Ice, Cloud, And Land Elevation Satellite Elevation Research Articles

A Terrestrial Validation of ICESat Elevation Measurements and Implications for Global Reanalyses

The primary goal of NASA's Ice, Cloud, and land Elevation Satellite (ICESat) mission was to detect centimeter-level changes in global ice sheet elevations at the spatial scale of individual ice streams. Confidence in detecting these small signals requires careful validation over time to characterize the uncertainty and stability of measured elevations. A common validation approach compares altimeter elevations to an independently characterized and stable reference surface. Using a digital elevation model (DEM) from geodetic surveys of one such surface, the salar de Uyuni in Bolivia, we show that ICESat elevations at this location have a 0.0-cm bias relative to the WGS84 ellipsoid, 4.0-cm (1-sigma) uncertainty overall, and 1.8-cm uncertainty under ideal conditions over short (50 km) profiles. We observe no elevation bias between ascending and descending orbits, but we do find that elevations measured immediately after transitions from low to high surface albedo may be negatively biased. Previous studies have reported intercampaign biases (ICBs) between various ICESat observation campaigns, but we find no statistically significant ICBs or ICB trends in our data. We do find a previously unreported 3.1-cm bias between ICESat's Laser 2 and Laser 3, and we find even larger interlaser biases in reanalyzed data from other studies. For an altimeter with an exact repeat orbit like ICESat, we also demonstrate that validation results with respect to averaged elevation profiles along a single ground track are comparable to results obtained using reference elevations from an in situ survey.

Estimation of snow accumulation over frozen Arctic lakes using repeat ICESat laser altimetry observations – A case study in northern Alaska

The spatial distribution and temporal dynamics of snow in Arctic regions have a direct impact on the regional energy balance and hydrologic cycle. However, our knowledge of snow cover in Arctic regions is very limited due to the sparseness of in situ measurements. This study presents a new method to derive snow accumulation information for Arctic regions through tracking the surface elevation changes of numerous frozen arctic lakes measured by Ice, Cloud, and land Elevation satellite (ICESat) repeat altimetry observations. The original ICESat elevation product for continental surface was generated by tracking the centroids of the emitted and the returned laser waveforms. This product contains many biased measurements over frozen arctic lake surfaces due to the scattering effects induced by thin clouds and blowing snow. This study derives an operational approach that produces more reliable altimetry observations by converting the elevation measurements from the centroid scheme to the max-amplitude-peak scheme. Time-variable biases exist between the repeat elevation measurements acquired in different ICESat campaigns. The correction of these inter-campaign biases in this study significantly improves the quantification of the surface elevation change, thus enabling more consistent subsequent snow accumulation estimates. Besides snow fall, lake ice growth also contributes to the surface elevation change. We developed a method to measure and remove this contribution from the total lake surface elevation change, which leads to more accurate estimates of snow accumulation on frozen surfaces of 277 lakes in Arctic regions of northern Alaska. The results were validated using in situ snow depth observations from terrestrial stations on the Arctic coastal plain of Alaska. After the correction of the ICESat inter-campaign biases and the removal of contribution by lake surface phase transformation, the snow accumulation derived from the repeat ICESat elevation measurements are highly correlated with in situ snow depth observations with a Pearson's correlation coefficient r of 0.88. In comparison with ground-based measurements, the root mean square error (RMSE) of our snow accumulation estimates is approximately 5 cm. Our method makes it possible to provide much denser snow accumulation information as compared to the existing in situ observations for the Circum-Arctic coastal regions and also the Qinghai-Tibet Plateau where seasonal frozen lakes are abundant.

