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许多基于物理机制的水文和作物模型需要日序列气象数据来驱动,CLIGEN是为WEPP等模型产生气候输入文件的天气发生器,可以产生10个日序列气象变量来满足这种需要,但是其在中国的适用性需要进行评估。研究的目标是利用黄土高原陕西长武1957~2001年的气象数据评估CLIGEN产生非降水要素(最高温度、最低温度、露点温度、太阳辐射和风速)的能力。结果表明,CLIGEN对最高温度、最低温度和露点温度的模拟效果较好,对太阳辐射和极端气候事件的模拟效果较差,对风速的模拟效果最差。相关性检验表明CLIGEN很好地保持了气象要素的季节性,这对模拟农业生产是非常重要的;但是没有保留气象要素逐日的自相关和互相关性,进而导致产生的温度变化不符合连续渐变的规律。
Many of the physical-based hydrological and crop models require day-sequence meteorological data to be driven. CLIGEN is a weather generator that generates climate input files for models such as WEPP and can generate 10 daily sequence meteorological variables to meet this need but in China The applicability needs to be assessed. The objective of the study was to evaluate the ability of CLIGEN to generate non-precipitation elements (maximum temperature, minimum temperature, dew point temperature, solar radiation and wind speed) using the Chang-Wu meteorological data from 1957 to 2001 in the Loess Plateau. The results show that CLIGEN simulates the maximum temperature, the minimum temperature and the dew point temperature better, has less effect on solar radiation and extreme climatic events and has the worst effect on the wind speed. The correlation test showed that CLIGEN kept the seasonal of meteorological elements very well, which is very important for simulating agricultural production. However, it did not keep the daily autocorrelation and cross-correlation of meteorological elements, which led to the temperature gradient does not meet the gradual gradual change The law.