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.
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.'
The Aura Validation Data Center (AVDC) is a centralized, long-term, archive for validation data hosted by the Atmospheric Chemistry and Dynamics Branch at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) in Greenbelt, Maryland.
The CDDIS was established in 1982 as a dedicated data bank to archive and distribute space geodesy related data sets. Today, the CDDIS archives and distributes mainly Global Navigation Satellite Systems (GNSS, currently Global Positioning System GPS and GLObal NAvigation Satellite System GLONASS), laser ranging (both to artificial satellites, SLR, and lunar, LLR), Very Long Baseline Interferometry (VLBI), and Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) data for an ever increasing user community of geophysists.
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 Dark-Target (DT) satellite aerosol product delivers comprehensive aerosol loading data over land and ocean, along with aerosol property over ocean and diagnostic information. Available on various sensors onboarding both low earth orbit and geostationary satellites, DT aerosol products have been used to develop global and regional aerosol climatology, to study the interaction of aerosols with clouds and ocean ecosystems, and for air quality assessments and forecasts. Click here to see the Dark Target website
Deep Blue uses measurements made by satellite instruments orbiting the Earth to determine the amount of aerosols in the atmosphere, and the properties of those aerosols. 'Aerosols' is a catch-all term covering particles suspended in the atmosphere, including but not limited to desert dust, smoke, volcanic ash, industrial smog, and sea spray.
FLDAS is the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System. The FLDAS is a custom instance of the NASA Land Information System (LIS) that has been adapted to work with domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing country settings.
GEODYN is used extensively for satellite orbit determination, geodetic parameter estimation, tracking instrument calibration, satellite orbit prediction, as well as for many other items relating to applied research in satellite geodesy using virtually all types of satellite tracking data.
The goal of the Global Land Data Assimilation System (GLDAS; http://ldas.gsfc.nasa.gov) is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes (Rodell et al., 2004a).
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.
We have developed wetness/drought indicator maps for shallow groundwater and surface and root zone soil moisture. The maps integrate data from multiple ground and space based observing systems, including NASA's Gravity Recovery and Climate Experiment (GRACE) satellite mission.
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
Rainfall-triggered landslides affect nearly every state in the U.S. and every country in the world, causing significant economic damage and resulting in thousands of fatalities each year. Characterizing and modeling these hazards over large scales is challenging due to the fairly small areas over which they typically occur. A new website has been developed to provide a regional and global perspective on rainfall-triggered landslides.
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).
The Earth as a whole responses to external forces as an elastic body. Putting additional mass on the Earth's surface causes crust deformation. Changes of loading mass result in variable displacements of Earth's surface.
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 NASA-USDA Global soil moisture data provides soil moisture information across the globe at 0.25°x0.25°spatial resolution.
NASA’s Energy and Water Cycle Study (NEWS) program supported an assessment of the state of the global water and energy cycles at the start of the millennium, based on data from the most advanced space and ground based measurement systems and output from observation-integrating models.
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.
The datasets below contain sea surface salinity retrieved by NASA’s Aquarius instrument collocated with in situ measurements by the Argo network of free drifting profiling floats. Sea surface salinity for Argo is defined as the shallower measurements reported by an Argo float as long as that measurement was reported for a depth of 10 m or less. Aquarius SSS, derived from L-band radiometry, are representative of the first few centimeters of the ocean surface layer.
Satellite laser ranging (SLR) tracking data provides more than four decades of measurements useful for estimating the long wavelength components of time-variable gravity, including C20 and C30. The estimation of these gravity coefficients with SLR has been critical to the success of the GRACE and GRACE-FO missions. GSFC routinely provides estimates of the gravity coefficients up to degree and order 5.
THOR data is usually visualized in two ways. The two examples below are from the March 2002 THOR Validation Campaign that took place over Oklahoma.
