B. E. Schutz’s research while affiliated with University of Texas at Austin and other places

A computer simulation has been performed for a Geopotential Research Mission (GRM) to enable study of the gravitational sensitivity of the range-rate measurement between two satellites and to provide a set of simulated measurements to assist in the evaluation of techniques developed for the determination of the gravity field. The simulation, identified as SGRM 8511, was conducted with two satellites in near circular, frozen orbits at 160 km altitude and separated by 300 km. High precision numerical integration of the polar orbits was used with a gravitational field complete to degree and order 180 coefficients and to degree 300 in orders 0 to 10. The set of simulated data for a mission duration of about 32 days was generated on a Cray X-MP computer. The characteristics of the simulation and the nature of the results are described in this report.

Algorithm Theoretical Basis Document (ATBD) https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_PPD_ATBD_r002.pdf

Estimation of the surface elevation change of the Greenland Ice Sheet (GrIS) is essential for understanding its response to recent and future climate change. Laser measurements from the NASA's Ice, Cloud, and land Elevation Satellite (ICESat) created altimetric surveys of GrIS surface elevations over the 2003-2009 operational period of the mission. This paper compares four change detection methods using Release 634 ICESat laser altimetry data: repeat tracks (RTs), crossovers (XOs), overlapping footprints (OFPs), and triangulated irregular networks (TINs). All four methods begin with a consistently edited data set and yield estimates of volumetric loss of ice from the GrIS ranging from -193 to -269 km³/yr. Using a uniform approach for quantifying uncertainties, we find that volume change rates at the drainage system scale from the four methods can be reconciled within 1-σ uncertainties in just 5 of 19 drainage systems. Ice-sheet-wide volume change estimates from the four methods cannot be reconciled within 1-σ uncertainties. Our volume change estimates lie within the range of previously published estimates, highlighting that the choice of method plays a dominant role in the scatter of volume change estimates. We find that for much of the GrIS, the OFP and TIN methods yield the lowest volume change uncertainties because of their superior spatial distribution of elevation change rate estimates. However, the RT and XO methods offer inherent advantages, and the future work to combine the elevation change detection methods to produce better estimates is warranted.

The Ice, Cloud, and land Elevation Satellite (ICESat) mission used laser altimetry measurements to determine changes in elevations of glaciers and ice sheets, as well as sea ice thickness distribution. These measurements have provided important information on the response of the cryopshere (Earth's frozen surfaces) to changes in atmosphere and ocean condition. ICESat operated from 2003 to 2009 and provided repeat altimetry measurements not only to the cryosphere scientific community but also to the ocean, terrestrial and atmospheric scientific communities. The conclusive assessment of significant ongoing rapid changes in the Earth's ice cover, in part supported by ICESat observations, has strengthened the need for sustained, high accuracy, repeat observations similar to what was provided by the ICESat mission. Following recommendations from the National Research Council for an ICESat follow-on mission, the ICESat-2 mission is now under development for planned launch in 2018. The primary scientific aims of the ICESat-2 mission are to continue measurements of sea ice freeboard and ice sheet elevation to determine their changes at scales from outlet glaciers to the entire ice sheet, and from 10s of meters to the entire polar oceans for sea ice freeboard. ICESat carried a single beam profiling laser altimeter that produced ~70m diameter footprints on the surface of the Earth at ~150m along-track intervals. In contrast, ICESat-2 will operate with three pairs of beams, each pair separated by about 3km cross-track with a pair spacing of 90m. Each of the beams will have a nominal 17m diameter footprint with an along-track sampling interval of 0.7m. The differences in the ICESat-2 measurement concept are a result of overcoming some limitations associated with the approach used in the ICESat mission. The beam pair configuration of ICESat-2 allows for the determination of local cross-track slope, a significant factor in measuring elevation change for the outlet glaciers surrounding the Greenland and Antarctica coasts. The multiple beam pairs also provide improved spatial coverage. The dense spatial sampling eliminates along-track measurement gaps, and the small footprint diameter is especially useful for sea surface height measurements in the often narrow leads needed for sea ice freeboard and ice thickness retrievals. The ICESat-2 instrumentation concept uses a low energy 532nm (green) laser in conjunction with single-photon sensitive detectors to measure range. Combining ICESat-2 data with altimetry data collected since the start of the ICESat mission in 2003, such as Operation IceBridge and ESA's CryoSat-2, will yield a 15+ year record of changes in ice sheet elevation and sea ice thickness. ICESat-2 will also provide information of mountain glacier and ice cap elevations changes, land and vegetation heights, inland water elevations, sea surface heights, and cloud layering and optical thickness.

Laser pointing knowledge for the Ice, Cloud, and land Elevation Satellite 2 is based on star observations from the laser reference sensor (LRS), which simultaneously observes stars and laser altimeter measurements in a single instrument coordinate frame. The LRS is modeled in this paper by two functions of the angle between star tracker zenith and the sun: pointing motion relative to the spacecraft; and sensitivity, or magnitude of the dim- mest trackable star. The objective is to track thermally induced motion driven by the sun using star observations that are simultaneously degraded by the sun. Sun blinding is mod- eled as zero sensitivity with sunshade performance, that is the extent to which the shade prevents the sun from affecting star observations, determining the detailed sensitivity curve between sunrise and blinding. Star tracking sensitivity is relatively low due to im- ager issues, and sunshade issues can further reduce sensitivity in sunlight. Effects of a range of possible sensitivities and sun shades on laser pointing knowledge (and conse- quently geolocation of the laser spot) are characterized in this paper.

