Mesoscale Atmospheric Model Research Articles

Atmospheric mesoscale modeling to simulate annual and seasonal wind speeds for wind energy production in Mexico

Numerical models have been used widely to reproduce wind resources around the globe. Mexico’s vast territory has a wide range of geographical characteristics with abundant wind potential. This work explores WRF simulations applied to reproduce the wind speed and capacity factor (CF) of 22 wind masts, organized into seven regions delimited by geographic conditions and consisting of 33 years of data. Biases, correlations, dispersion indexes and terrain gradient are selected to study the model and experimental data annually and seasonally. Results indicate that WRF simulations show a persistent positive bias in all regions, leading to overestimating CF. In a seasonal analysis, 86% of the CF data falls between the -0.1 and 0.1 bias range. Bias is not related to a physical seasonal phenomenon; instead, it appears to be related to geographic conditions. The findings indicate that different combinations of settings should be chosen to better reflect the geographical conditions and physical phenomena that affect the intricate Mexican landscape for wind energy production. This research identify regions with best reproducibility and suggests potential areas for future research on wind energy forecasting.

Resource Assessment for Distributed Wind Energy: An Evaluation of Best-Practice Methods in the Continental US

Current wind resources within the United States (US) indicate a potential to profitably install nearly 1,400 gigawatts of distributed wind (DW) capacity. This amount is equivalent to over half of the United States’ current energy demand from electricity, making it enough to power millions of homes and businesses and replace countless fossil fuel-based generating plants. Despite the potential growth of DW in the US, deployments are presently hindered by a lack of confidence in resource estimation methods. One potential challenge is that smaller-scale turbines, with hub heights of 40 meters or less, are disproportionately impacted by obstacles such as buildings and vegetation. These obstacles may produce complex wake effects, best modeled with high-fidelity complex fluid dynamics (CFD) models that are too computationally expensive to use for routine siting and resource assessment. Thus, installers today make use of heuristics and simple equations to approximate the impact of obstacles while also leveraging long-term resource data from commercial or publicly available atmospheric models. This study evaluates these historical and commonly used methods alongside new lower-order obstacle models produced from CFD simulations and measurement-based bias correction. The preliminary results from this study show the importance of taking care in the choice and application of mesoscale atmospheric models and the significant value of bias correction using measurements from nearby meteorological towers. Detailed obstacle modeling provides only modest additional gains in performance and, in some cases, can add error, especially at sites where turbines have already been located to avoid obvious impact from upwind obstacles. These findings reinforce the importance of collecting in situ measurements and suggest that obstacle models may be better applied in practice to automated or computer-aided siting, rather than in economic wind resource assessments.

A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)

Abstract. In recent years, urban canopy models (UCMs) have been used as fully coupled components of mesoscale atmospheric models as well as offline tools to estimate temperature and surface fluxes using atmospheric forcings. Examples include multi-layer urban canopy models (MLUCMs), where the vertical variability of turbulent fluxes is calculated by solving prognostic momentum and turbulent kinetic energy (TKE, k) using mixing length scale (l) and drag parameterizations. These parameterizations are based on the well-established 1.5-order k−l turbulence closure theory and are often informed by microscale fluid dynamics simulations. However, this approach can include simplifications such as assuming the same diffusion coefficient for momentum, TKE, and scalars. In addition, the dispersive stresses arising from spatially averaged flow properties have been parameterized together with the turbulent fluxes despite being controlled by different mechanisms. Both of these assumptions impact the quantification of the turbulent exchange of flow properties and subsequent air temperature predictions in urban canopies. To assess these assumptions and improve corresponding parameterization, we analyzed 49 large-eddy simulations (LES) for idealized urban arrays, encompassing variable building height distributions and a comprehensive range of urban densities (λp∈[0.0625,0.64]) seen in global cities. We find that the efficiency of turbulent transport (numerically described via diffusion coefficients) is similar for scalars and momentum but is 3.5 times higher for TKE. Additionally, parameterizing the dispersive momentum flux using the k−l closure was a source of error, while scaling with the pressure gradient and urban morphological parameters appears more appropriate. In response to these findings, we propose two changes to the previous version of MLUCM: (a) separate characterization for turbulent diffusion coefficient for momentum and TKE and (b) introduction of an explicit physics-based “mass-flux” term to represent the fraction of the dispersive momentum transport directly induced from buildings as an amendment to the existing “eddy-diffusivity” framework. The updated one-dimensional model, after being tuned for building height variability, is further compared against the original LES results and demonstrates improved performance in predicting vertical turbulent exchange in urban canopies.

