This ITS_LIVE data set, part of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, contains monthly, 120 m resolution ice masks for the Greenland Ice Sheet from 1972 to 2022. The presence of ice was determined from 237,556 manually and AI-derived terminus positions acquired by satellite optical and radar observations. Months with no observations have been gap-filled using past and future observations of terminus positions and advance rates constrained by the average flow speed of the glacier.

Animations are also available for 206 catchments that show how the ice front positions have changed over the course of the time series and can be used as a quality control check.

This ITS_LIVE data set, part of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, consists of 240 m Antarctic Ice Sheet extent masks at roughly annual resolution from 1997 through 2021. The ice masks were generated by combining data acquired by multiple satellite-borne optical, thermal, and radar sensors. The ice thickness and velocity data used to determine the presence of ice are also provided.

The MCD19A3D Version 6.1 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Bidirectional Reflectance Distribution Function (BRDF) Model Parameters gridded Level 3 product. Output daily at 1 kilometer (km) resolution, the Multi-angle Implementation of Atmospheric Correction (MAIAC) MCD19A3D product provides three coefficients (weights) of the RossThick/Li-Sparse (RTLS) BRDF model that can be used to describe the anisotropy of each pixel. The retrievals represent cloud-free and low aerosol conditions.

When snow is detected, gap-filled snow grain size and sub-pixel snow fraction are computed. The gap-filling process retains the parameter in MAIAC’s memory for each grid cell until updated with the latest cloud-free observation. The number of days since the last update is provided in a separate layer.

Over snow-free land, MAIAC also reports gap-filled Normalized Difference Vegetation Index (NDVI) at 1 km resolution and gap-filled Nadir BRDF-Adjusted Reflectance (NBAR) at 250 m resolution in the red and near-infrared (NIR) bands.

The MCD19A3 BRDF Model Parameters product contains the following Science Dataset (SDS) layers: RTLS isotropic kernel parameter (Kiso) for bands 1-8, the RTLS volumetric kernel parameter (Kvol) for bands 1-8, RTLS geometric kernel parameter (Kgeo) for bands 1-8, three snow parameters, NDVI, NBAR, and three separate layers for the number of days since last update to current day.

Validation at stage 1 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) has been achieved for the MCD19A3 data product. Further details regarding MODIS land product validation for MCD19 data products are available from the MODIS Land Team Validation site (https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MOD19).

Improvements/Changes from Previous Versions
* The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017.
* A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).
* The MCD19 Version 6.1 products have added 250 m resolution bands.
* The previous BRDF product (MCD19A3) was reported once every eight days and the new MCD19A3D is a daily product.
* MCD19A3D introduces gap-filled NDVI and gap-filled 250 m NBAR.
* Snow Fraction, Snow Fit, and Snow Grain size layers were moved from MCD19A1 to the MCD19A3D.
* There are four additional Climate Modeling Grid (CMG) products: MCD19A1CMGL, MCD19A1GO, MCD19A2CMG, and MCD19A3CMG.

This dataset provides estimates of trends in temperature, moisture, and vegetation changes over the circumpolar Arctic. Time series trends were measured by the Theil-Sen slope and associated p-values for a variety of variables including 2-meter air temperature, precipitation, soil moisture, non-frozen season days, permafrost active layer thickness, snow cover, vapor pressure deficit, land surface water fraction, normalized difference vegetation index (NDVI), and vegetation optical depth. Trends were measured annually and over specific seasons of spring (March to May), summer (June to August), autumn (September to November) and winter (December to February), and for the 1980-2020 and 1997-2020 time periods, depending on the variable and original data availability. Emerging hotspots of change were identified for the same variables and seasons, but only over the 1997-2020 period. In addition, a multivariate ranking was used to create combined hotspot layers to show areas of substantial changes in the thermal environment, moisture, and vegetation; these themes reflect landscape changes considered to be detrimental (e.g., a threat) to ecosystems and human populations. Ancillary files provide the boundaries of study regions, Brown permafrost regions, and a land cover product. The data are provided in cloud optimized GeoTIFF (COG) and shapefile formats.

