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

Abstract

Accurate and agile modelling of cities weather, climate, hydrology and air quality is essential for integrated urban 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) uses a 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, including the SUEWS interface modification, F2PY (Fortran to Python) configuration and Python front-end 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). Three online tutorials in Jupyter Notebook 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.