Next Article in Journal
Application of Farmyard Manure Rather Than Manure Slurry Mitigates the Net Greenhouse Gas Emissions from Herbage Production System in Nasu, Japan
Previous Article in Journal
The Weather Conditions for Desired Smoke Plumes at a FASMEE Burn Site
Previous Article in Special Issue
An Ensemble Mean and Evaluation of Third Generation Global Climate Reanalysis Models
Article Menu

Export Article

Open AccessArticle
Atmosphere 2018, 9(7), 260; https://doi.org/10.3390/atmos9070260

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

1
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
2
Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Data Science of Guangxi Higher Education Key Laboratory, Guangxi Teachers Education University, Ministry of Education, Nanning 530001, China
3
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China
4
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Guangzhou 510275, China
*
Authors to whom correspondence should be addressed.
Received: 16 April 2018 / Revised: 25 June 2018 / Accepted: 6 July 2018 / Published: 12 July 2018
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
View Full-Text   |   Download PDF [7779 KB, uploaded 20 July 2018]   |  

Abstract

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. View Full-Text
Keywords: nowcasting; subpixel; pyramid Lucas–Kanade optical flow algorithm nowcasting; subpixel; pyramid Lucas–Kanade optical flow algorithm
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Li, L.; He, Z.; Chen, S.; Mai, X.; Zhang, A.; Hu, B.; Li, Z.; Tong, X. Subpixel-Based Precipitation Nowcasting with the Pyramid Lucas–Kanade Optical Flow Technique. Atmosphere 2018, 9, 260.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Atmosphere EISSN 2073-4433 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top