Search

[Display omitted] Urban thermal anisotropy (UTA) drastically impacts satellite-derived urban surface temperatures and fluxes, and consequently makes it difficult to gain a more comprehensive understanding of global urban climates. However, UTA patterns and associated biases in observed urban climate variables have not been investigated across an adequate number of global cities with diverse contexts; nor is it known whether there are globally measurable factors that are closely related to the UTA intensity (UTAI, quantified as the maximum difference between the nadir and off-nadir urban thermal radiation). Here we investigate the UTAI over more than 5500 cities worldwide using multi-angle land surface temperature (LST) observations from 2003 to 2021 provided by Moderate Resolution Imaging Spectroradiometer (MODIS). The results show that the global mean UTAI can reach 5.1, 2.7, 2.4, and 1.7 K during summer daytime, winter daytime, summer nighttime, and winter nighttime, respectively. Using nadir LST observations as a reference, our analysis reveals that UTA can lead to an underestimation of satellite-based urban surface sensible heat fluxes (H) by 45.4% and surface urban heat island intensity (I s) by 43.0% when using LST observations obtained from sensor viewing zenith angles (VZAs) of ±60°. Practitioners can limit the biases of H and I s within ±10% by using LSTs from sensor VZAs within ±30°. We also find that UTAI is closely related to urban impervious surface percentage and surface air temperature across global cities. These findings have implications for angular normalization of satellite-retrieved instantaneous LST observations across cities worldwide. [ABSTRACT FROM AUTHOR]

A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed Is and Ic 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 Is trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six‐times the corresponding Ic 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 Is trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime Ic trend. At night, both global Is and Ic trends are mainly controlled by background climate. Plain Language Summary: Surface and canopy urban heat islands (surface and canopy UHIs, termed Is and Ic) are two major UHI types. These two counterparts are both related to urban population heat exposure and have long been a focus of urban climate research. However, the differences in the trends and major determinants of Is and Ic over global cities remain largely unclear. Based on spatially continuous land surface temperature and surface air temperature observations from 2003 to 2020, we find that the global mean Is trends are about 6.3 times and 2 times the Ic trends during the day and at night, respectively. During the day, the global Is trend is more regulated by surface property than by background climate, and vice versa for global Ic trend. At night, both the global Is and Ic trends are mainly regulated by background climate. These findings are important for better understanding global urban climate change and informing heat mitigation strategies. Key Points: The global Is trend is six‐fold and twofold larger than the Ic trend during the day and at night, respectivelyDuring the day, global Is trend is slightly more controlled by surface property, yet background climate plays a dominant role in Ic trendAt night, both global Is and Ic trends are more regulated by background climate [ABSTRACT FROM AUTHOR]

The weekend effect of the canopy urban heat island (UHI) has been long recognized. However, how the UHI weekend effect (UWE) varies with the hour of day and season of year is still unclear; it remains largely unknown on how the UWE is regulated by various controls. To address these knowledge gaps, here we took Beijing, China as an example and investigated the detailed spatiotemporal UWE patterns and the major regulators with a 3‐year data set of in‐situ surface air temperatures. Our results indicate that the annual ΔIc (the UHI intensity difference on weekends and weekdays) is stronger at night (−0.13 ± 0.12 K; mean ± 1 STD) than during the day (−0.05 ± 0.10 K); at the seasonal scale, ΔIc reaches the strongest in winter (−0.14 K) and the weakest in summer (−0.05 K). The ΔIc is strongly regulated by anthropogenic heat flux (AHF), evidenced by a quasi‐synchronous diurnal pattern between ΔIc and ΔAHF (i.e., the AHF difference between weekends and weekdays). The nighttime ΔIc is intensely modulated by urban morphology, with a stronger modulation by the landscape shape index than by the distance of the station from the urban center. Weather conditions also modulate the ΔIc, with the ΔIc weakening with the increase of cloud coverage and wind speed level. We consider these findings deepen our understanding of the weekly rhythms of UHI as well as the underlying modulators. Key Points: A significant ΔIc (weekend‐weekday difference in canopy urban heat island) is observed in Beijing, ChinaΔIc is stronger at night than during the day and the two minima of diurnal ΔIc correspond well to morning and evening rush hoursVariations in weekday‐weekend contrasts in Ic and anthropogenic heat flux are synchronous yet ΔIc is also modulated by urban morphology and weather condition [ABSTRACT FROM AUTHOR]