Atmospheric Sea Spray Modeling in the North‐East Atlantic Ocean Using Tunnel‐Derived Generation Functions and the SUMOS Cruise Data Set

AbstractThis study contributes to the communal effort to improve understanding of sea spray generation and transport. For the first time, laboratory‐derived sea spray generation functions (SSGFs) are parameterized in the Meso‐NH mesoscale atmospheric model and are field tested. Formulated from the MATE19 laboratory experiments (Bruch et al., 2021, https://doi.org/10.1007/s10546-021-00636-y) the two SSGFs are driven by the upwind component of the wave‐slope variance (herein B21A), or both and the wind friction velocity cubed (herein B21B). In this first attempt to incorporate the SSGFs in Meso‐NH, the simulations are run without a wave model, and the wave‐wind SSGFs are assumed wind‐dependent. Model evaluation is achieved with a new set of sea spray and meteorological measurements acquired over the 0.1–22.75 μm radius range and U10 1–20 m s−1 wind speeds onboard R/V Atalante during the 25 day SUMOS field campaign in the Bay of Biscay. The B21B SSGF offers particularly good sensitivity to a wide range of environmental conditions over the size range, with an average overestimation by a factor 1.5 compared with measurements, well below the deviations reported elsewhere. B21A also performs well for larger droplets at wind speeds above 15 m s−1. Associated with airflow separation and wave breaking, wave‐slope variance allows to represent multiple wave scales and to scale sea spray generation in the laboratory and the field. Using Meso‐NH simulations we find that sea spray may be transported inland and to altitudes well above the marine atmospheric boundary layer.

Конфигурация COSMO-Ru2By модели COSMO: успешность и методология оценки численных прогнозов - и γ-мезомасштабных атмосферных процессов

The paper gives а brief description of the COSMO-Ru2By configuration (the grid spacing is 2.2 km) of the COSMO model, which provides numerical weather forecasts for up to 48 hours for the European part of Russia and for the Republic of Belarus, as well the methodology and results of skill of these forecasts. The COSMO-Ru2By was realized in the Hydrometcentre of Russia and operates as an element of the COSMO-Ru operational limited-area numerical weather prediction system on the CRAY XС40-LC supercomputer. The features of the COSMO-Ru2By are: 1) a vast calculation domain with a grid spacing that allows an explicit description of large (over 5-6 km high) convective motions and considering in detail the features of terrain; 2) the “embedded” technology for assimilation of DMRL-C Doppler weather radar data providing more accurate forecasts of rapidly developing weather processes for the next few hours; 3) coupled visualization system providing a great number of maps for different regions with a cascade image detailing. Operational trials in 2020-2021 showed a high skill of forecasts of the basic weather parameters with the COSMO-Ru2By. For comparison with forecasts of highly variable weather parameters (wind gusts, hourly precipitation, parameters in mountain areas, etc.) based on mesoscale models with lower resolution (e.g., COSMO-Ru6ENA, the grid size is 6.6 km), it was proposed to apply expanded trial approaches and criteria: e.g., the estimation over geographically homogeneous areas, the use of special criteria for predicting rare events, the comparison with radar data. Keywords: numerical weather prediction, mesoscale atmospheric modeling, radar data assimilation, weather forecast skill estimation, non-hydrostatic atmosphere models

Validation of an OpenFOAM®-based solver for the Euler equations with benchmarks for mesoscale atmospheric modeling

