CHELSA_v1.0 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. Version 1.0 is a first release. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. CHELSA_v1 is based on a quasi-mechanistical statistical downscaling of the ERA interim global circulation model (http://www.ecmwf.int/en/research/climate-reanalysis/era-interim) with a GPCC (https://www.dwd.de/EN/ourservices/gpcc/gpcc.html) and GHCN (https://www.ncdc.noaa.gov/ghcnm/) bias correction. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Monthly coverage 1979 - 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). Downscaled ERA-interim model. Allows calculation of derived parameters based on monthly values such as length of dry periods etc.

CHELSA_v1.1 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns as well as derived bioclimatic and interannual parameters for the time period 1979-2013. CHELSA_v1.1 is based on a quasi-mechanistical statistical downscaling of the ERA interim global circulation model (http://www.ecmwf.int/en/research/climate-reanalysis/era-interim) with a GPCC (https://www.dwd.de/EN/ourservices/gpcc/gpcc.html) and GHCN (https://www.ncdc.noaa.gov/ghcnm/) bias correction.

CHELSA_v1.0 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. Version 1.0 is a first release. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. CHELSA_v1 is based on a quasi-mechanistical statistical downscaling of the ERA interim global circulation model (http://www.ecmwf.int/en/research/climate-reanalysis/era-interim) with a GPCC (https://www.dwd.de/EN/ourservices/gpcc/gpcc.html) and GHCN (https://www.ncdc.noaa.gov/ghcnm/) bias correction. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Monthly coverage 1979 - 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). Downscaled ERA-interim model. Allows calculation of derived parameters based on monthly values such as length of dry periods etc.

CHELSA_v1.1 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns as well as derived bioclimatic and interannual parameters for the time period 1979-2013. CHELSA_v1.1 is based on a quasi-mechanistical statistical downscaling of the ERA interim global circulation model (http://www.ecmwf.int/en/research/climate-reanalysis/era-interim) with a GPCC (https://www.dwd.de/EN/ourservices/gpcc/gpcc.html) and GHCN (https://www.ncdc.noaa.gov/ghcnm/) bias correction.

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.

Annual maxima of sub-daily precipitation were extracted from each of 35 members of a EURO-CORDEX ensemble with a spatial resolution of 0.11° (EURO-CORDEX: https://www.euro-cordex.net/). Precipitation durations range from 1 to 72 hours. Regional Climate Models (RCMs) involved are: ALADIN63,COSMO, HadREM3, RCA4, RegCM4-6, and REMO2015. For each member, we considered both historical (1950-2005) and future (2006-2100) RCP8.5 scenarios. Simulations of four RCMs (out of a total of six) are also available for the past, with imposed “perfect” lateral boundary conditions following ERA-Interim reanalyses (1979-2019). In EURO-CORDEX, different RCMs can have (slightly) different grids and some RCMs (e.g. ALADIN63 and RegCM4-6) have a much different domain. For each RCM the correct bounds are given in the corresponding dataset. In contrast, the bounds given in the Experiment are smaller and can be found on the EURO-CORDEX website: https://euro-cordex.net/060374/index.php.en For practical applications, we also provide the regridded values on a common grid of 0.11° × 0.11° with spatial coverage of 28N−70N and 13W−35E. In Version 2, we supplemented the original dataset from Version 1 with the regridded data in a common grid. We also added evaluation runs (where available) and useful variables such as “surface elevation” (orog) and “land surface fraction” (sftlf) to all NetCDF files.

Annual maxima of sub-daily precipitation were extracted from each of 35 members of a EURO-CORDEX ensemble with a spatial resolution of 0.11° (EURO-CORDEX: https://www.euro-cordex.net/). Precipitation durations range from 1 to 72 hours. Regional Climate Models (RCMs) involved are: ALADIN63,COSMO, HadREM3, RCA4, RegCM4-6, and REMO2015. For each member, we considered both historical (1950-2005) and future (2006-2100) RCP8.5 scenarios. In EURO-CORDEX, different RCMs can have (slightly) different grids and some RCMs (e.g. ALADIN63 and RegCM4-6) have a much different domain. For each RCM the correct bounds are given in the corresponding dataset. In contrast, the bounds given in the Experiment are smaller and can be found on the EURO-CORDEX website: https://euro-cordex.net/060374/index.php.en A new version exists now. In Version 2, we supplemented the original dataset from Version 1 with the regridded data in a common grid. We also added evaluation runs (where available) and useful variables such as “surface elevation” (orog) and “land surface fraction” (sftlf) to all NetCDF files.

The experiment aims to investigate how the representation of convection influences the West African Monsoon during the mid-Holocene. Atmospheric and SST input data originate from the MPI-ESM Holocene simulations reflecting Holocene condition. External Parameters (surface condition) were adjusted to reflect mid-Holocene vegetation conditions. We prescribe an idealized, denser vegetation cover based on the simulated desert fraction (1-vegetation fraction) of the transient mid-Holocene MPI-ESM simulations (Dallmeyer et al., 2020). We use the ICON (ICOsahedral Nonhydrostatic) model framework version 2.5.0 (see Zängl et al. (2014) for more details). The provided data covers one simulation from June to October (JJASO) for the year 7024 before present (BP) with the year 2000 as the reference year. The time axes of the NetCDF files reflect the model year which is based on the time axes of the MPI-ESM slo0021a Holocene simulations. The artificial model year 1001 in slo0021a refers to the year 8000 BP. Therefore, the model year 1978 refers to the year 7024 BP. The experiment compares a 5km horizontal resolution, deep convection resolving simulation with a 40km-horizontal resolution, parameterized convection simulation. The 40km-domain (DOM01) covers a range from 70.5°W - 99.5°E; 49°S - 59°N The 5km-domain (DOM04) covers a range from 37°W - 53°E; 0°N - 40°N The dataset provides daily mean values on the triangular ICON grid. The datasets provide atmospheric (_atm_ 3D), surface (_sfc_ 2D) and precipitation ( _prec_ 2D) and forcing (extpar_) data and the following variables: w_so, lhfl_s, shfl_s, runoff_s, runoff_g, rain_con_rate, rain_gsp_rate, geopot, temp, rh, qv, u, v, w, clc Precipitation and forcing data are combined into 2 data files for DOM01 and DOM04. Surface data are combined into 2 data files for DOM01. The dataset with the suffix "_constSM_sep_" contains the data for the constant soil moisture simulations. In these simulations we prescribe the same constant soil moisture field, representing 1st September-soil moisture conditions, both for the 40km-P (DOM01) and the 5km-E (DOM04) simulations. The DS ("Dry Sahara") simulations refer to the simulations where we prescribe present-day land surface cover - the Sahara remains a desert. The GS ("Green Sahara") simulations represent idealized mid-Holocene conditions where we prescribe a higher vegetation cover that also extend further north. The Sahara reflects more savannah-like vegetation.

The HEXM98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (M): 96 hours forecast T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 96 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)

The HEXO98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (O): 120 hours forecast (5 days) T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 120 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)