A Python-enhanced urban land surface model SuPy (SUEWS in Python, v2019.2): development, deployment and demonstration

Accurate and agile modelling of the climate of cities is essential for urban climate services. The Surface Urban Energy and Water balance Scheme (SUEWS) is a state-of-the-art, widely used, urban land surface model (ULSM) which simulates urban-atmospheric interactions by quantifying the energy, water and mass fluxes. Using SUEWS as the computation kernel, SuPy (SUEWS in Python), stands on the Python-based data stack to streamline the pre-processing, computation and post-processing that are involved in the common modelling-centred urban climate studies. This paper documents the development of SuPy, which includes the SUEWS interface modification, F2PY (Fortran to Python) configuration and Python frontend implementation. In addition, the deployment of SuPy via PyPI (Python Package Index) is introduced along with the automated workflow for cross-platform compilation. This makes SuPy available for all mainstream operating systems (Windows, Linux, and macOS). Furthermore, three online tutorials in Jupyter notebooks are provided to users of different levels to become familiar with SuPy urban climate modelling. The SuPy package represents a significant enhancement that supports existing and new model applications, reproducibility, and enhanced functionality

Atmospheric boundary layer characteristics from Ceilometer measurements part 2: application to London’s urban boundary layer

Long-term measurements of mixed layer height (ZML) are possible with advances in detecting ZML from Automatic Lidars and Ceilometers (ALC) observations. Six years of ALC measurements in central London are analysed using the CABAM (‘Characterising the Atmospheric Boundary layer based on ALC Measurements’) algorithm which provides ZML and an ABL classification by cloud cover and type. The boundary layer dynamics are shown to respond to day-length, cloud cover and cloud type. Median daily maxima range from 707 m (stratiform clouds) to 1704 m (days with convective boundary layer clouds following a clear night). A common approach to ABL classification and clear definition of key ZML-indicators would facilitate inter-city comparison. A simple parameterisation based on empirical coefficients derived from the London measurements is proposed to generalise the description of diurnal and seasonal variations in ZML, including cloud conditions. This has the potential to aid improved understanding of the complex relations between surface air quality and boundary layer dynamics

Urban warming in villages

Long term meteorological records (> 100 years) from stations associated with villages are generally classified as rural and assumed to have no urban influence. Using networks installed in two European villages, the local and microclimatic variations around two of these rural-village sites are examined. An annual average temperature difference ($\Delta{T}$) of 0.6 and 0.4 K was observed between the built-up village area and the current meteorological station in Geisenheim (Germany) and Haparanda (Sweden), respectively. Considerably larger values were recorded for the minimum temperatures and during summer. The spatial variations in temperature within the villages are of the same order as recorded over the past 100+ years in these villages (0.06 to 0.17 K/10 years). This suggests that the potential biases in the long records of rural-villages also warrant careful consideration like those of the more commonly studied large urban areas effects

Impact of building density on natural ventilation potential and cooling energy saving across Chinese climate zones

Natural ventilation is an energy-efficient approach to reduce the need for mechanical ventilation and air conditioning in buildings. However, traditionally weather data for building energy simulation are obtained from rural areas, which do not reflect the urban micrometeorological conditions. This study combines the Surface Urban Energy and Water Balance Scheme (SUEWS) and EnergyPlus to predict natural ventilation potential (NVP) and cooling energy saving in three idealised urban neighbourhoods with different urban densities in five Chinese cities of different climate zones. SUEWS downscales the meteorological inputs required by EnergyPlus, including air temperature, relative humidity, and wind speed profiles. The findings indicate that NVP and cooling energy saving differences between urban and rural areas are climate- and season-dependent. During summer, the urban-rural differences in natural ventilation hours are −43%–10% (cf. rural) across all climates, while in spring/autumn, they range from −7% to 36%. The study also suggests that single-sided ventilation can be as effective as cross ventilation for buildings in dense urban areas. Our findings highlight the importance of considering local or neighbourhood-scale climate when evaluating NVP. We demonstrate a method to enhance NVP prediction accuracy in urban regions using EnergyPlus, which can contribute to achieving low-carbon building design

Enhanced software and platform for the Town Energy Balance (TEB) model

The Town Energy Balance (TEB) model (Masson, 2000) is a physically based single layer Urban Canopy Model (UCM) to calculate the urban surface energy balance at neighborhood scale assuming a simplified canyon geometry. It includes several capabilities (Table 1) that have been extensively evaluated offline with flux observations (Lemonsu, Grimmond, & Masson, 2004; Leroyer, Mailhot, Bélair, Lemonsu, & Strachan, 2010; Masson, Grimmond, & Oke, 2002; Pigeon, Moscicki, Voogt, & Masson, 2008) and online coupled to atmospheric models such as ALARO (Gerard, Piriou, Brožková, Geleyn, & Banciu, 2009) in ALARO-TEB (Hamdi, Degrauwe, & Termonia, 2012), the Global Environmental Multiscale (GEM; Côté et al. (1998)) in GEM-TEB (Lemonsu, Belair, & Mailhot, 2009), Meso-NH (Lac et al., 2018; Lafore et al., 1998) in TEB-MesoNH (Lemonsu & Masson, 2002), the Regional Atmospheric Modeling System (RAMS; Pielke et al. (1992)) in RAMS-TEB (Freitas, Rozoff, Cotton, & Dias, 2007), the Advanced Regional Prediction System (ARPS; Xue et al., (2000)) in ARPS-TEB (Rozoff, Cotton, & Adegoke, 2003), and the Weather Research and Forecasting (WRF; Skamarock et al. (2019)) in WRF-TEB (Meyer et al., 2020). Here, we present an enhanced software and platform for the TEB model to help scientists and practitioners wishing to use the TEB model in their research as a standalone software application or as a library in their own software. This includes several features such as crossplatform support for Windows, Linux, and macOS using CMake (Kitware Inc., 2020), static and dynamic library generation for integration with other software/models, namelist-based configuration, integration with MinimalDX (Meyer & Raustad, 2019) and PsychroLib (Meyer & Thevenard, 2019) to improve the modelling of air conditioners (AC) and psychrometric calculations respectively, a thin interface used in the coupling with WRF-CMake (Riechert & Meyer, 2019), helper functions for Python for pre- and post-processing inputs and outputs files, and a tutorial in Jupyter Notebook to allow users to quickly become familiar with the general TEB modeling workflow. In the new platform we implement testing at every code commit through continuous integration (CI) and automate the generation of documentation. The project is developed as a free, open source, community-driven project on GitHub (https://github.com/teb-model/teb) to support existing and new model applications with enhanced functionality. We welcome contributions and encourage users to provide feedback, bug reports and feature requests, via GitHub’s issue system at https://github.com/teb-model/teb/issue

Urban climate modelling using SuPy: developing and supporting new research software

Meteorologists Dr Ting Sun and Professor Sue Grimmond developed an Open Source urban climate model with the aim of delivering reproducible research and exciting urban climate teaching. By making strategic decisions about how to package, distribute and support the software they have built an active community of research and education users. Dr Sun and Professor Grimmond were finalists in the University of Reading Open Research Award 2021