• Anderson, J. L., 1996: A method for producing and evaluating probabilistic forecasts from ensemble model integrations. J. Climate, 9 , 15181530.

    • Search Google Scholar
    • Export Citation
  • Black, T. L., 1994: The new NMC mesoscale Eta Model: Description and forecast examples. Wea. Forecasting, 9 , 265284.

  • Brooks, H. E., M. S. Tracton, D. J. Stensrud, G. DiMego, and Z. Toth, 1995: Short-range ensemble forecasting: Report from a workshop, 25–27 July 1994. Bull. Amer. Meteor. Soc., 76 , 16171624.

    • Search Google Scholar
    • Export Citation
  • Buizza, R., 2001: Accuracy and potential economic value of categorical and probabilistic forecasts of discrete events. Mon. Wea. Rev., 129 , 23292345.

    • Search Google Scholar
    • Export Citation
  • Buizza, R., A. Hollingsworth, F. Lalaurette, and A. Ghelli, 1999: Probabilistic predictions of precipitation using the ECMWF ensemble prediction system. Wea. Forecasting, 14 , 168189.

    • Search Google Scholar
    • Export Citation
  • Charba, J. P., D. W. Reynolds, B. E. McDonald, and G. M. Carter, 2003: Comparative verification of recent quantitative precipitation forecasts in the National Weather Service: A simple approach for scoring forecast accuracy. Wea. Forecasting, 18 , 161183.

    • Search Google Scholar
    • Export Citation
  • Daly, C., R. P. Neilson, and D. L. Phillips, 1994: A statistical–topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33 , 140158.

    • Search Google Scholar
    • Export Citation
  • Droegemeier, K. K., and Coauthors, 2000: Hydrological aspects of weather prediction and flood warnings: Report of the ninth prospectus development team of the U.S. weather research program. Bull. Amer. Meteor. Soc., 81 , 26652680.

    • Search Google Scholar
    • Export Citation
  • Du, J., and M. S. Tracton, 1999: Impact of lateral boundary conditions on regional-model ensemble prediction. Research activities in atmospheric and oceanic modelling. H. Ritchie, Ed., Rep. 28, CAS/JSC Working Group Numerical Experimentation WMO/TD-No. 942, 6.7–6.8.

  • Du, J., and M. S. Tracton, 2001: Implementation of a real-time short-range ensemble forecasting system at NCEP: An update. Preprints,. Ninth Conf. on Mesoscale Processes, Ft. Lauderdale, FL, Amer. Meteor. Soc., 355–356.

    • Search Google Scholar
    • Export Citation
  • Du, J., S. Mullen, and F. Sanders, 1997: Short-range ensemble forecasting of quantitative precipitation. Mon. Wea. Rev., 125 , 24272459.

    • Search Google Scholar
    • Export Citation
  • Eckel, F. A., and M. K. Walters, 1998: Calibrated probabilistic quantitative pecipitation forecasts based on the MRF ensemble. Wea. Forecasting, 13 , 11321147.

    • Search Google Scholar
    • Export Citation
  • Epstein, E. S., 1969: Stochastic dynamic prediction. Tellus, 21 , 739759.

  • Fritsch, J. M., and Coauthors, 1998: Quantitative precipitation forecasting: Report of the eighth prospectus development team, U.S. weather research program. Bull. Amer. Meteor. Soc., 79 , 285299.

    • Search Google Scholar
    • Export Citation
  • Fulton, R. A., J. P. Breidenbach, D-J. Seo, D. A. Miller, and T. O’Bannon, 1998: The WSR-88D rainfall algorithm. Wea. Forecasting, 13 , 377395.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., 1999: Hypothesis tests for evaluating numerical precipitation forecasts. Wea. Forecasting, 14 , 155167.

  • Hamill, T. M., 2001: Interpretation of rank histograms for verifying ensemble forecasts. Mon. Wea. Rev., 129 , 550560.

  • Hamill, T. M., and S. J. Colucci, 1998: Evaluation of Eta–RSM ensemble probabilistic precipitation forecasts. Mon. Wea. Rev., 126 , 711724.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., S. L. Mullen, C. Snyder, Z. Toth, and D. P. Baumhefner, 2000: Ensemble forecasting in the short to medium range: Report from a workshop. Bull. Amer. Meteor. Soc., 81 , 26532664.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., J. S. Whitaker, and C. Snyder, 2001: Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129 , 27762790.

