Subpixel-Based Precipitation Nowcasting with the Pyramid Lucas-Kanade Optical Flow Technique

被引：24

作者：

Li, Ling ^{[1
,2
]}

He, Zhengwei ^{[1
]}

Chen, Sheng ^{[3
,4
]}

Mai, Xiongfa ^{[2
]}

Zhang, Asi ^{[3
,4
]}

Hu, Baoqing ^{[2
]}

Li, Zhi ^{[2
]}

Tong, Xinhua ^{[2
]}

机构：

[1] Chengdu Univ Technol, State Key Lab Geohazard Prevent & Geoenvironm Pro, Chengdu 610059, Sichuan, Peoples R China

[2] Guangxi Teachers Educ Univ, Minist Educ, Data Sci Guangxi Higher Educ Key Lab, Key Lab Environm Change & Resources Use Beibu Gul, Nanning 530001, Peoples R China

[3] Sun Yat Sen Univ, Sch Atmospher Sci, Guangzhou 510275, Guangdong, Peoples R China

[4] Guangdong Prov Key Lab Climate Change & Nat Disas, Guangzhou 510275, Guangdong, Peoples R China

来源：

ATMOSPHERE | 2018年 / 9卷 / 07期

基金：

中国国家自然科学基金;

关键词：

nowcasting; subpixel; pyramid Lucas-Kanade optical flow algorithm; SINGLE DOPPLER RADAR; VERIFICATION; METHODOLOGY; ALGORITHM; TRACKING;

D O I：

10.3390/atmos9070260

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Short-term high-resolution quantitative precipitation forecasting (QPF) is very important for flash-flood warning, navigation safety, and other hydrological applications. This paper proposes a subpixel-based QPF algorithm using a pyramid Lucas-Kanade optical flow technique (SPLK) for short-time rainfall forecast. The SPLK tracks the storm on the subpixel level by using the optical flow technique and then extrapolates the precipitation using a linear method through redistribution and interpolation. The SPLK compares with object-based and pixel-based nowcasting algorithms using eight thunderstorm events to assess its performance. The results suggest that the SPLK can perform better nowcasting of precipitation than the object-based and pixel-based algorithms with higher adequacy in tracking and predicting severe storms in 0-2 h lead-time forecasting.

引用

页数：22

共 47 条

[1]

[Anonymous], 1999, OPENCV DOCUMENTS

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