高性能マイクロ波放射計（AMSR2）長期可降水量プロダクトの比較
本研究では、水循環変動観測衛星 (Global Change Observation Mission-Water、 略称GCOM-W)に搭載された高性能マイクロ波放射計(Advanced Microwave Scanning Radiometer 2、 略称AMSR2)による長期可降水量(Total Precipitable Water, 略称TPW)プロダクトに着目した。GCOM-WはAqua衛星などの他の衛星との同時観測を目的としたAfternoon Constellation (A-train)軌道を飛行している。我々は、宇宙航空研究開発機構(Japan Aerospace Explor...
Saved in:
| Published in | 気象集誌. 第2輯 Vol. 101; no. 4; pp. 289 - 308 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
公益社団法人 日本気象学会
2023
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 0026-1165 2186-9057 |
| DOI | 10.2151/jmsj.2023-018 |
Cover
| Abstract | 本研究では、水循環変動観測衛星 (Global Change Observation Mission-Water、 略称GCOM-W)に搭載された高性能マイクロ波放射計(Advanced Microwave Scanning Radiometer 2、 略称AMSR2)による長期可降水量(Total Precipitable Water, 略称TPW)プロダクトに着目した。GCOM-WはAqua衛星などの他の衛星との同時観測を目的としたAfternoon Constellation (A-train)軌道を飛行している。我々は、宇宙航空研究開発機構(Japan Aerospace Exploration Agency、 略称JAXA)とRemote Sensing Systems (RSS)により独自のアルゴリズムで開発された、２つのAMSR2 TPWプロダクトを2012年6月から2020年12月までのデータを用いて比較した。２つのプロダクト間では、TPWアノマリーのトレンドには特に違いは見られなかったが、TPWの絶対値には夏季の北西太平洋・北西大西洋で大きなTPWの差が見られた。我々は、この大きなTPWの差の原因となる気象条件を、再解析、現場観測、Aqua衛星搭載のMODerate resolution Imaging Spectroradiometer (MODIS)による可視赤外データを用いて調査した。これらの調査結果から、JAXAとRSSのTPWプロダクトの差が大きくなる場所では、大気下層に相対湿度が100%に近い逆転層があり、非常に低い高度の雲（霧）が存在する頻度が高いことが分かった。JAXAとRSSのTPW推定アルゴリズムの中で表現されている気温プロファイルを簡易的なモデルで近似し、それぞれのアルゴリズムへの逆転層と霧の影響の評価を、放射伝達モデルを用いて行った。感度実験の結果、逆転層がJAXAアルゴリズムでのTPWの過小推定、RSSアルゴリズムでのTPWの過大推定に関連していることが示唆された。 |
|---|---|
| AbstractList | 本研究では、水循環変動観測衛星 (Global Change Observation Mission-Water、 略称GCOM-W)に搭載された高性能マイクロ波放射計(Advanced Microwave Scanning Radiometer 2、 略称AMSR2)による長期可降水量(Total Precipitable Water, 略称TPW)プロダクトに着目した。GCOM-WはAqua衛星などの他の衛星との同時観測を目的としたAfternoon Constellation (A-train)軌道を飛行している。我々は、宇宙航空研究開発機構(Japan Aerospace Exploration Agency、 略称JAXA)とRemote Sensing Systems (RSS)により独自のアルゴリズムで開発された、２つのAMSR2 TPWプロダクトを2012年6月から2020年12月までのデータを用いて比較した。２つのプロダクト間では、TPWアノマリーのトレンドには特に違いは見られなかったが、TPWの絶対値には夏季の北西太平洋・北西大西洋で大きなTPWの差が見られた。我々は、この大きなTPWの差の原因となる気象条件を、再解析、現場観測、Aqua衛星搭載のMODerate resolution Imaging Spectroradiometer (MODIS)による可視赤外データを用いて調査した。これらの調査結果から、JAXAとRSSのTPWプロダクトの差が大きくなる場所では、大気下層に相対湿度が100%に近い逆転層があり、非常に低い高度の雲（霧）が存在する頻度が高いことが分かった。JAXAとRSSのTPW推定アルゴリズムの中で表現されている気温プロファイルを簡易的なモデルで近似し、それぞれのアルゴリズムへの逆転層と霧の影響の評価を、放射伝達モデルを用いて行った。感度実験の結果、逆転層がJAXAアルゴリズムでのTPWの過小推定、RSSアルゴリズムでのTPWの過大推定に関連していることが示唆された。 |
| Author | 小原, 慧一 可知, 美佐子 久保田, 拓志 計盛, 正博 |
| Author_xml | – sequence: 1 orcidid: 0000-0002-6284-604X fullname: 小原, 慧一 organization: 宇宙航空研究開発機構 – sequence: 1 orcidid: 0000-0002-2037-3563 fullname: 計盛, 正博 organization: 気象庁 – sequence: 1 fullname: 可知, 美佐子 organization: 宇宙航空研究開発機構 – sequence: 1 fullname: 久保田, 拓志 organization: 宇宙航空研究開発機構 |
| BookMark | eNo9kE1LAlEUhi9hkFrLfsbYPffO3DsuRewDjKCv7eXOVzmoxYybdtYE2SLcGBVEQQQFUQoFbaw_c3FwVv6F1KLNORze97zwPhmUqh_UXYQWAecIGLDk10I_RzChGgZzBqUJmEzLY4OnUBpjwjQAZsyhTBj6k1PnLI12k5fruPk0jL5UdKdOHtVJV0Wv8ftD3Pke9E6Hz61Rv1VY39oko_55cvkZ394P2t3k5iLufSRnbRVdje0qak7_Wur4Le52hv1oHs16shq6C387i3aWS9vFVa28sbJWLJQ1H4gpNUqlZ-kO9WzmcBebFuY62Jzq2LM9KQ0K3OEMc4ODBVhaDoW8SanugEeBjZtmUek31w8bcs8Vh0GlJoMjIYNGxa66YoJEAAahT-cEjhjD-dftfRkIX9Ifga97Qw |
| ContentType | Journal Article |
