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Evaporative misters have long been used in urban spaces for heat mitigation, yet their thermal stress impacts and optimal operating conditions have not been fully explored. To fill this gap, we develop a misting model and embed it into an urban canopy model for the first time. Our tests confirm that misters can considerably reduce maximum urban canyon air temperature (up to 17.5 °C) and human skin temperature (up to 0.48 °C) in a hot and dry city (Phoenix, AZ). They continue to effectively reduce thermal stress, albeit with half of the cooling benefits, in a hot and humid city (Houston, TX). These thermal stress impacts are contingent upon wind speeds: the optimal wind speeds generally fall within an intermediate range—from light air (with low mist flow rates) to a moderate breeze (with higher mist flow rates). We then incorporate misting into a broader comparison of blue cooling strategies, including irrigation (on vegetation) and sprinkling (on pavements). With abundant water resources, sprinkling on asphalt and misting are the most effective cooling solutions, particularly suitable for middays and late afternoons, respectively. To balance cooling benefits with limited water resources, we propose a thermostatic control scheme that can save at least 10.5 m3/day of water compared to continuous misting for a 100-m stretch of street, equivalent to the water demand of about 20 Phoenix residents. Notably, misting and sprinkling generate rapid cooling in under 10 min with sufficient flow rates, demonstrating their potential as fast activation measures during extreme heat emergencies. 

Abstract In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity , where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts , where is the molecular Schmidt number, is the water kinematic viscosity, and is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous around , a mechanism that was not previously considered. As the coefficient of variation in increases, must be adjusted by a multiplier that was derived from a log‐normal model for the probability density function of . Reported variations in with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in . Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of . That varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade. 

Large-eddy simulations (LES) above forests and cities typically constrain the simulation domain to the first 10--20\% of the Atmospheric Boundary Layer (ABL), aiming to represent the finer details of the roughness elements and sublayer. These simulations are also commonly driven by a constant pressure gradient term in the streamwise direction and zero stress at the top, resulting in an unrealistic fast decay of the total stress profile. In this study, we investigate five LES setups, including pressure and/or top-shear driven flows with and without the Coriolis force, with the aim of identifying which option best represents turbulence profiles in the atmospheric surface layer (ASL). We show that flows driven solely by pressure not only result in a fast-decaying stress profile, but also in lower velocity variances and higher velocity skewnesses. Top-shear driven flows, on the other hand, better replicate ASL statistics. Overall, we recommend, and provide setup guidance for, simulation designs that include both a large scale pressure forcing and a non-zero stress and scalar flux at the top of the domain, and that also represent the Coriolis force. Such setups retain all the forces used in typical full ABL cases and result in the best match of the profiles of various statistical moments. 

Sea ice surface patterns encode more information than can be represented solely by the ice fraction. The aim of this paper is thus to establish the importance of using a broader set of surface characterization metrics, and to identify a minimal set of such metrics that may be useful for representing sea-ice in Earth System Models. Large-eddy simulations of the atmospheric boundary layer over various idealized sea ice surface patterns, with equivalent ice fraction and average floe area, demonstrate that the spatial organization of ice and water can play a crucial role in determining boundary-layer structure. Thus, different methods to quantify heterogeneity in categorical lattice spatial data, such as those done in landscape ecology and Geographic Information System (GIS) studies, are used here on a set of high-resolution, recently-declassified sea ice surface images. It is found that, in conjunction with ice fraction, the patch density (representing the fragmentation of the surface), the splitting index (representing the variability in patch size), and perimeter-area fractal dimension (representing the tortuosity of the interface) are all required to describe the two-dimensional pattern exhibited by a sea ice surface. Furthermore, for surfaces with anisotropic patterns, the orientation of the surface relative to the mean wind is needed. Furthermore, scaling laws are derived for these relevant landscape metrics to estimate them from aggregated spatial sea ice surface data at any resolution. The methods used and results gained from this study are a first step towards further development of methods to quantify the variability of non-binary surfaces, and for parameterizing mixed ice-water surfaces in coarse geophysical models. 

