Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation

The purpose of this study is to develop and validate an algorithm for tracking and forecasting radiative and morphological characteristics of mesoscale convective systems (MCSs) through their entire life cycles using geostationary satellite thermal channel information (10.8 μm). The main features of...

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Autores principales: Vila, Daniel Alejandro, Velasco, Inés
Publicado: 2008
Materias:
Atmospheric radiation
Clouds
Geostationary satellites
Satellite imagery
Cloud cluster detection method
Geostationary satellite thermal channel information
Mesoscale convective systems (MCSs)
Weather forecasting
algorithm
convective cloud
convective system
geostationary satellite
infrared imagery
mesoscale meteorology
satellite imagery
statistical analysis
tracking
weather forecasting
South America
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_08828156_v23_n2_p233_Vila
http://hdl.handle.net/20.500.12110/paper_08828156_v23_n2_p233_Vila
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_08828156_v23_n2_p233_Vila
record_format dspace
spelling paper:paper_08828156_v23_n2_p233_Vila2023-06-08T15:46:25Z Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation Vila, Daniel Alejandro Velasco, Inés Atmospheric radiation Clouds Geostationary satellites Satellite imagery Cloud cluster detection method Geostationary satellite thermal channel information Mesoscale convective systems (MCSs) Weather forecasting algorithm convective cloud convective system geostationary satellite infrared imagery mesoscale meteorology satellite imagery statistical analysis tracking weather forecasting South America The purpose of this study is to develop and validate an algorithm for tracking and forecasting radiative and morphological characteristics of mesoscale convective systems (MCSs) through their entire life cycles using geostationary satellite thermal channel information (10.8 μm). The main features of this system are the following: 1) a cloud cluster detection method based on a threshold temperature (235 K), 2) a tracking technique based on MCS overlapping areas in successive images, and 3) a forecast module based on the evolution of each particular MCS in previous steps. This feature is based on the MCS's possible displacement (considering the center of the mass position of the cloud cluster in previous time steps) and its size evolution. Statistical information about MCS, evolution during the Wet Season Atmospheric Mesoscale Campaign (WETAMC) of the Large-Scale Biosphere-Atmosphere. Experiment in Amazonia (LBA) was used to obtain area expansion mean rates for different MCSs according to their lifetime durations. This nowcasting tool was applied to evaluate the MCS displacement and size evolution over the Del Plata basin in South America up to 120 min with 30-min intervals. The Forecast and Tracking the Evolution of Cloud Clusters (ForTraCC) technique's performance was evaluated based on the difference between the forecasted and observed images. This evaluation shows good agreement between the observed and forecast size and minimum temperature for shorter forecast lead times, but tends to underestimate MCS size (and overestimate the minimum temperature) for larger forecast lead times. © 2008 American Meteorological Society. Fil:Vila, D.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Velasco, I. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2008 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_08828156_v23_n2_p233_Vila http://hdl.handle.net/20.500.12110/paper_08828156_v23_n2_p233_Vila
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Atmospheric radiation
Clouds
Geostationary satellites
Satellite imagery
Cloud cluster detection method
Geostationary satellite thermal channel information
Mesoscale convective systems (MCSs)
Weather forecasting
algorithm
convective cloud
convective system
geostationary satellite
infrared imagery
mesoscale meteorology
satellite imagery
statistical analysis
tracking
weather forecasting
South America
spellingShingle Atmospheric radiation
Clouds
Geostationary satellites
Satellite imagery
Cloud cluster detection method
Geostationary satellite thermal channel information
Mesoscale convective systems (MCSs)
Weather forecasting
algorithm
convective cloud
convective system
geostationary satellite
infrared imagery
mesoscale meteorology
satellite imagery
statistical analysis
tracking
weather forecasting
South America
Vila, Daniel Alejandro
Velasco, Inés
Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation
topic_facet Atmospheric radiation
Clouds
Geostationary satellites
Satellite imagery
Cloud cluster detection method
Geostationary satellite thermal channel information
Mesoscale convective systems (MCSs)
Weather forecasting
algorithm
convective cloud
convective system
geostationary satellite
infrared imagery
mesoscale meteorology
satellite imagery
statistical analysis
tracking
weather forecasting
South America
description The purpose of this study is to develop and validate an algorithm for tracking and forecasting radiative and morphological characteristics of mesoscale convective systems (MCSs) through their entire life cycles using geostationary satellite thermal channel information (10.8 μm). The main features of this system are the following: 1) a cloud cluster detection method based on a threshold temperature (235 K), 2) a tracking technique based on MCS overlapping areas in successive images, and 3) a forecast module based on the evolution of each particular MCS in previous steps. This feature is based on the MCS's possible displacement (considering the center of the mass position of the cloud cluster in previous time steps) and its size evolution. Statistical information about MCS, evolution during the Wet Season Atmospheric Mesoscale Campaign (WETAMC) of the Large-Scale Biosphere-Atmosphere. Experiment in Amazonia (LBA) was used to obtain area expansion mean rates for different MCSs according to their lifetime durations. This nowcasting tool was applied to evaluate the MCS displacement and size evolution over the Del Plata basin in South America up to 120 min with 30-min intervals. The Forecast and Tracking the Evolution of Cloud Clusters (ForTraCC) technique's performance was evaluated based on the difference between the forecasted and observed images. This evaluation shows good agreement between the observed and forecast size and minimum temperature for shorter forecast lead times, but tends to underestimate MCS size (and overestimate the minimum temperature) for larger forecast lead times. © 2008 American Meteorological Society.
author Vila, Daniel Alejandro
Velasco, Inés
author_facet Vila, Daniel Alejandro
Velasco, Inés
author_sort Vila, Daniel Alejandro
title Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation
title_short Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation
title_full Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation
title_fullStr Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation
title_full_unstemmed Forecast and tracking the evolution of cloud clusters (ForTraCC) using satellite infrared imagery: Methodology and validation
title_sort forecast and tracking the evolution of cloud clusters (fortracc) using satellite infrared imagery: methodology and validation
publishDate 2008
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_08828156_v23_n2_p233_Vila
http://hdl.handle.net/20.500.12110/paper_08828156_v23_n2_p233_Vila
work_keys_str_mv AT viladanielalejandro forecastandtrackingtheevolutionofcloudclustersfortraccusingsatelliteinfraredimagerymethodologyandvalidation
AT velascoines forecastandtrackingtheevolutionofcloudclustersfortraccusingsatelliteinfraredimagerymethodologyandvalidation
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