The Ice, Cloud, and land Satellite-2 (ICESat-2) is planned to launch in 2016 carrying the Advanced Topographic Laser Altimeter System (ATLAS). ATLAS will be the first space-based photon-counting laser altimeter to be put into operation, and is tasked with observing the Earth’s ice sheets, sea ice, and vegetation. The environment in which ATLAS will be operating is expected to introduce a significant amount of noise into the received signal; this necessitates that a set of onboard Receiver Algorithms be developed to reduce the data volume and data rate to acceptable levels while still transmitting the relevant ranging data. The algorithms make use of signal processing techniques, along with three databases, the Digital Elevation Model (DEM), the Digital Relief Map (DRM), and the Surface Reference Mask (SRM), to find the signal and determine the appropriate dynamic range of vertical data surrounding the surface for downlink. The focus of this study is the development of the DEM and DRM databases. A number of elevation data sets are examined for use as inputs for the databases. No global data sets of sufficient quality and resolution are available for the development of the project, so best-available regional elevation data sets were selected instead. Software was developed in MATLAB to produce the DEM and DRM data bases from the input data sets. A method for calculating relief from a gridded elevation data set along the flight path of a satellite was developed for the generation of relief maps used to create the DRM. Global DEM and DRM databases were produced by mosaicking individual DEM and DRM tiles from each input data set into global grids. A technique was developed to determine the accuracy of the DRM by using ICESat ground elevations to evaluate the accuracy of an input elevation data set. By comparing values of DRM accuracy to values of DRM relief, estimates of DRM accuracy as a function of relief magnitude were determined and used to define values of DRM padding in the receiver algorithm. / text

This report compares surface elevation change and volume change esti- mates from three methods: repeat track (RT), crossover (CX), and overlapping footprints (OFP). These three methods use different approaches to group- ing elevation point measurements taken at different measurement epochs and estimating elevation change. Volume changes are calculated from elevation changes in the same manner for all three methods but differences in sampling resolution between the methods affect volume change estimates in different ways. The recently reprocessed Release 633 version of elevation measurements from the Geoscience Laser Altimeter System (GLAS), flown on the Ice, Cloud and land Elevation Satellite (ICESat), are used in this analysis. Both elevation changes and volume changes are compared for both the Greenland Ice Sheet (GrIS) and the Antarctic Ice Sheet (AIS). Additionally, uncertainties in the estimates for each method are quantified and compared. Results are separated by drainage systems and by above/below 2000 m surface elevation for the GrIS. For the AIS, results are aggregated to the East, West, and Penin- vi sula regions. Volume change estimates agree well for the three methods for the GrIS, with estimates of -227.75 ± 2.12 km³/yr, -249.30 ± 3.42 km³/yr, and -218.24 ± 7.39 km³/yr for the RT, CX, and OFP methods, respectively. These estimates are similar to those published from previous studies. For the AIS, however, larger discrepancies are found in the estimates. This stems primarily from a large discrepancy in the volume change estimate of the East AIS, where the RT, CX, and OFP methods estimate volume changes of 33.39 ± 1.42 km³/yr, 46.42 ± 5.46 km³/yr, and -2.72 ± 2.12 km³/yr, respectively. It's not entirely clear why this large discrepancy exists in this particular region, and elevation change estimates for a few particular drainage systems in this region are examined. Previously published volume changes for the AIS also show a large scatter and more work must be done to reconcile the various estimates. Finally, the volume change uncertainties reported do not completely account for the discrepancies in most regions. Additional analysis must be done to completely quantify all error sources. / text

No description available.

<p>The spaceborne lidar Ice, Cloud, and land Elevation Satellite (ICESat)-2 provides the ATL13 data product for inland water bodies. However, its quality characteristics are not yet fully understood. This study presents a robust method for extracting lake water level data and makes a comprehensive evaluation on the determined water levels. The selected study areas are Lake Huron and Lake Superior, which are part of the Great Lakes. The extracted water levels from ATL13 over a period of four years are validated by using the field measurements at the closest NOAA hydrological stations. The evaluation is carried out in terms of data specifications, wind speed, frozen precipitation, distance of photon segments to hydrological stations, data acquisition time, and beam intensity. The determined water levels are then further used for seasonal monitoring and modeling of water surface. This work demonstrates the critical need for outlier removal and the capability of the ATL13 data. A total bias of 9 - 10 cm is found in the ATL13 product. It is found that frozen precipitation can lead to an overestimation (~ 5 cm) of the water level. However, the uncertainty of water level determination is not found to be significantly related to the laser beam intensity and data acquisition time. We expect that these findings will be valuable for users employing the ATL13 inland water body product and for developers producing future versions of the ATL13 product.</p>

Lake Vostok, East Antarctica, represents an extensive water surface at the base of the ice sheet. Snow, ice and atmospheric pressure loads applied anywhere within the lake area produce a hydrostatic response, involving deformations of the ice surface, ice–water interface and particle horizons. A modelling scheme is developed to derive height changes of these surfaces for a given load pattern. It is applied to a series of load scenarios, and predictions based on load fields derived from a regional climate model are compared to observational datasets. Our results show that surface height changes due to snow-buildup anomalies are damped over the lake area, reducing the spatial standard deviation by one-third. The response to air pressure variations, in turn, adds surface height variability. Atmospheric pressure loads may produce height changes of up to 4 cm at daily resolution, but decay rapidly with integration time. The hydrostatic load response has no significant impact neither on ICESat laser campaign biases determined over the lake area nor on vertical particle movements derived from GNSS observations.