Generation of Ensemble Mean Precipitation Forecasts from Convection-Allowing Ensembles

被引:47
|
作者
Clark, Adam J. [1 ]
机构
[1] NOAA, OAR, Natl Severe Storms Lab, Norman, OK 73069 USA
关键词
MODEL; VERIFICATION; SYSTEM; SKILL;
D O I
10.1175/WAF-D-16-0199.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Methods for generating ensemble mean precipitation forecasts from convection-allowing model (CAM) ensembles based on a simple average of allmembers at each grid point can have limited utility because of amplitude reduction and overprediction of light precipitation areas caused by averaging complex spatial fields with strong gradients and high-amplitude features. To combat these issues with the simple ensemble mean, a method known as probability matching is commonly used to replace the ensemble mean amounts with amounts sampled from the distribution of ensemble member forecasts, which results in a field that has a bias approximately equal to the average bias of the ensemble members. Thus, the probability matched mean (PM mean hereafter) is viewed as a better representation of the ensemble members compared to the mean, and previous studies find that it is more skillful than any of the individual members. Herein, using nearly a year's worth of data from a CAM-based ensemble running in real time at the National Severe Storms Laboratory, evidence is provided that the superior performance of the PM mean is at least partially an artifact of the spatial redistribution of precipitation amounts that occur when the PM mean is computed over a large domain. Specifically, the PM mean enlarges big areas of heavy precipitation and shrinks or even eliminates smaller ones. An alternative approach for the PM mean is developed that restricts the grid points used to those within a specified radius of influence. The new approach has an improved spatial representation of precipitation and is found to perform more skillfully than the PM mean at large scales when using neighborhood-based verification metrics.
引用
收藏
页码:1569 / 1583
页数:15
相关论文
共 50 条
  • [1] Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles
    Lee, Changjae
    Brewster, Keith A.
    Snook, Nathan
    Spencer, Phillip
    Park, Jun
    [J]. Weather and Forecasting, 2024, 39 (11) : 1545 - 1558
  • [2] A Comparison of 36-60-h Precipitation Forecasts from Convection-Allowing and Convection-Parameterizing Ensembles
    Iyer, Eswar R.
    Clark, Adam J.
    Xue, Ming
    Kong, Fanyou
    [J]. WEATHER AND FORECASTING, 2016, 31 (02) : 647 - 661
  • [3] Assessing the Skill of Convection-Allowing Ensemble Forecasts of Precipitation by Optimization of Spatial-Temporal Neighborhoods
    Ma, Shenjia
    Chen, Chaohui
    He, Hongrang
    Wu, Dan
    Zhang, Chenxi
    [J]. ATMOSPHERE, 2018, 9 (02):
  • [4] Towards a Better Design of Convection-Allowing Ensembles for Precipitation Forecasts over Ensenada, Baja California, Mexico
    Mayor, Yandy G.
    Gross, Markus
    Magar, Vanesa
    [J]. ATMOSPHERE, 2020, 11 (09)
  • [5] Verification and Calibration of Neighborhood and Object-Based Probabilistic Precipitation Forecasts from a Multimodel Convection-Allowing Ensemble
    Johnson, Aaron
    Wang, Xuguang
    [J]. MONTHLY WEATHER REVIEW, 2012, 140 (09) : 3054 - 3077
  • [6] Spatial spread-skill relationship in terms of agreement scales for precipitation forecasts in a convection-allowing ensemble
    Chen, Xi
    Yuan, Huiling
    Xue, Ming
    [J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2018, 144 (710) : 85 - 98
  • [7] Generating Probabilistic Forecasts from Convection-Allowing Ensembles Using Neighborhood Approaches: A Review and Recommendations
    Schwartz, Craig S.
    Sobash, Ryan A.
    [J]. MONTHLY WEATHER REVIEW, 2017, 145 (09) : 3397 - 3418
  • [8] Perturbing Topography in a Convection-Allowing Ensemble Prediction System for Heavy Rain Forecasts
    Li, Jun
    Du, Jun
    Xiong, Jie
    Wang, Minghuan
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2021, 126 (14)
  • [9] Growth and Interactions of Multi-Source Perturbations in Convection-Allowing Ensemble Forecasts
    张璐
    闵锦忠
    庄潇然
    王世璋
    魏莉青
    [J]. Journal of Tropical Meteorology, 2024, 30 (02) - 131
  • [10] Growth and Interactions of Multi-Source Perturbations in Convection-Allowing Ensemble Forecasts
    Zhang, Lu
    Min, Jin-Zhong
    Zhuang, Xiao-ran
    Wang, Shi-zhang
    Wei, Li-qing
    [J]. JOURNAL OF TROPICAL METEOROLOGY, 2024, 30 (02) : 118 - 131