dor_id: 4120381
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/52916/46759
100.1.#.a: De Oliveira Filho, Rafael Arcanjo; Barreto Carvalho, Vanessa Silveira; Reboita, Michelle Simões
524.#.#.a: De Oliveira Filho, Rafael Arcanjo, et al. (2022). Evaluating the Global Forecast System (GFS) for energy management over Minas Gerais State (Brazil) against in-situ observations. Atmósfera; Vol. 35 No. 2, 2022; 357-376. Recuperado de https://repositorio.unam.mx/contenidos/4120381
720.#.#.a: Coordination for the Improvement of Higher Education PersonnelNational Institute of MeteorologyNational Oceanic and Atmospheric AdministrationMinas Gerais State Research Support FoundationCnpq
245.1.0.a: Evaluating the Global Forecast System (GFS) for energy management over Minas Gerais State (Brazil) against in-situ observations
502.#.#.c: Universidad Nacional Autónoma de México
561.1.#.a: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
264.#.0.c: 2022
264.#.1.c: 2022-02-14
653.#.#.a: renewable energy; wind power density; GFS analysis
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/52916
001.#.#.#: 022.oai:ojs.pkp.sfu.ca:article/52916
041.#.7.h: eng
520.3.#.a: Several regions of Brazil have experienced periods of intense drought in the last decades. Hydropower plants produce most of the country’s energy and a reduction in reservoir flow can compromise the energy sector. Therefore, the Brazilian government has sought the diversification of energy production with other renewable sources. The introduction of new renewable sources, such as wind and solar, requires detailed studies of the local weather conditions usually through historical data analysis. However, several areas in Brazil lack weather stations. In this context, this study aims to assess the ability of the Global Forecast System (GFS) reanalysis product to represent wind, in the state of Minas Gerais (MG) which has 79.5% of energy production associated with water resources. Although the study considers a specific region, it presents a methodology that can be replicated in regions where data is not available. Over most areas, 10 m wind speed values of the GFS reanalysis were similar to those registered by weather stations. Results at 10 and 100 m of altitude show high wind speed values in the north of the state, a region where the highest power densities are also recorded (approximately 150 W m–2 during winter and spring). In conclusion, the GFS reanalysis product, albeit with the biases reported here, can be used in regions with scarce meteorological data to estimate the potential for wind energy production as a complementary source of hydroelectricity.
773.1.#.t: Atmósfera; Vol. 35 No. 2 (2022); 357-376
773.1.#.o: https://www.revistascca.unam.mx/atm/index.php/atm/index
046.#.#.j: 2021-10-20 00:00:00.000000
022.#.#.a: ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236
310.#.#.a: Trimestral
300.#.#.a: Páginas: 357-376
264.#.1.b: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
doi: https://doi.org/10.20937/ATM.52916
handle: 69afd19983eae8b2
harvesting_date: 2023-06-20 16:00:00.0
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file_creation_date: 2021-02-04 03:12:12.0
file_modification_date: 2021-02-04 03:12:12.0
file_creator: Reviewer
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