Sammanfattning

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.

Publicerad i

Scientific World Journal
2012, Volym: 2012, nummer: Article ID 405675, artikelnummer: 405675

SLU författare

• Brady, Mark

  • Institutionen för ekonomi, Sveriges lantbruksuniversitet
    

Globala målen

SDG13 Vidta omedelbara åtgärder för att bekämpa klimatförändringarna och dess konsekvenser
SDG2 Avskaffa hunger, uppnå tryggad livsmedelsförsörjning och förbättrad nutrition samt främja ett hållbart jordbruk


UKÄ forskningsämne

Nationalekonomi


Publikationens identifierare

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

Permanent länk till denna sida (URI)

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