Mapping mesoscale average 'windy day' wind exposure across the Vestfold Hills, 2015-2017

The Davis Aerodrome Project (DAP) collected a range of environmental survey data over several field seasons to support a comprehensive environmental assessment of the proposed aerodrome. This data includes flora, fauna, soils, lake ecosystem, nearshore, marine, air quality and meteorological information which has been collected by a number of different methods, and extends across the current Davis Station, proposed aerodrome and supporting infrastructure footprint (Ridge Site), previous sites considered for the aerodrome (Heidemann Valley, Adams Flat), as well as locations across the Vestfold Hills away from any of the proposed developments. Antarctic wind patterns are some of the most extreme and wide-ranging on Earth (van Lipzig et al., 2004). Surface winds on the Antarctic continent are affected by local topography, and undergo annual cycles with underlying interannual trends (Turner et al., 2009; van Lipzig et al., 2004). Surface winds across Antarctica influence habitat suitability for plants and animals and shape their fine-scale distribution (Clarke et al., 2012). The influence of wind on Antarctic biota extend to not only the harshness of the local environment (Bramley-Alves et al., 2014), but also dispersal and the transport of biologically important aerosols such as salts and organic matter (Melick et al., 1994; Nkem et al., 2006).Fine-scale mapping of wind exposure across the Antarctic continent is incomplete. Here we use a bushfire management tool, WindNinja 3.6.0 (Wagenbrenner et al., 2019), to model wind exposure across the Vestfold Hills, an ice-free rocky region of East Antarctica. WindNinja downscales local wind speed (and angle) from a domain averaged wind speed (and angle) across a topographic raster using a mass and momentum balanced model. Wind exposure, defined as fine-scale prevailing wind speeds, across the Vestfold Hills were modelled in WindNinja using topography from a composite DEM of the Vestfold Hills (Travers et al., 2022) and wind predictions from the Antarctic Mesoscale Prediction System (AMPS) (Bromwich et al., 2003).Wind exposure, defined as fine-scale prevailing wind speeds (in m/s), across the Vestfold Hills were modelled in WindNinja using topography from a composite DEM of the Vestfold Hills (Travers et al., 2022) and wind predictions from the Antarctic Mesoscale Prediction System (AMPS) (Bromwich et al., 2003) at 126 m resolution, and downscaled to 8 m resolution. We use a bushfire management tool, WindNinja 3.6.0 (Wagenbrenner et al., 2019), to model wind exposure across the Vestfold Hills, an ice-free rocky region of East Antarctica. WindNinja downscales local wind speed (and angle) from a domain averaged wind speed (and angle) across a topographic raster using a mass and momentum balanced model.ReferencesBramley-Alves, J., King, D. H., Robinson, S. A., and Miller, R. E. (2014). Dominating the Antarctic environment: bryophytes in a time of change. In D. Hanson and S. Rice (Eds.), Photosynthesis in Bryophytes and Early Land Plants. Advances in Photosynthesis and Respiration (Including Bioenergy and Related Processes) (Vol. 37, pp. 309-324). Springer. https://doi.org/https://doi.org/10.1007/978-94-007-6988-5_17 Bromwich, D. H., Monaghan, A. J., Powers, J. G., Cassano, J. J., Wei, H.-L., Kuo, Y.-H., and Pellegrini, A. (2003). Antarctic Mesoscale Prediction System (AMPS): A Case Study from the 2000–01 Field Season. Monthly Weather Review, 131(2), 412-434. https://doi.org/10.1175/1520-0493(2003)131%3C0412:AMPSAA%3E2.0.CO;2 Clarke, L. J., Robinson, S. A., Hua, Q., Ayre, D. J., and Fink, D. (2012). Radiocarbon bomb spike reveals biological effects of Antarctic climate change. Global Change Biology, 18(1), 301-310. https://doi.org/https://doi.org/10.1111/j.1365-2486.2011.02560.x Melick, D. R., Hovenden, M. J., and Seppelt, R. D. (1994). Phytogeography of bryophyte and lichen vegetation in the Windmill Islands, Wilkes Land, Continental Antarctica. Vegetatio, 111(1), 71-87. https://doi.org/10.1007/BF00045578 Nkem, J. N., Wall, D. H., Virginia, R. A., Barrett, J. E., Broos, E. J., Porazinska, D. L., and Adams, B. J. (2006). Wind dispersal of soil invertebrates in the McMurdo Dry Valleys, Antarctica. Polar Biology, 29(4), 346-352. https://doi.org/10.1007/s00300-005-0061-x Travers, T. D., Raymond, B., and Sumner, M. (2022). Composite Digital Elevation Model of the Vestfold Hills (REMA / Smith 2015), Ver. 1. Australian Antarctic Data Centre. http://dx.doi.org/doi:10.26179/ssw5-0z19 Turner, J., Chenoli, S. N., abu Samah, A., Marshall, G., Phillips, T., and Orr, A. (2009). Strong wind events in the Antarctic. Journal of Geophysical Research: Atmospheres, 114(D18). https://doi.org/https://doi.org/10.1029/2008JD011642 van Lipzig, N. P. M., Turner, J., Colwell, S. R., and van Den Broeke, M. R. (2004). The near-surface wind field over the Antarctic continent. International Journal of Climatology, 24(15), 1973-1982. https://doi.org/https://doi.org/10.1002/joc.1090 Wagenbrenner, N. S., Forthofer, J. M., Page, W. G., and Butler, B. W. (2019). Development and Evaluation of a Reynolds-Averaged Navier–Stokes Solver in WindNinja for Operational Wildland Fire Applications. Atmosphere, 10(11), 672. https://www.mdpi.com/2073-4433/10/11/672

