Grid Spacing Research Articles

The Development of a Regional, High-Resolution OSSE Framework to Study the Impact of Observations from Uncrewed Aircraft Systems on Numerical Weather Prediction

Abstract Using Uncrewed Aircraft Systems (UAS) for routine weather observations is becoming increasingly feasible, but two open questions are the impact UAS observations will have on operational NWP and the optimal configuration of a UAS observing network. Deploying hundreds to thousands of UAS across the US to answer these questions is not feasible, so we propose using an Observing System Simulation Experiment (OSSE) instead. This article describes the development and validation of an OSSE framework for examining the impact of UAS observations on regional, convection-allowing NWP. The OSSE includes two week-long Nature Runs (NRs) over CONUS with 1-km grid spacing, simulated conventional observations, a 3-km forecast system similar to the prototype Rapid-Refresh Forecast System (RRFS), and verification workflows. Comparisons between the NR and various observations show that the NR generally mirrors reality, though the NR tends to produce too many reflectivity objects that are too large and larger coverage of intense precipitation rates compared to reality. Comparing real-data and OSSE RRFS runs indicates that, for the majority of the variables examined, forecast errors are not systematically smaller in the OSSE, suggesting that there is no identical twin issue. Data-denial experiments using either real or simulated conventional observations indicate that the OSSE has a similar ordering of most to least impactful observations, though the impact of aircraft observations tend to be larger in the OSSE. Altogether, these results suggest the OSSE framework can be used to glean meaningful information about UAS observation impacts on regional NWP.

Km-scale climate simulations over Madeira and Canary Islands under present and future conditions: a model intercomparison study

This study seeks to explore two new km-scale regional climate simulations prepared through the European Climate Prediction project over the Madeira and Canary islands, which are Portuguese and Spanish archipelagos located in the North Atlantic, off the African coast. The simulations are based on two models using different modelling approaches: COSMO-CLM with a three-step nesting at 50, 25 and 3 km grid spacing using a time-slice approach driven by a global climate model, and COSMO-crCLIM with a two-step nesting at 12 and 1 km grid spacing using the pseudo-global warming approach, where the current-day simulations are driven by ERA-Interim reanalysis. Although the modelling approaches are different, several findings are highlighted: (1) the use of km-scale simulation is essential to properly represent temperature and precipitation mean and extremes over small islands that are characterized by complex topography; (2) the projected changes in temperature and precipitation mean and extremes are qualitatively similar in all seasons except autumn; (3) the differences in the autumn projections are shown to be due to the large-scale driving conditions. Small islands, such as the Canary and Madeira ones, are often neglected by large modelling initiatives, so the presented simulations contribute to filling this gap for local policy makers, stakeholders and climate services. The encouraging results highlight the need for further coordinated km-scale projections.

Two-phase flow evolution and interfacial area transport downstream of the mixing-vane spacer grid in rod bundle channels

This study investigated the axial two-phase flow evolution and interfacial area transport characteristics downstream of the mixing vane spacer grid (MVSG) in a tight lattice rod bundle channel with a subchannel hydraulic diameter of Dh = 17.27 mm. The experiment was conducted under the air-water two-phase flow at room temperature and atmospheric pressure. The phase distributions of 6 positions downstream of MVSG (Z/Dh = 9.15, 14.94, 20.73, 26.52, 32.31, and 61.26) were measured utilizing a self-developed double-layer wire-mesh sensor (WMS). 42 cases were obtained, involving the bubbly flow, cap-bubbly flow, and slug flow. Void fraction, bubble velocity, interfacial area concentration (IAC), and bubble size distribution (BSD) databases were built. Under the group-1 (G-1) flow, due to the swirling flow generated by MVSG, the G-1 bubbles were drawn from the bundle surface and the gap region into the subchannel center to form a spindle core-peak distribution. BSD results demonstrate that the swirling flow promotes bubbles’ coalescence. The one-dimensional (1-D) void fraction and IAC downstream of the MVSG decrease first and then recover, which contrasts with the non-mixing vane spacer grid (N-MVSG) effect. It was attributed to the increment of the bubbles’ velocity after MVSG due to the bubbles’ migration to the channel center and coalescence. Under the group-2 (G-2) flow, MVSG intensifies the core peak distribution of void fraction, and the void fraction profile is also spindle-shaped. The obvious bubbles’ break-up occurs at Z/Dh = 14.94 attributed to the swirling decay. The 1-D void fraction and IAC transport indicate, that with the liquid-velocity increment, the MVSG effect is different from the N-MVSG effect, which is mainly achieved by affecting the G-1 bubbles’ dynamic behaviors. The model evaluation utilizing the interfacial area transport equation (IATE) closing bubble interaction source/sink terms indicates that the advection effect dominates the IAC evolution and the contribution of the pressure effect is weak. The remarkable bubbles’ coalescence occurs under the high liquid velocity. In future studies, the additional bubble break-up and coalescence source/sink term model considering the MVSG effect should be developed based on these cases to improve the IATE prediction ability.

