Denmark climate and weather data

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons. Fields available: SID: A unique storm identifier (SID) assigned by IBTrACS algorithm. ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss) BASIN: Basin of the current storm position SUBBASIN: Sub-basin of the current storm position NATURE: Type of storm (a combination of the various types from the available sources) NUMBER: Number of the storm for the year (restarts at 1 for each year LAT: Mean position - latitude (a combination of the available positions) LON: Mean position - longitude (a combination of the available positions) WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Climate change includes nationwide modelled depth for ground water, water content in the root zone and water flow in streams as well as associated uncertainties in the periods 1991-2020, 2041-2070 and 2071-2100. Calculations for the future are based on the reference period 1991-2020. The calculations were carried out by GEUS using the DK model HIP in a grid with a resolution of 500 m for climate adaptation. Climate change for the depth to ground water can also be found in a grid with a resolution of 100 m.

Machine learning and uncertainty is a data set that shows nationwide depth to ground-level groundwater in high spatial resolution (10 m-grid) for a typical summer and winter situation as well as associated uncertainties in the period 1991-2025. The calculations have been carried out by GEUS using the DK model HIP and machine learning in order to provide screening data that can support the work on water management, climate adaptation, urban planning and more.

Climate data include quality-controlled meteorological observations. Climate data is available as: 1. Station data for both Denmark and Greenland 2. Area data for Denmark only

DMI observes precipitation with radars in and near Danish territory. DMI’s meter network consists of five radars located at Stevns Naturcenter, Rømø, in Sindal in Vendsyssel, Almindingen on Bornholm and in Virring in East Jutland.

Real-time data on lightning detected by DMI's lightning goggle network in Denmark as well as a number of third-party lightning goggles in surrounding countries. The lightning sticks detect both lightning going from cloud to earth and lightning from cloud to cloud.

The dataset ‘Area management related to offshore wind turbines’ consists of free spatial data maintained by the Danish Energy Agency. The dataset contains geographical data on Denmark's offshore wind projects, including governmental land reservations for renewable energy and energy islands, existing offshore wind farms, parks under construction, planned projects as well as applied open-door projects and test areas. The data set is continuously updated, but there may be delays in relation to the actual status of land management for offshore wind turbines.

Data from DMI’s operational weather and ocean models, which include: - Wave model WAM – contains forecast data for the next 5 days for wave height, direction and period for Danish territory - The storm-river model DKSS – contains forecast data for the next 5 days for e.g. water level, sea temperature and sea current for Danish area - The weather model HARMONIE – contains forecast data for the upcoming (approx.) 2½ days for e.g. temperature, dew point, clouds, precipitation, wind and pressure for the Danish and Greenlandic areas (releases Q4 2022).