Performance of Satellite Rainfall Estimation Algorithms during TOGA COARE

Elizabeth E. Ebert Bureau of Meteorology Research Centre, Melbourne, Australia

Search for other papers by Elizabeth E. Ebert in
Current site
Google Scholar
PubMed
Close
and
Michael J. Manton Bureau of Meteorology Research Centre, Melbourne, Australia

Search for other papers by Michael J. Manton in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Over 50 satellite rainfall algorithms were evaluated for a 5° square region in the equatorial western Pacific Ocean during TOGA COARE, November 1992–February 1993. These satellite algorithms used GMS VIS/IR, AVHRR, and SSM/I data to estimate rainfall on both instantaneous and monthly timescales. Validation data came from two calibrated shipboard Doppler radars measuring rainfall every 10 min.

There was large variation among algorithms in the magnitude of the satellite-estimated rainfall, but the patterns of rainfall were similar among algorithm types. Compared to the radar observations, most of the satellite algorithms overestimated the amount of rain falling in the region, typically by about 30%. Patterns of monthly observed rainfall were well represented by the satellite algorithms, with correlation coefficients with the observations ranging from 0.86 to 0.90 for algorithms using geostationary data and 0.69 to 0.86 for AVHRR and SSM/I algorithms when validated on a 0.5° grid. Patterns of instantaneous rain rates were also well analyzed, with correlation coefficients with the radar observations of 0.43–0.58 for the geostationary algorithms and 0.60–0.78 for SSM/I algorithms.

Two case studies are presented to demonstrate the capability of one IR algorithm and three microwave algorithms to estimate instantaneous rainfall rates in the Tropics. The three microwave algorithms differed in their estimates of rain area but all showed greater ability than the IR algorithm to reproduce the spatial pattern of rainfall.

Corresponding author address: Elizabeth E. Ebert, Bureau of Meteorology Research Centre, G.P.O. Box 1289 K, Melbourne, Victoria 3001, Australia.

Email: e.ebert@bom.gov.au

Abstract

Over 50 satellite rainfall algorithms were evaluated for a 5° square region in the equatorial western Pacific Ocean during TOGA COARE, November 1992–February 1993. These satellite algorithms used GMS VIS/IR, AVHRR, and SSM/I data to estimate rainfall on both instantaneous and monthly timescales. Validation data came from two calibrated shipboard Doppler radars measuring rainfall every 10 min.

There was large variation among algorithms in the magnitude of the satellite-estimated rainfall, but the patterns of rainfall were similar among algorithm types. Compared to the radar observations, most of the satellite algorithms overestimated the amount of rain falling in the region, typically by about 30%. Patterns of monthly observed rainfall were well represented by the satellite algorithms, with correlation coefficients with the observations ranging from 0.86 to 0.90 for algorithms using geostationary data and 0.69 to 0.86 for AVHRR and SSM/I algorithms when validated on a 0.5° grid. Patterns of instantaneous rain rates were also well analyzed, with correlation coefficients with the radar observations of 0.43–0.58 for the geostationary algorithms and 0.60–0.78 for SSM/I algorithms.

Two case studies are presented to demonstrate the capability of one IR algorithm and three microwave algorithms to estimate instantaneous rainfall rates in the Tropics. The three microwave algorithms differed in their estimates of rain area but all showed greater ability than the IR algorithm to reproduce the spatial pattern of rainfall.

Corresponding author address: Elizabeth E. Ebert, Bureau of Meteorology Research Centre, G.P.O. Box 1289 K, Melbourne, Victoria 3001, Australia.

Email: e.ebert@bom.gov.au

Save
  • Adler, R. F., and A. J. Negri, 1988: A satellite infrared technique to estimate tropical convective and stratiform rainfall. J. Appl. Meteor.,27, 30–51.

  • ——, ——, P. R. Keehn, and I. M. Hakkarinen, 1993: Estimation of monthly rainfall over Japan and surrounding waters from a combination of low-orbit microwave and geosynchronous IR data. J. Appl. Meteor.,32, 335–356.

