An Alternative Bias Correction Scheme for CrIS Data Assimilation in a Regional Model

Xin Li Key Laboratory of Transportation Meteorology, CMA, and Jiangsu Research Institute of Meteorological Sciences, and Nanjing Joint Center of Atmospheric Research, Nanjing, China

Search for other papers by Xin Li in
Current site
Google Scholar
PubMed
Close
,
Xiaolei Zou Cooperative Institute for Climate and Satellites, Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

Search for other papers by Xiaolei Zou in
Current site
Google Scholar
PubMed
Close
, and
Mingjian Zeng Key Laboratory of Transportation Meteorology, CMA, and Jiangsu Research Institute of Meteorological Sciences, and Nanjing Joint Center of Atmospheric Research, Nanjing, China

Search for other papers by Mingjian Zeng in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Bias correction (BC) is a crucial step for satellite radiance data assimilation (DA). In this study, the traditional airmass BC scheme in the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) is investigated for Cross-track Infrared Sounder (CrIS) DA. The ability of the airmass predictors to model CrIS biases is diagnosed. Correlations between CrIS observation-minus-background (OB) samples and the two lapse rate–related airmass predictors employed by GSI are found to be very weak, indicating that the bias correction contributed by the airmass BC scheme is small. A modified BC scheme, which directly calculates the moving average of OB departures from data of the previous 2 weeks with respect to scan position and latitudinal band, is proposed and tested. The impact of the modified BC scheme on CrIS radiance DA is compared with the variational airmass BC scheme. Results from 1-month analysis/forecast experiments show that the modified BC scheme removes nearly all scan-dependent and latitude-dependent biases, while residual biases are still found in some channels when the airmass BC scheme is applied. Smaller predicted root-mean-square errors of temperature and specific humidity and higher equivalent threat scores are obtained by the DA experiment using the modified BC scheme. If OB samples are replaced by observation-minus-analysis (OA) samples for bias estimates in the modified BC scheme, the forecast impacts are reduced but remain positive. A convective precipitation case that occurred on 21 August 2016 is investigated. Using the modified BC scheme, the atmospheric temperature structure and the geopotential height structures near trough/ridge areas are better resolved, resulting in better precipitation forecasts.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. X. Zou, xzou1@umd.edu

Abstract

Bias correction (BC) is a crucial step for satellite radiance data assimilation (DA). In this study, the traditional airmass BC scheme in the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) is investigated for Cross-track Infrared Sounder (CrIS) DA. The ability of the airmass predictors to model CrIS biases is diagnosed. Correlations between CrIS observation-minus-background (OB) samples and the two lapse rate–related airmass predictors employed by GSI are found to be very weak, indicating that the bias correction contributed by the airmass BC scheme is small. A modified BC scheme, which directly calculates the moving average of OB departures from data of the previous 2 weeks with respect to scan position and latitudinal band, is proposed and tested. The impact of the modified BC scheme on CrIS radiance DA is compared with the variational airmass BC scheme. Results from 1-month analysis/forecast experiments show that the modified BC scheme removes nearly all scan-dependent and latitude-dependent biases, while residual biases are still found in some channels when the airmass BC scheme is applied. Smaller predicted root-mean-square errors of temperature and specific humidity and higher equivalent threat scores are obtained by the DA experiment using the modified BC scheme. If OB samples are replaced by observation-minus-analysis (OA) samples for bias estimates in the modified BC scheme, the forecast impacts are reduced but remain positive. A convective precipitation case that occurred on 21 August 2016 is investigated. Using the modified BC scheme, the atmospheric temperature structure and the geopotential height structures near trough/ridge areas are better resolved, resulting in better precipitation forecasts.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. X. Zou, xzou1@umd.edu
Save
  • Anthes, R. A., and Coauthors, 2008: The COSMIC/FORMOSAT-3 mission: Early results. Bull. Amer. Meteor. Soc., 89, 313334, https://doi.org/10.1175/BAMS-89-3-313.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Auligné, T., and A. P. McNally, 2007: Interaction between bias correction and quality control. Quart. J. Roy. Meteor. Soc., 133, 643653, https://doi.org/10.1002/qj.57.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Auligné, T., A. P. McNally, and D. P. Dee, 2007: Adaptive bias correction for satellite data in a numerical weather prediction system. Quart. J. Roy. Meteor. Soc., 133, 631642, https://doi.org/10.1002/qj.56.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Aumann, H. H., and Coauthors, 2003: AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems. IEEE Trans. Geosci. Remote Sens., 41, 253264, https://doi.org/10.1109/TGRS.2002.808356.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chander, G., T. J. Hewison, N. Fox, X. Wu, X. Xiong, and W. J. Blackwell, 2013: Overview of intercalibration of satellite instruments. IEEE Trans. Geosci. Remote Sens., 51, 10561080, https://doi.org/10.1109/TGRS.2012.2228654.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585, https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, X., and X. Zou, 2014: Postlaunch calibration and bias characterization of AMSU-A upper air sounding channels using GPS RO data. J. Geophys. Res. Atmos., 119, 39243941, https://doi.org/10.1002/2013JD021037.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collard, A., J. Derber, and R. Treadon, 2012: Toward assimilation of CrIS and ATMS in the NCEP Global Model. 18th Int. TOVS Study Conf., Toulouse, France, TOVS, 1.21.

