Detecting snowfall events over the Arctic using optical and microwave satellite measurements

The precipitation over the Arctic region is a difficult quantity to determine with high accuracy, as the in situ observation network is sparse, and current climate models, atmospheric reanalyses, and direct satellite-based precipitation observations suffer from diverse difficulties that hinder the c...

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Published in:Hydrology and Earth System Sciences
Main Authors: Jääskeläinen, Emmihenna, Kouki, Kerttu, Riihelä, Aku
Format: Text
Language:English
Published: 2024
Subjects:
Online Access:https://doi.org/10.5194/hess-28-3855-2024
https://hess.copernicus.org/articles/28/3855/2024/
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spelling ftcopernicus:oai:publications.copernicus.org:hess116149 2024-09-15T18:25:41+00:00 Detecting snowfall events over the Arctic using optical and microwave satellite measurements Jääskeläinen, Emmihenna Kouki, Kerttu Riihelä, Aku 2024-08-23 application/pdf https://doi.org/10.5194/hess-28-3855-2024 https://hess.copernicus.org/articles/28/3855/2024/ eng eng doi:10.5194/hess-28-3855-2024 https://hess.copernicus.org/articles/28/3855/2024/ eISSN: 1607-7938 Text 2024 ftcopernicus https://doi.org/10.5194/hess-28-3855-2024 2024-08-28T05:24:22Z The precipitation over the Arctic region is a difficult quantity to determine with high accuracy, as the in situ observation network is sparse, and current climate models, atmospheric reanalyses, and direct satellite-based precipitation observations suffer from diverse difficulties that hinder the correct assessment of precipitation. We undertake a proof-of-concept investigation into how accurately optical satellite observations, namely Sentinel-2 surface-reflectance-based grain-size-connected specific surface area of snow (SSA), and microwave-based snow water equivalent (SWE) estimates can detect snowfall over the Arctic. In addition to the satellite data, we also include ERA5-Land SWE data to support the analysis. Here, we chose a limited area (a circle of 100 km radius around Luosto radar located in Northern Finland) and a short time period (covering March 2018) to test these data sources and their usability in this precipitation assessment problem. We classified differences between observations independently for SSA and SWE and compared the results to the radar-based snowfall information. These initial results are promising. Situations with snowfall are classified with high recalls, 64 % for the satellite-based SWE, 77 % for ERA5-Land-based SWE, and around 90 % for SSA compared to radar-based data. Cases without snowfall are more difficult to classify correctly using satellite-based data. The recall values are 34 % for satellite-based SWE and vary from almost 60 % to over 70 % for SSA. SWE from ERA5-Land has the highest recall value for cases without snowfall, 80 %. These results indicate that optical and microwave-based satellite observations can be used to detect snowfall events over the Arctic. Text Northern Finland Copernicus Publications: E-Journals Hydrology and Earth System Sciences 28 16 3855 3870
institution Open Polar
collection Copernicus Publications: E-Journals
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language English
description The precipitation over the Arctic region is a difficult quantity to determine with high accuracy, as the in situ observation network is sparse, and current climate models, atmospheric reanalyses, and direct satellite-based precipitation observations suffer from diverse difficulties that hinder the correct assessment of precipitation. We undertake a proof-of-concept investigation into how accurately optical satellite observations, namely Sentinel-2 surface-reflectance-based grain-size-connected specific surface area of snow (SSA), and microwave-based snow water equivalent (SWE) estimates can detect snowfall over the Arctic. In addition to the satellite data, we also include ERA5-Land SWE data to support the analysis. Here, we chose a limited area (a circle of 100 km radius around Luosto radar located in Northern Finland) and a short time period (covering March 2018) to test these data sources and their usability in this precipitation assessment problem. We classified differences between observations independently for SSA and SWE and compared the results to the radar-based snowfall information. These initial results are promising. Situations with snowfall are classified with high recalls, 64 % for the satellite-based SWE, 77 % for ERA5-Land-based SWE, and around 90 % for SSA compared to radar-based data. Cases without snowfall are more difficult to classify correctly using satellite-based data. The recall values are 34 % for satellite-based SWE and vary from almost 60 % to over 70 % for SSA. SWE from ERA5-Land has the highest recall value for cases without snowfall, 80 %. These results indicate that optical and microwave-based satellite observations can be used to detect snowfall events over the Arctic.
format Text
author Jääskeläinen, Emmihenna
Kouki, Kerttu
Riihelä, Aku
spellingShingle Jääskeläinen, Emmihenna
Kouki, Kerttu
Riihelä, Aku
Detecting snowfall events over the Arctic using optical and microwave satellite measurements
author_facet Jääskeläinen, Emmihenna
Kouki, Kerttu
Riihelä, Aku
author_sort Jääskeläinen, Emmihenna
title Detecting snowfall events over the Arctic using optical and microwave satellite measurements
title_short Detecting snowfall events over the Arctic using optical and microwave satellite measurements
title_full Detecting snowfall events over the Arctic using optical and microwave satellite measurements
title_fullStr Detecting snowfall events over the Arctic using optical and microwave satellite measurements
title_full_unstemmed Detecting snowfall events over the Arctic using optical and microwave satellite measurements
title_sort detecting snowfall events over the arctic using optical and microwave satellite measurements
publishDate 2024
url https://doi.org/10.5194/hess-28-3855-2024
https://hess.copernicus.org/articles/28/3855/2024/
genre Northern Finland
genre_facet Northern Finland
op_source eISSN: 1607-7938
op_relation doi:10.5194/hess-28-3855-2024
https://hess.copernicus.org/articles/28/3855/2024/
op_doi https://doi.org/10.5194/hess-28-3855-2024
container_title Hydrology and Earth System Sciences
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