Urban surface and near-surface air temperatures are known to be often higher than their rural counterparts, a phenomenon now labeled as the urban heat island effect. However, whether the elevated urban temperatures are more persistent than rural temperatures at timescales commensurate to heat waves has not been addressed despite its importance for human health. Combining numerical simulations by a global climate model with a surface energy balance theory, it is demonstrated here that urban surface and near-surface air temperatures are significantly more persistent than their rural counterparts in cities dominated by impervious materials with large thermal inertia. Further use of these materials will result in even stronger urban temperature persistence, especially for tropical cities. The present findings help pinpoint mitigation strategies that can simultaneously ameliorate the larger magnitude and stronger persistence of urban temperatures. 

Abstract. Conventional and recently developed approaches for estimating turbulent scalar fluxes under stable atmospheric conditions are evaluated, with a focus on gases for which fast sensors are not readily available. First, the relaxed eddy accumulation (REA) classical approach and a recently proposed mixing length parameterization, labeled A22, are tested against eddy-covariance computations. Using high-frequency measurements collected from two contrasting sites (the frozen tundra near Utqiaġvik, Alaska, and a sparsely vegetated grassland in Wendell, Idaho, during winter), it is shown that the REA and A22 models outperform the conventional Monin–Obukhov similarity theory (MOST) utilized widely to infer fluxes from mean gradients. Second, scenarios where slow trace gas sensors are the only viable option in field measurements are investigated using digital filtering applied to fast-response sensors to simulate their slow-response counterparts. With a filtered scalar signal, the observed filtered eddy-covariance fluxes are referred to here as large-eddy-covariance (LEC) fluxes. A virtual eddy accumulation (VEA) approach, akin to the REA model but not requiring a mechanical apparatus to separate the gas flows, is also formulated and tested. A22 outperforms VEA and LEC in predicting the observed unfiltered (total) eddy-covariance (EC) fluxes; however, VEA can still capture the LEC fluxes well. This finding motivates the introduction of a sensor response time correction into the VEA formulation to offset the effect of sensor filtering on the underestimated net averaged fluxes. The only needed parameter for this correction is the mean velocity at the instrument height, a surrogate of the advective timescale. The VEA approach is very suitable and simple to use with gas sensors of intermediate speed (∼ 0.5 to 1 Hz) and with conventional open- or closed-path setups. 

Abstract Particularly challenging classes of heterogeneous surfaces are ones where strong secondary circulations are generated, potentially dominating the flow dynamics. In this study, we focus on land–sea breeze (LSB) circulations resulting from surface thermal contrasts, in the presence of increasing synoptic pressure forcing. The relative importance and orientation of the thermal and synoptic forcings are measured through two dimensionless parameters: a heterogeneity Richardson number (measuring the relative strength of geostrophic wind and convection induced by buoyancy), and the angleαbetween the shore and geostrophic wind. Large‐eddy simulations reveal the emergence of various regimes where the dynamics are asymmetric with respect toα. Along‐shore cases result in deep LSBs similar to the scenario with no synoptic background, irrespective of the geostrophic wind strength. Across‐shore simulations exhibit a circulation cell that decreases in height with increasing synoptic forcing. However, at the highest synoptic winds simulated, the circulation cell is advected away with sea‐to‐land winds, while a shallow circulation persists for land‐to‐sea cases. Scaling analysis that relates the internal parametersQ_shore(net shore volumetric flux) andq_shore(net shore advected kinematic heat flux) to the external input parameters results in a succinct model of the shore fluxes that also helps explain the physical implications of the identified LSBs. Finally, the vertical profiles of the shore‐normal velocity and shore‐advected heat flux are used, with the aid ofk‐means clustering, to independently classify the LSBs into four regimes (canonical, sea‐driven, land‐driven, and advected), corroborating our visual categorization.