  • Dee, D. P., 2004: Variational bias correction of radiance data in the ECMWF system. ECMWF Workshop on Assimilation of High Spectral Resolution Sounders in NWP, Reading, United Kingdom, ECMWF, 16 pp., https://www.ecmwf.int/sites/default/files/elibrary/2004/8930-variational-bias-correction-radiance-data-ecmwf-system.pdf.

  • Dee, D. P., 2005: Bias and data assimilation. Quart. J. Roy. Meteor. Soc., 131, 33233343, https://doi.org/10.1256/qj.05.137.

  • Derber, J. C., and W.-S. Wu, 1998: The use of TOVS cloud-cleared radiances in the NCEP SSI analysis system. Mon. Wea. Rev., 126, 22872299, https://doi.org/10.1175/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Engelen, R. J., and P. Bauer, 2014: The use of variable CO2 in the data assimilation of AIRS and IASI radiances. Quart. J. Roy. Meteor. Soc., 140, 958965, https://doi.org/10.1002/qj.919.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eresmaa, R., J. Letertre-Danczak, C. Lupu, N. Bormann, and T. McNally, 2017: The assimilation of Cross-track Infrared Sounder radiances at ECMWF. Quart. J. Roy. Meteor. Soc., 143, 31773188, https://doi.org/10.1002/qj.3171.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eyre, J. R., 1992: A bias correction scheme for simulated TOVS brightness temperatures. ECMWF Tech. Memo. 186, 34 pp., https://www.ecmwf.int/sites/default/files/elibrary/1992/9330-bias-correction-scheme-simulated-tovs-brightness-temperatures.pdf.

  • Eyre, J. R., and W. P. Menzel, 1989: Retrieval of cloud parameters from satellite sounder data: A simulation study. J. Appl. Meteor., 28, 267275, https://doi.org/10.1175/1520-0450(1989)028<0267:ROCPFS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gambacorta, A., and C. D. Barnet, 2013: Methodology and information content of the NOAA NESDIS operational channel selection for the Cross-track Infrared Sounder (CrIS). IEEE Trans. Geosci. Remote Sens., 51, 32073216, https://doi.org/10.1109/TGRS.2012.2220369.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goldberg, M., and Coauthors, 2011: The Global Space-based Inter-Calibration System. Bull. Amer. Meteor. Soc., 92, 467475, https://doi.org/10.1175/2010BAMS2967.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Han, Y., F. Weng, Q. Liu, and P. van Delst, 2007: A fast radiative transfer model for SSMIS upper atmosphere sounding channels. J. Geophys. Res., 112, D11121, https://doi.org/10.1029/2006JD008208.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Han, Y., and Coauthors, 2013: Suomi NPP CrIS measurements, sensor data record algorithm, calibration and validation activities, and record data quality. J. Geophys. Res. Atmos., 118, 12 73412 748, https://doi.org/10.1002/2013JD020344.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harris, B. A., and G. Kelly, 2001: A satellite radiance-bias correction scheme for data assimilation. Quart. J. Roy. Meteor. Soc., 127, 14531468, https://doi.org/10.1002/qj.49712757418.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Healy, S., and J. Eyre, 2000: Retrieving temperature, water vapor and surface pressure information from refractivity-index profiles derived by radio occultation: A simulation study. Quart. J. Roy. Meteor. Soc., 126, 16611683, https://doi.org/10.1256/smsqj.56606.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ho, S.-P., M. Goldberg, Y.-H. Kuo, C.-Z. Zou, and W. Schreiner, 2009: Calibration of temperature in the lower stratosphere from microwave measurements using COSMIC radio occultation: Preliminary results. Terr. Atmos. Ocean. Sci., 20, 87100, https://doi.org/10.3319/TAO.2007.12.06.01(F3C).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF Single-Moment 6-Class Microphysics Scheme (WSM6). J. Korean Meteor. Soc., 42, 129151.

