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Preprints
https://doi.org/10.5194/essd-2020-52
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-52
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  28 May 2020

28 May 2020

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A revised version of this preprint is currently under review for the journal ESSD.

BAYWRF: a convection-resolving,present-day climatological atmospheric dataset for Bavaria

Emily Collier and Thomas Mölg Emily Collier and Thomas Mölg
  • Climate System Research Group, Institute of Geography, Friedrich-Alexander University Erlangen-Nürnberg(FAU), Erlangen, Germany

Abstract. Climate impact assessments require information about climate change at regional and ideally local scales. In dendroecological studies, this information has traditionally been obtained using statistical methods, which preclude the linkage of local climate changes to large-scale drivers in a process-based way. As part of recent efforts to investigate the impact of climate change on forest ecosystems in Bavaria, Germany, within the BayTreeNet project, we developed a high-resolution atmospheric modelling dataset, BAYWRF, for the region of Bavaria over the thirty-year period of September 1987 to August 2018. The atmospheric model employed in this study, WRF, was configured with two nested domains of 7.5- and 1.5-km grid spacing, centred over Bavaria and forced at the outer lateral boundaries by ERA5 reanalysis data. Based on a shorter evaluation period of September 2017 to August 2018, we evaluate two aspects of the simulations: (i) we assess model biases compared with an extensive network of observational data at both two-hourly and daily mean temporal resolutions, and (ii) we investigate the influence of using grid analysis nudging. The model represents variability in near-surface meteorological conditions well, with a clear improvement when nudging is used, although there are cold and warm biases in winter and summer, respectively. We also present a brief overview of the full dataset, which will provide a unique and valuable tool for investigating climate change in Bavaria with high interdisciplinary relevance. Data from the finest resolution WRF domain are available for download at daily temporal resolution from a public repository at the Open Science Framework (Collier, 2020; https://www.doi.org/10.17605/OSF.IO/AQ58B).

Emily Collier and Thomas Mölg

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Emily Collier and Thomas Mölg

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BAYWRF E. Collier https://doi.org/10.17605/OSF.IO/AQ58B

Emily Collier and Thomas Mölg

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Short summary
As part of the BayTreeNet project that aims to investigate the impact of climate change on forest ecosystems in Bavaria, we developed a high-resolution atmospheric dataset, BAYWRF, for this region that covers the period of September 1987 to August 2018. The data reproduce observed variability in recent meteorological conditions well and provide a useful tool for linking large-scale climate change to local impacts on economic, societal, ecological, and agricultural processes.
As part of the BayTreeNet project that aims to investigate the impact of climate change on...
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