Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions
Atmosphere and surface properties are routinely retrieved from satellite measurements and extensively used in weather forecast and climate analysis. Satellite missions dedicated to fill the gap of far-infrared (far-IR) observations are scheduled to be launched this decade. To explore mid-infrared (m...
| Main Authors: | , , , , |
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| Format: | Article in Journal/Newspaper |
| Language: | unknown |
| Published: |
WORLD SCIENTIFIC
2023
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| Online Access: | https://hdl.handle.net/2027.42/176101 https://doi.org/10.1029/2022EA002684 |
| _version_ | 1835010286628634624 |
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| author | Xie, Yan Huang, Xianglei Chen, Xiuhong L’Ecuyer, Tristan S. Drouin, Brian J. |
| author_facet | Xie, Yan Huang, Xianglei Chen, Xiuhong L’Ecuyer, Tristan S. Drouin, Brian J. |
| author_sort | Xie, Yan |
| collection | Unknown |
| description | Atmosphere and surface properties are routinely retrieved from satellite measurements and extensively used in weather forecast and climate analysis. Satellite missions dedicated to fill the gap of far-infrared (far-IR) observations are scheduled to be launched this decade. To explore mid-infrared (mid-IR) and far-IR joint retrievals for the future far-IR satellite missions, this study uses an optimal-estimation-based method to retrieve atmospheric specific humidity and temperature profiles, surface skin temperature, and surface spectral emissivity from the Infrared Interferometer Sounder-D (IRIS-D) measurements in 1970, the only existing spaceborne far-IR spectral observations with global coverage. Based on a set of criteria, two cases in the Arctic, which are most likely under clear-sky conditions, are chosen for the retrieval experiments. Information content analysis suggests that the retrieved surface skin temperature and the mid-IR surface spectral emissivity are highly sensitive to the true values while the retrieval estimates of far-IR surface emissivity are subject to the variation of water vapor abundance. Results show that radiances based on the retrieved state variables are more consistent with the IRIS-D observations compared to those based on the reanalysis data. Retrieval estimates of the state variables along with retrieval uncertainties generally fall within reasonable ranges. The relative uncertainties of retrieved state variables decrease compared to the a priori relative uncertainties. In addition, the necessity to retrieve surface emissivity is corroborated by a parallel retrieval experiment assuming a blackbody surface emissivity that has revealed significant distortions of retrieved specific humidity and temperature profiles in the Arctic lower troposphere.Key PointsAtmospheric profiles and surface properties are simultaneously retrieved from satellite observations made 50 years agoCompared to reanalysis data, the retrieval estimates produce radiances which are more consistent with the ... |
| format | Article in Journal/Newspaper |
| genre | Arctic Arctic |
| genre_facet | Arctic Arctic |
| geographic | Arctic |
| geographic_facet | Arctic |
| id | ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/176101 |
| institution | Open Polar |
| language | unknown |
| op_collection_id | ftumdeepblue |
| op_relation | https://hdl.handle.net/2027.42/176101 doi:10.1029/2022EA002684 Earth and Space Science Li, J., Li, J., Weisz, E., & Zhou, D. K. ( 2007 ). Physical retrieval of surface emissivity spectrum from hyperspectral infrared radiances. Geophysical Research Letters, 34 ( 16 ), L16812. https://doi.org/10.1029/2007GL030543 Rodgers, C. D. ( 2000 ). Inverse methods for atmospheric sounding: Theory and practice (Vol. 2, p. 256 ). WORLD SCIENTIFIC. Scarlat, R. C., Heygster, G., & Pedersen, L. T. ( 2017 ). Experiences with an optimal estimation algorithm for surface and atmospheric parameter retrieval from passive microwave data in the Arctic. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 ( 9 ), 3934 – 3947. https://doi.org/10.1109/JSTARS.2017.2739858 Susskind, J., Barnet, C. D., & Blaisdell, J. M. ( 2003 ). Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE Transactions on Geoscience and Remote Sensing, 41 ( 2 ), 390 – 409. https://doi.org/10.1109/TGRS.2002.808236 Xie, Y., Huang, X., Chen, X., L’Ecuyer, T. S., Drouin, B. J., & Wang, J. ( 2022 ). Retrieval of surface spectral emissivity in polar regions based on the optimal estimation method. Journal of Geophysical Research: Atmospheres, 127 ( 5 ), e2021JD035677. https://doi.org/10.1029/2021JD035677 Zhou, D. K., Larar, A. M., Liu, X., Smith, W. L., Strow, L. L., Yang, P., et al. ( 2011 ). Global land surface emissivity retrieved from satellite ultraspectral IR measurements. IEEE Transactions on Geoscience and Remote Sensing, 49 ( 4 ), 1277 – 1290. https://doi.org/10.1109/TGRS.2010.2051036 Backus, G., Gilbert, F., & Bullard, E. C. ( 1970 ). Uniqueness in the inversion of inaccurate gross Earth data. Philosophical Transactions of the Royal Society of London Series A: Mathematical and Physical Sciences, 266 ( 1173 ), 123 – 192. https://doi.org/10.1098/rsta.1970.0005 Bell, B., Hersbach, H., Simmons, A., Berrisford, P., Dahlgren, P., Horányi, A., et al. ( 2021 ). The ERA5 global reanalysis: Preliminary extension to 1950. Quarterly Journal of the Royal Meteorological Society, 147 ( 741 ), 4186 – 4227. https://doi.org/10.1002/qj.4174 Bellisario, C., Brindley, H. E., Murray, J. E., Last, A., Pickering, J., Harlow, R. C., et al. ( 2017 ). Retrievals of the far infrared surface emissivity over the Greenland plateau using the tropospheric Airborne Fourier transform spectrometer (TAFTS). Journal of Geophysical Research: Atmospheres, 122 ( 22 ), 12152 – 112166. https://doi.org/10.1002/2017JD027328 Borel, C. C. ( 1998 ). Surface emissivity and temperature retrieval for a hyperspectral sensor. IEEE International Geoscience and Remote Sensing. Symposium Proceedings, 1, 546 – 549. https://doi.org/10.1109/IGARSS.1998.702966 Gillespie, A., Rokugawa, S., Matsunaga, T., Cothern, J. S., Hook, S., & Kahle, A. B. ( 1998 ). A temperature and emissivity separation algorithm for advanced spaceborne thermal emission and reflection radiometer (ASTER) images. IEEE Transactions on Geoscience and Remote Sensing, 36 ( 4 ), 1113 – 1126. https://doi.org/10.1109/36.700995 Hanel, R. A., Conrath, B. J., Kunde, V. G., Prabhakara, C., Revah, I., Salomonson, V. V., & Wolford, G. ( 1972 ). The Nimbus 4 infrared spectroscopy experiment: 1. Calibrated thermal emission spectra. Journal of Geophysical Research, 77 ( 15 ), 2629 – 2641. https://doi.org/10.1029/JC077i015p02629 Hanel, R. A., Schlachman, B., Rogers, D., & Vanous, D. ( 1971 ). Nimbus 4 michelson interferometer. Applied Optics, 10 ( 6 ), 1376 – 1382. https://doi.org/10.1364/AO.10.001376 Harries, J., Brindley, H., Sagoo, P., & Bantges, R. ( 2001 ). Increases in greenhouse forcing inferred from the outgoing longwave radiation spectra of the Earth in 1970 and 1997. Nature, 410 ( 6826 ), 355 – 357. https://doi.org/10.1038/35066553 Haskins, R. D., Goody, R. M., & Chen, L. ( 1997 ). A statistical method for testing a general circulation model with spectrally resolved satellite data. Journal of Geophysical Research, 102 ( D14 ), 16563 – 16581. https://doi.org/10.1029/97JD00897 Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., et al. ( 2018a ). ERA5 hourly data on pressure levels from 1959 to present [Dataset]. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.bd0915c6 Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., et al. ( 2018b ). ERA5 hourly data on single levels from 1959 to present [Dataset]. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.adbb2d47 Huang, X., Chen, X., Soden, B. J., & Liu, X. ( 2014 ). The spectral dimension of longwave feedback in the CMIP3 and CMIP5 experiments. Geophysical Research Letters, 41 ( 22 ), 7830 – 7837. https://doi.org/10.1002/2014GL061938 |
| op_rights | IndexNoFollow |
| publishDate | 2023 |
| publisher | WORLD SCIENTIFIC |
| record_format | openpolar |