| DOI | 10.2151/jmsj.2023-018 |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Meteorology & Climatology |
| EISSN | 2186-9057 |
| EndPage | 308 |
| ExternalDocumentID | article_jmsj_101_4_101_2023_018_article_char_ja |
| GroupedDBID | 29L 2WC 5GY 7.U ABEFU AENEX AI. ALMA_UNASSIGNED_HOLDINGS CS3 DU5 E3Z EBS ECGQY EJD GROUPED_DOAJ JSF KQ8 OK1 P2P RJT RNS TKC VH1 VOH ZY4 ~02 |
| ID | FETCH-LOGICAL-j128a-33afb4d3fc6d7e08b0741c7340fcfaa5317d7607571b10abd3198334d1f316023 |
| ISSN | 0026-1165 |
| IngestDate | Wed Sep 03 06:30:51 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Language | English |
| License | https://creativecommons.org/licenses/by/4.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-j128a-33afb4d3fc6d7e08b0741c7340fcfaa5317d7607571b10abd3198334d1f316023 |
| ORCID | 0000-0002-6284-604X 0000-0002-2037-3563 |
| OpenAccessLink | http://dx.doi.org/10.2151/jmsj.2023-018 |
| PageCount | 20 |
| ParticipantIDs | jstage_primary_article_jmsj_101_4_101_2023_018_article_char_ja |
| PublicationCentury | 2000 |
| PublicationDate | 2023 |
| PublicationDateYYYYMMDD | 2023-01-01 |
| PublicationDate_xml | – year: 2023 text: 2023 |
| PublicationDecade | 2020 |
| PublicationTitle | 気象集誌. 第2輯 |
| PublicationYear | 2023 |
| Publisher | 公益社団法人 日本気象学会 |
| Publisher_xml | – name: 公益社団法人 日本気象学会 |
| References | Kasahara, M., M. Kachi, K. Inaoka, H. Fujii, T. Kubota, R. Shimada, and Y. Kojima, 2020: Overview and current status of GOSAT-GW mission and AMSR3 instrument. Proc SPIE 11530, Sensors, Systems, and Next-Generation Satellites XXIV, 1153007, doi:10.1117/12.2573914 (Accessed July 8, 2022). Dai, A., J. Wang, P. W. Thorne, D. E. Parker, L. Haimberger, and X. L. Wang, 2011: A new approach to homogenize daily radiosonde humidity data. J. Climate, 24, 965–991. Geer, A. J., P. Bauer, and N. Bormann, 2010: Solar biases in microwave imager observations assimilated at ECMWF. IEEE Trans. Geosci. Remote Sens., 48, 2660–2669. Kawanishi, T., T. Sezai, Y. Ito, K. Imaoka, T. Takeshima, Y. Ishido, A. Shibata, M. Miura, H. Inahata, and R. W. Spencer, 2003: The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), NASDA's contribution to the EOS for global energy and water cycle studies. IEEE Trans. Geosci. Remote Sens., 41, 184–194. Wang, J., L. Zhang, A. Dai, T. Van Hove, and J. Van Baelen, 2007: A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements. J. Geophys. Res., 112, D11107, doi:10.1029/2006JD007529. Wentz, F. J., L. Ricciardulli, K. Hilburn, and C. Mears, 2007: How much more rain will global warming bring? Science, 317, 233–235. Chen, B., and Z. Liu, 2016: Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite. J. Geophys. Res.: Atmos., 121, 11442–11462. Nilsson, T., and G. Elgered, 2008: Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data. J. Geophys. Res., 113, D19101, doi: 10.1029/2008jd010110. Imaoka, K., M. Kachi, H. Fujii, H. Murakami, M. Hori, A. Ono, T. Igarashi, K. Nakagawa, T. Oki, Y. Honda, and H. Shimoda, 2010: Global Change Observation Mission (GCOM) for monitoring carbon, water cycles, and climate change. Proc. IEEE, 98, 