Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean

Cloud phase is an important factor affecting cloud contributions to the polar energy budget. Brightness temperature differences (BTDs) between two mid-infrared (mid-IR) spectral channels are commonly used in satellite remote sensing to determine the cloud phase, but the mid-IR has limitations for cl...

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Main Authors: Peterson, Colten A., Huang, Xianglei, Chen, Xiuhong, Yang, Ping
Format: Article in Journal/Newspaper
Language:unknown
Published: Copernicus ClimateChange Service (C3S) Climate Data Store (CDS) 2022
Subjects:
Atmospheric and Oceanic Sciences
Science
Arctic
Online Access:https://hdl.handle.net/2027.42/172281
https://doi.org/10.1029/2021JD035733
id ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/172281
record_format openpolar
institution Open Polar
collection University of Michigan: Deep Blue
op_collection_id ftumdeepblue
language unknown
topic Atmospheric and Oceanic Sciences
Science
spellingShingle Atmospheric and Oceanic Sciences
Science
Peterson, Colten A.
Huang, Xianglei
Chen, Xiuhong
Yang, Ping
Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean
topic_facet Atmospheric and Oceanic Sciences
Science
description Cloud phase is an important factor affecting cloud contributions to the polar energy budget. Brightness temperature differences (BTDs) between two mid-infrared (mid-IR) spectral channels are commonly used in satellite remote sensing to determine the cloud phase, but the mid-IR has limitations for cloud phase determination in polar regions. This study explores the synergy between the far- and mid-IR for ice cloud phase determinations over polar oceans. A far-IR BTD test (BTD449-521) is developed based on the spectral variations of both ice cloud scattering and absorption properties in the far-IR “dirty window” region (400–600 cm−1 or 16.7–25 μm). Synthetic IR radiances at 1 cm−1 spectral resolution are generated using ERA5 reanalysis data for both polar regions. A subset of these spectra is used to compare the ice phase determination skill of the far-IR test with an “AIRS-Like” mid-IR BTD test (BTD1231-960) for combinations of effective ice particle diameter (Deff_ice), cloud optical depth (COD), and cloud top pressure (CTP). The far-IR test is performing better for ice clouds with the smallest Deff_ice that we have studied (20 μm) due to the sensitivity of far-IR scattering to ice particle size. The mid-IR test was either comparable to or more successful than the far-IR test for ice clouds with large particle sizes. For all Deff_ice, increasing COD leads to enhanced far-IR BTD signals due to stronger multiple scattering in the far-IR than in the mid-IR. Overall, the variations in far-IR and mid-IR BTD test performance are strongly sensitive to Deff_ice, followed by COD and CTP.Key PointsFar-infrared (IR) scattering and absorption can be used together for ice cloud detection in passive remote sensing of polar regionsThe far-IR ice phase test is most useful for ice particle effective diameters less than 40 µmBoth the far-IR and mid-IR ice phase tests are more sensitive to ice particle size than to cloud top pressure and optical depth Peer Reviewed ...
format Article in Journal/Newspaper
author Peterson, Colten A.
Huang, Xianglei
Chen, Xiuhong
Yang, Ping
author_facet Peterson, Colten A.
Huang, Xianglei
Chen, Xiuhong
Yang, Ping
author_sort Peterson, Colten A.
title Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean
title_short Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean
title_full Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean
title_fullStr Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean
title_full_unstemmed Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean
title_sort synergistic use of far- and mid-infrared spectral radiances for satellite-based detection of polar ice clouds over ocean
publisher Copernicus ClimateChange Service (C3S) Climate Data Store (CDS)
publishDate 2022
url https://hdl.handle.net/2027.42/172281
https://doi.org/10.1029/2021JD035733
genre Arctic
genre_facet Arctic
op_relation Peterson, Colten A.; Huang, Xianglei; Chen, Xiuhong; Yang, Ping (2022). "Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean." Journal of Geophysical Research: Atmospheres 127(9): n/a-n/a.
