Urban Microclimate is an urban design simulation tool that provides climate-specific advice for cityscape geometry and land use to assist the development of energy-efficient cities that are also thermally comfortable. The software enables urban designers to parametrically test built densities for masterplanning and urban planners to advocate zoning regulations such as building height and land use as well as policies for traffic intensity with energy and thermal implications of these interventions. Urban Microclimate is the first tool publicly available that incorporates microclimate analysis in urban design and energy simulations.

The tool uses Urban Weather Generator (UWG) [Bueno et al, 2014] to model urban heat island effect (UHI) from measurements at an operational weather station based on neighborhood-scale energy balances. The recent evaluation against field data from a network of weather stations in Singapore represents a range of land uses, morphological parameters and building usages that the UWG is able to simulate. In an effort to create a usable and accessible urban design software, sensitivity analyses for Singapore and Boston, MA, USA are conducted to identify as key parameters the building morphologies such as horizontal building density and vertical to horizontal built ratio; building surface albedo and emissivity; and sensible anthropogenic heat in the urban canyon. The commonality of results for these cities allows reduction of user inputs to the model by 80% without reducing the simulation accuracy.

The newly proposed workflow for energy- and thermal comfort-driven urban design and planning is demonstrated through a case study of the new 1.4 million square feet development in Cambridge, MA, USA. Multiple urban development scenarios of different massings and construction materials are tested in parallel through the Urban Microclimate’s graphical user interface. Each design is evaluated and then ranked according to its effects on UHI and heating and cooling energy consumptions to allow users to quickly target and adopt strategies that are most effective for the specific climate and urban morphology for a sustainable urban growth.

As one of the important future trends of skyscraper, it is necessary to carry out prospective studies about the construction of the thousand-meter scale skyscraper. Due to the special nature of the meteorology element distribution, the air conditioning （A/C）load and energy consumption characteristics of the thousand-meter scale skyscraper differ from the common building significantly. This paper analyzes the effect of height on the A/C load for a hypothetical thousand-meter scale skyscraper in Dalian by both the energy simulation software TRNSYS16 (Transient System Simulation Program) and the mesoscale meteorological model WRFv3.4 (Weather Research and Forecasting Model). We calculated the weather conditions of Dalian by WRFv3.4 and get the variations of the meteorology element along the vertical direction in different seasons. Based on the vertical distribution of the meteorology element concerned with the calculation of building A/C load, we modified the database of TRNASYS16 according to the result from WRFv3.4, and calculated the A/C load of each room at different heights in the hypothetical thousand-meter scale skyscraper with the modified database by TRNASYS16. The results show that the cooling load gradually decreases with the increase of the height, and the heating load becomes larger as the height rising .The room cooling load at the height of 1000m above the ground was about 30% less than that close to the ground.

The paper addresses the necessity of coupling urban climate and building energy models when investigating the energy demand of urban buildings. It reports on a new Type for use in TRNSYS named Type 201, which is a new implementation of the urban canopy model “Town Energy Balance TEB” of Masson (2000) - when used in offline mode - for non-stationary building energy modelling, and which aims at coping with the non-availability of urban climate modelling routine within building energy tools.

The TEB-Type simulates under TRNSYS the urban microclimate and enables to adjust the standard climate data usually originating from rural sites to urban context prior to building energy simulation. This overcomes the lacking consideration of the microclimate changes like urban heat island effects, due to the surrounding built environment which constitutes the real boundary conditions of urban buildings.

The model TEB has some features which makes it favorable for a combination with TRNSYS, e.g.: 1) Compatibility with TRNSYS: Simulation at hourly basis, for 1 year, e.g. with TRY standard climate data, 2) Short simulation time: 2-3 min./ Simulation and 3) Detailed description of urban canyon facets as multi-layered components (street, roof, wall).