Within OpenFOAM, we develop a pressure-based solver for the Euler equations written in conservative form using density, momentum, and total energy as variables. Under simplifying assumptions, these equations are used to describe non-hydrostatic atmospheric flow. For the stabilization of the Euler equations and to capture sub-grid processes, we consider two Large Eddy Simulation models: the classical Smagorinsky model and the one equation eddy-viscosity model. To achieve high computational efficiency, our solver uses a splitting scheme that decouples the computation of each variable. The numerical results obtained with our solver are validated against numerical data available in the literature for two classical benchmarks: the rising thermal bubble and the density current. Through qualitative and quantitative comparisons, we show that our approach is accurate. This paper is meant to lay the foundation for a new open-source package specifically created for the quick assessment of new computational approaches for the simulation of atmospheric flows at the mesoscale level.

Postflight Analysis of Atmospheric Properties from Mars 2020 Entry, Descent, and Landing

The Mars 2020 spacecraft landed the Perseverance rover and Ingenuity helicopter successfully in Jezero crater on Feb. 18, 2021. The entry, descent, and landing (EDL) sequence of the spacecraft largely leveraged the previous 2012 Mars Science Laboratory (MSL) mission. The atmospheric modeling approach for Mars 2020 was also borrowed from MSL. It consisted of two mesoscale atmospheric models of the target site and a statistical model of the pressure, density, temperature, and winds based on the mesoscale model data. This paper briefly describes the preflight atmospheric models used for Mars 2020, but focuses on the postflight assessment of these models and comparison to near-landing day orbiter sounder and other onboard atmospheric measurements. Observations from postflight analysis showed that density was underpredicted in the upper atmosphere, but within the altitudes covered by the mesoscale models, the preflight modeling matched postflight results, including for quantities like wind velocities. Potential improvements to address the upper atmosphere and other deficiencies of the Mars 2020 preflight model are also discussed.

Coupled and Stand-Alone Regional Climate Modeling of Intensive Storms in Western Canada

A coupled atmospheric-hydrologic system models the complex interactions between the land surface and the atmospheric boundary layer and the water-energy cycle from groundwater across the land surface to the top of the atmosphere. A regional climate model called weather research forecasting (WRF) was coupled with a land-surface scheme (Noah) to simulate intensive storms in Alberta of Canada. Accounting for the land-atmosphere feedback enhances the predictability of the fine-tuned WRF-Noah system. Soil moisture, vegetation, and land-surface temperature influence latent and sensible heat fluxes and modulate both thermal and dynamical characteristics of land and the lower atmosphere. WRF was set up in a two-way, 3-domain nested framework so that the output of the outermost domain (D1) was used to run the 2nd domain (D2), and the output of D2 was used to run the innermost, 3rd domain (D3). By this 2-way nesting, D3 and D2 provide the feedback to their outer domains (D2 and D1), respectively. D3 was set at a 3-km resolution adequate to simulate convective storms. WRF-Noah was forced with climate outputs from global climate models (GCMs) for the baseline period 1980–2005. A regional frequency analysis and a quantile-quantile bias correction method were applied to develop intensity-duration-frequency (IDF) curves using precipitation data simulated by WRF-Noah. The simulated baseline precipitation of central Alberta agrees well with observed data from a 13-rain gauge network of the City of Edmonton. The 5th-generation mesoscale atmospheric model (MM5) of National Center for Atmospheric Research was also set up in a 3-domain, but 1-way nesting configuration. As expected, after bias correction, precipitation simulated by MM5 was less accurate than that simulated by WRF-Noah. For storms of short durations and return periods of more than 25 years, both MM5 driven by special reports on emission scenario climate scenarios of coupled model inter-comparison project (CMIP3) and WRF-Noah driven by representative concentration pathway climate scenarios of CMIP5 projected storm intensities in central Alberta to increase from the base period to the 2050s and to the 2080s.

