Application of the frequency-matching method in the probability forecast of landfalling typhoon rainfall

Abstract

In this paper, a revised method for typhoon precipitation probability forecast, based on the frequency-matching method, is developed by combining the screening and the neighborhood methods. The frequency of the high-resolution precipitation forecasts is used as the reference frequency, and the frequency of the low-resolution ensemble forecasts is used as the forecast frequency. Based on frequency–matching method, the frequency of rainfall above the rainstorm magnitude increases. The forecast members are then selected by using the typhoon tracks of the short-term predictions, and the precipitation probability is calculated for each member using a combination of the neighbor and the traditional probability statistical methods. Moreover, four landfalling typhoons (i.e., STY Lekima and STS Bailu in 2019, and TY Hagupit and Higos in 2020) were chose to test the rainfall probability forecast. The results show that the method performs well with respect to the forecast rainfall area and magnitude for the four typhoons. The Brier and Brier skill scores are almost entirely positive for the probability forecast of 0.1–250 mm rainfall during Bailu, Hagupit and Higos (except for 0.1mm of Hagupit), and for<100 mm rainfall (except for 25 mm) during Lekima.

Graphical abstract

Keywords

frequency-matching method / landfalling typhoon / rainfall probability / Brier score

References

[1] Bradley A A, Schwartz S S, Hashino T (2008). Sampling uncertainty and confidence intervals for the Brier score and Brier skill score. Weather Forecast, 23(5): 992–1006

[2] Brier G W (1950). Verification of forecasts expressed in terms of probability, Mon Wea Rev, 78: 1‒3

[3] Buizza R, Du J, Toth Z, Hou D (2018). Major operational ensemble prediction systems (EPS) and the future of EPS. In: Duan Q et al., eds., Handbook of Hydrometeorological Ensemble Forecasting, Springer: 1–43

[4] Chen P Y, Yu H, Xu M, Lei X, Zeng F (2019a). A simplified index to assess the combined impact of tropical cyclone precipitation and wind on China. Front Earth Sci, 13(4): 672–681

[5] Chen L S, Ding Y H (1979). An Introduction to the Western Pacific Typhoon. Beijing: Science Press (in Chinese)

[6] Chen L S, Xu Y L (2017), Review of typhoon very heavy rainfall in China. Meteorol Env S, 40 (1): 3–10 (in Chinese)

[7] Chen L S, Meng Z Y (2001). An overview on tropical cyclone research progress in China duiring the past ten years. Chin J Atmos Sci, 25(3): 420–432 (in Chinese)

[8] Chen C H, Wang T, Tan Y K, Li C Y, Xu Y C. (2009). Experiments of multi-model short-range ensemble precipitation probability forecasts. J Nanjing Instit of Meteor, 32(2): 206–214

[9] Chen G M, Zhang X P, Bai L N, Wan R J. (2019b). Verification on forecasts of tropical cyclones over Western North Pacific and South China Sea in 2017. Meteorol Mon, 45(4): 577–586 (in Chinese)

[10] Craig S S, John S K, Steven J W, Xue M, David R B, Fanyou K, Klein W T, Michael C C, Matthew S W (2010). Toward improved convection-allowing ensembles: model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Weather Forecast, (25): 263–280

[11] Du J, Mullen S L, Sanders F (1997). Short-range ensemble forecasting (SREF) of quantitative precipitation. Mon Weather Rev, 125(10): 2427–2459

[12] Du J (2002). Present Situation and Prospects of Ensemble Numerical Prediction. J Appl Meteor Sci, 13: 16–28 (in Chinese)

[13] Du J, Zhou B B (2011). A dynamical performance-ranking method for predicting individual ensemble member’s performance and its application to ensemble averaging. Mon Weather Rev, 139(10): 3284–3303

[14] Du J, Kang Z M (2014a). A survey on forecasters’ view about uncertainty in weather forecasts. Adv Meteorol S, 4(1): 58–67

[15] Du J, Berner J, Buizza R, Charron M, Houtekamer P, Hou D C, Jankov I, Mu M, Wang X G, Wei M Z, Yuan H L (2018). Ensemble methods for meteorological predictions. In: Duan et al., eds. Handbook of Hydrometeorological Ensemble Forecasting, Q. Cham: Springer

[16] Ebert E E (2001a). Ability of a poor man’s ensemble to predict the probability and distribution of precipitation. Mon Weather Rev, 129(10): 2461–2480

[17] Evert E E(2001b). Probability-matched ensemble mean. Available online at CAWCR website

[18] Ebert E E (2008). Fuzzy verification of high resolution gridded forecasts: A review and proposed framework. Meteorol Appl, 15(1): 51–66

