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  • Data  (1,058)
  • Published Data from (DKRZ) Deutsches Klimarechenzentrum  (1,058)
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  • 1
    Publication Date: 2020-11-25
    Description: RCM forcing data from the first realisation r1i1p1f1 of the CMIP6/CMIP DECK experiment amip (original name of the simulation "amip-HR"), conducted with the MPI-ESM1-2-HR on the Mistral supercomputer of the DKRZ. The experiment covers the years 1979 to 2014. The file format is gzip-compressed GRIB (*.grb.gz). CMIP6 website: https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6 CMIP6 paper: https://www.geosci-model-dev.net/9/1937/2016/gmd-9-1937-2016.html Experiment description amip: An atmosphere only climate simulation using prescribed sea surface temperature and sea ice concentrations but with other conditions as in the Historical simulation.
    Type: experiment
    Format: GRIB1 zipped; recs separated
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  • 2
    Publication Date: 2021-01-15
    Description: ICON 2.5 km simulations over the tropical Atlantic ([65W:15E],[10S:20N] for the months of December 2013 (NARVAL1 : 30 days) and August 2016 (NARVAL2 : 30 days). The grid spacing, computed as the square root of the triangular grid cells, amounts to 2.5 km. In the vertical, a stretched vertical coordinate is used with 75 layers, whereby 12 layers are located in the first kilometer. The simulations are conducted for the months of December 2013 and July 2016. They are started every day at 00 UTC from the analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) and integrated for 36 hours. Boundary data are taken from the ECMWF forecasts and updated every 3 hours. At the bottom boundary, the Sea Surface Temperature (SST) is taken from the ECMWF analysis. It is kept fixed at its initial value during the 36-h integration period. The simulations were conducted using the ICOsahedral Non-hydrostatic (ICON) model (Zängl et al., 2015). Given the horizontal grid spacing, no convective parameterization is employed and convection is explicitly resolved by the bulk microphysics scheme that predicts cloud water, rain, snow, ice and graupel (Baldauf et al., 2011). The parameterizations for gravity wave drag and subgrid-scale orography are also switched off, otherwise the model employs the same parameterizations as the operational model version in use at the German Weather Service (DWD), see Zängl et al. (2015) and Klocke et al. (2017) for further details.
    Type: experiment
    Format: NetCDF
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  • 3
    Publication Date: 2021-01-15
    Description: ICON 2.5 km simulations over the tropical Atlantic ([65W:15E],[10S:20N] for the months of December 2013 (NARVAL1 : 30 days) and August 2016 (NARVAL2 : 30 days). The grid spacing, computed as the square root of the triangular grid cells, amounts to 2.5 km. In the vertical, a stretched vertical coordinate is used with 75 layers, whereby 12 layers are located in the first kilometer. The simulations are conducted for the months of December 2013 and July 2016. They are started every day at 00 UTC from the analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) and integrated for 36 hours. Boundary data are taken from the ECMWF forecasts and updated every 3 hours. At the bottom boundary, the Sea Surface Temperature (SST) is taken from the ECMWF analysis. It is kept fixed at its initial value during the 36-h integration period. The simulations were conducted using the ICOsahedral Non-hydrostatic (ICON) model (Zängl et al., 2015). Given the horizontal grid spacing, no convective parameterization is employed and convection is explicitly resolved by the bulk microphysics scheme that predicts cloud water, rain, snow, ice and graupel (Baldauf et al., 2011). The parameterizations for gravity wave drag and subgrid-scale orography are also switched off, otherwise the model employs the same parameterizations as the operational model version in use at the German Weather Service (DWD), see Zängl et al. (2015) and Klocke et al. (2017) for further details.
    Type: experiment
    Format: NetCDF
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  • 4
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    WDCC
    Publication Date: 2021-01-09
    Description: The hydrodynamic model TRIM-NP in a barotropic mode is used to simulate the strong storm tide in March 1906 forced by NOAA-CIRES-DOE Twentieth Century Reanalysis (20CR) version 2c and 3. datasets (https://portal.nersc.gov/project/20C_Reanalysis/). The model area covers the region of 20W to 30E and 42N to 65N with a spatial resolution of 12.8x12.8 km for grid 1. At the lateral boundaries of grid 1, the water level is calculated with tide model FES2004. TRIM-NP calculates one way nested with higher resolution the North Sea (with 6.4km, grid2), southern North Sea (with 3.2km, grid3) and the German Bight (with 1.6km, grid4). In this data bank, the datasets are available hourly for grid 2 and grid 4. Please contact the authors for grid 1 and grid 3.
    Type: experiment
    Format: NetCDF
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  • 5
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    WDCC
    Publication Date: 2021-01-09
    Description: The hydrodynamic model TRIM-NP in a barotropic mode is used to simulate the strong storm tide in March 1906 forced by ECMWF ERA-20C and CERA-20C ensemble of coupled climate reanalyses (https://www.ecmwf.int). The model area covers the region of 20W to 30E and 42N to 65N with a spatial resolution of 12.8x12.8 km for grid 1. At the lateral boundaries of grid 1, the water level is calculated with tide model FES2004. TRIM-NP calculates one way nested with higher resolution the North Sea (with 6.4km, grid2), southern North Sea (with 3.2km, grid3) and the German Bight (with 1.6km, grid4). In this data bank, the datasets are available hourly for grid 2 and grid 4. Please contact the authors for grid 1 and grid 3.
    Type: experiment
    Format: NetCDF
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  • 6
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    WDCC
    Publication Date: 2021-01-16
    Description: Source code of the Max Planck Institute Earth System Model (MPI-ESM1.2) adopted to the project PRIMAVERA for the comparison of four different ocean vertical mixing schemes.
    Type: experiment
    Format: tar.gz
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  • 7
    Publication Date: 2020-03-21
    Description: Products of liquid water path (LWP), rain water path (RWP) and integrated water vapor (IWV, also called precipitable water vapor (PWV)) are retrieved from microwave radiometer observations with auxiliary measurements from backscatter lidar and cloud radar. The nadir measurements were taken by the German High Altitude and Long range research aircraft (HALO) during the Next generation Advanced Remote sensing for VALidation campaign South (NARVAL-South) in December 2013. Products are provided over tropical Atlantic east of Barbados. This experiment provides column integrated quantities as seen from satellite perspective but with higher spatially resolution (about 1 km footprint) than available from microwave satellites.
    Type: experiment
    Format: NetCDF
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  • 8
    Publication Date: 2020-03-21
    Description: Products of liquid water path (LWP), rain water path (RWP) and integrated water vapor (IWV, also called precipitable water vapor (PWV)) are retrieved from microwave radiometer observations with auxiliary measurements from backscatter lidar and cloud radar. The nadir measurements were taken by the German High Altitude and Long range research aircraft (HALO) during the Next generation Advanced Remote sensing for VALidation campaign 2 (NARVAL2) in August 2016. Products are provided over tropical Atlantic east of Barbados. This experiment provides column integrated quantities as seen from satellite perspective but with higher spatially resolution (about 1 km footprint) than available from microwave satellites.
    Type: experiment
    Format: NetCDF
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  • 9
    Publication Date: 2020-03-24
    Description: We developed a global dataset of downscaled future projections developed by applying a statistical method for climate model downscaling and bias correction. To develop the dataset, we applied the delta method, which comprises the sum of interpolated anomalies of each GCM to the WorldClim 1-km spatial resolution dataset. The GCMs were the 35 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, for four representative concentrations pathways (RCPs). For each of these, we used the 30-year future periods named as 2030s (mean of 2020-2049), 2050s (2040-2069), 2070s (2060-2089) and 2080s (2070-2099) with three climate variables (mean monthly maximum and minimum temperatures and monthly rainfall). From these, we also derive a set of bioclimatic indices.
    Type: experiment
    Format: ESRIarcinfoGrid.ascii.zip
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  • 10
    Publication Date: 2020-04-13
    Description: A marine physical biogeochemical model simulation was performed for the year 2012 covering the North Sea and Baltic Sea. Only data for the western Baltic Sea are provided here. The model output has been validated in Neumann et al. (2018a, doi: 10.5194/os-2018-71). The work was funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI, FKZ 50EW1601, https://www.io-warnemuende.de/meramo-en.html). The simulation was performed at the North-German Supercomputing Alliance (HLRN, project id: mvk00054, zulassung.hlrn.de/kurzbeschreibungen/mvk00054.pdf). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A). The model simulation was forced by operational meteorological data of the German Weather Service (DWD). Atmospheric nitrogen deposition data of 50x50 km2 spatial resolution were taken from the 2016 reporting of the European Measurement and Evaluation Programme (EMEP) as presented in EMEP (2016, url: http://emep.int/publ/reports/2016/EMEP_Status_Report_1_2016.pdf) and available from the Norwegian Meteorological Institute (2016, http://thredds.met.no/thredds/catalog/data/EMEP/2016_Reporting/catalog.html). Information on the riverine inputs, boundary conditions, and the model itself are provided in detail in Neumann et al. (2018b, doi: 10.5194/bg-2018-364). The concentrations of all prognostic biogeochemical model variables are given in nitrogen units according to the Redfield ratio.
    Type: experiment
    Format: NetCDF
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  • 11
    Publication Date: 2020-04-13
    Description: A marine physical biogeochemical model simulation was performed for the year 2012 covering the North Sea and Baltic Sea. Only data for the western Baltic Sea are provided here. The model output has been validated in Neumann et al. (2018a, doi: 10.5194/os-2018-71). The work was funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI, FKZ 50EW1601, https://www.io-warnemuende.de/meramo-en.html). The simulation was performed at the North-German Supercomputing Alliance (HLRN, project id: mvk00054, zulassung.hlrn.de/kurzbeschreibungen/mvk00054.pdf). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A). The model simulation was forced by operational meteorological data of the German Weather Service (DWD). Atmospheric nitrogen deposition data of medium spatial resolution of 16x16 km2 were provided by the Helmholtz-Zentrum Geesthacht within the EU BONUS SHEBA Project (Karl et al., 2019, doi: 10.5194/acp-2018-1317). Information on the riverine inputs, boundary conditions, and the model itself are provided in detail in Neumann et al. (2018b, doi: 10.5194/bg-2018-364). Nitrogen from atmospheric deposition of shipping-related nitrogen, agricultural-related nitrogen, and total nitrogen has been tagged in the model simulation according to a method by Menésguen et al. (2006, 10.4319/lo.2006.51.1_part_2.0591). Therefore, all nitrogen-containing model variables exist four times in the output: once as regular variables and once per tagged nitrogen source (total, shipping-related, agricultural-related). The concentrations of all prognostic biogeochemical model variables are given in nitrogen units according to the Redfield ratio.
