The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016

Fourteen years of spectral fluxes derived from collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations are used in conjunction with AIRS retrievals to examine the trends of zonal mean spectral outgoing longwave radiation (OLR) and greenhou...

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Published in:GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY
Main Authors: Peterson, Colten A., Chen, Xiuhong, Yue, Qing, Huang, Xianglei
Format: Article in Journal/Newspaper
Language:unknown
Published: Harvard University Press 2019
Subjects:
spectral flux
Arctic climate
greenhouse efficiency
outgoing longwave radiation
Atmospheric and Oceanic Sciences
Science
Arctic
The Cryosphere
Online Access:http://hdl.handle.net/2027.42/151304
https://doi.org/10.1029/2019JD030428
id ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/151304
record_format openpolar
institution Open Polar
collection University of Michigan: Deep Blue
op_collection_id ftumdeepblue
language unknown
topic spectral flux
Arctic climate
greenhouse efficiency
outgoing longwave radiation
Atmospheric and Oceanic Sciences
Science
spellingShingle spectral flux
Arctic climate
greenhouse efficiency
outgoing longwave radiation
Atmospheric and Oceanic Sciences
Science
Peterson, Colten A.
Chen, Xiuhong
Yue, Qing
Huang, Xianglei
The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016
topic_facet spectral flux
Arctic climate
greenhouse efficiency
outgoing longwave radiation
Atmospheric and Oceanic Sciences
Science
description Fourteen years of spectral fluxes derived from collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations are used in conjunction with AIRS retrievals to examine the trends of zonal mean spectral outgoing longwave radiation (OLR) and greenhouse efficiency (GHE) in the Arctic. AIRS retrieved profiles are fed into a radiative transfer model to generate synthetic clear‐sky spectral OLR. Trends are derived from the simulated clear‐sky spectral OLR and GHE and then compared with their counterparts derived from collocated observations. Spectral trends in different seasons are distinctively different. March and September exhibit positive trends in spectral OLR over the far‐IR dirty window and mid‐IR window region for most of the Arctic. In contrast, spectral OLR trends in July are negative over the far‐IR dirty window and can be positive or negative in the mid‐IR window depending on the latitude. Sensitivity studies reveal that surface temperature contributes much more than atmospheric temperature and humidity to the spectral OLR and GHE trends, while the contributions from the latter two are also discernible over many spectral regions (e.g., trends in the far‐IR dirty window in March). The largest increase of spectral GHE is seen north of 80°N in March across the water vapor v2 band and far‐IR. When the secular fractional change of spectral OLR is less than that of surface spectral emission, an increase of spectral GHE can be expected. Spectral trend analyses reveal more information than broadband trend analyses alone.Key PointsObserved Arctic zonal mean trends of spectral flux and greenhouse efficiency are studied for the first timeSpectral trends are seasonally dependent and reveal more information than broadband trendsChanges in surface temperature contribute the most to overall spectral trends, but changes due to air temperature and humidity trends are discernible Peer Reviewed https://deepblue.lib.umich.edu/bitstream/2027.42/151304/1/jgrd55648_am.pdf ...
format Article in Journal/Newspaper
author Peterson, Colten A.
Chen, Xiuhong
Yue, Qing
Huang, Xianglei
author_facet Peterson, Colten A.
Chen, Xiuhong
Yue, Qing
Huang, Xianglei
author_sort Peterson, Colten A.
title The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016
title_short The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016
title_full The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016
title_fullStr The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016
title_full_unstemmed The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016
title_sort spectral dimension of arctic outgoing longwave radiation and greenhouse efficiency trends from 2003 to 2016
publisher Harvard University Press
publishDate 2019
url http://hdl.handle.net/2027.42/151304
https://doi.org/10.1029/2019JD030428
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
The Cryosphere
genre_facet Arctic
Arctic
The Cryosphere
op_relation Peterson, Colten A.; Chen, Xiuhong; Yue, Qing; Huang, Xianglei (2019). "The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016." Journal of Geophysical Research: Atmospheres 124(15): 8467-8480.