  • ——, G. J. Huffman, and P. R. Keehn, 1994: Global tropical rain estimates from microwave-adjusted geosynchronous IR data. Remote Sens. Rev.,11, 125–152.

  • Allam, R. E., G. Holpin, P. Jackson, and G. L. Liberti, 1993: Second Algorithm Intercomparison Project of the Global Precipitation Climatology Project (AIP-2), U.K. and Northwest Europe, February–April 1991. Pre-Workshop Rep. Satellite Image Applications Group, U.K. Meteorological Office, 439 pp. [Available from Satellite Image Applications Group, U.K. Meteorological Office, Bracknell, Berkshire, RG12 2SZ, United Kingdom.].

  • Aonashi, K., A. Shibata, and G. Liu, 1996: An over-ocean precipitation retrieval using SSM/I multichannel brightness temperatures. J. Meteor. Soc. Japan,74, 617–637.

  • Arkin, P. A., and B. N. Meisner, 1987: The relationship between large-scale convective rainfall and cold cloud over the Western Hemisphere during 1982–84. Mon. Wea. Rev.,115, 51–74.

  • ——, and P. Xie, 1994: The Global Precipitation Climatology Project:First Algorithm Intercomparison Project. Bull. Amer. Meteor. Soc.,75, 401–419.

  • Barrett, E. C., R. F. Adler, K. Arpe, P. Bauer, W. Berg, A. Chang, R. Ferraro, J. Ferriday, S. Goodman, Y. Hong, J. Janowiak, C. Kidd, D. Kniveton, M. Morrissey, W. Olson, G. Petty, B. Rudolf, A. Shibata, E. Smith, and R. Spencer, 1994: The First WetNet Precipitation Intercomparison Project (PIP-1): Interpretation of results. Remote Sens. Rev.,11, 303–373.

  • Basili, P., P. Ciotti, G. d’Auria, F. S. Marzano, and N. Pierdicca, 1995:Microwave radiometry characterization of precipitating clouds. Microwave Radiometry of the Environment, D. Solimini, Ed., VSP International Scientific Publishers, 253–263.

  • Bauer, P., and P. Schluessel, 1993: Rainfall, total water, ice water, and water vapor over sea from polarized microwave simulations and Special Sensor Microwave/Imager data. J. Geophys. Res.,98, 20737–20759.

  • Berg, W., 1994: Precipitation retrieval during TOGA COARE using a combination of SSM/I and GMS data with application to climate studies. Preprints, Seventh Conf. on Satellite Meteorology and Oceanography, Monterey, CA, Amer. Meteor. Soc., 67–70.

  • ——, and R. Chase, 1992: Determination of mean rainfall from the Special Sensor Microwave/Imager (SSM/I) using a mixed lognormal distribution. J. Atmos. Oceanic Technol.,9, 129–141.

  • Carey, L. D., S. A. Rutledge, and R.H. Johnson, 1994: Heat and moisture budget over the TOGA COARE IFA during the mature phase of the 24 December 1992 mesoscale convective system. Preprints, Sixth Conf. on Mesoscale Processes, Portland, OR, Amer. Meteor. Soc., 5–8.

  • Churchill, D. D., and R. A. Houze, 1984: Development and structure of winter monsoon cloud clusters on 10 December 1978. J. Atmos. Sci.,41, 993–960.

  • Ebert, E. E., 1996: Results of the 3rd Algorithm Intercomparison Project (AIP-3) of the Global Precipitation Climatology Project (GPCP). Revision 1. BMRC Research Rep. No. 55, 299 pp. [Available from Bureau of Meteorology Research Centre, GPO Box 1289K, Melbourne, Australia 3000.].

  • ——, M. J. Manton, P. A. Arkin, R. J. Allam, G. E. Holpin, and A. Gruber, 1996: Results from the GPCP Algorithm Intercomparison Projects. Bull Amer. Meteor. Soc.,77, 2875–2887.

