Radar-based precipitation type analysis in the Baltic area

被引:12
|
作者
Walther, A [1 ]
Bennartz, R
机构
[1] Free Univ Berlin, Inst Weltraumwissensch, D-12165 Berlin, Germany
[2] Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI 53706 USA
来源
TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY | 2006年 / 58卷 / 03期
关键词
D O I
10.1111/j.1600-0870.2006.00183.x
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A method to classify precipitation events based on their spatial extent and texture has been developed and applied to 3 yr of BALTEX Radar Data Center weather radar composites over the Baltic region. The method is capable of distinguishing large-scale precipitation features typically associated with frontal systems from more small-scale features, which are usually found in convective systems. Data used for this Study are 2-D radar images. The classification is performed in three steps. First, contiguous precipitation areas are identified in the radar data. In the second step, each of these areas is Subjected to an analysis where different texture parameters are calculated. In a third step, these texture parameters are evaluated by means of a neural network, and a type of precipitation is assigned to each class. The neural network has been trained using a large set of visually classified radar scenes. A validation of the results has been performed by (1) comparing regions where U.K. Met Office analysis shows large contiguous frontal areas and (2) by using surface observations where the surface observer reported precipitation events that could clearly be associated either with intermittent convective precipitation or with frontal systems. The results of the different comparisons are generally in good agreement with each other, and the false classification rate ranges from 10% to 20%. The application to 3 yr of radar data has resulted in estimation of the frontal fraction of precipitation in the Baltic Sea area. About two-thirds of overall precipitation events are determined by frontal passages with high seasonal and diurnal variations.
引用
收藏
页码:331 / 343
页数:13
相关论文
共 50 条
  • [11] Hierarchical Transformer With Lightweight Attention for Radar-Based Precipitation Nowcasting
    Li, Wenhui
    Zhou, Ying
    Li, Yue
    Song, Dan
    Wei, Zhiqiang
    Liu, An-An
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 21 : 1 - 5
  • [12] A radar-based verification of precipitation forecast for local convective storms
    Rezacova, Daniela
    Sokol, Zbynek
    Pesice, Petr
    ATMOSPHERIC RESEARCH, 2007, 83 (2-4) : 211 - 224
  • [13] Quantifying and predicting the accuracy of radar-based quantitative precipitation forecasts
    Fabry, Frederic
    Seed, Alan W.
    ADVANCES IN WATER RESOURCES, 2009, 32 (07) : 1043 - 1049
  • [14] A review of current approaches to radar-based quantitative precipitation forecasts
    Liguori, Sara
    Rico-Ramirez, Miguel Angel
    INTERNATIONAL JOURNAL OF RIVER BASIN MANAGEMENT, 2014, 12 (04) : 391 - 402
  • [15] Stochastic Spectral Method for Radar-Based Probabilistic Precipitation Nowcasting
    Pulkkinen, Seppo
    Chandrasekar, V.
    Harri, Ari-Matti
    JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2019, 36 (06) : 971 - 985
  • [16] Comprehensive Framework for Assessment of Radar-Based Precipitation Data Estimates
    Teegavarapu, Ramesh S. V.
    Goly, Aneesh
    Wu, Qinglong
    JOURNAL OF HYDROLOGIC ENGINEERING, 2017, 22 (05)
  • [18] Examining the Robustness of a Spatial Bootstrap Regional Approach for Radar-Based Hourly Precipitation Frequency Analysis
    Eldardiry, Hisham
    Habib, Emad
    REMOTE SENSING, 2020, 12 (22) : 1 - 19
  • [19] Radar-Based Precipitation Nowcasting Based on Improved U-Net Model
    Tan, Youwei
    Zhang, Ting
    Li, Leijing
    Li, Jianzhu
    REMOTE SENSING, 2024, 16 (10)
  • [20] 3D downscaling model for radar-based precipitation fields
    Llort, Xavier
    Berenguer, Marc
    Franco, Maria
    Sanchez-Diezma, Rafael
    Sempere-Torres, Daniel
    METEOROLOGISCHE ZEITSCHRIFT, 2006, 15 (05) : 505 - 512