Surface topography of the Greenland Ice Sheet from satellite radar altimetry

Surface elevation maps of the southern half of the Greenland subcontinent are produced from radar altimeter data acquired by the Seasat satellite. A summary of the processing procedure and examples of return waveform data are given. The elevation data are used to generate a regular grid which is then computer contoured to provide an elevation contour map. Ancillary maps show the statistical quality of the elevation data and various characteristics of the surface. The elevation map is used to define ice flow directions and delineate the major drainage basins. Regular maps of the Jakobshavns Glacier drainage basin and the ice divide in the vicinity of Crete Station are presented. Altimeter derived elevations are compared with elevations measured both by satellite geoceivers and optical surveying

Satellite Altimetry, Semivariograms, and Seasonal Elevation Changes in the Ablation Zone of West Greenland

Seasonal mean changes in the surface elevation of the ablation zone of West Greenland to 72°N between spring 1985 and summer 1986 are measured using radar altimeter data from the 18-month Geosat Geodetic Mission. Semi-variograms are used to estimate the noise in the data as a function of position on the ice sheet. Mean elevation changes are computed by averaging the elevation differences measured at points where orbits ascending in latitude are later crossed by orbits descending in latitude (or the reverse), with each cross-over difference weighted in proportion to the inverse square of the noise level in the neighborhood of the cross-over point. The mean surface elevation of the ablation zone, relative to spring 1985, ranged from 1.5 ± 0.6 m lower during summer 1985 to 1.7 ± 0.4 m higher during spring 1986

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

Satellite radar altimetry over ice. Volume 1: Processing and corrections of Seasat data over Greenland

The data-processing methods and ice data products derived from Seasat radar altimeter measurements over the Greenland ice sheet and surrounding sea ice are documented. The corrections derived and applied to the Seasat radar altimeter data over ice are described in detail, including the editing and retracking algorithm to correct for height errors caused by lags in the automatic range tracking circuit. The methods for radial adjustment of the orbits and estimation of the slope-induced errors are given

Satellite radar altimetry over ice. Volume 4: Users' guide for Antarctica elevation data from Seasat

A gridded surface-elevation data set and a geo-referenced data base for the Seasat radar altimeter data over Greenland are described. This is a user guide to accompany the data provided to data centers and other users. The grid points are on a polar stereographic projection with a nominal spacing of 20 km. The gridded elevations are derived from the elevation data in the geo-referenced data base by a weighted fitting of a surface in the neighborhood of each grid point. The gridded elevations are useful for the creating of large-scale contour maps, and the geo-referenced data base is useful for regridding, creating smaller-scale contour maps, and examinating individual elevation measurements in specific geographic areas. Tape formats are described, and a FORTRAN program for reading the data tape is listed and provided on the tape

Satellite radar altimetry over ice. Volume 2: Users' guide for Greenland elevation data from Seasat

A gridded surface-elevation data set and a geo-referenced data base for the Seasat radar altimeter data over Antarctica are described. It is intended to be a user's guide to accompany the data provided to data centers and other users. The grid points are on a polar stereographic projection with a nominal spacing of 20 km. The gridded elevations are derived from the elevation data in the geo-referenced data base by a weighted fitting of a surface in the neighborhood of each grid point. The gridded elevations are useful for the creating smaller-scale contour maps, and examining individual elevation measurements in specific geographic areas. Tape formats are described, and a FORTRAN program for reading the data tape is listed and provided on the tape

Multi-Year Elevation Changes Near the West Margin of the Greenland Ice Sheet from Satellite Radar Altimetry

Mean changes in the surface elevation near the west margin of the Greenland ice sheet are measured using Seasat altimetry and altimetry from the Geosat Exact Repeat Mission (ERM). The Seasat data extend from early July through early October 1978. The ERM data extend from winter 1986-87 through fall 1988. Both seasonal and multi-year changes are measured using altimetry referenced to GEM T2 orbits. The possible effects of orbit error are minimized by adjusting the orbits into a common ocean surface. Seasonal mean changes in the surface height are recognizable during the Geosat ERM. The multi-year measurements indicate the surface was lower by 0.4 +/- 0.4 m on average in late summer 1987 than in late summer 1978. The surface was lower by 0.2 +/- 0.5 m on average in late summer 1988 than in late summer 1978. As a control case, the computations art also carried out using altimetry referenced to orbits not adjusted into a common ocean surface

An Algorithm for Detection of Ground and Canopy Cover in Micropulse Photon-Counting Lidar Altimeter Data in Preparation of the ICESat-2 Mission