PRECISION AND DEVIATION COMPARISON BETWEEN ICESAT AND ENVISAT IN TYPICAL ICE GAINING AND LOSING REGIONS OF ANTARCTICA

Abstract. This paper analyzes the precision and deviation of elevations acquired from Envisat and The Ice, Cloud and Land Elevation Satellite (ICESat) over typical ice gaining and losing regions, i.e. Lambert-Amery System (LAS) in east Antarctica, and Amundsen Sea Sector (ASS) in west Antarctica, during the same period from 2003 to 2008. We used GLA12 dataset of ICESat and Level 2 data of Envisat. Data preprocessing includes data filtering, projection transformation and track classification. Meanwhile, the slope correction is applied to Envisat data and saturation correction for ICESat data. Then the crossover analysis was used to obtain the crossing points of the ICESat tracks, Envisat tracks and ICESat-Envisat tracks separately. The two tracks we chose for cross-over analysis should be in the same campaign for ICESat (within 33 days) or the same cycle for Envisat (within 35 days).The standard deviation of a set of elevation residuals at time-coincident crossovers is calculated as the precision of each satellite while the mean value is calculated as the deviation of ICESat-Envisat. Generally, the ICESat laser altimeter gets a better precision than the Envisat radar altimeter. For Amundsen Sea Sector, the ICESat precision is found to vary from 8.9 cm to 17 cm and the Envisat precision varies from 0.81 m to 1.57 m. For LAS area, the ICESat precision is found to vary from 6.7 cm to 14.3 cm and the Envisat precision varies from 0.46 m to 0.81 m. Comparison result between Envisat and ICESat elevations shows a mean difference of 0.43 ±7.14 m for Amundsen Sea Sector and 0.53 ± 1.23 m over LAS.

Uncertainties in Antarctic sea-ice thickness retrieval from ICESat

AbstractA sensitivity study was carried out for the lowest-level elevation method to retrieve total (sea ice + snow) freeboard from Ice, Cloud and land Elevation Satellite (ICESat) elevation measurements in the Weddell Sea, Antarctica. Varying the percentage (P) of elevations used to approximate the instantaneous sea-surface height can cause widespread changes of a few to ˃10cm in the total freeboard obtained. Other input parameters have a smaller influence on the overall mean total freeboard but can cause large regional differences. These results, together with published ICESat elevation precision and accuracy, suggest that three times the mean per gridcell single-laser-shot error budget can be used as an estimate for freeboard uncertainty. Theoretical relative ice thickness uncertainty ranges between 20% and 80% for typical freeboard and snow properties. Ice thickness is computed from total freeboard using Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) snow depth data. Average ice thickness for the Weddell Sea is 1.73 ± 0.38 m for ICESat measurements from 2004 to 2006, in agreement with previous work. The mean uncertainty is 0.72 ± 0.09 m. Our comparison with data of an alternative approach, which assumes that sea-ice freeboard is zero and that total freeboard equals snow depth, reveals an average sea-ice thickness difference of ∼0.77m.

Variations in water level and glacier mass balance in Nam Co lake, Nyainqentanglha range, Tibetan Plateau, based on ICESat data for 2003-09

AbstractWater level fluctuations of inland lakes are related to regional-scale climate changes, and reflect variations in evaporation, precipitation and glacier meltwater flowing into the lake area in its catchment. In this paper, Ice, Cloud and land Elevation Satellite (ICESat) altimeter data and Landsat imagery (2002-09) are used to estimate Nam Co lake (Nyainqentanglha range, Tibetan Plateau) water elevation changes during 2002-09. In 2003 Nam Co lake covered an area of ~1998.8 ± 4.2 km2 and was situated at 4723 m a.s.l. Over such inland water bodies, ICESat altimeter data offer both wide coverage and spatial and temporal accuracy. We combine remote-sensing and GIS technology to map and reconstruct lake area and increased volume changes during a 7 year time series. Nam Co lake water level increased by 2.4±0.12m (0.33ma–1) between 23 February 2003 and 1 October 2009, and lake volume increased by 4.9 ±0.5 km3. In the past 7 years, Nam Co lake area has increased from 1998.78 ±5.4 to 2023.8 ±3.4 km2, the glacier-covered area has decreased from 832.34 to 821.0 km2 and the drainage basin area has decreased from 201.1 ±4.2 to 196.1 ±2.3 km2. However, the most spectacular feature is the continual water level rise from 2003 to 2009 without an obvious associated increase in precipitation. Based on digital elevation models (DEMs) from Shuttle Radar Topography Mission (SRTM) DEM data and corrected ICESat elevation data, significant changes to glacier mass balance in the western Nyainqentanglha mountains are indicated. Nyainqentanglha mountain glacier surface elevations decreased by 8.39 ± 0.45 m during 2003-09. Over the same period, at least 1.01 km3 of glacial meltwater flowed into Nam Co lake, assuming a glacial runoff coefficient of 0.6. The mean glacier mass-balance value is -490mmw.e. over the corresponding period, indicating that glacier meltwater in the catchment contributes to lake level rise. The contribution rate of glacial meltwater to lake water volume rise is 20.75%. The temporal lake level fluctuation correlates with temperature variations over the same time span.

