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  • Bell, W., and Coauthors, 2008: The assimilation of SSMIS radiances in numerical weather prediction models. IEEE Trans. Geosci. Remote Sens., 46, 884–900, doi:10.1109/TGRS.2008.917335.

    • Search Google Scholar
    • Export Citation

  • Berg, W., and Sapiano M. , 2013: Corrections and APC for SSMIS. Colorado State University Tech. Rep., 30 pp. [Available online at http://rain.atmos.colostate.edu/FCDR/doc/CSU_FCDR_ssmis_corrections_tech_report.pdf.]

  • Berg, W., Sapiano M. , Horsman J. , and Kummerow C. , 2013: Improved geolocation and Earth incidence angle information for a fundamental climate data record of the SSM/I sensors. IEEE Trans. Geosci. Remote Sens., 51, 1504–1513, doi:10.1109/TGRS.2012.2199761.

    • Search Google Scholar
    • Export Citation

  • Biswas, S. K., Gopalan K. , Jones W. L. , and Bilanow S. , 2010: Correction of time-varying radiometric errors in TRMM Microwave Imager calibrated brightness temperature products. IEEE Geosci. Remote Sens. Lett., 7, 851–855, doi:10.1109/LGRS.2010.2050135.

    • Search Google Scholar
    • Export Citation

  • Biswas, S. K., Gopalan K. , Santos-Garcia A. , and Jones W. L. , 2013: Intercalibration of the microwave radiometer brightness temperature for the Global Precipitation Measurement Mission. IEEE Trans. Geosci. Remote Sens., 51, 1465–1477, doi:10.1109/TGRS.2012.2217148.

    • Search Google Scholar
    • Export Citation

  • Blankenship, C., Al-Khalaf A. , and Wilheit T. , 2000: Retrieval of water vapor profiles using SSM/T-2 and SSM/I data. J. Atmos. Sci., 57, 939–955, doi:10.1175/1520-0469(2000)057<0939:ROWVPU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Brown, S. T., and Ruf C. S. , 2005: Determination of an Amazon hot reference target for the on-orbit calibration of microwave radiometers. J. Atmos. Oceanic Technol., 22, 1340–1352, doi:10.1175/JTECH1769.1.

    • Search Google Scholar
    • Export Citation

  • Buehler, S. A., Kuvatov M. , Sreerekha T. R. , John V. O. , Rydberg B. , Eriksson P. , and Notholt J. , 2007: A cloud filtering method for microwave upper tropospheric humidity measurements. Atmos. Chem. Phys., 7, 5531–5542, doi:10.5194/acp-7-5531-2007.

    • Search Google Scholar
    • Export Citation

  • Chander, G., Hewison T. J. , Fox N. , Wu X. , Xiong X. , and Blackwell W. J. , 2013: Overview of intercalibration of satellite instruments. IEEE Trans. Geosci. Remote Sens., 51, 1056–1080, doi:10.1109/TGRS.2012.2228654.

    • Search Google Scholar
    • Export Citation

  • Chung, E.-S., Soden B. , and John V. O. , 2013: Intercalibrating microwave satellite observations for monitoring long-term variations in upper- and midtropospheric water vapor. J. Atmos. Oceanic Technol., 30, 2303–2319, doi:10.1175/JTECH-D-13-00001.1.

    • Search Google Scholar
    • Export Citation

  • Colton, M. C., and Poe G. A. , 1999: Intersensor calibration of DMSP SSM/I’s: F-8 to F-14, 1987-1997. IEEE Trans. Geosci. Remote Sens., 37, 418–439, doi:10.1109/36.739079.

    • Search Google Scholar
    • Export Citation

  • Dee, D. P., and Coauthors, 2011: ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation

  • Draper, D. W., Newell D. A. , Teusch D. A. , and Yoho P. K. , 2013: Global Precipitation Measurement Microwave Imager prelaunch hot load calibration. IEEE Trans. Geosci. Remote Sens., 51, 4731–4742, doi:10.1109/TGRS.2013.2239300.

    • Search Google Scholar
    • Export Citation

  • Draper, D. W., Newell D. A. , McKague D. S. , and Piepmeier J. R. , 2015a: Assessing calibration stability using the Global Precipitation Measurement (GPM) Microwave Imager (GMI) noise diodes. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 8, 4239–4247, doi:10.1109/JSTARS.2015.2406661.

