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
  • [2] An Operational Weather Radar-Based Quantitative Precipitation Estimation and its Application in Catchment Water Resources Modeling
    He, Xin
    Vejen, Flemming
    Stisen, Simon
    Sonnenborg, Torben O.
    Jensen, Karsten H.
    [J]. VADOSE ZONE JOURNAL, 2011, 10 (01) : 8 - 24
  • [3] BALTEX weather radar-based precipitation products and their accuracies
    Koistinen, J
    Michelson, DB
    [J]. BOREAL ENVIRONMENT RESEARCH, 2002, 7 (03): : 253 - 263
  • [4] Radar-based quantitative precipitation estimation over Mediterranean and dry climate regimes
    Morin, Efrat
    Gabella, Marco
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2007, 112 (D20)
  • [5] Development of Radar-Based Multi-Sensor Quantitative Precipitation Estimation Technique
    Lee, Jae-Kyoung
    Kim, Ji-Hyeon
    Park, Hye-Sook
    Suk, Mi-Kyung
    [J]. ATMOSPHERE-KOREA, 2014, 24 (03): : 433 - 444
  • [6] Assessing Quantitative Precipitation Estimation Methods Based on the Fusion of Weather Radar and Rain-Gauge Data
    Biondi, Alessio
    Facheris, Luca
    Argenti, Fabrizio
    Cuccoli, Fabrizio
    Antonini, Andrea
    Melani, Samantha
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 21
  • [7] Comparing and Optimizing Four Machine Learning Approaches to Radar-Based Quantitative Precipitation Estimation
    Liu, Miaomiao
    Zuo, Juncheng
    Tan, Jianguo
    Liu, Dongwei
    [J]. Remote Sensing, 2024, 16 (24)
  • [8] On the use of radar-based quantitative precipitation estimates for precipitation frequency analysis
    Eldardiry, Hisham
    Habib, Emad
    Zhang, Yu
    [J]. JOURNAL OF HYDROLOGY, 2015, 531 : 441 - 453
  • [9] Improving high-resolution quantitative precipitation estimation via fusion of multiple radar-based precipitation products
    Rafieeinasab, Arezoo
    Norouzi, Amir
    Seo, Dong-Jun
    Nelson, Brian
    [J]. JOURNAL OF HYDROLOGY, 2015, 531 : 320 - 336
  • [10] Evaluation of the Specific Attenuation Method for Radar-Based Quantitative Precipitation Estimation: Improvements and Practical Challenges
    Seo, Bong-Chul
    Krajewski, Witold F.
    Ryzhkov, Alexander
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2020, 21 (06) : 1333 - 1347