  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47, 27842802, https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kelly, G. A., and J. F. Flobert, 1988: Radiance tuning. Proc. Fourth Int. TOVS Conf., Igls, Austria, TOVS, 99–117.

  • Kishore, P., S. P. Namboothiri, J. H. Jiang, V. Sivakumar, and K. Igarashi, 2009: Global temperature estimates in the troposphere and stratosphere: A validation study of COSMIC/FORMOSAT-3 measurements. Atmos. Chem. Phys., 9, 897908, https://doi.org/10.5194/acp-9-897-2009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klaes, K. D., and Coauthors, 2007: An introduction to the EUMETSAT polar system. Bull. Amer. Meteor. Soc., 88, 10851096, https://doi.org/10.1175/BAMS-88-7-1085.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kopp, T. J., and Coauthors, 2014: The VIIRS Cloud Mask: Progress in the first year of S-NPP toward a common cloud detection scheme. J. Geophys. Res. Atmos., 119, 24412456, https://doi.org/10.1002/2013JD020458.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kursinski, E., and Coauthors, 1996: Initial results of radio occultation observations of Earth’s atmosphere using the global positioning system. Science, 271, 11071100, https://doi.org/10.1126/science.271.5252.1107.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, X., and X. Zou, 2017: Bias characterization of CrIS radiances at 399 selected channels with respect to NWP model simulations. Atmos. Res., 196, 164181, https://doi.org/10.1016/j.atmosres.2017.06.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liang, D., and F. Weng, 2014: Evaluation of the impact of a new quality control method on assimilation of CrIS data in HWRF-GSI. Geosci. Remote Sens. Symp., Quebec City, Quebec, Canada, IEEE, 3778–3781, https://doi.org/10.1109/IGARSS.2014.6947306.

    • Crossref
    • Export Citation
  • Lin, L., X. Zou, R. Anthes, and Y.-H. Kuo, 2010: COSMIC GPS radio occultation temperature profiles in clouds. Mon. Wea. Rev., 138, 11041118, https://doi.org/10.1175/2009MWR2986.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, L., X. Zou, and F. Weng, 2017: Combining CrIS double CO2 bands for detecting clouds located in different layers of the atmosphere. J. Geophys. Res. Atmos., 122, 18111827, https://doi.org/10.1002/2016JD025505.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, Y., and K. E. Mitchell, 2005: The NCEP Stage II/IV hourly precipitation analyses: Development and applications. 19th Conf. on Hydrology, San Diego, CA, Amer. Meteor. Soc., 1.2, https://ams.confex.com/ams/Annual2005/techprogram/paper_83847.htm.

  • McNally, A. P., and P. D. Watts, 2003: A cloud detection algorithm for high-spectral-resolution infrared sounders. Quart. J. Roy. Meteor. Soc., 129, 34113423, https://doi.org/10.1256/qj.02.208.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, and M. J. Iacono, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 66316 682, https://doi.org/10.1029/97JD00237.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Monin, A. S., and A. M. Obukhov, 1954: Basic laws of turbulent mixing in the ground layer of the atmosphere. Tr. Geofiz. Inst., Akad. Nauk SSSR, 151, 163187.

