Long-term series of daily weather data are often required for the analysis of weather-impacted systems (e.g., cropping management systems, hydrologic studies, environmental studies, and others). Weather generators are computer programs that use existing weather records to produce long series of synthetic daily climatic data. The statistical properties of the generated data are expected to be similar to those of the actual data. Weather variables required by many applications include precipitation, maximum and minimum temperature, rainfall, solar radiation, wind speed and some measurement of air water vapor (Acock and Acock, 1991). In some cases, records of such variables may be not available, incomplete, insufficient in length, or only summarized in monthly archives. Weather generators are practical tools to bypass those problems (Johnson et al., 1996).
Several computer programs have been developed that are capable of producing stochastically generated weather data from existing daily data. Examples include WGEN (Richardson and Wright, 1984), WXGEN (Sharpley and Williams, 1990), CLIGEN (Arnold and Elliot, 1996), USCLIMATE (Johnson et al., 1996), CLIMAK (Danuso et al., 1997), and ClimGen (Stöckle et al., 1998).
ClimGen, the focus of this article, is a weather generator that uses similar general principles than WGEN, the first and most widely used weather generator in the US, but with significant modifications and additions. ClimGen generates precipitation, daily maximum and minimum temperature, solar radiation, air humidity, and wind speed. It uses a Weibull distribution to generate precipitation amounts instead of the Gamma distribution used by WGEN. The Weibull distribution is easier to parameterize, describes well the distribution of precipitation amounts, and can be simplified for applications to conditions with minimum data. In ClimGen, all generation parameters are calculated for each site of interest while WGEN used fixed coefficients optimized from a large US weather data base. The advantage is that ClimGen can be applied to any world location with enough information to parameterize the program. WGEN uses truncated Fourier series fits to produce daily values for monthly-calculated quantities of mean weather variables. This arbitrarily chosen functional form can lead to relatively poor fit to the data. ClimGen uses quadratic spline functions chosen to ensure that the average of the daily values are continuous across month boundaries, and that the first derivative of the function is continuous across month boundaries.
Other features of ClimGen that are not available in WGEN include the generation of vapor pressure deficit (VPD) and wind speed. In addition, alternative approaches allow users to estimate VPD and solar radiation from existing temperature records.
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