A set of five simulations for river runoff and total phosphorus transport within the European riverine system, driven by human activity and climate change. These simulations were carried out with the Hydrological Discharge model (Hagemann et al. 2020). The hindcast simulation utilizes hydrological forcings from HydroPy model (Stake and Hagemann, 2021) driven with the Global Soil Wetness Project Phase 3 (GWSP3; Dirmeyer et al. 2006; Kim 2017) atmospheric dataset, and phosphorus concentrations from the IMAGE-GNM model (Beusen et al. 2015). The historical simulation, along with three future scenarios, utilize hydrological forcings derived from the global Earth system model GFDL-ESM4 (John et al.2018), and phosphorus concentrations base on a newly developed parameterization. This parametrization incorporates land-use types and fertilizer application data in the form of nitrogen amounts from the Land-Use Harmonization 2 (LUH2; Hurtt et al. 2020). To account for the effects of human activity and climate change, the simulations employ three integrated scenarios that combine the Shared Socioeconomical Pathways (SSP) narratives and the Representative Concentration Pathways (RCP), specifically SSP1-RCP2.6, SSP3-RCP7.0 and SSP5-RCP8.5. This research was funded by the Cluster of Excellence "Climate, Climatic Change, and Society" (CLICCS), project No 390683824, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2037. Computational resources were made available by the German Climate Computing Center (DKRZ) through support from the German Federal Ministry of Education and Research (BMBF). We gratefully acknowledge the University of Hamburg for providing the data used in this study as part of the GLOWACHEM project, a component in the CLICCS framework.

ETCCDI indices calculated from two km-scale global models developed within the nextGEMS project (https://nextgems-h2020.eu/): ICON-Sapphire (Hohenegger et al. 2023) and IFS-FESOM (Rackow et al. 2025). The indices are based on the 30-year production simulations of nextGEMS, cycle 4 with a spatial resolution of about 10km (Segura et al. 2025). Here, we provide them in the 29-year period 2021-2049 (as the first year, 2020, is incomplete for IFS), driven by the high-emission pathway SSP3-7.0. The original data and the derived indices are available on the unstructured HEALPix grid (Górski et al. 2005). HEALPix organises data at discrete resolutions or zoom levels. Here, the highest resolved zoom level 9 (about 13km grid spacing corresponding to about 3 million grid cells globally) and the intermediate (“CMIP6-like”) zoom level 6 (about 102km, 50’000 grid cells) are provided. The data were processed by Lukas Brunner (https://orcid.org/0000-0001-5760-4524), using a Climate Data Operators (https://code.mpimet.mpg.de/projects/cdo/embedded/index.html) implementation of the ETCCID indices: code on GitHub (https://doi.org/10.5281/zenodo.15582463). Time-mean plots of all indices are available on Zenodo: https://doi.org/10.5281/zenodo.15613611 If you use the indices, please cite this dataset and the accompanying publication: Brunner L., B. Poschlod, E. Dutra, E. M. Fischer, O. Martius, and J. Sillmann (2025): A global perspective on the spatial representation of climate extremes from km-scale models. Environmental Research Letters, https://doi.org/10.1088/1748-9326/ade1ef

ERA5 is the fifth generation of atmospheric reanalysis (Hersbach et al., 2020) produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). It provides hourly data on many atmospheric, land-surface, and sea-state parameters at about 31 km resolution. It is frequently used to force regional climate models (RCMs) or ocean models. However, it lacks crucial information on riverine freshwater inflows at the land-ocean boundary. The latter is an important flux in ocean model or Earth System model applications, as it is affecting salinity and marine stratification in coastal areas. Therefore, we extended ERA5 with high-resolution river discharge from 1940-2024. Analogous to Hagemann and Stacke (2022), the global hydrology model HydroPy (Stacke and Hagemann 2021) and the Hydrological Discharge (HD) model (Vs. 5.2, Hagemann et al. 2023; Hagemann et al. 2020) were used to simulate daily discharge time series over the whole globe at 1/12° horizontal resolution. HydroPy was driven by daily ERA5 forcing data from 1940-2024 to generate daily input fields of surface and subsurface runoff at the ERA5 resolution. In order to initialize the storages in the HydroPy model and to avoid any drift during the actual simulation period, we conducted a 30-years spin-up simulation by repeatedly using year 1940 of the ERA5 dataset as forcing. To generate river runoff, the HD model was operated globally at 5 arc minutes horizontal resolution. First, the forcing data of surface and sub-surface runoff simulated by HydroPy were interpolated to the HD model grid. Then, daily discharges were simulated with the HD model. This work used resources of the Deutsches Klimarechenzentrum (DKRZ) granted via the Hereon part of the Helmholtz shareholder resources budget. Moreover, ERA5 datasets provided by DKRZ DM via the DKRZ data pool were used.

