dor_id: 4120240
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/8575/8045
100.1.#.a: Gay, Carlos; Estrada, F.; Conde Álvarez, C.
524.#.#.a: Gay, Carlos, et al. (2007). Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México. Atmósfera; Vol. 20 No. 2, 2007. Recuperado de https://repositorio.unam.mx/contenidos/4120240
245.1.0.a: Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México
502.#.#.c: Universidad Nacional Autónoma de México
561.1.#.a: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
264.#.0.c: 2007
264.#.1.c: 2009-10-05
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/8575
001.#.#.#: 022.oai:ojs.pkp.sfu.ca:article/8575
041.#.7.h: eng
520.3.#.a: The common practice of using 30-year sub-samples of climatological data for describing past, present and future conditions has been widely applied, in many cases without considering the properties of the time series analyzed. This paper shows that this practice can lead to an inefficient use of the information contained in the data and to an inaccurate characterization of present, and especially future, climatological conditions because parameters are time and sub-sample size dependent. Furthermore, this approach can lead to the detection of spurious changes in distribution parameters. The time series analysis of observed monthly temperature in Veracruz, México, is used to illustrate the fact that these techniques permit to make a better description of the mean and variability of the series, which in turn allows (depending on the class of process) to restrain uncertainty of forecasts, and therefore provides a better estimation of present and future risk of observing values outside a given coping range. Results presented in this paper show that, although a significant trend is found in the temperatures, giving possible evidence of observed climate change in the region, there is no evidence to support changes in the variability of the series and therefore there is neither observed evidence to support that monthly temperature variability will increase (or decrease) in the future. That is, if climate change is already occurring, it has manifested itself as a change-in-the-mean of these processes and has not affected other moments of their distributions (homogeneous non-stationary processes). The Magicc-Scengen, a software useful for constructing climate change scenarios, uses 20-year sub-samples to estimate future climate variability. For comparison purposes, possible future probability density functions are constructed following two different approaches: one, using solely the Magicc-Scengen output, and another one using a combination of this information and the time series analysis. It is shown that sub-sample estimations can lead to an inaccurate estimation of the potential impacts of present climate variability and of climate change scenarios in terms of the probabilities of obtaining values outside a given coping range.
773.1.#.t: Atmósfera; Vol. 20 No. 2 (2007)
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
264.#.1.b: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
handle: 00ae08c271c56cb1
harvesting_date: 2023-06-20 16:00:00.0
856.#.0.q: application/pdf
file_creation_date: 2007-04-09 19:05:18.0
file_modification_date: 2007-04-12 18:43:06.0
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245.1.0.b: Some implications ot time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México
last_modified: 2023-06-20 16:00:00
license_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode.es
license_type: by-nc
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