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15 results for “2045”
Statistical characterization of Andalusian wave climate for several combinations of Global Climate Models and Regional Climate Models and periods 2026 - 2045 and 2081 - 2100.
<p>The following text is an extract of the extended abstract entitled "<strong>Parametric Characterization of Wave Climate along the Andalusian Coast for Non-Stationary Stochastic Simulation</strong>" whose authors are Manuel Cobos, Pedro Magaña, Pedro Otiñar and Asunción Baquerizo, and that was included in proceedings of <em>39th IAHR World Congress</em> where this dataset is included.</p> <p><em>Processed data comes from PIMA Adapta Costas project (Ramírez et al., 2019), in particular, from projections of maritime climate for 2026-2045 and 2081-2100. Sea climate contains, among other information, time series of the significant wave height (H<sub>s</sub>) obtained for several combinations of GCM-RCM projections of EUR-11 for the RCP 8.5. GCM-RCM combinations ACCE, CMCC, CNRM, GFDL, HADG, IPSL, MIRO with a 0.1 degrees grid were used for the Atlantic facade while CNRM, HADG, IPSL, MIRO, MEDC, MPIE, ESM2, EART models with 1/11 degrees were used for the Mediterranean one. A total of 210 locations were analyzed, 54 at the Atlantic facade and 156 at the Mediterranean one (Figure 1). The data was bias adjusted using the Empirical Quantile Mapping (Déqué et al., 2007; Michelangeli et al., 2009). Information of the significant wave height and the dependence between the values at a given time with previous values with a VAR(q) model is already available. </em></p> <p><em>At each location, the methodology of Lira-Loarca et al. (2021) was applied, using the software described in Cobos et al. (2022a). More precisely, for every GCM-RCM (hereinafter, model n for n = 1, .., N where N = 7 for Atlantic data and N = 8 for the Mediterranean data), a non-stationary marginal distribution of H<sub>s</sub>, , assuming that the year was the largest periodicity of the climate, was fitted to data using a lognormal model for the central part and two generalized Pareto distribution for the lower and upper tails, as in Solari and Losada (2011). The non- stationarity is considered by assuming a decomposition of the parameters of the distribution and of the percentiles of the common end points of the interval into a trigonometric truncated expansion.</em></p> <p><em>In addition, the coefficients of the matrix, C<sub>n</sub>, of a VAR(q) model with q up to 92 hours were estimated. The ensemble multi-model characteristics of the data were obtained from the compound distributions and the weighted averaged matrix coefficients. </em></p> <p><em>Soon, the results of the peak period (T<sub>p</sub>) and mean incoming wave direction (ϑ<sub>m</sub>) and the coefficients of the multivariate VAR model will also be included.</em></p> <p> </p> <p> </p>
Trento 1936 - Building 2045
<u>Coordinates</u>: N/A <br><u>Length</u>: 17.69 m<br><u>Width</u>: 9.44 m<br><u>Height</u>: 5.52 m<br><u>Points</u>: 8 <br><u>Vertices</u>: 36 <br><u>Primitives</u>: 12 <br><br><u>Main Files:</u><br><table><tbody><tr><th>Filename</th><th>.glb</th><th>.xml</th><th>.obj</th></tr><tr><td><a href="https://zenodo.org/api/records/12693891/files/building_2045.glb/content">building_2045.glb</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045.glb/content">Link</a></td><td></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12693891/files/building_2045.obj/content">building_2045.obj</a></td><td></td><td></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045.obj/content">Link</a></td></tr><tr><td><a href="https://zenodo.org/api/records/12693891/files/11573815_metsmods.xml/content">11573815_metsmods.xml</a></td><td></td><td><a href="https://zenodo.org/api/records/12693891/files/11573815_metsmods.xml/content">Link</a></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12693891/files/11573815_edm.xml/content">11573815_edm.xml</a></td><td></td><td><a href="https://zenodo.org/api/records/12693891/files/11573815_edm.xml/content">Link</a></td><td></td></tr></tbody></table><br><br><u>Thumbnails:</u><br><table><tbody><tr><th>Perspective</th><th>1000x1000</th><th>512x512</th><th>256x256</th><th>128x128</th></tr><tr><td>Perspective 1</td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_1.