The ICESat-2 (Ice, Cloud and Land Elevation Satellite-2) photon-counting laser altimeter technology required the design and development of very sophisticated onboard algorithms to collect, store and downlink the observations. These algorithms utilize both software and hardware solutions for meeting data volume requirements and optimizing the science achievable via ICESat-2 measurements. Careful planning and dedicated development were accomplished during the pre-launch phase of the mission in preparation for the 2018 launch. Once on-orbit all of the systems and subsystems were evaluated for performance, including the receiver algorithms, to ensure compliance with mission standards and satisfy the mission science objectives. As the mission has progressed and the instrument performance and data volumes were better understood, there have been several opportunities to enhance ICESat-2’s contributions to earth observation science initiated by NASA and the ICESat-2 science community. We highlight multiple updates to the flight receiver algorithms, the onboard software for signal processing, that have extended ICESat-2’s data capabilities and allowed for advanced science applications beyond the original mission objectives.

This paper presents an assessment of the horizon-tal accuracy and precision of the laser altimetry observations collected by NASA’s ICESat-2 mission. We selected the terrain-matching method to determine the position of laser altimeter profiles within a precisely knownn surface, represented by a DEM. We took this classical approach a step further, approx-imated the DEM by planar surfaces and calculated the optimal position of the laser profile by minimizing the square sum of the elevation differences between reference DEMs and ICESat-2 profiles. We found the highly accurate DEMs of the McMurdo Dry Valleys, Antarctica, ideal for this research because of their stable landscape and rugged topography. We computed the 3D shift parameters of 379 different laser altimeter profiles along two reference ground tracks collected within the first two years of the mission. Analyzing these results revealed a total geolocation error (mean + 1 sigma) of 4.93 m for release 3 and 4.66 m for release 4 data. These numbers are the averages of the six beams, expressed as mean + 1 sigma and lie well within the mission requirement of 6.5 m.

NASA launched its second Earth observing laser altimeter in 2018 with mission objectives of studying the changes in our climate by monitoring global elevations, particularly in the polar regions. Since the mission is focused on generating accurate elevations and elevation change, the geolocation (or geodetic position) of the measurements are of upmost importance to each of the scientific disciplines supported by these observations. Geolocation validation is required to ensure that the mission is meeting its objectives with the appropriate level of geolocation accuracy. One validation technique uses small optical reflectors placed in a specific pattern along one or more satellite ground-tracks. The optics provide a unique signal back to the satellite that can be used to compare the geolocation of these returns in the data to the known position on the surface. Results of the position comparison indicate the measurement locations are accurate to within 3.5 m with a standard deviation of 1.6 m. They also provide a method for determining a representative footprint diameter using geometric analysis, which resulted in an average value of 10.9 m ±2.1 m.

The Advanced Topographic Laser Altimetry System (ATLAS) onboard the NASA Ice, Cloud and land Elevation Satellite-2 (ICESat-2) is the newest and most recent Earth observing satellite for global elevation studies. The primary objectives for ICESat-2 follow that of its predecessor, ICESat, and focus on providing cryospheric measurements to determine ice sheet mass balance, and monitor both sea ice thickness and extent. However, the global observations support secondary science objectives such as biomass estimation, inland water elevation, sea state height and aerosol concentrations. In all, ATLAS measurements support 7 along-track geophysical products with multiple gridded products to provide regional and global change detection for seasonal and annual cycles. Since the launch of ICESat-2, the instrument has operated nominally and collected more than a trillion measurements. This paper provides an overview of the mission, a description of the operational components that support the altimeter products for science discovery and on-orbit observatory performance.