    Type: experiment
    Format: NetCDF
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  • 12
    Publication Date: 2020-04-13
    Description: A marine physical biogeochemical model simulation was performed for the year 2012 covering the North Sea and Baltic Sea. Only data for the western Baltic Sea are provided here. The model output has been validated in Neumann et al. (2018a, doi: 10.5194/os-2018-71). The work was funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI, FKZ 50EW1601, https://www.io-warnemuende.de/meramo-en.html). The simulation was performed at the North-German Supercomputing Alliance (HLRN, project id: mvk00054, zulassung.hlrn.de/kurzbeschreibungen/mvk00054.pdf). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A). The model simulation was forced by operational meteorological data of the German Weather Service (DWD). Atmospheric nitrogen deposition data of high spatial resolution of 4x4 km2 were provided by the Helmholtz-Zentrum Geesthacht within the EU BONUS SHEBA Project (Karl et al., 2019, doi: 10.5194/acp-2018-1317). Information on the riverine inputs, boundary conditions, and the model itself are provided in detail in Neumann et al. (2018b, doi: 10.5194/bg-2018-364). Nitrogen from atmospheric deposition of shipping-related nitrogen has been tagged in the model simulation according to a method by Menésguen et al. (2006, 10.4319/lo.2006.51.1_part_2.0591). Therefore, all nitrogen-containing model variables exist twice in the output: once as regular variables and once as nitrogen content from shipping-related activities. The concentrations of all prognostic biogeochemical model variables are given in nitrogen units according to the Redfield ratio.
    Type: experiment
    Format: NetCDF
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  • 13
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    WDCC
    Publication Date: 2020-09-17
    Description: This is version v1.1 of the hydrographic part of the "Baltic and North Sea Climatology (BNSC)". It turned out that the original hydrographic data product of the BNSC (BNSClim hydrographic part (Version 1.0)) was erroneous. The errors occurred by accidentally reading obsolete files in two of the intermediate steps of the production procedure. By this, the basis of observations was altered. This happened after the quality control and interpolation of the observations on standard depths, in the step where the observations are sorted into the chosen grid (this affects temperature and salinity) and in the following step, the correction of the temporal sampling error (this affects only salinity). These errors were corrected in this Version 1.1. The parameters provided are water temperature and salinity on 105 depth levels. The data product comprises the time period from 1873-2015 and is based on more than one million observational profiles, which were obtained from several different data sources in the region of the Baltic, the North Sea and adjacent areas of the North Atlantic Ocean (15°W-30°E, 47°N-66°N). Intersection of observational data from different data sources is avoided and the in situ data were objected to an elaborate automatic quality control to identify erroneous observations that would bias the data product. Additionally, a correction of the temporal sampling error was applied to minimize the impact of the temporal distribution of the observations on the created temporal mean fields. The data product consists of gridded mean fields of water temperature and salinity. The spatial resolution is 0.25° in meridional and zonal direction. The depth levels are irregularly distributed: for the depth interval from 0 to 50m the distance between the single depth levels is 5m. Below 50m, the distance increases progressively by 1m to the last depth level of 4985m. The dimensions of the data product are 180*76*105 (longitude, latitude, depth). The BNSC climatology consists, on the one hand, of time series of monthly and annual mean values of the hydrographic parameters as fields of box averages. Grid boxes that show no observations are left empty. Based on these time series, decadal monthly mean fields are created for the decades 1956-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015 as another part of the data product. Again, gaps remain in observational data-void regions. The third part of the data product results from above mentioned decadal mean fields: horizontally interpolated fields by application of the method of objective analysis. Consequently, this subset does not contain gaps. Available parameters: box averages: monthly and annual mean, resp. standard deviation, number of observations decadal box averages: decadal monthly mean, resp. standard deviation, mean year, standard deviation to mean year, number of years decadal interpolated mean: interpolated monthly mean, absolute median deviation, number of bins, first guess, relative interpolation error, mean year, mean distance The products and a description of the differences between v1.0 and v1.1 are publicly available at the ICDC portal ( https://icdc.cen.uni-hamburg.de/1/daten/ocean/bnsc/)
    Type: experiment
    Format: NetCDF
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  • 14
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    WDCC
    Publication Date: 2020-10-03
    Description: Global paleoclimate simulations are carried out on the basis of the so-called time slice technique. The simulations are performed with the state-of-the-art global circulation model ECHAM5 (Roeckner et al., 2003) at a spectral resolution of T106 (∼1.125°×1.125°) and 19 vertical levels. Different time slices are selected at a time interval of approx. 1000 years from each other, from 6000 years ago to pre-industrial times. For each time slice a simulation is carried out over a period of 30 years. As boundary conditions prescribed sea ice fraction and sea surface temperatures were used, which were derived from a continuous simulation with transient periods. This simulation was performed with the coupled atmosphere-ocean circulation model ECHO-G, consisting of the ECHAM4 (Roeckner et al., 1996) and the ocean model HOPE (Wolff et al., 1997), at a spectral resolution of T30 (∼3.75◦×3.75◦). Further information on simulation realization can be found in Wagner et al. (2007). Detailed information on the model set-up can be found in Russo and Cubasch (2016). Russo, E. and Cubasch, U.: Mid-to-late Holocene temperature evolution and atmospheric dynamics over Europe in regional model simulations, Clim. Past, 12, 1645-1662, https://doi.org/10.5194/cp-12-1645-2016, 2016.
    Type: experiment
    Format: GRIB
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  • 15
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    WDCC
    Publication Date: 2020-10-03
    Description: High-resolution simulations of the palaeoclimate are carried out throughout Europe. A set of climate simulations will be performed, based on the so-called time slicing technique. The simulations are performed with the state-of-the-art regional climate model COSMO-CLM (cosmo_4.8_clm19) at a horizontal resolution of 0.44° longitude and 40 vertical levels. The COSMO-CLM is a non-hydrostatic RCM with rotated geographical coordinates and a terrain following height coordinate (Rockel et al., 2008), developed by the German Weather Service (DWD) of the COSMO model (Doms and Schättler, 2003). The ECHAM5 output is used as a boundary data set for the dynamic downscaling approach. Detailed information on the model set-up can be found in Russo and Cubasch (2016). Russo, E. and Cubasch, U.: Mid-to-late Holocene temperature evolution and atmospheric dynamics over Europe in regional model simulations, Clim. Past, 12, 1645-1662, https://doi.org/10.5194/cp-12-1645-2016, 2016.
    Type: experiment
    Format: NetCDF
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  • 16
    Publication Date: 2020-11-03
    Description: Polar regions are data sparse regions. Research ships operating in polar regions often record sea-ice conditions during their transects through ice infested waters. Such observations of the sea-ice conditions are often the only information that can be provided in addition to satellite-based estimates of the sea-ice conditions, such as sea-ice concentration or sea-ice thickness. Such observations have been carried out and gathered using two protocols. For the Antarctic, this is the so-called ASPeCt protocol [Worby and Allison, 1999; Worby and Dirita, 1999; Worby et al., 2008]. For the Arctic, this is the so-called ASSIST/IceWatch protocol [Hutchings et al., 2018]. The latter builds on the ASPeCt protocol, incorporating surface melt conditions being more ubiquitous in the Arctic. Ship-based observations of the sea-ice conditions are conducted manually, visually, i.e. by eye, regularly every hour taking into account an area around the ship of about one kilometer radius. Note that this area distorts to an elliptically shaped area as a function of observers' experience, ships' cruising speed and ice and visibility conditions. Each observation comprises the total sea-ice concentration, and the concentration, level ice thickness, level ice snow depth, fraction and height of ridges, ice type, snow type, and floe size for the up to three thickest ice types. For the Arctic, melt-pond fraction and stage-of-melt are also part of the observables. In addition to the ships' position often auxiliary parameters such as visibility, wind speed and direction, or air and water temperature are recorded. For development and evaluation of satellite-based sea-ice products, such ship-based observations are of great value. Because of this, within the ESA-CCI sea-ice ECV project (ESA-SICCI), phase 2, a standardized data set of such ship-based observations was generated for both polar regions. It comprises data from June 2002 through December 2015. This time period is motivated by the purpose to evaluate sea-ice concentration data retrieved from AMSR-E and AMSR2 brightness temperature measurements which, at the time the project was initiated, were planned to be retrieved until the end of 2015. The data set incorporates observational data from various collections, e.g. a part of the original ASPeCt collection [Worby et al., 2008], which ended in May 2005. More information about all data sources is given below. All data have been manually standardized to the same format (i.e., number of decimals, unit), using the same value to describe missing data, using the same temporal ordering, and filling gaps with the respective missing-data value. Double data entries have been removed. The data set is split into two ascii text files, one for the Arctic, one for the Antarctic. It has been successfully used to evaluate sea-ice concentration and thickness products of the ESA-SICCI phase 2 project.
    Type: experiment
    Format: GZ
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  • 17
    Publication Date: 2020-11-08
    Description: The eVolv2k database includes estimates of the magnitudes and approximate source latitudes of major volcanic stratospheric sulfur injection (VSSI) events from 500 BCE to 1900 CE. The VSSI estimates incorporate recent improvements to the ice core records in terms of synchronization and dating, refinements to the methods used to estimate VSSI from ice core records, and includes estimates of the random uncertainties in VSSI values. Ice core-derived volcanic sulfate deposition composites for Antarctica (Sigl et al., 2014) and Greenland (Sigl et al., 2015, Zielinski et al., 1995) are scaled to volcanic stratospheric sulfur injection based on a method similar to that of Gao et al. (2007). More details are described by Toohey and Sigl (2017). Compared to version 2, this update includes reassignment of eruption region for minor events in 1654, 1414, 1381, 688, 379 and -430. Also, minimum flux threshold adjusted downwards so as to include small Greenland flux for events in 1463, -190 and -430. Finally, events with 0 VSSI removed. In addition, a reconstruction of stratospheric aerosol optical depth (AOD) using the VSSI estimates and the EVA v1.2 volcanic forcing generator (Toohey et al., 2016) is provided. Complete optical properties (extinction, single scattering albedo, scattering asymmetry factor) as a function of height, latitude and time can be produced using the eVolv2k VSSI database and the EVA forcing generator. EVA version 1.2 includes a fix of a minor bug which affected the spatiotemporal distribution of AOD, most notably for extratropical eruptions. Gao, C., Oman, L., Robock, A. and Stenchikov, G. L.: Atmospheric volcanic loading derived from bipolar ice cores: Accounting for the spatial distribution of volcanic deposition, J. Geophys. Res., 112(D9), doi:10.1029/2006JD007461, 2007. Sigl, M., Winstrup, M., McConnell, J. R., Welten, K. C., Plunkett, G., Ludlow, F., Büntgen, U., Caffee, M., Chellman, N., Dahl-Jensen, D., Fischer, H., Kipfstuhl, S., Kostick, C., Maselli, O. J., Mekhaldi, F., Mulvaney, R., Muscheler, R., Pasteris, D. R., Pilcher, J. R., Salzer, M., Schüpbach, S., Steffensen, J. P., Vinther, B. M. and Woodruff, T. E.: Timing and climate forcing of volcanic eruptions for the past 2,500 years, Nature, 523, 543¿549, doi:10.1038/nature14565, 2015. Sigl, M., McConnell, J. R., Toohey, M., Curran, M., Das, S. B., Edwards, R., Isaksson, E., Kawamura, K., Kipfstuhl, S., Krüger, K., Layman, L., Maselli, O. J., Motizuki, Y., Motoyama, H., Pasteris, D. R. and Severi, M.: Insights from Antarctica on volcanic forcing during the Common Era, Nat. Clim. Chang., 4, 693-697, doi:10.1038/nclimate2293, 2014. Toohey, M. and Sigl, M.: Volcanic stratospheric sulfur injections and aerosol optical depth from 500 BCE to 1900 CE, Earth Syst. Sci. Data, 9(2), 809–831, doi:10.5194/essd-9-809-2017, 2017. Toohey, M., Stevens, B., Schmidt, H. and Timmreck, C.: Easy Volcanic Aerosol (EVA v1.0): an idealized forcing generator for climate simulations, Geosci. Model Dev., 9(11), 4049–4070, doi:10.5194/GMD-9-4049-2016, 2016.