Estimation of ICESat intercampaign elevation biases from comparison of lidar data in East Antarctica

The Ice, Cloud, and land Elevation Satellite (ICESat) laser campaign elevation biases are estimated from an analysis of ICESat and airborne Land, Vegetation, and Ice Sensor lidar intrasensor and intersensor elevation differences from two regions of the Antarctic ice sheet that experienced minimal surface elevation change. Elevation observations are corrected for a combination of accumulation, melting, and firn densification processes and glacial isostatic adjustment. ICESat elevations are adjusted for the saturation and Gaussian‐Centroid corrections. Relative to laser campaign L3I, biases are found to be less than ∼8 cm, except for campaign L2E at 14.72 cm corresponding to the time of a significant accumulation anomaly in East Antarctica. The intercampaign bias trend estimated from intersensor elevation differences computed over campaigns L2A to L2F (September 2003 to October 2009) excluding L2E is 1.04 ± 0.48 cm/yr. The intercampaign bias trend represents a correction to ICESat derived Antarctica mass balance of 117 ± 53 Gt/yr.

ICESat Elevations in Antarctica Along the 2007–09 Norway–USA Traverse: Validation With Ground-Based GPS

The 2007-09 Norway-USA Traverse of East Antarctica collected dual-frequency Global Positioning System (GPS) data at 5-s intervals on two of the traverse vehicles. The traverse covered 2400 km from the coast to the vicinity of the Amundsen-Scott South Pole Station in 2007-08, and a 2600 km route from the South Pole to the coast in 2008-09. Side traverses were also conducted in 2008-09, for a total of over 10 000 km of GPS data between the two vehicles. We use precise point positioning to post-process our single receiver kinematic GPS data. Analysis of data obtained while the vehicles were stationary shows individual solutions are accurate to ca. 1 cm horizontally and 3 cm vertically. We compare our GPS elevations with those determined by the National Aeronautics and Space Administration's Ice, Cloud, and Land Elevation Satellite (ICESat), a space-based altimeter designed to measure ice elevation. ICESat accuracy is evaluated by cross-over analysis; mean differences calculated between dh/dt-corrected ICESat data and GPS-derived surface elevations for two vehicles and two traverse seasons range from -12 to -2 cm, within ICESat's stated goal of ±15 cm, while 1-σ values of the same data imply that ICESat's precision is ca. 15.8 cm.

High-Resolution Ground-Based GPS Measurements Show Intercampaign Bias in ICESat Elevation Data Near Summit, Greenland

The Geoscience Laser Altimeter System (GLAS) aboard the National Aeronautics and Space Administration's Ice, Cloud, and land Elevation Satellite (ICESat) collected data from early 2003 to late 2009 with the specific goal of measuring ice-surface elevation changes. While the precision of GLAS instrumentation has been studied over its intended target (ice), its accuracy has only been robustly estimated using independent (terrestrial nonlaser) methods over salt flats. Here, we perform repeat high-precision Global Positioning System (GPS) surveys under four passes of ICESat track 0412 (campaigns L3I, L3J, L2D, and L2E) to compare directly GLAS elevation data footprints to a coincident GPS ground truth near Summit, Greenland. Analysis and comparison of GLAS data with GPS data show a campaign-dependent elevation bias ranging from -0.112 ±0.030 m (L3J) to 0.121 ± 0.071 m (L2E). Although uncorrected reflectance values and field observations both indicate that forward scattering of the laser signal through the atmosphere accounts for the anomalously negative L3J bias, the biases of all campaigns studied are within the instrument's goal accuracy of ±0.15 m. However, our analysis shows a campaign dependence in the bias, which may propagate through estimates of mass balance. The error introduced from intercampaign biases illustrates the importance of long-term independent validation experiments of satellite altimetry data over ice sheets.