2169-897X
2169-8996
http://hdl.handle.net/2027.42/151304
doi:10.1029/2019JD030428
Journal of Geophysical Research: Atmospheres
Parkinson, C. L., & Cavalieri, D. J. ( 2008 ). Arctic sea ice variability and trends, 1979–2006. Journal of Geophysical Research, 113, C07003. https://doi.org/10.1029/2007jc004558
Lee, S., Gong, T. T., Feldstein, S. B., Screen, J. A., & Simmonds, I. ( 2017 ). Revisiting the cause of the 1989–2009 Arctic surface warming using the surface energy budget: Downward infrared radiation dominates the surface fluxes. Geophysical Research Letters, 44, 10,654 – 10,661. https://doi.org/10.1002/2017gl075375
Liu, X., Smith, W. L., Zhou, D. K., & Larar, A. ( 2006 ). Principal component‐based radiative transfer model for hyperspectral sensors: Theoretical concept. Applied Optics, 45 ( 1 ), 201 – 209. https://doi.org/10.1364/ao.45.000201
Liu, Y., Key, J. R., Ackerman, S. A., Mace, G. G., & Zhang, Q. ( 2012 ). Arctic cloud macrophysical characteristics from CloudSat and CALIPSO. Remote Sensing of Environment, 124, 159 – 173. https://doi.org/10.1016/j.rse.2012.05.006
Loeb, N. G., Kato, S., Loukachine, K., & Manalo‐Smith, N. ( 2005 ). Angular distribution models for top‐of‐atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Terra satellite. Part I: Methodology. Journal of Atmospheric and Oceanic Technology, 22 ( 4 ), 338 – 351. https://doi.org/10.1175/JTECH1712.1
Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L., & Merchant, J. W. ( 2000 ). Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. International Journal of Remote Sensing, 21 ( 6‐7 ), 1303 – 1330. https://doi.org/10.1080/014311600210191
McClatchey, R., Fenn, R. R., Selby, J., Volz, F., & Garing, J. ( 1972 ). Optical properties of the atmosphere (Rep. AFCRL‐72‐0497). Bedford, MA: AIR Force Cambridge Research Laboratories.
Olsen, E. ( 2017 ). AIRS/AMSU/HSB version 6 data release user guide. Pasadena, CA: Jet Propulsion Laboratory. Retrieved from. https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/AIRS/3.3_ScienceDataProductDocumentation/3.3.4_ProductGenerationAlgorithms/V6_Data_Release_User_Guide.pdf
Pagano, T. S., Aumann, H. H., Hagan, D. E., & Overoye, K. ( 2003 ). Prelaunch and in‐flight radiometric calibration of the Atmospheric Infrared Sounder (AIRS ). IEEE Transactions on Geoscience and Remote Sensing, 41 ( 2 ), 265 – 273. https://doi.org/10.1109/tgrs.2002.808324
Pan, F., Huang, X. L., Leroy, S. S., Lin, P., Strow, L. L., Ming, Y., & Ramaswamy, V. ( 2017 ). The stratospheric changes inferred from 10 years of AIRS and AMSU‐A radiances. Journal of Climate, 30 ( 15 ), 6005 – 6016. https://doi.org/10.1175/jcli‐d‐17‐0037.1
Pithan, F., & Mauritsen, T. ( 2014 ). Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nature Geoscience, 7, 181 – 184. https://doi.org/10.1038/NGEO2071
Raval, A., & Ramanathan, V. ( 1989 ). Observational determination of the greenhouse‐effect. Nature, 342 ( 6251 ), 758 – 761. https://doi.org/10.1038/342758a0
Screen, J. A., & Simmonds, I. ( 2010a ). The central role of diminishing sea ice in recent Arctic temperature amplification. Nature, 464 ( 7293 ), 1334 – 1337. https://doi.org/10.1038/nature09051
Screen, J. A., & Simmonds, I. ( 2010b ). Increasing fall‐winter energy loss from the Arctic Ocean and its role in Arctic temperature amplification. Geophysical Research Letters, 37, L16707. https://doi.org/10.1029/2010gl044136
Serreze, M. C., Barrett, A. P., Slater, A. G., Steele, M., Zhang, J., & Trenberth, K. E. ( 2007 ). The large‐scale energy budget of the Arctic. Journal of Geophysical Research, 112, D11122. https://doi.org/10.1029/2006JD008230
