Browsing by Subject "Greenland"
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Item Effect of modeled pre-industrial Greenland ice sheet surface mass balance bias on uncertainty in sea level rise projections in 2100(2013-08) Gutowski, Gail Ruth; Blankenship, Donald D.; Jackson, Charles S., doctor of geophysical scienceChanges to ice sheet surface mass balance (SMB) are going to play a significant role in future sea level rise (SLR), particularly for the Greenland ice sheet. The Coupled Model Intercomparison Project Phase 5 (CMIP5) found that Greenland ice sheet (GIS) response to changes in SMB is expected to contribute 9 ± 4 cm to sea level by 2100 (Fettweis et al 2013), though other estimates suggest the possibility of an even larger response. Modern ice sheet geometry and surface velocities are common metrics for determining a model’s predictability of future climate. However, care must be taken to robustly quantify prediction uncertainty because errors in boundary conditions such as SMB can be compensated by (and therefore practically inseparable from) errors in other aspects of the model, complicating calculations of total uncertainty. We find that SMB calculated using the Community Earth System Model (CESM) differs from established standards due to errors in the CESM SMB boundary condition. During the long ice sheet initialization process, small SMB errors such as these have an opportunity to amplify into larger uncertainties in GIS sensitivity to climate change. These uncertainties manifest themselves in ice sheet surface geometry changes, ice mass loss, and subsequent SLR. While any bias in SMB is not desirable, it is not yet clear how sensitive SLR projections are to boundary condition forcing errors. We explore several levels of SMB forcing bias in order to analyze their influence on future SLR. We evaluate ensembles of ice sheets forced by 4 different levels of SMB forcing error, covering a range of errors similar to SMB biases between CESM and RACMO SMB. We find that GIS SMB biases on the order of 1 m/yr result in 7.8 ± 3.4 cm SLR between 1850 and 2100, corresponding to 100% uncertainty at the 2σ level. However, we find unexpected feedbacks between SMB and surface geometry in the northern GIS. We propose that the use of elevation classes may be incorrectly altering the feedback mechanisms in that part of the ice sheet.Item Elevation and volume change of the ice sheets from GLAS : a comparison of methods(2013-12) Felikson, Denis; Schutz, Bob E.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.Item Sensitivity analysis of repeat track estimation techniques for detection of elevation change in polar ice sheets(2010-05) Harpold, Robert Earl; Schutz, Bob E.; Urban, Timothy J.; Catania, Ginny; Fowler, Wallace; Ocampo, CesarRepeat track analysis is one tool that can be used to derive parameters describing elevation changes from elevation data collected from a satellite with a near-repeat groundtrack. While initially developed to study ocean topography, it was then applied to ice sheet data. This study expands upon that previous research by testing the method’s ability to estimate parameters using different amounts of data, different grid sizes and types, and different elevation models containing different parameters to be estimated. In all cases, ICESat-derived elevations were used as input data, as ICESat has a near-repeat groundtrack with extensive coverage of the Greenland and Antarctica ice sheets. Results were compared using the differences between modeled and ICESat-derived elevations, correlation of estimated parameters to known physical features, and differences between known and estimated parameter values for simulated elevation data. It was found that there should be data from at least as many distinct time periods (or, in the case of ICESat, laser campaigns) as parameters being estimated, grids centered on and aligned with the reference groundtrack should be used, and that elevation models containing a constant elevation change rate, slopes, an initial elevation at the grid center, and annual terms should be used. Crossover analysis is a different method to determine elevation change rate with elevation data and serves as an independent verification of the repeat track analysis method. It was found that the hdot values determined from crossover and repeat track analyses agreed to within 5 cm/yr in most areas of the ice sheets, with differences greater than 40 cm/yr along the coasts. While repeat track analysis provides greater coverage than crossover analysis, it is uncertain which method provides the most accurate results.