This data set reports monthly, gridded winter sea ice thickness across the Arctic Ocean. Sea ice thickness is estimated using ATLAS/ICESat-2 L3A Sea Ice Freeboard (ATL10) Version 6 data and NASA Eulerian Snow On Sea Ice Model (NESOSIM) snow loading.

This International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data set, ISLSCP II Global Sea Ice Concentration, is based on the Goddard Space Flight Center (GSFC) Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellites Program (DMSP) Special Sensor Microwave/Imager (SSM/I) Passive Microwave Data. This data set contains four zip files which includes sea ice concentration (in percentage of ocean area covered by sea ice), table data and map data. These original data were re-gridded by the National Snow and Ice Data Center (NSIDC) from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter, half and one degree spatial resolutions in latitude/longitude. The ISLSCP II staff have taken the one degree resolution original data provided by the Principal Investigator and created global maps of monthly sea ice concentration on a global one degree grid using the latitude and longitude coordinates that were provided. Individual monthly files were created and written to the ASCII format. The re-gridded one degree original data were also adjusted to match the one degree ISLSCP II land/water mask.

The Randolph Glacier Inventory (RGI) is a global set of glacier outlines intended as a snapshot of the world’s glaciers outside of ice sheets. It provides a single outline for each glacier from approximately the year 2000, as well as a set of attributes and other relevant auxiliary information. Glacier outlines are distributed as Shapefiles. Hypsometric data and attributes (CSV files) and metadata (json) are also available. All RGI data are packaged both globally and by region (as defined by the Global Terrestrial Network for Glaciers (GTN-G) Glacier Regions).

The RGI is not suitable for measuring glacier-by-glacier rates of area change. However, it can be used to estimate glacier volumes; rates of elevation change at regional and global scales; and glacier responses to climatic forcing.

RGI version 7.0 was developed by the “Working Group on the Randolph Glacier Inventory (RGI) and its role in future glacier monitoring” of the International Association of Cryospheric Sciences (IACS). The glaciological community contributes glacier mapping data to the Global Land Ice Measurements from Space (GLIMS) database. A subset of the glacier outlines in GLIMS are then extracted and reprocessed to produce the RGI.

See the RGI documentation under "User Guide" (below) for more information.

This dataset provides global gridded information on lake surface area and open water CH4 emissions at a resolution of 0.25-degree x 0.25-degree for an annual climatology representative of the average conditions from 2003 to 2015. A compilation of flux data from 575 individual lake systems and 893 aggregated flux values were used, and each flux measurement was classified into one of seven ecoclimatic types. Ice-cover-regulated emission seasonality was derived from satellite microwave observations of ice cover phenology and freeze-thaw dynamics. Global lake area was determined from the merger of HydroLAKES and Climate Change Initiative Inland-Water (CCI-IW) remote-sensing data, and lakes were classified into ecoclimatic regions to facilitate linking these types with ecosystem-specific CH4 measurements in the flux compilation. Exploratory estimates of fluxes associated with ice melt and with spring and fall water-column turnover are also included. The data are provided in NetCDF format.

This data set contains hourly and daily meteorological data from 23 meteorological stations across Canada from January 1975 to January 1997. The surface meteorology parameters include: date, time, temperature, precipitation, snow, snow depth, sea level pressure, station pressure, dew point, wind direction, wind speed, dry and wet bulb temperature, relative humidity, cloud opacity and cloud amount.

The Randolph Glacier Inventory (RGI) is a global set of glacier outlines; it is intended as a snapshot of the world’s glaciers. This data set provides a single outline for each glacier and is produced in coordination with the Global Land Ice Measurements from Space (GLIMS) initiative. The RGI is not suitable for measuring glacier-by-glacier rates of area change, but can be used to estimate glacier volumes, rates of elevation change at regional and global scales, and cryospheric responses to climatic forcing.

Glacier mapping data are contributed to both GLIMS and the RGI from the glaciological community. RGI is produced by the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, a body of the International Association of Cryospheric Sciences (IACS). This data set is updated approximately annually.

Glacier outlines are distributed as Shapefiles. Hypsometric data (CSV files) and gridded auxiliary data (GeoTIFFs) are also available. All RGI data are packaged globally and by region, with regions based upon the Global Terrestrial Network for Glaciers.