Abstract/Summary

Urban surface albedo is an essential biophysical variable in the surface energy balance across all scales, from micro-scale (materials) to the globe, changing with land covers and three-dimensional structures over urban areas. Urban albedos are dynamic over space and time but have not yet been quantified over global scales due to the lack of high-resolution albedo datasets. Here, we combined the direct estimation approach and Landsat surface reflectance product to generate a 30-m-resolution annual surface albedo dataset for 3037 large cities (area > 50 km2) worldwide for the period from 1986 to 2020, allowing spatial patterns and long-term temporal trends to be explored with possible causal drivers, and quantification of the surface radiative forcing from these albedo changes. Evaluation of this new albedo dataset using global urban flux tower-based measurements demonstrates its high accuracy with an overall bias and root-mean-square-error (RMSE) of 0.005 and 0.025, respectively. Analysis of the dataset reveals an overall decreasing trend of albedo during the 35-year evaluation period (1986–2020), which is robust accounting for uncertainties from training sample representativeness, Landsat data uncertainty, seasonal variation, and snow-cover contamination. Our results reveal that urban greening (measured by the positive Normalized Difference Vegetation Index (NDVI) trend) can well explain the total variances in the albedo trend for the 35-year period through two different pathways of tree planting and urban warming-enhanced vegetation growth. The decrease in urban albedo caused a warming effect indicated by positive surface radiative forcing, with a global city-level average surface radiative forcing of 2.76 W·m−2. These findings enhance our understanding of urbanization's impacts on albedo-related biophysical processes and can provide information to quantify urban surface radiation energy and design effective mitigation strategies to reduce urban warming.