Climate data guide content with tag Sea Ice Concentration
CERA-20C: ECMWF's Coupled Ocean-Atmosphere Reanalysis of the 20th Century
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The CERA-20C is a global, coupled reanalysis spanning 1901-2010 with a focus on low-frequency climate variability. Similar to ERA-20C, the surface observations assimilated include surface pressures from the International Surface Pressure Databank v3.2.6 and ICOADS v 2.5.1, and surface winds over the oceans from ICOADSv2.5.1. Upper-air and satellite data are…
Main variables and Earth System components
Atmosphere Multiple variables Cryosphere Sea Ice Concentration OceanExperts contributing reviews
- Laloyaux, Patrick
Merged Hadley-NOAA/OI Sea Surface Temperature & Sea-Ice Concentration (Hurrell et al, 2008)
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The merged Hadley-OI sea surface temperature (SST) and sea ice concentration (SIC) data sets were specifically developed as surface forcing data sets for AMIP style uncoupled simulations of the Community Atmosphere Model (CAM). The Hadley Centre's SST/SIC version 1.1 (HADISST1), which is derived gridded, bias-adjusted in situ observations, were merged with the NOAA-…
Main variables and Earth System components
Cryosphere Sea Ice Concentration Ocean SST - sea surface temperature-
Formats
- netCDF
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Timestep
- Monthly
Experts contributing reviews
- N/A
NSIDC Sea Ice Index
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The NSIDC Sea Ice Index is a suite of easy-to-use sea ice analyses to track changes in Arctic and Antarctic sea ice. The product is produced and supported by the NOAA at NSIDC group and consists of browse imagery and data text files (CSV or Excel format). The input data is from two sources distributed by the NASA NSIDC Distributed Active Archive Center (DAAC): (1) Sea…
Experts contributing reviews
- Meier, Walter
Sea Ice Concentration Climate Data Record from OSI SAF
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The Ocean and Sea Ice Satellite Applications Facility (OSI SAF) of EUMETSAT provides sea ice concentration products for the Arctic and Antarctic based on satellite passive microwave data. The concentration value is expressed as the fractional percentage of the ice cover in a given grid cell. Since 2023, OSI-450-a and OSI-430-a constitute the third fully reprocessed…
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Formats
- netCDF
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Timestep
- Daily
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Collections
- N/A
Experts contributing reviews
- Aaboe, Signe, Lavergne, Thomas
Sea Ice Concentration data from AMSR-E, AMSR2 & SSMIS, U Bremen and U Hamburg ASI algorithm
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The sea ice data derived from AMSR-E using the ARTIST sea ice (ASI) algorithm offer a factor of 4 finer spatial resolution than most sea ice data sets from passive microwave satellite instruments. ASI is based on the difference of vertically and horizontally polarized brightness temperatures at 89 GHz; this difference is independent of temperature but depends on…
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Timestep
- Daily
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Collections
- N/A
Experts contributing reviews
- N/A
Sea Ice Concentration data from HadISST
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Spanning 1871-present at monthly timesteps, HadISST provides the longest gridded sea ice data available for both the Arctic and Antarctic. It is a 1° x 1° spatially infilled data set that is It is intended as a consistent analyses for input into SST analyses or as boundary conditions for models. Version 1.1 is the currently available data set and is the one described…
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Timestep
- Monthly
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Collections
- Boundary Conditions
Experts contributing reviews
- N/A
Sea Ice Concentration data from NASA Goddard and NSIDC based on Bootstrap algorithm
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Bootstrap sea ice refers to a well-known algorithm used to estimate sea ice concentration from passive microwave brightness temperatures. It can be applied to data from many satellite instruments, such as SMMR, SSMI, and AMSR-E. This page discusses the algorithm itself and the long-term data set ("NSIDC 0079, version 2") produced by J. Comiso and distributed by NSIDC.…
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Timestep
- Daily, Monthly
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Collections
- N/A
Experts contributing reviews
- N/A
Sea Ice Concentration data from NASA Goddard and NSIDC based on NASA Team algorithm
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NASA Team sea ice refers to a well-known algorithm used to estimate sea ice concentration from passive microwave brightness temperatures. This page discusses the algorithm itself and the long-term data set ("NSIDC 0051") produced by scientists at NASA Goddard and distributed by NSIDC. The NASA Team data are very widely used and are a key input into other data sets…