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  • 18
    Publication Date: 2020-11-15
    Description: A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 2003 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1999 and, then, from 2000 to 2002 with tagging (see below). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html; IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx; HELCOM: Helsinki Commission). A publication is in preparation. The model simulation was forced by coastDat2 COSMO-CLM data (doi:10.1594/WDCC/coastDat-2_COSMO-CLM). Atmospheric nitrogen deposition data of 0.1° x 0.1° spatial resolution were taken from the 2018 reporting of the European Measurement and Evaluation Programme (EMEP) as presented in EMEP (2018, url: http://emep.int/publ/reports/2018/EMEP_Status_Report_1_2018.pdf) and available from the Norwegian Meteorological Institute (2018, url: http://thredds.met.no/thredds/catalog/data/EMEP/2018_Reporting/catalog.html). Nitrogen from atmospheric deposition of nitrogen from livestock/agricultural emissions (estimated, see documentation) and from all emission sectors has been tagged in the model simulation according to a method by Menésguen et al. (2006, doi:10.4319/lo.2006.51.1_part_2.0591). Therefore, all nitrogen-containing model variables exist three times in the output: once as regular variables and once per tagged nitrogen source (total atmospheric and agriculturally-related). The simulation was performed at the North-German Supercomputing Alliance (HLRN, project id: mvk00054, zulassung.hlrn.de/kurzbeschreibungen/mvk00054.pdf). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
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  • 19
    Publication Date: 2020-11-15
    Description: A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the year 2012 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1999 and, then, from 2000 to 2011 with tagging (see below; three years would have been sufficient). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html; IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx; HELCOM: Helsinki Commission). A publication is in preparation. The model simulation was forced by coastDat2 COSMO-CLM data (doi:10.1594/WDCC/coastDat-2_COSMO-CLM). Atmospheric nitrogen deposition data of 16x16 km2 horizontal resolution were provided by the Helmholtz-Zentrum Geesthacht within the EU BONUS SHEBA Project (Karl et al., 2019, doi:10.5194/acp-19-7019-2019). Nitrogen from atmospheric deposition of nitrogen from shipping emissions and from all emission sectors has been tagged in the model simulation according to a method by Menésguen et al. (2006, doi: 10.4319/lo.2006.51.1_part_2.0591). Therefore, all nitrogen-containing model variables exist three times in the output: once as regular variables and once per tagged nitrogen source (total atmospheric and shipping-related). The simulation was performed at the North-German Supercomputing Alliance (HLRN, project id: mvk00054, zulassung.hlrn.de/kurzbeschreibungen/mvk00054.pdf). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
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    Format: NetCDF
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  • 20
    Publication Date: 2020-11-28
    Description: A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1995 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1984 and, then, from 1985 to 1994 with tagging (see below). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html; IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx; HELCOM: Helsinki Commission). The model simulation was forced by coastDat2 COSMO-CLM data (doi:10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi:10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, doi:10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable. The default phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was used (PhosWaM SWAT case "ist"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the "Unterwarnow turnover estimation v05" (see final project report of PhosWaM for details). The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
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  • 21
    Publication Date: 2020-11-28
    Description: A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1995 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1984 and, then, from 1985 to 1994 with tagging (see below). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html; IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx; HELCOM: Helsinki Commission). The model simulation was forced by coastDat2 COSMO-CLM data (doi:10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi:10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, doi:10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable. The default phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was used ("base scenario"; PhosWaM SWAT case "ist"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the "Unterwarnow turnover estimation v04" (see final project report of PhosWaM for details). The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
    Type: experiment
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  • 22
    Publication Date: 2020-11-28
    Description: A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1995 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1984 and, then, from 1985 to 1994 with tagging (see below). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html; IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx; HELCOM: Helsinki Commission). The model simulation was forced by coastDat2 COSMO-CLM data (doi:10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi:10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, doi:10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable. The phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was calculated and a Maximum Technical Feasible Reduction (MTFR) approach was applied (PhosWaM SWAT case "35"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the "Unterwarnow turnover estimation v04" (see final project report of PhosWaM for details). The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
    Type: experiment
    Format: NetCDF
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  • 23
    Publication Date: 2020-11-28
    Description: A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1995 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1984 and, then, from 1985 to 1994 with tagging (see below). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html; IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx; HELCOM: Helsinki Commission). The model simulation was forced by coastDat2 COSMO-CLM data (doi:10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi:10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, doi:10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable. The phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was modified in order to comply with BASP (Baltic Sea Action Plan) targets (PhosWaM SWAT case "15"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the "Unterwarnow turnover estimation v04" (see final project report of PhosWaM for details). The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
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  • 24
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    Publication Date: 2019-07-06
    Description: Global HAPPI-MIP protocol data based on the NorESM1-HAPPI [1] AGCM developed by the NCC (NorESM Climate modeling Consortium). This CERA experiment includes data of 135 AMIP simulations within the period 1959-2016, 125 AMIP-like simulations of 2106-2116 representing a climate warmer by 1.5°C than under pre-industrial conditions (1861-1880) and 125 AMIP-like simulations of 2106-2116 representing a climate warmer by 2.0°C than under pre-industrial conditions. Reference: [1] https://doi.org/10.5194/esd-2017-115
    Type: experiment
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  • 25
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    Publication Date: 2019-07-06
    Description: Global HAPPI-MIP protocol data based on the CanAM4 [1] AGCM developed by the Canadian Centre for Climate Modelling and Analysis (CCCma). This CERA experiment includes data of 100 AMIP simulations of the period 2006-2015, 100 AMIP-like simulations of 2106-2115 representing a climate warmer by 1.5°C than under pre-industrial conditions (1861-1880) and 100 AMIP-like simulations of 2106-2115 representing a climate warmer by 2.0°C than under pre-industrial conditions (1861-1880). Reference: [1] https://doi.org/10.1080/07055900.2012.755610
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  • 26
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    Publication Date: 2019-07-06
    Description: Global HAPPI-MIP protocol data based on the CAM4[1]/CLM4 [2] (CAM4-2degree) AGCM developed by the National Center for Atmospheric Research – Department of Energy (NCAR-DOE). CAM4/CLM4 is part of the CESM 1.0.4 model release [3]. This CERA experiment includes data of 521 AMIP simulations within the period 1979-2016, 501 AMIP-like simulations of 2106-2116 representing a climate warmer by 1.5°C than under pre-industrial conditions (1861-1880) and 501 AMIP-like simulations of 2106-2116 representing a climate warmer by 2.0°C than under pre-industrial conditions (1861-1880). Reference: [1] Neale, R. B., Richter, J. H., Conley, A. J., Park, S., Lauritzen, P. H., Gettelman, A., Williamson, D. L., Rasch, P. J., Vavrus, S. J., Taylor, M. A., Collins, W. D., Zhang, M., and Lin, S.-J.: Description of the NCAR Community Atmosphere Model (CAM4). NCAR Tech. Note NCAR/TN-485+STR, National Center for Atmospheric Research, Boulder, CO, 120 pp., 2011. [2] Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E., Lawrence, P. J., Levis, S., Swenson, S. C., Thornton, P. E., Dai, A., Decker, M., Dickinson, R., Feddema, J., Heald, C. L., Hoffman, F., Lamarque, J.-F., Mahowald, N., Niu, G.-Y., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stockli, R., Wang, A., Yang, Z.-L., Zeng, Xi., and Zeng, Xu.: Technical Description of version 4.0 of the Community Land Model (CLM), NCAR Tech. Note NCAR/TN-478+STR, National Center for Atmospheric Research, Boulder, CO, 257 pp., 2010. [3] http://www.cesm.ucar.edu/models/cesm1.0/tags/index.html#CESM1_0_4
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  • 27
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    Publication Date: 2019-07-06
    Description: Global HAPPI-MIP protocol data based on the MIROC5 [1] AGCM developed by the University of Tokyo, NIES and JAMSTEC (MIROC). This CERA experiment includes data of 160 AMIP simulations within the period 1950-2016, 100 AMIP-like simulations of 2106-2116 representing a climate warmer by 1.5°C than under pre-industrial conditions (1861-1880) and 100 AMIP-like simulations of 2106-2116 representing a climate warmer by 2.0°C than under pre-industrial conditions. Reference: [1] https://doi.org/10.1175/2010JCLI3679.1
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  • 28
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    WDCC
    Publication Date: 2019-07-06
    Description: Global HAPPI-MIP protocol data based on the ECHAM6.3 [1] AGCM developed by the MPI-M (Max Planck Institute for Meteorology). This CERA experiment includes data of 100 AMIP simulations of the period 2006-2015, five AMIP simulations of 1959-2015, 100 AMIP-like simulations of 2106-2115 representing a climate warmer by 1.5°C than under pre-industrial conditions (1861-1880) and 100 AMIP-like simulations of 2106-2115 representing a climate warmer by 2.0°C than under pre-industrial conditions. The data of the current decade and of the 57-year long simulations are copies of those in https://doi.org/10.1594/WDCC/HAPPI-MIP-global-ECHAM6.3. The other data therein are flawed and are replaced herein by new versions. Reference: [1] doi:10.1002/jame.20015
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  • 29
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    Publication Date: 2020-03-12
    Description: Since the beginning of CALIPSO observations in June 2006 EARLINET has performed correlative measurements during nearby overpasses of the satellite at individual stations following a dedicated observational strategy. The EARLINET-CALIPSO correlative measurement plan considers the criteria established in the CALIPSO validation plan (http://calipsovalidation.hamptonu.edu). Participating EARLINET stations perform measurements, as close in time as possible and for a period of at least 30 min up to several hours, when CALIPSO overpasses their location within a horizontal radius of 100 km. Within the 16-day observational cycle of CALIPSO each station is overpassed within this distance 1-2 times during daytime (typically between 1100 and 1400 UTC) and 1-2 times during night time (typically between 0000 and 0300 UTC). Additional measurements are performed, mainly on a non-regular basis, when CALIPSO overpasses a neighboring station in order to study the horizontal variability of the aerosol distribution. The time schedule for correlative observations is calculated starting from the high-resolution ground-track data provided by NASA, and is updated and distributed to whole network weekly. The EARLINET-CALIPSO correlative dataset represents a statistically significant data set to be used for the validation and full exploitation of the CALIPSO mission, for studying the representativeness of cross sections along an orbit against network observations on a continental scale, and for supporting the continuous, harmonized observation of aerosol and clouds with remote-sensing techniques from space over long time periods.
