Two Different Integration Methods for Weather Radar-Based Quantitative Precipitation Estimation

被引:0
|
作者
Ren, Jing [1 ,2 ,3 ]
Huang, Yong [1 ,3 ]
Guan, Li [2 ]
Zhou, Jie [1 ,2 ,3 ]
机构
[1] Anhui Meteorol Inst, Key Lab Atmospher Sci & Satellite Remote Sensing, Hefei 230031, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Nanjing 210044, Peoples R China
[3] Shouxian Climatol Observ, Shouxian 232200, Peoples R China
基金
中国国家自然科学基金;
关键词
REAL-TIME; RAINFALL; SATELLITE; PRODUCTS; BASIN;
D O I
10.1155/2017/1269748
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
We discuss two different integration methods for radar-based quantitative precipitation estimation (QPE): the echo intensity integral and the rain intensity integral. Theoretical analyses and simulations were used to test differences between these two methods. Cumulative rainfall calculated by the echo intensity integral is usually greater than that from rain intensity integral. The difference of calculated precipitation using these two methods is generally smaller for stable precipitation systems and larger for unstable precipitation systems. If the echo intensity signal is sinusoidal, the discrepancy between the two methods is most significant. For stratiform and convective precipitation, the normalized error ranges from -0.138 to -0.15 and from -0.11 to -0.122, respectively. If the echo intensity signal is linear, the normalized error ranges from 0 to -0.13 and from 0 to -0.11, respectively. If the echo intensity signal is exponential, the normalized error ranges from 0 to -0.35 and from 0 to -0.30, respectively. When both the integration scheme and real radar data were used to estimate cumulative precipitation for one day, their spatial distributions were similar.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Research studies on improvement in real-time estimation of radar-based precipitation in Poland
    A. Jurczyk
    K. Ośródka
    J. Szturc
    [J]. Meteorology and Atmospheric Physics, 2008, 101 : 159 - 173
  • [32] Research studies on improvement in real-time estimation of radar-based precipitation in Poland
    Jurczyk, A.
    Osrodka, K.
    Szturc, J.
    [J]. METEOROLOGY AND ATMOSPHERIC PHYSICS, 2008, 101 (3-4) : 159 - 173
  • [33] Polarimetric Radar Quantitative Precipitation Estimation
    Ryzhkov, Alexander
    Zhang, Pengfei
    Bukovcic, Petar
    Zhang, Jian
    Cocks, Stephen
    [J]. REMOTE SENSING, 2022, 14 (07)
  • [34] Radar-based quantitative precipitation estimation for the identification of debris flow occurrence over earthquake-affected regions in Sichuan, China
    Shi, Zhao
    Wei, Fangqiang
    Chandrasekar, Venkatachalam
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2018, 18 (03) : 765 - 780
  • [35] An Approach for Radar Quantitative Precipitation Estimation Based on Spatiotemporal Network
    Wang, Shengchun
    Yu, Xiaozhong
    Liu, Lianye
    Huang, Jingui
    Wong, Tsz Ho
    Jiang, Chengcheng
    [J]. CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 65 (01): : 459 - 479
  • [36] Radar-based precipitation type analysis in the Baltic area
    Walther, A
    Bennartz, R
    [J]. TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY, 2006, 58 (03): : 331 - 343
  • [37] Radar-based precipitation classification in the Baltic Sea area
    Walther, A
    Bennartz, R
    Fischer, J
    [J]. 31ST CONFERENCE ON RADAR METEOROLOGY, VOLS 1 AND 2, 2003, : 467 - 468
  • [38] Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula
    Lee, Jae-Kyoung
    Song, Chang Geun
    [J]. APPLIED SCIENCES-BASEL, 2020, 10 (21): : 1 - 16
  • [39] Radar-based summer precipitation climatology of the Czech Republic
    Bliznak, Vojtech
    Kaspar, Marek
    Mueller, Miloslav
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2018, 38 (02) : 677 - 691
  • [40] Uncertainties in the radar-based analysis of intense precipitation events
    Treis A.
    Becker R.
    Teichgräber B.
    Pfister A.
    [J]. WasserWirtschaft, 2021, 111 (7-8) : 25 - 29