Increased heat risk in wet climate induced by urban humid heat

More extremely hot days, more heat exposure and fewer cooling options for people of color in Connecticut, U.S

It is well-documented that people of color in the U.S. are disproportionately exposed to extreme urban heat. However, most studies have focused on large cities for one point in time, and less is known about how heat exposure changes over time in smaller cities. Here, we present a study of the changing nature of urban heat exposure and cooling strategies for ten cities in Connecticut in the U.S. Our results show that people of color experience more heat exposure and fewer adaptation strategies. They experienced higher overall temperatures, more extremely hot days, and larger increases in heat exposure. Also, they have lower air conditioning ownership rates and lower tree cover. Taken together, the results indicate that people of color are not only exposed to higher temperatures but also disproportionately exposed to increasing temperatures over time. With lower heat adaptation capacity, people of color are more vulnerable to increasing urban heat.

Large disagreements in estimates of urban land across scales and their implications

Improvements in high-resolution satellite remote sensing and computational advancements have sped up the development of global datasets that delineate urban land, crucial for understanding climate risks in our increasingly urbanizing world. Here, we analyze urban land cover patterns across spatiotemporal scales from several such current-generation products. While all the datasets show a rapidly urbanizing world, with global urban land nearly tripling between 1985 and 2015, there are substantial discrepancies in urban land area estimates among the products influenced by scale, differing urban definitions, and methodologies. We discuss the implications of these discrepancies for several use cases, including for monitoring urban climate hazards and for modeling urbanization-induced impacts on weather and climate from regional to global scales. Our results demonstrate the importance of choosing fit-for-purpose datasets for examining specific aspects of historical, present, and future urbanization with implications for sustainable development, resource allocation, and quantification of climate impacts.

Surface and canopy urban heat island disparities across 2064 urban clusters in China

The vast majority of urban heat island (UHI) studies are now derived from surface temperatures, substituting for the original air temperature-based definition. The disparities in hourly surface-canopy UHI effects (SUHI, CUHI) and the contrasting mechanisms are currently poorly understood. Here, we use high-resolution hourly LST and air temperature data from 2064 urban clusters in China to estimate SUHI and CUHI intensities and their driving mechanisms during the summer and winter of 2022. Across all urban clusters, we find that SUHI is on average ten times higher than the CUHI in the summer (0.97 VS. 0.09 °C) yet nearly triple that in the winter (0.30 VS. 0.11 °C), with SUHI exceeding CUHI in 91.5 % and 65.7 % of urban clusters, respectively. Seasonal and hourly analyses on SUHI/CUHI confirm typically opposite hysteresis variations (magnitude, peak, and timing of occurrence) and more correlated surface-canopy UHIs patterns during the night. We further demonstrate that SUHI magnitude can be largely explained by biophysical factors, urban attributes, and climate contexts, whereas CUHI interferes with additional constraints linked to ground-air energy transfer and advective dissipation. The improvement of urban greenery aids summer cooling efficiently in equatorial and boreal regions, while albedo measures are relevant in mitigating nocturnal warming in arid regions. Our findings support multiple technologies as ideas for urban three-dimensional UHIs (surface, canopy and boundary) and energy mechanisms, and the urgent need for ambitious urban heat mitigation strategies to minimize future climate change impacts.

Reconstruction of all-sky daily air temperature datasets with high accuracy in China from 2003 to 2022

A high-accuracy, continuous air temperature (Ta) dataset with high spatiotemporal resolution is essential for human health, disease prediction, and energy management. Existing datasets consider factors such as elevation, latitude, and surface temperature but insufficiently address meteorological and spatiotemporal factors, affecting accuracy. Additionally, no high-resolution dataset currently includes daily maximum (Tmax), minimum (Tmin), and mean (Tmean) temperatures generated using a unified methodology. Here, we introduce the four-dimensional spatiotemporal deep forest (4D-STDF) model, integrating 12 multisource factors, encompassing static and dynamic parameters, and six refined spatiotemporal factors to produce Ta datasets. This approach generates three high-accuracy Ta datasets at 1 km spatial resolution covering mainland China from 2003 to 2022. These datasets, in GeoTIFF format with WGS84 projection, comprise daily Tmax, Tmin, and Tmean. The overall RMSE are 1.49 °C, 1.53 °C, and 1.18 °C for the estimates. The 4D-STDF model can also be applied to other regions with sparse meteorological stations.