We present a real-time volcano monitoring strategy using GNSS (Global Navigation Satellite System) and examine the performance of the strategy by processing simulated and real data and comparing results with published solutions. The cost of implementing the strategy is reduced greatly by using single-frequency GNSS receivers except for one dual frequency receiver that serves as a base receiver. Positions of the single-frequency receivers are computed relative to the base receiver in an epoch-by-epoch basis using the high-rate DD (Double-Difference) GNSS technique while position of the base station is fixed to the values obtained with a deferred-time PPP (Precise Point Positioning) technique and updated on a regular basis. Since the performance of the single-frequency high-rate DD technique depends on the conditions of the ionosphere over the monitoring area, the ionospheric TEC (Total Electron Content) is monitored using the dual-frequency data from the base receiver. The surface deformation obtained with the high-rate DD technique is eventually processed by a real-time inversion filter based on the Mogi point source model. The performance of the real time volcano monitoring strategy is assessed through a set of tests and case studies, in which the data recorded in the 2007 eruption of Kilauea Volcano and the 2005 eruption of Augustine Volcano are processed in a simulated real-time mode. The case studies show that the displacement time series obtained with the strategy seemed to agree with those obtained with deferred-time, dual-frequency approaches at the level of 10 - 15 mm. Difference in estimated volume change of the Mogi source between the real-time inversion filter and previously reported works was in the range of 11 to 13 % of the maximum volume changes of the cases examined.

The laser reference sensor is the central instrument in the Ice, Cloud, and land Elevation Satellite 2 laser pointing knowledge system, simultaneously observing stars and the altimetry laser in a single instrument coordinate frame. The star observations are relatively sparse, with a predicted brightness cutoff near visual magnitude 5, and their density varies significantly across the sky. There are star gaps of up to approximately 200s, and areas of the sky with 20 simultaneously observable stars. The star observations are augmented with observations from two spacecraft star trackers using an alignment filter. The filter tracks the motion of the laser reference sensor relative to the spacecraft. MonteCarlo simulation is used to characterize the effects of various magnitude cutoffs, types of alignment variations, and regions of the sky on alignment tracking and overall pointing knowledge performance. Multiple model adaptive estimation is used to map alignment process noise filter tuning with respect to the input parameters. The results include pointing knowledge uncertainty predictions over an input parameter space of three star brightness cutoffs, two types of alignment variations, and three alignment variation amplitudes. The results also map pointing uncertainty to regions of the sky and individual stars.

The laser reference sensor is the central instrument in the Ice, Cloud, and Land Elevation Satellite laser pointing knowledge system, simultaneously observing stars and the altimetry laser in a single instrument coordinate frame. The star measurements are sparse, with the intermittent tracking of individual stars because of the small field of view and no tracking in sunlight due to problems with scattered light. Attitude estimation for the laser reference sensor alone is challenging due to its limited stellar data output. There are also three commercial star trackers mounted on the science instrument and spacecraft bus. The time-varying alignments and attitudes of all four star trackers are tracked simultaneously using an alignment filter in order to determine the stability of the laser reference sensor and the effects of its sparse star observations on alignment and attitude knowledge. The filter is able to predict laser reference sensor star measurements with accuracies of approximately 0.5 to 1.5 arcseconds over time scales greater than the orbital period while tracking laser reference sensor alignment variations on the order of 40 arcseconds.

The Laser Reference Sensor is the central instrument in the Ice, Cloud, and land Elevation Satellite laser pointing knowledge system, simultaneously observing the altimetry laser, stars, and a reference signal in a single instrument coordinate frame. The reference signal is intended to provide direct observations of the alignment between the Laser Reference Sensor and the Instrument Star Tracker. The reference signal failed early in the mission and a method was developed to partially replace it by comparing two attitude time series: an attitude filter time series for the Instrument Star Tracker and a pure-gyro time series for the Laser Reference Sensor. Only the Instrument Star Tracker and gyros are used in the replacement method, with the gyros tracking the Laser Reference Sensor attitude in order to make the relative motion of the Instrument Star Tracker observable.

Since the launch of ICESat-1 in 2003, several different approaches have been developed to compute the elevation and volume changes of the Greenland and Antarctica ice sheets, one of the mission's primary objectives. This study investigated three different approaches in order to better assess the strengths and weaknesses of each method, and to better quantify the uncertainty of elevation/volume change estimates from ICESat-1. In particular, data processing techniques based on repeat tracks, crossovers, and overlapping footprints were evaluated. All three methods made use of the latest Release 633 ICESat-1 data along with linear least squares regression to estimate the elevation change trend. The comparisons show that data editing based on derived parameters, including the number of points used in the linear regression, is essential for good correlation of estimated elevation change trends between the three methods. Estimated variance of unit weight is used to examine model errors in the linear regression and to scale formal errors to obtain a more realistic estimate of the uncertainty. Differences in elevation changes between the three methods are used to validate the scaled formal errors. Finally, elevation changes from each of the three methods are converted to volume changes and reported per drainage basin for both ice sheets.