• SUHI and CUHI are investigated over 366 global cities. • Annual mean daytime (nighttime) SUHII is higher than CUHII by 1.1 °C (0.3 °C). • Cities increase T s –based DTR by 0.6 °C but reduce T a –based DTR by 0.2 °C. • The negative impact from annual mean T max is greater on SUHII than on CUHII. Interpreting the similarities and dissimilarities in spatiotemporal variations and various controls between surface and canopy urban heat islands (UHIs) is critical for a better understanding of their vertical structure. Preceding comparisons of the surface UHI (SUHI) and canopy UHI (CUHI), however, remain mostly restricted either in a single city or over a few cities within limited background climates; therefore, the associated similarities and dissimilarities between the SUHI and CUHI under different climates, especially at a global scale, remain largely unknown. Based on both satellite and in situ data, we simultaneously investigated the spatiotemporal patterns of the SUHI intensity (SUHII) and CUHI intensity (SUHII) of 366 global cities within various background climates. We further investigated the different impacts of several controls (e.g., vegetation coverage, population size, precipitation) on SUHII and CUHII. Our results indicate the following: (1) For the selected 366 cities, the annual mean SUHII is higher than CUHII by 1.1 ± 1.9 °C (mean ± Std) during the day and 0.3 ± 1.5 °C (mean ± Std) at night. The SUHII and CUHII in the equatorial, warm temperate, and snow climates are generally consistent with the above characteristics (i.e., SUHII > CUHII), however, in arid regions SUHII is lower than CUHII by 0.8 °C during the day. (2) The annual mean day–night difference in SUHII is positive (i.e., 0.6 ± 1.8 °C (mean ± Std)), while the difference in CUHII becomes negative (i.e., −0.2 ± 1.6 °C (mean ± Std)), indicating that urbanization increases the diurnal temperature range (DTR) based on land surface temperature, but it decreases the DTR based on surface air temperature. (3) Despite the high correlation between vegetation coverage and impervious surface percentage (ISP), their impacts on SUHII and CUHII were not consistent. The urban–rural difference in ISP exerts an insignificant impact on both SUHII and CUHII during the day and a greater impact on CUHII than on SUHII at night, whereas the urban–rural difference in vegetation coverage has a greater impact on SUHII than on CUHII during the day, while the opposite occurs at night. The impacts of population size on SUHII and CUHII are much greater during the night than on the day in which their impacts can be minimal. The relationship between annual mean precipitation and SUHII is positive during the day but negative at night, while for CUHII, their relationship is insignificantly negative both during the day and at night. These results can improve our understanding of the spatiotemporal patterns and controls of these two types of UHIs under various climates. [ABSTRACT FROM AUTHOR]

The local climate zone (LCZ) scheme has been widely used in urban heat island studies in the past decade. However, the general principle of LCZ surface air temperature (SAT) differences and their climatic differences on different timescales remain largely unclear. Here we investigated both the inter- and intra-LCZ differences at four timescales across nine Chinese megacities characterized with significantly different climates, based on three-year hourly SAT measurements collected at 898 stations from 2017 to 2019. The results showed that (1) at the annual mean scale, the Δ T inter (i.e., SAT differences between various LCZ types and LCZ D): and Δ T intra (i.e., standard deviation of SAT measurements belonging to the same LCZ) were larger during the night than the day for most LCZ types; and the Δ T inter and Δ T intra for warm temperate cities were usually greater than those of subtropical cities. (2) At the seasonal scale, the Δ T inter and Δ T intra of most LCZs often peaked at winter night. The largest seasonal variation of Δ T inter was observed in mid-temperate cities. (3) At the daily scale, the day-to-day difference of Δ T inter was smaller during the day than the night and mainly ranged from −0.5 °C to 0.5 °C. By contrast, the day-to-day difference of Δ T intra was relatively large both during the day and night. (4) At the hourly scale, both the Δ T inter and Δ T intra variations throughout a diurnal cycle followed a characteristic U-shape for most LCZs. We consider these findings are helpful for better understanding the inter- and intra-LCZ thermal differences across various timescales and climates. • Inter- and intra-LCZ surface air temperature differences are discussed on annual, seasonal, daily, and hourly scales. • Inter- and intra-LCZ SAT differences are both larger at night than during the day. • Inter- and intra-LCZ SAT differences are larger in warm temperate than in subtropical cities. • Inter- and intra-LCZ SAT differences reach their maxima for LCZ 1 and LCZ A, respectively. [ABSTRACT FROM AUTHOR]

Cities worldwide face escalating climate change risks, underscoring the need for spatially and temporally resolved urban air temperature (T a) data. While satellite-derived land surface temperature (LST) data have been widely used to estimate T a , high-resolution hourly T a estimation in urban areas remains underexplored. Traditional methods typically rely on LST data from geostationary satellites and continuous 24-h T a observations from weather stations. To address these limitations, we introduce a method that combines a diurnal temperature cycle (DTC) model with a random forest model to estimate monthly mean hourly urban T a at 1-km resolution. This approach leverages a limited number of diurnal T a observations from weather stations, MODIS LST data, and ancillary information. The core idea of the proposed method is to transform the estimation of monthly mean hourly 1-km T a into estimating 1-km DTC model parameters, primarily daily maximum and minimum T a values. This method capitalizes on MODIS LST's ability to estimate daily T a extremes and requires only four diurnal T a observations within a daily cycle to estimate monthly mean hourly 1-km T a. Station-based five-fold cross-validation yields overall RMSE values consistently below 1.0 °C across nine cities with diverse geographic and climatic contexts. The accuracy achieved with only four diurnal T a observations rivals that obtained using continuous 24-h T a observations. Even with a limited training set of ten stations, the overall RMSE remains below 1.0 °C for most cities. The proposed method proves effective for both single-city and multi-city modeling and can estimate daily hourly 1-km T a under clear-sky conditions. In conclusion, this study offers a feasible, efficient, and versatile method for accurately estimating monthly mean hourly 1-km T a , which can be readily applied to other cities and holds potential for various applications. • A novel method is proposed to estimate monthly mean hourly 1-km urban T a. • A diurnal temperature cycle model is used to reframe hourly T a estimation. • Only four rather than 24-h T a observations are necessitated. • Overall RMSE values are below 1.0 °C across various urban settings. • Employing ten training stations maintains acceptable accuracy. [ABSTRACT FROM AUTHOR]