This study investigates the influences of urban land cover on the extreme rainfall event over the Zhengzhou city in central China on 20 July 2021 using the Weather Research and Forecasting model at a convection-permitting scale [1-km resolution in the innermost domain (d3)]. Two ensembles of simulation (CTRL, NURB), each consisting of 11 members with a multi-layer urban canopy model and various combinations of physics schemes, were conducted using different land cover scenarios: (i) the real urban land cover, (ii) all cities in d3 being replaced with natural land cover. The results suggest that CTRL reasonably reproduces the spatiotemporal evolution of rainstorms and the 24-h rainfall accumulation over the key region, although the maximum hourly rainfall is underestimated and displaced to the west or southwest by most members. The ensemble mean 24-h rainfall accumulation over the key region of heavy rainfall is reduced by 13%, and the maximum hourly rainfall simulated by each member is reduced by 15–70 mm in CTRL relative to NURB. The reduction in the simulated rainfall by urbanization is closely associated with numerous cities/towns to the south, southeast, and east of Zhengzhou. Their heating effects jointly lead to formation of anomalous upward motions in and above the planetary boundary layer (PBL), which exaggerates the PBL drying effect due to reduced evapotranspiration and also enhances the wind stilling effect due to increased surface friction in urban areas. As a result, the lateral inflows of moisture and high-θe (equivalent potential temperature) air from south and east to Zhengzhou are reduced.

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Urban greening has often been proposed as a cost-effective solution to improve environmental comfort, but may also deteriorate air quality. Quantifying these two opposing effects of urban greening is necessary to develop successful environmental policies for specific mega-city clusters. In this study, a high-resolution regional climate and air quality model (WRF-Chem, v4.0.3) was employed to test three scenarios aimed at quantifying the impact of land-use change and biogenic emissions from urban greening on regional climate and air quality. It was found that urban greening could effectively decrease the near-surface temperature by up to 0.45 °C, but the increased biogenic volatile organic compound (BVOC) emissions offset some of this cooling effect (by up to 65%). Land-use change due to urban greening dominated the improvement in human comfort but worsened diffusion conditions to result in the convergence of fine particulate matter in specific areas. The selection of low-emission tree species may be imperative, although increased emissions from urban greening will not change the sensitivity of ozone to precursors under the current scenario of anthropogenic emissions. This is because BVOC emissions due to urban greening will become a more important source of pollution with the development of clean energy and the popularity of low-carbon lifestyles.

Abstract. Reanalysis data plays a vital role in weather and climate study, as well as meteorological resource development and application. In this work, the East Asia Reanalysis System (EARS) was developed using the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolations (GSI) data assimilation system. The regional reanalysis system is forced by the European Centre of Medium-Range Weather Forecasts (ECMWF) global reanalysis EAR-Interim data at 6-h intervals; and hourly surface observations are assimilated by the Four-Dimension Data Assimilation (FDDA) scheme during the WRF model integration; upper observations are assimilated in a three-dimensional variational data assimilation (3D-VAR) mode at analysis moment. It should be highlighted that many of the assimilated observations have not been used in other reanalysis systems. The reanalysis runs from 1980 to 2018, producing a regional reanalysis dataset covering East Asia and surrounding areas at 12-km horizontal resolution, 74 sigma levels, and 3-hour intervals. Finally, an evaluation of EARS has been performed with the respect to the root mean square error (RMSE), based on the 10-year (2008–2017) observational data. Compared to the global reanalysis data of the EAR-Interim, the regional reanalysis data of the EARS are closer to the observations in terms of RMSE in both surface and upper-level fields. The present study provides evidence for substantial improvements seen in EARS compared to the ERA-Interim reanalysis fields over East Asia. The study also demonstrates the potential use of the EARS data for applications over East Asia and proposes further plans to provide the latest reanalysis in real-time operation mode. Simple data and updated information are available on Zenodo at https://doi.org/10.5281/zenodo.7404918 (Yin et al., 2022), and the full datasets are publicly accessible on the Data-as-a-Service platform of China Meteorological Administration (CMA) at http://data.cma.cn.