Validation of the Ensemble Generalized Analog Regression Downscaling (En-GARD) Model to Downscale Near-Surface Wind Speed for the Northeast United States

Abstract Wind, often overlooked in climate change impact assessments, is now a crucial atmospheric variable due to our imminent reliance on renewable energy sources like wind energy. Therefore, establishing a wind speed database in higher temporal and spatial resolution is of great importance to assess wind power in historical periods and future projections. This study focuses on enhancing wind data representation and reliability of statistically downscaled model outputs by refining grid spacing from coarser to a desirable finer scale. Employing the Ensemble Generalized Analog Regression Downscaling (En-GARD) technique, we downscaled near-surface wind speed across a northeast (NE) U.S. domain that combines onshore and offshore wind farm areas. We tested multiple atmospheric variable combinations and identified near-surface wind speed (wind speed at 10 m), longitudinal and latitudinal wind at 10 m, and atmospheric temperature at 2 m, as the set that effectively guides the selection of analog days for the analog regression downscaling approach. Validation involved using ERA5 atmospheric reanalysis products (31 km) and high-resolution (4 km) Weather Research and Forecasting (WRF) Model simulations. Downscaling was conducted using a leave-one-year-out approach over 12 years (2001–12). Statistical analysis of the downscaled output over this period demonstrated a significant correlation and low error metrics (less than 20% for normalized RMSE and 16% for normalized MAE), indicating the reliability of the method and paving the way for its future application to downscale climate projection outputs. Significance Statement Wind speed has become a significant atmospheric variable due to our society’s imminent reliance on renewable energy resources like wind power. Often overlooked in climate change assessments, wind speed at a local scale over wind farm locations plays a crucial role in assessing and planning wind power resources in a future climate. We are providing the successful validation of a statistical downscaling methodology for near-surface wind speed at 4-km grid spacing using reanalysis data. The validity of the methodology gives confidence to downscale climate projection models and assess changes in wind speed for future climate scenarios in a follow-up study.

Enhancing structural analysis of nonrigid mechanisms in space grids through the Finite Particle Method

Enhancing structural analysis of nonrigid mechanisms in space grids through the Finite Particle Method

Regulable crack patterns for the fabrication of high-performance transparent EMI shielding windows.

Crack pattern-based metal grid film is an ideal candidate material for transparent electromagnetic interference shielding optical windows. However, achieving crack patterns with narrow grid spacing, small wire width, and high connectivity remains challenging. Herein, an aqueous acrylic colloidal dispersion was developed as a crack precursor for preparing crack patterns. The ratio of hard monomers in the precursor, the coating thickness, and the drying mediation strategy were systematically varied to control the spacing and width of the crack patterns. The resulting dense and narrow crack patterns served as sacrificial templates for the fabrication of patterning metal grid films on transparent substrates, intended for optoelectronic applications. These films demonstrated excellent optoelectronic properties (82.7% transmission at 550nm visible light, sheet resistance 4.1Ω/sq) and strong EMI shielding effectiveness (average shielding effectiveness 33.6 dB at 1-18 GHz), showcasing their potential as a scalable and effective transparent EMI shielding solution.

