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20 results for “North Sea region”
Updated gridded reconstruction of sea level pressure, temperature, and precipitation during winter in the North Atlantic region covering 1241-1970 CE
<ul> <li>This dataset is an updated version of the gridded climate reconstruction by Sjolte et al. 2018 (SEA18): Solar and volcanic forcing of North Atlantic climate inferred from a process-based reconstruction, <em>Climate of the Past,</em> 14, 1179–1194, https://doi.org/10.5194/cp-14-1179-2018. </li> </ul> <p> </p> <ul> <li>Relevant results of this new version (SEA18v2) are available in our recent paper: Tao, Q. , Sjolte, J. , & Muscheler, R. (2023). Persistent model biases in the spatial variability of winter North Atlantic atmospheric circulation. Geophysical Research Letters, 50, e2023GL105231. https://doi.org/10.1029/2023GL105231</li> </ul> <p> </p> <ul> <li>This dataset contains the gridded reconstruction of winter sea level pressure (slp), 2m temperature (t2m) and precipitation (precip) for the North Atlantic region over 1241-1970.</li> </ul> <p> </p> <ul> <li><strong>Methodology:</strong> The new reconstruction (SEA18v2), has been optimized for a better representation of the variability of the main modes of sea level pressure. The original reconstruction, SEA18, was an ensemble of 39 model analogues for each year and the reconstruction comprised of the mean of the analogues. For the new version, SEA18v2, a different approach to calculating the ensemble mean of the analogues has been applied. While the overall evaluation and ranking of model analogues are the same as for SEA18, we now apply a weighting function so that poor-fitting model analogues receive less weight and good-fitting analogues receive more weight. Furthermore, we evaluate the main modes of the reconstructed SLP and test the minimum number of ensemble members that can be used and still retain skill for the temporal and spatial variability of the first three modes. Retaining 16 ensemble members gives better performance for the spatial patterns for the first three EOFs of SLP compared to SEA18 and good skill for the temporal variability of the NAO.</li> </ul>
Text-fig. 1. Palaeogeographical scheme (distribution of land and sea basins) in part of Eurasia at the beginning of the Late Cretaceous (modified from Spicer et al. 2008). The green leaf symbol indicates the site of the Arman Flora. Asterisks indicate the Okhotsk-Chukotka volcanogenic belt. Dashdotted line indicates the boundary between the Siberian- Canadian and Euro-Sinian palaeofloristic regions (modified from Vakhrameev 1991). in On The Likely Palaeoelevation Of The Turonian - Coniacian Arman Flora Site (North-Eastern Asia)
Text-fig. 1. Palaeogeographical scheme (distribution of land and sea basins) in part of Eurasia at the beginning of the Late Cretaceous (modified from Spicer et al. 2008). The green leaf symbol indicates the site of the Arman Flora. Asterisks indicate the Okhotsk-Chukotka volcanogenic belt. Dashdotted line indicates the boundary between the Siberian- Canadian and Euro-Sinian palaeofloristic regions (modified from Vakhrameev 1991).
Data from: Phenotypic and genetic divergence among harbour porpoise populations associated with habitat regions in the North Sea and adjacent seas.
Determining the mechanisms that generate population structure is essential to the understanding of speciation and the evolution of biodiversity. Here, we investigate a geographic range that transects two habitat gradients, the North Sea to North Atlantic transition, and the temperate to sub-polar regions. We studied the harbour porpoise (Phocoena phocoena), a small odontocete inhabiting both sub-polar and temperate waters. To assess differentiation among putative populations we measured morphological variation at cranial traits (N=462 individuals) and variation at eight microsatellite loci for 338 of the same individuals from Norwegian, British and Danish waters. Significant morphological differentiation reflected the size of the buccal cavity. Porpoises forage in relatively shallow waters preying mainly on benthic species in British and Danish waters, and on mesopelagic and pelagic fish off the coast of Norway. We suggest that the observed differentiation may be explained by resource specialization and either adaptation or developmental responses to different local habitats.
