一种基于雨声谱形状的水面降雨强度反演方法

本文依据雨声谱的不同特征,结合最小二乘法和非线性方法,分频段使用不同的模型反演水面降雨的强度。文中首先研究雨声谱在15~30 kHz的对数线性变化规律,并利用模型中的参数值将降雨类型分为无雨、小雨(＜10 mm/h)及中雨或大雨(＞10 mm/h);其次采用S型增长模型(Logistic模型)拟合小雨时的雨声谱,获得小雨期间降雨强度的量化算法;第三,研究2~10 kHz雨声谱的对数线性规律,利用回归中的参数值获得大雨期间降雨强度的量化算法。反演精度的分析结果表明,利用本算法反演的水面降雨强度与实测的水面降雨强度比较一致,每分钟平均降雨量的误差只有1%~4%,因此,本算法可以较好地反演水面降雨的强度。 

A method to quantitatively estimate rainfall rate above water surface based on different spectrum shapes generated by rainfall

Rainfall measurements at sea are very difficult to make because rainfall is sharply discontinuous in both time and space.Distinct ambient sound spectra for various rainfall rates can be identified through a series of discrimination processes or vice versa.In this paper,a method combined with the nonlinear least-square regression to quantitatively estimate rainfall rate over water surface from the different spectrum shapes generated by rainfall in some frequency bands is presented.About 2000 min spectrum data generated by rainfall have been collected in an open-lake in Xiamen city.As a result,the spectrum shape in 15~30 kHz is fitted to log-linear law which allows classification of rain into three categories from the spectrum slope:no rain,drizzle (rainfall rate ＜10 mm/h) and heavy rain (rainfall rate ＞10 mm/h). Then,rainfall detection is made and rainfall rate is quantified in drizzle time with Logistic model in the frequency bands of 2~15 kHz,and the rainfall rate in heavy rainfall is also quantified with log-linear regression.Finally,all measured spectrum data are used to calculate rainfall rate with the algorithm.The results show that it is comparably coincidente with the synchronously measured ones.The average error of accumulative rainfall per min is only 1%~4%.