Weather generators (WG) became significant modules of crop models and decision support systems in the past decade. Using a large meteorological database from North America; two basic problems, related to the applicability of WGs in case of short or lacking data series, were investigated in the framework of the Multivariable weather generator (MVWG). First, the minimum data series length, required for adequate parameterization of the WG, was determined. Our results suggest that 15 years of observed data are enough for adequate parameterization of the MVWG. We then investigated a possibility of spatial interpolation of WG parameters using the outputs of the WG for sites with no meteorological observations. Coupled with the presented interpolation technique, MVWG was able to generate realistic weather data for sites with no measurements situated in climatically and geographically homogeneous regions.
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Environmental Science(all)