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Journal of Applied Meteorology and Climatology

  • Atlas, D., D. Rosenfeld, and D. B. Wolff, 1990: Climatologically tuned reflectivity–rain rate relations and links to area–time integrals. J. Appl. Meteor.,29, 1120–1135.

  • ——, P. Willis, and F. Marks, 1995: The effects of convective updrafts and downdrafts on reflectivity–rain rate relations and water budgets. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 19–22.

  • Austin, P. M., 1987: Relation between measured radar reflectivity and surface rainfall. Mon. Wea. Rev.,115, 1053–1070.

  • Baer, V. E., 1991: The transition from the present radar dissemination system to the NEXRAD Information Dissemination Service (NIDS). Bull. Amer. Meteor. Soc.,72, 29–33.

  • Battan, L. J., 1973: Radar Observations of the Atmosphere. University of Chicago Press, 324 pp.

  • ——, 1976: Vertical air motions and the Z–R relation. J. Meteor.,15, 1120–1121.

  • Blanchard, D. O., and R. E. López, 1985: Spatial patterns of convection in south Florida. Mon. Wea. Rev.,113, 1282–1299.

  • Burpee, R. W., and L. N. Lahiff, 1984: Area-average rainfall variations on sea-breeze days in south Florida. Mon. Wea. Rev.,112, 520–534.

  • Byers, H. R., and H. R. Rodebush, 1948: Causes of thunderstorms of the Florida Peninsula. J. Meteor.,5, 275–280.

  • Cain, D. E., and P. L. Smith Jr., 1977: A sequential analysis strategy for adjusting radar rainfall estimates on the basis of raingage data in real time. Preprints, Second Conf. on Hydrometeorology, Toronto, ON, Canada, Amer. Meteor. Soc., 280–285.

  • Calheiros, R. V., and I. Zawadzki, 1987: Reflectivity–rain rate relationships for radar hydrology in Brazil. J. Climate Appl. Meteor.,26, 118–132.

  • Cheng, C.-P., and R. A. Houze Jr., 1979: The distribution of convective and mesoscale precipitation in GATE radar echo patterns. Mon. Wea. Rev.,107, 1370–1381.

  • Chong, M., and D. Hauser, 1989: A tropical squall line observed during the COPT 81 experiment in West Africa. Part II: Water budget. Mon. Wea. Rev.,117, 728–744.

  • Churchill, D. D., and R. A. Houze Jr., 1984: Development and structure of winter monsoon cloud clusters on 10 December 1978. J. Atmos. Sci.,41, 933–960.

  • Ciach, G. J., W. F. Krajewski, E. N. Anagnostou, M. L. Baeck, J. A. Smith, J. R. McCollum, and A. Kruger, 1997: Radar rainfall estimation for ground validation studies of the Tropical Rainfall Measuring Mission. J. Appl. Meteor., in press.

  • Court, A., and J. F. Griffiths, 1986: Thunderstorm climatology. Thunderstorm: A Social and Technological Documentary, E. Kessler, Ed., Vol. II, University of Oklahoma Press, 11–52.

  • Crum, T. D., and R. L. Alberty, 1993: The WSR-88D and the WSR-88D Operational Support Facility. Bull. Amer. Meteor. Soc.,74, 1669–1687.

  • ——, ——, and D. W. Burgess, 1993: Recording, archiving, and using WSR-88D data. Bull. Amer. Meteor. Soc.,74, 645–652.

  • DeMaria, M., 1985: Linear response of a stratified tropical atmosphere to convective forcing. J. Atmos. Sci.,42, 1944–1959.

  • Drosdowsky, W., 1984: Structure of a northern Australian squall line system. Aust. Meteor. Mag.,32, 177–183.

  • ——, 1996: Variability of the Australian summer monsoon at Darwin: 1957–1992. J. Climate,9, 85–96.

