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.