Data Tools

Explore web services, interactive tutorials, and other tools to access and work with NSIDC data

There are many ways to access and work with NSIDC data to accommodate a wide diversity of users. Use the filter menu to explore and narrow down your options. Note that the list defaults to show our Featured tools first, however, you have more options in the Sort by menu.

  • To see which tools are available for which data sets, you must go to a specific data set landing page. On the landing page under Data Access and Tools, you will see data-set specific tools to access and work with the data.
  • Once you are ready to find a data set, explore our data catalog.
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Learn how to discover, access, subset, and visualize Arctic sea ice data from Python-based Jupyter Notebooks. Tutorial comes with open-source libraries to harmonize sea ice height from ICESat-2, and ice surface temperature from MODIS.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
View Metadata
Customization Capabilities:
spatial subsetting
temporal subsetting
variable subsetting
reprojection
 

Download data, and explore data coverage and customization using the Python-based Jupyter Notebook.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
View Metadata
Customization Capabilities:
reprojection
spatial subsetting
temporal subsetting
variable subsetting
 

Notebook for streaming cloud-hosted ICESat-2 ATL15 (Gridded Antarctic/Arctic Land Ice Height) to calculate dh/dt trends.
Type: Downloadable Software

Demonstrates using the earthaccess python package to search for and directly access cloud-hosted ICESat-2 data from an Amazon Compute Cloud (EC2) instance. This python-based Jupyter notebook uses Land Ice Height (ATL06) granules as an example.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
View Metadata

Utilize the Jupyterbook for the latest Hackweek virtual event and learn about the ICESat-2 satellite, data products, data-access tools, and more. Access past hackwork tutorials from the ICESat-2 Hackweek Github Organization listed in the Quick Links.
Supported software languages:
Python
Type: Downloadable Software
View Metadata
Customization Capabilities:
spatial subsetting
temporal subsetting
variable subsetting
 

Search and select Greenland Ice Mapping Project GIMP data at NSIDC, guided by a Python-based Jupyter Notebook. Build a QGIS project file from the search results. View data remotely if desired.
Supported software languages:
Python
Example QGIS projects
Type: Downloadable Software
Last updated:

Spatially and temporally filter Greenland Ice Mapping Project (GIMP) image and velocity data, guided by a Python-based Jupyter Notebook. Spatially subset data and download in NetCDF format. This tool creates an interactive plot of time series data at selected points.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
Customization Capabilities:
spatial subsetting
variable subsetting
data reformatting
 

Search for and download NSIDC DAAC data using the earthaccess python package. This python-based Jupyter notebook also demonstrates geospatial operations to crop and resample one GeoTIFF based on the extent and pixel size of another GeoTIFF, with the end goal of plotting one on top of the other. Two data sets from the NASA MEaSUREs program are used as examples.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
View Metadata
Customization Capabilities:
spatial subsetting
resampling
 

Download, bulk download, or visualize SMAP L3 and L4 data, guided by Python-based Jupyter Notebooks. These notebooks include examples of applying recommended quality flags for SMAP data.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
View Metadata

A Python-based Jupyter Notebook demonstrating how to access and visualize coincident snow data from the NSIDC DAAC across in-situ, airborne, and satellite platforms from NASA's SnowEx, ASO, and MODIS data sets, respectively.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
View Metadata
Customization Capabilities:
data reformatting
reprojection
spatial subsetting
 
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