Regional CO2 Inversion Through Ensemble‐Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments

AbstractAtmospheric inversions provide estimates of carbon dioxide (CO2) fluxes between the surface and atmosphere based on atmospheric CO2 concentration observations. The number of CO2 observations is projected to increase severalfold in the next decades from expanding in situ networks and next‐generation CO2‐observing satellites, providing both an opportunity and a challenge for inversions. This study introduces the TRACE Regional Atmosphere–Carbon Ensemble (TRACE) system, which employ an ensemble‐based simultaneous state and parameter estimation (ESSPE) approach to enable the assimilation of large volumes of observations for constraining CO2 flux parameters. TRACE uses an online full‐physics mesoscale atmospheric model and assimilates observations serially in a coupled atmosphere–carbon ensemble Kalman filter. The data assimilation system was tested in a series of observing system simulation experiments using in situ observations for a regional domain over North America in summer. Under ideal conditions with known prior flux parameter error covariances, TRACE reduced the error in domain‐integrated monthly CO2 fluxes by about 97% relative to the prior flux errors. In a more realistic scenario with unknown prior flux error statistics, the corresponding relative error reductions ranged from 80.6% to 88.5% depending on the specification of prior flux parameter error correlations. For regionally integrated fluxes on a spatial scale of 106 km2, the sum of absolute errors was reduced by 34.5%–50.9% relative to the prior flux errors. Moreover, TRACE produced posterior uncertainty estimates that were consistent with the true errors. These initial experiments show that the ESSPE approach in TRACE provides a promising method for advancing CO2 inversion techniques.

High resolution wind resource assessment method based on mesoscale atmospheric model and CFD technology

The evaluation results of wind energy resources directly affect the economic benefits and healthy development of wind farms. Therefore, a high-resolution wind resource assessment method for wind farms based on mesoscale atmospheric model and CFD technology is studied to accurately simulate relevant data of wind resources and improve the assessment effect. The mesoscale WRF numerical model is used to solve the regional data of wind farms and obtain the mesoscale meteorological analysis data. According to the solution results of the mesoscale atmospheric model, the wind speed profile is established, the boundary conditions and initial conditions are extracted, and the CFD micro scale model is input to obtain the wind speed and wind speed frequency at the height of the fan impeller. In order to improve the accuracy of numerical simulation of micro scale CFD model, the large eddy simulation method is used to simulate the operation of wind farms. Complete theoretical power generation evaluation based on wind speed, wind speed frequency and generator power. The experimental results show that this method can accurately simulate wind resources and accurately evaluate the theoretical power generation of wind farms. The wind farm is rated as Level 3, and the wind frequency is mainly between 4 and 10 m/s. This method can ensure that the wind farm can generate electricity all year round without damaging the wind speed.

From Macro- to Microscale: A combined modelling approach for near-surface wind flow on Mars at sub-dune length-scales.

The processes that initiate and sustain sediment transport which contribute to the modification of aeolian deposits in Mars' low-density atmosphere are still not fully understood despite recent atmospheric modelling. However, detailed microscale wind flow modelling, using Computational Fluid Dynamics at a resolution of <2 m, provides insights into the near-surface processes that cannot be modeled using larger-scale atmospheric modeling. Such Computational Fluid Dynamics simulations cannot by themselves account for regional-scale atmospheric circulations or flow modifications induced by regional km-scale topography, although realistic fine-scale mesoscale atmospheric modeling can. Using the output parameters from mesoscale simulations to inform the input conditions for the Computational Fluid Dynamics microscale simulations provides a practical approach to simulate near-surface wind flow and its relationship to very small-scale topographic features on Mars, particularly in areas which lack in situ rover data. This paper sets out a series of integrated techniques to enable a multi-scale modelling approach for surface airflow to derive surface airflow dynamics at a (dune) landform scale using High Resolution Imaging Science Experiment derived topographic data. The work therefore provides a more informed and realistic Computational Fluid Dynamics microscale modelling method, which will provide more detailed insight into the surface wind forcing of aeolian transport patterns on martian surfaces such as dunes.

