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Bayesian Model Averaging을 이용한 풍속의 확률론적 예측

A Probabilistic Forecast of Wind Speed using Bayesian Model Averaging

김찬수|김찬식|한근희
기후연구소 (KU Climate Research Institute)|2016.09|기후연구 (Journal of Climate Research)|제11권 제3호|pp. 221-235|DOI http://dx.doi.org/10.14383/cri.2016.11.3.221

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참고문헌

키워드

gamma distribution베이지안 모델 평균연속순위확률점수감마분포순위히스토그램bayesian model averagingcontinuous ranked probability scorerank histogram

초록

Abstract

This paper used the Bayesian model averaging (BMA) with gamma distribution that takes the form of probability density functions to calibrate probabilistic forecasts of wind speed. We considered the alternative implementation of BMA, which was BMA gamma exchangeable model. This method was applied for forecasting of wind speed over Pyeongchang area using 51 members of the Ensemble Prediction System for Global (EPSG). The performances were evaluated by rank histogram, means absolute error, root mean square error, continuous ranked probability score and skill score. The results showed that BMA gamma exchangeable models performed better in forecasting wind speed, compared to the raw ensemble and ensemble mean.

참고문헌 (28)

  1. Baran, S., "Probabilistic wind speed forecasting using Bayesian model averaging with truncated normal components", Computational Statistics and Data Analysis, 75, pp.227~238 (2014)
  2. Buizza, R., "Computation of optimal unstable structures for a numerical weather prediction model", Tellus, A, 45(5), pp.388~407 (1993)
  3. Dempster, A. P., "Maximum likelihood from incomplete data via the EM algorithm", Journal of the Royal Statistical Society Series B, 39, pp.1~38 (1977)
  4. L. Descamps, "PEARP, the Météo-France short-range ensemble prediction system", Quarterly Journal of the Royal Meteorological Society, 141(690), pp.1671~1685 (2015), Wiley-Blackwell[DOI]
  5. ECMWF Directorate, "Describing ECMWF’s forecasts and forecasting system", ECMWF Newsletter, 133, pp.11~13 (2012)
  6. Fraley, C. A., "Calibrating multimodel forecast ensembles with exchangeable and missing members using Bayesian model averaging", Monthly Weather Review, 138(1), pp.190~202 (2010)
  7. Gneiting, T., "Probabilistic forecasts, calibration and sharpness", Journal of the Royal Statistical Society Series B, 69(2), pp.243~268 (2007)
  8. Gneiting, T., "Weather forecasting with ensemble methods", Science, 310, pp.248~249 (2005)
  9. Gneiting, T., "Strictly proper scoring rules, prediction, and estimation", Journal of the American Statistical Association, 102(477), pp.359~378 (2007)
  10. Gneiting, T., "Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation", Monthly Weather Review, 113(5), pp.1098~1118 (2005)
  11. Hamill, T. M., "Interpretation of rank histograms for verifying ensemble forecasts", Monthly Weather Review, 129(3), pp.550~560 (2001)
  12. 한근희, "동질성과 비 동질성 회귀모델을 이용한 평창지역 기온에 대한확률론적 예측", 기후연구, 11(1), pp.87~103 (2016), 기후연구소[DOI]
  13. 한근희, "Bayesian Model Averaging을 이용한 평창 지역 기온에 대한 확률론적 예측 및 성능 평가", 기후연구, 11(1), pp.49~67 (2016), 기후연구소[DOI]
  14. Hersbach, H., "Decomposition of the continuous ranked probability score for ensemble prediction systems", Weather Forecasting, 15(5), pp.559~570 (2000)
  15. Hoeting, J. A., "Bayesian model averaging:A tutorial", Statistical Science, 14(4), pp.382~401 (1999)
  16. Kass, R. E., "Bayes Factors", Journal of the American Statistical Association, 90(430), pp.773~795 (1995)
  17. 김찬수, "Prospects of Using Bayesian Model Averaging for the Calibration of One-month Forecasts of Surface Air Temperature over South Korea", 한국기상학회지, 49(3), pp.301~311 (2013), 한국기상학회
  18. Leamer, E. E., "Specification Search -Ad Hoc inference with nonexperimental data", pp.370~ (1978), Wiley
  19. Leith, C. E., "Theorectical skill of Monte-Carlo forecasts", Monthly Weather Review, 102(6), pp.409~418 (1974)
  20. Sebastian Lerch, "Comparison of non-homogeneous regression models for probabilistic wind speed forecasting", Tellus A, 65(0) (2013), Informa UK Limited[DOI]
  21. Liu, C., "The ECME algorithm:A simple extension of EM and ECM with faster monotone convergence", Biometrika, 81(4), pp.633~648 (1994)
  22. Murphy, A. H., "A general framework for forecast verification", Monthly Weather Review, 115(7), pp.1330~1338 (1987)
  23. Raftery, A. E., "Using Bayesian model averaging to calibrate forecast ensembles", Monthly Weather Review, 133, pp.1155~1174 (2005)
  24. Sloughter, J. M., "Probabilistic wind speed forecasting using ensembles and Bayesian model averaging", Journal of the American Statistical Association, 105(489), pp.25~35 (2010)
  25. Thorarinsdottir, T. L., "Probabilistic forecasts of wind speed: Ensemble model output statistics by using heteroscedastic censored regression", Journal of the Royal Statistical Society Series A, 173, pp.371~388 (2010)
  26. Toth, Z., "Ensemble forecasting at NCEP: the breeding method", Monthly Weather Review, 125(12), pp.3297~3318 (1997)
  27. Unger, D. A., "A method to estimate the continuous ranked probability score in Preprints", Ninth Conference on Probability and Statistics in Atmospheric Sciences, pp.206~213 (1985), American Meteorological Society
  28. Wilson, L. J., "Calibrated surface temperature forecasts from the Canadian ensemble prediction system using Bayesian model averaging", Monthly Weather Review, 135(4), pp.1364~1385 (2007)

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