Abstract
Abstract. A set of Python-based tools, WRF4PALM, has been developed for offline nesting of the PALM model system 6.0 into the Weather Research and Forecasting (WRF) modelling system. Time-dependent boundary conditions of the atmosphere are critical for accurate representation of microscale meteorological dynamics in high-resolution real-data simulations. WRF4PALM generates initial and boundary conditions from WRF outputs to provide time-varying meteorological forcing for PALM. The WRF model has been used across the atmospheric science community for a broad range of multidisciplinary applications. The PALM model system 6.0 is a turbulence-resolving large-eddy simulation model with an additional Reynolds-averaged Navier–Stokes (RANS) mode for atmospheric and oceanic boundary layer studies at microscale (Maronga et al., 2020). Currently PALM has the capability to ingest output from the regional scale Consortium for Small-scale Modelling (COSMO) atmospheric prediction model. However, COSMO is not an open source model and requires a licence agreement for operational use or academic research (http://www.cosmo-model.org/, last access: 23 April 2021). This paper describes and validates the new free and open-source WRF4PALM tools (available at https://github.com/dongqi-DQ/WRF4PALM, last access: 23 April 2021). Two case studies using WRF4PALM are presented for Christchurch, New Zealand, which demonstrate successful PALM simulations driven by meteorological forcing from WRF outputs. The WRF4PALM tools presented here can potentially be used for micro- and mesoscale studies worldwide, for example in boundary layer studies, air pollution dispersion modelling, wildfire emissions and spread, urban weather forecasting, and agricultural meteorology.
Highlights
Over the last decade, research in numerical weather and climate simulations, environmental modelling, and agricultural and urban meteorology has developed to include higher spatial resolutions, such that the feedback from the microscale processes impacted by surface heterogeneities can be explicitly resolved and better represented
To extend the use of Parallelised Large-Eddy Simulation Model (PALM) for the scientific community, we have developed a set of Python tools to allow PALM to include mesoscale forcing from the Weather Research and Forecasting modelling system (WRF; http://www. wrf-model.org, last access: 23 April 2021; Skamarock et al, 2019)
This study describes a utility WRF4PALM that is developed to generate mesoscale forcing from WRF output for the PALM model system 6.0
Summary
Research in numerical weather and climate simulations, environmental modelling, and agricultural and urban meteorology has developed to include higher spatial resolutions, such that the feedback from the microscale (from 10−2 to m; from seconds to hours) processes impacted by surface heterogeneities can be explicitly resolved and better represented. At the mesoscale (from to 5 × m; from hours to days), numerical weather prediction (NWP) models are widely used to simulate regional atmospheric flows in real meteorological conditions. Mesoscale NWP models are primarily Reynolds-averaged (Navier– Stokes) (RANS) simulation models that parameterise turbulence without discrepancy for scale (Sagaut, 2006, Chapter 1.4). The parameterisations applied in RANS models only consider the average properties of atmospheric flows impacted by surface geometries at the grid resolution of the simulation.
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