ICESat-2 carries NASA’s next-generation laser altimeter, ATLAS, (Advanced Topographic Laser Altimeter System), designed to measure changes in ice sheet height, sea ice freeboard, and vegetation canopy height. ATLAS contains a photon-counting lidar which transmits green (532-nm) pulses at 10kHz. Each pulse is split into 3 pairs of beams (one strong and one weak). Approximately 1014photons per pulse travel from ATLAS through the atmosphere to reflect off the Earth’s surface. Some return back into the ATLAS telescope where they are recorded. Photons from sunlight and instrument noise at the same wavelength are also recorded. The flight software time tags all photons within a 500m to 6 km range window and generates histograms. Using the histograms, it selects a telemetry window which varies from 20m over flat surfaces to hundreds of meters over rougher terrain. ATL03 contains the time, height (relative to the WGS-84 ellipsoid), latitude and longitude of every photon within the telemetry window. The basic challenge is to determine which of these photons were reflected off the surface. We have developed an algorithm that identifies these signal photons and assigns a confidence level (low, medium, or high) to each signal photon based on the signal to noise ratio. We present an overview of the signal identification algorithm and show the results on actual ICESat-2 data over ice sheet, sea ice, vegetated, and water surfaces. Higher level ATLAS products work with aggregations of the photons in order to determine the ellipsoidal height of the Earth, canopy height and structure, and other quantities of geophysical interest.

Remote sensing from Earth-observing satellites is now providing valuable information about the ocean phytoplankton distributions. This paper presents the new ocean subsurface optical properties obtained from two space-based lidars: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite and the Advanced Topographic Laser Altimeter System (ATLAS) aboard Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) satellite. Obtaining reliable estimates of subsurface biomass necessitates removing instrument artifacts peculiar to each sensor; i.e., polarization crosstalk artifacts in the CALIOP signals and after pulsing effects arising from the ATLAS photodetectors. We then validate the lidar retrieved optical properties with MODerate-resolution Imaging Spectroradiometer (MODIS) ocean color measurements and autonomous biogeochemical Argo float profiles. Our results support the continued use of present and future spaceborne lidars to study the global plankton system and characterize its vertical structures in the upper ocean.

Two traverses have been conducted for validation of the NASA Ice, Cloud, and land Satellite 2 on the flat interiors of the Antarctic and Greenland ice sheets. GNSS data collected on three separate 88S Traverses intersect 20% of the ICESat-2 reference ground tracks and have height errors of 5.6 and 8.0 cm. GNSS data from the monthly Summit Traverse in Greenland have 0.9 cm of bias and 5.7 cm precision. Data from these traverses were used to assess heights from ICESat-2, CryoSat-2, and Airborne Topographic Mapper (ATM). ICESat-2 heights have better than ±2.9 cm bias and better than ±6.7 cm precision. ATM heights have better than 9.3 cm bias and better than ±9.6 cm precision. CryoSat-2 heights have more than 20 cm of bias and more than ±40 cm precision. These best-case results are from the ice-sheet interiors but provide a characterization of the quality of satellite and airborne altimetry.

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission has collected global surface elevation measurements for over three years. ICESat-2 carries the Advanced Topographic Laser Altimeter (ATLAS) instrument, which emits laser light at 532 nm, and ice and snow absorb weakly at this wavelength. Previous modeling studies found that melting snow could induce significant bias to altimetry signals, but there is no formal assessment on ICESat-2 acquisitions during the Northern Hemisphere melting season. In this work, we performed two case studies over the Greenland Ice Sheet to quantify volumetric scattering in ICESat-2 signals over snow. Elevation data from ICESat-2 was compared to Airborne Topographic Mapper (ATM) data to quantify bias. We used snow optical grain sizes derived from ATM and the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) to attribute altimetry bias to snowpack properties. For the first case study, the mean optical grain sizes were 340±65 µm (AVIRIS-NG) and 670±420 µm (ATM), which corresponded with a mean altimetry bias of 4.81±1.76 cm in ATM. We observed larger grain sizes for the second case study, with a mean grain size of 910±381 µm and biases of 6.42±1.77 cm (ICESat-2) and 9.82±0.97 cm (ATM). Although these altimetry biases are within the accuracy requirements of the ICESat-2 mission, we cannot rule out more significant errors over coarse-grained snow, particularly during the Northern Hemisphere melting season.