Data from: Seascape genetics and biophysical connectivity modelling support conservation of the seagrass Zostera marina in the Skagerrak-Kattegat region of the eastern North Sea
Maintaining and enabling evolutionary processes within meta-populations is critical to resistance, resilience and adaptive potential. Knowledge about which populations act as sources or sinks, and the direction of gene flow, can help to focus conservation efforts more effectively and forecast how populations might respond to future anthropogenic and environmental pressures. As a foundation species and habitat provider, Zostera marina (eelgrass) is of critical importance to ecosystem functions including fisheries. Here we estimate connectivity of Z. marina in the Skagerrak-Kattegat region of the North Sea based on genetic and biophysical modelling. Genetic diversity, population structure and migration were analysed at 23 locations using 20 microsatellite loci and a suite of analytical approaches. Oceanographic connectivity was analysed using Lagrangian dispersal simulations based on contemporary and historical distribution data dating back to the late 19th century. Population clusters, barriers and networks of connectivity were found to be very similar based on either genetic or oceanographic analyses. A single-generation model of dispersal was not realistic, whereas multi-generation models that integrate stepping-stone dispersal and extant and historic distribution data were able to capture and model genetic connectivity patterns well. Passive rafting of flowering shoots along oceanographic currents is the main driver of gene flow at this spatial-temporal scale and extant genetic connectivity strongly reflects the "ghost of dispersal past" sensu Benzie 1999. The identification of distinct clusters, connectivity hotspots and areas where connectivity has become limited over the last century is critical information for spatial management, conservation and restoration of eelgrass.
FIGURE 8 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 8. Plots of principal component scores for (A) morphometric, (B) meristic, and (C) combined morphometric and meristic characters of eastern Pacific and Arctic species of the Careproctus rastrinus species complex lacking a postorbital pore: C. lerikimae n. sp. (♦), C. phasma (□), C. spectrum (▲).
FIGURE 7 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 7. Plots of principal component scores for (A) morphometric, (B) meristic, and (C) combined morphometric and meristic characters of western Pacific species of the Careproctus rastrinus species complex: C. rastrinus (□), C. trachysoma (), C. acanthodes (♦), and C. pellucidus (▲).
FIGURE 6 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 6. Distribution of species of the Careproctus rastrinus species complex: C. rastrinus (□), C. trachysoma (●), C. scottae (○), C. acanthodes (◊), C. pellucidus (▲), C. phasma (■), C. spectrum (∆),and C. lerikimae n. sp. (♦), based on material examined. Each symbol may represent more than one capture.
FIGURE 5 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 5. Pectoral girdles of species of the Careproctus rastrinus species complex: A) C. rastrinus, HUMZ 60772, 149.2 mm; B) C. trachysoma, FAKU 131179, 229.2 mm; C) C. scottae, UW 155110, 165 mm; D) C. acanthodes, FAKU 135569, 79.2 mm; E) C. pellucidus, FAKU 135317, 210.0 mm; F) C. phasma, UW 117934, 191 mm; G) C. lerikimae n. sp., paratype, UW 154841. Scale bar = 5 mm. c = coracoid, f = interradial fenestra, pr = proximal radial, dr = distal radial, s = scapula. Shaded areas represent cartilage.
FIGURE 4 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 4. Types of selected species of the Careproctus rastrinus species complex: A) C. phasma, SU 3028, paralectotype, 72.3 mm; B) C. spectrum, SU 48, lectotype, 91 mm.
FIGURE 2 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 2. Selected western Pacific species of the Careproctus rastrinus species complex: A) C. acanthodes, FAKU 130975, 93.1 mm; B) C. pellucidus, FAKU 134751, 138.2 mm.
FIGURE 3 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 3. Eastern Pacific and Arctic species of the Careproctus rastrinus species complex: A) C. scottae, UW 151322, 195.0 mm; B) C. phasma, UW 154447, 72.3 mm; C) Careproctus lerikimae n. sp., UW 118033, holotype, 132.3 mm.
FIGURE 1 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea
FIGURE 1. Selected western Pacific species of the Careproctus rastrinus species complex: A) C. rastrinus, FAKU 131687, 320.7 mm; B) C. trachysoma, FAKU 130800, 214.4 mm, light morphotype; C) C. trachysoma, FAKU 131402, 264.8 mm, dark morphotype.