Air–Sea Interactions on Titan: Effect of Radiative Transfer on the Lake Evaporation and Atmospheric Circulation

Titan’s northern high latitudes host many large hydrocarbon lakes. Like water lakes on Earth, Titan’s lakes are constantly subject to evaporation. This process strongly affects the atmospheric methane abundance, the atmospheric temperature, the lake mixed layer temperature, and the local wind circulation. In this work we use a 2D atmospheric mesoscale model coupled to a slab lake model to investigate the effect of solar and infrared radiation on the exchange of energy and methane between Titan’s lakes and atmosphere. The magnitude of solar radiation reaching the surface of Titan through its thick atmosphere is only a few watts per square meter. However, we find that this small energy input is important and is comparable in absolute magnitude to the latent and sensible heat fluxes, as suggested in a study by Rafkin & Soto (2020). The implementation of a gray radiative scheme in the model confirms the importance of radiation when studying lakes at the surface of Titan. Solar and infrared radiation change the energy balance of the system leading to an enhancement of the methane evaporation rate, an increase of the equilibrium lake temperature almost completely determined by its environment (humidity, insolation, and background wind), and a strengthening of the local sea breeze, which undergoes diurnal variations. The sea breeze efficiently transports methane vapor horizontally, from the lake to the land, and vertically due to rising motion along the sea breeze front and due to radiation-induced turbulence over the land.

МОДЕЛИРОВАНИЕ ЭВОЛЮЦИИ ЗАСУШЛИВЫХ УСЛОВИЙ В XXI ВЕКЕ ДЛЯ ОБОСНОВАНИЯ МЕР ПО АДАПТАЦИИ АГРОСЕКТОРА РОССИИ К КЛИМАТИЧЕСКИМ ВОЗДЕЙСТВИЯМ

The spatiotemporal evolution of actual and potential evapotranspiration and water deficit (stress) of the irrigated surfaces during the 21st century influenced by the changes in the meteorological drought characteristics is analyzed for the southern regions of European Russia for individual months of the growing season. The joint system of the MGO regional climate model and the mesoscale atmospheric boundary layer model is used to estimate regional and local climate change. The effect of the evapotranspiration evaluation method on the resulting estimates is investigated. The expansion of the territory affected by droughts of various severity is projected for all months of the growing season. It is shown that the major risk for vegetation due to water deficit during droughts may be expected at the beginning of the growing season.

Mesoscale/Microscale and CFD Modeling for Wind Resource Assessment: Application to the Andaman Coast of Southern Thailand

Situated in the southern part and on the western coast of Thailand, the Andaman Coast covers the provinces of Ranong, Phangnga, Phuket, Krabi, Trang and Satun. Using a coupled mesoscale atmospheric model and a microscale wind flow model, along with computational fluid dynamics (CFD) modeling, this paper presents a detailed assessment of the wind energy potential for power generation along the Andaman Coast of Thailand. The climatic data are obtained from the Modern Era Retrospective analysis for Research and Applications (MERRA), along with a high-resolution topography database and Land Use Land Cover digital data. The results are compared to the equivalent wind speeds obtained with the Weather Research and Forecasting (WRF) atmospheric model. The results showed that, at 120 m above ground level (agl), the predicted wind speeds from the models proposed were 20% lower for the mesoscale model and 10% lower for the microscale model when compared to the equivalent wind speeds obtained from the WRF model. A CFD wind flow model was then used to investigate 3D wind fields at 120–125 m agl over five potential sites offering promising wind resources. The annual energy productions (AEP) and the capacity factors under three different wake loss models and for five wind turbine generator technologies were optimized for 10-MW wind power plants, as per Thailand’s energy policies. With capacity factors ranging from 20 to 40%, it was found that the AEPs of the best sites were in the range of 18–36 GWh/year, with a total AEP in the vicinity of 135 GWh/year when using a single wind turbine model for the five sites studied. The combined energy productions by these wind power plants, once operational, could avoid GHG emissions of more than 80 ktons of CO2eq/year.