COMPUTING THE LOCAL QUALITY CHARACTERISTIC OF TETRAHEDRAL MESH ELEMENTS AS A SOLUTION EXTREME TASK

The paper discusses the problem of calculating the quality characteristic of elements of a triangulation grid (in multidimensional space). We call quality the degree of difference between a mesh element in a sense critical. For example, the difference between a triangle and a degenerate triangle. To calculate this value, the following construction is used. Mesh element vertices are treated as a numbered set of 𝑋 — points point family. In the space of such sets, the metric proposed in early works is introduced. As a result, the problem boils down to calculating the value of dist(𝑋,𝒴) — the distance between a set 𝑋 and a set 𝒴 defined by critical elements. In early works, the problem was solved through the empirical classification of families 𝑌 ∈ 𝒴 and excluding those that are not known to be closest to 𝑋. Namely, such that the offset some point in the 𝑌 family is given by the 𝑌 ′ ∈ 𝒴 family, which is closer to 𝑋. At the same time, empirical classification led to a large amount of calculations. This work gives a standardized classification of the families of the set 𝒴, allowing you to accurately describe the set of 𝒴− ⊂ 𝒴 of such families for which The specified conversion is not possible. That is, 𝒴− is approved dist(𝑋,𝒴) = dist(𝑋,𝒴−) . In addition, a diagram is given for constructing families of the set 𝒴− — analogues of the points of the assumed extremum in the extremum research problem of the function of numerical variables.

Optimal Location Method of Urban and Rural Emergency Shelter Based on Improved Ant Colony Algorithm

In order to realize the automatic location of urban and rural emergency shelters, the optimal location method of urban and rural emergency shelters based on the improved ant colony algorithm is proposed. Combined with the method of urban and rural land block grid space planning, the spatial grid planning of urban and rural distribution and the method of remote sensing image covering big data detection are adopted to extract the spatial grid geospatial detection model of urban and rural emergency shelters. The remote sensing images of urban and rural emergency shelters and the wireless sensor information sampling method of unmanned aerial vehicle (UAV) are adopted to establish the remote sensing images of urban and rural emergency shelters and the monitoring map database of UAV wireless sensor information. The improved ant colony optimization algorithm is adopted to optimize the path in the process of urban and rural emergency shelters’ site selection, and the overall geographical and geometric characteristics of urban and rural emergency shelters’ site selection are analyzed. The texture, color, shape and other characteristics related to the location of urban and rural emergency shelters are extracted, and the distributed optimization control method of dynamic ant colony is adopted to detect the distribution of geometric deformation characteristics and optimize the location of urban and rural emergency shelters. The location is realized by spatial enhancement of remote sensing dynamic information and the location of spatial feature points. The simulation results show that this method has a good positioning ability and a strong ability to optimize the location of emergency shelters in urban and rural areas.

A Numerical Study of the Impact of Topography on the July 2021 Extreme Rainfall Event in Zhengzhou, China

AbstractAn unprecedented extreme rainfall event occurred in Zhengzhou, Henan Province, China, in July 2021. To understand the impact of local topography on this extreme rainfall event, the Weather Research and Forecasting model is configured with 27 and 9 km model grid spacings (MGS), along with United States Geological Survey (USGS) topography data at 8.3 and 0.9 km resolutions, called MGS27_USGS8.3, MGS9_USGS8.3, and MGS9_USGS0.9. Results show that the 9 km MGS, permitting activities with coarse γ scales (∼20 km), successfully reproduces the generation of mesoscale cyclones. However, the finer topography enables a more accurate representation of orographic blocking and lifting effects, thereby adjusting the position of the mesoscale cyclone. It can depict the location of adiabatic processes, local circulation, and vertical pressure gradient forces more accurately, thereby adjusting the position of topography‐induced vertical motions. The turbulence diagnostics show that the topography‐induced lifting motion enhances clouds that block longwave radiation, leading to local environment warming, which in turn enhances turbulence and further amplifies the updrafts, ultimately improving the spatial distribution and temporal variation of precipitation. This study provides insights for an in‐depth understanding of the mechanisms of topography on extreme rainfall.

