Exploring Domain Size for WRF High-Resolution Urban Rainfall Simulation

crossref(2023)

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摘要
<p><strong>Abstract: </strong>With climate change, rainfall is expected to get more intense, leading to cities being increasingly at risk of urban flooding. Understanding local climate change over cities has therefore become a priority for the scientific community and city planners on building resilient cities and mitigating hydrometeorological disasters. Very high resolution (km-scale, &#8216;convection-permitting&#8217;) climate models are required to adequately represent cities and local rainfall extremes. Here we assess the Weather Research and Forecasting (WRF) model for simulating urban rainfall. Despite the wide application of WRF in rainfall simulations (including urban areas), there are limited investigations on the impact of the domain size and how to search for a suitable domain size over a particular city region.</p> <p>To fill this knowledge gap, Newcastle upon Tyne is selected as the study area to simulate a summer heavy rainfall event with ERA5 (a fifth-generation dataset of global reanalysis developed by the European Centre for Medium-Range Weather Forecasts) as the input data and a radar product from the UK Met Office for validation. Accordingly, different domain sizes with the convection-permitting resolutions from 1 km to 4.5 km (increment: 0.5 km) are explored, and the hourly model outputs are compared with the radar observation data.</p> <p>This study has proposed and tested a method to decide the most suitable domain size. By using eight assessment indexes (including pattern, cumulative time series, hourly time series, particular values (max/min/mean) as well as the seven statistical indicators of each data and overall data), there are two preliminary conclusions: 1) 200 km &#215; 200 km is the best domain size for the single domain simulation; 2) For 200 km &#215; 200 km or smaller domain sizes, higher resolution produces better results, but for 250 km &#215; 250 km or large domain sizes, resolution sensitivity is opposite. Regarding next steps, the above procedure will be further investigated by applying it to more extreme rainfall case studies and to other cities in order to assess whether results here are generally applicable, and therefore the optimal domain configuration can be usefully applied to produce reliable urban rainfall simulations.</p>
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