    • Search Google Scholar
    • Export Citation
  • Higgins, R. W., W. Shi, E. Yarosh, and R. Joyce, 2003: Improved United States Precipitation Quality Control System and Analysis. NCEP/CPC Atlas 7, 47 pp. [Available online at http://www.cpc.ncep.noaa.gov/research_papers/ncep_cpc_atlas/7/index.html.].

    • Search Google Scholar
    • Export Citation
  • Hoffman, R. N., and E. Kalnay, 1983: Lagged average forecasting, an alternative to Monte Carlo forecasting. Tellus, 35A , 100118.

  • Hong, S-Y., and A. Leetmaa, 1999: An evaluation of the NCEP RSM for regional climate modeling. J. Climate, 12 , 592609.

  • Jolliffe, I. T., and D. B. Stephenson, 2003: Forecast Verification. : A Practitioner’s Guide in Atmospheric Science. Wiley and Sons, 240 pp.

    • Search Google Scholar
    • Export Citation
  • Juang, H-M. H., 2000: The NCEP mesoscale spectral model: A revised version of the nonhydrostatic regional spectral model. Mon. Wea. Rev., 128 , 23292362.

    • Search Google Scholar
    • Export Citation
  • Juang, H-M. H., and M. Kanamitsu, 1994: The NMC nested regional spectral model. Mon. Wea. Rev., 122 , 326.

  • Juang, H-M. H., S-Y. Hong, and M. Kanamitsu, 1997: The NCEP regional spectral model: An update. Bull. Amer. Meteor. Soc., 78 , 21252143.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., 2003: Atmospheric Modeling, Data Assimilation and Predictability. Cambridge University Press, 341 pp.

  • Kanamitsu, M., 1989: Description of the NMC global data assimilation and forecast system. Wea. Forecasting, 4 , 335342.

  • Kelsch, M., 2002: COMET flash flood cases: Summary of characteristics. Preprints,. 16th Conf. on Hydrology, Orlando, FL, Amer. Meteor. Soc., CD-ROM, 2.1.

    • Search Google Scholar
    • Export Citation
  • Kelsch, M., 2004: A review of some significant urban floods across the United States in 2003. Preprints,. 2004 AMS Annual Weather Review Preliminary Program, Seattle, WA, Amer. Meteor. Soc., 2–3.

    • Search Google Scholar
    • Export Citation
  • Leith, C. E., 1974: Theoretical skill of Monte Carlo forecasts. Mon. Wea. Rev., 102 , 409418.

  • Maddox, R. A., J. Zhang, J. J. Gourley, and K. W. Howard, 2002: Weather radar coverage over the contiguous United States. Wea. Forecasting, 17 , 927934.

    • Search Google Scholar
    • Export Citation
  • Molteni, F., R. Buizza, T. N. Palmer, and T. Petroliagis, 1996: The ECMWF ensemble prediction system: Methodology and validation. Quart. J. Roy. Meteor. Soc., 122 , 73119.

    • Search Google Scholar
    • Export Citation
  • Mullen, S. L., and R. Buizza, 2001: Quantitative precipitation forecasts over the United States by the ECMWF ensemble prediction system. Mon. Wea. Rev., 129 , 638663.

    • Search Google Scholar
    • Export Citation
  • Mullen, S. L., J. Du, and F. Sanders, 1999: The dependence of ensemble dispersion on analysis–forecast systems: Implications to short-range ensemble forecasting of precipitation. Mon. Wea. Rev., 127 , 16741686.

    • Search Google Scholar
    • Export Citation
  • Mureau, R., F. Molteni, and T. N. Palmer, 1993: Ensemble prediction using dynamically-conditioned perturbations. Quart. J. Roy. Meteor. Soc., 119 , 299323.

    • Search Google Scholar
    • Export Citation
  • Murphy, A. H., 1991: Forecast verification: Its complexity and dimensionality. Mon. Wea. Rev., 119 , 15901601.