Dealing with steep slopes when modeling stable boundary‐layer flow in Alpine terrain

AbstractSteep slopes in mountainous terrain are challenging for commonly used numerical weather prediction models using terrain‐following coordinates since they can generate numerical errors when evaluating horizontal gradients, and numerical instabilities. The model orography is therefore generally smoothed locally so as to remove slopes exceeding a defined threshold, typically in the range 30°–40°. However, this process can lead to undesired changes to orographic features at the scale of the mountain range. So as to preserve properties of the orography, e.g., mean terrain height across the domain, a global smoothing algorithm is developed. The algorithm is then applied to a domain centred on the Alpine Grenoble valley. Exploration of the parameters of the algorithm allows to minimize the changes in the orography in the domain, especially that of the two main valleys (of width 2 and 5 km and depth about 2000 m). Results of numerical model simulations are next analyzed to evaluate the effects of the slope threshold on local‐ and valley‐scale atmospheric dynamics for a cold‐air pool episode. Model results from simulations with slope thresholds of 28° and 42° are compared, the lower threshold allowing for a reduction (albeit small in practice) of the near‐surface vertical grid spacing. Remarkably, not only are the near‐surface boundary‐layer temperature and wind fields similar for both simulations (and in very good agreement with observations), but this similarity holds in the whole inversion layer throughout the episode. The reasons for this similarity are that, for this cold‐air pool episode, the valley atmospheric dynamics is confined within the inversion layer and the orography is essentially unchanged by the smoothing algorithm in that layer for the slope threshold of 28° and 42°.

Коррекция и усвоение данных гидрологических наблюдений температуры водных объектов

The paper proposes an algorithm for correcting the data of hydrological observations of water temperature and an algorithm for assimilating corrected data for calculations of water body surface temperatures in Russia. The temperatures are used in initial data for computing global medium-range weather forecasts with the new version of the SLAV10 model with a grid spacing of about 10 km. The correction algorithm for hydrological observations of water temperature makes it possible to eliminate ambiguity in temperature coding at most gauging stations. The assimilation of corrected hydrological observations allows reducing water body surface temperature errors in the SLAV10 model initial data as compared to specifying water temperature from the data of the nearest land points.

The actuator farm model for large eddy simulation (LES) of wind-farm-induced atmospheric gravity waves and farm–farm interaction

Abstract. This study introduces the actuator farm model (AFM), a novel parameterization for simulating wind turbines within large eddy simulations (LESs) of wind farms. Unlike conventional models like the actuator disk (AD) or actuator line (AL), the AFM utilizes a single actuator point at the rotor center and only requires two to three mesh cells across the rotor diameter. Turbine force is distributed to the surrounding cells using a new projection function characterized by an axisymmetric spatial support in the rotor plane and Gaussian decay in the streamwise direction. The spatial support's size is controlled by three parameters: the half-decay radius r1/2, smoothness s, and streamwise standard deviation σ. Numerical experiments on an isolated National Renewable Energy Laboratory (NREL) 5MW wind turbine demonstrate that selecting r1/2=R (where R is the turbine radius), s between 6 and 10, and σ≈Δx/1.6 (where Δx is the grid size in the streamwise direction) yields wake deficit profiles, turbine thrust, and power predictions similar to those obtained using the actuator disk model (ADM), irrespective of horizontal grid spacing down to the order of the rotor radius. Using these parameters, LESs of a small cluster of 25 turbines in both staggered and aligned layouts are conducted at different horizontal grid resolutions using the AFM. Results are compared against ADM simulations employing a spatial resolution that places at least 10 grid points across the rotor diameter. The wind farm is placed in a neutral atmospheric boundary layer (ABL) with turbulent inflow conditions interpolated from a previous simulation without turbines. At horizontal resolutions finer than or equal to R/2, the AFM yields similar velocity, shear stress, turbine thrust, and power as the ADM. Coarser resolutions reveal the AFM's ability to accurately capture power at the non-waked wind farm rows, although it underestimates the power of waked turbines. However, the far wake of the cluster can be predicted well even when the cell size is of the order of the turbine radius. Finally, combining the AFM with a domain nesting method allows us to conduct simulations of two aligned wind farms in a fully neutral ABL and of wind-farm-induced atmospheric gravity waves under a conventionally neutral ABL, obtaining excellent agreement with ADM simulations but with much lower computational cost. The simulations highlight the AFM's ability to investigate the mutual interactions between large turbine arrays and the thermally stratified atmosphere.