717–734. Schröder, M., M. Lockhoff, F. Fell, J. Forsythe, T. Trent, R. Bennartz, E. Borbas, M. G. Bosilovich, E. Castelli, H. Hersbach, M. Kachi, S. Kobayashi, E. R. Kursinski, D. Loyola, C. Mears, R. Preusker, W. B. Rossow, and S. Saha, 2018: The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses. Earth Syst. Sci. Data, 10, 1093–1117. Trenberth, K. E., J. T. Fasullo, and J. Kiehl, 2009: Earth's global energy budget. Bull. Amer. Meteor. Soc., 90, 311–324. Norris, J. R., and S. F. Iacobellis, 2005: North Pacific cloud feedbacks inferred from synoptic-scale dynamic and thermodynamic relationships. J. Climate, 18, 4862–4878. Hashino, T., M. Satoh, Y. Hagihara, S. Kato, T. Kubota, T. Matsui, T. Nasuno, H. Okamoto, and M. Sekiguchi, 2016: Evaluating Arctic cloud radiative effects simulated by NICAM with A-train. J. Geophys. Res.: Atmos., 121, 7041–7063. Sakurai, T., K. Yukio, and T. Kuragano, 2005: Merged satellite and in-situ data global daily SST. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS ’05, Seoul, Korea, 2606–2608. Zhai, P., and R. E. Eskridge, 1997: Atmospheric water vapor over China. J. Climate, 10, 2643–2652. Mears, C. A., D. K. Smith, L. Ricciardulli, J. Wang, H. Huelsing, and F. J. Wentz, 2018: Construction and uncertainty estimation of a satellite-derived total precipitable water data record over the world's oceans. Earth Space Sci., 5, 197–210. Kidd, C., G. Huffman, V. Maggioni, P. Chambon, and R. Oki, 2021: The global satellite precipitation constellation: Current status and future requirements. Bull. Amer. Meteor. Soc., 102, E1844–E1861. Norris, J. R., and C. B. Leovy, 1994: Interannual variability in stratiform cloudiness and sea surface temperature. J. Climate, 7, 1915–1925. Mieruch, S., S. Noël, H. Bovensmann, and J. P. Burrows, 2008: Analysis of global water vapour trends from satellite measurements in the visible spectral range. Atmos. Chem. Phys., 8, 491–504. Mieruch, S., M. Schröder, S. Noël, and J. Schulz, 2014: Comparison of decadal global water vapor changes derived from independent satellite time series. J. Geophys. Res.: Atmos., 119, 12489–12499. Hashino, T., M. Satoh, Y. Hagihara, T. Kubota, T. Matsui, T. Nasuno, and H. Okamoto, 2013: Evaluating cloud microphysics from NICAM against CloudSat and CALIPSO. J. Geophys. Res.: Atmos., 118, 7273–7292. Wentz, F. J., 2000: Algorithm Theoretical Basis Document (ATBD) AMSR Ocean Algorithm (version 2). RSS Tech. Proposal 121599A-1, Remote Sensing Syst., Santa Rosa, CA, 74 pp. [Available at http://www.ssmi.com/tmiInfo.html.] Klein, S. A., and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 1587–1606. Wentz, F. J., and M. Schabel, 2000: Precise climate monitoring using complementary satellite data sets. Nature, 403, 414–416. Kubar, T. L., D. E. Waliser, J.