DANRA: The Kilometer-Scale Danish Regional Atmospheric Reanalysis
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arXiv
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| Autori principali: | , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916991265144832 |
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| author | Yang, Xiaohua Peralta, Carlos Amstrup, Bjarne Hintz, Kasper Stener Thorsen, Søren Borg Denby, Leif Christiansen, Simon Kamuk Schulz, Hauke Pelt, Sebastian Schreiner, Mathias |
| author_facet | Yang, Xiaohua Peralta, Carlos Amstrup, Bjarne Hintz, Kasper Stener Thorsen, Søren Borg Denby, Leif Christiansen, Simon Kamuk Schulz, Hauke Pelt, Sebastian Schreiner, Mathias |
| contents | The DANish regional atmospheric ReAnalysis (DANRA) is a novel high-resolution (2.5 km) reanalysis dataset covering Denmark and its surrounding regions over a 34-year period (1990-2023). Denmark's complex coastline, with over 400 islands and an extensive 7,400 km coastline, means that most municipalities experience mixed land-sea variability. This complexity requires a regional climate reanalysis that can resolve fine-scale coastal and inland features, as well as their impact on climate variability. DANRA is based on the HARMONIE-AROME Numerical Weather Prediction (NWP) model and assimilates a comprehensive set of observations, with a particular focus on Denmark. Compared to global reanalyses such as the ECMWF Reanalysis v5 (ERA5), DANRA demonstrates superior performance in representing essential climate variables, including near-surface weather parameters during both extreme and ordinary conditions. We illustrate these improvements in the representation of several extreme weather cases over Denmark, such as the December 1999 hurricane-force storm, the July 2022 national temperature record, and the August 2007 cloudburst in South Jutland. DANRA is made to support climate adaptation, impact modelling, and the training of next-generation data-driven atmospheric forecasting models. DANRA is distributed as Zarr dataset freely accessible from an object store, maximizing its usability for climate adaptation, impact modelling, and data-driven research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_04681 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DANRA: The Kilometer-Scale Danish Regional Atmospheric Reanalysis Yang, Xiaohua Peralta, Carlos Amstrup, Bjarne Hintz, Kasper Stener Thorsen, Søren Borg Denby, Leif Christiansen, Simon Kamuk Schulz, Hauke Pelt, Sebastian Schreiner, Mathias Atmospheric and Oceanic Physics The DANish regional atmospheric ReAnalysis (DANRA) is a novel high-resolution (2.5 km) reanalysis dataset covering Denmark and its surrounding regions over a 34-year period (1990-2023). Denmark's complex coastline, with over 400 islands and an extensive 7,400 km coastline, means that most municipalities experience mixed land-sea variability. This complexity requires a regional climate reanalysis that can resolve fine-scale coastal and inland features, as well as their impact on climate variability. DANRA is based on the HARMONIE-AROME Numerical Weather Prediction (NWP) model and assimilates a comprehensive set of observations, with a particular focus on Denmark. Compared to global reanalyses such as the ECMWF Reanalysis v5 (ERA5), DANRA demonstrates superior performance in representing essential climate variables, including near-surface weather parameters during both extreme and ordinary conditions. We illustrate these improvements in the representation of several extreme weather cases over Denmark, such as the December 1999 hurricane-force storm, the July 2022 national temperature record, and the August 2007 cloudburst in South Jutland. DANRA is made to support climate adaptation, impact modelling, and the training of next-generation data-driven atmospheric forecasting models. DANRA is distributed as Zarr dataset freely accessible from an object store, maximizing its usability for climate adaptation, impact modelling, and data-driven research. |
| title | DANRA: The Kilometer-Scale Danish Regional Atmospheric Reanalysis |
| topic | Atmospheric and Oceanic Physics |
| url | https://arxiv.org/abs/2510.04681 |