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_1_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_1_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_1_128x128.png/content">Link</a></td></tr><tr><td>Perspective 2</td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_2.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_2_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_2_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_2_128x128.png/content">Link</a></td></tr><tr><td>Perspective 3</td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_3.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_3_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_3_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_3_128x128.png/content">Link</a></td></tr><tr><td>Perspective 4</td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_4.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_4_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_4_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_4_128x128.png/content">Link</a></td></tr><tr><td>Perspective Top</td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_top.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_top_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_top_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12693891/files/building_2045_perspective_top_128x128.png/content">Link</a></td></tr></tbody></table><br><br><br><u>Changelog</u>: <br> - v<a href="https://doi.org/10.5281/zenodo.12541894">0.0.2</a>: Thumbnails added, Description updated with Link Tables.<br> - v<a href="https://doi.org/10.5281/zenodo.12693891">0.0.3</a>: Added XMLs for Europeana Data Model (EDM) and MetsMods.<br>
Heat Stress Exposure Maps - Urban Planning Scenario 2026 - 2045: Berlin, Germany
<p><strong>Berlin heat stress exposure map: average number of heatwave days per year versus socio economic data - urban planning scenario (2026-2045).</strong></p> <p>Heat stress exposure maps for Berlin representing the average number of heatwave days per year versus socio economic data per statistical unit. The average number of heatwave days per year has been modeled over the reference period 2026-2045 using the present land use / cover situation for the city but combined with urban planning projects information until 2030. Hence, the urban morphology has been updated accordingly.</p> <p><strong>Scenario: </strong>Urban planning scenario (situation LULC today + integrated urban planning projects 2030)</p> <p><strong>Exposure mapping variable: </strong><br /> Total population 2030<br /> Population density inhabitants per hectare 2030</p>
Heat Stress Maps - Urban Planning Scenarios 1986-2005 / 2026 - 2045: Berlin, Germany
<p>Heat stress maps for Berlin representing<br /> * the average number of heatwave days<br /> (1986 – 2005 | 2026 – 2045 | 2081 – 2100)<br /> per statistical unit or per grid</p> <p>The heat stress parameter considered has been modelled over the reference period 2026 - 2045 using the present land use / cover situation for the city but combined urban planning projects information until 2030. Hence, the urban morphology has been updated accordingly.</p> <p>Scenario: Urban Planning</p>
Heat Stress Maps - Urban Planning Scenarios 1986-2005 / 2026 - 2045: Antwerp, Belgium
<p>Heat stress maps for Antwerp representing<br /> * the average number of heatwave days<br /> (1986 – 2005 | 2026 – 2045 | 2081 – 2100)<br /> per statistical unit or per grid</p> <p>The heat stress parameter considered has been modelled over the reference period 2026 - 2045 using the present land use / cover situation for the city but combined urban planning projects information until 2030. Hence, the urban morphology has been updated accordingly.</p>
Heat Stress Maps - Urban Planning Scenarios 1986-2005 / 2026 - 2045: Almada, Portugal
<p>Heat stress maps for the city of Almada representing<br /> * the average number of heatwave days<br /> (1986 – 2005 | 2026 – 2045 | 2081 – 2100)<br /> per statistical unit or per grid</p> <p>The heat stress parameter considered has been modelled over the reference period 2026 - 2045 using the present land use / cover situation for the city but combined urban planning projects information until 2030. Hence, the urban morphology has been updated accordingly.</p>
Heat Stress Exposure Maps - Urban Planning Scenario 2026 - 2045: Antwerp, Belgium