  • Gage, K. S., C. R. Williams, and W. L. Ecklund, 1994: UHF wind profilers: A new tool for diagnosing tropical convective cloud systems. Bull. Amer. Meteor. Soc.,75, 2289–2294.

  • Gamache, J. F., and R. A. Houze Jr., 1983: Water budget of a mesoscale convective system in the Tropics. J. Atmos. Sci.,40, 1835–1850.

  • Hartmann, D. L., H. H. Hendon, and R. A. Houze Jr., 1984: Some implications of the mesoscale circulations in tropical cloud clusters for large-scale dynamics and climate. J. Atmos. Sci.,41, 113–121.

  • Heiss, W. H., D. L. McGrew, and D. Sirmans, 1990: NEXRAD: Next Generation Weather Radar (WSR-88D). Microwave J.,33, 79–98.

  • Hitchfeld, W. F., and J. Bordan, 1954: Errors inherent in the radar measurement of rainfall at attenuating wavelengths. J. Meteor.,11, 58–67.

  • Holland, G. J., 1986: Interannual variability of the Australian summer monsoon at Darwin: 1952–82. Mon. Wea. Rev.,114, 594–604.

  • Houghton, H. G., 1968: On precipitation mechanisms and their artificial modification. J. Appl. Meteor.,7, 851–859.

  • Houze, R. A., Jr., 1977: Structure and dynamics of a tropical squall-line system. Mon. Wea. Rev.,105, 1540–1567.

  • ——, 1982: Cloud clusters and large-scale vertical motions in the Tropics. J. Meteor. Soc. Japan,60, 396–410.

  • ——, 1989: Observed structure of mesoscale convective systems and implications for large-scale heating. Quart. J. Roy. Meteor. Soc.,115, 425–461.

  • ——, 1993: Cloud Dynamics. Academic Press, 573 pp.

  • ——, and A. K. Betts, 1981: Convection inGATE. Rev. Geophys. Space Phys.,19, 541–576.

  • ——, and E. N. Rappaport, 1984: Air motions and precipitation structure of an early summer squall line over the eastern tropical Atlantic. J. Atmos. Sci.,41, 553–574.

  • Johnson, R. H., and R. A. Houze Jr., 1987: Precipitating cloud systems of the Asian monsoon. Monsoon Meteorology, C. P. Chang and T. N. Krishnamurti, Eds., Oxford University Press, 298–353.

  • Joss, J., and A. Waldvogel, 1970: A method to improve the accuracy of radar-measured amounts of precipitation. Preprints, 14th Radar Meteorology Conf., Tucson, AZ, Amer. Meteor. Soc., 237–238.

  • ——, and ——, 1990: Precipitation measurements and hydrology. Radar in Meteorology, D. Atlas, Ed., Amer. Meteor. Soc., 577–606.

  • Keenan, T. D., and R. E. Carbone, 1992: A preliminary morphology of precipitation systems in tropical northern Australia. Quart. J. Roy. Meteor. Soc.,118, 283–326.

  • ——, G. J. Holland, M. J. Manton, and J. Simpson, 1988: TRMM ground truth in a monsoon environment: Darwin, Australia. Aust. Meteor. Mag.,36, 81–90.

  • ——, B. R. Morton, M. J. Manton, and G. J. Holland, 1989: The Island Thunderstorm Experiment (ITEX)—A study of tropical thunderstorms in the maritime continent. Bull. Amer. Meteor. Soc.,70, 152–159.

  • ——, ——, X. S. Zhang, and K. Nyguen, 1990: Some characteristics of thunderstorms over Bathurst and Melville Islands near Darwin, Australia. Quart. J. Roy. Meteor. Soc.,116, 1153–1172.

  • Klazura, G. E., 1981: Differences between some radar-rainfall estimation procedures in a high rain rate gradient storm. J. Appl. Meteor.,20, 1376–1380.

  • Koistinen, J., and T. Puhakka, 1986: Can we calibrate radar with raingauges? Geophysica,22, 119–129.

