Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba

The Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extrem...

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Main Authors: Tahimy Fuentes-Alvarez, Pedro M. González-Jardines, José C. Fernández-Alvarez, Laura de la Torre, Juan A. Añel
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Climate
Subjects:
Online Access:https://www.mdpi.com/2225-1154/11/10/209
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author Tahimy Fuentes-Alvarez
Pedro M. González-Jardines
José C. Fernández-Alvarez
Laura de la Torre
Juan A. Añel
author_facet Tahimy Fuentes-Alvarez
Pedro M. González-Jardines
José C. Fernández-Alvarez
Laura de la Torre
Juan A. Añel
author_sort Tahimy Fuentes-Alvarez
collection DOAJ
description The Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extreme weather events, such as tropical storms and hurricanes, some of them worsened by climate change. This research analyzes the effectiveness of the GDI in detecting the potential for convective cloud development, using forecast data from the Weather Research and Forecasting (WRF) model for Western Cuba. To accomplish this, here, we evaluated the performance of the GDI in ten study cases from the dry and wet seasons. As part of our study, we researched how GDI correlates with brightness temperatures (BTs) measured using GOES-16. In addition, the GDI results with the WRF model are compared with results using the Global Forecast System (GFS). Our results show a high correlation between the GDI and BT, concluding that the GDI is a robust tool for forecasting both synoptic and mesoscale convective phenomena over the region studied. In addition, the GDI is able to adequately forecast stability conditions. Finally, the GDI values computed from the WRF model perform much better than those from the GFS, probably because of the greater horizontal resolution in the WRF model.
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spelling doaj.art-d2fe5f2781a24db0939216a57f9f7db72023-11-19T16:07:08ZengMDPI AGClimate2225-11542023-10-01111020910.3390/cli11100209Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western CubaTahimy Fuentes-Alvarez0Pedro M. González-Jardines1José C. Fernández-Alvarez2Laura de la Torre3Juan A. Añel4Facultad de Ciencias del Mar, Universidad de Las Palmas de Gran Canaria, 35017 Las Palmas de Gran Canaria, SpainCentro de Física de la Atmósfera, Instituto de Meteorología, Casablanca, La Habana 10400, CubaCentro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus As Lagoas s/n, 32004 Ourense, SpainCentro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus As Lagoas s/n, 32004 Ourense, SpainCentro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus As Lagoas s/n, 32004 Ourense, SpainThe Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extreme weather events, such as tropical storms and hurricanes, some of them worsened by climate change. This research analyzes the effectiveness of the GDI in detecting the potential for convective cloud development, using forecast data from the Weather Research and Forecasting (WRF) model for Western Cuba. To accomplish this, here, we evaluated the performance of the GDI in ten study cases from the dry and wet seasons. As part of our study, we researched how GDI correlates with brightness temperatures (BTs) measured using GOES-16. In addition, the GDI results with the WRF model are compared with results using the Global Forecast System (GFS). Our results show a high correlation between the GDI and BT, concluding that the GDI is a robust tool for forecasting both synoptic and mesoscale convective phenomena over the region studied. In addition, the GDI is able to adequately forecast stability conditions. Finally, the GDI values computed from the WRF model perform much better than those from the GFS, probably because of the greater horizontal resolution in the WRF model.https://www.mdpi.com/2225-1154/11/10/209GDIthermodynamics indexconvective cloudsbrightness temperatureWRFGFS
spellingShingle Tahimy Fuentes-Alvarez
Pedro M. González-Jardines
José C. Fernández-Alvarez
Laura de la Torre
Juan A. Añel
Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba
Climate
GDI
thermodynamics index
convective clouds
brightness temperature
WRF
GFS
title Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba
title_full Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba
title_fullStr Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba
title_full_unstemmed Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba
title_short Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba
title_sort analysis of the galvez davison index for the forecasting formation and evolution of convective clouds in the tropics western cuba
topic GDI
thermodynamics index
convective clouds
brightness temperature
WRF
GFS
url https://www.mdpi.com/2225-1154/11/10/209
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