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The sensitivity of urban canopy air temperature ($T_a$) to anthropogenic heat flux ($Q_{AH}$) is known to vary with space and time, but the key factors controlling such spatiotemporal variabilities remain elusive. To quantify the contributions of different physical processes to the magnitude and variability of$\mathrm{\Delta }{T}_a/\mathrm{\Delta }{Q}_{AH}$(where$\mathrm{\Delta }$represents a change), we develop a forcing-feedback framework based on the energy budget of air within the urban canopy layer and apply it to diagnosing$\mathrm{\Delta }{T}_a/\mathrm{\Delta }{Q}_{AH}$simulated by the Community Land Model Urban over the contiguous United States (CONUS). In summer, the median$\mathrm{\Delta }{T}_a/\mathrm{\Delta }{Q}_{AH}$is around 0.01$\text{K\hspace{0.17em}}{\left(\text{W\hspace{0.17em}}{\text{m}}^{-\text{2}}\right)}^{-1}$over the CONUS. Besides the direct effect of$Q_{AH}$on$T_a$, there are important feedbacks through changes in the surface temperature, the atmosphere–canopy air heat conductance ($c_a$), and the surface–canopy air heat conductance. The positive and negative feedbacks nearly cancel each other out and$\mathrm{\Delta }{T}_a/\mathrm{\Delta }{Q}_{AH}$is mostly controlled by the direct effect in summer. In winter,$\mathrm{\Delta }{T}_a/\mathrm{\Delta }{Q}_{AH}$becomes stronger, with the median value increased by about 20% due to weakened negative feedback associated with$c_a$. The spatial and temporal (both seasonal and diurnal) variability of$\mathrm{\Delta }{T}_a/\mathrm{\Delta }{Q}_{AH}$as well as the nonlinear response of$\mathrm{\Delta }{T}_a$to$\mathrm{\Delta }{Q}_{AH}$are strongly related to the variability of$c_a$, highlighting the importance of correctly parameterizing convective heat transfer in urban canopy models.

 

Abstract The two-resistance mechanism (TRM) attribution method, which was designed to analyze the urban–rural contrast of temperature, is improved to study the urban–rural contrast of heat stress. The improved method can be applied to diagnosing any heat stress index that is a function of temperature and humidity. As an example, in this study we use it to analyze the summertime urban–rural contrast of simplified wet bulb globe temperature (SWBGT) simulated by the Geophysical Fluid Dynamics Laboratory land model coupled with an urban canopy model. We find that the urban–rural contrast of SWBGT is primarily caused by the lack of evapotranspiration in urban areas during the daytime and the release of heat storage during the nighttime, with the urban–rural differences in aerodynamic features playing either positive or negative roles depending on the background climate. Compared to the magnitude of the urban–rural contrast of temperature, the magnitude of the urban–rural contrast of SWBGT is damped due to the moisture deficits in urban areas. We further find that the urban–rural contrast of 2-m air temperature/SWBGT is fundamentally different from that of canopy air temperature/SWBGT. Turbulent mixing in the surface layer leads to much smaller urban–rural contrasts of 2-m air temperature/SWBGT than their canopy air counterparts. Significance Statement Heat leads to serious public health concerns, but urban and rural areas have different levels of heat stress. Our study explains the magnitude and pattern of the simulated urban–rural contrast in heat stress at the global scale and improves an attribution method to quantify which biophysical processes are mostly responsible for the simulated urban–rural contrast in heat stress. We highlight two well-known causes of higher heat stress in cities: the lack of evapotranspiration and the stronger release of heat storage. Meanwhile, we draw attention to the vegetation types in rural areas, which determine the urban–rural difference in surface roughness and significantly affect the urban–rural difference in heat stress. Last, we find the urban–rural contrasts of 2-m air temperature/SWBGT are largely reduced relative to their canopy air counterparts due to the turbulent mixing effect. 

Urban greening is often proposed for urban heat island (UHI) mitigation because vegetation provides shade and increases evapotranspiration. However, vegetation has lower albedo and higher emissivity than the bare soil it often replaces, which increases incoming energy fluxes. Here, we use the Weather Research and Forecasting model to quantify and compare the albedo and non‐albedo effects (i.e., changes in emissivity, surface roughness, and evaporative fluxes) of urban greening in the Los Angeles Basin under policy relevant urban greening scenarios. When albedo‐induced effects were included in the model, daytime surface temperatures in urban areas warmed by 0.70 ± 0.89°C with increases in the sensible heat flux outweighing increases in the latent heat flux from increased evapotranspiration. In contrast, daytime surface temperatures cooled by 0.27 ± 0.72°C when the albedo‐induced effects were ignored. At night, including albedo‐induced effects of urban greening resulted in only half the cooling modeled in the non‐albedo simulations. Near surface air temperatures also had contrasting model results, with nighttime cooling of 0.21 ± 0.47°C outweighing slight daytime warming of 0.04 ± 0.32°C in the non‐albedo simulations and daytime warming of 0.33 ± 0.41°C outweighing slight nighttime cooling of 0.05 ± 0.46°C in the albedo simulations. Our results reveal the critical role that albedo plays in determining the net surface climate effects of urban greening. Reductions in albedo from urban greening should be carefully considered by policy makers and urban planners, especially as high albedo roofs and pavements are simultaneously being deployed for UHI mitigation in many cities.

 

The transition from moderate to weak turbulence regimes remains a grand challenge for stable boundary layer parameterizations in weather and climate models. In this study, a critical horizontal Froude number (≈0.28) is proposed to characterize such a transition, which corresponds to the development of quasi two‐dimensional pancake vortices. Traditionally defined stability parameters corresponding to the critical horizontal Froude number are estimated and are consistent with values in the literature. The critical horizontal Froude number can recover previously used height‐ and site‐dependent mean wind speed thresholds. These findings offer a way to constrain the validity range of Monin‐Obukhov similarity theory in numerical models for weather and pollutants dispersion.

 

Abstract In this work, we investigate the effect of areawide building retrofitting on summertime, street-level outdoor temperatures in an urban district in Berlin, Germany. We perform two building-resolving, weeklong large-eddy simulations: one with nonretrofitted buildings and the other with retrofitted buildings in the entire domain to meet today’s energy efficiency standards. The comparison of the two simulations reveals that the mean outdoor temperatures are higher with retrofitted buildings during daytime conditions. This behavior is caused by the much smaller inertia of the outermost roof/wall layer in the retrofitting case, which is thermally decoupled from the inner roof/wall layers by an insulation layer. As a result, the outermost layer heats up more rigorously during the daytime, leading to increased sensible heat fluxes into the atmosphere. During the nighttime, the outermost layer’s temperature drops down faster, resulting in cooling of the atmosphere. However, as the simulation progresses, the cooling effect becomes smaller and the warming effect becomes larger. After 1 week, we find the mean temperatures to be 4 K higher during the daytime while the cooling effects become negligible. Significance Statement Building retrofitting is taking place in Europe and other continents as a measure to reduce energy consumption. The change in the building envelope directly influences the urban atmosphere. Our study reveals that areawide retrofitting in a German city district can have negative effects on the outdoor microclimate in summer by causing higher air temperatures. 

The decomposition of multi-subject fMRI data using rank- (L,L,1,1) block term decomposition (BTD) can preserve higher-way data structure and is more robust to noise effects by decomposing shared spatial maps (SMs) into a product of two rank-L loading matrices. However, since the number of whole-brain voxels is very large and rank L is larger than 1, the rank-(L,L,1,1) BTD requires high computation and memory. Therefore, we propose an accelerated rank- (L,L,1,1) BTD algorithm based upon the method of alternating least squares (ALS). We speed up updates of loading matrices by reducing fMRI data into subspaces, and add an orthonormality constraint on shared SMs to improve the performance. Moreover, we evaluate the rank-L effect on the proposed method for actual task-related fMRI data. The proposed method shows better performance when L=35. Meanwhile, experimental comparison results verify that the proposed method largely reduced (17.36 times) computation time compared to ALS while also providing satisfying separation performance. 

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that impedes patients’ cognition, social, speech and communication skills. ASD is highly heterogeneous with a variety of etiologies and clinical manifestations. The prevalence rate of ASD increased steadily in recent years. Presently, molecular mechanisms underlying ASD occurrence and development remain to be elucidated. Here, we integrated multi-layer genomics data to investigate the transcriptome and pathway dysregulations in ASD development. The RNA sequencing (RNA-seq) expression profiles of induced pluripotent stem cells (iPSCs), neural progenitor cells (NPCs) and neuron cells from ASD and normal samples were compared in our study. We found that substantially more genes were differentially expressed in the NPCs than the iPSCs. Consistently, gene set variation analysis revealed that the activity of the known ASD pathways in NPCs and neural cells were significantly different from the iPSCs, suggesting that ASD occurred at the early stage of neural system development. We further constructed comprehensive brain- and neural-specific regulatory networks by incorporating transcription factor (TF) and gene interactions with long 5 non-coding RNA(lncRNA) and protein interactions. We then overlaid the transcriptomes of different cell types on the regulatory networks to infer the regulatory cascades. The variations of the regulatory cascades between ASD and normal samples uncovered a set of novel disease-associated genes and gene interactions, particularly highlighting the functional roles of ELF3 and the interaction between STAT1 and lncRNA ELF3-AS 1 in the disease development. These new findings extend our understanding of ASD and offer putative new therapeutic targets for further studies.