Serreze, M. C., Barrett, A. P., & Stroeve, J. ( 2012 ). Recent changes in tropospheric water vapor over the Arctic as assessed from radiosondes and atmospheric reanalyses. Journal of Geophysical Research, 117, D10104. https://doi.org/10.1029/2011jd017421
Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., & Holland, M. M. ( 2009 ). The emergence of surface‐based Arctic amplification. The Cryosphere, 3, 11 – 19. https://doi.org/10.5194/tc‐3‐11‐2009
Serreze, M. C., & Barry, R. G. ( 2011 ). Processes and impacts of Arctic amplification: A research synthesis. Global and Planetary Change, 77, 85 – 96. https://doi.org/10.1016/j.gloplacha.2011.03.004
Serreze, M. C., & Francis, J. A. ( 2006 ). The Arctic amplification debate. Climatic Change, 76, 241 – 264. https://doi.org/10.1007/s10584‐005‐9017‐y
Stroeve, J. C., Serreze, M. C., Holland, M. M., Kay, J. E., Malanik, J., & Barrett, A. P. ( 2012 ). The Arctic’s rapidly shrinking sea ice cover: A research synthesis. Climatic Change, 110, 1005 – 1027. https://doi.org/10.1007/s10584‐011‐0101‐1
Susskind, J., Blaisdell, J. M., & Iredell, L. ( 2014 ). Improved methodology for surface and atmospheric soundings, error estimates, and quality control procedures: The Atmospheric Infrared Sounder science team version‐6 retrieval algorithm. Journal of Applied Remote Sensing, 8, 084994. https://doi.org/10.1117/1.jrs.8.084994
Yang, P., Mlynczak, M. G., Wei, H., Kratz, D. P., Baum, B. A., Hu, Y. X., Wiscombe, W. J., Heidinger, A., & Mishchenko, M. I. ( 2003 ). Spectral signature of ice clouds in the far‐infrared region: Single‐scattering calculations and radiative sensitivity study. Journal of Geophysical Research, 108 ( D18 ), 4569. https://doi.org/10.1029/2002jd003291
Yue, Q., Fetzer, E. J., Kahn, B. H., Wong, S., Manipon, G., Guillaume, A., & Wilson, B. ( 2013 ). Cloud‐state‐dependent sampling in AIRS observations based on CloudSat cloud classification. Journal of Climate, 26, 8357 – 8377. https://doi.org/10.1175/jcli‐d‐13‐00065.1
Chen, X. H., Huang, X. L., & Liu, X. ( 2013 ). Non‐negligible effects of cloud vertical overlapping assumptions on longwave spectral fingerprinting studies. Journal of Geophysical Research: Atmospheres, 118, 7309 – 7320. https://doi.org/10.1002/jgrd.50562
Chen, X. H., Huang, X. L., Loeb, N. G., & Wei, H. L. ( 2013 ). Comparisons of clear‐sky outgoing far‐IR flux inferred from satellite observations and computed from the three most recent reanalysis products. Journal of Climate, 26 ( 2 ), 478 – 494. https://doi.org/10.1175/jcli‐d‐12‐00212.1
Aumann, H. H., Broberg, S., Elliott, D., Gaiser, S., & Gregorich, D. ( 2006 ). Three years of Atmospheric Infrared Sounder radiometric calibration validation using sea surface temperatures. Journal of Geophysical Research, 111, D16S90. https://doi.org/10.1029/2005jd006822
Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., & Susskind, J. ( 2003 ). AIRS/AMSU/HSB on the aqua mission: Design, science objectives, data products, and processing systems. IEEE Transactions on Geoscience and Remote Sensing, 41 ( 2 ), 253 – 264. https://doi.org/10.1109/tgrs.2002.808356
Aumann, H. H., & Pagano, T. S. ( 2008 ). Using AIRS and IASI data to evaluate absolute radiometric accuracy and stability for climate applications. Paper presented at Conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization IV ‐ Readiness for GEOSS II, Spie‐Int Soc Optical Engineering, San Diego, CA.
