AMSR-E/Aqua 5-Day L3 Global Snow Water Equivalent EASE-Grids, Version 2
Data set id:
AE_5DSno
DOI: 10.5067/AMSR-E/AE_5DSNO.002
This is the most recent version of these data.
Version Summary
Version Summary
Overview
These Level-3 Snow Water Equivalent (SWE) data sets contain SWE data and quality assurance flags mapped to Northern and Southern Hemisphere 25 km Equal-Area Scalable Earth Grids (EASE-Grids).
Parameter(s):
SNOW WATER EQUIVALENT
Platform(s):
AQUA
Sensor(s):
AMSR-E
Data Format(s):
HDF-EOS2
Temporal Coverage:
20 June 2002 to 3 October 2011
Temporal Resolution:
- 5 day
Spatial Resolution:
- 25 km
- 25 km
Spatial Reference System(s):
NSIDC EASE-Grid North
EPSG:3408
NSIDC EASE-Grid South
EPSG:3409
Spatial Coverage:
N:
90
S:
-90
E:
180
W:
-180
Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.
Data Access & Tools
A free NASA Earthdata Login account is required to access these data. Learn More
Documentation
User Guide
ATBDs
General Resources
Quality Assessment Reports
Help Articles
General Questions & FAQs
This article describes what customizing services are available for AMSR-E data using Earthdata Search.
How to Articles
Many NSIDC DAAC data sets can be accessed using the NSIDC DAAC's Data Access Tool. This tool provides the ability to search and filter data with spatial and temporal constraints using a map-based interface.Users have the option to
To convert HDF5 files into binary format you will need to use the h5dump utility, which is part of the HDF5 distribution available from the HDF Group. How you install HDF5 depends on your operating system.
All data from the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) can be accessed directly from our HTTPS file system, using wget or curl. Basic command line instructions are provided in the article below.
This article highlights the NSIDC DAAC data sets available with customization options and outlines a workflow for searching, ordering, and customizing data in NASA Earthdata Search. This approach is ideal for users who want to download data to their local machine.