[19] Hamill T M, Colucci S J (1997). Verification of Eta–RSM short-range ensemble forecasts. Mon Weather Rev, 125(6): 1312–1327

[20] Hamill T M, Colucci S J (1998). Evaluation of Eta-RSM ensemble probabilistic precipitation forecasts. Mon Wea Rev, 126: 711–724

[21] Hamill T M, Whitaker J S, Fiorino M, Benjamin S G (2010). Global ensemble predictions of 2009’s tropical cyclones initialized with an ensemble Kalman Filter. Mon Wea Rev, 139: 668‒688

[22] Li J, Du J, Wang M H, Gong Y, Lai A W. (2010). Precipitation verifications to an ensemble prediction system using two initial perturbation schemes based on arem. J Trop Meteorol, 6: 733–742 (in Chinese)

[23] Li J, Du J, Zhang D L, Cui C, Liao Y (2014a). Ensemble-based analysis and sensitivity of mesoscale forecasts of a vortex over southwest China. Q J R Meteorol Soc, 140(680): 766–782

[24] Li J, Du J, Chen C J (2014b). Introduction and analysis to frequency or area matching method applied to precipitation forecast bias correction. Meteorol Mon, 40(5): 580–588 (in Chinese)

[25] Li J, Du J, Chen C J (2015). Applications of ‘frequency-matching’ method to ensemble precipitation forecasts. Meteorol Mon, 41(6): 674–684 (in Chinese)

[26] Li Z C, Chen D H (2002). The development and application of the operational ensemble prediction system at national meteorological center. J Appl Meteorol Sci, 13(1): 1–15 (in Chinese)

[27] Lorenz E N (1995). The Essence of Chaos. Seatle: University of Washington Press

[28] Lorenz E N (1996). Predictability: a problem partly solved. IN: Proc. Seminar on Predictability, Vol. 1, Reading, United Kingdom, ECMWF, 1–18

[29] Mu M, Zhang Z (2006). Conditional nonlinear optimal perturbations of a two-dimensional quasi-geostrophic model. J Atmos Sci, 63(6): 1587–1604

[30] Murphy A H (1973). A new vector partition of the probability score. J Appl Meteorol, 12(4): 595–600

[31] National Research Council (2006). Completing the Forecast: Characterizing and Communicating Uncertainty for Better Decision Using Weather and Climate Forecasts. Washington DC: The National Academy Press (USA)

[32] Rosenfeld D, Wolff D B, Atlas D (1993). General probability-matched relations between radar reflectivity and rain rate. J Appl Meteorol, 32(1): 50–72

[33] Schwartz C S, Kain J S, Weiss S J, Xue M, Bright D R, Kong F, Thomas K W, Levit J J, Coniglio M C, Wandishin M S (2010). Toward improved convection-allowing ensembles: model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Weather Forecast, 25(1): 263–280

[34] Stensrud D J, Bao J W, Warner T T (2000). Using initial condition and model physics perturbations in short—range ensemble simulations of mesoscale convective systems. Mon Weather Rev, 128(7): 2077–2107

[35] Stefanova L, Krishnamurti T N (2002). Interpretation of seasonal climate forecast using Brier skill score, The Florida State University Superensemble, and the AMIP-I Dataset. J Clim, 15(5): 537–544

[36] Voisin N, Schaake J C, Lettenmaier D P (2010). Calibration and downscaling methods for quantitative ensemble precipitation forecasts. Weather Forecast, 25(6): 1603–1627

[37] Yamaguchi M, Sakai R, Kyoda M, Komori T, Kadowaki T (2009). Typhoon ensemble prediction system developed at the Japan Meteorological Agency. Mon Weather Rev, 137(8): 2592–2604

[38] Yamaguchi M, Nakazawa T, Hoshino S (2012). On the relative benefits of a multi-centre grand ensemble for tropical cyclone track prediction in the western north Pacific. Q J R Meteorol Soc, 138(669): 2019–2029

[39] Yang X S (2001). The new development and the outlook of the operational ensemble prediction system. Meteorol Mon, 27(6): 3–9 (in Chinese)

[40] Yu H, Chen L S (2019). Impact assessment of landfalling tropical cyclones: introduction to the special issue. Front Earth Sci, 13(4): 669–671

[41] Zhi X F, Lyu Y (2019). Calibration of the multimodel precipitation forecasts in China using the frequency matching method. Transac Atmosph Sci, 42(6): 814–823 (in Chinese)

[42] Zhu Y J, Luo Y (2015). Precipitation calibration based on the frequency-matching method. Weather Forecast, 30(5): 1109–1124

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