CALCULATION OF PLASMA HEATING BY CHARGED PRODUCTS OF THERMONUCLEAR REACTIONS BASED ON A SIMPLIFIED FOKKER–PLANCK EQUATION

A two-time-layer scheme has been developed for solving the simplified kinetic Fokker–Planck equation related to the transport of charged products of thermonuclear reactions, which includes an interpolation procedure in four-dimensional grid space. Instabilities in the scheme were detected at low particle velocities and for a specific choice of particle deceleration in the ion field, which enters the kinetic equation as a parameter. It was shown that the thermalization condition, which prohibits solving the kinetic equation for particles with energy lower than the average ion energy, significantly limits the number of thermonuclear reactions where instability can manifest. The scheme was tested on the problem of relaxation to a stationary state and on a problem with a prescribed time-dependent thermonuclear reaction rate, for which an exact solution to the kinetic equation can be found.

Simulating Precipitation Efficiency Across the Deep Convective Gray Zone

AbstractPrecipitation efficiency (PE) relates cloud condensation to precipitation and thus reflects how much of the total atmospheric condensate reaches the surface as precipitation. Because the PE in convective storms is directly linked to their updraft and downdraft dynamics, it is a helpful metric to identify convective processes that influence precipitation. However, km‐scale model simulations do not properly resolve convective processes such as individual updrafts and entrainment, which raises the question if such simulations can accurately represent PE. Here, we present two methods to derive PE from standard model output because condensation is usually not available as an output variable. The first method estimates PE from the state variables vertical velocity, temperature, and pressure, whereas the second method estimates PE from ice water path (IWP) and precipitation. We validate the proposed methods with the explicitly calculated PE using a set of idealized Weather Research and Forecast model simulations of organized midlatitude convective storms at different horizontal grid spacings. We show that PE can be reliably estimated from state variables with an error of less than 5%, partly due to error cancellation effects. Additionally, PE can be simulated by km‐scale models within ∼15% accuracy compared to large‐eddy simulations (LESs). The IWP method is slightly less accurate with a stronger grid spacing dependency of the error, but since it is based on observable quantities, it allows for a validation of simulated PE with satellite observations. Finally, we analyze the grid spacing dependency of the climate change signal of PE and find that future decreases in PE in LESs are robustly captured by km‐scale models.

Investigating numerical stability by scaling heat conduction in a 1D hydrodynamic model of the solar atmosphere

Numerical models of the solar atmosphere are widely used in solar research and provide insights into unsolved problems such as the heating of coronal loops. A prerequisite for such simulations is an initial condition for the plasma temperature and density. Many explicit numerical schemes employ high-order derivatives that require some diffusion, for example isotropic diffusion, for each independent variable to maintain numerical stability. Otherwise, significant numerical inaccuracies and subsequent wiggles will occur and grow at steep temperature gradients in the solar transition region. We tested how to adapt the isotropic heat conduction to the grid resolution so that the model is capable of resolving varying temperature gradients. Our ultimate goal is to construct an atmospheric stratification that can serve as an initial condition for multi-dimensional models. Our temperature stratification spans from the solar interior to the outer corona. From that, we computed the hydrostatic density stratification. Since numerical and analytical derivatives are not identical, the model needs to settle to a numerical equilibrium to fit all model parameters, such as mass diffusion and radiative losses. To compensate for energy losses in the corona, we implemented an artificial heating function that mimics the expected heat input from the 3D field-line braiding mechanism. Our heating function maintains and stabilises the obtained coronal temperature stratification. However, the diffusivity parameters need to be adapted to the grid spacing. Unexpectedly, we find that higher grid resolutions may need larger diffusivities --- contrary to the common understanding that high-resolution models are automatically more realistic and would need less diffusivity. Smaller grid spacing causes larger temperature gradients in the solar transition region and hence a greater potential for numerical problems. We conclude that isotropic heat conduction is an efficient remedy when using explicit schemes with high-order numerical derivatives.

