资料均一化对沈阳站气温趋势和城市化偏差分析的影响

Effect of data homogenization on temperature trend estimation and urban bias at Shenyang station

利用国家气象信息中心2013年发布的逐日均一化气温资料,对沈阳站资料均一化处理前后平均气温和极端气温指数序列的线性趋势及其城市化影响偏差进行了比较评价。结果表明:1)资料均一化处理对日最高气温及其衍生的极端气温指数序列趋势估计的影响较弱,但对日最低气温及其衍生的极端气温指数序列趋势估计具有显著影响。2)经资料均一化处理后,平均气温序列中的城市化影响偏差有所增大,平均最低气温序列中的城市化影响偏差增大尤其明显;与冷事件有关的极端气温指数序列的城市化影响偏差数值有所减小,与暖事件有关的极端气温指数序列的城市化影响偏差数值有所增加。3)资料均一化处理有效纠正了因迁站等原因造成的地面气温观测记录中的非均一性,但却在很大程度上还原了城市站地面气温观测记录中的城市化影响偏差。

Based on the homogeneous daily surface air temperature dataset in 2013 from the National Meteorological Information Center,the linear trends of mean temperature and extreme temperature indices and their urban biases at Shenyang station before and after homogenization were compared and evaluated.The result shows that homogeneity of temperature series exerts weak effect on the daily maximum temperature and the relevant extreme temperature indices trend estimation.Meanwhile,it exerts obvious effect on the daily minimum temperature and the relevant extreme temperature indices trend estimation.The result also indicates that the urban bias of annual mean temperature increases after homogenization,especially that of annual mean minimum temperature.However,the urban bias of extreme temperature indices relevant to cold events reduces while that relevant to warm events increases after homogenization.Therefore,homogenization can correct the non-uniformity of surface temperature observation data effectively such as relocation of weather stations but it also brings new urban bias to the observation records to a certain extent.