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5 results for “the Gulf of Riga”
Spatiotemporal Dataset on Moon Jellyfish (Aurelia aurita) Incidental Observations in the Gulf of Riga and Eastern Gotland Basin, Baltic Sea
<p>This data article describes the occurrences of the moon jelly <em>Aurelia aurita </em>medusae in the Eastern Gotland basin and the Gulf of Riga (Baltic Sea) between 1998 and 2023. All data are incidental observations obtained during Latvian national monitoring cruises. </p>
Water Body Checklists 2019: Gulf of Riga Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the Gulf of Riga using effechecka and a modified polygon from the International Hydrographic Association. A filter was applied (based on data from WoRMS) to remove all non-marine taxa.
Water Body Checklists: Gulf of Riga Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the Gulf of Riga using effechecka and a modified polygon from the International Hydrographic Association. A filter was applied (based on data from WoRMS) to remove all non-marine taxa.
Reanalysis and future wave climate projections of the wave climate of the Gulf of Riga 1993-2100
<h4><strong>Data sets</strong></h4><p>There are two data sets: (1) reanalysis (1993-2021) and (2) future projection (2015-2100).</p><p>The dataset provides gridded monthly mean values of the parameters of the wind waves in the Gulf of Riga, Baltic Sea. The variables of the dataset of the wave field state of the Gulf of Riga are as follows (Long name: <i>acronym</i>, <i>units</i>) </p><ul><li>Mean wave direction: <i>VMDR_WW, </i>°</li><li>Spectral significant wave height: <i>VHM0_WW, m</i></li><li>Spectral moment (0,1) of wave period or mean wave period: <i>VTM01_WW, s</i></li><li>Eastward wave energy flux: <i>WWEFu, W/m</i></li><li>Northward wave energy flux: <i>WWEFv, W/m</i></li></ul><p> </p><p>The grid size of the dataset is 101 (latitude) x 93 (longitude). The horizontal grid spacing is 1 nm. The time resolution of the dataset is monthly – the monthly mean value is provided in the 1st day of the month in the time dimension.</p><p>The original climatic calculations are based on the University of Latvia (UL) set-up of the SWAN model for the Gulf of Riga. The original output of the model run is hourly data series. </p><h4><strong>Reanalysis</strong></h4><p>Time period: 1993-2021, 29 years.</p><p>The main characteristics of the input data and approach for the reanalysis run are as follows: </p><ul><li>EMODNET2020 bathymetry.</li><li>Atmospheric forcing (eastward and northward components of the near surface wind) – ERA5 meteorology.</li><li>Ice conditions – LU HBM, see Frishfelds et. al. 2023.</li><li>Boundary conditions – Baltic Sea Wave Hindcast.</li></ul><h4><strong>Future climate projection</strong></h4><p>Time period: 2015-2100, 86 years.</p><p>The main characteristics of the input data and approach for the future wave climate projections run are as follows: </p><ul><li>Emodnet2020 bathymetry.</li><li>Atmospheric forcing (eastward and northward components of the near surface wind) from downscaled CMIP6 climate projection model NorESM2-MM_ssp585_r1i1p1f1 (search string – project:'CMIP6', source_id:'NorESM2-MM', experiment_id:'ssp585', variant_label:'r1i1p1f1').</li><li>Ice conditions – LU HBM, see Frishfelds et. al. 2023. </li><li>Boundary conditions – fetch model according to Shore protection manual, 1984.</li></ul><h4><strong>References</strong></h4><p>Frishfelds, V., Cepīte-Frišfelde, D., Timuhins, A., Bethers, U., Sennikovs, J., Reanalysis and future climate projections of the physical state of the Gulf of Riga 1993-2100, Zenodo, <a href="https://zenodo.org/doi/10.5281/zenodo.8248942">10.5281/zenodo.8248942</a>, (2023).</p><p>Baltic Sea Wave Hindcast. E.U. Copernicus Marine Service Information (CMEMS). Marine Data Store (MDS). doi: <a href="https://doi.org/10.48670/moi-00014">https://doi.org/10.48670/moi-00014</a>.</p><p>Shore protection manual, Army Corps of Engineers, Coastal Engineering Research Center (CERC), (1984).</p>