-L. Li, and X. Jiang, 2012: On the annual cycle, variability, and correlations of oceanic low-topped clouds with large-scale circulation using Aqua MODIS and ERA-Interim. J. Climate, 25, 6152–6174. Schröder, M., M. Lockhoff, J. M. Forsythe, H. Q. Cronk, T. H. Vonder Haar, and R. Bennartz, 2016: The GEWEX water vapor assessment: Results from intercomparison, trend, and homogeneity analysis of total column water vapor. J. Appl. Meteor. Climatol., 55, 1633–1649. Held, I. M., and B. J. Soden, 2000: Water vapor feedback and global warming. Annu. Rev. Energy Environ., 25, 441–475. IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Masson-Delmotte, V., P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.), Cambridge University Press, Cambridge, UK, and New York, USA, 2391 pp. IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H. L. Miller (eds.), Cambridge University Press, Cambridge, UK, and New York, USA, 996 pp. Wentz, F. J., and T. Meissner, 2007: Supplement 1: Algorithm Theoretical Basis Document for AMSR-E Ocean Algorithms. RSS Tech. Rpt. 051707. Remote Sen. Syst., Santa Rosa, CA, 6 pp. Ross, R. J., and W. P. Elliott, 2001: Radiosonde-based Northern Hemisphere tropospheric water vapor trends. J. Climate, 14, 1602–1612. Schröder, M., M. Lockhoff, L. Shi, T. August, R. Bennartz, H. Brogniez, X. Calbet, F. Fell, J. Forsythe, A. Gambacorta, S. Ho, E. R. Kursinski, A. Reale, T. Trent, and Q. Yang, 2019: The GEWEX water vapor assessment: Overview and introduction to results and recommendations. Remote Sens., 11, 251, doi:10.3390/rs11030251. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stocker, T. F., D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P. M. Midgley (eds.), Cambridge University Press, Cambridge, UK, and New York, USA, 1535 pp. Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 1205–1218. Wang, J., A. Dai, and C. Mears, 2016: Global water vapor trend from 1988 to 2011 and its diurnal asymmetry based on GPS, radiosonde, and microwave satellite measurements. J. Climate, 29, 5205–5222. Kazumori, M., T. Egawa, and K. Yoshimoto, 2012: A retrieval algorithm of atmospheric water vapor and cloud liquid water for AMSR-E. Eur. J. Remote Sens., 45, 63–74. Wagner, T., S. Beirle, M. Grzegorski, and U. Platt, 2006: Global trends (1996–2003) of total column precipitable water observed by Global Ozone Monitoring Experiment (GOME) on ERS-2 and their relation to near-surface temperature. J. Geophys. Res., 111, D12102, doi:10.1029/2005jd006523. |
| References_xml | – reference: Norris, J. R., and S. F. Iacobellis, 2005: North Pacific cloud feedbacks inferred from synoptic-scale dynamic and thermodynamic relationships. J. Climate, 18, 4862–4878. – reference: Wang, J., L. Zhang, A. Dai, T. Van Hove, and J. Van Baelen, 2007: A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements. J. Geophys. Res., 112, D11107, doi:10.1029/2006JD007529. – reference: Kawanishi, T., T. Sezai, Y. Ito, K. Imaoka, T. Takeshima, Y. Ishido, A. Shibata, M. Miura, H. Inahata, and R. W. Spencer, 2003: The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), NASDA's contribution to the EOS for global energy and water cycle studies. IEEE Trans. Geosci. Remote Sens., 41, 184–194. – reference: Ross, R. J., and W. P. Elliott, 2001: Radiosonde-based Northern Hemisphere tropospheric water vapor trends. J. Climate, 14, 1602–1612. – reference: Schröder, M., M. Lockhoff, J. M. Forsythe, H. Q. Cronk, T. H. Vonder Haar, and R. Bennartz, 2016: The GEWEX water vapor assessment: Results from intercomparison, trend, and homogeneity analysis of total column water vapor. J. Appl. Meteor. Climatol., 