  • Ferraro, R. R., and G. F. Marks, 1995: The development of SSM/I rain-rate retrieval algorithms using ground-based radar measurements. J. Atmos. Oceanic Technol.,12, 755–770.

  • Ferriday, J. G., and S. K. Avery, 1994: Passive microwave remotesensing of rainfall with SSM/I: Algorithm development and implementation. J. Appl. Meteor.,33, 1587–1596.

  • Fiore, J. B., and N. C. Grody, 1990: A classification algorithm for monitoring snow cover and precipitation using SSM/I measurements. Preprints, Fifth Conf. on Satellite Meteorology and Oceanography, London, United Kingdom, Amer. Meteor. Soc., 237–240.

  • Goodman, B., P. Menzel, D. Martin, and E. Cutrim, 1993: A non-linear algorithm for estimating three-hourly rain rates over Amazonia from GOES/VISSR observations. Remote Sens. Rev.,10, 169–177.

  • Grassotti, C., and L. Garand, 1994: Classification-based rainfall estimation using satellite data and numerical forecast model fields. J. Appl. Meteor.,33, 159–178.

  • Grody, N. C., 1991: Classification of snow cover and precipitation using the Special Sensor Microwave/Imager (SSM/I). J. Geophys. Res.,96, 7423–7435.

  • Hogg, W. D., 1990: Comparison of some VIS/IR rainfall estimation techniques. Preprints, Fifth Conf. on Satellite Meteorology and Oceanography, London, United Kingdom, Amer. Meteor. Soc., 287–291.

  • Inoue, T., 1987: An instantaneous delineation of convective rainfall areas using split-window data of NOAA-7 AVHRR. J. Meteor. Soc. Japan,65, 469–481.

  • Janowiak, J. E., 1992: Tropical rainfall: A comparison of satellite-derived rainfall estimates with model precipitation forecasts, climatologies, and observations. Mon. Wea. Rev.,120, 448–462.

  • Jobard, I., and M. Desbois, 1994: Satellite estimation of the tropical precipitation using the METEOSAT and SSM/I data. Atmos. Res.,34, 285–298.

  • Kummerow, C., and L. Giglio, 1994: A passive microwave technique for estimating rainfall and vertical structure information from space. Part I: Algorithm description. J. Appl. Meteor.,33, 3–18.

  • Lee, T. H., J. E., Janowiak, and P. A. Arkin, 1991: Atlas of Products from the Algorithm Intercomparison Project 1: Japan and Surrounding Oceanic Regions, June–August 1989. University Corporation for Atmospheric Research, 131 pp. [Available from the Climate Analysis Center, NOAA, 5200 Auth Road, Camp Springs, MD 20746-4304.].

  • Liu, G., and J. A. Curry, 1992: Retrieval of precipitation from satellite microwave measurement using both emission and scattering. J. Geophys. Res.,97, 9959–9974.

  • ——, ——, and R.-S. Sheu, 1995: Classification of clouds over the western equatorial Pacific Ocean using combined infrared and microwave satellite data. J. Geophys. Res.,100, 13811–13826.

  • Marzano, F. S., A. Mugnai, N. Pierdicca, E. A. Smith, J. Turk, and J. Vivekanandanan, 1995: Precipitation profile retrieval from airborne microwave radiometers: A case study over ocean during CaPE. Microwave Radiometry of the Environment, D. Solimini, Ed., VSP International Scientific Publishing, 264–274.

  • McBride, J. L., N. E. Davidson, K. Puri, and G. C. Tyrell, 1995: The flow during TOGA COARE as diagnosed by the BMRC Tropical Analysis and Prediction System. Mon. Wea. Rev.,123, 717–736.

  • Morrissey, M. L., and J. S. Greene, 1991: The Pacific Atoll raingage data set. JIMAR Contribution No. 91-242, 45 pp. [Available from School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, HI 96822.].

  • ——, W. F. Krajewski, and M. J. McPhaden, 1994: Estimating rainfallin the Tropics using the fractional time raining. J. Appl. Meteor.,33, 387–393.

