降水与相对湿度协同算法研究

Research on Collaborative Algorithm Between Precipitation and Relative Humidity

利用2016年1月—2017年12月天津市国家气象观测站资料和欧洲中心数值模式资料,基于降水与相对湿度的统计关系,建立两者之间协同订正算法并检验评估,结果表明:观测资料显示小时降水量级越小,其相对湿度的离散度越大,日变化特征越明显。累积雨量越大,降水持续时间越长,相对湿度越稳定。模式预报有降水时相对湿度分布有较大离散度,无法直接业务应用,需应用协同算法进行订正。对订正结果检验可知,对于小雨天气的相对湿度订正效果较好,而对于中雨以上订正结果偏低。

Using the observed hourly precipitation and relative humidity data from the national meteorological stations in Tianjin City,and the forecast data from European Centre for Medium Range Weather Forecasts(ECMWF),spanning January 2016 to December 2017,we establish a coordinated revised statistical algorithm for precipitation and relative humidity,considering the statistical relationship between them.Results show that the smaller the hourly precipitation is,the greater the dispersion of relative humidity is,together with the obvious diurnal variation characteristics.Furthermore,the greater the accumulated rainfall and the longer the precipitation duration,the more stable the relative humidity.However,due to the fact that in the numerical weather prediction,the distribution of relative humidity always has a large dispersion when there is precipitation.Thus,the result can not be directly offered for operational application and needs to be revised by the collaborative algorithm method.Results show that the adjustment of relative humidity is better for light rain,but lower for moderate rain.