    • Search Google Scholar
    • Export Citation

  • Draper, D. W., Newell D. A. , Wentz F. J. , Krimchansky S. , and Skofronick-Jackson G. , 2015b: The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument overview and early on-orbit performance. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 8, 3452–3462, doi:10.1109/JSTARS.2015.2403303.

    • Search Google Scholar
    • Export Citation

  • Ebrahimi, H., Datta S. , Santos-Garcia A. , and Jones W. L. , 2014a: Radiometric inter-calibration of SAPHIR using the Microwave Humidity Sounders. 13th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment: MicroRad 2014; Proceedings, IEEE, 211–214, 10.1109/MicroRad.2014.6878942.

  • Ebrahimi, H., Datta S. , and Jones W. L. , 2014b: Radiometric inter-calibration of satellite microwave humidity sounders using the GPM Microwave Imager. 2014 IEEE International Geoscience and Remote Sensing Symposium: Proceedings, IEEE, 2566–2569, doi:10.1109/IGARSS.2014.6946997.

  • Elsaesser, G. S., and Kummerow C. D. , 2008: Toward a fully parametric retrieval of the nonraining parameters over the global oceans. J. Appl. Meteor. Climatol., 47, 1599–1618, doi:10.1175/2007JAMC1712.1.

    • Search Google Scholar
    • Export Citation

  • Farrar, S., Draper D. , Jones L. , and Alquaied F. , 2016: Advantages of calibration attitude maneuvers for spaceborne microwave radiometer missions. 14th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment: Proceedings, IEEE, 186–190, doi:10.1109/MICRORAD.2016.7530531.

  • Gaiser, P. W., and Coauthors, 2004: The WindSat spaceborne polarimetric microwave radiometer: Sensor description and early orbit performance. IEEE Trans. Geosci. Remote Sens., 42, 2347–2361, doi:10.1109/TGRS.2004.836867.

    • Search Google Scholar
    • Export Citation

  • Goldberg, M., and Coauthors, 2011: The Global Space-based Inter-Calibration System. Bull. Amer. Meteor. Soc., 92, 467–475, doi:10.1175/2010BAMS2967.1.

    • Search Google Scholar
    • Export Citation

  • Gopalan, K., Jones L. , Biswas S. , Bilanow S. , Wilheit T. , and Kasparis T. , 2009: A time-varying radiometric bias correction for the TRMM Microwave Imager. IEEE Trans. Geosci. Remote Sens., 47, 3722–3730, doi:10.1109/TGRS.2009.2028882.

    • Search Google Scholar
    • Export Citation

  • Hou, A. Y., and Coauthors, 2014: The Global Precipitation Measurement Mission. Bull. Amer. Meteor. Soc., 95, 701–722, doi:10.1175/BAMS-D-13-00164.1.

    • Search Google Scholar
    • Export Citation

  • Imaoka, K., and Coauthors, 2003: Post-launch calibration and data evaluation of AMSR-E. 2003 IEEE International Geoscience and Remote Sensing Symposium, Vol. 1, IEEE, 666–668, doi:10.1109/IGARSS.2003.1293875.

  • John, V. O., Holl G. , Buehler S. A. , Candy B. , Saunders R. W. , and Parker D. E. , 2012: Understanding intersatellite biases of microwave humidity sounders using global simultaneous nadir overpasses. J. Geophys. Res., 117, D02305, doi:10.1029/2011JD016349.

    • Search Google Scholar
    • Export Citation

  • John, V. O., Allan R. P. , Bell W. , Buehler S. A. , and Kottayil A. , 2013: Assessment of intercalibration methods for satellite microwave humidity sounders. J. Geophys. Res. Atmos., 118, 4906–4918, doi:10.1002/jgrd.50358.

    • Search Google Scholar
    • Export Citation

  • Jones, W. L., Park J. D. , Soisuvarn S. , Hong L. , Gaiser P. W. , and St. Germain K. M. , 2006: Deep-space calibration of the WindSat radiometer. IEEE Trans. Geosci. Remote Sens., 44, 476–495, doi:10.1109/TGRS.2005.862499.

