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/

The spectral longwave feedback parameter quantifies the change in Earth's spectrally resolved outgoing longwave radiation (OLR) in response to warming. It contains the radiative signature of all longwave feedbacks making it a key quantity influencing Earth's climate sensitivity. By spectrally resolving these changes in OLR, one can gain important information about the underlying feedback processes. This experiment contains spectrally resolved radiative quantities that can be used for the calculation of the global mean all-sky spectral longwave feedback parameter based on seasonal and interannual variability, using both satellite observations and simulations. This dataset was updated to provide more information on the sensitivity of the spectral longwave feedback parameter on relative humidity changes as well as on the impact of the surface feedback at different surface temperatures.

The spectral longwave feedback parameter quantifies the change in Earth's spectrally resolved outgoing longwave radiation (OLR) in response to warming. It contains the radiative signature of all longwave feedbacks making it a key quantity influencing Earth's climate sensitivity. By spectrally resolving these changes in OLR, one can gain important information about the underlying feedback processes. This experiment contains spectrally resolved radiative quantities that can be used for the calculation and interpretation of the global mean all-sky spectral longwave feedback parameter based on seasonal and interannual variability, using both satellite observations and simulations. This is an updated version of the experiment. Compared to the first version, this version contains more data on the sensitivity of the spectral longwave feedback parameter on relative humidity changes. Additionally, this version also contains data on the contribution of the surface feedback for different surface temperatures.

This experiment contains the model output of a simulation by the microscale obstacle resolving model MITRAS (Salim et al., 2018; Schluenzen et al., 2018, model version MITRAS ver2 rev471a5b5). MITRAS can resolve small scale atmospheric processes in urban areas and is maintained by the MEMI working group of the University of Hamburg (https://www.mi.uni-hamburg.de/en/arbeitsgruppen/memi/). The aim of this simulation was to create an obstacle resolving model (ORM) dataset to test the suitability of the newly established ATMODAT standard (Ganske et al., 2021) in standardising ORM results, as a part of the AtMoDat project (https://www.atmodat.de/). The simulation results show the distribution of passive tracer and wind field within the city center of Hamburg, Germany. Emitted tracer represent particulate matter (pm10), emitted from green spaces in the city center. Only dynamical effects are calculated in this simulation. The model domain covers an area of 2000x2000x8000 m, using a non-equidistant, cartesian grid with an spatial resolution of 2.5 m in horizontal and 5 m in vertical direction with increasing grid cell size towards the model boundaries. Information about the location and height of the obstacles are provided within the dataset. The model domain is based on the study of Hefny Salim et al., (2015). The simulation covers one hour model time, starting at 4 am model time, with a temporal resolution of 5 minutes. This dataset contains a selection of output variables; control variables are not included. Model Settings: passive tracer emission; no diurnal cycle; stable stratification; low wind speed (u,v = 3 m/s, 0 m/s). This dataset has been standardized according to the ATMODAT Standard (v3.0) (Ganske et al., 2021). The AtMoDat project was funded in the framework of \"Forschungsvorhaben zur Entwicklung und Erprobung von Kurationskriterien und Qualitaetsstandards von Forschungsdaten\" by the German Federal Ministry of Education and Research (BMBF; FKZ: 16QK02C). This data was prepared in the project AtMoDat and acts as an example dataset for standardisation of microscale model data using the ATMODAT standard.

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.

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.

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 experiment contains sensitivity test results (Ferner et al. 2023) of 11 simulations with the microscale, obstacle-resolving model MITRAS v 3.1 (Salim et al., 2018; Schluenzen et al., 2018) for a domain of 1.6 x 1.8 km² around Hamburg City Hall in Hamburg. The domain contains various street configurations, open spaces, water surfaces, orography and building heights. The simulations were performed with different initial wind speeds, rain amounts, wind directions, and domain configurations. The simulations cover 1:40 hours, starting at 7:30 LST (LST refers to Local Solar Time), with a temporal resolution of 10, 1 or 5 minutes. This experiment contains a selection of output variables, control variables are not included. The file names of the data sets are composed as follows. {precipitation}_{intensity}_{windspeed}_ {intensity}_{winddirection}_{value}_{case ID}.nc There are 3 intensities: low, medium, high Associated values are these: pr_low = 0.5 mm, pr_medium =0.9 mm, pr_high = 1.7 mm (after 10 minutes) ff_low = 2 m/s, ff_medium = 4 m/s, ff_high = 4 m/s Example: pr_medium_ff_low_dd_270_ML27.nc

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. Now a more recent version (Version 2) exists with the following changes: - 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.

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