| spelling | ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/176101 2025-06-15T14:17:46+00:00 Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions Xie, Yan Huang, Xianglei Chen, Xiuhong L’Ecuyer, Tristan S. Drouin, Brian J. 2023-03 application/pdf https://hdl.handle.net/2027.42/176101 https://doi.org/10.1029/2022EA002684 unknown WORLD SCIENTIFIC Wiley Periodicals, Inc. https://hdl.handle.net/2027.42/176101 doi:10.1029/2022EA002684 Earth and Space Science Li, J., Li, J., Weisz, E., & Zhou, D. K. ( 2007 ). Physical retrieval of surface emissivity spectrum from hyperspectral infrared radiances. Geophysical Research Letters, 34 ( 16 ), L16812. https://doi.org/10.1029/2007GL030543 Rodgers, C. D. ( 2000 ). Inverse methods for atmospheric sounding: Theory and practice (Vol. 2, p. 256 ). WORLD SCIENTIFIC. Scarlat, R. C., Heygster, G., & Pedersen, L. T. ( 2017 ). Experiences with an optimal estimation algorithm for surface and atmospheric parameter retrieval from passive microwave data in the Arctic. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 ( 9 ), 3934 – 3947. https://doi.org/10.1109/JSTARS.2017.2739858 Susskind, J., Barnet, C. D., & Blaisdell, J. M. ( 2003 ). Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE Transactions on Geoscience and Remote Sensing, 41 ( 2 ), 390 – 409. https://doi.org/10.1109/TGRS.2002.808236 Xie, Y., Huang, X., Chen, X., L’Ecuyer, T. S., Drouin, B. J., & Wang, J. ( 2022 ). Retrieval of surface spectral emissivity in polar regions based on the optimal estimation method. Journal of Geophysical Research: Atmospheres, 127 ( 5 ), e2021JD035677. https://doi.org/10.1029/2021JD035677 Zhou, D. K., Larar, A. M., Liu, X., Smith, W. L., Strow, L. L., Yang, P., et al. ( 2011 ). Global land surface emissivity retrieved from satellite ultraspectral IR measurements. IEEE Transactions on Geoscience and Remote Sensing, 49 ( 4 ), 1277 – 1290. https://doi.org/10.1109/TGRS.2010.2051036 Backus, G., Gilbert, F., & Bullard, E. C. ( 1970 ). Uniqueness in the inversion of inaccurate gross Earth data. Philosophical Transactions of the Royal Society of London Series A: Mathematical and Physical Sciences, 266 ( 1173 ), 123 – 192. https://doi.org/10.1098/rsta.1970.0005 Bell, B., Hersbach, H., Simmons, A., Berrisford, P., Dahlgren, P., Horányi, A., et al. ( 2021 ). The ERA5 global reanalysis: Preliminary extension to 1950. Quarterly Journal of the Royal Meteorological Society, 147 ( 741 ), 4186 – 4227. https://doi.org/10.1002/qj.4174 Bellisario, C., Brindley, H. E., Murray, J. E., Last, A., Pickering, J., Harlow, R. C., et al. ( 2017 ). Retrievals of the far infrared surface emissivity over the Greenland plateau using the tropospheric Airborne Fourier transform spectrometer (TAFTS). Journal of Geophysical Research: Atmospheres, 122 ( 22 ), 12152 – 112166. https://doi.org/10.1002/2017JD027328 Borel, C. C. ( 1998 ). Surface emissivity and temperature retrieval for a hyperspectral sensor. IEEE International Geoscience and Remote Sensing. Symposium Proceedings, 1, 546 – 549. https://doi.org/10.1109/IGARSS.1998.702966 Gillespie, A., Rokugawa, S., Matsunaga, T., Cothern, J. S., Hook, S., & Kahle, A. B. ( 1998 ). A temperature and emissivity separation algorithm for advanced spaceborne thermal emission and reflection radiometer (ASTER) images. IEEE Transactions on Geoscience and Remote Sensing, 36 ( 4 ), 1113 – 1126. https://doi.org/10.1109/36.700995 Hanel, R. A., Conrath, B. J., Kunde, V. G., Prabhakara, C., Revah, I., Salomonson, V. V., & Wolford, G. ( 1972 ). The Nimbus 4 infrared spectroscopy experiment: 1. Calibrated thermal emission spectra. Journal of Geophysical Research, 77 ( 15 ), 2629 – 2641. https://doi.org/10.1029/JC077i015p02629 Hanel, R. A., Schlachman, B., Rogers, D., & Vanous, D. ( 1971 ). Nimbus 4 michelson interferometer. Applied Optics, 10 ( 6 ), 1376 – 1382. https://doi.org/10.1364/AO.10.001376 Harries, J., Brindley, H., Sagoo, P., & Bantges, R. ( 2001 ). Increases in greenhouse forcing inferred from the outgoing longwave radiation spectra of the Earth in 1970 and 1997. Nature, 410 ( 6826 ), 355 – 357. https://doi.org/10.1038/35066553 Haskins, R. D., Goody, R. M., & Chen, L. ( 1997 ). A statistical method for testing a general circulation model with spectrally resolved satellite data. Journal of Geophysical Research, 102 ( D14 ), 16563 – 16581. https://doi.org/10.1029/97JD00897 Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., et al. ( 2018a ). ERA5 hourly data on pressure levels from 1959 to present [Dataset]. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.bd0915c6 Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., et al. ( 2018b ). ERA5 hourly data on single levels from 1959 to present [Dataset]. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.adbb2d47 Huang, X., Chen, X., Soden, B. J., & Liu, X. ( 2014 ). The spectral dimension of longwave feedback in the CMIP3 and CMIP5 experiments. Geophysical Research Letters, 41 ( 22 ), 7830 – 7837. https://doi.org/10.1002/2014GL061938 IndexNoFollow atmospheric retrieval satellite observation far-infrared Atmospheric and Oceanic Sciences Geological Sciences Space Sciences Science Article 2023 ftumdeepblue 2025-06-04T05:59:21Z Atmosphere and surface properties are routinely retrieved from satellite measurements and extensively used in weather forecast and climate analysis. Satellite missions dedicated to fill the gap of far-infrared (far-IR) observations are scheduled to be launched this decade. To explore mid-infrared (mid-IR) and far-IR joint retrievals for the future far-IR satellite missions, this study uses an optimal-estimation-based method to retrieve atmospheric specific humidity and temperature profiles, surface skin temperature, and surface spectral emissivity from the Infrared Interferometer Sounder-D (IRIS-D) measurements in 1970, the only existing spaceborne far-IR spectral observations with global coverage. Based on a set of criteria, two cases in the Arctic, which are most likely under clear-sky conditions, are chosen for the retrieval experiments. Information content analysis suggests that the retrieved surface skin temperature and the mid-IR surface spectral emissivity are highly sensitive to the true values while the retrieval estimates of far-IR surface emissivity are subject to the variation of water vapor abundance. Results show that radiances based on the retrieved state variables are more consistent with the IRIS-D observations compared to those based on the reanalysis data. Retrieval estimates of the state variables along with retrieval uncertainties generally fall within reasonable ranges. The relative uncertainties of retrieved state variables decrease compared to the a priori relative uncertainties. In addition, the necessity to retrieve surface emissivity is corroborated by a parallel retrieval experiment assuming a blackbody surface emissivity that has revealed significant distortions of retrieved specific humidity and temperature profiles in the Arctic lower troposphere.Key PointsAtmospheric profiles and surface properties are simultaneously retrieved from satellite observations made 50 years agoCompared to reanalysis data, the retrieval estimates produce radiances which are more consistent with the ... Article in Journal/Newspaper Arctic Arctic Unknown Arctic |
| spellingShingle | atmospheric retrieval satellite observation far-infrared Atmospheric and Oceanic Sciences Geological Sciences Space Sciences Science Xie, Yan Huang, Xianglei Chen, Xiuhong L’Ecuyer, Tristan S. Drouin, Brian J. Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions |
| title | Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions |
| title_full | Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions |
| title_fullStr | Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions |
| title_full_unstemmed | Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions |
| title_short | Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far-Infrared Missions |
| title_sort | joint use of far-infrared and mid-infrared observation for sounding retrievals: learning from the past for upcoming far-infrared missions |
| topic | atmospheric retrieval satellite observation far-infrared Atmospheric and Oceanic Sciences Geological Sciences Space Sciences Science |
| topic_facet | atmospheric retrieval satellite observation far-infrared Atmospheric and Oceanic Sciences Geological Sciences Space Sciences Science |
| url | https://hdl.handle.net/2027.42/176101 https://doi.org/10.1029/2022EA002684 |