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We have found 52 datasets for the keyword " antarctic oscillation". You can continue exploring the search results in the list below.
Datasets: 103,401
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52 Datasets, Page 1 of 6
Past and Future Sea Surface Temperature Changes in the Oceans Surrounding Canada
Wang, Z., Greenan, B.J.W., Hannah, C.G., and Layton, C. 2025. Past and future sea surface temperature changes in the oceans surrounding Canada. Can. Tech. Rep. Hydrogr. Ocean. Sci. 404: v + 44 pThis study presents changes in the sea surface temperature (SST) in the oceans surrounding Canada using past observations and model projections of future scenarios. The past changes are derived using an SST product, HadISST, in which a recent period (2012-2022) was referenced to a 26-year climatology (1955-1980). The future changes in SST are estimated using a 22-member ensemble of CMIP6 models. The SST changes for overlapping periods from the CMIP6 ensemble and the HadISST in the 10 regions of the Canadianshelf waters are in general agreement, although the CMIP6 results tend to overestimate the observed changes by about 0.1 oC. One exception to this is the Scotian Shelf where the CMIP6 models underestimate the observed SST change. The Gulf of Maine, Scotian Shelf, Gulf of St. Lawrence and southern Newfoundland shelf are the regions with the largest observed SST increases around Canada. The Gulf of St. Lawrence has the highest correlation (r=0.65) with the Atlantic Multi-decadal Oscillation (AMO) among the subregions in the North Atlantic Ocean, and the British Columbia Shelf is correlated with the Pacific Decadal Oscillation (r=0.58). Under the four climate scenarios (SSP1-2.6 to SSP5-8.5), among the mid-century (2040-2059) annual mean SST changes (reference period of 1990-2014) in the 10 regions, the Gulf of St. Lawrence is projected to have the largest increases in temperature (1.8 – 2.5oC), and Baffin Bay has the smallest increases (0.5 – 0.9oC), However, for the summer means, the southern Beaufort Sea has the largest SST increase (2.4 -3.1oC) with Baffin Bay having the smallest changes (1.3-2.1oC).Cite this data as: Wang, Z., Greenan, B.J.W., Hannah, C.G., and Layton, C. (2025) Data of:Past and Future Sea Surface Temperature Changes in the Oceans Surrounding Canada.Published: October 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.https://open.canada.ca/data/en/dataset/3c336e55-4266-406a-922d-bbf8e717558c
Regional Ice-Ocean Prediction System
The Regional Ice Ocean Prediction System (RIOPS) provides ice and ocean forecasts up to 84 hours, four times per day on a 1/12° resolution grid (3-8 km). RIOPS is initialized using analyses from the Global Ice-Ocean Prediction System (GIOPS). Atmospheric fluxes up to 84 hours forecasts are calculated using fields from a component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution
Global Ice-Ocean Prediction System
The Global Ice-Ocean Prediction System (GIOPS) produces global sea ice and ocean analyses and 10 day forecasts daily. This product contains time-mean sea ice and ocean forecast fields interpolated to two grids. One of the grids is a 0.2° resolution regular latitude-longitude grid covering the global ocean (north of 80° S). The other grid is in north-polar stereographic projection with a 5-km spacing at the standard parallel 60° N and covers the Arctic Ocean and the neighbouring sub-polar seas. Data is available for 50 depths. The data files are in netCDF format and comply with the Climate and Forecast Conventions.
Global Deterministic Wave Prediction System
The Global Deterministic Wave Prediction System (GDWPS) produces wave forecasts out to 120 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds and the ice concentration from the Global Deterministic Prediction System (GDPS). The ice concentration is used by the model to attenuate wave growth in areas covered by 25% to 75% ice and to suppress it for concentration above 75%. Forecast elements include significant wave height, peak period and primary swell height, direction and period.
CMIP5 Multi-model Ensembles of Sea Ice Concentration projections
Multi-model ensembles of sea ice concentration based on projections from twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of sea ice concentration as represented as the percentage (%) of grid cell area, are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.
Northeast Pacific Monthly Mean Ocean Current Climatology (October - March)
This dataset provides 1/36-degree monthly mean ocean current climatology (October - March) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the perid from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).
Projected Sea Ice Thickness change based on CMIP5 multi-model ensembles
Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in sea ice thickness, based on an ensemble of twenty-six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Projected change in sea ice thickness is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensemble of sea ice thickness change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in sea ice thickness (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.
Bottom temperature at the Atlantic Zone Monitoring Program (AZMP)-Quebec’s stations
Bottom temperature time series at the 3 fixed stations and 46 stations, grouped into transects, of the Atlantic Zonal Monitoring Program (AZMP) under the Quebec region responsibility.The mean bottom temperature of the last ten years are displayed as 2 layers, one for the June survey (2014-2023, 2020 not sampled), another for the autumn survey (2014-2023). A third layer shows the positions of the fixed stations of the program (Anticosti Gyre, Gaspé Current and Rimouski).Each station is linked with a .png file showing the bottom temperature time series and with a .csv file containing all the bottom temperature data acquired at those stations since the beginning of the program sampling (columns : Station, Latitude, Longitude, Date(UTC), Sounding(m), Depth/Profondeur(m), Temperature/Température(ºC)).PurposeThe Atlantic Zone Monitoring Program (AZMP) was implemented in 1998 with the aim of increasing the Department of Fisheries and Oceans Canada’s (DFO) capacity to detect, track and predict changes in the state and productivity of the marine environment.The AZMP collects data from a network of stations composed of high-frequency monitoring sites and cross-shelf sections in each following DFO region: Québec, Gulf, Maritimes and Newfoundland. The sampling design provides basic information on the natural variability in physical, chemical, and biological properties of the Northwest Atlantic continental shelf. Cross-shelf sections sampling provides detailed geographic information but is limited in a seasonal coverage while critically placed high-frequency monitoring sites complement the geography-based sampling by providing more detailed information on temporal changes in ecosystem properties.In Quebec region, two surveys (46 stations grouped into transects) are conducted every year, one in June and the other in autumn in the Estuary and Gulf of St. Lawrence. Historically, 3 fixed stations were sampled more frequently. One of these is the Rimouski station that still takes part of the program and is sampled about weekly throughout the summer and occasionally in the winter period.Annual reports (physical, biological and a Zonal Scientific Advice) are available from the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Devine, L., Scarratt, M., Plourde, S., Galbraith, P.S., Michaud, S., and Lehoux, C. 2017. Chemical and Biological Oceanographic Conditions in the Estuary and Gulf of St. Lawrence during 2015. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/034. v + 48 pp.Supplemental InformationThe bottom temperature is determined from CTD profile in the water column according to AZMP sampling protocol:Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.
CMIP5 Multi-Model Ensembles of Snow Depth projections
Multi-model ensembles of snow depth based on projections from twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of snow depth (m) are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.
Coastal Ice-Ocean Prediction System for the West Coast of Canada (CIOPS-West)
The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.
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