There have long been arguments about the impact of urbanization on local meteorological observations. This letter reviews up-to-date studies of the urbanization-related warming in the observed land surface air tempera...There have long been arguments about the impact of urbanization on local meteorological observations. This letter reviews up-to-date studies of the urbanization-related warming in the observed land surface air temperature series in China. Many previous studies have suggested that, over the past few decades, the local warming due to urbanization could have been about 0.1 °C/10 yr, or even larger. However, based on recently developed homogenized temperature records, the estimated urban bias is smaller. Major uncertainties arise from either the data quality or the techniques used to estimate the urbanization effect. A key example is the ‘observationminus-reanalysis' method, which tends to overestimate the urban signal in this region, partly due to systematic bias in the multi-decadal variability of surface air temperature in the reanalysis data. It is expected that improved numerical modeling with high-resolution information regarding the changing land surface in the region will help to further understand and quantify the effect of urbanization in local temperature records.展开更多
基金supported by the National Natural Science Foundation of China[grant number 41475078]Strategic Priority Research Program–Climate Change:Carbon Budget and Relevant Issues of the Chinese Academy of Sciences[grant number XDA05090105]
文摘There have long been arguments about the impact of urbanization on local meteorological observations. This letter reviews up-to-date studies of the urbanization-related warming in the observed land surface air temperature series in China. Many previous studies have suggested that, over the past few decades, the local warming due to urbanization could have been about 0.1 °C/10 yr, or even larger. However, based on recently developed homogenized temperature records, the estimated urban bias is smaller. Major uncertainties arise from either the data quality or the techniques used to estimate the urbanization effect. A key example is the ‘observationminus-reanalysis' method, which tends to overestimate the urban signal in this region, partly due to systematic bias in the multi-decadal variability of surface air temperature in the reanalysis data. It is expected that improved numerical modeling with high-resolution information regarding the changing land surface in the region will help to further understand and quantify the effect of urbanization in local temperature records.