Inter-comparison of the infrared channels of the meteorological imager onboard COMS and hyperspectral IASI data

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• 作者：Dohyeong Kim ; Myoung-Hwan Ahn ; Minjin Choi
• 关键词：meteorological imager ; inter ; comparison ; instrument long ; term stability ; water vapor channel
• 刊名：Advances in Atmospheric Sciences
• 出版年：2015
• 出版时间：July 2015
• 年：2015
• 卷：32
• 期：7
• 页码：979-990
• 全文大小：779 KB
• 参考文献：Choi, J.-K., Y. J. Park, J. H. Ahn, H. S. Lim, J. Eom, and J.-H. Ryu, 2012: GOCI, the world’s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity. J. Geophys. Res., 117(C9), doi:10.1029/2012JC008046.
  Clough, S. A., M. W. Shephard, E. J. Mlawer, J. S. Delamere, M. J. Iacono, K. Cady-Pereira, S. Boukabara, and P. D. Brown, 2005: Atmospheric radiative transfer modeling: A summary of the AER codes. Journal of Quantitative Spectroscopy and Radiative Transfer, 91, 233-44.View Article
  EUMETSAT, 2013: IASI Level 1 Products Guide. EUM/OPSEPS/MAN/04/0032, v4A, EUMETSAT, Darmstadt, Germany. [Available online at http://?oiswww.?eumetsat.?org/?WEBOPS/?eps-pg/?IASI-L1/?IASIL1-PG-0TOC.?htm .]
  Goldberg, M., and Coauthors, 2011: The global space-based intercalibration system (GSICS). Bull. Amer. Meteor. Soc., 92(4), 468-75.View Article
  Hewison, T. J., X. Wu, F. Yu, Y. Tahara, X. Hu, D. Kim, and M. K?nig, 2013: GSICS inter-calibration of infrared channels of geostationary imagers using Metop/IASI. IEEE Trans. Geosci. Remote Sens., 51(3), 1160-170.View Article
  Hilton, F. I., and Coauthors, 2012: Hyperspectral earth observation from IASI: Five years of accomplishments. Bull. Amer. Meteor. Soc., 93(4), 347-70.View Article
  Illingworth, S. M., J. J. Remedios, and R. J. Parker, 2009: Intercomparison of integrated IASI and AATSR calibrated radiances at 11 μm and 12 μm, IASI data. Atmos. Chem. Phys., 9, 6677-683.View Article
  Kim, B.-R., S.-H. Ham, D. Kim, and B. J. Sohn, 2014: Post-Flight radiometric calibration of the Korean geostationary satellite COMS meteorological imager. Asia-Pac. J. Atmos. Sci., 50(2), 201-10, doi: 10.1007/s13143-014-0008-7.View Article
  Kim, D., and M. H. Ahn, 2014: Introduction to the in-orbit-test and its performance of the first meteorological imager of the Communication, Ocean, and Meteorological Satellite. Atmos. Meas. Tech., 7, 2471-485, doi:10.5194/amt-7-2471-2014.View Article
  Ryu, J. H., H. J. Han, S. Cho, Y. J. Park, and Y. H. Ahn, 2012: Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS). Ocean Science Journal, 47(3), 223-33.View Article
  Tahara, Y., 2008: New approach to intercalibration using high spectral resolution sounder, MSC/JMA Technical Note, No. 50, 1-4.
  Tahara, Y., and K. Kato, 2009: New spectral compensation method for intercalibration using high spectral resolution sounder. MSC/JMA Technical Note, No. 52, 1-7.
  Wang, L., C. Cao, and M. D. Goldberg, 2009: Intercalibration of GOES-11 and GOES-12 water vapor channels with MetOp/IASI hyperspectral measurements. J. Atmos. Oceanic Technol., 26, 1843-855.View Article
  Wang, L. K., X. Q. Wu, M. Goldberg, C. Y. Cao, Y. P. Li, and S. H. Sohn, 2010: Comparison of AIRS and IASI radiances using GOES imagers as transfer radiometers toward climate data records. J. Appl. Meteor. Climatol., 49, 478-92.View Article
  Wang, L. K., M. Goldberg, X. Q. Wu, C. Y. Cao, R. A. Iacovazzi Jr., F. F. Yu, and Y. P. Li, 2011: Consistency assessment of atmospheric infrared sounder and infrared atmospheric sounding interferometer radiances: Double differences versus simultaneous nadir overpasses. J. Geophys. Res., 116, D11111, doi:10.1029/2010JD014988.View Article
  Weinreb, M., and D. Han, 2003: Implementation of midnight blackbody calibration correction (MBCC). NOAA NESDIS Office of Satellite Operations. [Available online at http://?www.?ospo.?noaa.?gov/?Operations/?GOES/?calibration/?mbcc_?implemmentation.?html .]
  Woo, J., B. I. Lee, H. Oh, J. S. Kim, and S. H. Sohn, 2013: Diurnal variation of COMS MI image navigation and registration performance. 4th Asia-Oceania Meteorological Satellite Users Confereence, Oct. 9-1, Melbourne, Australia.
  Wu, X., and F. Yu, 2011: GSICS Algorithm Theoretical Basis Document (ATBD) for GOES-AIRS/IASI Inter-Calibration, NOAA NESDIS. [Available online at https://?gsics.?nesdis.?noaa.?gov/?wiki/?GPRC/?AtbdCentral .]
  Wu, X. Q., and F. F. Yu, 2013: Correction for GOES imager spectral response function using GSICS. Part I: Theory. IEEE Trans. Geosci. Remote Sens., 51(3), 1215-223.View Article
  Wu, X. Q., T. Hewison, and Y. Tahara, 2009: GSICS GEO-LEO inter-calibration: Baseline algorithm and early results. Proc. SPIE, 7456, 745604-1-45604-12.
  
