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

• Published in: Atmosphere Vol. 9; no. 7; p. 260
• Main Authors: Li, Ling, He, Zhengwei, Chen, Sheng, Mai, Xiongfa, Zhang, Asi, Hu, Baoqing, Li, Zhi, Tong, Xinhua
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2018
• Subjects: Accuracy; Adequacy; Algorithms; Atmospheric precipitations; Doppler radar; Education; Flash flood warnings; Flash flooding; Flash floods; Flood forecasting; Flood warnings; Hydrology; Identification; Interpolation; Laboratories; Lead time; Meteorology; Navigation; Navigation safety; Nowcasting; Optical flow (image analysis); Pixels; Precipitation; pyramid Lucas–Kanade optical flow algorithm; Rain; Rainfall; Rainfall forecasting; Severe storms; Short term; Storm forecasting; Storms; subpixel; Thunderstorms; Tracking; Weather forecasting; China
• ISSN: 2073-4433; 2073-4433
• DOI: 10.3390/atmos9070260

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.