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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

ICESat Spacecraft Pointing Support Study Grant

The Geodetic Laser Altimeter System (GLAS) mission is designed to measure changes in the elevations of the polar ice sheets. The ICESat satellite will carry the GLAS altimeter, and will have a nominal orbit altitude of 600 km and orbit inclination of 94deg. The groundtrack repeat period is 182 days and will be maintained to less than 1 km at the equator via routine orbit adjustments. Science requirements for the GLAS mission demand that the laser altimeter be pointed to within 50 meters of a predetermined reference groundtrack. As the actual ICESat groundtrack drifts away from the reference groundtrack, the attitude must be controlled such that the altimeter boresight is pointed, crosstrack, at the reference groundtrack. This orientation may be described by a rotation, theta, about the instantaneous geodetic local horizontal direction vector, which lies in the orbit plane and is oriented in the direction of motion of the satellite. The attitude is further complicated by requirements related to thermal and power considerations for various instruments, spacecraft components, and solar array orientation. In order to keep battery temperatures within the specified operating range, and maintain near normal pointing of the solar array with respect to the sunline direction vector as the orbit precesses relative to the sun, the satellite will be oriented in one of four fixed yaw modes. Each of these yaw modes depends upon the angle between the orbit plane and the sunline direction vector; this angle is designated Beta'. Table 1 shows the satellite yaw angle, Psi, for a given Beta' range. The angle Psi represents a rotation about the satellite z-axis, which points in the geodetic nadir direction; for Psi = 0deg the satellite x-axis points in the direction of motion.

Source record↗
NASA NTRS2004

ICESat Observations of Arctic Sea Ice: A First Look

Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin ice or open water) in the sea ice cover as well as to surface relief of old and first-year ice. The precision of the elevation estimates, measured over relatively flat sea ice, is approx. 2 cm Using the thickness of thin-ice in recent openings to estimate sea level references, we obtain the sea-ice free-board along the altimeter tracks. This step is necessitated by the large uncertainties in the time-varying sea surface topography compared to that required for accurate determination of free-board. Unknown snow depth introduces the largest uncertainty in the conversion of free-board to ice thickness. Surface roughness is also derived, for the first time, from the variability of successive elevation estimates along the altimeter track Overall, these ICESat measurements provide an unprecedented view of the Arctic Ocean ice cover at length scales at and above the spatial dimension of the altimeter footprint.

Kwok, Ron↗
NASA NTRS2004

Recent Results in ICESat Geolocation Parameter Calibration from Range Residual Analysis

The Ice, Cloud and land Elevation Satellite (ICESat), launched on January 12, 2003, carries the Geoscience Laser Altimeter System (GLAS), which has a primary measurement of short-pulse laser-ranging to the Earths surface at 1064 nm wavelength at a rate of 40 pulses per second. The instrument has collected (at the time of this writing) over 540 million observations of the Earth's surface including precise elevation measurements of the ice sheets, sea ice roughness and thickness, ocean and land surface elevations and surface reflectivity. The accurate geolocation of GLASs surface returns, the spots from which the laser energy reflects on the Earths surface, is a critical issue in the scientific application of these data. Pointing, ranging, timing and orbit errors must be compensated to accurately geolocate the laser altimeter surface returns. Towards this end, the laser range observations can be fully exploited in an integrated residual analysis to accurately calibrate these geolocation/instrument parameters. The ICESat laser altimeter data have been simultaneously processed as direct altimetry from ocean sweeps and around-the-world scans along with dynamic crossovers in order to calibrate pointing ranging and timing. The analysis has resolved complex time varying signal resulting from thermal variations of instrument pointing and boresite shadowing. The calibration methodology and current calibration results are discussed along with future efforts and current geolocation accuracies.

Luthcke, Scott B.↗
NASA NTRS2005

The Beauty and Complexity of the Brunt Ice Shelf from MOA and ICESat

Beginning in February 2003, NASA's Ice, Cloud, and land Elevation Satellite (ICESat) has determined surface elevations from approx. 86degN to 86degS latitude. To date, altimetry data have been acquired in a series of observation periods in repeated track patterns using all three Geoscience Laser Altimeter System (GLAS) lasers. This paper will focus on ice shelf elevation data that were obtained in 2003 across the Brunt Ice Shelf and the Stancomb-Wills Ice Tongue. Integrating the altimetry with the recently available MODIS Mosaic of Antarctica (MOA), quantifies the relative accuracy and precision of the resulting ice shelf elevations. Furthermore, the elevation data was processed onto an elevation grid, by regional interpolation across the area s complex glacial features only. Ice thickness estimation from the altimetry of the floating ice is discussed. ICESat operates at 40Hz and its elevation data is obtained every 172m along track. These elevations have a relative accuracy of about 14cm based on the standard deviation of low-slope crossover differences and a precision of close to 2cm for the Laser 2a, Release 21, GLA12 data used here.

