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This article describes how to import passive microwave EASE-Grid brightness temperature data into ArcGIS. For importing EASE-Grid 2.0 data into ArcGIS, refer to How do I import EASE-Grid 2.0 snow cover and sea ice data into ArcGIS?

The following are instructions describing how to import sea ice binary files into ArcGIS. These instructions were tested with ArcMap 10.5 and 10.6. 1. Rename the Data File. In order to be able to import a Polar Stereographic sea ice concentration file into ArcGIS, you will need to: Rename the file extension, changing it from .bin to .bil Example: nt_20090115_f17_nrt_n.bin  to  nt_20090115_f17_nrt_n.bil

The following steps will work for all eight SNODAS variables in ArcGIS 10.0 or higher.

SMAP data files contain rich quality information that can be useful for many data users. The retrieval quality flag and surface flag bit values and interpretations are documented in the respective product Data Fields pages of the user guides for these data products Level-2 soil moisture product (SPL2SMP) spl2smp#retrieval_qual_flag spl2smp#surface_flag Go to the SPL2SMP data set landing page to review the user guide  

NASA Earthdata Search is a map-based web interface for discovering and ordering data using spatial and temporal filters. This article explains how to search for ICESat/GLAS data based on spatial and temporal constraints. Additionally, you can subset files based on spatial bounding box, parameter, and temporal range, as well as reformat the data to ASCII. 

We recommend using the Geospatial Data Abstraction Library (GDAL) or a GIS to reproject geoTIFF files. Here we outline command line or python options for using GDAL, and instructions for QGIS and ArcMap to reproject a geoTIFF into geographic lat/lon projection.

Each AE_L2A data file has a time stamp for each scan. The time array is stored as Vdata under the variable name, Time. a) Using the hdp tool, the Time array can be dumped into a text file using the following commands: hdp dumpvd –n Time input file > output file Example: hdp dumpvd -n Time AMSR_E_L2A_BrightnessTemperatures_V12_200206010011_D.hdf > time.txt Refer to The HDF Group for more information on the hdp tool.

"Freeboard" is a measure of the height of sea ice above the ocean surface. The geoid height field ("d_gdHt") cannot be effectively used as a proxy for sea level in order to estimate freeboard, because current models of the Earth's geoid are too coarse to account for the local variations in geoid height that ICESat/GLAS actually detects.

The instructions below will describe how to extract elevation in text format from GLAS HDF5 Altimetry data using the free open source tool HDFView. The following example was created using GLAS/ICESat L1B Global Elevation Data, Version 34 (GLAH06), but this method can be applied to the other GLAS HDF5 Altimetry data as well. Data format: HDF5 Software: HDFView version 3.1.0 Operating System/Playform: Windows/PC (not tested on macOS)

There are several places you can find example code and other resources to read SMAP data in MATLAB, Python, IDL, and NCL:

The HDF Group has example code for access and visualization of MODIS, GLAS HDF5, AMSR-E, and NISE data in MATLAB, IDL, Python, and NCL. Go to HDF Group example code >

Analysis of altimetric data acquired by the GLAS instrument requires accurate determination of the laser spot location on the Earth's surface (ice, land, water, clouds) or geolocation of the laser spot. The spot location with respect to the Earth's center of mass (geocenter) is determined by both the orbital location of GLAS in an appropriate reference frame and the direction of the laser beam described in the same reference frame.

Data products from VIIRS are created to be similar to MODIS data products to ensure the continuity needed for the development of snow and sea ice climate records beyond the life expectancy of MODIS. The temporal resolution and spatial extent are identical in MODIS and VIIRS. A benefit of VIIRS snow and sea ice products, however, is the higher spatial resolution when compared to similar MODIS products (375m vs. 500m for snow and 375m/750m vs. 1000m for sea ice, respectively).

For ICESat/GLAS mission data, the elevation of the surface at each laser footprint is the height of the spacecraft minus the measured distance to the surface. A standard parameterization is used to calculate surface elevation for ice sheets, oceans, and sea ice, using the elevation of the maximum peak and no more than two Gaussian functions with a minimum spacing of 30 ns (4.5 m) between Gaussian centers. For land elevations, the centroid of the return signal is used; a maximum of six Gaussians is allowed with 5 ns (75 cm) minimum spacing.

NOAA@NSIDC data recently transitioned to HTTPS. The directory structure has NOT changed, but the beginning of the URL has changed from: ftp://sidads.colorado.edu/pub/DATASETS/ to: https://noaadata.apps.nsidc.org/NOAA/

This tutorial describes how to access data via FTP using FTP client, command line, wget, and Python.

Currently three NOAA@NSIDC data sets are available in NOAA's PolarWatch Data Catalog. Please note that in the catalog the Climate Data Record (CDR) data sets are split up into Antarctic and Arctic data sets:

There are external Jupyter notebooks available that can be used to search for GrIMP products and incorporate them into a new QGIS project:

This article illustrates the how to convert NetCDF variables to single-band GeoTIFFs. You will need to have the Geospatial Data Abstraction Library (GDAL, http://gdal.org/) installed on your system before continuing. Once you have acquired the NetCDF file of the tile(s) you are interested in and have GDAL installed, you may execute the following command:  gdal_translate NETCDF:"Input_FileName.nc":variable_name Output_FileName.tif

This article describes how to convert the u (horizontal) and v (vertical) components from the ice motion data set to East and North components on the Earth's surface. Instructions for both the Northern and Southern Hemispheres are described below: Northern Hemisphere The latitudes and longitudes for the Northern Hemisphere are shown in Figure 1.