  • Krajewski, W. F., 1987: Cokriging radar-rainfall and rain gage data. J. Geophys. Res.,92, 9571–9580.

  • ——, and P. R. Ahnert, 1986: Near real-time tests of a multivariate analysis system. Preprints, 23rd Conf. on Radar Meteorology and Conf. on Cloud Physics, Snowmass, CO, Amer. Meteor. Soc., JP66–JP69.

  • Lau, K. M., and L. Peng, 1987: Origin of the low-frequency (intraseasonal) oscillation in the tropical atmosphere. Part I: Basic theory. J. Atmos. Sci.,44, 950–972.

  • Leary, C. A., 1984: Precipitation structure of the cloud clusters in a tropical easterly wave. Mon. Wea. Rev.,112, 313–325.

  • Mapes, B. E., and R. A. Houze Jr., 1992: An integrated view of the 1987 Australian monsoon and its mesoscale convective systems. Part I: Horizontal structure. Quart. J. Roy. Meteor. Soc.,118, 927–963.

  • ——, and ——, 1993: An integrated view of the 1987 Australian monsoon and its mesoscale convective systems. Part II: Vertical structure. Quart. J. Roy. Meteor. Soc.,119, 733–754.

  • ——, and ——, 1995: Diabatic divergence profiles in western Pacific mesoscale convective systems. J. Atmos. Sci.,52, 1807–1828.

  • Marks, F. D., Jr., 1985: Evolution and structure of precipitation in hurricane Allen (1980). Mon. Wea. Rev.,113, 909–930.

  • ——, and R. A. Houze Jr., 1987: Inner core structure of hurricane Alicia from airborne Doppler radar observations. J. Atmos. Sci.,44, 1296–1317.

  • Marshall, J. S., and W. McK. Palmer, 1948: The distribution of raindrops with size. J. Meteor.,5, 165–166.

  • Miller, J. R., 1972: A climatological Z–R relationship for convective storms in the northern Great Plains. Preprints, 15th Radar Meteorology Conf., Champaign–Urbana, IL, Amer. Meteor. Soc., 153–154.

  • Neumann, C. J., 1971: Thunderstorm forecasting at Cape Kennedy, Florida, utilizing multiple regression techniques. NOAA Tech. Memo. NWS SOS-8, 44 pp. [Available from U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1325 East–West Highway, Silver Springs, MD 20910-3282.].

  • Rogers, R. R., 1979: A Short Course in Cloud Physics. 2d ed. Pergamon Press, 235 pp.

  • Rosenfeld, D., 1995: Comparison of WPMM vs. regression methods for evaluating Z–R relationships. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 23–25.

  • ——, D. B. Wolff, and D. Atlas, 1993: General probability-matched relations between radar reflectivity and rain rate. J. Appl. Meteor.,32, 50–72.

  • ——, ——, and E. Amitai, 1994: The window probability matching method for rainfall measurements with radar. J. Appl. Meteor.,33, 682–693.

  • Seliga, T. A., and V. N. Bringi, 1976: Potential use of radar differential reflectivity measurements at orthogonal polarizations for measuring precipitation. J. Appl. Meteor.,15, 69–76.

  • Short, D. A., T. Kozu, and K. Nakamura, 1990: Rainrate and raindrop size distribution observations in Darwin Australia. Proc. URSI Commission F Open Symp. on Regional Factors in Predicting Radiowave Attenuation due to Rain, Rio de Janeiro, The Rutherford Appleton Laboratory and Empresa Brasileira de Telecomunicaoes, Brazil, 35–40.

  • ——, D. B. Wolff, D. Rosenfeld, and D. Atlas, 1993: A study of the threshold method utilizing raingage data. J. Appl. Meteor.,32, 1379–1387.

