Next Article in Journal
The Hydrometeorology Testbed–West Legacy Observing Network: Supporting Research to Applications for Atmospheric Rivers and Beyond
Previous Article in Journal
Gravity Waves in Planetary Atmospheres: Their Effects and Parameterization in Global Circulation Models
Open AccessArticle

New Algorithm for Rain Cell Identification and Tracking in Rainfall Event Analysis

1
Information Center (Hydrology Monitor and Forecast Center), Ministry of Water Resources, Beijing 100053, China
2
Institute of Geographical Sciences, Free University of Berlin, 12249 Berlin, Germany
3
hydro&metro GmbH&Co.KG, 23552 Lubeck, Germany
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(9), 532; https://doi.org/10.3390/atmos10090532
Received: 29 July 2019 / Revised: 30 August 2019 / Accepted: 4 September 2019 / Published: 10 September 2019
(This article belongs to the Section Climatology and Meteorology)
This study proposes a new algorithm termed rain cell identification and tracking (RCIT) to identify and track rain cells from high resolution weather radar data. Previous algorithms have limitations when tracking non-consequent rain cells owing to their use of maximum correlation coefficient methods and their lack of an alternative way to handle the variation stages of rain cells during their life cycles. To address these deficiencies, various methods are implemented in the new algorithm. These include the particle image velocimetry (PIV) method for motion estimation and the rain cell matching rule to obtain the stage changes of rain cells. High resolution (5 min and 1 km) radar data from three rainy days over the German federal state North Rhine Westphalia (NRW) are used in this study. The performance of the identification module for the new algorithm is accessed by two object-oriented verification methods: structure–amplitude–location (SAL) and geometric index, while the performance of the tracking module is compared with TREC and SCOUT tracking algorithms and evaluated by the contingency table verification approach. Results suggest that the performance of the new algorithm is better than reference tracking method. Application of the RCIT algorithm to the selected cases shows that the inner structure of rainfall events in the experimental region present extreme value distributions, with most rainfall events having a short duration with less intensity. The new algorithm can effectively capture the stage changes of rain cells during their life cycles. The proposed algorithm can serve as the basis for further hydro-meteorological applications such as spatial and temporal analysis of rainfall events and short-term flood forecasting. View Full-Text
Keywords: rain cell; tracking; PIV; feature-based verification rain cell; tracking; PIV; feature-based verification
Show Figures

Figure 1

MDPI and ACS Style

He, T.; Einfalt, T.; Zhang, J.; Hua, J.; Cai, Y. New Algorithm for Rain Cell Identification and Tracking in Rainfall Event Analysis. Atmosphere 2019, 10, 532.

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.

Article Access Map by Country/Region

1
Back to TopTop