55, 1633–1649. – reference: Kazumori, M., T. Egawa, and K. Yoshimoto, 2012: A retrieval algorithm of atmospheric water vapor and cloud liquid water for AMSR-E. Eur. J. Remote Sens., 45, 63–74. – reference: Kidd, C., G. Huffman, V. Maggioni, P. Chambon, and R. Oki, 2021: The global satellite precipitation constellation: Current status and future requirements. Bull. Amer. Meteor. Soc., 102, E1844–E1861. – reference: Nilsson, T., and G. Elgered, 2008: Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data. J. Geophys. Res., 113, D19101, doi: 10.1029/2008jd010110. – reference: Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 1205–1218. – reference: Wentz, F. J., and M. Schabel, 2000: Precise climate monitoring using complementary satellite data sets. Nature, 403, 414–416. – reference: Geer, A. J., P. Bauer, and N. Bormann, 2010: Solar biases in microwave imager observations assimilated at ECMWF. IEEE Trans. Geosci. Remote Sens., 48, 2660–2669. – reference: Kasahara, M., M. Kachi, K. Inaoka, H. Fujii, T. Kubota, R. Shimada, and Y. Kojima, 2020: Overview and current status of GOSAT-GW mission and AMSR3 instrument. Proc SPIE 11530, Sensors, Systems, and Next-Generation Satellites XXIV, 1153007, doi:10.1117/12.2573914 (Accessed July 8, 2022). – reference: Dai, A., J. Wang, P. W. Thorne, D. E. Parker, L. Haimberger, and X. L. Wang, 2011: A new approach to homogenize daily radiosonde humidity data. J. Climate, 24, 965–991. – reference: Held, I. M., and B. J. Soden, 2000: Water vapor feedback and global warming. Annu. Rev. Energy Environ., 25, 441–475. – reference: Wagner, T., S. Beirle, M. Grzegorski, and U. Platt, 2006: Global trends (1996–2003) of total column precipitable water observed by Global Ozone Monitoring Experiment (GOME) on ERS-2 and their relation to near-surface temperature. J. Geophys. Res., 111, D12102, doi:10.1029/2005jd006523. – reference: Zhai, P., and R. E. Eskridge, 1997: Atmospheric water vapor over China. J. Climate, 10, 2643–2652. – reference: IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H. L. Miller (eds.), Cambridge University Press, Cambridge, UK, and New York, USA, 996 pp. – reference: Sakurai, T., K. Yukio, and T. Kuragano, 2005: Merged satellite and in-situ data global daily SST. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS ’05, Seoul, Korea, 2606–2608. – reference: Trenberth, K. E., J. T. Fasullo, and J. Kiehl, 2009: Earth's global energy budget. Bull. Amer. Meteor. Soc., 90, 311–324. – reference: Wang, J., A. Dai, and C. Mears, 2016: Global water vapor trend from 1988 to 2011 and its diurnal asymmetry based on GPS, radiosonde, and microwave satellite measurements. J. Climate, 29, 5205–5222. – reference: Norris, J. R., and C. B. Leovy, 1994: Interannual variability in stratiform cloudiness and sea surface temperature. J. Climate, 7, 1915–1925. – reference: IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stocker, T. F., D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P. M. Midgley (eds.), Cambridge University Press, Cambridge, UK, and New York, USA, 1535 pp. – reference: Wentz, F. J., 2000: Algorithm Theoretical Basis Document (ATBD) AMSR Ocean