Estimating vertical error of SRTM and map-based DEMs using ICESat altimetry data in the eastern Tibetan Plateau

The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud and land Elevation Satellite (ICESat) provides elevation data with very high accuracy which can be used as ground data to evaluate the vertical accuracy of an existing Digital Elevation Model (DEM). In this article, we examine the differences between ICESat elevation data (from the 1064 nm channel) and Shuttle Radar Topography Mission (SRTM) DEM of 3 arcsec resolution (90 m) and map-based DEMs in the Qinghai-Tibet (or Tibetan) Plateau, China. Both DEMs are linearly correlated with ICESat elevation for different land covers and the SRTM DEM shows a stronger correlation with ICESat elevations than the map-based DEM on all land-cover types. The statistics indicate that land cover, surface slope and roughness influence the vertical accuracy of the two DEMs. The standard deviation of the elevation differences between the two DEMs and the ICESat elevation gradually increases as the vegetation stands, terrain slope or surface roughness increase. The SRTM DEM consistently shows a smaller vertical error than the map-based DEM. The overall means and standard deviations of the elevation differences between ICESat and SRTM DEM and between ICESat and the map-based DEM over the study area are 1.03 ± 15.20 and 4.58 ± 26.01 m, respectively. Our results suggest that the SRTM DEM has a higher accuracy than the map-based DEM of the region. It is found that ICESat elevation increases when snow is falling and decreases during snow or glacier melting, while the SRTM DEM gives a relative stable elevation of the snow/land interface or a glacier elevation where the C-band can penetrate through or reach it. Therefore, this makes the SRTM DEM a promising dataset (baseline) for monitoring glacier volume change since 2000.

The Relevance of GLAS/ICESat Elevation Data for the Monitoring of River Networks

The Ice, Cloud and Land Elevation Satellite (ICESat) laser altimetry mission from 2003 to 2008 provided an important dataset for elevation measurements. The quality of GLAS/ICESat (Geoscience Laser Altimeter System) data was investigated for Lake Leman in Switzerland and France by comparing laser data to hydrological gauge water levels. The correction of GLAS/ICESat waveform saturation successfully improved the quality of water elevation data. First, the ICESat elevations and waveforms corresponding to water footprints across the transition from the land to water were analyzed. Water elevations (2 to 10 measurements) following the land-water transition are often of lesser quality. The computed accuracy for the ICESat elevation measurements is approximately 5 cm, excluding transitions footprints, and 15 cm, including these footprints. Second, the accuracy of ICESat elevation was studied using data acquired on French rivers with a width greater than the size of the ICESat footprint. The obtained root mean square error (RMSE) for ICESat elevations in regard to French rivers was 1.14 m (bias = 0.07 m; standard deviation = 1.15 m), which indicates that small rivers could not be monitored using ICESat with acceptable accuracy due to land-water transition sensor inertia.

Ice, Cloud, and land Elevation Satellite (ICESat) over Arctic sea ice: Retrieval of freeboard

Total freeboard (snow and ice) of the Arctic Ocean sea ice cover is derived using Ice, Cloud, and land Elevation Satellite (ICESat) data from two 35‐day periods: one during the fall (October−November) of 2005 and the other during the winter (February−March) of 2006. Three approaches are used to identify near‐sea‐surface tiepoints. Thin ice or open water samples in new openings, typically within 1−2 cm of the sea surface, are used to assess the sea surface estimates. Results suggest that our retrieval procedures could provide consistent freeboard estimates along 25‐km segments with uncertainties of better than 7 cm. Basin‐scale composites of sea ice freeboard show a clear delineation of the seasonal ice zone in the fall. Overall, the mean freeboards of multiyear (MY) and first‐year (FY) ice are 35 cm and 14 cm in the fall, and 43 cm and 27 cm in the winter. The increases of ∼9 cm and ∼12 cm on MY and FY sea ice are associated with the 4 months of ice growth and snow accumulation between data acquisitions. Since changes in snow depth account for >90% of the seasonal increase in freeboard on MY ice, it dominates the seasonal signal. Our freeboard estimates are within 10 cm of those derived from available snow/ice thickness measurements from ice mass balance buoys. Examination of the two residual elevations fields, after the removal of the sea ice freeboard contribution, shows coherent spatial patterns with a standard deviation (S.D.) of ∼23 cm. Differencing them reduces the variance and gives a near random field with a mean of ∼2 cm and a standard deviation of ∼14 cm. While the residual fields seem to be dominated by the static component of unexplained sea surface height and mean dynamic topography (S.D. ∼23 cm), the difference field reveals the magnitude of the time‐varying components as well as noise in the ICESat elevations (S.D. ∼10 cm).