Subspecies and Distribution. U. a. arctos Linnaeus, 1758 — Europe and W Russia. U. a. alascensis Merriam, 1896 — most of Alaska (excluding Alaska Peninsula, SE panhandle & Kodiak Island group). U. a. beringianus Middendorff, 1853 — NE Russia (Kamchatka Peninsula & N Kuril Islands northward through the Koryak Autonomous District, and along W coast of the Sea of Okhotsk). U. a. collaris Cuvier, 1824 — Russia (Siberia, from E of the Yenisey River to the Bering Sea, but excluding Kamchatka and more southern parts of the Russian Far East), N Mongolia. U. a. dalli Merriam, 1896 — SE Alaska (N of Alexander Archipelago). U. a. gyas Merriam, 1902 — Alaska peninsula. U. a. horribilis Ord, 1815 —W Canada (Yukon, North-West Territories, British Columbia & Alberta), inland W USA (extirpated from S Wyoming to Mexico). U. a. isabellinus Horsfield, 1826 — N India, Pakistan, Afghanistan, N to Kazakhstan and Mongolia (Gobi Desert). U. a. lasiotus Gray, 1867 — Russia (Southern Kuril Islands, Sakhalin, Ussuri/Amur river region of the Russian Far East), NE China, North Korea, and Japan (Hokkaido). U. a. middendorffi Merriam, 1896 — Alaska (Kodiak Island & nearby islands). U. a. pruinosus Blyth, 1853 — Tibetan Plateau, China, N Nepal. U. a. sitkensis Merriam, 1896 — SE Alaska (Alexander Archipelago & adjacent coastal area). U. a. stikeenensis Merriam, 1914 — W Canada (W British Columbia), and formerly W USA (W Washington and Oregon). U. a. syriacus Hemprich & Ehrenberg, 1828 — Middle East, from Turkey to Iran (extirpated in Syria), Caucasus mountains of Russia, Georgia, Armenia and Azerbaijan. in Ursidae
Subspecies and Distribution. U. a. arctos Linnaeus, 1758 — Europe and W Russia. U. a. alascensis Merriam, 1896 — most of Alaska (excluding Alaska Peninsula, SE panhandle & Kodiak Island group). U. a. beringianus Middendorff, 1853 — NE Russia (Kamchatka Peninsula & N Kuril Islands northward through the Koryak Autonomous District, and along W coast of the Sea of Okhotsk). U. a. collaris Cuvier, 1824 — Russia (Siberia, from E of the Yenisey River to the Bering Sea, but excluding Kamchatka and more southern parts of the Russian Far East), N Mongolia. U. a. dalli Merriam, 1896 — SE Alaska (N of Alexander Archipelago). U. a. gyas Merriam, 1902 — Alaska peninsula. U. a. horribilis Ord, 1815 —W Canada (Yukon, North-West Territories, British Columbia & Alberta), inland W USA (extirpated from S Wyoming to Mexico). U. a. isabellinus Horsfield, 1826 — N India, Pakistan, Afghanistan, N to Kazakhstan and Mongolia (Gobi Desert). U. a. lasiotus Gray, 1867 — Russia (Southern Kuril Islands, Sakhalin, Ussuri/Amur river region of the Russian Far East), NE China, North Korea, and Japan (Hokkaido). U. a. middendorffi Merriam, 1896 — Alaska (Kodiak Island & nearby islands). U. a. pruinosus Blyth, 1853 — Tibetan Plateau, China, N Nepal. U. a. sitkensis Merriam, 1896 — SE Alaska (Alexander Archipelago & adjacent coastal area). U. a. stikeenensis Merriam, 1914 — W Canada (W British Columbia), and formerly W USA (W Washington and Oregon). U. a. syriacus Hemprich & Ehrenberg, 1828 — Middle East, from Turkey to Iran (extirpated in Syria), Caucasus mountains of Russia, Georgia, Armenia and Azerbaijan.
