Advances in Atmospheric Sciences

, Volume 30, Issue 1, pp 15–28 | Cite as

A regional ensemble forecast system for stratiform precipitation events in the Northern China Region. Part II: Seasonal evaluation for summer 2010

  • Jiangshan Zhu (朱江山)
  • Fanyou Kong (孔凡铀)
  • Hengchi Lei (雷恒池)
Article

Abstract

In this study, the Institute of Atmospheric Physics, Chinese Academy of Sciences — regional ensemble forecast system (IAP-REFS) described in Part I was further validated through a 65-day experiment using the summer season of 2010. The verification results show that IAP-REFS is skillful for quantitative precipitation forecasts (QPF) and probabilistic QPF, but it has a systematic bias in forecasting near-surface variables. Applying a 7-day running mean bias correction to the forecasts of near-surface variables remarkably improved the reliability of the forecasts. In this study, the perturbation extraction and inflation method (proposed with the single case study in Part I) was further applied to the full season with different inflation factors. This method increased the ensemble spread and improved the accuracy of forecasts of precipitation and near-surface variables. The seasonal mean profiles of the IAP-REFS ensemble indicate good spread among ensemble members and some model biases at certain vertical levels.

Key words

short-range ensemble forecast rain enhancement operation probabilistic forecast 

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References

  1. Anderson, J. L., 1996: A Method for Producing and Evaluating Probabilistic Forecasts from Ensemble Model Integrations. J. Climate, 9(7), 1518–1530.CrossRefGoogle Scholar
  2. Buizza, R., A. Hollingsworth, F. Lalaurette, and A. Ghelli, 1999: Probabilistic Predictions of Precipitation Using the ECMWF Ensemble Prediction System. Wea. Forecasting, 14(2), 168–189.CrossRefGoogle Scholar
  3. Eckel, F. A., and C. F. Mass, 2005: Aspects of Effective Mesoscale, Short-Range Ensemble Forecasting. Wea. Forecasting, 20(3), 328–350.CrossRefGoogle Scholar
  4. Hamill, T. M., 2001: Interpretation of Rank Histograms for Verifying Ensemble Forecasts. Mon. Wea. Rev., 129(3), 550–560.CrossRefGoogle Scholar
  5. Hamill, T. M., and S. J. Colucci, 1997: Verification of Eta-RSM Short-Range Ensemble Forecasts. Mon. Wea. Rev., 125(6), 1312–1327.CrossRefGoogle Scholar
  6. Hamill, T. M., and S. J. Colucci, 1998: Perturbations to the land surface condition in short-range ensemble forecasts. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 273–276.Google Scholar
  7. Hou, D., E. Kalnay, and K. K. Droegemeier, 2001: Objective Verification of the SAMEX’ 98 Ensemble Forecasts. Mon. Wea. Rev., 129(1), 73–91.CrossRefGoogle Scholar
  8. Hu, X.-M., J. W. Nielsen-Gammon, and F. Zhang, 2010: Evaluation of Three Planetary Boundary Layer Schemes in the WRF Model. J. Appl. Meteor. Climatol., 49(9), 1831–1844.CrossRefGoogle Scholar
  9. Murphy, A. H., 1973: A New Vector Partition of the Probability Score. Journal of Applied Meteorology, 12(4), 595–600.CrossRefGoogle Scholar
  10. Shen, Y., M. Feng, H. Zhang, and F. Gao, 2010: Interpolation Methods of China Daily Precipitation Data. Journal of Applied Meteorological Science, 21(3), 279–286. (in chinese)Google Scholar
  11. Skamarock, W. C., and Coauthors, 2008: A Description of the Advanced Research WRF Version 3. NCAR Technical Note, NCAR/TN-475+STR, 133pp.Google Scholar
  12. Stensrud, D. J., and N. Yussouf, 2003: Short-Range Ensemble Predictions of 2-m Temperature and Dewpoint Temperature over New England. Mon. Wea. Rev., 131(10), 2510–2524.CrossRefGoogle Scholar
  13. Stensrud, D. J., J.-W. Bao, and T. T. Warner, 2000: Using Initial Condition and Model Physics Perturbations in Short-Range Ensemble Simulations of Mesoscale Convective Systems. Mon. Wea. Rev., 128(7), 2077–2107.CrossRefGoogle Scholar
  14. Swets, J. A., 1973: The relative operating characteristic in psychology. New York Times, 7 December, 182(4116), 990–1000.Google Scholar
  15. Toth, Z., and E. Kalnay, 1997: Ensemble Forecasting at NCEP and the Breeding Method. Mon. Wea. Rev., 125(12), 3297–3319.CrossRefGoogle Scholar
  16. Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. Academic Press, San Diego, US, 467pp.Google Scholar
  17. Zhu, J., F. Kong, and H. Lei, 2012: A Regional Ensemble Forecast System for Stratiform Precipitation Events in northern China Region. Part I: A case study. Adv. Atmos. Sci., 29, 201–216.CrossRefGoogle Scholar

Copyright information

© Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jiangshan Zhu (朱江山)
    • 1
  • Fanyou Kong (孔凡铀)
    • 2
  • Hengchi Lei (雷恒池)
    • 1
  1. 1.Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.Center for Analysis and Prediction of StormsUniversity of OklahomaNormanUSA

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