  • Simpson, J., R. F. Adler, and G. R. North, 1988: A proposed Tropical Rainfall Measuring Mission (TRMM) satellite. Bull. Amer. Meteor. Soc.,69, 278–295.

  • ——, T. D. Keenan, B. Ferrier, R. H. Simpson, and G. J. Holland, 1993: Cumulus mergers in the maritime continent region. Meteor. Atmos. Phys.,51, 73–99.

  • Smith, J. A., and W. F. Krajewski, 1993: A modeling study of rainfall rate–reflectivity relationships. Water Resour. Res.,29, 2505–2514.

  • Smith, P. L., Jr., 1990: Precipitation measurements and hydrology: Panel report. Radar in Meteorology, D. Atlas, Ed., Amer. Meteor. Soc., 607–618.

  • ——, and D. E. Cain, 1983: Use of sequential analysis methods in adjusting radar rainfall estimates on the basis of raingauge data. Rep. 83-2, 84 pp. [Available from Institute of Atmospheric Sciences, South Dakota School of Mines and Technology, 501 E. St. Joseph St., Rapid City, SD 57701-3995.].

  • ——, ——, and A. S. Dennis, 1975: Derivation of an R–Z relationship by computer optimization and its use in measuring daily areal rainfall. Preprints, 16th Radar Meteorology Conf., Houston, TX, Amer. Meteor. Soc., 461–466.

  • Steiner, M., 1996: Uncertainties of estimates of monthly areal rainfall for temporally sparse remote observations. Water Resour. Res.,32, 373–388.

  • ——, R. A. Houze Jr., and S. E. Yuter, 1995: Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteor.,34, 1978–2007.

  • Tao, W.-K., S. Lang, J. Simpson, and R. Adler, 1993: Retrieval algorithms for estimating the vertical profiles of latent heat release: Their applications for TRMM. J. Meteor. Soc. Japan,71, 685–700.

  • Telesetsky, W., 1995: Current status and issues of the Weather Surveillance Radar—1988 Doppler program. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., xxxviii–xlii.

  • Tokay, A., and D. A. Short, 1996: Evidence from tropical raindrop spectra of the origin of rain from stratiform versus convective clouds. J. Appl. Meteor.,35, 355–371.

  • Ulbrich, C. W., 1983: Natural variations in the analytical form of the raindrop size distribution. J. Climate Appl. Meteor.,22, 1764–1775.

  • Waldvogel, A., 1975a: Reply. J. Atmos. Sci.,32, 653–654.

  • ——, 1975b: Tropfenspektren, Niederschlagstyp und Z–R Beziehungen. Meteor. Rundsch.,28, 33–36.

  • Webster, P. J., and R. Lukas, 1992: TOGA COARE: The Coupled Ocean–Atmosphere Response Experiment. Bull. Amer. Meteor. Soc.,73, 1377–1416.

  • Wei, T., and R. A. Houze Jr., 1987: The GATE squall line of 9–10 August 1974. Adv. Atmos. Sci.,4, 85–92.

  • Wilson, J. W., and E. A. Brandes, 1979: Radar measurement of rainfall—A summary. Bull. Amer. Meteor. Soc.,60, 1048–1058.

  • Yuter, S. E., and R. A. Houze Jr., 1997: Measurements of raindrop size distribution over the Pacific warm pool and implications for Z–R relations. J. Appl. Meteor., in press.

  • Zawadzki, I., 1984: Factors affecting the precision of radar measurements of rain. Preprints, 22nd Conf. on Radar Meteorology, Zurich, Switzerland, Amer. Meteor. Soc., 251–256.

