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Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign
Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah, USA.
Department of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA.
Norwegian Meteorological Institute, Oslo, Norway.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.ORCID iD: 0000-0003-3701-7925
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2022 (English)In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 103, no 8, p. E1762-E1780Article in journal (Refereed) Published
Abstract [en]

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.

Place, publisher, year, edition, pages
American Meteorological Society, 2022. Vol. 103, no 8, p. E1762-E1780
Keywords [en]
Climate variability, Ice crystals, Snow cover, In situ atmospheric observations, Radars/Radar observations, Numerical weather prediction/forecasting
National Category
Meteorology and Atmospheric Sciences
Research subject
Atmospheric Science
Identifiers
URN: urn:nbn:se:ltu:diva-93326DOI: 10.1175/bams-d-21-0007.1ISI: 000886646700003Scopus ID: 2-s2.0-85137639240OAI: oai:DiVA.org:ltu-93326DiVA, id: diva2:1700014
Funder
EU, European Research Council, StG 758005
Note

Validerad;2022;Nivå 2;2022-09-29 (sofila);

Funder:  National Science Foundation (grants nos. 1531930 and 1531690); NASA NIP (grant no. 80NSSC21K0931); Norwegian Research Council (grant no. 224106/E10)

Available from: 2022-09-29 Created: 2022-09-29 Last updated: 2023-11-10Bibliographically approved

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Kuhn, ThomasVásquez Martín, Sandra

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