The Interdependence between Rainfall and Temperature: Copula Analyses
Cong, Ronggang LU and Brady, Mark LU
(2012)
In The Scientific World Journal
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3327866
- author
- Cong, Ronggang
LU
and Brady, Mark
LU
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- in
- The Scientific World Journal
- article number
- 405675
- publisher
- Hindawi Limited
- external identifiers
-
- wos:000311456800001
- pmid:23213286
- scopus:84871360142
- pmid:23213286
- ISSN
- 2356-6140
- DOI
- 10.1100/2012/405675
- language
- English
- LU publication?
- yes
- id
- 097489ec-5deb-483a-b0d7-533a9fcc931b (old id 3327866)
- date added to LUP
- 2016-04-01 10:12:27
- date last changed
- 2023-12-22 21:14:01
@article{097489ec-5deb-483a-b0d7-533a9fcc931b,
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.}},
author = {{Cong, Ronggang and Brady, Mark}},
issn = {{2356-6140}},
language = {{eng}},
publisher = {{Hindawi Limited}},
series = {{The Scientific World Journal}},
title = {{The Interdependence between Rainfall and Temperature: Copula Analyses}},
url = {{https://lup.lub.lu.se/search/files/1651853/3327867.pdf}},
doi = {{10.1100/2012/405675}},
year = {{2012}},
}