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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

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336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

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270.#.#.d: MX

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883.#.#.a: Revistas UNAM

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

856.4.0.u: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/ATM.2015.28.02.02/43370

100.1.#.a: Tatli, Hasan

524.#.#.a: Tatli, Hasan (2015). DOWNSCALING STANDARDIZED PRECIPITATION INDEX VIA MODEL OUTPUT STATISTICS. Atmósfera; Vol. 28 No. 2, 2015; 83-98. Recuperado de https://repositorio.unam.mx/contenidos/11142

245.1.0.a: DOWNSCALING STANDARDIZED PRECIPITATION INDEX VIA MODEL OUTPUT STATISTICS

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

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

264.#.0.c: 2015

264.#.1.c: 2015-03-27

653.#.#.a: Climate of Turkey; statistical downscaling; logistic regression; standard precipitation index (SPI)

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/ATM.2015.28.02.02

001.#.#.#: 022.oai:ojs.pkp.sfu.ca:article/42623

041.#.7.h: eng

520.3.#.a: This study investigates the possible impacts of future climate change on meteorological drought events in Turkey by using a new statistical downscaling technique based on polytomous logistic regression, denoted as the model output statistics (MOS) technique. It is designed to downscale the drought classes of the 12-month Standardized Precipitation Index (SPI). The main goal of a downscaling procedure is to determine the influences of large-scale climatic variability and the projected changes on the local scale-regional variables. The large-scale predictors used in this study were obtained from the output of the Second Generation Canadian Coupled General Circulation Model (CGCM2) simulations, run from 1940 to 2100 for three socioeconomic scenarios, namely control, with the constraint of the 20th century atmospheric concentration of greenhouse gases, and the SRES A2 and B2 scenarios. Observations from 96 meteorological stations were used to estimate 12-month SPI values for the period 1940-2010, leaving the last 10 years for validation against the results simulated by the CGCM2. The MOS results derived from the control climate simulation agree with the observed patterns for present climate. The MOS results derived from future climate scenarios lead to conclude that there is a decreased probability of very wet and extremely wet conditions. In addition, the probabilities of near-normal conditions will decrease in the Black Sea coast and will increase towards the Marmara Transition and continental eastern Anatolia regions.

773.1.#.t: Atmósfera; Vol. 28 No. 2 (2015); 83-98

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: 83-98

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

doi: https://doi.org/10.20937/ATM.2015.28.02.02

handle: 00db9e39d3385477

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

856.#.0.q: application/pdf

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

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No entro en nada

No entro en nada 2

Artículo

DOWNSCALING STANDARDIZED PRECIPITATION INDEX VIA MODEL OUTPUT STATISTICS

Tatli, Hasan

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

Tatli, Hasan (2015). DOWNSCALING STANDARDIZED PRECIPITATION INDEX VIA MODEL OUTPUT STATISTICS. Atmósfera; Vol. 28 No. 2, 2015; 83-98. Recuperado de https://repositorio.unam.mx/contenidos/11142

Descripción del recurso

Autor(es)
Tatli, Hasan
Tipo
Artículo de Investigación
Área del conocimiento
Físico Matemáticas y Ciencias de la Tierra
Título
DOWNSCALING STANDARDIZED PRECIPITATION INDEX VIA MODEL OUTPUT STATISTICS
Fecha
2015-03-27
Resumen
This study investigates the possible impacts of future climate change on meteorological drought events in Turkey by using a new statistical downscaling technique based on polytomous logistic regression, denoted as the model output statistics (MOS) technique. It is designed to downscale the drought classes of the 12-month Standardized Precipitation Index (SPI). The main goal of a downscaling procedure is to determine the influences of large-scale climatic variability and the projected changes on the local scale-regional variables. The large-scale predictors used in this study were obtained from the output of the Second Generation Canadian Coupled General Circulation Model (CGCM2) simulations, run from 1940 to 2100 for three socioeconomic scenarios, namely control, with the constraint of the 20th century atmospheric concentration of greenhouse gases, and the SRES A2 and B2 scenarios. Observations from 96 meteorological stations were used to estimate 12-month SPI values for the period 1940-2010, leaving the last 10 years for validation against the results simulated by the CGCM2. The MOS results derived from the control climate simulation agree with the observed patterns for present climate. The MOS results derived from future climate scenarios lead to conclude that there is a decreased probability of very wet and extremely wet conditions. In addition, the probabilities of near-normal conditions will decrease in the Black Sea coast and will increase towards the Marmara Transition and continental eastern Anatolia regions.
Tema
Climate of Turkey; statistical downscaling; logistic regression; standard precipitation index (SPI)
Idioma
eng
ISSN
ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236

Enlaces