2169-897X
2169-8996
https://hdl.handle.net/2027.42/172281
doi:10.1029/2021JD035733
Journal of Geophysical Research: Atmospheres
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Peterson, C. A., Huang, X., Chen, X., & Yang, P. ( 2022 ). Synergistic use of far- and mid-infrared spectral radiances for polar ice cloud detection from space. Zenodo. https://doi.org/10.5281/zenodo.5874365
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Strabala, K. I., Ackerman, S. A., & Menzel, W. P. ( 1994 ). Cloud properties inferred from 8–12-µm data. Journal of Applied Meteorology and Climatology, 33 ( 2 ), 212 – 229. https://doi.org/10.1175/1520-0450(1994)033<0212:CPIFD>2.0.CO;2
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Vergara-Temprado, J., Miltenberger, A. K., Furtado, K., Grosvenor, D. P., Shipway, B. J., Hill, A. A., et al. ( 2018 ). Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles. Proceedings of the National Academy of Sciences of the United States of America, 115 ( 11 ), 2687 – 2692. https://doi.org/10.1073/pnas.1721627115
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Yang, P., Bi, L., Baum, B. A., Liou, K., Kattawar, G. W., Mishchenko, M. I., & Cole, B. ( 2013b ). Spectrally consistent scattering, absorption, and polarization properties of atmospheric ice crystals at wavelengths from 0.2 to 100 μm (Version 1) [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.6468778
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spelling ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/172281 2023-08-20T04:03:10+02:00 Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean Peterson, Colten A. Huang, Xianglei Chen, Xiuhong Yang, Ping 2022-05-16 application/pdf https://hdl.handle.net/2027.42/172281 https://doi.org/10.1029/2021JD035733 unknown Copernicus ClimateChange Service (C3S) Climate Data Store (CDS) Wiley Periodicals, Inc. Peterson, Colten A.; Huang, Xianglei; Chen, Xiuhong; Yang, Ping (2022). "Synergistic Use of Far- and Mid-Infrared Spectral Radiances for Satellite-Based Detection of Polar Ice Clouds Over Ocean." Journal of Geophysical Research: Atmospheres 127(9): n/a-n/a. 2169-897X 2169-8996 https://hdl.handle.net/2027.42/172281 doi:10.1029/2021JD035733 Journal of Geophysical Research: Atmospheres Rowe, P. M., Cox, C. J., Neshyba, S., & Walden, V. P. ( 2019 ). Toward autonomous surface-based infrared remote sensing of polar clouds: Retrievals of cloud optical and microphysical properties. Atmospheric Measurement Techniques, 12 ( 9 ), 5071 – 5086. https://doi.org/10.5194/amt-12-5071-2019 Palchetti, L., Brindley, H., Bantges, R., Buehler, S. A., Camy-Peyret, C., Carli, B., et al. ( 2020 ). FORUM: Unique far-infrared satellite observations to better understand how Earth radiates energy to space. Bulletin of the American Meteorological Society, 101 ( 12 ), E2030 – E2046. https://doi.org/10.1175/BAMS-D-19-0322.1 Peterson, C. A., Huang, X., Chen, X., & Yang, P. ( 2022 ). Synergistic use of far- and mid-infrared spectral radiances for polar ice cloud detection from space. Zenodo. https://doi.org/10.5281/zenodo.5874365 Peterson, C. A., Yue, Q., Kahn, B. H., Fetzer, E., & Huang, X. ( 2020 ). Evaluation of AIRS cloud phase classification over the Arctic Ocean against combined CloudSat–CALIPSO observations. Journal of Applied Meteorology and Climatology, 59 ( 8 ), 1277 – 1294. https://doi.org/10.1175/JAMC-D-20-0016.1 Rathke, C., Fischer, J., Neshyba, S., & Shupe, M. ( 2002 ). Improving IR cloud phase determination with 20 microns spectral observations. Geophysical Research Letters, 29 ( 8 ), 50-1 – 50-4. https://doi.org/10.1029/2001GL014594 Ridolfi, M., Del Bianco, S., Di Roma, A., Castelli, E., Belotti, C., Dandini, P., et al. ( 2020 ). FORUM earth explorer 9: Characteristics of level 2 products and synergies with IASI-NG. Remote Sensing, 12 ( 9 ), 1496. https://doi.org/10.3390/rs12091496 Rossow, W. B., & Schiffer, R. A. ( 1999 ). Advances in understanding clouds from ISCCP. Bulletin of the American Meteorological Society, 80 ( 11 ), 2261 – 2287. https://doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2 Rowe, P. M., Cox, C. J., & Walden, V. P. ( 2016 ). Toward autonomous surface-based infrared remote sensing of polar clouds: Cloud-height retrievals. Atmospheric Measurement Techniques, 9, 3641 – 3659. https://doi.org/10.5194/amt-9-3641-2016 Saito, M., Yang, P., Huang, X., Brindley, H. E., Mlynczak, M. G., & Kahn, B. H. ( 2020 ). Spaceborne middle- and far-infrared observations improving nighttime ice cloud property retrievals. Geophysical