Modeling the Historical Temperature in the Province of Laguna Using Ornstein-Uhlenbeck Process

Authors

  • Kemuel III Quindala Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños
  • Diane Carmeliza Cuaresma Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños
  • Jonathan Mamplata Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños https://orcid.org/0000-0001-6867-3728

DOI:

https://doi.org/10.29020/nybg.ejpam.v14i1.3911

Keywords:

Temperature, Laguna, Ornstein-Uhlenbeck process

Abstract

The behavior of temperature is one of the major factors in the study of climate change which has already invited a lot of researchers and policymakers. These studies help in deciding the best adaptation and mitigation strategy. However, there are little studies on the progression of climate change in a local setting, such as in a municipal or provincial level. This study explored to model, using regression, the daily temperature in the province of Laguna. The daily maximum and minimum temperature from 1960 to 2018 were modeled using the classical Ornstein-Uhlenbeck (OU) process with additive seasonality. The model showed that the province saw an increase of $1.16^\circ$C (resp. $0.55^\circ$C) in the mean daily minimum (resp. maximum) temperature from 1960 to 2018. It was also found that minimum temperature showed a steadier increase than maximum temperature, which poses threats to agricultural activities. Consistent with other international predictions, there was a $0.02^\circ$C annual increase in 1960 to a $0.05^\circ$C starting in 2010.  The proposed model can be used by authorities in designing and creating adaptive measures that would be more effective to the province of Laguna.

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Published

2021-01-31

Issue

Section

Nonlinear Analysis

How to Cite

Modeling the Historical Temperature in the Province of Laguna Using Ornstein-Uhlenbeck Process. (2021). European Journal of Pure and Applied Mathematics, 14(1), 327-339. https://doi.org/10.29020/nybg.ejpam.v14i1.3911

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