MODES applies three-dimensional linear wave theory for the decomposition of global circulation in terms of normal-mode functions (NMFs). NMFs used by MODES are eigensolutions of the linearized primitive equations in the terrain-following sigma coordinates and were derived by Kasahara and Puri (1981, Mon. Wea. Rev). The available data are three data sets (40 years), calculated from ERA5 reanalyses by modal filtering of certain wave components, here Kelvin waves (KW), Mixed Rossby-gravity waves (MRG) and Rossby wave n=1 (Rosn1). Near-realtime modal decompositions of ECMWF deterministic forecasts, using the same tool (MODES) as has been used for the generation of the dataset are under this URL: https://modes.cen.uni-hamburg.de/

This data contains results of the mesoscale transport and stream model METRAS (Schlünzen et al., 2018) for 20 summer situations described in detail in Boettcher et al. (in prep.). Combined they characterise the Hamburg urban summer climate based on statistical-dynamical downscaling (Boettcher et al., in prep.). They are used as reference climate for quantifying the impact of climate adaptation measures. The situation selection is based on analysed in-situ data for years 1981 to 2010 (Boettcher et al., in prep.). The data include wind speed, wind direction, wind components, real air temperature, relative humidity, total air pressure and total air density at lowest model level (about 10 m above ground). The data cover an area of approximately 60 x 60 km² with a spatial resolution of 250 m in horizontal. Forcing data are ECMWF analysis data at lateral and upper model boundaries. Each situation covers 3 days of model time. Data have a resolution of 30 minutes.

An operational, single-polarized X-band weather radar (WRX) provides measurements in Hamburg’s city center since 2013. This local area weather radar (LAWR) is located on the rooftop of the high-rise building "Geomatikum" in Hamburg (HHG), which is the location of the Meteorological Institute of the Universität Hamburg. The radar operates at one beam elevation angle with a high temporal 30 s, range 60 m, and sampling 1° resolution refining observations of the German nationwide C-band radars within a 20 km scan radius. Several sources of radar-based errors were adjusted gradually improving the measurement variables, e.g. the radar calibration, alignment, attenuation, noise, non-meteorologial echoes. This experiment includes data sets of the equivalent radar reflectivity factor (dbz) in level 1 (without attenuation correction) and the rainfall rate (rr) in level 2 (applied attenuation correction). The WRX/LAWR HHG measurements were calibrated and evaluated with measurements of micro rain radars (MRR). With this high-quality and -resolution weather radar product, refined studies on the spatial and temporal scale of urban precipitation will be possible. For example, the data sets will be used for further hydrological research in an urban area within the project Sustainable Adaption Scenarios for Urban Areas – Water from Four Sides of the Cluster of Excellence Climate Climatic Change, and Society (CliCCS). This work was partly funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany‘s Excellence Strategy – EXC 2037 'CLICCS - Climate, Climatic Change, and Society' – Project Number: 390683824, contribution to the Center for Earth System Research and Sustainability (CEN) of Universität Hamburg. Changes in Version 2: - We provide daily instead of hourly files to reduce the number of files for better data handling. For the days 23.09.2014, 12.03.2015, 09.06.2015, 05.07.2017, and 01.02.2018 there are two files to avoid additional time dependencies of variables because of changes in calibration or alignment parameters. - We changed the data type (double to int64) and the unit days since 1970-01-01 to seconds since 1970-01-01 of the time coordinate. - We changed the standard names / long names of the variables azimuth, range and ele. - We added the integer variable grid_mapping with the attributes grid_mapping_name ("radar_lidar_radial_scan"), latitude_of_projection_origin, longitude_of_projection_origin and height_of_projection_origin, as suggested by the CfRadial conventions. Since the grid_mapping variable provides the same information as the variables lat_center, lon_center and zsl_center, we removed them. We added the attribute grid_mapping to the variable rr and dbz.

This data contains results of the mesoscale transport and stream model METRAS (Schlünzen et al., 2018) for 43 winter situations described in detail in Boettcher et al. (in prep.). Combined they characterise the Hamburg urban winter climate based on statistical-dynamical downscaling (Boettcher et al., in prep.). They are used as reference climate for quantifying the impact of climate adaptation measures. The situation selection is based on analysed in-situ data for years 1981 to 2010 (Boettcher et al., in prep.). The data include wind speed, wind direction, wind components, real air temperature, relative humidity, total air pressure and total air density at lowest model level (about 10 m above ground). A non-uniform grid is used. The data cover an area of approximately 240 x 240 km² with a horizontal spatial solution of 6000 m at the lateral boundaries and down to 250 m resolution in the inner domain. Forcing data are ECMWF analysis data at lateral and upper model boundaries. Each situation covers 3 days of model time. Data have a resolution of 30 minutes.