Baldridge, A. M., Hook, S. J., Grove, C. I., & Rivera, G. ( 2009 ). The ASTER spectral library version 2.0. Remote Sensing of Environment, 113, 711 – 715. https://doi.org/10.1016/j.rse.2008.11.007
Bantges, R. J., Brindley, H. E., Chen, X. H., Huang, X. L., Harries, J. E., & Murray, J. E. ( 2016 ). On the detection of robust multidecadal changes in Earth’s outgoing longwave radiation spectrum. Journal of Climate, 29, 4939 – 4947. https://doi.org/10.1175/jcli‐d‐15‐0713.1
Bintanja, R., Graversen, R. G., & Hazeleger, W. ( 2011 ). Arctic winter warming amplified by the thermal inversions and consequent low infrared cooling to space. Nature Geoscience, 4, 758 – 761. https://doi.org/10.1038/NGEO1285
Boisvert, L. N., & Stroeve, J. C. ( 2015 ). The Arctic is becoming warmer and wetter as revealed by the Atmospheric Infrared Sounder. Geophysical Research Letters, 42, 4439 – 4446. https://doi.org/10.1002/2015gl063775
Boisvert, L. N., Wu, D. L., & Shie, C. L. ( 2015 ). Increasing evaporation amounts seen in the Arctic between 2003 and 2013 from AIRS data. Journal of Geophysical Research: Atmospheres, 120, 6865 – 6881. https://doi.org/10.1002/2015jd023258
Boisvert, L. N., Wu, D. L., Vihma, T., & Susskind, J. ( 2015 ). Verification of air/surface humidity differences from AIRS and ERA‐Interim in support of turbulent flux estimation in the Arctic. Journal of Geophysical Research: Atmospheres, 120, 945 – 963. https://doi.org/10.1002/2014jd021666
Cao, Y. F., Liang, S. L., Chen, X. N., He, T., Wang, D. D., & Cheng, X. ( 2017 ). Enhanced wintertime greenhouse effect reinforcing Arctic amplification and initial sea‐ice melting. Scientific Reports, 7 ( 1 ), 8462. https://doi.org/10.1038/s41598‐017‐08545‐2
Cavalieri, D. J., & Parkinson, C. L. ( 2012 ). Arctic sea ice variability and trends, 1979‐2010. The Cryosphere, 6 ( 4 ), 881 – 889. https://doi.org/10.5194/tc‐6‐881‐2012
Chahine, M. T., Pagano, T. S., Aumann, H. H., Atlas, R., Barnet, C., Blaisdell, J., Chen, L., Divakarla, M., Fetzer, E. J., GoldBerg, M., Gauteir, C., Granger, S., Hannon, S., Irion, F. W., Kakar, R., Kalnay, E., Lambrigtsen, B. H., Lee, S.‐Y., Le Marshall, J., Mcmillan, W. W., Mcmillin, L., Olsen, E. T., Revercomb, H., Rosenkranz, P., Smith, W. L., Staelin, D., Strow, L. L., Susskind, J., Tobin, D., Wolf, W., & Zhou, L. ( 2006 ). Improving weather forecasting and providing new data on greenhouse gases. Bulletin of the American Meteorological Society, 87 ( 7 ), 911 – 926. https://doi.org/10.1175/bams‐87‐7‐911
Chen, X., Huang, X., Dong, X., Xi, B., Dolinar, E. K., Loeb, N. G., Kato, S., Stackhouse, P. W., & Bosilovich, M. G. ( 2018 ). Using AIRS and ARM SGP clear‐sky observations to evaluate meteorological reanalyses: A hyperspectral radiance closure approach. Journal of Geophysical Research: Atmospheres, 123, 11,720 – 11,734. https://doi.org/10.1029/2018JD028850
Chen, X. H., Huang, X. L., & Flanner, M. G. ( 2014 ). Sensitivity of modeled far‐IR radiation budgets in polar continents to treatments of snow surface and ice cloud radiative properties. Geophysical Research Letters, 41, 6530 – 6537. https://doi.org/10.1002/2014gl061216
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge‐Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., & Vitart, F. ( 2011 ). The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137 ( 656 ), 553 – 597. https://doi.org/10.1002/qj.828
Elsasser, W. M. ( 1942 ). Heat transfer by infrared radiation in the atmosphere, Harvard Meteorological Studies (Vol. 6, p. 107 ). Cambridge, MA: Harvard University Press.