戴维斯机场项目（DAP）在多个野外季节收集了一系列环境调查数据，以支持对拟议机场的综合环境评估。这些数据涵盖植物群、动物群、土壤、湖泊生态系统、近岸、海洋、空气质量及气象信息，通过多种不同方法采集，覆盖范围包括当前的戴维斯站、拟议机场及配套基础设施区域（山脊选址区）、此前考虑的机场备选地点（海德曼谷、亚当斯平原），以及韦斯特福尔丘陵中远离任何拟议开发项目的区域。

南极的风型是地球上最极端且分布最广泛的风型之一（van Lipzig等人，2004）。南极大陆的地表风受局部地形影响，呈现出年度周期变化并具有潜在的年际趋势（Turner等人，2009；van Lipzig等人，2004）。南极地区的地表风影响动植物栖息地的适宜性，并塑造其精细尺度的分布格局（Clarke等人，2012）。风对南极生物群的影响不仅体现在加剧当地环境的严酷性（Bramley-Alves等人，2014），还包括促进生物扩散及盐分、有机质等具有生物学意义的气溶胶的传输（Melick等人，1994；Nkem等人，2006）。

南极大陆的精细尺度风暴露制图尚不完善。本研究使用野火管理工具WindNinja 3.6.0（Wagenbrenner等人，2019），对东南极洲无冰岩石区域韦斯特福尔丘陵的风暴露情况进行建模。WindNinja利用质量和动量平衡模型，将区域平均风速（及风向）降尺度至地形栅格上的局部风速（及风向）。韦斯特福尔丘陵的风暴露（定义为精细尺度的盛行风速）通过WindNinja建模得到，所使用的地形数据来自韦斯特福尔丘陵的复合数字高程模型（Digital Elevation Model，DEM）（Travers等人，2022），风场预测数据来自南极中尺度预报系统（AMPS）（Bromwich等人，2003）。

韦斯特福尔丘陵的风暴露（定义为精细尺度的盛行风速，单位：m/s）通过WindNinja建模得到，所用地形数据为韦斯特福尔丘陵的复合DEM（Travers等人，2022），风场预测数据来自分辨率为126米的南极中尺度预报系统（AMPS）（Bromwich等人，2003），并被降尺度至8米分辨率。我们使用野火管理工具WindNinja 3.6.0（Wagenbrenner等人，2019）对东南极洲无冰岩石区域韦斯特福尔丘陵的风暴露情况进行建模。WindNinja利用质量和动量平衡模型，将区域平均风速（及风向）降尺度至地形栅格上的局部风速（及风向）。

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