自动气象站自适应数据处理方法的研究

Self-adaptive data processing method for automatic weather station

根据气象服务需求而灵活配置气象要素和观测梯度的自动气象站获得了广泛应用,但其数据存储传输采用格式固定的方式,囊括了探测要素的并集与每个要素的最大观测梯度,存在大量冗余数据。通过自动气象站输出数据格式的灵活设计,提出了一种自适应数据采集处理方法,自动识别每个气象站所配置探测要素对应的梯度观测数据,并根据探测要素和对应的观测梯度动态存储观测数据。应用表明,该方法满足了探测要素和观测梯度配置互不相同的气象观测站网的高效数据采集处理,并为每个自动气象站动态输出与其要素和观测梯度配置匹配的数据存储产品,有效降低了自动气象站数据存储的冗余度,大大提高了气象观测站网数据采集、处理与传输效率,节约了大量存储资源。

According to each meteorological application requirement,automatic weather station（AWS）is usually configured with meteorological element and gradient observation.Because its output data is always saved in fixed format which is defined with all observing elements and maximum gradient,it contains lots of redundant data.A self-adaptive data processing method is advanced based on flexible definition of data output format from AWS hardware interface.Meteorological elements and corresponding gradient configuration of each AWS are identified automatically,and observation data of each gradient for each element are processed self-adaptively and saved dynamically.Application shows that data products can be achieved self-adaptively for AWS network whose element and gradient configuration differ from one another.Redundancy for data products is reduced effectively and data processing and transmission efficiency is increased greatly with a lot of storage resources being saved.