ALBERT

Description: This is an atmospheric hourly hindcast for the German Bight using COSMO-CLM version 5.00_clm2 from 1948-August 2015 (http://www.cosmo-model.org/content/model/documentation/core/default.htm). 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.

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.

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.

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.

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.

Description: This is a hydrodynamic hindcast for the Baltic Sea over the period 1958-2011. The simulation has been performed with the hydrodynamic model TRIM-NP V2.1 in barotropic 2D mode. Water level and current component fields are stored hourly. The model is set up on an equidistant Cartesian grid cascade with the center near Helgoland (7.88 E, 54.18 N) for the coarsest grid (12.8km resolution) (http://dx.doi.org/doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d). Further model results from three nested grids (6.4km,3.2km, 1.6km resolution) for the Baltic Sea are hourly available for the period 1958-2011.

Description: Hindcast simulation has been performed for reconstruction of meso-scale weather systems, especially of intense storms by using the global atmospheric model ECHAM6 in its version 6.1.00 (CMIP5), the spectral nudging technique and NCEP reanalysis as forcing data. Horizonatal resolution: (768x384) gridpoints (T255L95), vertical resolution: 95 levels. Time period: 1948 - 2015 april. The output from the model run: /work/gg0301/g260070/ECHAM6/echam-6.1.00/experiments/echam6_t255l95_sn_ncep1/scripts on the HLRE-2 Blizzard and the Original-Outputs of the 8 ECHAM6-streams were named and differed by their suffixes: echam6_t255l95_sn_ncep1_199212.01_co2 echam6_t255l95_sn_ncep1_199212.01_echam echam6_t255l95_sn_ncep1_199212.01_jsbach echam6_t255l95_sn_ncep1_199212.01_land echam6_t255l95_sn_ncep1_199212.01_nudg echam6_t255l95_sn_ncep1_199212.01_surf echam6_t255l95_sn_ncep1_199212.01_veg echam6_t255l95_sn_ncep1_199212.01_vphysc

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. 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.

Description: Reflectances measured in the visible frequency range at three channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Earth Observation Satellite (EOS) TERRA were used to derive the melt pond fraction on Arctic sea ice using an artificial neural network. This analysis was done on reflectances gridded onto a polar-stereographic grid tangent to the Earths' surface at 70 deg N with 500 m grid resolution. The reflectances used originate from the 8-day composite reflectances provided via https://wist.echo.nasa.gov/api/ as product: "MODIS surface Reflectance 8-Day L3 Global 500m SIN Grid V005". After gridding and flagging for clouds and other disturbances the artificial neural network was applied, providing fractions of three surface classes: 1) melt ponds, 2) sea ice and snow, and 3) open water at 500 m grid resolution. This data has been interpolated onto a similar polar-stereographic grid but with 12.5 km grid resolution. The data set offered here comprises several data layers: the melt pond fraction, its standard deviation, the open water fraction, and the number of individual valid grid cells with 500 m grid resolution included in each 12.5 km grid cell. In addition, in three separate data layers melt pond fraction, its standard deviation, and the open water fraction are given with those grid cells (with 12.5 km grid resolution) flagged as invalid where less than 90 % of the native 500 m grid resolution data indicate clear sky conditions. Valid for all these layers is, that grid cells with an open water fraction larger than 85 % have been flagged as invalid as well. The data set offered here is version 02 of the melt pond data set. The main difference to version 01 is a bias correction carried out to remove a positive bias in the melt pond fraction and in the open water fraction.

Description: Simulated 2D residual velocity fields in the inner German Bight were subjected to Principal Component Analysis (PCA). Residual currents were obtained from coastDat2 barotropic 2D simulations with the hydrodynamic model TRIM-NP V2.1.22 in barotropic 2D mode on a Cartesian grid (1.6km spatial resolution) stored on an hourly basis for the years 1948 - 2012 (doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d) and later extended until August 2015. The present analysis refers to the period Jan 1958 - Aug 2015. The spatial domain considered is the region to the east of 6 degrees east and to the south of 55.6 degrees north. All grid nodes with a bathymetry of less than 10m were excluded. Residual velocities were calculated in two different ways: 1.) as 25h means, 2.) as monthly means. Both types of residual current data are available from * RESIDUAL_CURRENTS_195801_201508 The directory contains sub-directories for years and months. Daily residual currents for the 13th of September 1974, for instance, are stored in * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/MONTH_09/TRIM2D_1974_09_13_means.nc while monthly mean residual currents for September 1974 are stored in: * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/TRIM2D_1974_09_means.nc All current fields provided were interpolated from the original Cartesian model grid to a more convenient regular geographical grid (116x76 nodes). Mean residual currents are stored in: * mean_residual_currents.nc This data set contains residual velocities both on original Cartesian grid nodes and interpolated to the geographical grid. An example plot is provided: * mean_residual_currents.png For PCA, two residual velocity components from each of 12133 Cartesian grid nodes were combined into one data vector (length 2x12133), referring to 21061 daily or 692 monthly time levels. Results of two independent PCAs for either daily or monthly mean fields are stored in: * PCA_daily_residual_currents.nc * PCA_monthly_residual_currents.nc Files contain three leading Principal Components (PCs) and corresponding Emipirical Orthogonal Functions (EOFs). Again EOFs were also interpolated to a regular geographical grid. PC time series are also stored in plain ASCII format: * PCs_daily.txt * PCs_monthly.txt For monthly fields the number N of variables (N=2x12133) is much larger than the number T of time levels (T=692). Therefore, to reduce computational demands, the roles of time and space were formally interchanged. Having conducted the PCA the EOFs were then transformed back to the original spatial coordinates (cf. Section 12.2.6 in von Storch and Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press). A much larger number of time levels made even this approach prohibitive for the full set of daily data. Therefore, PCAs were performed for six sub-periods (1958-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015(Aug)) independently. EOFs obtained from these six sub-periods were then averaged to obtain EOFs representative for the whole period. Corresponding PCs were calculated by projecting daily fields onto these average EOFs. IMPORTANT: In contrast with PCA of monthly data, the PCA of daily data INVOLVES SOME APPROXIMATIONS! EOFs on the original nodes were normalized to have unit lengths. The following figures, * daily_EOF1.png * daily_EOF2.png * daily_EOF3.png show the first three EOFs obtained from daily data, assuming that corresponding PCs have the value of one standard deviation. The following two plots, * monthly_EOF1.png * monthly_EOF2.png show the leading EOFs for monthly mean data. EOF3 is omitted as it represents just a very small percentage of overall variance (1.7%).