dor_id: 4147271

506.#.#.a: Público

590.#.#.d: Los artículos enviados a la revista "Atmósfera", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Consejo Nacional de Ciencia y Tecnología (CONACyT); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Scientific Electronic Library Online (SciELO); SCOPUS, Web Of Science (WoS); SCImago Journal Rank (SJR)

561.#.#.u: https://www.atmosfera.unam.mx/

650.#.4.x: Físico Matemáticas y Ciencias de la Tierra

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://www.revistascca.unam.mx/atm/index.php/atm/index

351.#.#.b: Atmósfera

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

590.#.#.c: Open Journal Systems (OJS)

270.#.#.d: MX

270.1.#.d: México

590.#.#.b: Concentrador

883.#.#.u: https://revistas.unam.mx/catalogo/

883.#.#.a: Revistas UNAM

590.#.#.a: Coordinación de Difusión Cultural

883.#.#.1: https://www.publicaciones.unam.mx/

883.#.#.q: Dirección General de Publicaciones y Fomento Editorial

850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/53248/46977

100.1.#.a: Da Fonseca Aguiar, Louise; Cataldi, Marcio; Marton, Edilson; Ribeiro, Eric Miguel; Da Cunha Luz, Priscila

524.#.#.a: Da Fonseca Aguiar, Louise, et al. (2024). Evaluation of the SACZ index as a prognostic tool based on GFS forecasts. Atmósfera; Vol. 38, 2024; 91-104. Recuperado de https://repositorio.unam.mx/contenidos/4147271

245.1.0.a: Evaluation of the SACZ index as a prognostic tool based on GFS forecasts

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM

264.#.0.c: 2024

264.#.1.c: 2023-08-01

653.#.#.a: atmospheric modeling; weather forecasting; South Atlantic Convergence Zone

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC 4.0 Internacional, https://creativecommons.org/licenses/by-nc/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico editora@atmosfera.unam.mx

884.#.#.k: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/53248

001.#.#.#: 022.oai:ojs.pkp.sfu.ca:article/53248

041.#.7.h: eng

520.3.#.a: The South Atlantic Convergence Zone (SACZ) is an atmospheric phenomenon typical of summertime where a band of nebulosity causes intense or persistent rainfall in many regions of Brazil. SACZ episodes can be responsible for many natural disasters. Besides, the impacts of rainfall on water availability and consequently on the energy sector are extensive. The main objective of this study was to investigate the implementation of the SACZ index as an objective forecasting tool using input data from the Global Forecast System (GFS) model. Initially, we compared the index with the SACZ events identified by the Center for Weather Forecasting and Climate Studies (CPTEC ) from 2017 to 2021. Results showed that the index represented all events identified SACZs by CPTEC. Finally, we used data from the GFS 0.25 Degree from 2017 to 2021 to calculate Accuracy, Probability of detection, and False alarm ratio to evaluate the SACZ index as a prediction tool. Three thresholds are defined for the binary classification of a possible SACZ event. Results showed that above the most sensitive threshold (h1), within 10 days in advance, the sign of a possible SACZ can be detected. For the intermediate threshold (h2), a forecast of 96 h can detect a sign. For the most specific threshold (h3), the index can detect the event within 72 h in advance with a probability of detection of almost 90%. The SACZ index proved to be an efficient tool for detecting the dynamics of the phenomenon and can be used to assist operationally and in decision-making.

773.1.#.t: Atmósfera; Vol. 38 (2024); 91-104

773.1.#.o: https://www.revistascca.unam.mx/atm/index.php/atm/index

022.#.#.a: ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236

310.#.#.a: Trimestral

300.#.#.a: Páginas: 91-104

264.#.1.b: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM

doi: https://doi.org/10.20937/ATM.53248

harvesting_date: 2023-10-03 16:10:00.0

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