Impact of Multi-Thresholds and Vector Correction for Tracking Precipitating Systems over the Amazon Basin

Impact of Multi-Thresholds and Vector Correction for Tracking Precipitating Systems over the Amazon Basin

Different algorithms for forecasting and tracking meteorological systems have been developed over the years. Many of them are used to study cloud propagation, precipitation and lightning for nowcasting. Therefore, it is necessary to define carefully the parameters (e.g., intensity thresholds and min...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 14; no. 21; p. 5408
Main Authors: Leal, Helvecio B., Calheiros, Alan J. P., Barbosa, Henrique M. J., Almeida, Adriano P., Sanchez, Arturo, Vila, Daniel A., Garcia, Sâmia R., Macau, Elbert E. N.
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-11-2022
Subjects:
Algorithms
Amazon precipitating systems
Convection
Dry season
Methods
Morphology
Nowcasting
Parameters
Precipitation
Propagation
Rain
Rainfall
Rainy season
Remote sensing
Seasons
Thresholds
Tracking
tracking corrections
Weather forecasting
Amazon Basin
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Summary:Different algorithms for forecasting and tracking meteorological systems have been developed over the years. Many of them are used to study cloud propagation, precipitation and lightning for nowcasting. Therefore, it is necessary to define carefully the parameters (e.g., intensity thresholds and minimum size) that impact tracking of these variables. In order to represent the physical aspects of rain propagation over the Amazon region, several methods of correction and displacement detection were studied. Different parameters were used to validate the methods based on the extrapolated rain cell. A probability detection of 78.4% and 68.6% was achieved for 20 dBZ thresholds during the wet and dry season, respectively. However, the POD decreases for higher reflectivity thresholds. The results for corrections by Inner Nuclei showed that embedded convection can dictate the propagation of rain cells. Split and merge corrections performed well; however, they applied only to a few cases. Corrections performed better for precipitating systems with larger areas and longer duration. The correction methods showed similar skills for both seasons. Which shows that they are able to monitor rain cells throughout the year. The automated combination of different methods for the 20 dBZ threshold proved to be the best choice for tracking rainfall in the Amazon region.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14215408