Algorithm (version 2). RSS Tech. Proposal 121599A-1, Remote Sensing Syst., Santa Rosa, CA, 74 pp. [Available at http://www.ssmi.com/tmiInfo.html.] – reference: Klein, S. A., and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 1587–1606. – reference: Schröder, M., M. Lockhoff, L. Shi, T. August, R. Bennartz, H. Brogniez, X. Calbet, F. Fell, J. Forsythe, A. Gambacorta, S. Ho, E. R. Kursinski, A. Reale, T. Trent, and Q. Yang, 2019: The GEWEX water vapor assessment: Overview and introduction to results and recommendations. Remote Sens., 11, 251, doi:10.3390/rs11030251. – reference: Hashino, T., M. Satoh, Y. Hagihara, S. Kato, T. Kubota, T. Matsui, T. Nasuno, H. Okamoto, and M. Sekiguchi, 2016: Evaluating Arctic cloud radiative effects simulated by NICAM with A-train. J. Geophys. Res.: Atmos., 121, 7041–7063. – reference: Mieruch, S., S. Noël, H. Bovensmann, and J. P. Burrows, 2008: Analysis of global water vapour trends from satellite measurements in the visible spectral range. Atmos. Chem. Phys., 8, 491–504. – reference: Wentz, F. J., L. Ricciardulli, K. Hilburn, and C. Mears, 2007: How much more rain will global warming bring? Science, 317, 233–235. – reference: Chen, B., and Z. Liu, 2016: Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite. J. Geophys. Res.: Atmos., 121, 11442–11462. – reference: Wentz, F. J., and T. Meissner, 2007: Supplement 1: Algorithm Theoretical Basis Document for AMSR-E Ocean Algorithms. RSS Tech. Rpt. 051707. Remote Sen. Syst., Santa Rosa, CA, 6 pp. – reference: Mears, C. A., D. K. Smith, L. Ricciardulli, J. Wang, H. Huelsing, and F. J. Wentz, 2018: Construction and uncertainty estimation of a satellite-derived total precipitable water data record over the world's oceans. Earth Space Sci., 5, 197–210. – reference: Schröder, M., M. Lockhoff, F. Fell, J. Forsythe, T. Trent, R. Bennartz, E. Borbas, M. G. Bosilovich, E. Castelli, H. Hersbach, M. Kachi, S. Kobayashi, E. R. Kursinski, D. Loyola, C. Mears, R. Preusker, W. B. Rossow, and S. Saha, 2018: The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses. Earth Syst. Sci. Data, 10, 1093–1117. – reference: IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Masson-Delmotte, V., P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.), Cambridge University Press, Cambridge, UK, and New York, USA, 2391 pp. – reference: Hashino, T., M. Satoh, Y. Hagihara, T. Kubota, T. Matsui, T. Nasuno, and H. Okamoto, 2013: Evaluating cloud microphysics from NICAM against CloudSat and CALIPSO. J. Geophys. Res.: Atmos., 118, 7273–7292. – reference: Mieruch, S., M. Schröder, S. Noël, and J. Schulz, 2014: Comparison of decadal global water vapor changes derived from independent satellite time series. J. Geophys. Res.: Atmos., 119, 12489–12499. – reference: Imaoka, K., M. Kachi, H. Fujii, H. Murakami, M. Hori, A. Ono, T. Igarashi, K. Nakagawa, T. Oki, Y. Honda, and H. Shimoda, 2010: Global Change Observation Mission (GCOM) for monitoring carbon, water cycles, and climate change. Proc. IEEE, 98, 717–734. – reference: Kubar, T. L., D. E. Waliser, J.-L. Li, and X. Jiang, 2012: On the annual cycle, variability, and correlations of oceanic low-topped clouds with large-scale circulation using Aqua MODIS and ERA-Interim. J. Climate, 25, 6152–6174. |
