Abstract

Rainfall and temperature are important climatic inputs for agricultural production, especially in the context of climate change. However, accurate analysis and simulation of the joint distribution of rainfall and temperature are difficult due to possible interdependence between them. As one possible approach to this problem, five families of copula models are employed to model the interdependence between rainfall and temperature. Scania is a leading agricultural province in Sweden and is affected by a maritime climate. Historical climatic data for Scania is used to demonstrate the modeling process. Heteroscedasticity and autocorrelation of sample data are also considered to eliminate the possibility of observation error. The results indicate that for Scania there are negative correlations between rainfall and temperature for the months from April to July and September. The student copula is found to be most suitable to model the bivariate distribution of rainfall and temperature based on the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Using the student copula, we simulate temperature and rainfall simultaneously. The resulting models can be integrated with research on agricultural production and planning to study the effects of changing climate on crop yields.

Published in

Scientific World Journal
2012, Volume: 2012, number: Article ID 405675, article number: 405675

SLU Authors

• Brady, Mark

  • Department of Economics, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

Take urgent action to combat climate change and its impacts
End hunger, achieve food security and improved nutrition and promote sustainable agriculture


UKÄ Subject classification

Economics


Publication identifier

DOI: https://doi.org/10.1100/2012/405675

Permanent link to this page (URI)

https://res.slu.se/id/publ/39439