• On Wednesday, June 12 from 9:00 a.m. to 12:00 p.m. (US Mountain Time), the following data collections may not be available due to a planned system maintenance: ASO, AMSR Unified, AMSR-E, Aquarius, High Mountain Asia, IceBridge, ICESat/GLAS, ICESat-2, LVIS, MEaSUREs, MODIS, Nimbus, SMAP, SnowEx, SSM/I-SSMIS and VIIRS. Users of the SMAP near real-time products should use the NASA LANCE HTTPS File System for data access. 

  • For a list of known issues with this product, see the Known Issues document under the Documentation section of the page.

ATLAS/ICESat-2 L1B Converted Telemetry Data, Version 6
Data set id:
ATL02
DOI: 10.5067/ATLAS/ATL02.006
This is the most recent version of these data.
Version Summary
The following changes were implemented in Version 6 of the data set:

  • Corrected the implementation of the computation of receiver sensitivity as a function of transmit/receive misalignment

  • Updated calibration data products that affect the computation of time of flight, i.e., delay line cell widths, receiver channel skews, and start skews.

Overview

This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.
Parameter(s):
ENGINEERING TELEMETRY ANCILLARY DATA
Platform(s):
ICESat-2
Sensor(s):
ATLAS
Data Format(s):
HDF5
Temporal Coverage:
13 October 2018 to present
Temporal Resolution:
  • Not applicable
Spatial Resolution:
  • not applicable
  • not applicable
Spatial Reference System(s):
WGS 84
EPSG:4326
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

Help Articles

General Questions & FAQs

This article covers frequently asked questions about the NASA NSIDC DAAC's Earthdata cloud migration project and what it means to data users.
This short article describes the customization services available for ICESat-2 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.
This guide will provide an overview of the altimetry measurements and data sets across the missions, as well as a guide for accessing the data through NASA Earthdata Search and programmatically using an Application Programming Interface (API).
The NASA Earthdata Cloud is the NASA cloud-based archive of Earth observations. It is hosted by Amazon Web Services (AWS). Learn how to find and access NSIDC DAAC data directly in the cloud.
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. 
NASA Earthdata Search is a map-based interface where a user can search for Earth science data, filter results based on spatial and temporal constraints, and order data with customizations including re-formatting, re-projecting, and spatial and parameter subsetting.
This webinar introduces the ICESat-2 mission and shows you how to explore, access and customize ICESat-2 data with the OpenAltimetry application, using NSIDC DAAC tools, and shows you how to subset, reformat and analyze the data using Python.