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Improving precipitation ensemble forecasts of typhoon heavy rainfall over East China with a modified probability-matching technique

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Abstract

In this paper, four schemes involving the probability-matching technique were studied to obtain ensemble-based quantitative precipitation forecasts (QPFs) associated with Typhoon Lekima over East China. With the use of this technique, synthetic ensembles were created by blending low- and high-resolution rainfall forecasts. To effectively derive high-resolution ensemble forecasts, the neighborhood method was applied to mesoscale deterministic forecasts. Four schemes were explored based on the probability-matching technique. Two schemes resulted in ensemble forecasts, and the other two schemes yielded deterministic forecasts. By analyzing quantitative precipitation forecasts (QPFs) and ensemble forecasts, modified probability-matching-based schemes were determined to substantially reduce or eliminate the intrinsic model rainfall bias and to provide better QPF guidance. These encouraging results suggest that the modified probability-matching technique is a useful tool for QPFs of typhoon heavy rainfall over East China using dual-resolution ensemble forecasts.

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All data, models, and code generated or used during the study appear in the submitted article.

References

  • Accadia C, Mariani S, Casaioli M, Lavagnini A, Speranza A (2005) Verification of precipitation forecasts from two limited area models over Italy and comparison with ECMWF forecasts using a resampling technique. Wea Forecasting 20:276–300

    Article  Google Scholar 

  • Anthes RA, Kuo Y-H, Hsie E-Y, Low-Nam S, Bettge TW (1989) Estimation of skill and uncertainty in regional numerical models. Quart J Roy Meteor Soc 115:763–806. https://doi.org/10.1002/qj.49711548803

    Article  Google Scholar 

  • Bowler NE, Pierce CE, Seed AW (2006) Steps: a probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP. Quart J Roy Meteor Soc 132:2127–2155

    Article  Google Scholar 

  • Cheung KKW, Huang L-R, Lee C-S (2008) Characteristics of rainfall during tropical cyclone periods in Taiwan. Nat Hazards Earth Syst Sci 8:1463–1474. https://doi.org/10.5194/nhess-8-1463-2008

    Article  Google Scholar 

  • Clark AJ (2017) Generation of ensemble mean precipitation forecasts from convection-allowing ensembles. Wea Forecasting 32:1569–1583. https://doi.org/10.1175/WAF-D-16-0199.1

    Article  Google Scholar 

  • Dey SR, Roberts NM, Plant RS, Migliorini S (2016) A new method for the characterization and verification of local spatial predictability for convective-scale ensembles. Quart J Roy Meteor Soc 142:1982–1996

    Article  Google Scholar 

  • Ebert EE (2001) Ability of a poor man’s ensemble to predict the probability and distribution of precipitation. Mon Wea Rev 129:2461–2480

    Article  Google Scholar 

  • Epstein ES (1969) A scoring system for probability forecasts of ranked categories. J Appl Meteor 8:985–987

    Article  Google Scholar 

  • Fang X, Kuo YH (2013) Improving ensemble-based quantitative precipitation forecasts for topography-enhanced typhoon heavy rainfall over Taiwan with a modified probability-matching technique [J]. Mon Weather Rev 141(11):3908–3932

    Article  Google Scholar 

  • Germann U, Zawadzki I (2004) Scale dependence of the predictability of precipitation from continental radar images. part ii: Probability forecasts. J Appl Meteor 43:74–89. https://doi.org/10.1175/1520-0450(2004)0432.0.CO;2

    Article  Google Scholar 

  • Goerss JS (2000) Tropical cyclone track forecasts using an ensemble of dynamical models. Mon Wea Rev 128:1187–1193

    Article  Google Scholar 

  • Goerss JS, Sampson CR, Gross JM (2004) a history of western North Pacific tropical cyclone track forecast skill. Wea Forecasting 19:633–638

    Article  Google Scholar 

  • Han S, Shi CX, Xu B et al (2019) Development and evaluation of hourly and kilometer resolution retrospective and realtime surface meteorological blended forcing dataset (SMBFD) in China. J Meteor Res 33:1168–1181. https://doi.org/10.1007/s13351-019-9042-9

    Article  Google Scholar 

  • Kober K, Craig G, Keil C, Dörnbrack A (2012) Blending a probabilistic nowcasting method with a high-resolution numerical weather prediction ensemble for convective precipitation forecasts. Quart J Roy Meteor Soc 138:755–768

    Article  Google Scholar 

  • Murphy AH (1969) On the ranked probability skill score. J Appl Meteor 8:988–989

    Article  Google Scholar 

  • Qi L, Yu H, Chen P (2014) Selective ensemble-mean technique for tropical cyclone track forecast by using ensemble prediction systems. Q J R Meteorol Soc 140:805–813

    Article  Google Scholar 

  • Qiao X, Wang S, Schwartz CS, Liu Z, Min J (2020) A method for probability matching based on the ensemble maximum for quantitative precipitation forecasts. Mon Weather Rev 148(8):3379–3396

    Article  Google Scholar 

  • Scheufele K, Kober K, Craig GC, Keil C (2014) Combining probabilistic precipitation forecasts from a nowcasting technique with a time-lagged ensemble. Meteor Appl 21:230–240

    Article  Google Scholar 

  • Schwartz CS, Kain JS, Weiss SJ, Xue M, Bright DR, Kong F, Thomas KW, Levit JJ, Coniglio MC, Wandishin MS (2010) Toward improved convection allowing ensembles: model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Wea Forecast 25:263–280

    Article  Google Scholar 

  • Seed A (2003) A dynamic and spatial scaling approach to advection forecasting. J Appl Meteor 42:381–388

    Article  Google Scholar 

  • Shi CX, Xie ZH, Qian H et al (2011) China land soil moisture EnKF data assimilation based on satellite remote sensing data. Sci China Earth Sci 54:1430–1440. https://doi.org/10.1007/s11430-010-4160-3

    Article  Google Scholar 

  • Sokol Z, Pesice P (2012) Nowcasting of precipitation advective statistical forecast model (SAM) for the Czech Republic. Atmos Res 103:70–79

    Article  Google Scholar 

  • Sokol Z, Mejsnar J, Pop L, Bližnák V (2017) Probabilistic precipitation nowcasting based on an extrapolation of radar reflectivity and an ensemble approach. Atmos Res 194:245–257

    Article  Google Scholar 

  • Theis S, Hense A, Damrath U (2005) Probabilistic precipitation forecasts from a deterministic model: a pragmatic approach. Meteor Appl 12:257–268

    Article  Google Scholar 

  • Tuleya RE, DeMaria M, Kuligowski RJ (2007) Evaluation of GFDL and simple statistical model rainfall forecasts for U.S. landfalling tropical storms. Wea Forecasting 22:56–70

    Article  Google Scholar 

  • Zadeh L (1965) Fuzzy sets. Inf Control 8:338–353

    Article  Google Scholar 

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Acknowledgements

The authors would like to extend their sincere gratitude to China Meteorological Administration providing the relevant data.

Funding

This study was supported by Anhui Provincial Natural Science Foundation (2008085QD190), Special Project for Forecasters of China Meteorological Administration (CMAYBY2019-050), Innovation and Development Project of China Meteorological Administration (CXFZ2022J067), Hefei Key Technology Project (J2020J07), Key Research and Development Plan of Anhui Province (206038346013) and Anhui Meteorological Bureau Innovation Team.

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Authors

Contributions

Conceptualization, C.L. and X.Q.; methodology, C.L. and H.D.; software, C.L.; validation, H.D. and X.Q.; formal analysis, C.L.; investigation, L.Z., Y.L., and Y.Z.; resources, H.D.; data curation, H.D.; writing—original draft preparation, C.L.; writing—review and editing, H.D. and X.Q.; visualization, C.L.; supervision, L.Z.; project administration, X.Q.; funding acquisition, C.L. and H.D. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Hanqing Deng.

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Liu, C., Deng, H., Qiu, X. et al. Improving precipitation ensemble forecasts of typhoon heavy rainfall over East China with a modified probability-matching technique. Bull. of Atmos. Sci.& Technol. 3, 4 (2022). https://doi.org/10.1007/s42865-022-00048-x

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  • DOI: https://doi.org/10.1007/s42865-022-00048-x

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