• 作者单位：Dohyeong Kim (1)
  Myoung-Hwan Ahn (2)
  Minjin Choi (1)
  
  1. National Meteorological Satellite Center of the Korea Meteorological Administration, 64-18 Guam-gil, Gwanghyewon-myeon, Jincheon-gun, Chungcheongbuk-do, 365-830, Republic of Korea
  2. Department of Atmospheric Science and Engineering, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul, 120-750, Republic of Korea
  
• 刊物主题：Atmospheric Sciences; Meteorology; Geophysics/Geodesy;
• 出版者：Springer Berlin Heidelberg
• ISSN：1861-9533

文摘

The successful launch and commissioning of the first geostationary meteorological satellite of Korea has the potential to enhance earth observation capability over the Asia Pacific region. Although the specifications of the payload, the meteorological imager (MI), have been verified during both ground and in-orbit tests, there is the possibility of variation and/or degradation of data quality due to many different reasons, such as the accumulation of contaminants, the aging of instrument components, and unexpected external disturbance. Thus, for better utilization of MI data, it is imperative to continuously monitor and maintain the data quality. As a part of such activity, this study presents an inter-calibration, based on the Global Space-based Inter-Calibration System (GSICS), between the MI data and the high quality hyperspectral data from the Infrared Atmospheric Sounding Interferometer (IASI) of the Metop-A satellite. Both sets of data, acquired for three years from April 2011 to March 2014, are processed to prepare the matchup dataset, which is spatially collocated, temporally concurrent, angularly coincident, and spectrally comparable. The results show that the MI data are stable within the specifications and show no significant degradation during the study period. However, the water vapor channel shows a rather large bias value of ?.77 K, with a root-mean-square difference (RMSD) of around 1.1 K, which is thought to be due to the shift in the spectral response function. The shortwave channel shows a maximum RMSD of around 1.39 K, mainly due to the coarse digitization at the lower temperature. The inter-comparison results are re-checked through a sensitivity analysis with different sets of threshold values used for the matchup dataset. Based on this, we confirm that the overall quality of the MI data meets the user requirements and maintains the expected performance, although the water vapor channel requires further investigation.