Next Article in Journal
Detection of Maize Tassels from UAV RGB Imagery with Faster R-CNN
Previous Article in Journal
Maintaining Semantic Information across Generic 3D Model Editing Operations
Previous Article in Special Issue
The Precipitation Structure of the Mediterranean Tropical-Like Cyclone Numa: Analysis of GPM Observations and Numerical Weather Prediction Model Simulations
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Backward Adaptive Brightness Temperature Threshold Technique (BAB3T): A Methodology to Determine Extreme Convective Initiation Regions Using Satellite Infrared Imagery

1
Departamento de Ciencias de la Atmósfera y los Océanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires C1428EGA, Argentina
2
Centro de Investigaciones del Mar y la Atmósfera (CIMA), Instituto Franco Argentino sobre Estudios de Clima y sus Impactos (UMI IFAECI)/CNRS-CONICET, Universidad de Buenos Aires, Buenos Aires C1428EGA, Argentina
3
National Institute for Space Research, INPE/CPTEC, Cachoeira Paulista 12630-000, Brazil
4
Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
5
Servicio Meteorológico Nacional, Buenos Aires C1425GBE, Argentina
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(2), 337; https://doi.org/10.3390/rs12020337
Submission received: 31 October 2019 / Revised: 15 January 2020 / Accepted: 16 January 2020 / Published: 20 January 2020

Abstract

Thunderstorms in southeastern South America (SESA) stand out in satellite observations as being among the strongest on Earth in terms of satellite-based convective proxies, such as lightning flash rate per storm, the prevalence for extremely tall, wide convective cores and broad stratiform regions. Accurately quantifying when and where strong convection is initiated presents great interest in operational forecasting and convective system process studies due to the relationship between convective storms and severe weather phenomena. This paper generates a novel methodology to determine convective initiation (CI) signatures associated with extreme convective systems, including extreme events. Based on the well-established area-overlapping technique, an adaptive brightness temperature threshold for identification and backward tracking with infrared data is introduced in order to better identify areas of deep convection associated with and embedded within larger cloud clusters. This is particularly important over SESA because ground-based weather radar observations are currently limited to particular areas. Extreme rain precipitation features (ERPFs) from Tropical Rainfall Measurement Mission are examined to quantify the full satellite-observed life cycle of extreme convective events, although this technique allows examination of other intense convection proxies such as the identification of overshooting tops. CI annual and diurnal cycles are analyzed and distinctive behaviors are observed for different regions over SESA. It is found that near principal mountain barriers, a bimodal diurnal CI distribution is observed denoting the existence of multiple CI triggers, while convective initiation over flat terrain has a maximum frequency in the afternoon.
Keywords: convective initiation; satellite observations; algorithms; severe weather convective initiation; satellite observations; algorithms; severe weather
Graphical Abstract

Share and Cite

MDPI and ACS Style

Cancelada, M.; Salio, P.; Vila, D.; Nesbitt, S.W.; Vidal, L. Backward Adaptive Brightness Temperature Threshold Technique (BAB3T): A Methodology to Determine Extreme Convective Initiation Regions Using Satellite Infrared Imagery. Remote Sens. 2020, 12, 337. https://doi.org/10.3390/rs12020337

AMA Style

Cancelada M, Salio P, Vila D, Nesbitt SW, Vidal L. Backward Adaptive Brightness Temperature Threshold Technique (BAB3T): A Methodology to Determine Extreme Convective Initiation Regions Using Satellite Infrared Imagery. Remote Sensing. 2020; 12(2):337. https://doi.org/10.3390/rs12020337

Chicago/Turabian Style

Cancelada, Maite, Paola Salio, Daniel Vila, Stephen W. Nesbitt, and Luciano Vidal. 2020. "Backward Adaptive Brightness Temperature Threshold Technique (BAB3T): A Methodology to Determine Extreme Convective Initiation Regions Using Satellite Infrared Imagery" Remote Sensing 12, no. 2: 337. https://doi.org/10.3390/rs12020337

APA Style

Cancelada, M., Salio, P., Vila, D., Nesbitt, S. W., & Vidal, L. (2020). Backward Adaptive Brightness Temperature Threshold Technique (BAB3T): A Methodology to Determine Extreme Convective Initiation Regions Using Satellite Infrared Imagery. Remote Sensing, 12(2), 337. https://doi.org/10.3390/rs12020337

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop