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: https://doi.org/10.1002/env.2550
ISSN: 1099-095X
Appears in Collections:CIDMA - Artigos
ESTGA - Artigos

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