Sketching the spatial disparities in heatwave trends by changing atmospheric teleconnections in the Northern Hemisphere

Pronounced spatial disparities in heatwave trends are bound up with a diversity of atmospheric signals with complex variations, including different phases and wavenumbers. However, assessing their relationships quantitatively remains a challenging problem. Here, we use a network-searching approach to identify the strengths of heatwave-related atmospheric teleconnections (AT) with ERA5 reanalysis data. This way, we quantify the close links between heatwave intensity and AT in the Northern Hemisphere. Approximately half of the interannual variability of heatwaves is explained and nearly 80% of the zonally asymmetric trend signs are estimated correctly by the AT changes in the mid-latitudes. We also uncover that the likelihood of extremely hot summers has increased sharply by a factor of 4.5 after 2000 over areas with enhanced AT, but remained almost unchanged over the areas with attenuated AT. Furthermore, reproducing Eastern European heatwave trends among various models of the Coupled Model Intercomparison Project Phase 6 largely depends on the simulated Eurasian AT changes, highlighting the potentially significant impact of AT shifts on the simulation and projection of heatwaves.

Uncovering the Nexus between Urban Heat Islands and Material Stocks of Built Environment in 335 Chinese Cities

China's unprecedented rapid urbanization has dramatically reshaped the urban built environment, disrupting the thermal balance of cities. This disruption causes the urban heat island (UHI) effect, adversely affecting urban sustainability and public health. Although studies have highlighted the remarkable impacts of the built environment on UHIs, the specific effects of its various structures and components remain unclear. In this study, a multidimensional remote sensing data set was used to quantify the atmospheric UHIs across 335 Chinese cities from 1980 to 2020. In conjunction with stocks of three end-use sectors and three material groups, the impacts of gridded material stocks on UHI variations were analyzed. The findings reveal that building stocks exert a predominant influence in 48% of cities. Additionally, the extensive use of metal and inorganic materials has increased thermal stress in 220 cities, leading to an average UHI increase of 0.54 °C. The effect of organic materials, primarily arising from mobile heat sources, is continuously increasing. Overall, this study elucidates the effect of the functional structure and material composition of urban landscapes on UHIs, highlighting the complexities associated with the influence of the built environment on the urban heat load.

Uniformly elevated future heat stress in China driven by spatially heterogeneous water vapor changes

The wet bulb temperature (Tw) has gained considerable attention as a crucial indicator of heat-related health risks. Here we report south-to-north spatially heterogeneous trends of Tw in China over 1979-2018. We find that actual water vapor pressure (Ea) changes play a dominant role in determining the different trend of Tw in southern and northern China, which is attributed to the faster warming of high-latitude regions of East Asia as a response to climate change. This warming effect regulates large-scale atmospheric features and leads to extended impacts of the South Asia high (SAH) and the western Pacific subtropical high (WPSH) over southern China and to suppressed moisture transport. Attribution analysis using climate model simulations confirms these findings. We further find that the entire eastern China, that accommodates 94% of the country's population, is likely to experience widespread and uniform elevated thermal stress the end of this century. Our findings highlight the necessity for development of adaptation measures in eastern China to avoid adverse impacts of heat stress, suggesting similar implications for other regions as well.

