EVALUATION OF RADIATION AND TEMPERATURE DATA GENERATORS IN THE AUSTRALIAN TROPICS AND SUBTROPICS USING CROP SIMULATION-MODELS

Long-term, historical weather data are needed to conduct crop simulation analyses. However, the network of weather recording stations which collect all necessary daily weather data (commonly rainfall, solar radiation, maximum and minimum temperature) for such analyses is sparse. Frequently only rainfall is recorded. Thus, weather data generation techniques are required for three situations: (i) where only rainfall data are available, (ii) where both rainfall and temperature data are available, but radiation is missing, and (iii) where records are otherwise complete, but techniques are required to fill short periods of missing data. Three weather generation techniques are compared, termed here (i) Bristow and Campbell's method, (ii) TAMSIM and (iii) WGEN. Methods (ii) and (iii) were used to generate temperature and radiation data to accompany recorded rainfall records, and methods (i)-(iii) to generate a solar radiation record to accompany recorded temperature and rainfall records. Data from four stations in tropical and subtropical Australia with long-term complete weather records were used to compare actual with generated data sets. Results were evaluated firstly by comparing the cumulative distribution function (CDF) of generated and actual values, and secondly by comparing CDFs calculated from the output of three crop simulation models used with the generated and actual data sets. Generally the distributions of radiation and temperature differed significantly. However, when the weather data sets were used by simulation models to estimate biomass, only 10 of the 50 CDFs differed significantly. When both temperature and radiation were generated, 30% of CDFs from TAMSIM and 20% of WGEN differed significantly. When only radiation was generated, 40% of CDFs generated by the Bristow and Campbell's method, 10% of WGEN and none of TAMSIM differed significantly. All methods simulated the more temperate sites with higher precision than the wet, tropical site. Simulated yields showed a similar pattern. It was concluded that where both temperature and radiation data have to be generated, WGEN is appropriate because it contains a stochastic element and thus simulates catastrophic events such as frosts. Where only radiation generation is required, both WGEN and TAMSIM performed adequately. Where temperature or radiation data sets are complete except for occasional missing days, TAMSIM was considered to be the most appropriate. In cases were the objective is not to conduct long-term simulation analyses, Bristow and Campbell's method appeared more appropriate because of its ability to better simulate the day to day variation in solar radiation.