Statistical Evaluation of Predicted Maximum and Minimum Temperatures with CLIGEN Climate Model

Abstract

Climate simulation models are widely used in generating estimated daily data to be used in climate change, soil erosion, water holding capacity, water quality, product development, and many other studies. Climate models are used to simulate the impact of future climate smülations in cases when long-term measured data is not sufficient, the measured data contain erroneous records since the collection of observed data is costly or requires a lot of time. Most climate models predict one or more climate variables such as wind speed, relative humidity, solar radiation, temperature, and precipitation. Climate models such as the CLIGEN, USCLIMATE and the WXGEN create max and min temperature values using the standard normal distribution. In the present study, the CLIGEN climate model was used to simulate the long-term average temperature data for Kayseri, Sivas, and Yozgat meteorologic stations. The compliance of both observed and simulated data with the normal distribution was determined by the Kolmogorov-Smirnov test. It was observed that the maximum and minimum temperature values did not conform to the normal distribution, and the skew value was negative for almost all months. It was found that the CLIGEN simulated above the observed value for the summer months and the values obtained for some months showed the normal distribution.

Keywords

• CLIGEN
• Climate
• Kolmogorov-Smirnov
• Simulation
• Temperature

Kaynakça

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