Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface s...

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Published in:Atmospheric Chemistry and Physics
Main Authors: von Lerber, Annakaisa, Mech, Mario, Rinke, Annette, Zhang, Damao, Lauer, Melanie, Radovan, Ana, Gorodetskaya, Irina, Crewell, Susanne
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
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Online Access:https://doi.org/10.5194/acp-22-7287-2022
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spelling ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00061348 2023-05-15T14:50:08+02:00 Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic von Lerber, Annakaisa Mech, Mario Rinke, Annette Zhang, Damao Lauer, Melanie Radovan, Ana Gorodetskaya, Irina Crewell, Susanne 2022-06 electronic https://doi.org/10.5194/acp-22-7287-2022 https://noa.gwlb.de/receive/cop_mods_00061348 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00060830/acp-22-7287-2022.pdf https://acp.copernicus.org/articles/22/7287/2022/acp-22-7287-2022.pdf eng eng Copernicus Publications Atmospheric Chemistry and Physics -- http://www.atmos-chem-phys.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2069847 -- 1680-7324 https://doi.org/10.5194/acp-22-7287-2022 https://noa.gwlb.de/receive/cop_mods_00061348 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00060830/acp-22-7287-2022.pdf https://acp.copernicus.org/articles/22/7287/2022/acp-22-7287-2022.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess CC-BY article Verlagsveröffentlichung article Text doc-type:article 2022 ftnonlinearchiv https://doi.org/10.5194/acp-22-7287-2022 2022-06-12T23:11:43Z In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81∘ N. Excellent agreement (difference less than 1 %) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45 % and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and ... Article in Journal/Newspaper Arctic Greenland North Atlantic Svalbard Niedersächsisches Online-Archiv NOA Arctic Greenland Svalbard Atmospheric Chemistry and Physics 22 11 7287 7317
institution Open Polar
collection Niedersächsisches Online-Archiv NOA
op_collection_id ftnonlinearchiv
language English
topic article
Verlagsveröffentlichung
spellingShingle article
Verlagsveröffentlichung
von Lerber, Annakaisa
Mech, Mario
Rinke, Annette
Zhang, Damao
Lauer, Melanie
Radovan, Ana
Gorodetskaya, Irina
Crewell, Susanne
Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic
topic_facet article
Verlagsveröffentlichung
description In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81∘ N. Excellent agreement (difference less than 1 %) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45 % and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and ...
format Article in Journal/Newspaper
author von Lerber, Annakaisa
Mech, Mario
Rinke, Annette
Zhang, Damao
Lauer, Melanie
Radovan, Ana
Gorodetskaya, Irina
Crewell, Susanne
author_facet von Lerber, Annakaisa
Mech, Mario
Rinke, Annette
Zhang, Damao
Lauer, Melanie
Radovan, Ana
Gorodetskaya, Irina
Crewell, Susanne
author_sort von Lerber, Annakaisa
title Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic
title_short Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic
title_full Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic
title_fullStr Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic
title_full_unstemmed Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic
title_sort evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the arctic
publisher Copernicus Publications
publishDate 2022
url https://doi.org/10.5194/acp-22-7287-2022
https://noa.gwlb.de/receive/cop_mods_00061348
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00060830/acp-22-7287-2022.pdf
https://acp.copernicus.org/articles/22/7287/2022/acp-22-7287-2022.pdf
geographic Arctic
Greenland
Svalbard
geographic_facet Arctic
Greenland
Svalbard
genre Arctic
Greenland
North Atlantic
Svalbard
genre_facet Arctic
Greenland
North Atlantic
Svalbard
op_relation Atmospheric Chemistry and Physics -- http://www.atmos-chem-phys.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2069847 -- 1680-7324
https://doi.org/10.5194/acp-22-7287-2022
https://noa.gwlb.de/receive/cop_mods_00061348
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00060830/acp-22-7287-2022.pdf
https://acp.copernicus.org/articles/22/7287/2022/acp-22-7287-2022.pdf
op_rights https://creativecommons.org/licenses/by/4.0/
uneingeschränkt
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5194/acp-22-7287-2022
container_title Atmospheric Chemistry and Physics
container_volume 22
container_issue 11
container_start_page 7287
op_container_end_page 7317
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