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Sensitivity of the Estimated Monthly Convective Rain Fraction to the Choice of Z–R Relation

Matthias SteinerDepartment of Atmospheric Sciences, University of Washington, Seattle, Washington

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Robert A. Houze Jr.Department of Atmospheric Sciences, University of Washington, Seattle, Washington

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Print Publication:
01 May 1997
DOI:
https://doi.org/10.1175/1520-0450(1997)036<0452:SOTEMC>2.0.CO;2
Page(s):
452–462
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Abstract

This study investigates the sensitivity of the estimated monthly convective rain fraction—that is, the percentage of the areal rain accumulation contributed by precipitation identified as convective—to variations of the Z–R parameters used in radar-based rainfall estimation. Accurate knowledge of the fractions of precipitation that are convective and stratiform is important for climatological studies estimating the heating of the atmosphere. Extensive datasets from two climatologically different precipitation regimes, Darwin, Australia, and Melbourne, Florida, are used. The potential uncertainty of using (i) an arbitrary choice of the power factor b and (ii) either single or multiple Z–R relations (stratified by precipitation type) for converting radar reflectivity to rain rate is investigated quantitatively.

The analyses reveal that estimates of the monthly convective rain fraction are sensitive to the choice of Z–R parameters. A maximum sensitivity is found for precipitation regimes with an approximately equal mix of rainfall from convective and stratiform precipitation systems. For example, estimates of the convective rain fraction for monsoonal rainfall at Darwin may range from 30% to 80%, solely depending on the choice of Z–R parameters, even though all of these Z–R relations are tuned to produce the same total rainfall. In contrast, for the highly convective, sea-breeze-triggered, multicellular storms around Melbourne, the estimates of the convective rain fraction may range from 80% to 100%.

Different approaches to how the appropriate parameters of the Z–R relation(s) may be obtained are discussed. Varying the Z–R parameters to maximize the correlation of the radar-estimated monthly rainfall at the gauge sites and the rain gauge accumulations does not reveal enough sensitivity to make any choice significantly better than a single Z–R relation for both convective and stratiform rain. Multiple Z–R relations may be justified, but apparently not on the basis of a convective–stratiform separation.

Corresponding author address: Dr. Matthias Steiner, Water Resources Program, Dept. of Civil Engineering and Operations Research, Princeton University, Princeton, NJ 08544.

msteiner@radap.princeton.edu

Abstract

This study investigates the sensitivity of the estimated monthly convective rain fraction—that is, the percentage of the areal rain accumulation contributed by precipitation identified as convective—to variations of the Z–R parameters used in radar-based rainfall estimation. Accurate knowledge of the fractions of precipitation that are convective and stratiform is important for climatological studies estimating the heating of the atmosphere. Extensive datasets from two climatologically different precipitation regimes, Darwin, Australia, and Melbourne, Florida, are used. The potential uncertainty of using (i) an arbitrary choice of the power factor b and (ii) either single or multiple Z–R relations (stratified by precipitation type) for converting radar reflectivity to rain rate is investigated quantitatively.

The analyses reveal that estimates of the monthly convective rain fraction are sensitive to the choice of Z–R parameters. A maximum sensitivity is found for precipitation regimes with an approximately equal mix of rainfall from convective and stratiform precipitation systems. For example, estimates of the convective rain fraction for monsoonal rainfall at Darwin may range from 30% to 80%, solely depending on the choice of Z–R parameters, even though all of these Z–R relations are tuned to produce the same total rainfall. In contrast, for the highly convective, sea-breeze-triggered, multicellular storms around Melbourne, the estimates of the convective rain fraction may range from 80% to 100%.

Different approaches to how the appropriate parameters of the Z–R relation(s) may be obtained are discussed. Varying the Z–R parameters to maximize the correlation of the radar-estimated monthly rainfall at the gauge sites and the rain gauge accumulations does not reveal enough sensitivity to make any choice significantly better than a single Z–R relation for both convective and stratiform rain. Multiple Z–R relations may be justified, but apparently not on the basis of a convective–stratiform separation.

Corresponding author address: Dr. Matthias Steiner, Water Resources Program, Dept. of Civil Engineering and Operations Research, Princeton University, Princeton, NJ 08544.

msteiner@radap.princeton.edu

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