Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México
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| Format: | Artículo científico |
| Language: | en |
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Universidad Nacional Autónoma de México
2007
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| _version_ | 1876470889620439040 |
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| author | F. Estrada |
| author_facet | F. Estrada |
| contents | Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México F. Estrada C. Gay C. Conde Biología The common practice of using 30-year sub-samples of climatological data for describing past, present andfuture conditions has been widely applied, in many cases without considering the properties of the time seriesanalyzed. This paper shows that this practice can lead to an inefficient use of the information contained in thedata and to an inaccurate characterization of present, and especially future, climatological conditions becauseparameters are time and sub-sample size dependent. Furthermore, this approach can lead to the detection ofspurious changes in distribution parameters. The time series analysis of observed monthly temperature inVeracruz, México, is used to illustrate the fact that these techniques permit to make a better description ofthe mean and variability of the series, which in turn allows (depending on the class of process) to restrainuncertainty of forecasts, and therefore provides a better estimation of present and future risk of observingvalues outside a given coping range. Results presented in this paper show that, although a significant trendis found in the temperatures, giving possible evidence of observed climate change in the region, there is noevidence to support changes in the variability of the series and therefore there is neither observed evidenceto support that monthly temperature variability will increase (or decrease) in the future. That is, if climatechange is already occurring, it has manifested itself as a change-in-the-mean of these processes and has notaffected 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 futureclimate variability. For comparison purposes, possible future probability density functions are constructedfollowing two different approaches: one, using solely the Magicc-Scengen output, and another one usinga combination of this information and the time series analysis. It is shown that sub-sample estimations canlead to an inaccurate estimation of the potential impacts of present climate variability and of climate changescenarios in terms of the probabilities of obtaining values outside a given coping range 2007 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56520203 en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.2 Vol.20 |
| format | Artículo científico |
| id | redalyc_56520203 |
| institution | Redalyc |
| language | en |
| publishDate | 2007 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México F. Estrada Biología Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México F. Estrada C. Gay C. Conde Biología The common practice of using 30-year sub-samples of climatological data for describing past, present andfuture conditions has been widely applied, in many cases without considering the properties of the time seriesanalyzed. This paper shows that this practice can lead to an inefficient use of the information contained in thedata and to an inaccurate characterization of present, and especially future, climatological conditions becauseparameters are time and sub-sample size dependent. Furthermore, this approach can lead to the detection ofspurious changes in distribution parameters. The time series analysis of observed monthly temperature inVeracruz, México, is used to illustrate the fact that these techniques permit to make a better description ofthe mean and variability of the series, which in turn allows (depending on the class of process) to restrainuncertainty of forecasts, and therefore provides a better estimation of present and future risk of observingvalues outside a given coping range. Results presented in this paper show that, although a significant trendis found in the temperatures, giving possible evidence of observed climate change in the region, there is noevidence to support changes in the variability of the series and therefore there is neither observed evidenceto support that monthly temperature variability will increase (or decrease) in the future. That is, if climatechange is already occurring, it has manifested itself as a change-in-the-mean of these processes and has notaffected 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 futureclimate variability. For comparison purposes, possible future probability density functions are constructedfollowing two different approaches: one, using solely the Magicc-Scengen output, and another one usinga combination of this information and the time series analysis. It is shown that sub-sample estimations canlead to an inaccurate estimation of the potential impacts of present climate variability and of climate changescenarios in terms of the probabilities of obtaining values outside a given coping range 2007 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56520203 en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.2 Vol.20 |
| title | Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, México |
| topic | Biología |
| url | https://www.redalyc.org/articulo.oa?id=56520203 |