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中文摘要：
天气和气候虽然遵从流体力学规律，但是却显示出随机性，研究天气和气候之间的关系必须引人分数阶的导数和积分，从物理上讲不外乎说明天气和气候的随机程度是不相同的。为此提出气候的q（0≤q≤1）阶微商是天气，扩展了Hasselmann的结果。实际资料分析表明，气候距平具有长程相关，比天气有更好的记忆性。气候距平的概率密度分布函数有较长的尾巴，较长的尾巴反映了极值气候所发生的频率。
英文摘要：
The weather and climate comply with the fluid dynamical equation and appear stochastic. In order to explore the relationship between weather and climate, the fractional derivative and integration are introduced. Physically, the stochastic degrees of weather and climate are different. It is proposed that the qth （0≤q≤1） derivative of climate is weather. When q = 1, it is the Hasselmann＇ s result. The analysis based on observation data shows that climate anomaly has longer range correlation and better memory than weather. The probability density function of climate has a long tail, which can reflect the probability of extreme weather and climate.
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