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Timestep
- Daily, Monthly
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Collections
- Diagnostic Data Sets, NCAR-DOE-CESM, seaicediagnostics
Experts contributing reviews
- N/A
Sea Ice Concentration data from NASA Goddard and NSIDC using AMSR-E and NASA TEAM2 (NT2) algorithm
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The AMSR-E/NASA Team 2 (NT2) data set of Arctic and Antarctic sea ice concentration is available at daily timesteps and 12.5 km (optionally 25km) spatial resolution for 2002-2011. NT2, an extension of the original NASA Team algorithm, uses AMSR-E 89GHz channels to help resolve ambiguity between low ice concentrations and areas with strong surface effects (due to snow…
Experts contributing reviews
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Sea ice concentration data from NASA Goddard based on SSMI and NASA Team (NT2) algorithm
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The NASA Team 2 (NT2) / SSMI data set of Arctic and Antarctic sea ice concentration is available at daily timesteps and 25km spatial resolution for 1992-2008. NT2, an extension of the original NASA Team algorithm, uses SSMI 85GHz channels to help resolve ambiguity between low ice concentrations and areas with strong surface effects (due to snow layering and glazing).…
Experts contributing reviews
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Sea Ice Concentration data from NOAA OI
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The NOAA Optimal Interpolation (OI) v2 sea ice data set contains gridded, weekly or monthly resolution sea ice concentration estimates for both the Northern and Southern Hemispheres. It is intended as a consistent analyses for input into SST analyses (and is the basis for calculating SSTs in sea ice zones for the OI SST data) or as boundary conditions for atmospheric…
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Formats
- netCDF
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Timestep
- Monthly, Weekly
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Collections
- Boundary Conditions
Experts contributing reviews
- N/A
Sea Ice Concentration data: Overview, Comparison table and graphs
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Sea ice concentration is both an indicator and driver of high-latitude climate change with strong societal and ecological importance. It is a key boundary condition for atmospheric models (including those used in atmospheric reanalyses) and a benchmark for coupled climate models. As such, numerous methods have been developed to estimate sea ice concentration. The most…
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Formats
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Timestep
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Collections
- Overview / Comparison page
Experts contributing reviews
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Sea Ice Concentration: NOAA/NSIDC Climate Data Record
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The NOAA/NSIDC Climate Data Record (CDR) of sea ice concentration is available at 25 x 25 km spatial resolution in daily or monthly timesteps for 1987-2014. It provides a consistent interpretation of sea ice for the satellite record, with the intent of being suitable for studies of climate variability and change. The CDR is produced by an automated and independent…
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Formats
- netCDF
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Timestep
- Daily, Monthly
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Collections
- Climate Data Record
Experts contributing reviews
- Meier, Walter
SST data: NOAA High-resolution (0.25x0.25) Blended Analysis of Daily SST and Ice, OISSTv2
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"NOAA’s Optimum Interpolation Sea Surface temperature (OISST, also known as Reynolds’ SST) is a series of global analysis products, including the weekly OISST on a 1° grid to the more recent daily on a ¼° grid. An SST analysis is a spatially gridded product created by interpolating and extrapolating data, resulting in a smoothed complete field. OISST provides global…
Main variables and Earth System components
Cryosphere Sea Ice Concentration Ocean SST - sea surface temperatureExperts contributing reviews
- Banzon, Viva, Reynolds, Richard
Walsh and Chapman Northern Hemisphere Sea Ice
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The Walsh and Chapman Sea Ice Data Set provides a long record of Arctic sea ice concentrations on a monthly basis for 1870-2011. Historical observations were gridded and combined with satellite-derived sea ice concentrations for the recent decades. Mostly climatologies before the 1950s. The Walsh and Chapman sea ice data set is the main input data set into the HadiSST…
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Formats
- ascii
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Timestep
- Monthly
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Domain
- NH - Northern Hemisphere, Arctic
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Collections
- N/A
Experts contributing reviews
- Chapman, William