Research Letters, 47 ( 18 ), e2020GL087491. https://doi.org/10.1029/2020GL087491 Scott, R. C., Lubin, D., Vogelmann, A. M., & Kato, S. ( 2017 ). West Antarctic ice sheet cloud cover and surface radiation budget from NASA A-Train satellites. Journal of Climate, 30 ( 16 ), 6151 – 6170. https://doi.org/10.1175/JCLI-D-16-0644.1 Sgheri, L., Belotti, C., Ben-Yami, M., Bianchini, G., Carnicero Dominguez, B., Cortesi, U., et al. ( 2021 ). The FORUM end-to-end simulator project: Architecture and results. Atmospheric Measurement Techniques Discussion. https://doi.org/10.5194/amt-2021-196 Shupe, M. D. ( 2011 ). Clouds at Arctic atmospheric observatories. Part ii: Thermodynamic phase characteristics. Journal of Applied Meteorology and Climatology, 50 ( 3 ), 645 – 661. https://doi.org/10.1175/2010jamc2468.1 Shupe, M. D., & Intrieri, J. M. ( 2004 ). Cloud radiative forcing of the Arctic surface: The influence of cloud properties, surface albedo, and solar zenith angle. Journal of Climate, 17 ( 3 ), 616 – 628. https://doi.org/10.1175/1520-0442(2004)017<0616:crfota>2.0.co.2 Stamnes, K., Tsay, S. C., Wiscombe, W., & Jayaweera, K. ( 1988 ). Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. Applied Optics, 27 ( 12 ), 2502 – 2509. https://doi.org/10.1364/AO.27.002502 Strabala, K. I., Ackerman, S. A., & Menzel, W. P. ( 1994 ). Cloud properties inferred from 8–12-µm data. Journal of Applied Meteorology and Climatology, 33 ( 2 ), 212 – 229. https://doi.org/10.1175/1520-0450(1994)033<0212:CPIFD>2.0.CO;2 Turner, D. D. ( 2005 ). Arctic mixed-phase cloud properties from AERI lidar observations: Algorithm and results from SHEBA. Journal of Applied Meteorology, 44 ( 4 ), 427 – 444. https://doi.org/10.1175/JAM2208.1 Vergara-Temprado, J., Miltenberger, A. K., Furtado, K., Grosvenor, D. P., Shipway, B. J., Hill, A. A., et al. ( 2018 ). Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles. Proceedings of the National Academy of Sciences of the United States of America, 115 ( 11 ), 2687 – 2692. https://doi.org/10.1073/pnas.1721627115 Yang, P., Bi, L., Baum, B. A., Liou, K., Kattawar, G. W., Mishchenko, M. I., & Cole, B. ( 2013a ). Spectrally consistent scattering, absorption, and polarization properties of atmospheric ice crystals at wavelengths from 0.2 to 100 μm. Journal of the Atmospheric Sciences, 70 ( 1 ), 330 – 347. https://doi.org/10.1175/JAS-D-12-039.1 Yang, P., Bi, L., Baum, B. A., Liou, K., Kattawar, G. W., Mishchenko, M. I., & Cole, B. ( 2013b ). 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Brightness temperature differences (BTDs) between two mid-infrared (mid-IR) spectral channels are commonly used in satellite remote sensing to determine the cloud phase, but the mid-IR has limitations for cloud phase determination in polar regions. This study explores the synergy between the far- and mid-IR for ice cloud phase determinations over polar oceans. A far-IR BTD test (BTD449-521) is developed based on the spectral variations of both ice cloud scattering and absorption properties in the far-IR “dirty window” region (400–600 cm−1 or 16.7–25 μm). Synthetic IR radiances at 1 cm−1 spectral resolution are generated using ERA5 reanalysis data for both polar regions. A subset of these spectra is used to compare the ice phase determination skill of the far-IR test with an “AIRS-Like” mid-IR BTD test (BTD1231-960) for combinations of effective ice particle diameter (Deff_ice), cloud optical depth (COD), and cloud top pressure (CTP). The far-IR test is performing better for ice clouds with the smallest Deff_ice that we have studied (20 μm) due to the sensitivity of far-IR scattering to ice particle size. The mid-IR test was either comparable to or more successful than the far-IR test for ice clouds with large particle sizes. For all Deff_ice, increasing COD leads to enhanced far-IR BTD signals due to stronger multiple scattering in the far-IR than in the mid-IR. Overall, the variations in far-IR and mid-IR BTD test performance are strongly sensitive to Deff_ice, followed by COD and CTP.Key PointsFar-infrared (IR) scattering and absorption can be used together for ice cloud detection in passive remote sensing of polar regionsThe far-IR ice phase test is most useful for ice particle effective diameters less than 40 µmBoth the far-IR and mid-IR ice phase tests are more sensitive to ice particle size than to cloud top pressure and optical depth Peer Reviewed ... Article in Journal/Newspaper Arctic University of Michigan: Deep Blue

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