W2W: A Python package that injects WUDAPT’s Local Climate Zone information in WRF

Abstract

License Authors of papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Summary The Python-based WUDAPT-to-WRF (W2W) package is developed to translate Local Climate Zone (LCZ) maps into urban canopy parameters readable by WRF, the community "Weather Research and Forecasting" model (Skamarock et al., 2021). It is the successor of the Fortran-based W2W package developed by Brousse et al. (2016) and Martilli et al. (2016), and provides an improved, simpler, and more efficient procedure to use LCZ information in WRF. Some important changes include direct manipulation of the geogrid files without the creation of temporary files, and the use of average LCZ-based urban morphological parameters instead of assigning them to the modal LCZ class. This development of this package is in line with the objectives of WUDAPT, the World Urban Database and Access Portals Tools community project, that aims to 1) acquire and make accessible coherent and consistent information on the form and function of urban morphology relevant to climate weather and environmental studies, and 2) provide tools that extract relevant urban parameters and properties for models and model applications at appropriate scales for various climate, weather, environment, and urban planning purposes (Ching et al., 2018). Statement of need Since the pioneering work of Brousse et al. (2016) and Martilli et al. (2016), the level-0 WUDAPT information, the Local Climate Zone maps, have been used increasingly in WRF. We expect this trend to continue because of three recent developments: 1) the creation of city-wide LCZ maps is now easier than ever with the launch of the LCZ Generator web application (Demuzere et al., 2021), 2) the availability of a global LCZ map (Demuzere et al., 2022), and 3) WRF versions > 4.3 (Skamarock et al., 2021) can ingest 10 or 11 built classes (corresponding to WUDAPT's LCZs) by default, whereas previous WRF versions required manual code changes (see Martilli et al. (2016), Zonato & Chen (2021) and Zonato et al. (2021) for more information). Because of these developments, an improved, Python-based, WUDAPT-to-WRF (W2W) routine is presented here to translate LCZ-based parameters better and simpler. It differs from its Fortran-based predecessor mainly by 1) using a more up-to-date LCZ-based urban extent, 2) aggregating the morphological parameters instead of using modal values, and 3) the fact that all processing is done with one (automated) tool, whereas the Fortran-based version required multiple pre-processing steps and manual namelist changes, described in more detail by Martilli Demuzere et al. (2022). W2W: A Python package that injects WUDAPT's Local Climate Zone information in WRF. Journal of Open Source Software, 7 (76), 4432. https://doi.org/10.21105/joss.04432.