Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019
Recent changes in Earth’s climate system have significantly affected the radiation budget and its year-to-year variations at top of the atmosphere (TOA). Observing high-latitude TOA fluxes is still challenging from space, because spatial inhomogeneity of surface/atmospheric radiative processes and s...
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ftmdpi:oai:mdpi.com:/2072-4292/12/9/1460/ 2023-08-20T03:59:16+02:00 Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019 Dong L. Wu Jae Nyung Lee Kyu-Myong Kim Young-Kwon Lim agris 2020-05-05 application/pdf https://doi.org/10.3390/rs12091460 EN eng Multidisciplinary Digital Publishing Institute Environmental Remote Sensing https://dx.doi.org/10.3390/rs12091460 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 9; Pages: 1460 interannual variations albedo shortwave radiation top of the atmosphere 4-year oscillation lagged correlation Text 2020 ftmdpi https://doi.org/10.3390/rs12091460 2023-07-31T23:27:35Z Recent changes in Earth’s climate system have significantly affected the radiation budget and its year-to-year variations at top of the atmosphere (TOA). Observing high-latitude TOA fluxes is still challenging from space, because spatial inhomogeneity of surface/atmospheric radiative processes and spectral variability can reflect sunlight very differently. In this study we analyze the 20-year TOA flux and albedo data from CERES and MISR over the Arctic, the Antarctic, and Tibetan Plateau (TP), and found overall great consistency in the TOA albedo trend and interannual variations. The observations reveal a lagged correlation between the Arctic and subarctic albedo fluctuations. The observed year-to-year variations are further used to evaluate the reanalysis data, which exhibit substantial shortcomings in representing the polar TOA flux variability. The observed Arctic flux variations are highly correlated with cloud fraction (CF), except in the regions where CF > 90% or where the surface is covered by ice. An empirical orthogonal function (EOF) analysis shows that the first five EOFs can account for ~50% of the Arctic TOA variance, whereas the correlation with climate indices suggests that Sea Ice Extent (SIE), North Atlantic Oscillation (NAO) and 55°N–65°N cloudiness are the most influential processes in driving the TOA flux variabilities. Text albedo Antarc* Antarctic Arctic North Atlantic North Atlantic oscillation Sea ice Subarctic MDPI Open Access Publishing Arctic Antarctic The Antarctic Remote Sensing 12 9 1460 |
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Open Polar |
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MDPI Open Access Publishing |
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ftmdpi |
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English |
topic |
interannual variations albedo shortwave radiation top of the atmosphere 4-year oscillation lagged correlation |
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interannual variations albedo shortwave radiation top of the atmosphere 4-year oscillation lagged correlation Dong L. Wu Jae Nyung Lee Kyu-Myong Kim Young-Kwon Lim Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019 |
topic_facet |
interannual variations albedo shortwave radiation top of the atmosphere 4-year oscillation lagged correlation |
description |
Recent changes in Earth’s climate system have significantly affected the radiation budget and its year-to-year variations at top of the atmosphere (TOA). Observing high-latitude TOA fluxes is still challenging from space, because spatial inhomogeneity of surface/atmospheric radiative processes and spectral variability can reflect sunlight very differently. In this study we analyze the 20-year TOA flux and albedo data from CERES and MISR over the Arctic, the Antarctic, and Tibetan Plateau (TP), and found overall great consistency in the TOA albedo trend and interannual variations. The observations reveal a lagged correlation between the Arctic and subarctic albedo fluctuations. The observed year-to-year variations are further used to evaluate the reanalysis data, which exhibit substantial shortcomings in representing the polar TOA flux variability. The observed Arctic flux variations are highly correlated with cloud fraction (CF), except in the regions where CF > 90% or where the surface is covered by ice. An empirical orthogonal function (EOF) analysis shows that the first five EOFs can account for ~50% of the Arctic TOA variance, whereas the correlation with climate indices suggests that Sea Ice Extent (SIE), North Atlantic Oscillation (NAO) and 55°N–65°N cloudiness are the most influential processes in driving the TOA flux variabilities. |
format |
Text |
author |
Dong L. Wu Jae Nyung Lee Kyu-Myong Kim Young-Kwon Lim |
author_facet |
Dong L. Wu Jae Nyung Lee Kyu-Myong Kim Young-Kwon Lim |
author_sort |
Dong L. Wu |
title |
Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019 |
title_short |
Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019 |
title_full |
Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019 |
title_fullStr |
Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019 |
title_full_unstemmed |
Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019 |
title_sort |
interannual variations of toa albedo over the arctic, antarctic and tibetan plateau in 2000–2019 |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12091460 |
op_coverage |
agris |
geographic |
Arctic Antarctic The Antarctic |
geographic_facet |
Arctic Antarctic The Antarctic |
genre |
albedo Antarc* Antarctic Arctic North Atlantic North Atlantic oscillation Sea ice Subarctic |
genre_facet |
albedo Antarc* Antarctic Arctic North Atlantic North Atlantic oscillation Sea ice Subarctic |
op_source |
Remote Sensing; Volume 12; Issue 9; Pages: 1460 |
op_relation |
Environmental Remote Sensing https://dx.doi.org/10.3390/rs12091460 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs12091460 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
9 |
container_start_page |
1460 |
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1774724822129967104 |