DANRA: The Kilometer-Scale Danish Regional Atmospheric Reanalysis

TL;DR

DANRA delivers a 34-year, kilometer-scale regional reanalysis for Denmark at 2.5 km resolution using the non-hydrostatic HARMONIE-AROME system, with enhanced observational input and QA to accurately capture coastal and near-surface processes. The dataset, available as CF-compliant Zarr archives, is benchmarked against ERA5 and validated through SYNOP station comparisons and notable extreme-weather case studies, showing improved representation of temperature, wind, and heavy precipitation. The work demonstrates that high-resolution regional reanalysis provides substantial advantages for climate adaptation, impact modelling, and data-driven forecasting, enabling finer-scale analysis of coastal dynamics and extreme events in Denmark. The authors also detail the data workflow, from system adaptations and observation rescue to cloud-friendly data publication, and outline plans to release hourly forecasts for broader use. Overall, DANRA offers a robust, long-span, high-resolution resource that advances regional climate research and practical decision-making in Denmark.

Abstract

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.

Figures (10)

• Figure 1: (a) Domain of the reanalysis, (b) Model orography over Denmark of at 2.5 km horizontal resolution and (c) model orography over Denmark of at 31 km horizontal resolution.
• Figure 2: Time series of from DMIdb (red) and ERA5 (blue) for station 06118 (Sø nderborg airport) during an episode between 11 and 12 March 2009.
• Figure 3: Time series of DMIdb surface pressure (green) and DMIdb MSLP (red), corrected MSLP (orange) and ERA5 MSLP (blue) for 06017 (Horns Rev B) during second half of July 2018.
• Figure 4: Scatter plot of 3-hourly analyses for 2m temperature () by (left) and (right) versus SYNOP observations over Denmark during 1990–2023. The color scale shows the density of points.
• Figure 5: Scatterplot of 3-hourly 10m wind speed () analyses by (left) and (right) versus SYNOP observations over Denmark during 1990–2023. The color scale shows the density of points.