Skip to main content
Log in

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

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

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 −0.77 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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • 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.

    Google Scholar 

  • 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, 233–244.

    Article  Google Scholar 

  • 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.]

    Google Scholar 

  • Goldberg, M., and Coauthors, 2011: The global space-based intercalibration system (GSICS). Bull. Amer. Meteor. Soc., 92(4), 468–475.

    Article  Google Scholar 

  • Hewison, T. J., X. Wu, F. Yu, Y. Tahara, X. Hu, D. Kim, and M. König, 2013: GSICS inter-calibration of infrared channels of geostationary imagers using Metop/IASI. IEEE Trans. Geosci. Remote Sens., 51(3), 1160–1170.

    Article  Google Scholar 

  • Hilton, F. I., and Coauthors, 2012: Hyperspectral earth observation from IASI: Five years of accomplishments. Bull. Amer. Meteor. Soc., 93(4), 347–370.

    Article  Google Scholar 

  • 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, 6677–6683.

    Article  Google Scholar 

  • 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), 201–210, doi: 10.1007/s13143-014-0008-7.

    Article  Google Scholar 

  • 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, 2471–2485, doi:10.5194/amt-7-2471-2014.

    Article  Google Scholar 

  • 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), 223–233.

    Article  Google Scholar 

  • Tahara, Y., 2008: New approach to intercalibration using high spectral resolution sounder, MSC/JMA Technical Note, No. 50, 1–14.

    Google Scholar 

  • Tahara, Y., and K. Kato, 2009: New spectral compensation method for intercalibration using high spectral resolution sounder. MSC/JMA Technical Note, No. 52, 1–37.

    Google Scholar 

  • 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, 1843–1855.

    Article  Google Scholar 

  • 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, 478–492.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.]

    Google Scholar 

  • 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. 9–11, Melbourne, Australia.

    Google Scholar 

  • 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.]

    Google Scholar 

  • 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), 1215–1223.

    Article  Google Scholar 

  • Wu, X. Q., T. Hewison, and Y. Tahara, 2009: GSICS GEO-LEO inter-calibration: Baseline algorithm and early results. Proc. SPIE, 7456, 745604-1–745604-12.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Myoung-Hwan Ahn.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, D., Ahn, MH. & Choi, M. Inter-comparison of the infrared channels of the meteorological imager onboard COMS and hyperspectral IASI data. Adv. Atmos. Sci. 32, 979–990 (2015). https://doi.org/10.1007/s00376-014-4124-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00376-014-4124-1

Key words

Navigation