Humbert, Angelika↗
NASA NTRS2006

On Orbit Receiver Performance Assessment of the Geoscience Laser Altimeter System (GLAS) on ICESAT

The GLAS instrument on the NASA's ICESat mission has provided over a billion measurements of the Earth surface elevation and atmosphere backscattering at both 532 and 1064-nm wavelengths. The receiver performance has stayed nearly unchanged since ICESat launch in January 2003. The altimeter receiver has achieved a less than 3-cm ranging accuracy when excluding the effects of the laser beam pointing angle determination uncertainties. The receiver can also detect surface echoes through clouds of one-way transmission as low as 5%. The 532-nm atmosphere backscattering receiver can measure aerosol and clouds with cross section as low as 1e-7/m.sr with a 1 second integration time and molecular backscattering from upper atmosphere with a 60 second integration time. The 1064-nm atmosphere backscattering receiver can measure aerosol and clouds with a cross section as low as 4e-6/m.sr. This paper gives a detailed assessment of the GLAS receiver performance based on the in-orbit calibration tests.

Sun, Xiaoli↗
NASA NTRS2004

ICESat Observations of Arctic Sea Ice: A First Look

Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin ice or open water) in the sea ice cover as well as to surface relief of old and first-year ice. The precision of the elevation estimates, measured over relatively flat sea ice, is approx. 2 cm. Using the thickness of thin-ice in recent openings to estimate sea level references, we obtain the sea-ice freeboard along the altimeter tracks. This step is necessitated by the large uncertainties in the sea surface topography compared to that required for accurate determination of freeboard. Unknown snow depth introduces the largest uncertainty in the conversion of freeboard to ice thickness. Surface roughness is also derived, for the first time, from the variability of successive elevation estimates along the altimeter track. Overall, these ICESat measurements provide an unprecedented view of the Arctic Ocean ice cover at length scales at and above the spatial dimension of the altimeter footprint of approx. 70 m.

Arctic Ocean↗
NASA NTRS2006

Merging IceSAT GLAS and Terra MODIS Data in Order to Derive Forest Type Specific Tree Heights in the Central Siberian Boreal Forest

Mapping of boreal forest's type, biomass, and other structural parameters are critical for understanding of the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. We believe the nature of the forest structure information available from MISR and GLAS can be used to help identify forest type, age class, and estimate above ground biomass levels beyond that now possible with MODIS alone. The ground measurements will be used to develop relationships between remote sensing observables and forest characteristics and provide new information for understanding forest changes with respect to environmental change. Lidar is a laser altimeter that determines the distance from the instrument to the physical surface by measuring the time elapsed between the pulse emission and the reflected return. Other studies have shown that the returned signal may identify multiple returns originating from trees, building and other objects and permits the calculation of their height. Studies using field data have shown that lidar data can provide estimates of structural parameters such as biomass, stand volume and leaf area index and allows remarkable differentiation between primary and secondary forest. NASA's IceSAT Geoscience Laser Altimeter System (GLAS) was launched in January 2003 and collected data during February and September of that year. This study used data acquired over our study sites in central Siberia to examine the GLAS signal as a source of forest height and other structural characteristics. The purpose of our Siberia project is to improve forest cover maps and produce above-ground biomass maps of the boreal forest in Northern Eurasia from MODIS by incorporating structural information inherent in the Terra MISR and ICESAT Geoscience Laser Altimeter System (GLAS) instruments. A number of forest cover classifications exist for the boreal forest. We believe the limiting factor in these products is the lack of structural information, particularly in the vertical dimension. The emphasis of this project is to improve upon satellite maps of boreal forest structure parameters (i.e. height and biomass) using temporal, multi-angle, and vertical profile information of GLAS data. The existing and near future lidar data is useful for demonstrating these techniques and pursuing current estimates. Future lidar missions may be several years in the future, so we will work other new data sets that may aide in biomass estimates such as ALOS PALSAR We will continue this work to produce an accurate map of current above ground forest phytomass/carbon storage possible for the study area. We plan to develop, test, and integrate remote sensing methods for extracting forest canopy structure measures. We are compiling our field measurements and will compare them with the remote sensing methods where possible. We also be able to produce a realistic error bound on the remotely sensed carbon estimates.

