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Simple Ocean Data Assimilation
The Simple Ocean Data Assimilation (SODA) analysis is an Ocean reanalysis, oceanic reanalysis data set consisting of gridded state variables for the global ocean, as well as several derived fields. SODA was developed in the 1990s as a collaborative project between the Department of Atmospheric and Oceanic Science at the University of Maryland and the Department of Oceanography at Texas A&M University with the goal of providing an improved estimate of ocean state from those based solely on observations or numerical simulations. Since its first release there have been several updates, the most recent of which extends from 1958 to 2008, as well as a “beta release” of a long-term reanalysis for 1871–2008. Initial release Initially released in 2000, SODA included data from the 1994 World Ocean Atlas (WOA-94) such as MBT, Expendable bathythermograph, XBT, Conductivity, temperature, depth, CTD and station data; hydrography, SST, and altimeter measured sea level; as well as data from ...
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Ocean Reanalysis
Ocean reanalysis is a method of combining historical ocean observations with a general ocean model (typically a computational model) driven by historical estimates of surface winds, heat, and freshwater, by way of a data assimilation algorithm to reconstruct historical changes in the state of the ocean. Historical observations are sparse and insufficient for understanding the history of the ocean and its circulation. By utilizing data assimilation techniques in combination with advanced computational models of the global ocean, researchers are able to Interpolation, interpolate the historical observations to all points in the ocean. This process has an analog in the construction of atmospheric reanalysis and is closely related to ocean state estimation. Current projects A number of efforts have been initiated in recent years to apply data assimilation to estimate the physical state of the ocean, including Sea surface temperature, temperature, salinity, Ocean currents, currents, an ...
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European Centre For Medium-Range Weather Forecasts
The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent intergovernmental organisation supported by most of the nations of Europe. It is based at three sites: Shinfield Park, Reading, United Kingdom; Bologna, Italy; and Bonn, Germany. It operates one of the largest supercomputer complexes in Europe and the world's largest archive of numerical weather prediction data. History ECMWF was established in 1975, in recognition of the need to pool the scientific and technical resources of Europe's meteorological services and institutions for the production of weather forecasts for medium-range timescales (up to approximately two weeks) and of the economic and social benefits expected from it. The Centre employs about 350 staff, mostly appointed from across the member states and co-operating states. In 2017, the centre's member states accepted an offer from the Italian Government to move ECMWF's data centre to Bologna, Italy. The new site, a former tobacco ...
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ECMWF Re-analysis
The ECMWF reanalysis project is a meteorological reanalysis project carried out by the European Centre for Medium-Range Weather Forecasts (ECMWF), integrating historical meteorological observations onto a regularly spaced global grid for retrospective weather data analysis. The first reanalysis product, ERA-15, generated reanalyses for approximately 15 years, from December 1978 to February 1994. The second product, ERA-40 (originally intended as a 40-year reanalysis) begins in 1957 (the International Geophysical Year) and covers 45 years to 2002 at a resolution of 125 km. As a precursor to a revised extended reanalysis product to replace ERA-40, ECMWF released ERA-Interim, which covers the period from 1979 to 2019. The reanalysis product ERA5, released by ECMWF as part of the Copernicus Climate Change Service, features a spatial resolution of 31 km and currently spans from 1940 to the present. It has since become one of the most widely used global historical weather datasets in sc ...
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NCEP/NCAR Reanalysis
The NCEP/NCAR Reanalysis is an atmospheric reanalysis produced by the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). It is a continually updated globally gridded data set that represents the state of the Earth's atmosphere, incorporating observations and numerical weather prediction (NWP) model output from 1948 to present. Accessing the data The data is available for free download from the NOAA Earth System Research Laboratory and NCEP. It is distributed in Netcdf and GRIB files, for which a number of tools and libraries exist. It is available for download through the NCAR CISL Research Data Archive on the NCEP/NCAR Reanalysis main data page. Uses * Initializing a smaller scale atmospheric model * Climate assessment Subsequent updates Since then NCEP-DOE Reanalysis 2 and the NCEP CFS Reanalysis are released. The former focuses in fixing existing bugs with the NCEP/NCAR Reanalysis system – most notably surface e ...
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NetCDF
NetCDF (Network Common Data Form) is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. The project homepage is hosted by the Unidata program at the University Corporation for Atmospheric Research (UCAR). They are also the chief source of netCDF software, standards development, updates, etc. The format is an open standard. NetCDF Classic and 64-bit Offset Format are an international standard of the Open Geospatial Consortium. History The project started in 1988 and is still actively supported by UCAR. The original netCDF binary format (released in 1990, now known as "netCDF classic format") is still widely used across the world and continues to be fully supported in all netCDF releases. Version 4.0 (released in 2008) allowed the use of the HDF5 data file format. Version 4.1 (2010) added support for C and Fortran client access to specified subsets of remote data via ...
