EnviSat was a satellite mission monitoring Earth's environment. EnviSat application areas included meteorology, climatology, environment, atmospheric chemistry, vegetation, hydrology, land use, and ocean and ice processes. EnviSat was a research mission that carried ten instruments and provided a wealth of data related to Earth's health and climate change. EnviSat carried the Medium Resolution Imaging Spectrometer( MERIS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), Radar Altimeter-2 (RA-2), Laser Retro-Reflector (LRR), Microwave Radiometer (MWR), Advanced SAR (ASAR), Global Ozone Monitoring by Occultation of Stars (GOMOS), Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), Advanced Along Track Scanning Radiometer, provided by the UK and Australia (AATSR), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS).

Sentinel-1 is a constellation of two imaging radar satellites operated by ESA. Sentinel-1B experienced an anomaly which rendered it unable to deliver radar data in December 2021, and the launch of Sentinel-1C is planned for 2023.

Habitat found in the zone on mountain tops between permanent snow and the cold limits of trees, or in arctic regions, characterized by very low winter temperatures, short cool summers, permafrost below a surface layer subject to summer melt, short growing season, and low precipitation.[The Nature Conservancy]

This dataset presents monthly gridded sea ice and ocean parameters for the Arctic derived from the European Space Agency's satellite CryoSat-2. Parameters include sea ice freeboard, sea ice thickness, sea ice surface roughness, mean sea surface height, sea level anomaly, and geostrophic circulation. Data are provided as monthly grids with a resolution of 25 km, mapped onto the NSIDC EASE2-Grid, covering the Arctic region north of 50 degrees latitude, for all winter months (Oct-Apr) between 2010 and 2018. CryoSat-2 Level 1b Baseline C observed waveforms have been retracked using a numerical model for the SAR altimeter backscattered echo from snow-covered sea ice presented in Landy et al. (2019), which offers a sophisticated physically-based treatment of the effect of ice surface roughness on retracked ice and ocean elevations. Methods for optimizing echo model fits to observed CryoSat-2 waveforms, retracking waveforms, classifying returns, deriving sea ice freeboard, and converting to thickness are detailed in Landy et al. (In Review). This dataset contains derived sea ice thicknesses from two processing chains, the first using the conventional snow depth and density climatology from Warren et al. (1999) and the second using reanalysis and model-based snow data from SnowModel (Stroeve et al., In Review). Sea surface height and ocean topography grids were derived from only those CryoSat-2 samples classified as leads. Both the random and systematic uncertainties relevant for each parameter have been carefully estimated and are provided in the data files. NetCDF files contain detailed descriptions of each derived parameter. Funding was provided by ESA Living Planet Fellowship Arctic-SummIT grant ESA/4000125582/18/I-NS and NERC Project PRE-MELT grant NE/T000546/1.

The Antarctic Oscillation (AAO) is the dominant pattern of non-seasonal tropospheric circulation variations south of 20S, and it is characterized by pressure anomalies of one sign centered in the Antarctic and anomalies of the opposite sign centered about 40-50S. The AAO is also referred to as the Southern Annular Mode (SAM). There is a Northern Hemisphere analog to the AAO, and it is called the Arctic Oscillation (or Northern Annular Mode).

The stratosphere is the upper middle part of the atmosphere, and is the level of the Jet Stream winds. Colder temperatures in the stratosphere over the Arctic are associated with the positive phase of the Arctic Oscillation, and are indicative of stronger polar winds.

This dataset presents biweekly gridded sea ice thickness and uncertainty for the Arctic derived from the European Space Agency's satellite CryoSat-2. An associated 'developer's product' also includes intermediate parameters used or output in the sea ice thickness processing chain. Data are provided as biweekly grids with a resolution of 80 km, mapped onto a Northern Polar Stereographic Grid, covering the Arctic region north of 50 degrees latitude, for all months of the year between October 2010 and July 2020. CryoSat-2 Level 1b Baseline-D observed radar waveforms have been retracked using two different approaches, one for the 'cold season' months of October-April and the second for 'melting season' months of May-September. The cold season retracking algorithm uses a numerical model for the SAR altimeter backscattered echo from snow-covered sea ice presented in Landy et al. (2019), which offers a physical treatment of the effect of ice surface roughness on retracked ice and ocean elevations. The method for optimizing echo model fits to observed CryoSat-2 waveforms, retracking waveforms, classifying returns, and deriving sea ice radar freeboard are detailed in Landy et al. (2020). The melting season retracking algorithm uses the SAMOSA+ analytical echo model with optimization to observed CryoSat-2 waveforms through the SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research and Exploitation) service available through ESA Grid Processing on Demand (GPOD). The method for classifying radar returns and deriving sea ice radar freeboard in the melting season are detailed in Dawson et al. (2022). The melting season sea ice radar freeboards require a correction for an electromagnetic range bias, as described in Landy et al. (2022). After applying the correction, year-round freeboards are converted to sea ice thickness using auxiliary satellite observations of the sea ice concentration and type, as well as snow depth and density estimates from a Lagrangian snow evolution scheme: SnowModel-LG (Stroeve et al., 2020; Liston et al., 2020). The sea ice thickness uncertainties have been estimated based on methods described in Landy et al. (2022). NetCDF files contain detailed descriptions of each parameter. Funding was provided by the NERC PRE-MELT grant NE/T000546/1 and the ESA Living Planet Fellowship Arctic-SummIT grant ESA/4000125582/18/I-NS.

Difference of sea surface height and mean sea surface. Sea surface height may be corrected using models for effects such as tides and atmospheric forcing

ICESat (Ice, Cloud, and Land Elevation Satellite) is a NASA/GSFC mission within the ESE (Earth Science Enterprise) program. The prime objective is to monitor the mass balance of the polar ice sheets and their contributions to global sea level change. Secondary goals are to measure cloud heights and the vertical structure of clouds and aerosols in the atmosphere, further to measure roughness, reflectivity, vegetation heights, snow-cover, and sea-ice surface characteristics, and to map topography of land surfaces. Note: ICESat is the renamed former "Laser Altimetry-1" mission.

GRACE (Gravity Recovery And Climate Experiment) satellites mapped detailed measurements of the global gravitational fields with unprecedented precision. Data from GRACE satellites covered wide application areas. GRACE consists of two satellites (A, B) serving one mission.