Distribution. Widespread in Mediterranean Basin from Iberian Peninsula and associated Is E through S Europe to Balkans, Caucasus, and Middle East; in North Africa in Morocco, Algeria, Tunisia, Libya, and Egypt as far S as S Sinai; from Middle East, range continues patchily E into regions surrounding Black and Caspian seas, including Iran, Turkmenistan, Uzbekistan, SE Kazakhstan, Kyrgyzstan, Tajikistan, and Afghanistan, and then finally in two isolated populations in E Nepal and N Myanmar; also Canary Is. in Molossidae
Distribution. Widespread in Mediterranean Basin from Iberian Peninsula and associated Is E through S Europe to Balkans, Caucasus, and Middle East; in North Africa in Morocco, Algeria, Tunisia, Libya, and Egypt as far S as S Sinai; from Middle East, range continues patchily E into regions surrounding Black and Caspian seas, including Iran, Turkmenistan, Uzbekistan, SE Kazakhstan, Kyrgyzstan, Tajikistan, and Afghanistan, and then finally in two isolated populations in E Nepal and N Myanmar; also Canary Is.
Data from: Seascape genetics and biophysical connectivity modelling support conservation of the seagrass Zostera marina in the Skagerrak-Kattegat region of the eastern North Sea
Open the record for dataset details and reuse information.
Data from: Phenotypic and genetic divergence among harbour porpoise populations associated with habitat regions in the North Sea and adjacent seas.
Open the record for dataset details and reuse information.
GHRSST Level 3C North Atlantic Regional Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-19 (GDS2 version)
A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 platform (launched 6 Feb 2009). This particular dataset is produced by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) in France. The AVHRR is a space-borne scanning sensor on the National Oceanic and Atmospheric Administration (NOAA) family of Polar Orbiting Environmental Satellites (POES) having a operational legacy that traces back to the Television Infrared Observation Satellite-N (TIROS-N) launched in 1978. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micrometer) and near-infrared (0.9 micrometer) regions, the third one is located around 3.5 micrometer, and the last two sample the emitted thermal radiation, around 11 and 12 micrometers, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micrometer. Typically the 11 and 12 micron channels are used to derive sea surface temperature (SST) sometimes in combination with the 3.5 micron channel. The highest ground resolution that can be obtained from the current AVHRR instruments is 1.1 km at nadir. The NOAA-19 platform is sun synchronous generally viewing the same earth location twice a day (latitude dependent) due to the relatively large AVHRR swath of approximately 2400 km. The NAR products are SST fields derived from 1km AVHRR data that are re-mapped onto a 0.02 degree equal angle grid. In the processing chain, global AVHRR level 1b data are acquired at Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. A cloud mask is applied and SST is retrieved from the AVHRR infrared (IR) channels by using a multispectral technique. This dataset adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications.
GHRSST Level 3C North Atlantic Regional (NAR) subskin Sea Surface Temperature from Metop/AVHRR (GDS V2) produced by OSI SAF
A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) derived from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-B (MetOp-B) platform (launched 17 Sep 2012). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT),Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near realtime from Metop/AVHRR and SNPP/VIIRS. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system.NAR SNPP/VIIRS level 0 data are acquired through direct readout and converted into l1b at CMS.SST is retrieved from the AVHRR and VIIRS infrared channels using a multispectral algorithm.This product is delivered as four six hourly collated files per day on a regular 2km grid. Theproduct format is compliant with the GHRSST Data Specification (GDS) version 2.
GHRSST Level 3C North Atlantic Regional (NAR) subskin Sea Surface Temperature from SNPP/VIIRS (GDS V2) produced by OSI SAF
A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset for the North Atlantic Region (NAR) based on retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR and SNPP/VIIRS. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. NAR SNPP/VIIRS level 0 data are acquired through direct readout and converted into l1b at CMS. SST is retrieved from the AVHRR and VIIRS infrared channels using a multispectral algorithm. This product is delivered as four six hourly collated files per day on a regular 2km grid. The product format is compliant with the GHRSST Data Specification (GDS) version 2.
GHRSST Level 3C North Atlantic Regional (NAR) subskin Sea Surface Temperature from SNPP/VIIRS and Metop-A/AVHRR (GDS V2) produced by OSI SAF
A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) derived from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-A (MetOp-A) platform (launched 19 Oct 2006). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR and SNPP/VIIRS. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. NAR SNPP/VIIRS level 0 data are acquired through direct readout and converted into l1b at CMS. SST is retrieved from the AVHRR and VIIRS infrared channels using a multispectral algorithm.This product is delivered as four six hourly collated files per day on a regular 2km grid. The product format is compliant with the GHRSST Data Specification (GDS) version 2.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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