Inter-Research > CR > v25 > n2 > p109-119  
Climate Research

via Mailchimp

CR 25:109-119 (2003)  -  doi:10.3354/cr025109

Minimum data requirements for parameter estimation of stochastic weather generators

Afshin Soltani1,*, Gerrit Hoogenboom2

1Department of Agronomy and Plant Breeding, Gorgan University of Agricultural Sciences, Gorgan, Iran
2Department of Biological and Agricultural Engineering, The University of Georgia, Griffin, Georgia 30223, USA

ABSTRACT: Long-term daily weather data are commonly required for the application of simulation models in agricultural systems. The objective of this study was to evaluate the impact of the length of input weather data on the quality of generated weather data and to determine the minimum data required for an accurate estimation of the climate coefficients for a weather generator. Five locations in Iran with contrasting climates were selected for this study. The WGEN and SIMMETEO weather generators were parameterized using 5, 10, 15, 20 and 30 yr of weather data as the base period (BP), and then 30 yr daily weather data sets were generated corresponding to each BP. While WGEN requires daily weather data for parameter estimation, SIMMETEO uses monthly summaries. The quality of the generated weather was measured as percentage significant differences between observed and generated data. Statistical tests were conducted, including t- and F-tests, to compare differences between generated weather data versus 30 yr historical weather data. The results showed that the number of years required to obtain generated data that were similar to observed data was a function of the weather generator and the weather variable. WGEN was more sensitive to the amount of input data than SIMMETEO. In 8 of the 14 cases WGEN required a specific minimum amount of data to be efficient in weather generation versus 6 of the 14 cases for SIMMETEO. There was a correlation between generator performance and its minimum data requirement. For the cases where the generators showed a good performance, i.e. low-percentage significant differences between observed and generated data, a specific minimum number of years was required. For generating precipitation, a smaller number of years was required than for generating temperature. Based on the results from this study, it can be concluded that at least 15 yr of input data are needed for WGEN and SIMMETEO to obtain generated sequences with statistical characteristics similar to the observed data. However, a greater length of input data may lead to an improved set of generated data as shown through more stable generated data.

KEY WORDS: Weather generation · Weather data · Climate · Simulation models · Decision support systems

Full text in pdf format