    Type: experiment
    Format: tar-File(s)
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  • 30
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    Publication Date: 2020-03-12
    Description: This collection contains all measurements that have been performed in the frame of the EARLINET project during the period April 2000 - December 2015. Some of these measurements are also part of the collections 'Calipso', 'Climatology', 'SaharanDust' or 'VolcanicEruption'. In addition this collection also contains measurements from the categories 'Cirrus', 'DiurnalCycles', 'ForestFires', 'Photosmog', 'RuralUrban', and 'Stratosphere'. This collection also contains measurements not devoted to any of the above categories. More information about these categories and the contributing stations can be found in the file 'EARLINET_general_introduction.pdf' accompanying this dataset.
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  • 31
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    Publication Date: 2020-03-12
    Description: The geographical distribution of the EARLINET stations is particularlysuitable for dust observation, with stations located all around the Mediterranean(from the Iberian Peninsula in the West to the Greece and Bulgaria and Romania in the East) and in the center of the Mediterranean (Italian stations) where dust intrusions are frequent, and with several stations in the central Europe where dust penetrates occasionally. A suitable observing methodology has been established within the network, based on Saharan dust alerts distributed to all EARLINET stations. The dust alert is based on the operational outputs (aerosol dust load) of the SDS-WAS (Sand and Dust Storm- Warning and Advisory System of WMO), and the Skiron models. The alerts are diffused 24 to 36 hours prior to the arrival of dust aerosols over the EARLINET sites. Runs of measurements longer than 3-hour observations, typical for the EARLINET climatological measurements are performed at the EARLINET stations in order to investigate the temporal evolution of the dust events. All aerosol backscatter and extinction profiles related to observations of Saharan dust layers are collected in the "Saharan dust" category of the EARLINET database.
    Type: experiment
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  • 32
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    Publication Date: 2020-03-12
    Description: Aerosols originating from volcanic emissions have an impact on the climate: sulfate and ash particles from volcanic emissions reflect solar radiation, act as cloud condensation and ice nuclei, and modify the radiative properties and lifetime of clouds, and therefore influence the precipitation cycle. These volcanic particles can also have an impact on environmental conditions and could be very dangerous for aircraft in flight. In addition to the routine measurements, further EARLINET observations are devoted to monitor volcano eruptions. The EARLINET volcanic dataset includes extended observations related to two different volcanoes in Europe Mt. Etna (2001 and 2002 eruptions), and the Eyjafjallajökull volcano in Iceland (April - May 2010 eruption). This dataset includes also events of volcanic eruptions in the North Pacific region (2008-2010) that emitted sulfuric acid droplets into the upper troposphere lower stratosphere (UTLS) height region of the northern hemisphere. The EARLINET volcanic observations in the UTLS are complemented by the long-term stratospheric aerosol observations collected in the Stratosphere category.
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  • 33
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    Publication Date: 2020-03-12
    Description: EARLINET climatological lidar observations are performed on a regular schedule of one daytime measurement per week around noon (on Monday), when the boundary layer is usually well developed, and two night-time measurements per week (on Monday and Thursday), with low background light, in order to perform Raman extinction measurements. This regular schedule for observations minimizes the bias in the dataset possibly related to specific measurement conditions. The resulting dataset is used to obtain unbiased data for climatological studies. This dataset contains profiles of aerosol extinction, backscatter and lidar ratio. Several aerosol extinction/backscatter datasets can be present for the same climatological measurement in order to provide profiles either with a better temporal resolution or with an extended height range by using a larger temporal average. This is by far the largest ground based dataset on the aerosol vertical distribution, and it is the only one which is collected systematically and is covering a whole continent.
    Type: experiment
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  • 34
    Publication Date: 2020-04-23
    Description: Attenuated backscatter profiles from the CALIOP satellite lidar are used to estimate cloud base heights of lower-troposphere liquid clouds (cloud base height below approximately 3 km). Even when clouds are thick enough to attenuate the lidar beam (optical thickness 〉 5), the technique provides cloud base heights by treating the cloud base height of nearby thinner clouds as representative of the surrounding cloud field. Using ground-based ceilometer data, uncertainty estimates for the cloud base height product at retrieval resolution are derived as a function of various properties of the CALIOP lidar profiles. Evaluation of the predicted cloud base heights and their predicted uncertainty using a second, statistically independent, ceilometer dataset shows that cloud base heights and uncertainties are biased by less than 10%. CBASE provides two files for each CALIOP VFM input file: one using a 40 km window to detect the cloud field base height, and one using a 100 km window. (The input CALIOP VFM dataset is organized by the daytime/nighttime half of each orbit.) The file name pattern is CBASE〈resolution〉_〈date〉T〈time〉〈day/night〉.nc (identical to the input CALIOP VFM file name with the exception of the product name). Files are organized into subdirectories by half-orbit start date.
    Type: experiment
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  • 35
    Publication Date: 2020-04-23
    Description: The "climate" water vapor product developed within ESA's "GOME-Evolution" project provides a consistent time series of monthly mean global maps of total column water vapor derived from the satellite instruments GOME, SCIAMACHY, and GOME-2 (Metop-A). Consistency amongst the different instruments (including cloud treatment) is substantially improved by (1) merging SCIAMACHY and GOME-2 observations to GOME pixel size, and (2) reducing the GOME-2 swath width to GOME/SCIAMACHY swath, thereby mimicking GOME-like observation conditions for all three sensors. This is Version 2.2
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  • 36
    Publication Date: 2020-04-23
    Description: Data contain dominating soil type in a grid cell for the whole world at 30 arc-second (~1km) horizontal resolution. The data are based on Harmonized World Soil Database (HWSD), but reclassified according to the State Soil Geographic (STATSGO) classification table of the Weather Research and Forecasting (WRF) Model for NOAH and NOAH-MP Land Surface Models (LSMs). The source of the data is HWSD version 1.21, provided by the Food and Agriculture Organization of the United Nations (FAO), the International Institute for Applied Systems Analysis (IIASA), International Soil Reference and Information Centre (ISRIC), Institute of Soil Science - Chinese Academy of Sciences (ISSCAS) and Joint Research Centre of the European Commission (JRC) in 2012 (FAO/IIASA/ISRIC/ISSCAS/JRC, 2012. Harmonized World Soil Database (version 1.21). FAO, Rome, Italy and IIASA, Laxenburg, Austria). Horizontal resolution: 0.0083333333333333° Type/units: categorical/1-16 categories Missing_value: -9999(ascii file), 241.0 (WRF-bin) Projection: regular latitude longitude
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    Format: ascii
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  • 37
    Publication Date: 2020-06-03
    Description: This directory (experiment) contains volcanic SO2 data derived from limb viewing satellites for the lower stratosphere from 1998 to 2012. The usage of the data is described in Timmreck et al., (2018), datasets VolcDB1 and VolcDB1_3D. We provide 3D-plumes of observed volume mixing ratio perturbations in the lower stratosphere / upper troposphere typically derived from 10-day periods as nc-files and integrated values of injected SO2 mass with peak latitudes and altitudes as Fortran formatted ascii files (A11,5(1X,I3),I4,4(1X,I3),5(1X,I2),I3,4(1X,I2)) for at maximum 5 events at one time. Instead of A11 I2,I5,I5 can be used to read in the components of time. The data from Dec. 1997 to Jan. 2002 are based on L2-files of SAGE II (V7.0) provided by the NASA DAAC (Thomason et al., 2008). The data from Jul. 2002 to Mar. 2012 use the updated 5-day time series of MIPAS (Hoepfner et al., 2015), supplemented by SO2 derived from GOMOS extinctions (Bingen et al., 2017, with a corresponding table). SO2volc3D_pap_T42L90r.nc: 3D SO2 for 131 events in T42L90 resolution (ECHAM-grid in grid_T42L90.nc) surface to about 80km).. SO2volc3D_pap_T63L90r.nc: same in T63L90 resolution (ECHAM-grid in grid_T63L90.nc). Here a downscaling by 0.7 for low latitude eruptions is recommended because of less removal by overshooting convection (The data in the T42 file and in the table in Bingen et al 2017 were upscaled within the measurement uncertainty to overcome the model artifact in low resolution, this applies only for the ENVISAT part from Jul. 2002 on). Latitude from South to North, for use with ECHAM please reverse. The levels on the hybrid-grid in the grid files are defined as lev(x,y,z)=hyam(z)+hybm(z)*apsave(x,y), in Pa (apsave annual average of surface pressure or orography). Volcano_or_region_echam_merged_dd_mm_yyyy.txt: integrated SO2 mass injected (in kt), SAGE and ENVISAT period. The postscript-file is an example on the T42 grid, the *doc-file includes the volcano names for the data in the *.txt Files, see also http://wwww.volcano.si.edu (Smithsonian volcano database). AEROCOM-DIEHL_UMZ1_tropo11.nc: Fluxes from outgassing volcanoes in the troposphere (below 200hPa), taken from AEROCOM (Diehl, 2012; Caution, filled with odd climatology after 2009, monthly, beginning in Jan. 1950) AEROCOM-DIEHL_1297-0312_tropo11.nc: Subset beginning Dec. 1997.
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  • 38
    Publication Date: 2020-10-21
    Description: NARVAL-North: Measurements of microwave radiometer brightness temperatures, radar reflectivity and linear depolarisation ratio, and dropsonde atmospheric profiles from aircraft campaign over mid-latitude Atlantic out of Iceland. Aim of the campaign was the observation of clouds associated with the cold sector of mid-latitude cyclones.