Feldman, D. R., Algieri, C. A., Collins, W. D., Roberts, Y. L., & Pilewskie, P. A. ( 2011 ). Simulation studies for the detection of changes in broadband albedo and shortwave nadir reflectance spectra under a climate change scenario. Journal of Geophysical Research, 116, D24103. https://doi.org/10.1029/2011JD016407
Feldman, D. R., Collins, W. D., & Paige, J. L. ( 2015 ). Pan‐spectral observing system simulation experiments of shortwave reflectance and long‐wave radiance for climate model evaluation. Geoscientific Model Development, 8, 1943 – 1954. https://doi.org/10.5194/gmd‐8‐1943‐2015
Fetzer, E. J., Lambrigtsen, B. H., Eldering, A., Aumann, H. H., & Chahine, M. T. ( 2006 ). Biases in total precipitable water vapor climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer. Journal of Geophysical Research, 111, D09S16. https://doi.org/10.1029/2005jd006598
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spelling ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/151304 2023-08-20T04:03:07+02:00 The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016 Peterson, Colten A. Chen, Xiuhong Yue, Qing Huang, Xianglei 2019-08-16 application/pdf http://hdl.handle.net/2027.42/151304 https://doi.org/10.1029/2019JD030428 unknown Harvard University Press Wiley Periodicals, Inc. Peterson, Colten A.; Chen, Xiuhong; Yue, Qing; Huang, Xianglei (2019). "The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016." Journal of Geophysical Research: Atmospheres 124(15): 8467-8480. 2169-897X 2169-8996 http://hdl.handle.net/2027.42/151304 doi:10.1029/2019JD030428 Journal of Geophysical Research: Atmospheres Parkinson, C. L., & Cavalieri, D. J. ( 2008 ). Arctic sea ice variability and trends, 1979–2006. Journal of Geophysical Research, 113, C07003. https://doi.org/10.1029/2007jc004558 Lee, S., Gong, T. T., Feldstein, S. B., Screen, J. A., & Simmonds, I. ( 2017 ). Revisiting the cause of the 1989–2009 Arctic surface warming using the surface energy budget: Downward infrared radiation dominates the surface fluxes. Geophysical Research Letters, 44, 10,654 – 10,661. https://doi.org/10.1002/2017gl075375 Liu, X., Smith, W. L., Zhou, D. K., & Larar, A. ( 2006 ). Principal component‐based radiative transfer model for hyperspectral sensors: Theoretical concept. Applied Optics, 45 ( 1 ), 201 – 209. https://doi.org/10.1364/ao.45.000201 Liu, Y., Key, J. R., Ackerman, S. A., Mace, G. G., & Zhang, Q. ( 2012 ). Arctic cloud macrophysical characteristics from CloudSat and CALIPSO. Remote Sensing of Environment, 124, 159 – 173. https://doi.org/10.1016/j.rse.2012.05.006 Loeb, N. G., Kato, S., Loukachine, K., & Manalo‐Smith, N. ( 2005 ). Angular distribution models for top‐of‐atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Terra satellite. Part I: Methodology. Journal of Atmospheric and Oceanic Technology, 22 ( 4 ), 338 – 351. https://doi.org/10.1175/JTECH1712.1 Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L., & Merchant, J. W. ( 2000 ). Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. International Journal of Remote Sensing, 21 ( 6‐7 ), 1303 – 1330. https://doi.org/10.1080/014311600210191 McClatchey, R., Fenn, R. R., Selby, J., Volz, F., & Garing, J. ( 1972 ). Optical properties of the atmosphere (Rep. AFCRL‐72‐0497). Bedford, MA: AIR Force Cambridge Research Laboratories. Olsen, E. ( 2017 ). AIRS/AMSU/HSB version 6 data release user guide. Pasadena, CA: Jet Propulsion Laboratory. Retrieved from. https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/AIRS/3.3_ScienceDataProductDocumentation/3.3.4_ProductGenerationAlgorithms/V6_Data_Release_User_Guide.pdf Pagano, T. S., Aumann, H. H., Hagan, D. E., & Overoye, K. ( 2003 ). Prelaunch and in‐flight radiometric calibration of the Atmospheric Infrared Sounder (AIRS ). IEEE Transactions on Geoscience and Remote Sensing, 41 ( 2 ), 265 – 273. https://doi.org/10.1109/tgrs.2002.808324 Pan, F., Huang, X. L., Leroy, S. S., Lin, P., Strow, L. L., Ming, Y., & Ramaswamy, V. ( 2017 ). The stratospheric changes inferred from 10 years of AIRS and AMSU‐A radiances. Journal of Climate, 30 ( 15 ), 6005 – 6016. https://doi.org/10.1175/jcli‐d‐17‐0037.1 Pithan, F., & Mauritsen, T. ( 2014 ). Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nature Geoscience, 7, 181 – 184. https://doi.org/10.1038/NGEO2071 Raval, A., & Ramanathan, V. ( 1989 ). Observational determination of the greenhouse‐effect. Nature, 342 ( 6251 ), 758 – 761. https://doi.org/10.1038/342758a0 Screen, J. A., & Simmonds, I. ( 2010a ). The central role of diminishing sea ice in recent Arctic temperature amplification. Nature, 464 ( 7293 ), 1334 – 1337. https://doi.org/10.1038/nature09051 Screen, J. A., & Simmonds, I. ( 2010b ). Increasing fall‐winter energy loss from the Arctic Ocean and its role in Arctic temperature amplification. Geophysical Research Letters, 37, L16707. https://doi.org/10.1029/2010gl044136 Serreze, M. C., Barrett, A. P., Slater, A. G., Steele, M., Zhang, J., & Trenberth, K. E. ( 2007 ). The large‐scale energy budget of the Arctic. Journal of Geophysical Research, 112, D11122. https://doi.org/10.1029/2006JD008230 Serreze, M. C., Barrett, A. P., & Stroeve, J. ( 2012 ). Recent changes in tropospheric water vapor over the Arctic as assessed from radiosondes and atmospheric reanalyses. Journal of Geophysical Research, 117, D10104. https://doi.org/10.1029/2011jd017421 Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., & Holland, M. M. ( 2009 ). The emergence of surface‐based Arctic amplification. The Cryosphere, 3, 11 – 19. https://doi.org/10.5194/tc‐3‐11‐2009 Serreze, M. C., & Barry, R. G. ( 2011 ). Processes and impacts of Arctic amplification: A research synthesis. Global and Planetary Change, 77, 85 – 96. https://doi.org/10.1016/j.gloplacha.2011.03.004 Serreze, M. C., & Francis, J. A. ( 2006 ). The Arctic amplification debate. Climatic Change, 76, 241 – 264. https://doi.org/10.1007/s10584‐005‐9017‐y Stroeve, J. C., Serreze, M. C., Holland, M. M., Kay, J. E., Malanik, J., & Barrett, A. P. ( 2012 ). The Arctic’s rapidly shrinking sea ice cover: A research synthesis. Climatic Change, 110, 1005 – 1027. https://doi.org/10.1007/s10584‐011‐0101‐1 Susskind, J., Blaisdell, J. M., & Iredell, L. ( 2014 ). Improved methodology for surface and atmospheric soundings, error estimates, and quality control procedures: The Atmospheric Infrared Sounder science team version‐6 retrieval algorithm. Journal of Applied Remote Sensing, 8, 084994. https://doi.org/10.1117/1.jrs.8.084994 Yang, P., Mlynczak, M. G., Wei, H., Kratz, D. P., Baum, B. A., Hu, Y. X., Wiscombe, W. J., Heidinger, A., & Mishchenko, M. I. ( 2003 ). Spectral signature of ice clouds in the far‐infrared region: Single‐scattering calculations and radiative sensitivity study. Journal of Geophysical Research, 108 ( D18 ), 4569. https://doi.org/10.1029/2002jd003291 Yue, Q., Fetzer, E. J., Kahn, B. H., Wong, S., Manipon, G., Guillaume, A., & Wilson, B. ( 2013 ). Cloud‐state‐dependent sampling in AIRS observations based on CloudSat cloud classification. Journal of Climate, 26, 8357 – 8377. https://doi.org/10.1175/jcli‐d‐13‐00065.1 Chen, X. H., Huang, X. L., & Liu, X. ( 2013 ). Non‐negligible effects of cloud vertical overlapping assumptions on longwave spectral fingerprinting studies. Journal of Geophysical Research: Atmospheres, 118, 7309 – 7320. https://doi.org/10.1002/jgrd.50562 Chen, X. H., Huang, X. L., Loeb, N. G., & Wei, H. L. ( 2013 ). Comparisons of clear‐sky outgoing far‐IR flux inferred from satellite observations and computed from the three most recent reanalysis products. Journal of Climate, 26 ( 2 ), 478 – 494. https://doi.org/10.1175/jcli‐d‐12‐00212.1 Aumann, H. H., Broberg, S., Elliott, D., Gaiser, S., & Gregorich, D. ( 