Reanalysis and future climate projections of the physical state of the Gulf of Riga 1993-2100
<p><strong>Data sets</strong></p> <p>There are two data sets: (1) reanalysis (1993-2021) and (2) future projection (2015-2100). Future projection data set is split into 10 files.<br> The dataset provides gridded monthly mean values of physical parameters in the Gulf of Riga, Baltic Sea. The variables of the dataset of the physical state of the Gulf of Riga are as follows (Long name: <em>acronym</em>, <em>units</em>)</p> <ul> <li>Potential temperature: <em>thetao, </em>°<em>C</em></li> <li>Sea water salinity: <em>s, g/kg</em></li> <li>Eastward sea water velocity: <em>ocu, m/s</em></li> <li>Northward sea water velocity: <em>ocv, m/s</em></li> <li>Deviation of sea-level from the mean sea level: <em>zos, m</em></li> <li>Sea ice area fraction <em>siconc</em>, m<sup>2</sup>/ m<sup>2</sup></li> <li>Sea ice thickness: <em>sithick, m</em></li> <li>Bathymetry: <em>bathymetry, m </em>(included only in reanalysis data set)</li> </ul> <p>The grid size of the dataset is 15 (depth) x 203 (latitude) x 187 (longitude). The horizontal grid spacing is 0.5 nm; the vertical grid has 15 depth layers – 2 m deep surface layer and 4 m step for deeper layers. The time resolution of the dataset is monthly – the monthly mean value is provided in the 1st day of the month in time dimension.<br> The original climatic calculations are based on the University of Latvia (UL) set-up of the Hiromb-BOOS model routinely implemented for the operational oceanography in the Baltic Sea and the Gulf of Riga in Latvia. Its parametrization is empirically suited for climatical reanalysis in the Gulf of Riga domain. The original output of the model run is hourly data series.</p> <p><strong>Reanalysis</strong></p> <p>Time period: 1993-2021 (29 years).<br> The main characteristics of the input data and approach for the reanalysis run are as follows:</p> <ul> <li>EMODNET2020 bathymetry.</li> <li>Initial conditions – bias corrected Copernicus Marine Service (CMS).</li> <li>Atmospheric forcing – ERA5 meteorology with improved cloudiness.</li> <li>Boundary conditions from CMS 1993-2018 reanalysis and CMS operational archive (2019-2021) with bias correction for waterlevel in CMS forecast.</li> <li>River inflow – 15 main rivers taken into consideration according to E-HYPE hydrological model data. E-HYPE discharge multiplied by 0.75.</li> <li>Tides: astronomic calculations.</li> </ul> <p><strong>Future climate projection</strong></p> <p>Time period: 2015-2100 (86 yrs).<br> The main characteristics of the input data and approach for the future climate projections run are as follows:</p> <ul> <li>Emodnet2020 bathymetry.</li> <li>Initial conditions – bias corrected Copernicus Marine Service (CMS).</li> <li>Boundary conditions from downscaled CMIP6 climate projection model NorESM2-MM_ssp585_r1i1p1f1 (search string – project:'CMIP6', source_id:'NorESM2-MM', experiment_id:'ssp585', variant_label:'r1i1p1f1').</li> <li>River inflow – 15 main rivers taken into consideration according to E-HYPE climatological model (SMHI_RCA4_HadGEM2-ES_rcp45). E-HYPE discharge multiplied by 1.093.</li> <li>The past period data was used for the downscaling: <ul> <li>ERA5 reanalysis data was used for the downscaling of the atmospheric forcing time series of CMIP6 climate projection model,</li> <li>CMS reanalysis model data was used for the downscaling of the sea state time series.</li> </ul> </li> <li>Downscaled variables: eastward and northward components of the near surface wind, air temperature, air pressure, water temperature, water salinity, sea level.</li> </ul>
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