A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed I_s and I_c trends, respectively) is critical for better designing urban heat mitigation strategies. However, such a global comparison remains largely absent. Using spatially continuous land surface temperatures and surface air temperatures (2003–2020), here we find that the magnitude of the global mean I_s trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six‐times the corresponding I_c trend (0.03 ± 0.002°C/decade) during the day, while the former (0.06 ± 0.004°C/decade) is double the latter (0.03 ± 0.002°C/decade) at night. Variable importance scores indicate that global daytime I_s trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime I_c trend. At night, both global I_s and I_c trends are mainly controlled by background climate.

The significant reduction in human activities during COVID‐19 lockdown is anticipated to substantially influence urban climates, especially urban heat islands (UHIs). However, the UHI variations during lockdown periods remain to be quantified. Based on the MODIS daily land surface temperature and the in‐situ surface air temperature observations, we reveal a substantial decline in both surface and canopy UHIs over 300‐plus megacities in China during lockdown periods compared with reference periods. The surface UHI intensity (UHII) is reduced by 0.25 (one S.D. = 0.22) K in the daytime and by 0.23 (0.20) K at night during lockdown periods. The reductions in canopy UHII reach 0.42 (one S.D. = 0.26) K in the daytime and 0.39 (0.29) K at night. These reductions are mainly due to the near‐unprecedented drop in human activities induced by strict lockdown measures. Our results provide an improved understanding of the urban climate variations during the global pandemic.

The urban heat island (UHI) effect, in which urbanized areas tend to have warmer conditions compared to their rural surroundings, has drawn increasing attention in recent years. Using ground-based and satellite remote sensing data, we present a method to quantify the spatial pattern and diurnal and seasonal variations in canopy layer heat islands (CLHIs) in China’s 32 major cities during 2009 and investigate their relationships with built-up intensity (BI), nighttime lights, vegetation activity, surface albedo, and surface urban heat island intensity (SUHII). The results show that both the annual daytime and nighttime CLHI intensities (CLHIIs) were positive ranging from 0.2 °C to 2.2 °C and from 0.3 °C to 2.4 °C for these major cities, respectively. Higher CLHIIs were observed in the night, especially for northern parts of China. Along urban–rural gradients, the CLHI effect had an exponential decay shape and differed greatly by season. The CLHII distribution correlated positively and significantly to BI and nighttime lights. Vegetation activity was negatively correlated with the CLHII and more strongly in summer. Surface albedo showed an extremely weak correlation with the CLHII. In addition, CLHII had a strong correlation with SUHII. The annual daytime SUHII was 1.2 ± 1.1 °C (mean ± standard deviation) with 0.40 °C (95% confidence interval 0.36 to 0.44 °C) of annual daytime CLHII. The annual nighttime SUHII was 2.0 ± 0.8 °C with 1.04 °C (0.99 to 1.09 °C) of annual nighttime CLHII. Our results suggest that, reducing built-up intensity and anthropogenic heat emissions and increasing urban vegetation provide a co-benefit of mitigating SUHI and CLHI effects.