African Journal of Environmental Science and Technology Vol.1(4), pp. 086-092, November 2007

ISSN 1996-0786 © 2007 Academic Journals

Full Length Research Paper

Assessment of the ClimGen stochastic weather generator at Cameroon sites

Munang Tingem¹*, Mike Rivington², Sayed Azam-Ali¹ and Jeremy Colls¹

¹Agriculture and Environmental Science Division, School of Bioscience, University of Nottingham, NG7 2RD, UK.

²Macaulay Institute, Craigiebuckler, Aberdeen, AB15 8QH, Scotland UK.

*Corresponding author: E-mail : plxmrt@nottingham.ac.uk . Tel: +44(0)1158466585. Fax: +44(0)1159516261.

Accepted 2 October, 2007

Simulation of agricultural risk assessment and environmental management requires long series of daily weather data for the area being modelled. Acquiring and formatting this data can be very complex and time-consuming. This has led to the development of weather generation procedures and tools. Weather generators can produce time series of synthetic weather data of any length, interpolating observed data to produce synthetic weather data at new sites. Any generator must be tested to ensure that the data that it produces is satisfactory for the purposes for which it is to be used. The aim of this paper is to test a commonly used weather generator, ClimGen (version 4.1.05) at eight sites with contrasting climates in Cameroon. Statistical test were conducted, including t-test and F-test, to compare the differences between generated weather data versus 25 years observed weather data. The results showed that the generated weather series was similar to the observed data for its distribution of monthly precipitation and its variances, monthly means and variance of minimum and maximum air temperatures. Based on the results from this study, it can be concluded that ClimGen performs well in the simulation of weather statistics in Cameroon.

Key words: Weather generators, weather data, Cameroon, climate change.