    • Search Google Scholar
    • Export Citation

  • Kroodsma, R. A., McKague D. S. , and Ruf C. S. , 2012: Inter-calibration of microwave radiometers using the vicarious cold calibration double difference method. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 5, 1006–1013, doi:10.1109/JSTARS.2012.2195773.

    • Search Google Scholar
    • Export Citation

  • Kroodsma, R. A., McKague D. S. , and Ruf C. S. , 2016: Vicarious cold calibration for conical scanning microwave imagers. IEEE Trans. Geosci. Remote Sens., doi:10.1109/TGRS.2016.2615552, in press.

    • Search Google Scholar
    • Export Citation

  • Kummerow, C., 1993: On the accuracy of the Eddington approximation for radiative transfer in the microwave frequencies. J. Geophys. Res., 98, 2757–2765, doi:10.1029/92JD02472.

    • Search Google Scholar
    • Export Citation

  • Kunkee, D. B., Poe G. A. , Boucher D. J. , Swadley S. D. , Hong Y. , Wessel J. E. , and Uliana E. A. , 2008a: Design and evaluation of the first Special Sensor Microwave Imager/Sounder. IEEE Trans. Geosci. Remote Sens., 46, 863–883, doi:10.1109/TGRS.2008.917980.

    • Search Google Scholar
    • Export Citation

  • Kunkee, D. B., Swadley S. D. , Poe G. A. , Hong Y. , and Werner M. F. , 2008b: Special Sensor Microwave Imager Sounder (SSMIS) radiometric calibration anomalies—Part I: Identification and characterization. IEEE Trans. Geosci. Remote Sens., 46, 1017–1033, doi:10.1109/TGRS.2008.917213.

    • Search Google Scholar
    • Export Citation

  • Meissner, T., and Wentz F. J. , 2012: The emissivity of the ocean surface between 6 and 90 GHz over a large range of wind speeds and Earth incidence angles. IEEE Trans. Geosci. Remote Sens., 50, 3004–3026, doi:10.1109/TGRS.2011.2179662.

    • Search Google Scholar
    • Export Citation

  • Moradi, I., Meng H. , Ferraro R. R. , and Bilanow S. , 2013: Correcting geolocation errors for microwave instruments aboard NOAA satellites. IEEE Trans. Geosci. Remote Sens., 51, 3625–3637, doi:10.1109/TGRS.2012.2225840.

    • Search Google Scholar
    • Export Citation

  • Moradi, I., Ferraro R. R. , Eriksson P. , and Weng F. , 2015: Intercalibration and validation of observations from ATMS and SAPHIR microwave sounders. IEEE Trans. Geosci. Remote Sens., 53, 5915–5925, doi:10.1109/TGRS.2015.2427165.

    • Search Google Scholar
    • Export Citation

  • NOAA/NCEP, 2000: NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999 (updated daily). National Center for Atmospheric Research Computational and Information Systems Laboratory Research Data Archive, accessed 12 May 2016, doi:10.5065/D6M043C6.

  • Rosenkranz, P. W., 1998: Water vapor microwave continuum absorption: A comparison of measurements and models. Radio Sci., 33, 919–928, doi:10.1029/98RS01182.

    • Search Google Scholar
    • Export Citation

  • Ruf, C. S., 2000: Detection of calibration drifts in spaceborne microwave radiometers using a vicarious cold reference. IEEE Trans. Geosci. Remote Sens., 38, 44–52, doi:10.1109/36.823900.

    • Search Google Scholar
    • Export Citation

  • Sapiano, M., Berg W. , McKague D. , and Kummerow C. , 2013: Towards an intercalibrated fundamental climate data record of the SSM/I sensors. IEEE Trans. Geosci. Remote Sens., 51, 1492–1503, doi:10.1109/TGRS.2012.2206601.

    • Search Google Scholar
    • Export Citation

  • Schaerer, G., and Wilheit T. T. , 1979: A passive microwave technique for profiling of atmospheric water vapor. Radio Sci., 14, 371–375, doi:10.1029/RS014i003p00371.

    • Search Google Scholar
    • Export Citation

  • Troyan, D., 2012: Merged sounding value added product. U.S. Dept. of Energy Rep. DOE/SC-ARM-TR-087, 13 pp. [Available online at https://www.arm.gov/publications/tech_reports/doe-sc-arm-tr-087.pdf.]