The Ice, Cloud and Land Elevation Satellite-II (ICESat-2) mission has been selected by NASA as a Decadal Survey mission, to be launched in 2016. Mission objectives are to measure land ice elevation, sea ice freeboard/ thickness and changes in these variables and to collect measurements over vegetation that will facilitate determination of canopy height, with an accuracy that will allow prediction of future environmental changes and estimation of sea-level rise. The importance of the ICESat-2 project in estimation of biomass and carbon levels has increased substantially, following the recent cancellation of all other planned NASA missions with vegetation-surveying lidars. Two innovative components will characterize the ICESat-2 lidar: (1) Collection of elevation data by a multi-beam system and (2) application of micropulse lidar (photon counting) technology. A micropulse photon-counting altimeter yields clouds of discrete points, which result from returns of individual photons, and hence new data analysis techniques are required for elevation determination and association of returned points to reflectors of interest including canopy and ground in forested areas. The objective of this paper is to derive and validate an algorithm that allows detection of ground under dense canopy and identification of ground and canopy levels in simulated ICESat-2-type data. Data are based on airborne observations with a Sigma Space micropulse lidar and vary with respect to signal strength, noise levels, photon sampling options and other properties. A mathematical algorithm is developed, using spatial statistical and discrete mathematical concepts, including radial basis functions, density measures, geometrical anisotropy, eigenvectors and geostatistical classification parameters and hyperparameters. Validation shows that the algorithm works very well and that ground and canopy elevation, and hence canopy height, can be expected to be observable with a high accuracy during the ICESat-2 mission. A result relevant for instrument design is that even the two weaker beam classes considered can be expected to yield useful results for vegetation measurements (93.01-99.57% correctly selected points for a beam with expected return of 0.93 mean signals per shot (msp9) and 72.85% - 98.68% for 0.48 msp (msp4)). Resampling options affect results more than noise levels. The algorithm derived here is generally applicable for analysis of micropulse lidar altimeter data collected over forested areas as well as other surfaces, including land ice, sea ice and land surfaces

Comparison of Surface Elevation Changes of the Greenland and Antarctic Ice Sheets from Radar and Laser Altimetry

A primary purpose of satellite altimeter measurements is determination of the mass balances of the Greenland and Antarctic ice sheets and changes with time by measurement of changes in the surface elevations. Since the early 1990's, important measurements for this purpose have been made by radar altimeters on ERS-l and 2, Envisat, and CryoSat and a laser altimeter on ICESat. One principal factor limiting direct comparisons between radar and laser measurements is the variable penetration depth of the radar signal and the corresponding location of the effective depth of the radar-measured elevation beneath the surface, in contrast to the laser-measured surface elevation. Although the radar penetration depth varies significantly both spatially and temporally, empirical corrections have been developed to account for this effect. Another limiting factor in direct comparisons is caused by differences in the size of the laser and radar footprints and their respective horizontal locations on the surface. Nevertheless, derived changes in elevation, dHldt, and time-series of elevation, H(t), have been shown to be comparable. For comparisons at different times, corrections for elevation changes caused by variations in the rate offrrn compaction have also been developed. Comparisons between the H(t) and the average dH/dt at some specific locations, such as the Vostok region of East Antarctic, show good agreement among results from ERS-l and 2, Envisat, and ICESat. However, Greenland maps of dHidt from Envisat and ICESat for the same time periods (2003-2008) show some areas of significant differences as well as areas of good agreement. Possible causes of residual differences are investigated and described

NASA Ocean Altimeter Pathfinder Project

The NOAA/NASA Pathfinder program was created by the Earth Observing System (EOS) Program Office to determine how satellite-based data sets can be processed and used to study global change. The data sets are designed to be long time-sedes data processed with stable calibration and community consensus algorithms to better assist the research community. The Ocean Altimeter Pathfinder Project involves the reprocessing of all altimeter observations with a consistent set of improved algorithms, based on the results from TOPEX/POSEIDON (T/P), into easy-to-use data sets for the oceanographic community for climate research. This report describes the processing schemes used to produce a consistent data set and two of the products derived f rom these data. Other reports have been produced that: a) describe the validation of these data sets against tide gauge measurements and b) evaluate the statistical properties of the data that are relevant to climate change. The use of satellite altimetry for earth observations was proposed in the early 1960s. The first successful space based radar altimeter experiment was flown on SkyLab in 1974. The first successful satellite radar altimeter was flown aboard the Geos-3 spacecraft between 1975 and 1978. While a useful data set was collected from this mission for geophysical studies, the noise in the radar measured and incomplete global coverage precluded ft from inclusion in the Ocean Altimeter Pathfinder program. This program initiated its analysis with the Seasat mission, which was the first satellite radar altimeter flown for oceanography