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Arctic Ocean
The Arctic Ocean is the smallest and shallowest of the world's five oceanic divisions. It spans an area of approximately and is the coldest of the world's oceans. The International Hydrographic Organization (IHO) recognizes it as an ocean, although some oceanographers call it the Arctic Mediterranean Sea. It has also been described as an estuary of the Atlantic Ocean. It is also seen as the northernmost part of the all-encompassing world ocean. The Arctic Ocean includes the North Pole region in the middle of the Northern Hemisphere and extends south to about 60°N. The Arctic Ocean is surrounded by Eurasia and North America, and the borders follow topographic features: the Bering Strait on the Pacific side and the Greenland Scotland Ridge on the Atlantic side. It is mostly covered by sea ice throughout the year and almost completely in winter. The Arctic Ocean's surface temperature and salinity vary seasonally as the ice cover melts and freezes; its salinity is the ...
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Parallel Ocean Program
The Parallel Ocean Program (POP) is a three-dimensional ocean circulation model designed primarily for studying the ocean climate Climate is the long-term weather pattern in a region, typically averaged over 30 years. More rigorously, it is the mean and variability of meteorological variables over a time spanning from months to millions of years. Some of the meteoro ... system. The model is developed and supported primarily by researchers at LANL. External links {{climate-stub Physical oceanography ...
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QuickSCAT
The NASA QuikSCAT (Quick Scatterometer) was an Earth observation satellite carrying the SeaWinds scatterometer. Its primary mission was to measure the surface wind speed and direction over the ice-free global oceans via its effect on water waves. Observations from QuikSCAT had a wide array of applications, and contributed to climatological studies, weather forecasting, meteorology, oceanographic research, marine safety, commercial fishing, tracking large icebergs, and studies of land and sea ice, among others. This SeaWinds scatterometer is referred to as the QuikSCAT scatterometer to distinguish it from the nearly identical SeaWinds scatterometer flown on the ADEOS-2 satellite. Mission description QuikSCAT was launched on 19 June 1999 with an initial 3-year mission requirement. QuikSCAT was a "quick recovery" mission replacing the NASA Scatterometer (NSCAT), which failed prematurely in June 1997 after just 9.5 months in operation. QuikSCAT, however, far exceeded these design expe ...
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ERA-40
The ECMWF reanalysis project is a meteorological reanalysis project carried out by the European Centre for Medium-Range Weather Forecasts (ECMWF), integrating historical meteorological observations onto a regularly spaced global grid for retrospective weather data analysis. The first reanalysis product, ERA-15, generated reanalyses for approximately 15 years, from December 1978 to February 1994. The second product, ERA-40 (originally intended as a 40-year reanalysis) begins in 1957 (the International Geophysical Year) and covers 45 years to 2002 at a resolution of 125 km. As a precursor to a revised extended reanalysis product to replace ERA-40, ECMWF released ERA-Interim, which covers the period from 1979 to 2019. The reanalysis product ERA5, released by ECMWF as part of the Copernicus Climate Change Service, features a spatial resolution of 31 km and currently spans from 1940 to the present. It has since become one of the most widely used global historical weather datasets in sc ...
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Sea Surface Temperature
Sea surface temperature (or ocean surface temperature) is the ocean temperature, temperature of ocean water close to the surface. The exact meaning of ''surface'' varies in the literature and in practice. It is usually between and below the sea surface. Sea surface temperatures greatly modify air masses in the Atmosphere of Earth, Earth's atmosphere within a short distance of the shore. The thermohaline circulation has a major impact on average sea surface temperature throughout most of the world's oceans. Warm sea surface temperatures can develop and Tropical cyclogenesis, strengthen cyclones over the ocean. Tropical cyclones can also cause a cool wake. This is due to turbulent mixing of the upper of the ocean. Sea surface temperature changes during the day. This is like the air above it, but to a lesser degree. There is less variation in sea surface temperature on breezy days than on calm days. Coastal sea surface temperatures can cause offshore winds to generate upwelling ...
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State Variable
A state variable is one of the set of Variable (mathematics), variables that are used to describe the mathematical "state" of a dynamical system. Intuitively, the state of a system describes enough about the system to determine its future behaviour in the absence of any external forces affecting the system. Models that consist of coupled first-order differential equations are said to be in state-variable form. Examples *In mechanics, mechanical systems, the position coordinates and Velocity, velocities of mechanical parts are typical state variables; knowing these, it is possible to determine the future state of the objects in the system. *In thermodynamics, a state variable is an independent variable of a state function. Examples include internal energy, enthalpy, thermodynamic temperature, temperature, pressure, volume and entropy. Heat and Work (Thermodynamics), work are not state functions, but process functions. *In electronics, electronic/electrical circuits, the voltages ...
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Data Assimilation
Data assimilation refers to a large group of methods that update information from numerical computer models with information from observations. Data assimilation is used to update model states, model trajectories over time, model parameters, and combinations thereof. What distinguishes data assimilation from other estimation methods is that the computer model is a dynamical model, i.e. the model describes how model variables change over time, and its firm mathematical foundation in Bayesian Inference. As such, it generalizes inverse methods and has close connections with machine learning. Data assimilation initially developed in the field of numerical weather prediction. Numerical weather prediction models are equations describing the evolution of the atmosphere, typically coded into a computer program. When these models are used for forecasting the model output quickly deviates from the real atmosphere. Hence, we use observations of the atmosphere to keep the model on track. Data ...
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