Ranson, K. Jon↗
NASA NTRS2010

ICESat Observations of Seasonal and Interannual Variations of Sea-Ice Freeboard and Estimated Thickness in the Weddell Sea, Antarctica (2003-2009)

Sea-ice freeboard heights for 17 ICESat campaign periods from 2003 to 2009 are derived from ICESat data. Freeboard is combined with snow depth from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) data and nominal densities of snow, water and sea ice, to estimate sea-ice thickness. Sea-ice freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of growth and decay of the Weddell Sea (Antarctica) pack ice. During October-November, sea ice grows to its seasonal maximum both in area and thickness; the mean freeboards are 0.33-0.41 m and the mean thicknesses are 2.10-2.59 m. During February-March, thinner sea ice melts away and the sea-ice pack is mainly distributed in the west Weddell Sea; the mean freeboards are 0.35-0.46 m and the mean thicknesses are 1.48-1.94 m. During May-June, the mean freeboards and thicknesses are 0.26-0.29 m and 1.32-1.37 m, respectively. The 6 year trends in sea-ice extent and volume are (0.023+/-0.051) x 10(exp 6)sq km/a (0.45%/a) and (0.007+/-1.0.092) x 10(exp 3)cu km/a (0.08%/a); however, the large standard deviations indicate that these positive trends are not statistically significant.

Yi, Donghui↗
NASA NTRS2010

Overview of Ice-Sheet Mass Balance and Dynamics from ICESat Measurements

The primary purpose of the ICESat mission was to determine the present-day mass balance of the Greenland and Antarctic ice sheets, identify changes that may be occurring in the surface-mass flux and ice dynamics, and estimate their contributions to global sea-level rise. Although ICESat's three lasers were planned to make continuous measurements for 3 to 5 years, the mission was re-planned to operate in 33-day campaigns 2 to 3 times each year following failure of the first laser after 36 days. Seventeen campaigns were conducted with the last one in the Fall of 2009. Mass balance maps derived from measured ice-sheet elevation changes show that the mass loss from Greenland has increased significantly to about 170 Gt/yr for 2003 to 2007 from a state of near balance in the 1990's. Increased losses (189 Gt/yr) from melting and dynamic thinning are over seven times larger'than increased gains (25 gt/yr) from precipitation. Parts of the West Antarctic ice sheet and the Antarctic Peninsula are losing mass at an increasing rate, but other parts of West Antarctica and the East Antarctic ice sheet are gaining mass at an increasing rate. Increased losses of 35 Gt/yr in Pine Island, Thwaites-Smith, and Marie-Bryd.Coast are more than balanced by gains in base of Peninsula and ice stream C, D, & E systems. From the 1992-2002 to 2003-2007 period, the overall mass balance for Antarctica changed from a loss of about 60 Gt/yr to near balance or slightly positive.

Zwally, H. Jay↗
NASA NTRS2011

Assessment of Cloud Screening with Apparent Surface Reflectance in Support of the ICESat-2 Mission

The separation of cloud and clear scenes is usually one of the first steps in satellite data analysis. Before deriving a geophysical product, almost every satellite mission requires a cloud mask to label a scene as either clear or cloudy through a cloud detection procedure. For clear scenes, products such as surface properties may be retrieved; for cloudy scenes, scientist can focus on studying the cloud properties. Hence the quality of cloud detection directly affects the quality of most satellite operational and research products. This is certainly true for the Ice, Cloud, and land Elevation Satellite-2 (lCESat-2), which is the successor to the ICESat-l. As a top priority mission, ICESat-2 will continue to provide measurements of ice sheets and sea ice elevation on a global scale. Studies have shown that clouds can significantly affect the accuracy of the retrieved results. For example, some of the photons (a photon is a basic unit of light) in the laser beam will be scattered by cloud particles on its way. So instead of traveling in a straight line, these photons are scattered sideways and have traveled a longer path. This will result in biases in ice sheet elevation measurements. Hence cloud screening must be done and be done accurately before the retrievals.