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  • 39
    Publication Date: 2020-10-21
    Description: NARVAL-South: Measurements of microwave radiometer brightness temperatures, radar reflectivity and linear depolarisation ratio, and dropsonde atmospheric profiles from aircraft campaign over tropical Atlantic out of Barbados. Aim of the campaign was the observation of shallow convection in the trade wind region east of Barbados. website: http://www.mpimet.mpg.de/en/science/the-atmosphere-in-the-earth-system/working-groups/tropical-cloud-observation/halo/missions/
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  • 40
    Publication Date: 2020-10-21
    Description: NAWDEX: Measurements of microwave radiometer brightness temperatures, radar reflectivity and linear depolarisation ratio, and dropsonde atmospheric profiles from aircraft campaign over mid-latitude Atlantic out of Iceland. The campaign explored the impact of diabatic processes on disturbances of the jet stream and their influence on downstream high-impact weather through the deployment of four research aircraft. Website: http://www.pa.op.dlr.de/nawdex/
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  • 41
    Publication Date: 2020-10-21
    Description: NARVAL2: Measurements of microwave radiometer brightness temperatures, radar reflectivity and linear depolarisation ratio, and dropsonde atmospheric profiles from aircraft campaign over tropical Atlantic out of Barbados. During this campaign, a broad range of states of convection were observed from suppressed and shallow convection in relatively dry surroundings to deep convection in the ITCZ. website: https://www.mpimet.mpg.de/en/science/the-atmosphere-in-the-earth-system/working-groups/tropical-cloud-observation/halo/missions/
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  • 42
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    Publication Date: 2020-11-13
    Description: This experiment comprises 5 different simulations: - hind-cast simulations with specified dynamics from 1979 to 2013 - ERA-Interim SSTs/SICs RC1SD-base-07 T42L90MA “wave zero” (i.e. the global mean) temperature included for the Newtonian relaxation RC1SD-base-08 T42L47MA global mean temperature (wave 0) included for the Newtonian relaxation RC1SD-base-09 T42L47MA global mean temperature (wave 0) not included for the Newtonian relaxation RC1SD-base-10 T42L90MA global mean temperature (wave 0) not included for the Newtonian relaxation RC1SD-base-10a (years 2000-2014) T42L90MA global mean temperature (wave 0) not included for the Newtonian relaxation with corrected road traffic emissions and stratospheric aerosol optical properties For further studies based on simulations of the ESCiMo project and on the EMAC model please also refer to: https://www.atmos-chem-phys.net/special_issue812.html https://gmd.copernicus.org/articles/special_issue10_22.html https://www.atmos-chem-phys.net/special_issue22.html http://www.pa.op.dlr.de/~PatrickJoeckel/ESCiMo/publications/escimo_publications.html
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  • 43
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    Publication Date: 2020-11-17
    Description: Simulation with most recent version of MADE3 into the atmospheric chemistry general circulation model EMAC, including a detailed evaluation of a ten-year aerosol simulation with MADE3 as part of EMAC. Model details and setup specification are described in Kaiser et al. (Geosci. Model Dev., 2018). We compare simulation output to station network measurements of near-surface aerosol component mass concentrations, to airborne measurements of aerosol mass mixing ratio and number concentration vertical profiles, to ground-based and airborne measurements of particle size distributions, and to station network and satellite measurements of aerosol optical depth. Furthermore, we describe and apply a new evaluation method, which allows a comparison of model output to size-resolved electron microscopy measurements of particle composition. Although there are indications that fine mode particle deposition may be underestimated by the model, we obtained satisfactory agreement with the observations. Remaining deviations are of similar size as those identified in other global aerosol model studies. Thus, MADE3 can be considered ready for application within EMAC. Due to its detailed representation of aerosol mixing state, it is especially useful for simulating wet and dry removal of aerosol particles, aerosol-induced formation of cloud droplets and ice crystals as well as aerosol-radiation interactions. Besides studies on these fundamental processes, we also plan to use MADE3 for a reassessment of the climate effects of anthropogenic aerosol perturbations. Please cite Kaiser et al. (Geosci. Model Dev., 2018) if using the data.
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  • 44
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    WDCC
    Publication Date: 2020-11-17
    Description: Simulation with most recent version of MADE3 into the atmospheric chemistry general circulation model EMAC, including a detailed evaluation of a ten-year aerosol simulation with MADE3 as part of EMAC. Model details and setup specification are described in Kaiser et al. (Geosci. Model Dev., 2018). We compare simulation output to station network measurements of near-surface aerosol component mass concentrations, to airborne measurements of aerosol mass mixing ratio and number concentration vertical profiles, to ground-based and airborne measurements of particle size distributions, and to station network and satellite measurements of aerosol optical depth. Furthermore, we describe and apply a new evaluation method, which allows a comparison of model output to size-resolved electron microscopy measurements of particle composition. Although there are indications that fine mode particle deposition may be underestimated by the model, we obtained satisfactory agreement with the observations. Remaining deviations are of similar size as those identified in other global aerosol model studies. Thus, MADE3 can be considered ready for application within EMAC. Due to its detailed representation of aerosol mixing state, it is especially useful for simulating wet and dry removal of aerosol particles, aerosol-induced formation of cloud droplets and ice crystals as well as aerosol-radiation interactions. Besides studies on these fundamental processes, we also plan to use MADE3 for a reassessment of the climate effects of anthropogenic aerosol perturbations. Please cite Kaiser et al. (Geosci. Model Dev., 2018) if using the data.
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  • 45
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    Publication Date: 2020-11-24
    Description: This is the first version (v1.0) of the hydrographic part of the "Baltic and North Sea Climatology (BNSC)". The parameters provided here are water temperature and salinity on 105 depth levels. The data product comprises the time period from 1873-2015 and is based on more than one million observational profiles, which were obtained from several different data sources in the region of the Baltic, the North Sea and adjacent areas of the North Atlantic Ocean (15°W-30°E, 47°N-66°N). Intersection of observational data from different data sources is avoided and the in situ data were objected to an elaborate automatic quality control to identify erroneous observations that would bias the data product. Additionally, a correction of the temporal sampling error was applied to minimize the impact of the temporal distribution of the observations on the created temporal mean fields. The data product consists of gridded mean fields of water temperature and salinity. The spatial resolution is 0.25° in meridional and zonal direction. The depth levels are irregularly distributed: for the depth interval from 0 to 50m the distance between the single depth levels is 5m. Below 50m, the distance increases progressively by 1m to the last depth level of 4985m. The dimensions of the data product are 180*76*105 (longitude, latitude, depth). The BNSC climatology consists, on the one hand, of time series of monthly and annual mean values of the hydrographic parameters as fields of box averages. Grid boxes that show no observations are left empty. Based on these time series, decadal monthly mean fields are created for the decades 1956-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015 as another part of the data product. Again, gaps remain in observational data-void regions. The third part of the data product results from above mentioned decadal mean fields: horizontally interpolated fields by application of the method of objective analysis. Consequently, this subset does not contain gaps. Available parameters: box averages: monthly and annual mean, resp. standard deviation, number of observations decadal box averages: decadal monthly mean, resp. standard deviation, mean year, standard deviation to mean year, number of years decadal interpolated mean: interpolated monthly mean, absolute median deviation, number of bins, first guess, relative interpolation error, mean year, mean distance The products are publicly available at the ICDC portal ( https://icdc.cen.uni-hamburg.de/1/daten/ocean/bnsc/)
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  • 46
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    Publication Date: 2020-12-03
    Description: This is the Baltic and North Sea Climatology (BNSC) for the Baltic Sea and the North Sea in the range 47 ° N to 66 ° N and 15 ° W to 30 ° E. It is the follow-up project to the KNSC climatology. The climatology was first made available to the public in March 2018 by ICDC and is published here in a slightly revised version 2. It contains the monthly averages of mean air pressure at sea level, and air temperature, and dew point temperature at 2 meter height. It is available on a 1 ° x 1 ° grid for the period from 1950 to 2015. For the calculation of the mean values, all available quality-controlled data of the DWD (German Meteorological Service) of ship observations and buoy measurements were taken into account during this period. Additional dew point values were calculated from relative humidity and air temperature if available. Climatologies were calculated for the WMO standard periods 1951-1980, 1961-1990, 1971-2000 and 1981-2010 (monthly mean values). As a prerequisite for the calculation of the 30-year-climatology, at least 25 out of 30 (five-sixths) valid monthly means had to be present in the respective grid box. For the long-term climatology from 1950 to 2015, at least four-fifths valid monthly means had to be available. Two methods were used (in combination) to calculate the monthly averages, to account for the small number of measurements per grid box and their uneven spatial and temporal distribution: 1. For parameters with a detectable annual cycle in the data (air temperature, dew point temperature), a 2nd order polynomial was fitted to the data to reduce the variation within a month and reduce the uncertainty of the calculated averages. In addition, for the mean value of air temperature, the daily temperature cycle was removed from the data. In the case of air pressure, which has no annual cycle, in version 2 per month and grid box no data gaps longer than 14 days were allowed for the calculation of a monthly mean and standard deviation. This method differs from KNSC and BNSC version 1, where mean and standard deviation were calculated from 6-day windows means. 2. If the number of observations fell below a certain threshold, which was 20 observations per grid box and month for the air temperature as well as for the dew point temperature, and 500 per box and month for the air pressure, data from the adjacent boxes was used for the calculation. The neighbouring boxes were used in two steps (the nearest 8 boxes, and if the number was still below the threshold, the next sourrounding 16 boxes) to calculate the mean value of the center box. Thus, the spatial resolution of the parameters is reduced at certain points and, instead of 1 ° x 1 °, if neighboring values are taken into account, data from an area of 5 ° x 5 ° can also be considered, which are then averaged into a grid box value. This was especially used for air pressure, where the 24 values of the neighboring boxes were included in the averaging for most grid boxes. The mean value, the number of measurements, the standard deviation and the number of grid boxes used to calculate the mean values are available as parameters in the products. The calculated monthly and annual means were allocated to the centers of the grid boxes: Latitudes: 47.5, 48.5, ... Longitudes: -14.5, -13.5, … In order to remove any existing values over land, a land-sea mask was used, which is also provided in 1 ° x 1 ° resolution. In this version 2 of the BNSC, a slightly different database was used, than for the KNSC, which resulted in small changes (less than 1 K) in the means and standard deviations of the 2-meter air temperature and dew point temperature. The changes in mean sea level pressure values and the associated standard deviations are in the range of a few hPa, compared to the KNSC. The parameter names and units have been adjusted to meet the CF 1.6 standard.
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  • 47
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    Publication Date: 2019-04-22
    Description: Please note that data representing a warmer future climate are flawed by the use of incorrect sea ice coverage data. All data of the 1.5°C and the 2.0°C experiment of this CERA experiment have been replaced by and all data of the current decade and the 57-year-long AMIP experiment have been copied to http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=HAPPI-global-ECHAM6.3_v2. For detailed information refer to that experiment. Global HAPPI-MIP protocol data based on the ECHAM6.3 AGCM developed by the MPI-M (Max Planck Institute for Meteorology). This CERA experiment includes data of five AMIP simulations of the period 1959-2015 and 100 AMIP simulations of 2006-2015. In addition it includes data of 100 AMIP-like simulations of 2106-2115 representing a climate warmer by 1.5°C than under pre-industrial conditions (1861-1880) and 100 AMIP-like simulations of 2106-2115 representing a climate warmer by 2.0°C than under pre-industrial conditions.
