowfall events, the cloud microphysical properties, and what constitutes an efficient or inefficient snowfall event (i.e., its ability to convert atmospheric liquid water into snowfall). As part of this process, we identify how many snowfall events in a season are inefficient to determine the number of snowfall events in a season that are candidates for enhancement by glaciogenic cloud seeding. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 172853403 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Drivers of Snowfall Accumulation in the Central Idaho Mountains Using Long-Term High-Resolution WRF Simulations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Warms%2C+Mikell%22">Warms, Mikell</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mikell.warms@colorado.edu</i><br /><searchLink fieldCode="AR" term="%22Friedrich%2C+Katja%22">Friedrich, Katja</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xue%2C+Lulin%22">Xue, Lulin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tessendorf%2C+Sarah%22">Tessendorf, Sarah</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ikeda%2C+Kyoko%22">Ikeda, Kyoko</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Meteorology+%26+Climatology%22">Journal of Applied Meteorology & Climatology</searchLink>. Sep2023, Vol. 62 Issue 9, p1279-1295. 17p. 1 Chart, 14 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Snowpack+augmentation%22">Snowpack augmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Supercooled+liquids%22">Supercooled liquids</searchLink><br /><searchLink fieldCode="DE" term="%22Rain-making%22">Rain-making</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+power+consumption%22">Electric power consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Topography%22">Topography</searchLink><br /><searchLink fieldCode="DE" term="%22Ice+clouds%22">Ice clouds</searchLink><br /><searchLink fieldCode="DE" term="%22Renewable+energy+sources%22">Renewable energy sources</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Idaho%22">Idaho</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The western United States region, an economic and agricultural powerhouse, is highly dependent on winter snowpack from the mountain west. Coupled with increasing water and renewable electricity demands, the predictability and viability of snowpack resources in a changing climate are becoming increasingly important. In Idaho, specifically, up to 75% of the state's electricity production comes from hydropower, which is dependent on the timing and volume of spring snowmelt. While we know that 1 April snowpack is declining from SNOTEL observations and is expected to continue to decline as indicated by GCM predictions, our ability to understand the variability of snowfall accumulation and distribution at the regional level is less robust. In this paper, we analyze snowfall events using 0.9-km-resolution WRF simulations to understand the variability of snowfall accumulation and distribution in the mountains of Idaho between 1 October 2016 and 31 April 2017. Various characteristics of snowfall events throughout the season are evaluated, including the spatial coverage, event durations, and snowfall rates, along with the relationship between cloud microphysical variables—particularly liquid and ice water content—on snowfall amounts. Our findings suggest that efficient snowfall conditions—for example, higher levels of elevated supercooled liquid water—can exist throughout the winter season but are more impactful when surface temperatures are near or below freezing. Inefficient snowfall events are common, exceeding 50% of the total snowfall events for the year, with some of those occurring in peak winter. For such events, glaciogenic cloud seeding could make a significant impact on snowpack development and viability in the region. Significance Statement: The purpose and significance of this study is to better understand the variability of snowfall event accumulation and distribution in the Payette Mountains region of Idaho as it relates to the local topography, the drivers of snowfall events, the cloud microphysical properties, and what constitutes an efficient or inefficient snowfall event (i.e., its ability to convert atmospheric liquid water into snowfall). As part of this process, we identify how many snowfall events in a season are inefficient to determine the number of snowfall events in a season that are candidates for enhancement by glaciogenic cloud seeding. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=172853403 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1175/JAMC-D-23-0050.1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 1279 Subjects: – SubjectFull: Snowpack augmentation Type: general – SubjectFull: Supercooled liquids Type: general – SubjectFull: Rain-making Type: general – SubjectFull: Electric power consumption Type: general – SubjectFull: Topography Type: general – SubjectFull: Ice clouds Type: general – SubjectFull: Renewable energy sources Type: general – SubjectFull: Idaho Type: general Titles: – TitleFull: Drivers of Snowfall Accumulation in the Central Idaho Mountains Using Long-Term High-Resolution WRF Simulations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Warms, Mikell – PersonEntity: Name: NameFull: Friedrich, Katja – PersonEntity: Name: NameFull: Xue, Lulin – PersonEntity: Name: NameFull: Tessendorf, Sarah – PersonEntity: Name: NameFull: Ikeda, Kyoko IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 15588424 Numbering: – Type: volume Value: 62 – Type: issue Value: 9 Titles: – TitleFull: Journal of Applied Meteorology & Climatology Type: main |
| ResultId | 1 |