  • Murphy, A. H., and R. L. Winkler, 1987: A general framework for forecast verification. Mon. Wea. Rev., 115 , 13301338.

  • Palmer, P. L., 1988: The SCS snow survey water supply forecasting program: Current operations and future directions. Proc. 56th Annual Western Snow Conf., Kalispell, MT, Western Snow Conference, 43–51.

  • Palmer, T. N., F. Molteni, R. Mureau, R. Buizza, P. Chapelet, and J. Tribbia, 1993: Ensemble prediction. Proc. ECMWF Seminar on Validation of Models over Europe, Vol. 1, ECMWF, Shinfield Park, Reading, UK, 21–66.

    • Search Google Scholar
    • Export Citation
  • Pielke Jr, R. A., and M. W. Downton, 2000: Precipitation and damaging floods: Trends in the United States, 1932–97. J. Climate, 13 , 36253637.

    • Search Google Scholar
    • Export Citation
  • Reynolds, D., 2003: Value-added quantitative precipitation forecasts: How valuable is the forecaster? Bull. Amer. Meteor. Soc., 84 , 876878.

    • Search Google Scholar
    • Export Citation
  • Richardson, D. S., 2000: Skill and economic value of the ECMWF ensemble prediction system. Quart. J. Roy. Meteor. Soc., 126 , 649668.

  • Rogers, E., D. G. Deaven, and G. S. Dimego, 1995: The regional analysis system for the operational “early” Eta Model: Original 80-km configuration and recent changes. Wea. Forecasting, 10 , 810825.

    • Search Google Scholar
    • Export Citation
  • Sanders, F., 1986: Trends in skill of Boston forecasts made at MIT, 1966–84. Bull. Amer. Meteor. Soc., 67 , 170176.

  • Serreze, M., M. Clark, R. Armstrong, D. McGinnis, and R. Pulwarty, 1999: Characteristics of western U.S. snowpack telemetry (SNOTEL) data. Water Resour. Res., 35 , 21452160.

    • Search Google Scholar
    • Export Citation
  • Stanski, H. R., L. J. Wilson, and W. R. Burrows, 1989: Survey of common verification methods in meteorology. World Meteorological Organization, World Weather Watch Rep. 8, Tech. Doc. 358, 114 PP.

  • Stensrud, D. J., H. E. Brooks, J. Du, M. S. Tracton, and E. Rogers, 1999: Using ensembles for short-range forecasting. Mon. Wea. Rev., 127 , 433446.

    • Search Google Scholar
    • Export Citation
  • Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of perturbations. Bull. Amer. Meteor. Soc., 74 , 23172330.

  • Toth, Z., and E. Kalnay, 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev., 125 , 32973319.

  • Toth, Z., E. Kalnay, M. S. Tracton, R. Wobus, and J. Irwin, 1997: A synoptic evaluation of the NCEP ensemble. Wea. Forecasting, 12 , 140153.

    • Search Google Scholar
    • Export Citation
  • Toth, Z., Y. Zhu, I. Szunyogh, M. Iredell, and R. Wobus, 2002: Does increased model resolution enhance predictability? Preprints, Symp. on Observations, Data Assimilation, and Probabilistic Prediction, Orlando, FL, Amer. Meteor. Soc., CD-ROM, J1.9.

    • Search Google Scholar
    • Export Citation
  • Tracton, M. S., and E. Kalnay, 1993: Operational ensemble prediction at the National Meteorological Center: Practical aspects. Wea. Forecasting, 8 , 379400.

    • Search Google Scholar
    • Export Citation
  • Wallace, J. M., 1975: Diurnal variations in precipitation and thunderstorm frequency over the conterminous United States. Mon. Wea. Rev., 103 , 406419.

    • Search Google Scholar
    • Export Citation
  • Wandishin, M. S., S. L. Mullen, D. J. Stensrud, and H. E. Brooks, 2001: Evaluation of a short-range multimodel ensemble system. Mon. Wea. Rev., 129 , 729747.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. International Geophysics Series, Vol. 59, Academic Press, 467 pp.

    • Search Google Scholar
    • Export Citation
  • Wilson, L. J., 2000: Comments on “Probabilistic predictions of precipitation using the ECMWF ensemble prediction system.”. Wea. Forecasting, 15 , 361364.