2006 ). Three years of Atmospheric Infrared Sounder radiometric calibration validation using sea surface temperatures. Journal of Geophysical Research, 111, D16S90. https://doi.org/10.1029/2005jd006822 Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., & Susskind, J. ( 2003 ). AIRS/AMSU/HSB on the aqua mission: Design, science objectives, data products, and processing systems. IEEE Transactions on Geoscience and Remote Sensing, 41 ( 2 ), 253 – 264. https://doi.org/10.1109/tgrs.2002.808356 Aumann, H. H., & Pagano, T. S. ( 2008 ). Using AIRS and IASI data to evaluate absolute radiometric accuracy and stability for climate applications. Paper presented at Conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization IV ‐ Readiness for GEOSS II, Spie‐Int Soc Optical Engineering, San Diego, CA. Baldridge, A. M., Hook, S. J., Grove, C. I., & Rivera, G. ( 2009 ). The ASTER spectral library version 2.0. Remote Sensing of Environment, 113, 711 – 715. https://doi.org/10.1016/j.rse.2008.11.007 Bantges, R. J., Brindley, H. E., Chen, X. H., Huang, X. L., Harries, J. E., & Murray, J. E. ( 2016 ). On the detection of robust multidecadal changes in Earth’s outgoing longwave radiation spectrum. Journal of Climate, 29, 4939 – 4947. https://doi.org/10.1175/jcli‐d‐15‐0713.1 Bintanja, R., Graversen, R. G., & Hazeleger, W. ( 2011 ). Arctic winter warming amplified by the thermal inversions and consequent low infrared cooling to space. Nature Geoscience, 4, 758 – 761. https://doi.org/10.1038/NGEO1285 Boisvert, L. N., & Stroeve, J. C. ( 2015 ). The Arctic is becoming warmer and wetter as revealed by the Atmospheric Infrared Sounder. Geophysical Research Letters, 42, 4439 – 4446. https://doi.org/10.1002/2015gl063775 Boisvert, L. N., Wu, D. L., & Shie, C. L. ( 2015 ). Increasing evaporation amounts seen in the Arctic between 2003 and 2013 from AIRS data. Journal of Geophysical Research: Atmospheres, 120, 6865 – 6881. https://doi.org/10.1002/2015jd023258 Boisvert, L. N., Wu, D. L., Vihma, T., & Susskind, J. ( 2015 ). Verification of air/surface humidity differences from AIRS and ERA‐Interim in support of turbulent flux estimation in the Arctic. Journal of Geophysical Research: Atmospheres, 120, 945 – 963. https://doi.org/10.1002/2014jd021666 Cao, Y. F., Liang, S. L., Chen, X. N., He, T., Wang, D. D., & Cheng, X. ( 2017 ). Enhanced wintertime greenhouse effect reinforcing Arctic amplification and initial sea‐ice melting. Scientific Reports, 7 ( 1 ), 8462. https://doi.org/10.1038/s41598‐017‐08545‐2 Cavalieri, D. J., & Parkinson, C. L. ( 2012 ). Arctic sea ice variability and trends, 1979‐2010. The Cryosphere, 6 ( 4 ), 881 – 889. https://doi.org/10.5194/tc‐6‐881‐2012 Chahine, M. T., Pagano, T. S., Aumann, H. H., Atlas, R., Barnet, C., Blaisdell, J., Chen, L., Divakarla, M., Fetzer, E. J., GoldBerg, M., Gauteir, C., Granger, S., Hannon, S., Irion, F. W., Kakar, R., Kalnay, E., Lambrigtsen, B. H., Lee, S.‐Y., Le Marshall, J., Mcmillan, W. W., Mcmillin, L., Olsen, E. T., Revercomb, H., Rosenkranz, P., Smith, W. L., Staelin, D., Strow, L. L., Susskind, J., Tobin, D., Wolf, W., & Zhou, L. ( 2006 ). Improving weather forecasting and providing new data on greenhouse gases. Bulletin of the American Meteorological Society, 87 ( 7 ), 911 – 926. https://doi.org/10.1175/bams‐87‐7‐911 Chen, X., Huang, X., Dong, X., Xi, B., Dolinar, E. K., Loeb, N. G., Kato, S., Stackhouse, P. W., & Bosilovich, M. G. ( 2018 ). Using AIRS and ARM SGP clear‐sky observations to evaluate meteorological reanalyses: A hyperspectral radiance closure approach. Journal of Geophysical Research: Atmospheres, 123, 11,720 – 11,734. https://doi.org/10.1029/2018JD028850 Chen, X. H., Huang, X. L., & Flanner, M. G. ( 2014 ). Sensitivity of modeled far‐IR radiation budgets in polar continents to treatments of snow