  • Twarog, E. M., Purdy W. E. , Gaiser P. W. , Cheung K. H. , and Kelm B. E. , 2006: WindSat on-orbit warm load calibration. IEEE Trans. Geosci. Remote Sens., 44, 516–529, doi:10.1109/TGRS.2005.863300.

    • Search Google Scholar
    • Export Citation

  • Wang, J. R., Racette P. , and Chang L. A. , 1997: MIR measurements of atmospheric water vapor profiles. IEEE Trans. Geosci. Remote Sens., 35, 212–221, doi:10.1109/36.563259.

    • Search Google Scholar
    • Export Citation

  • Wentz, F. J., 1997: A well-calibrated ocean algorithm for special sensor microwave/imager. J. Geophys. Res., 102, 8703–8718, doi:10.1029/96JC01751.

    • Search Google Scholar
    • Export Citation

  • Wentz, F. J., 2015: A 17-year climate record of environmental parameters derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. J. Climate, 28, 6882–6902, doi:10.1175/JCLI-D-15-0155.1.

    • Search Google Scholar
    • Export Citation

  • Wentz, F. J., and Draper D. , 2016: On-orbit absolute calibration of the Global Precipitation Mission Microwave Imager. J. Atmos. Oceanic Technol., 33, 1393–1412, doi:10.1175/JTECH-D-15-0212.1.

    • Search Google Scholar
    • Export Citation

  • Wentz, F. J., Ashcroft P. , and Gentemann C. , 2001: Post-launch calibration of the TRMM microwave imager. IEEE Trans. Geosci. Remote Sens., 39, 415–422, doi:10.1109/36.905249.

    • Search Google Scholar
    • Export Citation

  • Wilheit, T., 2013: Comparing calibrations of similar conically scanning window-channel microwave radiometers. IEEE Trans. Geosci. Remote Sens., 51, 1453–1464, doi:10.1109/TGRS.2012.2207122.

    • Search Google Scholar
    • Export Citation

  • Wilheit, T., Berg W. , Ebrahami H. , Kroodsma R. , McKague D. , Payne V. , and Wang J. , 2015: Intercalibrating the GPM constellation using the GPM Microwave Imager (GMI). 2015 IEEE International Geoscience and Remote Sensing Symposium: Proceedings, IEEE, 5162–5165, doi:10.1109/IGARSS.2015.7326996.

  • Yan, B., and Weng F. , 2008: Intercalibration between Special Sensor Microwave Imager/Sounder and Special Sensor Microwave Imager. IEEE Trans. Geosci. Remote Sens., 46, 984–995, doi:10.1109/TGRS.2008.915752.

    • Search Google Scholar
    • Export Citation

  • Yang, J. X., and McKague D. S. , 2016: Improving collocation-based scan-dependent intercalibration over the ocean for spaceborne radiometry. IEEE Geosci. Remote Sens. Lett., 13, 589–593, doi:10.1109/LGRS.2016.2528261.

    • Search Google Scholar
    • Export Citation

  • Yang, J. X., McKague D. S. , and Ruf C. S. , 2016: Boreal, temperate, and tropical forests as vicarious calibration sites for spaceborne microwave radiometry. IEEE Trans. Geosci. Remote Sens., 54, 1035–1051, doi:10.1109/TGRS.2015.2472532.

    • Search Google Scholar
    • Export Citation

  • Yang, S., Weng F. , Yan B. , Sun N. , and Goldberg M. , 2011: Special Sensor Microwave Imager (SSM/I) intersensor calibration using a simultaneous conical overpass technique. J. Appl. Meteor. Climatol., 50, 77–95, doi:10.1175/2010JAMC2271.1.

    • Search Google Scholar
    • Export Citation

  • Zou, C.-Z., and Wang W. , 2011: Intersatellite calibration of AMSU-A observations for weather and climate applications. J. Geophys. Res., 116, D23113, doi:10.1029/2011JD016205.