Yang, Yuekui↗
NASA NTRS2018

ICESat-2 Photon Classification: Finding Signal Photons in the ATL03 Geolocated Photon Data Product

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 1014 photons 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↗
NASA NTRS2019

Assessment of Altimetry Using Ground-Based GPS Data from the 88S Traverse, Antarctica, in Support of ICESat-2

We conducted a 750 km kinematic GPS survey, referred to as the 88S Traverse, based out of South Pole Station, Antarctica, between December 2017 and January 2018. This ground-based survey was designed to validate space-borne altimetry and airborne altimetry developed at NASA. The 88S Traverse intersects 20% of the ICESat-2 satellite orbits on a route that has been flown by two different Operation IceBridge airborne laser altimeters: the Airborne Topographic Mapper (ATM; 26 October 2014) and the University of Alaska Fairbanks (UAF) Lidar (30 November and 3 December 2017). Here we present an overview of the ground-based GPS data quality and a quantitative assessment of the airborne laser altimetry over a flat section of the ice sheet interior. Results indicate that the GPS data are internally consistent (1:1+- 4:1 cm). Relative to the ground-based 88S Traverse data, the elevation biases for ATM and the UAF lidar range from -9:5 to 3.6 cm, while surface measurement precisions are equal to or better than 14.1 cm. These results suggest that the ground-based GPS data and airborne altimetry data are appropriate for the validation of ICESat-2 surface elevation data.

Brunt, Kelly M.↗
NASA NTRS2020

Arctic Snow Depth and Sea Ice Thickness From ICESat‐2 and CryoSat‐2 Freeboards: A First Examination

The snow layer atop Arctic sea ice is an important component of the climate system. In winter, the insulating effects of snow slow the rate of ice growth. In spring, the onset of ice surface melt is delayed until the highly reflective snow layer disappears. During summer, meltwater from snow collects in depressions to form melt ponds, which enhances the absorption of solar radiation leading to more rapid surface warming. Presently, there are no routine measurements of snow depth suitable for assessing the impact of climate changes on the precipitation and accumulation of snow on sea ice.Our current understanding of snow depth is limited and has been based on field measurements conducted in the middle of last century and from airborne surveys conducted over the last decade. In this paper, we combine the measurements from two altimetry missions (ICESat‐2 and CryoSat‐2) to calculate snow depth over the entire Arctic Ocean. ICESat‐2 (a lidar) and CryoSat‐2 (a radar) measure the heights to the top and bottom of the snow layer, respectively. Differencing the two heights provides an estimate of the thickness of the snow layer. This paper describes this novel approach and an assessment of the snow depth estimates.

R. Kwok↗
NASA NTRS2021

ICESat-2 Pointing Calibration and Geolocation Performance

ICESat-2 science requirements are dependent on the accurate real-time pointing control (i.e. geolocation control) and post-processed geolocation knowledge of the laser altimeter surface returns. Pre-launch pointing alignment errors and post-launch pointing alignment variation result in large geolocation errors that must be calibrated on orbit. In addition, the changing sun-orbit geometry causes thermal-mechanical forced laser frame alignment variations at the orbit period and trends from days, weeks and months. Early mission analysis computed precise post-launch laser beam alignment calibration. The alignment calibration was uploaded to the spacecraft and enabled the pointing control performance to achieve 4.4 ± 6.0 m, a significant improvement over the 45 m (1 σ) mission requirement. Laser frame alignment calibrations are used to reduce the alignment bias and time variation, as well as the orbital variation contributions to geolocation knowledge error from 6 m to 1.7 m (1 σ). Relative beam alignment of the six beams is calibrated and shown to contribute between 0.5 ± 0.1 m and 2.4 ± 0.2 m of remaining geolocation knowledge error. Independent geolocation assessment based on comparison to high-resolution digital elevation models agrees well with the calibration geolocation error estimates. The analysis demonstrates the ICESat-2 mission is performing far better than its geolocation knowledge requirement of 6.5 m (1 σ) after the laser frame alignment bias variation and orbital variation calibrations have been applied. Remaining geolocation error is beam dependent and ranges from 2.5 m for beam 6 to 4.4 m for beam 2 (mean + 1 σ).

S. B. Luthcke↗
NASA NTRS2021

ICESat-2 Precision Orbit Determination

The ICESat-2 Precision Orbit Determination (POD) system computes the precise position of the laser altimeter instrument in inertial space, a measurement necessary for accurate geolocation of individual photon surface returns. ICESat-2 POD solutions are generated by the reduction of Global Positioning System (GPS) double-difference carrier phase observable residuals with NASA Goddard Space Flight Center's GEODYN software. Independent satellite laser ranging (SLR) measurements are withheld from the POD solutions and used as an independent arbiter of POD performance. Measurement model updates in the form of estimated GPS antenna phase center and satellite laser ranging retro-reflector tracking point offset vectors as well as a GPS antenna phase center variation map have led to significant improvement in POD performance. GPS residual analysis and orbit precision analysis show no significant anomalous temporal or geographic POD performance issues. The independent SLR residual analysis indicates that POD solutions have achieved a radial orbit accuracy just below 1.5 cm, thus exceeding the mission radial orbit accuracy requirement of 3.0 cm by more than a factor of 2. Future POD processing updates have been identified and will lead to even further improvements in POD performance.