<p><strong>Antwerp heat stress exposure map: average number of heatwave days per year versus socio economic data - urban planning scenario (2026-2045)</strong></p> <p>Heat stress exposure maps for Antwerp representing the average number of heatwave days per year versus socio economic data per statistical unit. The average number of heatwave days per year has been modeled over the reference period 2026-2045 using the present land use / cover situation for the city but combined with urban planning projects information until 2030. Hence, the urban morphology has been updated accordingly.</p> <p><strong>Exposure mapping variable include:</strong><br /> * Total population 2030<br /> * Population density inhabitants per hectare 2030</p>
Heat Stress Exposure Maps - Urban Planning Scenario 2026 - 2045: Almada, Portugal
<p><strong>Almada heat stress exposure map: average number of heatwave days per year versus socio economic data - urban planning scenario (2026-2045)</strong></p> <p>Heat stress exposure maps for the city of Almada representing the average number of heatwave days per year versus socio economic data per statistical unit. The average number of heatwave days per year has been modeled over the reference period 2026-2045 using the present land use / cover situation for the city but combined with urban planning projects information until 2030. Hence, the urban morphology has been updated accordingly.</p> <p>Exposure mapping variable include:<br /> * Total population 2011<br /> * Population density inhabitants per hectare 2011</p>
Heat Stress Maps - Base Scenarios 1986-2005 / 2026 - 2045 / 2081 - 2100: Almada, Portugal
<p>Heat stress maps for the city of Almada representing<br /> * the average number of heatwave days<br /> (1986 – 2005 | 2026 – 2045 | 2081 – 2100)<br /> per statistical unit or per grid</p> <p>* The Urban Heat Island effect at 11pm per year<br /> (1986 - 2005) per statistical unit or per grid</p> <p>The heat stress parameter considered has been modelled over the reference period using the present land use / cover situation for the city.</p> <p>Please note that only the base scenario 1986-2005 has got maps with the 2 heat stress parameters:<br /> * Average number of heat wave days per year<br /> * Urban Heat Island effect at 11pm per year</p>
Heat Stress Maps - Base Scenarios 1986-2005 / 2026 - 2045 / 2081 - 2100: Berlin, Germany
<p>Heat stress maps for Berlin representing<br /> * the average number of heatwave days<br /> (1986 – 2005 | 2026 – 2045 | 2081 – 2100)<br /> per statistical unit or per grid</p> <p>* The Urban Heat Island effect at 11pm per year<br /> (1986 - 2005) per statistical unit or per grid</p> <p>The heat stress parameter considered has been modelled over the reference period using the present land use / cover situation for the city.</p> <p>Please note that only the base scenario 1986-2005 has got maps with the 2 heat stress parameters:<br /> * Average number of heat wave days per year<br /> * Urban Heat Island effect at 11pm per year</p> <p>Scenario: Base scenario (situation LULC today)</p>
Heat Stress Maps - Base Scenarios 1986-2005 / 2026 - 2045 / 2081 - 2100: Antwerp, Belgium
<p>Heat stress maps for Antwerp representing<br /> * the average number of heatwave days<br /> (1986 – 2005 | 2026 – 2045 | 2081 – 2100)<br /> per statistical unit or per grid</p> <p>* The Urban Heat Island effect at 11pm per year<br /> (1986 - 2005) per statistical unit or per grid</p> <p>The heat stress parameter considered has been modelled over the reference period using the present land use / cover situation for the city.</p> <p>Please note that only the base scenario 1986-2005 has got maps with the 2 heat stress parameters:<br /> * Average number of heat wave days per year<br /> * Urban Heat Island effect at 11pm per year</p>
Binary black-hole simulation SXS:BBH:2045
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
TARP 2019: SU 2045
Photogrammetric capture of stratigraphic unit SU 2045. Source: Objaverse 1.0 / Sketchfab
IO Islamic 2045. Iḳbâlnâma-i-Jahângîrî, History of Sulṭân Akbar and Sulṭân Jahângîr
<p>IO Islamic 2045. Iḳbâlnâma-i-Jahângîrî, History of Sulṭân Akbar and Sulṭân Jahângîr</p>
Binary black-hole simulation SXS:BBH:2045
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
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