Causes of Differences in Depiction of Convective Lines in 1-km and 3-km CM1 Simulations

Abstract Previous research has shown that 3-km horizontal grid spacing simulations depicting clusters of cells often change to showing linear structures when grid spacing is refined to 1-km. This increase in linear structures at finer horizontal grid spacings may be due simply to the resolving of stronger vertical motion along the leading edge of the MCS cold pool resulting in more continuous zones of convection in higher resolution runs. However, prior work has suggested that the cold pools themselves are stronger with finer grid spacing, enhancing lift to grow linear morphologies faster. In the present study, Cloud Model 1 was used to simulate an array of MCSs with varying wind profiles and a constant thermodynamic profile (Weisman-Klemp analytic sounding) at both 1- and 3-km horizontal grid spacings and with 50 and 100 vertical levels. A line of seven randomly-spaced warm bubbles was used to initiate convection. In 1-km Δx simulations, gravity waves dominated in initiating new convection for growth into lines, and the ascent associated with them was much greater than in 3-km runs. Upscale growth into lines in 3-km Δx simulations was driven more by ascent caused by the collision of convective cold pools.

Robust variability of grid cell properties within individual grid modules enhances encoding of local space.

Although grid cells are one of the most well studied functional classes of neurons in the mammalian brain, whether there is a single orientation and spacing value per grid module has not been carefully tested. We analyze a recent large-scale recording of medial entorhinal cortex to characterize the presence and degree of heterogeneity of grid properties within individual modules. We find evidence for small, but robust, variability and hypothesize that this property of the grid code could enhance the encoding of local spatial information. Performing analysis on synthetic populations of grid cells, where we have complete control over the amount heterogeneity in grid properties, we demonstrate that grid property variability of a similar magnitude to the analyzed data leads to significantly decreased decoding error. This holds even when restricted to activity from a single module. Our results highlight how the heterogeneity of the neural response properties may benefit coding and opens new directions for theoretical and experimental analysis of grid cells.

What Are the Finger‐Like Clouds in the Hurricane Inner‐Core Region?

AbstractFinger‐like km‐scale features have been observed along the inner‐edge of the eyewall of intense hurricanes. But due to the limited availability of observations, many important aspects of these features remain unknown. In this study, we aim to offer insights on the nature of these phenomena based on a four‐day‐duration O(100 m) grid spacing simulation that covers the inner‐core region of an idealized hurricane. The simulation successfully captured the finger‐like features, which closely resemble observed ones. We propose that these features are formed due to the shear instability associated with vertical distribution of the tangential wind in the inner‐core region. This proposed mechanism offers insights on several key characteristics of the features of interest, including their emergence time, frequency, radial location and vertical extent. Our study also demonstrates the feasibility of using multi‐level nesting for O(100 m) grid spacing hurricane simulations and predictions, aligning with the goals for next generation hurricane models.

Use of multiple reference data sources to cross-validate gridded snow water equivalent products over North America

Abstract. We use snow course and airborne gamma data available over North America to compare the validation of gridded snow water equivalent (SWE) products when evaluated with one reference dataset versus the other. We assess product performance across both non-mountainous and mountainous regions, determining the sensitivity of relative product rankings and absolute performance measures. In non-mountainous areas, product performance is insensitive to the choice of SWE reference dataset (snow course or airborne gamma): the validation statistics (bias, unbiased root mean squared error, and correlation) are consistent with one another. In mountainous areas, the choice of reference dataset has little impact on relative product ranking but a large impact on assessed error magnitudes (bias and unbiased root mean squared error). Further analysis indicates the agreement in non-mountainous regions occurs because the reference SWE estimates themselves agree up to spatial scales of at least 50 km, comparable to the grid spacing of most available SWE products. In mountain areas, there is poor agreement between the reference datasets, even at short distances (< 5 km). We determine that differences in assessed error magnitudes result primarily from the range of SWE magnitudes sampled by each method, although their respective spatiotemporal distribution and elevation differences between the reference measurements and grid centroids also play a role. We use this understanding to produce a combined reference SWE dataset for North America, applicable to future gridded SWE product evaluations and other applications.

The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Many current gridded surface meteorological datasets are inadequate for quantifying near-surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981–2018 over the CONUS at daily temporal resolution. Daily maximum, minimum, and mean values for a variety of temperature estimates, humidity, and surface energy budget terms, among others, are included. This High-resolution Urban Meteorology for Impacts Dataset (HUMID) will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology.