Improvement of Local Categorical Precipitation Forecasts from an NWP Model by Various Statistical Postprocessing Methods

被引：0
|
作者：
Zbyněk Sokol
Daniela Řezáčová
机构：
[1] Acad. Sci,Institute of Atmospheric Physics
[2] Czech Republic,undefined
来源：
Studia Geophysica et Geodaetica | 2000年 / 44卷
关键词：
Statistical postprocessing; Precipitation forecast; NWP model;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Several statistical postprocessing methods are applied to results from a numerical weather prediction (NWP) model to test the potential for increasing the accuracy of its local precipitation forecasts. Categorical (Yes/No) forecasts for 12hr precipitation sums equalling or exceeding 0.1, 2.0 and 5.0 mm are selected for improvement. The two 12hr periods 0600-1800 UTC and 1800-0600 UTC are treated separately based on NWP model initial times 0000 UTC and 1200 UTC, respectively. Input data are taken from three successive summer seasons, April-September, 1994-96. The forecasts are prepared and verified for five synoptic stations, four located in the western Czech Republic, and one in Germany near the Czech-German border.
引用
收藏
页码：38 / 56
页数：18
相关论文
共 50 条
  • [31] Verification of visibility forecasts from NWP model with satellite and surface observations
    Aditi
    George, John P.
    Das Gupta, M.
    Rajagopal, E. N.
    Basu, Swati
    MAUSAM, 2015, 66 (03): : 603 - 616
  • [32] Spatial connections in extreme precipitation events obtained from NWP forecasts: A complex network approach
    Singhal, Akshay
    Jaseem, Muhammed
    Jha, Sanjeev K.
    ATMOSPHERIC RESEARCH, 2022, 283
  • [33] Diagnosing probabilities of convective precipitation from NWP model outputs
    Hand, WH
    Pierce, CE
    16TH CONFERENCE ON WEATHER ANALYSIS AND FORECASTING / SYMPOSIUM ON THE RESEARCH FOCI OF THE U.S. WEATHER RESEARCH PROGRAM, 1998, : J126 - J128
  • [34] Diagnosing probabilities of convective precipitation from NWP model outputs
    Hand, WH
    Pierce, CE
    12TH CONFERENCE ON NUMERICAL WEATHER PREDICTION, 1998, : J42 - J44
  • [35] A Variable-Correlation Model to Characterize Asymmetric Dependence for Postprocessing Short-Term Precipitation Forecasts
    Li, Wentao
    Wang, Quan J.
    Duan, Qingyun
    MONTHLY WEATHER REVIEW, 2020, 148 (01) : 241 - 257
  • [36] Statistical Postprocessing of Water Level Forecasts Using Bayesian Model Averaging With Doubly Truncated Normal Components
    Baran, Sandor
    Hemri, Stephan
    El Ayari, Mehrez
    WATER RESOURCES RESEARCH, 2019, 55 (05) : 3997 - 4013
  • [37] DEVELOPMENT OF AN MOS MODEL USING RANKED NWP PREDICTORS AND THE FORECASTS FROM AN ANALOG MODEL AS INPUT
    YACOWAR, N
    BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 1981, 62 (06) : 883 - 883
  • [38] Multifractal evaluation of simulated precipitation intensities from the COSMO NWP model
    Wolfensberger, Daniel
    Gires, Auguste
    Tchiguirinskaia, Ioulia
    Schertzer, Daniel
    Berne, Alexis
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2017, 17 (23) : 14253 - 14273
  • [39] Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?
    R. Manzanas
    A. Lucero
    A. Weisheimer
    J. M. Gutiérrez
    Climate Dynamics, 2018, 50 : 1161 - 1176
  • [40] Intercomparison of multiple statistical methods in post-processing ensemble precipitation and temperature forecasts
    Li, Xiangquan
    Chen, Jie
    Xu, Chong-Yu
    Chen, Hua
    Guo, Shenglian
    METEOROLOGICAL APPLICATIONS, 2020, 27 (04)
12345