Since the early 2000s, sea ice has experienced an increased rate of decline in thickness and extent and is transitioning to a seasonal ice cover. This shift to thinner, seasonal ice in the ‘New Arctic’ is accompanied by a reshuffling of energy flows at the surface.

EOS Aqua AMSR-E Arctic Sea-Ice Validation

Medley, B., & Thomas, E. R. (2019). Increased snowfall over the Antarctic Ice Sheet mitigated twentieth-century sea-level rise. Nature Climate Change, 9(1), 34, https://doi.org/10.1038/s41558-018-0356-x.

GRACE and ICESat Antarctic mass-balance differences are resolved utilizing their dependencies on corrections for changes in mass and volume of the same underlying mantle material forced by ice-loading changes.

Sea ice freeboard (height of sea ice plus snow layer above sea level) and thickness data derived from ICESat laser altimetry data. Data consist of 13 measurement campaigns spanning the time period from October 2003 to March 2008.

Antarctic Snow: Daily maps of the snow depth on top of the floating sea ice as sea ice concentration measurements. Snow depth distribution over sea ice in the Southern Ocean from satellite passive microwave data. Sea ice concentration, ice temperature, and snow depth using AMSR-E data.

Weekly polar-gridded products of Aquarius L-band Brightness Temperature (TB), L-band Normalized Radar Cross Section (NRCS), and Sea Surface Salinity (SSS), along with sea ICE Fraction (ICEF), were produced on the version 2.0 Equal-Area Scalable Earth (EASE) grid. Each grid cell is 36 km x 36 km.

Yearly maps of early melt (earliest observed melt conditions), melt (melt conditions observed from this point until freeze), early freeze (earliest observed freeze conditions), and freeze (freeze conditions observed from this point on) for the surface of sea ice derived from SSM/I data.

Arctic Snow: Daily maps of the snow depth on top of the floating sea ice. This dataset also determines the multi-year ice cover of the Arctic Ocean where, at this point, no snow depth can be retrieved. Reference: Markus, T. and D.J. Cavalieri, Snow depth distribution over sea ice in the Southern Ocean from satellite passive microwave data, in Antarctic Sea Ice Physical Processes, Interactions and Variability, Antarctic Research Series, 74, edited by M.O. Jeffries, pp.19-40, AGU, Washington, D.C., 1998. Comiso, J.C., D.J. Cavalieri, and T. Markus, Sea ice concentration, ice temperature, and snow depth using AMSR-E data, IEEE Trans. Geoscience and Remote Sensing, 41(2), 243-252, 2003.

The sea ice data presented here were derived from satellite passive-microwave radiometers, specifically, the Scanning Multichannel Microwave Radiometer (SMMR) on NASA’s Nimbus 7 satellite, for November 1978-August 1987, a sequence of Special Sensor Microwave Imagers (SSMIs) on the F8, F11, and F13 satellites of the Defense Meteorological Satellite Program (DMSP), for August 1987-December 2007, and the Special Sensor Microwave Imager Sounder (SSMIS) on the DMSP F17 satellite for January 2008-December 2012.

Atmospheric drag coefficients over Arctic sea ice (spring, 2009-2015): Maps of the neutral atmospheric form drag coefficient from surface feature variability derived from NASA's Operation IceBridge Airborne Topographic Mapper data and extrapolated across the Arctic domain with ASCAT backscatter data. Also included is the total neutral atmospheric drag coefficient, which includes contributions from surface feature variability (as above), but also from floe edges in the marginal ice zone (concentration from the NASA Team algorithm), a constant form drag coefficient over open water and a constant skin drag coefficient.'

Up-to-date satellite observations of the sea ice covers of both the Arctic and the Antarctic, along with comparisons with the historical satellite record of more than 4 decades.

The GSFC time variable gravity mascon products optimize the signal-to-noise ratio through the application of spatial regularization in the estimation of both monthly and high-resolution trends from GRACE and GRACE-FO Level 1B data. These mascon products do not require any additional filtering prior to their research application.

Greenland Ice Sheet surface elevation is changing as mass loss accelerates. This data set investigates the amount of and processes related to, change in elevation at Summit station, Greenland, over the past decade.

Greenland Land and Ice Mask Data.

Higher-resolution videos and crater shapefiles for the Hiawatha impact crater in northwest Greenland (Kjær et al., 2018)

Sea Surface Salinity Polar-Gridded Satellite Products at High Latitudes in the Northern Hemisphere

LIMA was created from nearly 1100 individual Landsat-7 images of Antarctica, most collected between 1999 and 2003. A single Landsat image records the reflected brightness of a 185km x 185 km area of the earth’s surface in six spectral bands (30-meter spatial resolution), two thermal bands (60-meter resolution) and a panchromatic band (15-meter resolution).

Arctic sea ice snow depth and density estimates simulated with the NASA Eulerian Snow On Sea Ice Model (NESOSIM).

NESOSIM is a three-dimensional, two-layer (vertical), Eulerian snow on sea ice budget model. The data included here are from the NESOSIM v1.0 model configuration forced with daily inputs of snowfall (from ERA-I and a median of three reanalyses), near-surface winds (from ERA-I), sea ice concentration (from Bootstrap satellite passive microwave data) and sea ice drift (from the NSIDC Polar Pathfinder satellite feature tracking data).

The goal of NLDAS is to construct quality-controlled, and spatially and temporally consistent, land-surface model (LSM) datasets from the best available observations and model output to support modeling activities.

A series of global ocean tide models has been developed in this laboratory, primarily from analysis of satellite altimetry.  Some of the models are widely used in space geodetic applications.  Some are available here; other iterations are available by inquiry.

The Cryosphere Lab at NASA/GSFC has processed satellite radar and aircraft laser altimetry over the continental ice sheets and surrounding sea ice to calculate surface elevations.

Daily and weekly satellite data are provided in color visualizations together with time series animations of the key variables in support of the Distributed Biological Observatory (DBO), a multi-agency program in the Arctic.

Daily maps of sea ice concentrations using the enhanced NASA Team (NT2) algorithm derived using SSM/I data. Reference: Markus, T. and D.J. Cavalieri, An enhancement of the NASA Team sea ice algorithm, IEEE Trans. Geoscience Remote Sensing, 38, 1387-1398, 2000.