Numerical Analysis of the Atmospheric Boundary-Layer Turbulence Influence on Microscale Transport of Pollutant in an Idealized Urban Environment

The mesoscale atmospheric model Meso-NH is used to investigate the influence of mesoscale atmospheric turbulence on the mean flow, turbulence, and pollutant dispersion in an idealized urban-like environment, the array of containers investigated during the Mock Urban Setting Test field experiment. First, large-eddy simulations are performed as in typical computational fluid dynamics-like configurations, i.e., without accounting for the atmospheric- boundary-layer (ABL) turbulence on scales larger than the building scale. Second, in a multiscale configuration, turbulence of all scales prevailing in the ABL is accounted for by using the grid-nesting approach to downscale from the mesoscale to the microscale. The building-like obstacles are represented using the immersed boundary method and a new turbulence recycling method is used to enhance the turbulence transition between two nested domains. Upstream of the container array, flow characteristics such as wind speed, direction and turbulence kinetic energy are well reproduced with the multiscale configuration, showing the efficiency of the grid-nesting approach in combination with turbulence recycling for downscaling from the mesoscale to the microscale. Only the multiscale configuration is able to reproduce the mesoscale turbulent structures crossing the container array. The accuracy of the numerical results is evaluated for wind speed, wind direction, and pollutant concentration. The microscale numerical simulation of wind speed and pollutant dispersion in an urban-like environment benefits from taking into account the ABL turbulence. However, this benefit is significantly less important than that described in the literature for the Oklahoma City Joint Urban 2003 real case. The present study highlights that pollutant dispersion simulation improvement when accounting for ABL turbulence is dependent on the specific configuration of the city.

The Skill Assessment of Weather and Research Forecasting and WAVEWATCH-III Models During Recent Meteotsunami Event in the Persian Gulf

This study aims to use a fully realistic high-resolution mesoscale atmospheric and wave model to reproduce met-ocean conditions during a meteotsunami in the Persian Gulf. The atmospheric simulations were performed with the Weather and Research Forecasting (WRF) model by varying planetary boundary layer, microphysics, cumulus, and radiations parameterizations. The atmospheric results were compared to the meteorological observations (e.g., air pressure and wind speed) from the coastal and island synoptic and buoy stations of the nearest area to the meteotsunami event. The results show that using Mellor-Yamada-Nakanishi-Niino (MYNN) scheme for planetary boundary and surface layer had the best performance for stations over the water, whereas applying Mellor-Yamada-Janjic scheme for planetary boundary and Eta similarity surface layer had the best performance for stations over the land. For wave simulations, the WAVEWATCH-III model was employed with the well-known WAM-Cycle4 formulation and a more recent ST6 package. Six WRF experiments and ERA5 wind data were used to force the wave models. The new error parameter was introduced to identify the optimum wind data for wave simulation. EXP4 configuration which uses the MYNN scheme for planetary boundary and surface layer was led to minimum error, while ERA5 severely underestimated Hs and Tp parameters. For the first time, the Gaussian Quadrature Method (GQM) was implemented in the WAVEWATCH-III model and combined with a depth scale to be used in the Persian Gulf. This method is more accurate for non-linear wave-wave interaction than the default Discrete Interaction Approximation (DIA) method. Lower coefficients for dissipation term were required for GQM and the resulted bulk wave parameters were improved compared to the DIA method. The calibrated ST6 formulation with GQM resulted in a more realistic prediction of wave spectrum than the default settings of the WAVEWATCH-III.

Estimation of mean radiant temperature in cities using an urban parameterization and building energy model within a mesoscale atmospheric model

Estimation of mean radiant temperature in cities using an urban parameterization and building energy model within a mesoscale atmospheric model

Planet Four: Derived South Polar Martian Winds Interpreted Using Mesoscale Modeling