Weak correlations among leaf thermal metrics, economic traits and damages under natural heatwaves

The frequency and intensity of heatwaves are increasing around the world, causing severe damages to plants, but whether leaf thermal metrics is in line with leaf economic spectrum is still controversial. Here, we measured leaf damage ratio, leaf thermal metrics (tolerance and sensitivity) and economic traits of 131 woody species across five cities along the Yangtze River after a two-month natural extreme temperature event. We found that leaf thermal sensitivity but not thermal tolerance was correlated with leaf damage ratio, and the relationships between leaf thermal metrics and economic traits were weak, indicating that leaf thermal adaptation may be independent from leaf carbon construction. This study suggests a potential indicator for predicting plant survival under heatwaves, urging future research to explore more physiological traits to comprehensively understand plant heat responses and adaptations.

Different explanations for surface and canopy urban heat island effects in relation to background climate

The background climatic conditions and urban morphology greatly influence urban heat island effects (UHIs), but one-size-fits-all solutions are frequently employed to mitigate UHIs. Here, attribution models for surface UHIs (SUHIs) and canopy UHIs (CUHIs) were developed to describe UHI formation. The contribution of factors to SUHIs and CUHIs shows similar dependencies on background climate and urban morphology. Furthermore, the factors that mainly contributed to CUHIs were more complex, and anthropogenic heat was the more critical factor. Influence from urban morphology also highlights that there is no one-size-fit-all solution for heat mitigation at the neighborhood. In particular, maintaining a low building density should be prioritized, especially mitigating CUHIs. Moreover, it is more effective to prioritize urban irrigation maintenance over increasing green cover in arid regions but the opposite in humid regions. The work can provide scientific evidence to support developing general and regional guidelines for urban heat mitigation.

Intensifying urban imprint on land surface warming: Insights from local to global scale

Increasing urbanization exacerbates surface energy balance perturbations and the health risks of climate warming; however, it has not been determined whether urban-induced warming and attributions vary from local, regional, to global scale. Here, the local surface urban heat island (SUHI) is evidenced to manifest with an annual daily mean intensity of 0.99°C-1.10°C during 2003-2018 using satellite observations over 536 cities worldwide. Spatiotemporal patterns and mechanisms of SUHI tightly link with climate-vegetation conditions, with regional warming effect reaching up to 0.015°C-0.138°C (annual average) due to surface energy alterations. Globally, the SUHI footprint of 1,860 cities approximates to 1% of the terrestrial lands, about 1.8-2.9 times far beyond the urban impervious areas, suggesting the enlargements of the imprint of urban warming from local to global scales. With continuous development of urbanization, the implications for SUHI-added warming and scaling effects are considerably important on accelerating global warming.

Heterogeneous effects of the availability and spatial configuration of urban green spaces on their cooling effects in China

The impacts of the availability and spatial configuration of urban green spaces (UGS) on their cooling effects can vary with background climate conditions. However, large-scale studies that assess the potential heterogeneous relationships of UGS availability and spatial configuration with urban thermal environment are still lacking. In this study, we investigated the impacts of UGS availability and spatial configuration on urban land surface temperature (LST) taking 306 cities in China as a case study covering a multi-biome-scale. We first calculated the availability of surrounding UGS for urban built-up pixels in each city using a distance-weighted approach, and its spatial configuration was quantified through the Gini coefficient. Then, we employed various regression models to explore how the impacts of UGS availability and the Gini coefficient on LST varies across different LST quantiles and between day- and nighttime. The results revealed that UGS availability was negatively associated with both daytime and nighttime LST, while the Gini coefficient showed a positive impact solely on daytime LST, indicating that an adequate and equally distributed UGS contributes to lower environmental temperatures during the daytime. Furthermore, the impact of UGS availability on LST decreased during both day- and nighttime with increased background LST quantiles. Whereas the impact of the Gini coefficient increased only with daytime LST quantile levels, with its effect remaining almost insignificant during the night. Our findings provide new insights into the impacts of UGS on urban thermal environment, offering significant implications for urban green infrastructure planning aiming at lowering the urban heat island.