Verification of the Vertical Error in C-Band SRTM DEM Using ICESat and Landsat-7, Otter Tail County, MN

The Shuttle Radar Topography Mission (SRTM) provided scientists with digital elevation data on a nearly global scale and with highly consistent accuracy. This paper compares elevation values of the C-band SRTM 30-m digital elevation model (DEM) with pointwise elevations from the Ice, Cloud, and land-Elevation Satellite (ICESat) laser altimetry for Otter Tail County, Minnesota. The accuracy of SRTM DEM is measured as a function of land covers and geomorphologic characteristics. The typical mean vertical difference between the SRTM DEM and ICESat elevations in this paper was determined in each classified land-use type and is approximately 1.5 m over bare ground, with the SRTM measuring lower elevations. Significant changes in the SRTM DEM uncertainties have been identified over different surface types classified from Landsat-7 imagery, e.g., bare ground, urban, and forested areas. Based on this result, the difference of the SRTM 30-m DEM and ICESat elevations has been removed from the DEM and made available for improved hydrological applications

ICESat Altimetry Data Product Verification at White Sands Space Harbor

Three unique techniques have been developed to validate the Ice, Cloud, and Land Elevation Satellite (ICESat) mission altimetry data product and implemented at White Sands Space Harbor (WSSH) in New Mexico. One specific technique at WSSH utilizes zenith-pointed sensors to detect the laser on the surface and enable geolocation determination of the altimeter footprint that is independent of the data product generation. The system of detectors also registers the laser light time of arrival, which is related to the data product time tag. Several overflights of the WSSH have validated these time tags to less than 3plusmn1 mus. The ground-based detector system also verified the laser illuminated spot geolocation to 10.6 m (3.5 arcsec) plusmn4.5 m on one occasion, which is consistent with the requirement of 3.5 m (1sigma). A third technique using corner cube retroreflector signatures in the altimeter echo waveforms was also shown to provide an assessment of the laser spot geolocation. Although the accuracy of this technique is not equal to the other methodologies, it does offer position determination for comparison to the spacecraft altimetry data product. In addition, elevation verifications were made using the comparison of the ICESat elevation products at WSSH to those acquired with an airborne light detection and ranging. The elevation comparisons show an agreement to within plusmn34 cm (plusmn6.7 cm under best conditions) which indicate no significant errors associated with the pointing knowledge of the altimeter

ICESat Antarctic elevation data: Preliminary precision and accuracy assessment

Since ‘first light’ on February 20th, 2003, NASA's Ice, Cloud, and land Elevation Satellite (ICESat) has derived surface elevations from ∼86°N to 86°S latitude. These unique altimetry data have been acquired in a series of observation periods in repeated track patterns using all three Geoscience Laser Altimeter System (GLAS) lasers. Here, we focus on Antarctic ice sheet elevation data that were obtained in 2003–2004. We present preliminary precision and accuracy assessments of selected elevation data, and discuss factors impacting elevation change detection. We show that for low slope and clear sky conditions, the precision of GLA12 Laser 2a, Release 21 data is ∼2.1 cm and the relative accuracy of ICESat elevations is ±14 cm based on crossover differences.

SRTM C-Band and ICESat Laser Altimetry Elevation Comparisons as a Function of Tree Cover and Relief

The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation Satellite (ICESat) provides a globally distributed elevation data set that is well-suited to independently evaluate the accuracy of digital elevation models (DEMs), such as those produced by the Shuttle Radar Topography Mission (SRTM). We document elevation differences between SRTM C-band 1 and 3 arcsecond resolution DEMs and ICESat 1064 nm altimeter channel elevation data acquired in an areas of variable topography and vegetation cover in the South American Amazon Basin, Asian Tibetan Plateau ‐ Himalayan Mountains, East Africa, western Australia, and the western United States. GLAS received waveforms enable the estimation of SRTM radar phase center elevation biases and variability with respect to the highest (canopy top where vegetated), centroid (distanceweighted average), and lowest (ground) elevations detected within ICESat laser footprints. Distributions of ICESat minus SRTM elevation differences are quantified as a function of waveform extent (a measure of within-footprint relief), SRTM roughness (standard deviation of a 3 � 3 array of elevation posts), and percent tree cover as reported in the Vegetation Continuous Field product derived from Moderate Resolution Imaging Spectrometer (MODIS) data. SRTM roughness is linearly correlated with waveform extent for areas where percent tree cover is low. The SRTM phase center elevation is usually located between the ICESat highest and lowest elevations, and on average is closely correlated with the ICESat centroid. In areas of low relief and sparse tree cover, the mean of ICESat centroid minus SRTM phase center elevation differences for the five regions examined vary between � 3.9 and 1.0 m, and the corresponding standard deviations are between 3.0 and 3.7 m. With increasing SRTM