NDLI: The Interdependence between Rainfall and Temperature: Copula Analyses

Content Provider	PubMed Central
Author	Cong, Rong-gang Brady, Mark
Copyright Year	2012
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.
Related Links	http://dx.doi.org/10.1100/2012/405675
Starting Page	405675
File Format	PDF
ISSN	1537744X
e-ISSN	1537744X
Journal	The Scientific World Journal
Volume Number	2012
Language	English
Publisher	The Scientific World Journal
Publisher Date	2012-11-13
Access Restriction	Open
Rights Holder	The Scientific World Journal
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Medicine Biochemistry, Genetics and Molecular Biology Environmental Science

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