Abstract For the first time, model-derived and imagery-derived wind directions and speeds have been compared in Mars’s south polar region. Seasonal fan-shaped deposits are routinely observed by HiRISE in the polar regions. They are widely accepted to result from CO2 gas jet eruptions. Fan lengths, sizes, and shapes can provide information about wind directions and strengths at the times such eruptions occur. We utilize a catalog of those fan-shaped deposits, marked by citizen scientists within the framework of the Planet Four (P4) project, at 27 regions of interest (ROIs) for two spring seasons (Mars years 29 and 30). Fans change considerably from one HiRISE image to another at most of these ROIs as wind direction changes over the spring season. Leveraging this characteristic, intraseasonal variations in near-surface wind speeds and directions were retrieved and compared to near-surface winds predicted by a mesoscale atmospheric model (MRAMS) at the same ROIs. At most ROIs P4-inferred wind directions are consistent with those from MRAMS. The P4-derived wind speeds are less constrained but are consistent with MRAMS wind speeds at the majority of ROIs. The overall consistency between the P4-inferred and MRAMS wind directions supports the underlying assumption that fan formation is controlled by the wind and is not simply due to ballistic trajectories of material exiting suitably nonvertical vents. Measurements of seasonal fan-shaped deposits in HiRISE imagery can thus provide important intraseasonal information about near-surface winds—invaluable for both validating climate modeling and quantitatively investigating Mars’s polar processes.

To what extent can urban ventilation features cool a compact built-up environment during a prolonged heatwave? A mesoscale numerical modelling study for Hong Kong

Recent advances in numerical tools and data for the study of urban microclimates have helped to evaluate countermeasures for urban heat in heterogeneous and high-rise cities such as Hong Kong. Thus, two ventilation strategy designs, point ('oases') and linear ('corridors') features, were numerically simulated during a typical heatwave using the multi-layer coupled MesoNH-SURFEX-TEB mesoscale atmospheric model. These strategies proved to be effective at night with respect to thermal comfort but caused a localised increase in heat stress during the day in the ventilated areas, which were less shaded. There was no significant deterioration in the wind performance around the developments that were redesigned to accommodate the displaced population due to the construction of the ventilation features; however, an improvement was observed in thermal comfort during the daytime. The simulated impacts were relatively localised, suggesting the importance of increasing porosity across the entire urban fabric. The corridors, especially when built along the axis of the prevailing winds, exhibited better ventilation at the pedestrian level than the oases. Nevertheless, the oases remain interesting features in the context of progressive urban ventilation planning that involve the implementation of isolated, connected, and eventually a network of features to provide benefits at the megalopolis scale.

Towards decarbonisation targets by changing setpoint temperature to avoid building overcooling and implementing district cooling in (sub)tropical high-density cities – A case study of Hong Kong

Climate warming, rapid economic development, and urbanisation in (sub)tropical regions lead to increasing electricity demand for building air-conditioning that could jeopardise the efforts of decarbonisation required to meet the climate change mitigation goals. This study investigates two strategies to reduce building energy consumption due to air-conditioning: 1) the bottom-up adoption of an Adaptive Thermal Comfort (ATC)-based cooling setpoint temperature and 2) the top-down implementation of efficient District Cooling Systems (DCS). The subtropical high-density city of Hong Kong is chosen for case study since detailed data on the city's current and realistic future urban form and function are available. Numerical simulations representing the feedback between urban climate and building energy consumption are conducted by employing a mesoscale atmospheric model coupled to an urban climate and building energy model for a scenario of future (mid-21st century) Hong Kong. A prolonged high temperature event representative of future extreme conditions is simulated, during which the ATC and DCS strategies reduce building cooling energy consumption by 9.7% and 5.9%, respectively. The ATC has almost no effect on the local meteorological conditions, whereas the DCS reduces daytime sensible heat flux by up to 600 W/m2 and near-surface air temperature by almost 1 °C in the districts where it is adopted. The DCS thus also contributes to lowering outdoor heat stress in these areas. The cost-free ATC strategy is easily applicable in residential buildings worldwide and can break the vicious cycle in overcooled buildings, where occupants are acclimatised to lower indoor temperature and thus require more air-conditioning than necessary. Apart from reducing energy consumption and near-surface air temperature, the DCS brings additional benefits in building space utilisation and rooftop design. Future policy orientations should therefore encourage a societal change towards the ATC lifestyle and incorporate DCS in the planning of new development areas.