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Numerical experiments to "Everything Hits at Once: How Remote Rainfall Matters for the Prediction of the 2021 North American Heat Wave"

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DataCite Commons2025-02-21 更新2025-04-16 收录
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This archive contains primary data for the manuscript “Everything Hits at Once: How Remote Rainfall Matters for the Prediction of the 2021 North American Heat Wave”. Article: ------------------------------- * Authors: Oertel, Annika; Pickl, Moritz; Quinting, Julian F.; Hauser, Seraphine; Wandel, Jan Lucas; Magnusson, Linus; Balmaseda, Magdalena; Vitart, Frédéric; Grams, Christian M. * Title: Everything Hits at Once: How Remote Rainfall Matters for the Prediction of the 2021 North American Heat Wave. * Journal: Geophysical research letters * Publication Year: 2023 * doi: https://doi.org/10.1029/2022GL100958 The data set contains numerical experiments produced with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Following the approach of Magnusson (2017), the forecast model is nudged towards the analysis in a pre-defined regional box during the model integration, leading to a perfect forecast within the box and reduced forecast errors downstream. The experiments, comprising 22 ensemble members plus control forecast each, are initialized on 19, 20 and 21 June 00 UTC and run until 360 hours lead (see Oertel et al. 2023 for details). The nudging is constrained to the region 100°–160°E, 15°–45°N (Experiment “relax_exp_WPAC”). For comparison, additional nudging experiments with a box shifted further upstream (60°–100°E, 0°–60°N) were performed (Experiment “relax_exp_UPSTREAM”). Data description: ------------------------------- The dataset is in netCDF format and contains the variables geopotential (z), temperature (t), zonal (u), meridional (v) and vertical (w) wind components, and specific humidity (q) on the pressure levels 1000, 925, 850, 700, 500, 300, 200 and 100 hPa. References: ------------------------------- Magnusson, L. (2017). Diagnostic methods for understanding the origin of forecast errors. Quarterly Journal of the Royal Meteorological Society, 143 (706), 2129–2142. doi:10.1002/qj.3072
提供机构:
Karlsruhe Institute of Technology
创建时间:
2023-06-21
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