    • Search Google Scholar
    • Export Citation
  • Young, C. B., A. A. Bradley, W. F. Krajewski, A. Kruger, and M. L. Morrissey, 2000: Evaluating NEXRAD multisensor precipitation estimates for operational hydrologic forecasting. J. Hydrometeor., 1 , 241254.

    • Search Google Scholar
    • Export Citation
  • Zhu, Y., Z. Toth, R. Wobus, D. Richardson, and K. Mylne, 2002: The economic value of ensemble-based weather forecasts. Bull. Amer. Meteor. Soc., 83 , 7383.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 5 5 5
PDF Downloads 0 0 0

Verification of Probabilistic Quantitative Precipitation Forecasts over the Southwest United States during Winter 2002/03 by the RSM Ensemble System

View More View Less
  • 1 Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, California
  • | 2 Department of Atmospheric Sciences, The University of Arizona, Tucson, Arizona
  • | 3 Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, California
  • | 4 NWS/NOAA/NCEP/Environmental Modeling Center, Washington, D.C
Restricted access

Abstract

The National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) is used to generate ensemble forecasts over the southwest United States during the 151 days of 1 November 2002 to 31 March 2003. RSM forecasts to 24 h on a 12-km grid are produced from 0000 and 1200 UTC initial conditions. Eleven ensemble members are run each forecast cycle from the NCEP Global Forecast System (GFS) ensemble analyses (one control and five pairs of bred modes) and forecast lateral boundary conditions. The model domain covers two NOAA River Forecast Centers: the California Nevada River Forecast Center (CNRFC) and the Colorado Basin River Forecast Center (CBRFC). Ensemble performance is evaluated for probabilistic forecasts of 24-h accumulated precipitation in terms of several accuracy and skill measures. Differences among several NCEP precipitation analyses are assessed along with their impact on model verification, with NCEP stage IV blended analyses selected to represent “truth.”

Forecast quality and potential value are found to depend strongly on the verification dataset, geographic region, and precipitation threshold. In general, the RSM forecasts are skillful over the CNRFC region for thresholds between 1 and 50 mm but are unskillful over the CBRFC region. The model exhibits a wet bias for all thresholds that is larger over Nevada and the CBRFC region than over California. Mitigation of such biases over the Southwest will pose serious challenges to the modeling community in view of the uncertainties inherent in verifying analyses.

Corresponding author address: Huiling Yuan, Department of Civil and Environmental Engineering, University of California, Irvine, E-4130 Engineering Gateway, Irvine, CA 92697-2175. Email: yhl@hwr.arizona.edu

Abstract

The National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) is used to generate ensemble forecasts over the southwest United States during the 151 days of 1 November 2002 to 31 March 2003. RSM forecasts to 24 h on a 12-km grid are produced from 0000 and 1200 UTC initial conditions. Eleven ensemble members are run each forecast cycle from the NCEP Global Forecast System (GFS) ensemble analyses (one control and five pairs of bred modes) and forecast lateral boundary conditions. The model domain covers two NOAA River Forecast Centers: the California Nevada River Forecast Center (CNRFC) and the Colorado Basin River Forecast Center (CBRFC). Ensemble performance is evaluated for probabilistic forecasts of 24-h accumulated precipitation in terms of several accuracy and skill measures. Differences among several NCEP precipitation analyses are assessed along with their impact on model verification, with NCEP stage IV blended analyses selected to represent “truth.”

Forecast quality and potential value are found to depend strongly on the verification dataset, geographic region, and precipitation threshold. In general, the RSM forecasts are skillful over the CNRFC region for thresholds between 1 and 50 mm but are unskillful over the CBRFC region. The model exhibits a wet bias for all thresholds that is larger over Nevada and the CBRFC region than over California. Mitigation of such biases over the Southwest will pose serious challenges to the modeling community in view of the uncertainties inherent in verifying analyses.

Corresponding author address: Huiling Yuan, Department of Civil and Environmental Engineering, University of California, Irvine, E-4130 Engineering Gateway, Irvine, CA 92697-2175. Email: yhl@hwr.arizona.edu

Save