surface and ice cloud radiative properties. Geophysical Research Letters, 41, 6530 – 6537. https://doi.org/10.1002/2014gl061216 Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge‐Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., & Vitart, F. ( 2011 ). The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137 ( 656 ), 553 – 597. https://doi.org/10.1002/qj.828 Elsasser, W. M. ( 1942 ). Heat transfer by infrared radiation in the atmosphere, Harvard Meteorological Studies (Vol. 6, p. 107 ). Cambridge, MA: Harvard University Press. Feldman, D. R., Algieri, C. A., Collins, W. D., Roberts, Y. L., & Pilewskie, P. A. ( 2011 ). Simulation studies for the detection of changes in broadband albedo and shortwave nadir reflectance spectra under a climate change scenario. Journal of Geophysical Research, 116, D24103. https://doi.org/10.1029/2011JD016407 Feldman, D. R., Collins, W. D., & Paige, J. L. ( 2015 ). Pan‐spectral observing system simulation experiments of shortwave reflectance and long‐wave radiance for climate model evaluation. Geoscientific Model Development, 8, 1943 – 1954. https://doi.org/10.5194/gmd‐8‐1943‐2015 Fetzer, E. J., Lambrigtsen, B. H., Eldering, A., Aumann, H. H., & Chahine, M. T. ( 2006 ). Biases in total precipitable water vapor climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer. Journal of Geophysical Research, 111, D09S16. https://doi.org/10.1029/2005jd006598 IndexNoFollow spectral flux Arctic climate greenhouse efficiency outgoing longwave radiation Atmospheric and Oceanic Sciences Science Article 2019 ftumdeepblue https://doi.org/10.1029/2019JD030428 2023-07-31T20:33:33Z Fourteen years of spectral fluxes derived from collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations are used in conjunction with AIRS retrievals to examine the trends of zonal mean spectral outgoing longwave radiation (OLR) and greenhouse efficiency (GHE) in the Arctic. AIRS retrieved profiles are fed into a radiative transfer model to generate synthetic clear‐sky spectral OLR. Trends are derived from the simulated clear‐sky spectral OLR and GHE and then compared with their counterparts derived from collocated observations. Spectral trends in different seasons are distinctively different. March and September exhibit positive trends in spectral OLR over the far‐IR dirty window and mid‐IR window region for most of the Arctic. In contrast, spectral OLR trends in July are negative over the far‐IR dirty window and can be positive or negative in the mid‐IR window depending on the latitude. Sensitivity studies reveal that surface temperature contributes much more than atmospheric temperature and humidity to the spectral OLR and GHE trends, while the contributions from the latter two are also discernible over many spectral regions (e.g., trends in the far‐IR dirty window in March). The largest increase of spectral GHE is seen north of 80°N in March across the water vapor v2 band and far‐IR. When the secular fractional change of spectral OLR is less than that of surface spectral emission, an increase of spectral GHE can be expected. Spectral trend analyses reveal more information than broadband trend analyses alone.Key PointsObserved Arctic zonal mean trends of spectral flux and greenhouse efficiency are studied for the first timeSpectral trends are seasonally dependent and reveal more information than broadband trendsChanges in surface temperature contribute the most to overall spectral trends, but changes due to air temperature and humidity trends are discernible Peer Reviewed https://deepblue.lib.umich.edu/bitstream/2027.42/151304/1/jgrd55648_am.pdf ... Article in Journal/Newspaper Arctic Arctic The Cryosphere University of Michigan: Deep Blue Arctic GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 10 3 66 86

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