Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations
Reanalyses have proven to be convenient tools for studying the Arctic climate system, but their uncertainties should first be identified. In this study, five reanalyses (JRA-55, 20CRv2c, CFSR, ERA-Interim, and MERRA-2) are compared with NASA CERES-MODIS (CM)-derived cloud fractions (CFs), cloud wate...
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AMER METEOROLOGICAL SOC
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Online Access: | http://hdl.handle.net/10150/625985 https://doi.org/10.1175/JCLI-D-16-0722.1 |
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ftunivarizona:oai:repository.arizona.edu:10150/625985 2023-05-15T14:25:19+02:00 Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations Huang, Yiyi Dong, Xiquan Xi, Baike Dolinar, Erica K. Stanfield, Ryan E. Qiu, Shaoyue Univ Arizona, Dept Hydrol & Atmospher Sci Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Arizona Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota 2017-10 http://hdl.handle.net/10150/625985 https://doi.org/10.1175/JCLI-D-16-0722.1 en eng AMER METEOROLOGICAL SOC http://journals.ametsoc.org/doi/10.1175/JCLI-D-16-0722.1 Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations 2017, 30 (19):8007 Journal of Climate 0894-8755 1520-0442 doi:10.1175/JCLI-D-16-0722.1 http://hdl.handle.net/10150/625985 Journal of Climate © 2017 American Meteorological Society. Article 2017 ftunivarizona https://doi.org/10.1175/JCLI-D-16-0722.1 2020-06-14T08:15:57Z Reanalyses have proven to be convenient tools for studying the Arctic climate system, but their uncertainties should first be identified. In this study, five reanalyses (JRA-55, 20CRv2c, CFSR, ERA-Interim, and MERRA-2) are compared with NASA CERES-MODIS (CM)-derived cloud fractions (CFs), cloud water paths (CWPs), top-of-atmosphere (TOA) and surface longwave (LW) and shortwave (SW) radiative fluxes over the Arctic (70 degrees-90 degrees N) over the period of 2000-12, and CloudSat-CALIPSO (CC)-derived CFs from 2006 to 2010. The monthly mean CFs in all reanalyses except JRA-55 are close to or slightly higher than the CC-derived CFs from May to September. However, wintertime CF cannot be confidently evaluated until instrument simulators are implemented in reanalysis products. The comparison between CM and CCCFs indicates that CM-derived CFs are reliable in summer but not in winter. Although the reanalysis CWPs follow the general seasonal variations of CM CWPs, their annual means are only half or even less than the CM-retrieved CWPs (126 g m(-2)). The annual mean differences in TOA and surface SW and LW fluxes between CERES EBAF and reanalyses are less than 6 W m(-2) for TOA radiative fluxes and 16 W m(-2) for surface radiative fluxes. All reanalyses show positive biases along the northern and eastern coasts of Greenland as a result of model elevation biases or possible CM clear-sky retrieval issues. The correlations between the reanalyses and CERES satellite retrievals indicate that all five reanalyses estimate radiative fluxes better than cloud properties, and MERRA-2 and JRA-55 exhibit comparatively higher correlations for Arctic cloud and radiation properties. NOAA MAPP Grant at the University of North Dakota [NA13OAR4310105]; NASA CERES project at The University of Arizona [NNX17AC52G] 6 month embargo; Published online: 6 Sept 2017. This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu. Article in Journal/Newspaper Arctic Arctic Greenland The University of Arizona: UA Campus Repository Arctic Greenland Merra ENVELOPE(12.615,12.615,65.816,65.816) Journal of Climate 30 19 8007 8029 |
institution |
Open Polar |
collection |
The University of Arizona: UA Campus Repository |
op_collection_id |
ftunivarizona |
language |
English |
description |
Reanalyses have proven to be convenient tools for studying the Arctic climate system, but their uncertainties should first be identified. In this study, five reanalyses (JRA-55, 20CRv2c, CFSR, ERA-Interim, and MERRA-2) are compared with NASA CERES-MODIS (CM)-derived cloud fractions (CFs), cloud water paths (CWPs), top-of-atmosphere (TOA) and surface longwave (LW) and shortwave (SW) radiative fluxes over the Arctic (70 degrees-90 degrees N) over the period of 2000-12, and CloudSat-CALIPSO (CC)-derived CFs from 2006 to 2010. The monthly mean CFs in all reanalyses except JRA-55 are close to or slightly higher than the CC-derived CFs from May to September. However, wintertime CF cannot be confidently evaluated until instrument simulators are implemented in reanalysis products. The comparison between CM and CCCFs indicates that CM-derived CFs are reliable in summer but not in winter. Although the reanalysis CWPs follow the general seasonal variations of CM CWPs, their annual means are only half or even less than the CM-retrieved CWPs (126 g m(-2)). The annual mean differences in TOA and surface SW and LW fluxes between CERES EBAF and reanalyses are less than 6 W m(-2) for TOA radiative fluxes and 16 W m(-2) for surface radiative fluxes. All reanalyses show positive biases along the northern and eastern coasts of Greenland as a result of model elevation biases or possible CM clear-sky retrieval issues. The correlations between the reanalyses and CERES satellite retrievals indicate that all five reanalyses estimate radiative fluxes better than cloud properties, and MERRA-2 and JRA-55 exhibit comparatively higher correlations for Arctic cloud and radiation properties. NOAA MAPP Grant at the University of North Dakota [NA13OAR4310105]; NASA CERES project at The University of Arizona [NNX17AC52G] 6 month embargo; Published online: 6 Sept 2017. This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu. |
author2 |
Univ Arizona, Dept Hydrol & Atmospher Sci Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Arizona Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota |
format |
Article in Journal/Newspaper |
author |
Huang, Yiyi Dong, Xiquan Xi, Baike Dolinar, Erica K. Stanfield, Ryan E. Qiu, Shaoyue |
spellingShingle |
Huang, Yiyi Dong, Xiquan Xi, Baike Dolinar, Erica K. Stanfield, Ryan E. Qiu, Shaoyue Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations |
author_facet |
Huang, Yiyi Dong, Xiquan Xi, Baike Dolinar, Erica K. Stanfield, Ryan E. Qiu, Shaoyue |
author_sort |
Huang, Yiyi |
title |
Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations |
title_short |
Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations |
title_full |
Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations |
title_fullStr |
Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations |
title_full_unstemmed |
Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations |
title_sort |
quantifying the uncertainties of reanalyzed arctic cloud and radiation properties using satellite surface observations |
publisher |
AMER METEOROLOGICAL SOC |
publishDate |
2017 |
url |
http://hdl.handle.net/10150/625985 https://doi.org/10.1175/JCLI-D-16-0722.1 |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Arctic Greenland Merra |
geographic_facet |
Arctic Greenland Merra |
genre |
Arctic Arctic Greenland |
genre_facet |
Arctic Arctic Greenland |
op_relation |
http://journals.ametsoc.org/doi/10.1175/JCLI-D-16-0722.1 Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations 2017, 30 (19):8007 Journal of Climate 0894-8755 1520-0442 doi:10.1175/JCLI-D-16-0722.1 http://hdl.handle.net/10150/625985 Journal of Climate |
op_rights |
© 2017 American Meteorological Society. |
op_doi |
https://doi.org/10.1175/JCLI-D-16-0722.1 |
container_title |
Journal of Climate |
container_volume |
30 |
container_issue |
19 |
container_start_page |
8007 |
op_container_end_page |
8029 |
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1766297740889817088 |