    • Search Google Scholar
    • Export Citation
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Editorial Type:
Article
Article Type:
Research Article

Intercalibration of the GPM Microwave Radiometer Constellation

Wesley Berg1, Stephen Bilanow2, Ruiyao Chen3, Saswati Datta4, David Draper5, Hamideh Ebrahimi3, Spencer Farrar3, W. Linwood Jones3, Rachael Kroodsma6, Darren McKague7, Vivienne Payne8, James Wang9, Thomas Wilheit10, and John Xun Yang7
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  • 1 Colorado State University, Fort Collins, Colorado
  • | 2 Wyle Information Systems, McLean, Virginia
  • | 3 University of Central Florida, Orlando, Florida
  • | 4 Data and Image Processing Consultants, LLC, Morrisville, North Carolina
  • | 5 Ball Aerospace and Technologies Corporation, Boulder, Colorado
  • | 6 Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, and NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 7 University of Michigan, Ann Arbor, Michigan
  • | 8 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California
  • | 9 Science Systems and Applications, Inc., Lanham, Maryland
  • | 10 Texas A&M University, College Station, Texas
Print Publication:
01 Dec 2016
Collections:
Global Precipitation Measurement (GPM): Science and Applications
DOI:
https://doi.org/10.1175/JTECH-D-16-0100.1
Page(s):
2639–2654
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Abstract

The Global Precipitation Measurement (GPM) mission is a constellation-based satellite mission designed to unify and advance precipitation measurements using both research and operational microwave sensors. This requires consistency in the input brightness temperatures (Tb), which is accomplished by intercalibrating the constellation radiometers using the GPM Microwave Imager (GMI) as the calibration reference. The first step in intercalibrating the sensors involves prescreening the sensor Tb to identify and correct for calibration biases across the scan or along the orbit path. Next, multiple techniques developed by teams within the GPM Intersatellite Calibration Working Group (XCAL) are used to adjust the calibrations of the constellation radiometers to be consistent with GMI. Comparing results from multiple approaches helps identify flaws or limitations of a given technique, increase confidence in the results, and provide a measure of the residual uncertainty. The original calibration differences relative to GMI are generally within 2–3 K for channels below 92 GHz, although AMSR2 exhibits larger differences that vary with scene temperature. SSMIS calibration differences also vary with scene temperature but to a lesser degree. For SSMIS channels above 150 GHz, the differences are generally within ~2 K with the exception of SSMIS on board DMSP F19, which ranges from 7 to 11 K colder than GMI depending on frequency. The calibrations of the cross-track radiometers agree very well with GMI with values mostly within 0.5 K for the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) and the Microwave Humidity Sounder (MHS) sensors, and within 1 K for the Advanced Technology Microwave Sounder (ATMS).

Corresponding author address: Wesley Berg, Dept. of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523-1371. E-mail: berg@atmos.colostate.edu

This article is included in the Global Precipitation Measurement (GPM) special collection.

Abstract

The Global Precipitation Measurement (GPM) mission is a constellation-based satellite mission designed to unify and advance precipitation measurements using both research and operational microwave sensors. This requires consistency in the input brightness temperatures (Tb), which is accomplished by intercalibrating the constellation radiometers using the GPM Microwave Imager (GMI) as the calibration reference. The first step in intercalibrating the sensors involves prescreening the sensor Tb to identify and correct for calibration biases across the scan or along the orbit path. Next, multiple techniques developed by teams within the GPM Intersatellite Calibration Working Group (XCAL) are used to adjust the calibrations of the constellation radiometers to be consistent with GMI. Comparing results from multiple approaches helps identify flaws or limitations of a given technique, increase confidence in the results, and provide a measure of the residual uncertainty. The original calibration differences relative to GMI are generally within 2–3 K for channels below 92 GHz, although AMSR2 exhibits larger differences that vary with scene temperature. SSMIS calibration differences also vary with scene temperature but to a lesser degree. For SSMIS channels above 150 GHz, the differences are generally within ~2 K with the exception of SSMIS on board DMSP F19, which ranges from 7 to 11 K colder than GMI depending on frequency. The calibrations of the cross-track radiometers agree very well with GMI with values mostly within 0.5 K for the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) and the Microwave Humidity Sounder (MHS) sensors, and within 1 K for the Advanced Technology Microwave Sounder (ATMS).

Corresponding author address: Wesley Berg, Dept. of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523-1371. E-mail: berg@atmos.colostate.edu

This article is included in the Global Precipitation Measurement (GPM) special collection.

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