    • Search Google Scholar
    • Export Citation
  • Noh, Y., W. G. Cheon, S.-Y. Hong, and S. Raasch, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401427, https://doi.org/10.1023/A:1022146015946.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Palmer, P. I., J. Barnett, J. Eyre, and S. Healy, 2000: A nonlinear optimal estimation inverse method for radio occultation measurements of temperature, humidity, and surface pressure. J. Geophys. Res., 105, 17 51317 526, https://doi.org/10.1029/2000JD900151.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prunet, P., J. N. Thépaut, and V. Cassé, 1998: The information content of clear sky IASI radiances and their potential for numerical weather prediction. Quart. J. Roy. Meteor. Soc., 124, 211241, https://doi.org/10.1002/qj.49712454510.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rocken, C., and Coauthors, 1997: Analysis and validation of GPS/MET data in the neutral atmosphere. J. Geophys. Res., 102, 29 84929 866, https://doi.org/10.1029/97JD02400.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schrøder, T., S. Leroy, M. Stendel, and E. Kaas, 2003: Validating the microwave sounding unit stratospheric record using GPS occultation. Geophys. Res. Lett., 30, 1734, https://doi.org/10.1029/2003GL017588.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, A., N. Atkinson, W. Bell, and A. Doherty, 2015: An initial assessment of observations from the Suomi-NPP satellite: Data from the Cross-track Infrared Sounder (CrIS). Atmos. Sci. Lett., 16, 260266, https://doi.org/10.1002/asl2.551.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Strow, L. L., and Coauthors, 2013: Spectral calibration and validation of the Cross-track Infrared Sounder (CrIS) on the Suomi NPP satellite. J. Geophys. Res. Atmos., 118, 12 48612 496, https://doi.org/10.1002/2013JD020480.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tobin, D., and Coauthors, 2013: Suomi-NPP CrIS radiometric calibration uncertainty. J. Geophys. Res. Atmos., 118, 10 58910 600, https://doi.org/10.1002/jgrd.50809.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, L., and Coauthors, 2013: Geolocation assessment for CrIS sensor data records. J. Geophys. Res. Atmos., 118, 12 69012 704, https://doi.org/10.1002/2013JD020376.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weng, F., 2007: Advances in radiative transfer modeling in support of satellite data assimilation. J. Atmos. Sci., 64, 37993807, https://doi.org/10.1175/2007JAS2112.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wickert, J., G. Beyerle, R. König, S. Heise, L. Grunwaldt, G. Michalak, C. Reigber, and T. Schmidt, 2005: GPS radio occultation with CHAMP and GRACE: A first look at a new and promising satellite configuration for global atmospheric sounding. Ann. Geophys., 23, 653658, https://doi.org/10.5194/angeo-23-653-2005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, W. S., R. J. Purser, and D. F. Parrish, 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130, 29052916, https://doi.org/10.1175/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, S., and X. Zou, 2012: Assessments of cloud liquid water contributions to GPS radio occultation refractivity using measurements from COSMIC and CloudSat. J. Geophys. Res., 117, D06219, https://doi.org/10.1029/2011JD016452.

    • Search Google Scholar
    • Export Citation
  • Zhu, Y., J. Derber, A. Collard, D. Dee, R. Treadon, G. Gayno, and J. A. Jung, 2014a: Enhanced radiance bias correction in the National Centers for Environmental Prediction’s Gridpoint Statistical Interpolation data assimilation system. Quart. J. Roy. Meteor. Soc., 140, 14791492, https://doi.org/10.1002/qj.2233.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhu, Y., and Coauthors, 2014b: Variational bias correction in the NCEP’s data assimilation system. 19th Int. TOVS Conf., Jeju Island, South Korea, TOVS 13 pp., http://cimss.ssec.wisc.edu/itwg/itsc/itsc19/program/papers/10_02_zhu.pdf.

  • Zou, X., L. Lin, and F. Weng, 2014: Absolute calibration of ATMS upper level temperature sounding channels using GPS RO observations. IEEE Trans. Geosci. Remote Sens., 52, 13971406, https://doi.org/10.1109/TGRS.2013.2250981.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 650 231 19
PDF Downloads 565 147 9