T. C. Thomas↗
NASA NTRS2020

Decay of the Snow Cover Over Arctic Sea Ice From ICESat‐2 Acquisitions During Summer Melt in 2019

From the onset of melt in early June, corresponding declines in Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) freeboard and surface albedo can be seen over the entire Arctic sea ice cover. In the 2019 summer, area‐averaged freeboard decreased from 34 cm prior to melt to a minimum of 12 cm in August while the area‐averaged albedo decreased from ~0.7 to 0.38 for the same period. Calculations using ICESat‐2 freeboards and modeled ice thickness from Pan‐Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) give area‐averaged snow depths ranging from 17 cm prior to melt to 3 cm in August over seasonal ice and from 34 to 4 cm over multiyear ice. Mean rates of snow ablation (including evaporation) in mid‐June were as high as 2 cm/day, comparable to field records from other years. Increases in freeboard after mid‐August in the high latitude (>80°N) multiyear ice cover, north of the Greenland coast, are likely due to earlier freeze‐up and snow accumulation in these regions with shorter melt seasons.

R Kwok↗
NASA NTRS2021

ICESat-2 Atmospheric Channel Description, Data Processing and First Results

The Advanced Topographic Laser Altimeter System (ATLAS) was launched aboard the Ice Cloud and land-Elevation Satellite-2 (ICESat-2) satellite in September 2018. ATLAS is a single wavelength (532 nm) lidar system designed to acquire high resolution measurements of the earth's surface while also obtaining atmospheric backscatter from molecules, clouds, and aerosols. Because ATLAS is optimized for altimetry, the atmospheric data acquired is unique in many respects and requires non-standard analysis techniques. For example, the high repetition rate laser limits the vertical extent of the profiles to just 14 km and causes atmospheric scattering from above 15 km to be added to the scattering in the lower 0–14 km profile. In addition, the limited vertical range of the acquired profiles renders it difficult to compute the magnitude of the solar background and hinders the application of standard calibration techniques. Despite these limitations, methods have been developed to successfully produce data products that have value to the atmospheric community for cloud and aerosol research and are currently available at the National Snow and Ice Data Center (NSIDC). In this paper we describe the ICESat-2 atmospheric channel and the methods used to process the ATLAS raw photon count data to obtain calibrated backscatter and higher level products such as layer heights and type, blowing snow, column optical depth and apparent surface reflectance.

Stephen P Palm↗
NASA NTRS2021

ICESat-2 Pointing Calibration and Geolocation Performance

ICESat-2 science requirements are dependent on the accurate real-time pointing control (i.e., geolocation control) and postprocessed geolocation knowledge of the laser altimeter surface returns. Prelaunch pointing alignment errors and postlaunch pointing alignment variation result in large geolocation errors that must be calibrated on orbit. In addition, the changing sun-orbit geometry causes thermal-mechanical forced laser frame alignment variations at the orbit period and trends from days, weeks, and months. Early mission analysis computed precise postlaunch laser beam alignment calibration. The alignment calibration was uploaded to the spacecraft and enabled the pointing control performance to achieve 4.4 ± 6.0 m, a significant improvement over the 45 m (1 σ) mission requirement. Laser frame alignment calibrations are used to reduce the alignment bias and time variation, as well as the orbital variation contributions to geolocation knowledge error from 6 to 1.7 m (1 σ). Relative beam alignment of the six beams is calibrated and shown to contribute between 0.5 ± 0.1 m and 2.4 ± 0.2 m of remaining geolocation knowledge error. Independent geolocation assessment based on comparison to high-resolution digital elevation models agrees well with the calibration geolocation error estimates. The analysis demonstrates the ICESat-2 mission is performing far better than its geolocation knowledge requirement of 6.5 m (1 σ) after the laser frame alignment bias variation and orbital variation calibrations have been applied. Remaining geolocation error is beam dependent and ranges from 2.5 m for beam 6 to 4.4 m for beam 2 (mean + 1 σ).

S B Luthcke↗