对相对湿度(RH)年循环进行有效诊断可以对季节内雾霾的监测和调控,流行性疾病爆发空间分布和防治以及季风降水量的实时预报和决策等提供重要帮助。通过总结RH及其年循环的研究现状,系统介绍了当前几类常用的信号提取方法,并评估了这些方法提取年循环信号的可行性。得出以下结论:针对RH年循环的时变特征和非对称三角波、类方波、状态瞬变等复杂结构,以谐波为基础的提取方法难以成功,高抗噪的非线性信号提取方法是解决这个问题的突破口。因此,现阶段对于RH年循环的研究迫切需要完善并提高RH观测数据的质量,精确提取并量化其年循环的时变特征和复杂结构,最后结合动力学过程和统计学进行分析,以期使我国对RH年循环(频率、相位、振幅等)变化的物理机制研究达到更高水平。

Studies on the characteristics of relative humidity annual cycle change include the frequency, phase, and amplitude of the time series and their changes. The effective diagnosis of the relative humidity annual cycle can provide important help in the monitoring and regulation of seasonal haze, the spatial distribution of epidemic outbreaks and their prevention and control, and the real-time forecasting and decision-making of monsoon precipitation. Different from studies on the trend of the relative humidity, the diagnosis in the annual cycle is scarce. This paper summarized the research status of relative humidity and its annual cycle, introduced several current methods for extracting common signals, and evaluated the feasibility of these methods for extracting annual cycle signals. Due to the time-varying characteristics of the annual cycle of relative humidity and complex structures such as asymmetric triangular waves, square-like waves, and state transients, harmonic-based extraction methods are difficult to succeed. The nonlinear signal extraction method with high noise immunity will solve this problem. At present, the relative humidity annual cycle studies urgently need to be improved and improve the quality of relative humidity observation data, accurately extract and quantify the time-varying characteristics and complex structure of the annual cycle. Moreover, combining the dynamic process and statistical analysis, we also need to study the physical mechanism of the change of relative humidity annual cycle (frequency, phase, amplitude, etc.) in China.