dor_id: 4120098

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

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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/52804/46742

100.1.#.a: Martínez-sabari, Evelyn Elisa; García-reynoso, José Agustín

524.#.#.a: Martínez-sabari, Evelyn Elisa, et al. (2021). Meteorological data assimilation for air quality modeling with WRF-Chem: Central Mexico case study. Atmósfera; Vol. 34 No. 3, 2021; 311-336. Recuperado de https://repositorio.unam.mx/contenidos/4120098

720.#.#.a: Conacyt

245.1.0.a: Meteorological data assimilation for air quality modeling with WRF-Chem: Central Mexico case study

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

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

264.#.0.c: 2021

264.#.1.c: 2021-06-30

653.#.#.a: WRFDA; WRF-Chem; 3DVAR; meteorological data assimilation

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/52804

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041.#.7.h: eng

520.3.#.a: Meteorological data assimilation from surface observations (PREPBUFR) and satellite radiance (BUFR) provided by the National Centers for Environmental Prediction (NCEP) is carried out to determine their possible influence on chemical variables concentrations such as ozone (O3), obtained from air quality modeling over central Mexico using the photochemical Weather Research and Forecasting Model with Chemistry (WRF-Chem) during a bad-pollution event due to high O3 concentrations in the Mexico City Metropolitan Area on May 1-4, 2013. For this, the Weather Research and Forecasting Data Assimilation (WRFDA) module was adapted to run with WRF-Chem, and the 3DVAR assimilation technique (which is implemented in the WRFDA) was selected. Six study cases were defined taking into account the combination of the data source type with the assimilation process start times (00:00 and 12:00 UTC). Results indicate that independently of these factors, data assimilation modifies in general the meteorological variables (temperature and wind) initial conditions to obtain a better agreement between model simulations and observations, although statistics results are even higher when the process starts at 12:00 UTC using a combination of PREPBUFR and BUFR data (PB+RD cases). It was also verified that there is an influence on O3 concentrations since the statistical metrics obtained for the different experiments carried out are modified; however, it is insufficient to considerably improve the chemical variable model performance.

773.1.#.t: Atmósfera; Vol. 34 No. 3 (2021); 311-336

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: 311-336

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

doi: https://doi.org/10.20937/ATM.52804

handle: 008a2e5ec2a79cdd

harvesting_date: 2023-06-20 16:00:00.0

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last_modified: 2023-06-20 16:00:00

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Artículo

Meteorological data assimilation for air quality modeling with WRF-Chem: Central Mexico case study

Martínez-sabari, Evelyn Elisa; García-reynoso, José Agustín

Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM, publicado en Atmósfera, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Entidad o dependencia
Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
Revista
Repositorio
Contacto
Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

Cita

Martínez-sabari, Evelyn Elisa, et al. (2021). Meteorological data assimilation for air quality modeling with WRF-Chem: Central Mexico case study. Atmósfera; Vol. 34 No. 3, 2021; 311-336. Recuperado de https://repositorio.unam.mx/contenidos/4120098

Descripción del recurso

Autor(es)
Martínez-sabari, Evelyn Elisa; García-reynoso, José Agustín
Colaborador(es)
Conacyt
Tipo
Artículo de Investigación
Área del conocimiento
Físico Matemáticas y Ciencias de la Tierra
Título
Meteorological data assimilation for air quality modeling with WRF-Chem: Central Mexico case study
Fecha
2021-06-30
Resumen
Meteorological data assimilation from surface observations (PREPBUFR) and satellite radiance (BUFR) provided by the National Centers for Environmental Prediction (NCEP) is carried out to determine their possible influence on chemical variables concentrations such as ozone (O3), obtained from air quality modeling over central Mexico using the photochemical Weather Research and Forecasting Model with Chemistry (WRF-Chem) during a bad-pollution event due to high O3 concentrations in the Mexico City Metropolitan Area on May 1-4, 2013. For this, the Weather Research and Forecasting Data Assimilation (WRFDA) module was adapted to run with WRF-Chem, and the 3DVAR assimilation technique (which is implemented in the WRFDA) was selected. Six study cases were defined taking into account the combination of the data source type with the assimilation process start times (00:00 and 12:00 UTC). Results indicate that independently of these factors, data assimilation modifies in general the meteorological variables (temperature and wind) initial conditions to obtain a better agreement between model simulations and observations, although statistics results are even higher when the process starts at 12:00 UTC using a combination of PREPBUFR and BUFR data (PB+RD cases). It was also verified that there is an influence on O3 concentrations since the statistical metrics obtained for the different experiments carried out are modified; however, it is insufficient to considerably improve the chemical variable model performance.
Tema
WRFDA; WRF-Chem; 3DVAR; meteorological data assimilation
Idioma
eng
ISSN
ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236

Enlaces