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  • 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/)

  • 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.

  • 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.

  • 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.

  • 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.

  • 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/)

  • The assessment of climate change impacts on the North Sea and the overlying atmosphere requires reliable reference data in order to identify change and impacts against a highly variable background with time scales from hours to multi-decadal. Therefore, in the frame work of the research programme "KLIWAS - Impacts of climate change on waterways and navigation - Searching for options of adaptation" of the German Federal Ministry of Transport, Building and Urban Development (BMVBS), a new climatology was developed in a close co-operation of the Federal Maritime and Hydrographic Agency (BSH), the German Meteorological Service (DWD) and the Integrated Climate Data Center (ICDC) of the University Hamburg. All available oceanographic in-situ data for temperature and salinity have been carefully checked for quality before further processing, while the atmospheric data had already been quality controlled by the DWD. More than 13 million temperature and 12 million salinity (starting in 1890) as well as more than 19 million atmospheric data (air temperature, dew point and air pressure starting in 1950) have been processed. Monthly averages have been created on specified grids for the ocean and atmosphere. For the first time oceanographic and meteorological climatologies are provided on a coordinated grid. The climatological data set is supposed to be growing with time and new data can be implemented as they are collected. it is planned to add additional parameters in future. The climatologies will be used to analyse the temporal and spatial variability in the North Sea area and deduce long-term trends. Additional the data sets will be needed for the validation of regional climate scenarios. The products are publicly available at the ICDC portal ( http://icdc.cen.uni-hamburg.de/1/projekte/knsc.html ). A corrected version of the climatology is available. For more information see Accuracy report.

  • The assessment of climate change impacts on the North Sea and the overlying atmosphere requires reliable reference data in order to identify change and impacts against a highly variable background with time scales from hours to multi-decadal. Therefore, in the frame work of the research programme "KLIWAS - Impacts of climate change on waterways and navigation - Searching for options of adaptation" of the German Federal Ministry of Transport, Building and Urban Development (BMVBS), a new climatology was developed in a close co-operation of the Federal Maritime and Hydrographic Agency (BSH), the German Meteorological Service (DWD) and the Integrated Climate Data Center (ICDC) of the University Hamburg. All available oceanographic in-situ data for temperature and salinity have been carefully checked for quality before further processing, while the atmospheric data had already been quality controlled by the DWD. More than 13 million temperature and 12 million salinity (starting in 1890) as well as more than 19 million atmospheric data (air temperature, dew point and air pressure starting in 1950) have been processed. Monthly averages have been created on specified grids for the ocean and atmosphere. For the first time oceanographic and meteorological climatologies are provided on a coordinated grid. The climatological data set is supposed to be growing with time and new data can be implemented as they are collected. it is planned to add additional parameters in future. The climatologies will be used to analyse the temporal and spatial variability in the North Sea area and deduce long-term trends. Additional the data sets will be needed for the validation of regional climate scenarios. The products are publicly available at the ICDC portal ( http://icdc.cen.uni-hamburg.de/1/projekte/knsc.html ).

  • 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.

  • 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.