  • Negri, J. J., R. F. Adler, and P. J. Wetzel, 1984: Rain estimation from satellites: An examination of the Griffith–Woodley technique. J. Climate Appl. Meteor.,23, 102–116.

  • Petty, G. W., and D. R. Stettner, 1994: A new inversion-based algorithm for retrieval of over-water rain rate from SSM/I multichannel imagery. Preprints, Seventh Conf. on Satellite Meteorology and Oceanography, Monterey, CA, Amer. Meteor. Soc., 144–147.

  • Puri, K., and N. E. Davidson, 1992: The use of infrared satellite cloud imagery data as proxy data for moisture and diabatic heating in data assimilation. Mon. Wea. Rev.,120, 2329–2341.

  • Rasmussen, E. M., and P. A. Arkin, 1993: A global view of large-scale precipitation variability. J. Climate,6, 1495–1522.

  • Richards, F., and P. Arkin, 1981: On the relationship between satellite-observed cloud cover and precipitation. Mon. Wea. Rev.,109, 1081–1093.

  • Rosenfeld, D., and G. Gutman, 1994: Retrieving microphysical properties near the tops of potential rain clouds by multispectral analysis of AVHRR data. Atmos. Res.,34, 259–283.

  • Shinoda, T., and R. Lukas, 1995: Lagrangian mixed layer modeling of the western equatorial Pacific. J. Geophys. Res.,100, 2523–2541.

  • Short, D., P. Kucera, B. Ferrier, J. Gerlach, S. Rutledge, and O. Thiele, 1997: Shipboard radar rainfall patterns within the TOGA COARE IFA. Bull. Amer. Meteor. Soc.,78, 2817–2836.

  • Smith, E., X. Xiang, A. Mugnai, and G. I. Tripoli, 1994: Design of an inversion-based precipitation profile retrieval algorithm using an explicit cloud model for initial guess microphysics. Meteor. Atmos. Phys.,54, 53–78.

  • ——, J. Lamm, R. Adler, J. Alishouse, K. Aonashi, E. Barrett, P. Bauer, W. Berg, A. Chang, R. Ferraro, J. Ferriday, S. Goodman, N. Grody, C. Kidd, C. Kummerow, G. Liu, F. Marzano, A. Mugnai, W. Olson, G. Petty, A. Shibata, R. Spencer, F. Wentz, and T. Wilheit, 1998: Results of WetNet PIP-2 Project. J. Atmos. Sci.,55, 1483–1536.

  • WCRP, 1995: Report of the eighth session of the WCRP/GEWEX working group on data management for the Global Precipitation Climatology Project (GPCP), 28–30 September 1994, Offenbach, Germany. World Meteorological Organization, 21 pp. [Available from World Climate Research Programme, C. P. 2300, CH-1211 Geneva 2, Switzerland.].

  • Weng, F., R. R. Ferraro, and N. C. Grody, 1994: Global precipitation estimations using Defense Meteorological Satellite Program F10 and F11 special sensor microwave imager data. J. Geophys. Res.,99, 14493–14502.

  • Wilheit, T., A. T. C. Chang, and L. S. Chiu, 1991: Retrieval of monthly rainfall indices from microwave radiometric measurements using probability distribution functions. J. Atmos. Oceanic Technol.,8, 118–136.

  • ——, R. Adler, S. Avery, E. Barrett, P. Bauer, W. Berg, A. Chang, J. Ferriday, N. Grody, S. Goodman, C. Kidd, D. Kniveton, C. Kummerow, A. Mugnai, W. Olson, G. Petty, A. Shibata, E. Smith, and R. Spencer, 1994: Algorithms for the retrieval of rainfall from passive microwave measurements. Remote Sens. Rev.,11, 163–194.

  • Xie, P., and P. A. Arkin, 1995: An intercomparison of gauge observations and satellite estimates of monthly precipitation. J. Appl. Meteor.,34, 1143–1160.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 482 172 26
PDF Downloads 168 34 1