| SSID | ssj0026476 ssib026971113 |
| Score | 2.3353868 |
| Snippet | 本研究では、水循環変動観測衛星 (Global Change Observation Mission-Water、 略称GCOM-W)に搭載された高性能マイクロ波放射計(Advanced Microwave Scanning Radiometer 2、 略称AMSR2)による長期可降水量(Total... |
| SourceID | jstage |
| SourceType | Publisher |
| StartPage | 289 |
| SubjectTerms | comparison and validation Global Change Observation Mission-Water/Advanced Microwave Scanning Radiometer 2 inversion layer long-term analysis sea fog water vapor content |
| Title | 高性能マイクロ波放射計（AMSR2）長期可降水量プロダクトの比較 |
| URI | https://www.jstage.jst.go.jp/article/jmsj/101/4/101_2023-018/_article/-char/ja |
| Volume | 101 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| ispartofPNX | 気象集誌. 第2輯, 2023, Vol.101(4), pp.289-308 |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpR1Na9RANJR68SJ-Yv0oe3A8KKlJZpLJXITJbpaiVFBa6W1JNllo0VZqe_FUu4L1IL1UVBAFERREW1DwUv0zS5fuqX_B994k2616sApDeDvzvl_Cm5edmVjWBT8RUogst30ulC1k07UT3-e2yCDf5qoJdxUWihM3gvEpcW3anx4avjSwamlpMR1rPvjjvpJ_iSr0QVxxl-wBIttnCh0AQ3zhChGG61_FmMWK6YipkMUBLlnQksUhCzmLaizmCKiYAI9pUQL1YkjXkCoCwENACRYBss8ih4UC-WhgBZzrLKoCABX_La_8pVCyAlxJpFWm6kga1ok9DCkWGvYOiwT2hBJHC6XkgAoEgO6_aIeS4eoyHSMf6FekFErngzPqQooi0yPAd0mBiIUBGaFZWB27zGLJdBWaVzDR_RXNpc3GghhNgduOPOqTR8Ex4AlnD7_vGolyoBX4YI7mxKXGlB7kXzhGInPtG3yJ_gZ5yB_wHcTTCOwRwohCLRAAB9SIg0BtSw1BPEnEYTn4Bsdsr6anjRTw0XyjcKjJG2W8oQe1pltBGVkaGvEHr4K6JsRI_7urSWcdEFm1tLrcwRHYeOySmQNQH36azFaOOSy8nxmL90wzg-99TJ4z330qpkycjub4LRvjbBKz8d37s2Not-0UqXb_AefF49NAPFxx2BB0RYoGUDTKcdyG2JiFWuiQJ6WLy3ev3-znDi9QEtJ2fxYG83z6sGTfVnO-Lqp0ZZ9CMPOchTqsXMNJ08rJo9aRoh6saCP9mDWUzx23RiaglJ1foH-8Khcr1TszUFfSrxPW7d7HF93l9zvt7532687Ku87KRqf9qfvlbXf9x_bmo50Pq7tbq_Sw7m496T371n31Zntto_fyaXfza-_xWqf9HNA77WWiW-08_NzdWN_Zap-0purxZHXcLj6OYs_ClDKxOU9aqch4qxlkMnfCFGuDpuTCaTVbSQKpVWYygIJAuqnrJGkGuTbkXGRui7sBGH_KGp6bn8tPWxVPZmmaZa7n5A5UTy2V5r7vuFmaJV7GU3_Eumpc1LhnTsBpHDBkZ_6XwVnrcBEvaOes4cWFpfw8FAOL6Si9RBule-EnkBjY9Q |
| linkProvider | Colorado Alliance of Research Libraries |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E9%AB%98%E6%80%A7%E8%83%BD%E3%83%9E%E3%82%A4%E3%82%AF%E3%83%AD%E6%B3%A2%E6%94%BE%E5%B0%84%E8%A8%88%EF%BC%88AMSR2%EF%BC%89%E9%95%B7%E6%9C%9F%E5%8F%AF%E9%99%8D%E6%B0%B4%E9%87%8F%E3%83%97%E3%83%AD%E3%83%80%E3%82%AF%E3%83%88%E3%81%AE%E6%AF%94%E8%BC%83&rft.jtitle=%E6%B0%97%E8%B1%A1%E9%9B%86%E8%AA%8C.+%E7%AC%AC2%E8%BC%AF&rft.au=%E5%B0%8F%E5%8E%9F%2C+%E6%85%A7%E4%B8%80&rft.au=%E8%A8%88%E7%9B%9B%2C+%E6%AD%A3%E5%8D%9A&rft.au=%E5%8F%AF%E7%9F%A5%2C+%E7%BE%8E%E4%BD%90%E5%AD%90&rft.au=%E4%B9%85%E4%BF%9D%E7%94%B0%2C+%E6%8B%93%E5%BF%97&rft.date=2023&rft.pub=%E5%85%AC%E7%9B%8A%E7%A4%BE%E5%9B%A3%E6%B3%95%E4%BA%BA+%E6%97%A5%E6%9C%AC%E6%B0%97%E8%B1%A1%E5%AD%A6%E4%BC%9A&rft.issn=0026-1165&rft.eissn=2186-9057&rft.volume=101&rft.issue=4&rft.spage=289&rft.epage=308&rft_id=info:doi/10.2151%2Fjmsj.2023-018&rft.externalDocID=article_jmsj_101_4_101_2023_018_article_char_ja |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0026-1165&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0026-1165&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0026-1165&client=summon |