    Type: experiment
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  • 48
    Publication Date: 2020-04-23
    Description: COSMO-CLM simulation for Bohai, Yellow and East China Sea: System Analysis and Modelling Group at the Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research (referred to hereinafter as data producer) has computed the regional climate simulation. By making these data available, the data producer wishes to stimulate and support climate change and impact research projects. The data producer is aiming to make the results produced on the basis of these data available on its website and in publications as part of an international overview of regional climate change research. All interested users will have access to the simulation data being calculated with high resolution both in space and time. The data were computed at the German Climate Computing Centre (DKRZ) in Hamburg using the regional climate model COSMO-CLM. The simulations were carried out with support by the China Scholarship Council, the Helmholtz Climate Initiative REKLIM and the CLM community.
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  • 49
    Publication Date: 2020-04-23
    Description: Note: please use https://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=EKF400_v1.1 data instead of EKF400_v1 (details see Quality information EKF400_v1.1)! EKF400 is a monthly resolved paleo-reanalysis covering the period 1603 to 2003. Early instrumental temperature and surface pressure observations, temperature indices derived from historical documents and temperature and moisture sensitive tree-ring measurements were assimilated into an atmospheric general circulation model ensemble using a Kalman filtering technique. This data set combines the advantage of traditional reconstruction methods of being as close as possible to observations with the advantage of climate models of being physically consistent and having 3-dimensional information about the state of the atmosphere for various variables and at all points in time.
    Type: experiment
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  • 50
    Publication Date: 2020-04-23
    Description: The concentrations and deposition of atmospheric constituents such as air pollutants were modeled with the Community Multiscale Air Quality (CMAQ) Model system for the year 2008. A focus was on sea salt emissions, atmospheric sea salt concentrations and the interaction between sea salt particles and atmospheric nitrogen compounds. For this purpose, two model runs with different realistic sea salt emission parameterizations were performed and are provided here. The model run CMAQ_CD24_seasalt_base uses the default sea salt emission parameterization of CMAQ denoted as GO03. The model run CMAQ_CD24_seasalt_ov14 uses an alternative sea salt emission parameterization denoted as OV14. Please refer to the connected references for information on the two sea salt emission parameterizations and their implementation. The dataset also contains meteorological input parameters in order to allow the user to perform unit conversions for some model variables. Additionally, the land-sea mask and land fraction data per model grid cell are provided. The projection is a Lambert Conformal Conic projection. The parameters are given in the netCDF files.
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  • 51
    Publication Date: 2020-04-23
    Description: This experiment (2006-2100) uses 'CMIP5 HadGEM2-ES r1i1p1 rcp45' forcing data for downscaling to 60km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'rcp45' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 4.1 rcp45 (4.1 RCP4.5) - future projection (2006-2300) forced by RCP4.5. Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with HadGEM forcing refer to a calendar with 360 days. The 60 km resolution of this experiment is an intermediate step to the 12km downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 52
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    Publication Date: 2020-04-23
    Description: This data of the project CORDEX includes CORDEX experiments for the domain Africa (AFR-44) based on UQAM's CRCM5 model. Each file contains a single variable in the format NetCDF-4 compressed with CF standard names (CF-1.4). The data are provided on the model computational (native) grid. Information on additional project naming conventions is specified in the project description.
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  • 53
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    WDCC
    Publication Date: 2020-04-23
    Description: This experiment uses the data from the WRF60_eraint_ctrl experiment as forcing data for downscaling to 12km resolution by the regional model, WRFV3.5.1 for the region of West Africa. The 'control'-run is a reanalysis of observed data similar to an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. The 12 km resolution of this experiment is the second step of the two step downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 54
    Publication Date: 2020-04-23
    Description: This experiment (2006-2100) uses the data from the WRF60_mpiesm_rcp45 experiment as forcing data for downscaling to 12km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'rcp45' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 4.1 rcp45 (4.1 RCP4.5) - future projection (2006-2300) forced by RCP4.5. Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with MPIESM forcing refer to a Gregorian calendar. The 12 km resolution of this experiment is the second step of the two step downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 55
    Publication Date: 2020-04-23
    Description: This experiment (2006-2100) uses the data from the WRF60_gfdlesm_rcp45 experiment as forcing data for downscaling to 12 km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'rcp45' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 4.1 rcp45 (4.1 RCP4.5) - future projection (2006-2300) forced by RCP4.5. Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with GFDL forcing refer to a calendar with 365 days (noleap). The 12 km resolution of this experiment is the second step of the two step downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 56
    Publication Date: 2020-04-23
    Description: The eVolv2k database includes estimates of the magnitudes and approximate source latitudes of major volcanic stratospheric sulphur injection (VSSI) events from 500 BCE to 1900 CE. The VSSI estimates incorporate recent improvements to the ice core records in terms of synchronization and dating, refinements to the methods used to estimate VSSI from ice core records, and includes first estimates of the random uncertainties in VSSI values. Ice core-derived volcanic sulfate deposition composites for Antarctica (Sigl et al., 2014) and Greenland (Sigl et al., 2015, Zielinski et al., 1995) are scaled to volcanic stratospheric sulfur injection based on a method similar to that of Gao et al. (2007). More details to be published in a forthcoming article (Toohey and Sigl, in prep). Compared to version 1, this version (1) contains estimates of the random error in the VSSI estimates, (2) includes a clarification regarding the format of years in the BCE period by including both years BCE/CE and according to the ISO 8601 standard (which includes a year 0), and (3) includes some minor modifications to the VSSI values. In addition, a reconstruction of stratospheric aerosol optical depth (AOD) using the VSSI estimates and the EVA v1 volcanic forcing generator (Toohey et al., 2016) is provided. Complete optical properties (extinction, single scattering albedo, scattering asymmetry factor) as a function of height, latitude and time can be produced using the eVolv2k VSSI database and the EVA forcing generator. Gao, C., Oman, L., Robock, A. and Stenchikov, G. L.: Atmospheric volcanic loading derived from bipolar ice cores: Accounting for the spatial distribution of volcanic deposition, J. Geophys. Res., 112(D9), doi:10.1029/2006JD007461, 2007. Sigl, M., Winstrup, M., McConnell, J. R., Welten, K. C., Plunkett, G., Ludlow, F., Büntgen, U., Caffee, M., Chellman, N., Dahl-Jensen, D., Fischer, H., Kipfstuhl, S., Kostick, C., Maselli, O. J., Mekhaldi, F., Mulvaney, R., Muscheler, R., Pasteris, D. R., Pilcher, J. R., Salzer, M., Schüpbach, S., Steffensen, J. P., Vinther, B. M. and Woodruff, T. E.: Timing and climate forcing of volcanic eruptions for the past 2,500 years, Nature, 523, 543¿549, doi:10.1038/nature14565, 2015. Sigl, M., McConnell, J. R., Toohey, M., Curran, M., Das, S. B., Edwards, R., Isaksson, E., Kawamura, K., Kipfstuhl, S., Krüger, K., Layman, L., Maselli, O. J., Motizuki, Y., Motoyama, H., Pasteris, D. R. and Severi, M.: Insights from Antarctica on volcanic forcing during the Common Era, Nat. Clim. Chang., 4, 693-697, doi:10.1038/nclimate2293, 2014. Toohey, M. and Sigl, M.: Volcanic stratospheric sulphur injections and aerosol optical depth from 500 BCE to 1900 CE, in preparation. Toohey, M., Stevens, B., Schmidt, H. and Timmreck, C.: Easy Volcanic Aerosol (EVA v1.0): an idealized forcing generator for climate simulations, Geosci. Model Dev., 9(11), 4049–4070, doi:10.5194/GMD-9-4049-2016, 2016. Zielinski, G. A.: Stratospheric loading and optical depth estimates of explosive volcanism over the last 2100 years derived from the Greenland Ice Sheet Project 2 ice core, J. Geophys. Res., 100(D10), 20937–20955, doi:10.1029/95JD01751, 1995.
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  • 57
    Publication Date: 2020-04-23
    Description: The WOCE/ARGO Global Hydrographic Climatology (WAGHC) is concieved as the update of the previous WOCE Global Hydrographic Climatology (WGHC) (Gouretski and Koltermann, 2004). The following improvements have been made compared to the WGHC: 2) finer spatial resolution (0.25 degrees Lat/Lon compared to 0.5 degrees for WGHC); 3) finer vertical resolution (65 compared to 45 WGHC standard levels); 4) monthly temporal resolution compared to the all-data-mean WGHC parameters; 5) narrower overall time period; 6) calculation of the mean year corresponding to the optimally interpolated temperature and salinity values; 7) depth of the upper mixed layer. Similar to the WGHC the optimal spatial interpolation is performed on the local isopycnal surfaces. This approach diminishes the production of the artificial water masses. In addition to the isopycnally interpolated parameters parameter values interpolated on the isobaric levels are also provided. The monthly gridded vertical profiles extend to the depth of 1898 m, below only annual mean parameter values are available. Additionally, there is a dataset and a map available providing indexes for selected regions of the world ocean. Finally, the comparison with the last update of the NOAA World Ocean Atlas (Locarnini et al, 2013) was done.
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  • 58
    Publication Date: 2020-04-23
    Description: This experiment uses 'CMIP5 GFDL r1i1p1 historical' forcing data for downscaling to 60km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'historical' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 3.2 historical (3.2 Historical) - Version 1: Simulation of recent past (1850 to 2005). Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with GFDL forcing refer to a calendar with 365 days (noleap). The 60 km resolution of this experiment is an intermediate step to the 12km downscaling WRF experiment.
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  • 59
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    Publication Date: 2020-04-23
    Description: High RESolution Atmospheric Forcing Fields (HiResAFF) consist of key meteorological variables on daily scale which are typically used to drive ocean or ecosystem models. The fields are reconstructed through non-linear statistical upscaling using the analog-method (Schenk and Zorita, 2012). The method resamples atmospheric fields from a regional climate model (RCAO/RCA3) in time based on the best pattern similarity in the predictor space of homogenous historical station data since 1850. The dataset provides physically consistent homogeneous atmospheric fields suitable to derive long-term simulations and statistical analysis since 1850 over the North Sea and Baltic Sea region of Europe. The analog-method and reconstruction skill is described in Schenk and Zorita (2012) and the extended dataset to 1850 in Schenk (2015). The research leading to these results has received funding from the European Union Seventh Framework Programme (FP/2007-2013) under grant agreement no. 217246 made with the joint Baltic Sea research and development programme BONUS, and the German Federal Ministry of Education and Research (03F0492A).
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  • 60
    Publication Date: 2020-04-23
    Description: This experiment (2006-2100) uses the data from the WRF60_hadgem2_rcp45 experiment as forcing data for downscaling to 12km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'rcp45' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 4.1 rcp45 (4.1 RCP4.5) - future projection (2006-2300) forced by RCP4.5. Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with HadGEM forcing refer to a calendar with 360 days. The 12 km resolution of this experiment is the second step of the two step downscaling WRF experiment.
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    Format: NetCDF
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  • 61
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    Publication Date: 2020-04-23
    Description: purpose: The map shows the median grain size (or d50) of surface sediments in the North Sea predicted by interpolation of legacy grain size distribution data. It has been produced to aid in describing physical habitat characteristics and to supply consistent baseline data and boundary conditions for ecological and biophysical modelling. abstract: In grain size analysis, the median is the midpoint of the cumulative particles size distribution curve of a sediment sample. The median grain size is an important biophysical variable that relates to sediment stability and often can be mapped with a quantifiable correspondence to the occurrence of benthic species and assemblages. This map conveys information on the median grain size of seabed sediments in the North Sea. It has been produced with multivariate geostatistics (external drift kriging) using the percentage mud content as a trend variable. The underlying data set is a compilation of over 30,000 sediment samples from many national and European surveys conducted over a period of more than 50 years. Due to the vintage of some samples in the database, users are advised to consider the dynamic nature of the seafloor when using the data and when creating derived surrogate based habitat maps. Also, due to the diversity of sources for the pointdata, users should be aware of the differing methods by which the grain size analyses were conducted. As a consequence, map confidence is not necessarily uniform and thus areas not always comparable, even though the interpolation surface my look continuous.
    Type: dataset_group
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  • 62
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    Publication Date: 2020-04-23
    Description: abstract: In grain size analysis, the proportion of particles with a diameter of less than 63 µm is commonly referred to as the mud content of a sediment sample. The mud content is an important biophysical variable that often can be mapped with a quantifiable correspondence to organic matter, contaminants and the occurrence of benthic species and assemblages. Thismap conveys information on the percentage mud content of seabedsediments in the North Sea. It has been produced with multivariate geostatistics (external drift kriging) using water depth as a trend variable. The underlying data set is a compilation of over 30,000 sediment samples from many national and Europaen surveys conducted over a period of more than 50 years. Due to the vintage of some samples in the database, users are advised to consider the dynamic nature of the seafloor when using the data and when creating derived surrogate based habitatmaps. Also, due to the diversity of sources for the pointdata, users should be aware of the differing methods by which the grain size analyses were conducted. As a consequence, map confidence is not necessarily uniform and thus areas not always comparable, even though the interpolation surface may look continuous. purpose: The map shows the percentage mud content (silt + clay) of surface sediments in the North Sea predicted by interpolation of legacy grain size distribution data. It has been produced to aid in describing physical habitat characteristics and to supply consistent baseline data and boundary conditions for ecological and biophysical modelling.
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  • 63
    Publication Date: 2020-04-23
    Description: purpose: This map shows the total organic carbon content (TOC) of surface sediments in the North Sea. It was produced by interpolation of legacy data from more than 3000 samples collected between 1960 and 2014. The distribution of this map allows the user to visualize an important marine habitat characteristic and to exploit the dataset for ecological and biogeochemical modelling. abstract: Weight percent total organic carbon (TOC) is one of the most commonly used descriptors for marine sediments. It is used to judge primary productivity of the overlying water column and refers to the amount of organic matter preserved within sediment. TOC has a major influence on biogeochemical processes occurring in sediments, including the regulation of the behavior of the other chemical species such as metals and organic pollutants. Therefore, determination of TOC is an essential component of environmental characterization analysis.This map conveys information on the weight percent TOC of seabed sediments in the North Sea. It has been produced with multivariate geostatistics (external drift kriging) using the percentage mud content as a trend variable. The underlying data set is a compilation of over 3,000 sediment samples from many national and European surveys conducted between 1960 and 2014. Due to the vintage of some samples in the database, users are advised to consider the dynamic nature of the seafloor when using the data and when creating derived surrogate based habitat maps. Also, due to the diversity of sources for the point data, users should be aware of the differing methods by which the TOC analyses were conducted. As a consequence, map confidence is not necessarily uniform and thus areas not always comparable, even though the interpolation surface may look continuous.
    Type: dataset_group
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  • 64
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    Publication Date: 2020-04-23
    Description: The MPIC/DLR "climate" water vapor product, developed within ESA's "GOME Evolution" project, provides a consistent time series of monthly mean H2O columns from the satellite instruments GOME, SCIAMACHY, and GOME-2 (MetopA). Consistency amongst the different instruments (including cloud treatment) is substantially improved by (1) merging SCIAMACHY and GOME-2 observations to GOME pixel size, and (2) reducing the GOME-2 swath width to GOME/SCIAMACHY swath, thereby mimicking GOME-like observation conditions for all three sensors. WARNING: Version 1.0 is based on spectral analysis settings which have slightly changed during the GOME-2 timeseries, introducing a small but clear "jump" in the TCWV timeseries at the turn of the years 2012/2013. This version should not be used any more! Use version 〉2.2 instead! doi:10.1594/WDCC/GOME-EVL_water_vapor_clim_v2.2
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  • 65
    Publication Date: 2020-04-23
    Description: Regional simulation with the fully coupled physical-biogeochemical model ECOSMO II. Model details and setup specifications are described in Daewel and Schrum (2013). The basis for ECOSMO II is a baroclinic hydrodynamic coupled sea-ice model (Schrum and Backhaus, 1999), which is coupled to a lower trophic level ecosystem NPZD-model. The experiment contains hindcast simulations for the coupled North Sea and Baltic Sea ecosystem for the period 1948-2008 forced by the NCEP/NCAR reanalysis (Kalnay et al., 1996). The spatial resolution is 6’ x 10’ in the horizontal and 20 layers in the vertical. The data-set contains daily averaged data. Data for biological, physical and ice variables are stored in separate files. The 3d model grid is defined in ECOSMOII_NCEP.1948-2008.dm.griddef.000000.nc (https://cera-www.dkrz.de/WDCC/ui/cerasearch/entry?acronym=ECOSMOII_NCEP_griddef ), which contains information on vertical layer thickness in each model grid-box. The output format is netCDF.
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  • 66
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    Publication Date: 2020-04-23
    Description: This experiment uses 'CMIP5 ECMWF-ERAINT reanalysis data' as forcing data for downscaling to 60km resolution by the regional model WRFV3.5.1 for the region of West Africa. The 'control'-run is a reanalysis of observed data similar to an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. The 60 km resolution of this experiment is an intermediate step to the 12km downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 67
    Publication Date: 2020-04-23
    Description: This experiment (2006-2100) uses 'CMIP5 GFDL r1i1p1 rcp45' forcing data for downscaling to 60km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'rcp45' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 4.1 rcp45 (4.1 RCP4.5) - future projection (2006-2300) forced by RCP4.5. Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with GFDL forcing refer to a calendar with 365 days (noleap). The 60 km resolution of this experiment is an intermediate step to the 12km downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 68
    Publication Date: 2020-04-23
    Description: This experiment uses 'CMIP5 MPIESM r1i1p1 historical' forcing data for downscaling to 60km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'historical' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 3.2 historical (3.2 Historical) - Version 1: Simulation of recent past (1850 to 2005). Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with MPIESM forcing refer to a Gregorian calendar. The 60 km resolution of this experiment is an intermediate step to the 12km downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 69
    Publication Date: 2020-04-23
    Description: This experiment uses 'CMIP5 HadGEM2-ES r1i1p1 historical' forcing data for downscaling to 60km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'historical' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 3.2 historical (3.2 Historical) - Version 1: Simulation of recent past (1850 to 2005). Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with HadGEM forcing refer to a calendar with 360 days. The 60 km resolution of this experiment is an intermediate step to the 12km downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 70
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    WDCC
    Publication Date: 2020-04-23
    Description: Note: Do not use use this version any more, use version 1.1 instead! https://doi.org/10.1594/WDCC/NSBClim_v1.1 This is the first version of a biogeochemical climatology in the wider North Sea region. It is an expansion of the NOWESP data base („North Western European Shelf Programme“; Laane et al., 1996) and the KLIWAS North Sea Climatology of Hydrographic Data (Bersch et al., 2013). The data collection comprises observations of the parameters ammonium, chlorophyll-a, nitrate(+nitrite), phosphate, oxygen and silicate for the time period 1960-2014. If accompanying the biogeochemical parameters, temperature and salinity were also included in the collection.
    Type: experiment
    Format: NetCDF
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  • 71
    Publication Date: 2020-04-23
    Description: The "climate" water vapor product developed within ESA's "GOME-Evolution" project provides a consistent time series of monthly mean global maps of total column water vapor derived from the satellite instruments GOME, SCIAMACHY, and GOME-2 (Metop-A). Consistency amongst the different instruments (including cloud treatment) is substantially improved by (1) merging SCIAMACHY and GOME-2 observations to GOME pixel size, and (2) reducing the GOME-2 swath width to GOME/SCIAMACHY swath, thereby mimicking GOME-like observation conditions for all three sensors. Use version 〉2.2 instead! doi:10.1594/WDCC/GOME-EVL_water_vapor_clim_v2.2
    Type: experiment
    Format: NetCDF
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  • 72
    Publication Date: 2020-04-23
    Description: OceanRAIN version 1.0, OceanRAIN-M - Number Concentration Particle Size Distribution and Precipitation Microphysics, 37 along-track parameters plus 128 size bins for 8 ships, 692.000 precipitation minutes in total, temporally discontinuous data for each ship, 1-minute-resolution
    Type: experiment
    Format: ascii
    Format: NetCDF
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  • 73
    Publication Date: 2020-04-23
    Description: OceanRAIN version 1.0, OceanRAIN-R - ODM470 Raw number count Particle Size Distribution and Precipitation Microphysics, 37 along-track parameters plus 128 size bins for 8 ships, 692.000 precipitation minutes in total, temporally discontinuous data for each ship, 1-minute-resolution
    Type: experiment
    Format: ascii
    Format: NetCDF
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  • 74
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    WDCC
    Publication Date: 2020-04-23
    Description: These data are made available as part of paper: S. J. Gonzalez-Roji, J. Saenz, G. Ibarra-Berastegi, J. Diaz de Argandona (2018) Moisture balance over the Iberian Peninsula according to a regional climate model, Journal of Geophysical Research 123(2):708-729. The dataset holds selected postprocessed files that allow to reproduce all the results in the paper. An analysis of the atmospheric branch of the hydrological cycle by means of a 15 km resolution numerical integration performed using Weather Research and Forecasting (WRF) nested in ERA Interim is presented. Two WRF experiments covering the period 2010–2014 were prepared. The first one (N) was configured as in standard numerical downscaling experiments. The second one (D), with the same parameterizations, included a step of 3DVAR data assimilation every 6 h. Experiment D: -windowed-D-AI: Analysis increments (T2, Q2), 2010-2014 for the D experiment -windowed-wavacurip4paper-D: Netcdf files corresponding to experiment D (using 3DVAR assimilation) and years 2010-2014 holding 3-hourly outputs from the run after selecting the window covering the Iberian Peninsula. Experiment N: -windowed-wavacurip4paper-N: Netcdf files corresponding to experiment N (no data assimilation) and years 2010-2014 holding 3-hourly outputs from the run after selecting the window covering the Iberian Peninsula
    Type: experiment
    Format: NetCDF
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  • 75
    Publication Date: 2020-04-23
    Description: This experiment (2006-2100) uses 'CMIP5 MPIESM r1i1p1 rcp45' forcing data for downscaling to 60km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'rcp45' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 4.1 rcp45 (4.1 RCP4.5) - future projection (2006-2300) forced by RCP4.5. Experiment design: https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with MPIESM forcing refer to a Gregorian calendar. The 60 km resolution of this experiment is an intermediate step to the 12km downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 76
    Publication Date: 2020-04-23
    Description: OceanRAIN version 1.0, OceanRAIN-W - Water cycle components, 73 along-track parameters for 8 ships, 6.83 million minutes in total, temporally continuous data for each ship, 1-minute-resolution
    Type: experiment
    Format: ascii
    Format: NetCDF
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  • 77
    Publication Date: 2020-04-23
    Description: This experiment uses the data from the WRF60_gfdlesm_historical experiment as forcing data for downscaling to 12 km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'historical' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 3.2 historical (3.2 Historical) - Version 1: Simulation of recent past (1850 to 2005). Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with GFDL forcing refer to a calendar with 365 days (noleap). The 12 km resolution of this experiment is the second step of the two step downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 78
    Publication Date: 2020-04-23
    Description: This experiment uses the data from the WRF60_hadgem2_historical experiment as forcing data for downscaling to 12km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'historical' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 3.2 historical (3.2 Historical) - Version 1: Simulation of recent past (1850 to 2005). Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with HadGEM forcing refer to a calendar with 360 days. The 12 km resolution of this experiment is the second step of the two step downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 79
    Publication Date: 2020-04-23
    Description: This experiment uses the data from the WRF60_mpiesm_historical experiment as forcing data for downscaling to 12km resolution by the regional model WRFV3.5.1 for the region of West Africa. 'historical' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). 3.2 historical (3.2 Historical) - Version 1: Simulation of recent past (1850 to 2005). Experiment design:https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=Taylor_CMIP5_design.pdf . This experiment is divided into several time slices of 11 years. The first year of each time slice is used as a spin-up phase and should not be used in the analysis. All experiments with MPIESM forcing refer to a Gregorian calendar. The 12 km resolution of this experiment is the second step of the two step downscaling WRF experiment.
