Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/26279
Title: | A periodic mixed linear state-space model to monthly long-term temperature data |
Author: | Costa, Marco Monteiro, Magda |
Keywords: | Air temperature Climate change Kalman filter Portuguese cities Seasonality Time series analysis |
Issue Date: | Aug-2019 |
Publisher: | Wiley |
Abstract: | In recent decades, the world has been confronted with the consequences of global warming; however, this phenomenon is not reflected equally in every part of the globe. Thus, the warming phenomenon must be monitored in a more regional or local scale. This paper analyzes monthly long-term time series of air temperatures in three Portuguese cities: Lisbon, Oporto and Coimbra. We propose a periodic state space framework, associated with a suitable version of the Kalman filter; which allows for the estimation of monthly warming rates taking into account the seasonal behavior and serial correlation. Results about the monthly mean of the daily mid-range temperature time series show that there are different monthly warming rates. The greatest annual mean rise was found in Oporto with 2.17◦C whereas, in Lisbon and Coimbra, it was respectively, 0.62ºC and 0.55ºC, per century. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/26279 |
DOI: | |
ISSN: | 1099-095X |
Appears in Collections: | CIDMA - Artigos ESTGA - Artigos PSG - Artigos |
Files in This Item:
File | Description | Size | Format | |
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CostaMonteiroEnv2019.pdf | 1.86 MB | Adobe PDF | View/Open |
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