Type 201 provides all terms of the energy balance at each surface (street, roof, wall) so that the physical processes prevailing in the formation of a specific urban microclimate can be explained. These include for each urban facet: The total absorbed short-wave radiation, long-wave radiation, total net radiation, the sensible and latent heat fluxes, the heat storage, the anthropogenic heat flux, as well as the single surface temperatures, the prognosticated air canyon temperature.

The new TEB -Type is very versatile and allows large parametric runs with minimal input preparation. The new implementation of TEB in TRNSYS also solves a number of disadvantages of the original tool: 1) The low user friendly graphical interface under LINUX, 2) the time-consuming pre-processing and lack of consistency check of the inputs and the too large outputs files for each key metric and 3) The fragmented source code which is rather difficult to decrypt by an end-user.

Exemplarily, an application of the Type 201 is given by showing the microclimate effects of urban facets properties (street, rood, walls). Different constructions are systematically compared including 3-steps variation of thermal insulation levels, thermal inertia and urban density. The results confirm that the canyon is mostly warmer and the daily air temperature patterns are influenced by each of the investigated parameters. This advocates for a systematic prior consideration of microclimate changes in Building energy modelling.

The Type 201 partly solves the methodological problem of lacking connection between building climate and urban climate simulations. Yet, the paper discusses the potential of further development of such a type towards a more extensive coupled urban canopy and building energy model for synchronized dynamic simulation of outdoor and indoor energy balances and climates, i.e. including their interactions at each time step.

This coupling requires eliminating the redundancy in calculating the energy budget at the urban facets which are the shared surfaces between the two entities. This currently occurs in TRNSYS and TEB with different methods. This further development is set as next task.

The Urban Weather Generator (UWG) is a simple and computationally efficient model that predicts canopy level urban air temperature using meteorological information measured at a reference weather station. Intended for use by architects, planners and building service engineers, it simplifies the inherent thermal coupling between buildings and the urban canopy and requires a level of user expertise and computation time commensurate with typical building design workflows. To map typical or annual meteorological year weather files to an urban weather file in the same format, UWG uses four submodules: the rural station model, vertical diffusion model, urban boundary-layer (UBL) model and urban canopy and building energy model. The near-universal nature of the urban weather file makes it compatible with widely used building energy simulation programs. Decoupling the production of the urban weather file from the building energy simulation requires the user to represent within UWG the thermal characteristics of existing or proposed buildings with reasonable accuracy. Comparison with an iterative coupling of buildings with urban canyons shows satisfactory performance. Access by designers to urban and building parameters required by UWG is assessed.

Improvements to the model, allow the user to define and describe different urban neighborhoods. Thermal interactions between neighborhoods are modeled as occurring through vertical transport of heat by convection and radiation from the urban canopy to higher regions of the urban boundary layer and advection of that heat, where the warmer UBL interacts with downwind neighborhoods. Designers can also specify the weighted presence of different building uses (i.e., commercial, residential, industrial) in each neighborhood. An upgraded representation of the energy balance in the UBL uses the known physics of longwave radiation in participating media to define an equivalent sky temperature. The current UWG also provides an improved representation of the effects of surface roughness on airflow.

A recent comparison of model predictions and measurements in Singapore will be presented and compared with previous validations in two mid-latitude cities. The comparison in Singapore shows satisfactory performance of the model for all weather conditions. Somewhat unexpectedly, the choice of two reference weather stations in Singapore, one near open water and the other in the interior of the island, has minimal impact on the estimation of diurnal temperature patterns in targeted neighborhoods. Analysis indicates that vertical energy exchange dominates the impact of advection in the UBL. However, the temperatures at the two reference stations are not identical and differences between neighborhood temperatures estimated by the UWG and the reference station, which show the magnitude of the urban heat island effect, depend on the choice of weather station. In aggregate, validations to date show that the model can be applied to different climates and urban configurations to obtain an estimation of the Urban Heat Island (UHI) effect. The spatial specificity and accuracy of these estimates are assessed in the context of building performance.