Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective
Mid-level clouds play a crucial role in the Arctic. Due to observational limitations, there is scarce research on the long-term evolution of Arctic mid-level clouds. From a satellite perspective, this study attempts to analyze the seasonal variations in Arctic mid-level clouds and explore the possib...
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MDPI AG
2024-01-01
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Online Access: | https://www.mdpi.com/2072-4292/16/1/202 |
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author | Xi Wang Jian Liu Hui Liu |
author_facet | Xi Wang Jian Liu Hui Liu |
author_sort | Xi Wang |
collection | DOAJ |
description | Mid-level clouds play a crucial role in the Arctic. Due to observational limitations, there is scarce research on the long-term evolution of Arctic mid-level clouds. From a satellite perspective, this study attempts to analyze the seasonal variations in Arctic mid-level clouds and explore the possible relationships with sea ice changes using observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) over the past two decades. For mid-level clouds of three layers (648, 548, and 447 hPa) involved in AIRS, high values of effective cloud fraction (ECF) occur in summer, and low values primarily occur in early spring, while the seasonal variations are different. The ECF anomalies are notably larger at 648 hPa than those at 548 and 447 hPa. Meanwhile, the ECF values at 648 hPa show a clear reduced seasonal variability for the regions north of 80°N, which has its minimum coefficient of variation (CV) during 2019 to 2020. The seasonal CV is relatively lower in the regions dominated by Greenland and sea areas with less sea ice coverage. Analysis indicates that the decline in mid-level ECF’s seasonal mean CV is closely correlated to the retreat of Arctic sea ice during September. Singular value decomposition (SVD) analysis reveals a reverse spatial pattern in the seasonal CV anomaly of mid-level clouds and leads anomaly. However, it is worth noting that this pattern varies by region. In the Greenland Sea and areas near the Canadian Arctic Archipelago, both CV and leads demonstrate negative (positive) anomalies, probably attributed to the stronger influence of atmospheric and oceanic circulations or the presence of land on the sea ice in these areas. |
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id | doaj.art-da0c29a9564c44c9bca98b65090b2c94 |
institution | Directory Open Access Journal |
issn | 2072-4292 |
language | English |
last_indexed | 2024-03-08T14:58:48Z |
publishDate | 2024-01-01 |
publisher | MDPI AG |
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series | Remote Sensing |
spelling | doaj.art-da0c29a9564c44c9bca98b65090b2c942024-01-10T15:07:58ZengMDPI AGRemote Sensing2072-42922024-01-0116120210.3390/rs16010202Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite PerspectiveXi Wang0Jian Liu1Hui Liu2National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, ChinaNational Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, ChinaNational Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, ChinaMid-level clouds play a crucial role in the Arctic. Due to observational limitations, there is scarce research on the long-term evolution of Arctic mid-level clouds. From a satellite perspective, this study attempts to analyze the seasonal variations in Arctic mid-level clouds and explore the possible relationships with sea ice changes using observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) over the past two decades. For mid-level clouds of three layers (648, 548, and 447 hPa) involved in AIRS, high values of effective cloud fraction (ECF) occur in summer, and low values primarily occur in early spring, while the seasonal variations are different. The ECF anomalies are notably larger at 648 hPa than those at 548 and 447 hPa. Meanwhile, the ECF values at 648 hPa show a clear reduced seasonal variability for the regions north of 80°N, which has its minimum coefficient of variation (CV) during 2019 to 2020. The seasonal CV is relatively lower in the regions dominated by Greenland and sea areas with less sea ice coverage. Analysis indicates that the decline in mid-level ECF’s seasonal mean CV is closely correlated to the retreat of Arctic sea ice during September. Singular value decomposition (SVD) analysis reveals a reverse spatial pattern in the seasonal CV anomaly of mid-level clouds and leads anomaly. However, it is worth noting that this pattern varies by region. In the Greenland Sea and areas near the Canadian Arctic Archipelago, both CV and leads demonstrate negative (positive) anomalies, probably attributed to the stronger influence of atmospheric and oceanic circulations or the presence of land on the sea ice in these areas.https://www.mdpi.com/2072-4292/16/1/202mid-level cloudsArcticseasonal variabilitysea iceAIRS |
spellingShingle | Xi Wang Jian Liu Hui Liu Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective Remote Sensing mid-level clouds Arctic seasonal variability sea ice AIRS |
title | Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective |
title_full | Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective |
title_fullStr | Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective |
title_full_unstemmed | Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective |
title_short | Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective |
title_sort | seasonal variability of arctic mid level clouds and the relationships with sea ice from 2003 to 2022 a satellite perspective |
topic | mid-level clouds Arctic seasonal variability sea ice AIRS |
url | https://www.mdpi.com/2072-4292/16/1/202 |
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