A Python-enhanced urban land surface model SuPy (SUEWS in Python, v2019.2): development, deployment and demonstrationSun, T. ORCID: https://orcid.org/0000-0002-2486-6146 and Grimmond, S. ORCID: https://orcid.org/0000-0002-3166-9415 (2019) A Python-enhanced urban land surface model SuPy (SUEWS in Python, v2019.2): development, deployment and demonstration. Geoscientific Model Development, 12 (7). pp. 2781-2795. ISSN 1991-962X
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.5194/gmd-12-2781-2019 Abstract/SummaryAccurate 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.
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