    Type: experiment
    Format: NetCDF
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  • 80
    Publication Date: 2020-04-23
    Description: The data are results from radiative transfer simulations from 390 to 1020 nm in 1nm resolution. They can be convoluted to any ocean colour instrumental spectral response function and therefore represent satellite based aircraft- or groundbased measurements of the remote sensing reflectance. The data is simulated with the radiative transfer code MOMO (Matrix Operator Model), which simulates the full radiative transfer in atmosphere and ocean. The code is hosted at the institute of space sciences at Freie Universität Berlin and is not pubicly available. In addition to molecular Rayleigh scattering one maritime aerosol scatterer is considered. The data is available for 9 solar, 9 viewing zenith and 25 azimuth angles. The remote sensing reflectance is simulated in dependency of IOPs representing pure water with different salinities and 5 water constituents (Chlorophyll-a-pigment, Detritus, Yellow substance, a ’big’ and a ’small’ scatterer) in a global range of concentrations. The IOPs are varied independently. The grid points for each IOP where choosen in order to reproduce the full relation between this particular IOP and the resulting remote sensing reflectance.
    Type: experiment
    Format: NetCDF
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  • 81
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    WDCC
    Publication Date: 2020-04-23
    Description: This is Version 1.1 of a biogeochemical climatology in the wider North Sea region. It is an expansion of the NOWESP data base („North Western European Shelf Programme“; Laane et al., 1996) and the KLIWAS North Sea Climatology of Hydrographic Data (Bersch et al., 2013). The data collection comprises observations of the parameters ammonium, chlorophyll-a, nitrate(+nitrite), phosphate, oxygen and silicate for the time period 1960-2014. If accompanying the biogeochemical parameters, temperature and salinity were also included in the collection.
    Type: experiment
    Format: NetCDF
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  • 82
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    WDCC
    Publication Date: 2020-06-11
    Description: This is an atmospheric hourly hindcast for the German Bight using COSMO-CLM version 5.00_clm2 from 1948-August 2015. The model uses a rotated grid with 250 x 180 grid points and a grid point distance of 0.025 degrees, the rotated North pole is located at 172.97 W, 34.925 N. The forcing is coastDat2 doi:10.1594/WDCC/coastDat-2_COSMO-CLM . In rotated coordinates the model area extends from 2.25 W to 2.25 E, 3.125 S to 3.125 N, in geographical coordinates this corresponds to about 1.3 E to 12.8 E, 52.7 N to 57.3 N.
    Type: experiment
    Format: NetCDF
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  • 83
    Publication Date: 2020-04-23
    Description: 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.
    Type: experiment
    Format: GeoTIFF
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  • 84
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    WDCC
    Publication Date: 2020-04-23
    Description: This is a North Sea wave hindcast for the period 1949-2014. The simulation has been performed with the wave model WAM Version 4.5.4. The model domain covers the area from 51N to 59N and 4.75W to 13E, with a spatial resolution of 0.05 degree latitude x 0.075 degree longitude (approx. 3 by 3 nautical miles). Integrated parameter derived from 2D spectra are available every hour; the wave spectra themselves are available with a 3-hour time step. Atmospheric forcing was obtained from an atmospheric hindcast with COSMO-CLM (doi:10.1594/WDCC/coastDat-2_COSMO-CLM) driven by the NCEP/NCAR Reanalysis 1 data set. Lateral boundary conditions were obtained from corresponding coarse grid hindcast covering most of the Northeast Atlantic driven by the same atmospheric forcing.
    Type: experiment
    Format: NetCDF
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  • 85
    Publication Date: 2020-04-23
    Description: 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.
    Type: experiment
    Format: zip-file
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  • 86
    Publication Date: 2020-04-23
    Description: This dataset contains ice core-based estimates of volcanic stratospheric sulfur injections covering the years 500 BCE to 1900 CE. Ice core-derived volcanic sulfate deposition composites for Antarctica (Sigl et al., 2014) and Greenland (Sigl et al., 2015) are scaled to volcanic stratospheric sulfur injection based on a method similar to that of Gao et al., (2007). Sigl, M., Winstrup, M., McConnell, J. R., Welten, K. C., Plunkett, G., Ludlow, F., Büntgen, U., Caffee, M., Chellman, N., Dahl-Jensen, D., Fischer, H., Kipfstuhl, S., Kostick, C., Maselli, O. J., Mekhaldi, F., Mulvaney, R., Muscheler, R., Pasteris, D. R., Pilcher, J. R., Salzer, M., Schüpbach, S., Steffensen, J. P., Vinther, B. M. and Woodruff, T. E.: Timing and climate forcing of volcanic eruptions for the past 2,500 years, Nature, 523, 543-549, doi:10.1038/nature14565, 2015. Sigl, M., McConnell, J. R., Toohey, M., Curran, M., Das, S. B., Edwards, R., Isaksson, E., Kawamura, K., Kipfstuhl, S., Krüger, K., Layman, L., Maselli, O. J., Motizuki, Y., Motoyama, H., Pasteris, D. R. and Severi, M.: Insights from Antarctica on volcanic forcing during the Common Era, Nat. Clim. Chang., 4, 693-697, doi:10.1038/nclimate2293, 2014. Gao, C., Oman, L., Robock, A. and Stenchikov, G. L.: Atmospheric volcanic loading derived from bipolar ice cores: Accounting for the spatial distribution of volcanic deposition, J. Geophys. Res., 112(D9), doi:10.1029/2006JD007461, 2007.
    Type: experiment
    Format: NetCDF
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  • 87
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    WDCC
    Publication Date: 2019-04-22
    Description: The experiment includes the latest CMIP5 data of CSIRO for January 2015. The data is a newer version of the IPCC DDC AR5 data of CSIRO. '1pctCo2' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 6.1 1pctCo2 (6.1 1 percent per year CO2) - Version 1: Idealized 1% per year increase in atmospheric CO2 to quadrupling. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax (https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc.
    Type: dataset_group
    Format: NetCDF
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  • 88
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    WDCC
    Publication Date: 2019-04-22
    Description: The experiment includes the latest CMIP5 data of CSIRO for January 2015. The data is a newer version of the IPCC DDC AR5 data of CSIRO. 'sstClimSulfate' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 6.4b sstClimSulfate (6.4b sulfate aerosol forcing) - Version 1: AMIP-style experiment with control run climatological SSTs and sea ice (as in expt. 6.2a) but with aerosols consistent with conditions in year 2000 of the historical run (expt. 3.2) Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax (https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc.
    Type: dataset_group
    Format: NetCDF
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  • 89
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    WDCC
    Publication Date: 2019-04-22
    Description: The experiment includes the latest CMIP5 data of CSIRO for January 2015. The data is a newer version of the IPCC DDC AR5 data of CSIRO. 'amip' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 3.3 amip (3.3 AMIP) - Version 1: AMIP (1979 - at least 2008). Impose SSTs and sea ice from observations but with other conditions as in experiment 3.2 historical. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax (https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc.
    Type: dataset_group
    Format: NetCDF
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  • 90
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    WDCC
    Publication Date: 2019-04-22
    Description: The experiment includes the latest CMIP5 data of CSIRO for January 2015. The data is a newer version of the IPCC DDC AR5 data of CSIRO. piControl is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 ( https://pcmdi.llnl.gov/mips/cmip5 ). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 3.1 piControl (3.1 Pre-Industrial Control) - Version 1: Pre-Industrial coupled atmosphere/ocean control run. Imposes non-evolving pre-industrial conditions. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax ( https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf ) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc .
    Type: dataset_group
    Format: NetCDF
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  • 91
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    WDCC
    Publication Date: 2019-04-22
    Description: The experiment includes the latest CMIP5 data of CSIRO for January 2015. The data is a newer version of the IPCC DDC AR5 data of CSIRO. 'historicalNat' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 7.1 historicalNat (7.1 natural-only historical simulation) - Version 1: Historical simulation but with natural forcing only. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax (https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc.
    Type: dataset_group
    Format: NetCDF
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  • 92
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    WDCC
    Publication Date: 2019-04-22
    Description: The experiment includes the latest CMIP5 data of CSIRO for January 2015. The data is a newer version of the IPCC DDC AR5 data of CSIRO. '1pctCo2' is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 (https://pcmdi.llnl.gov/mips/cmip5). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 6.1 1pctCo2 (6.1 1 percent per year CO2) - Version 1: Idealized 1% per year increase in atmospheric CO2 to quadrupling. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax (https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc.
    Type: dataset_group
    Format: NetCDF
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