Abstract:
The Antarctic mass trends have been collated from a combination of different remote sensing datasets. These are trends of yearly elevation changes over Antarctica for the period 2003-2013 due to the different geophysical processes driving changes in Antarctica: ice dynamics, surface mass balance and glacio-isostatic adjustment (GIA). Net trends can be easily calculated by adding together surface and ice dynamics trends.
20 km gridded datasets have been produced for each process, per year (except the GIA solution which is time-invariant).
To convert elevation to mass trends, we also provide the density fields for surface (SMB) and GIA processes used in Martin-Espanol et al (2016). These can be directly multiplied by the dh/dt. To convert dh/dt from ice dynamics, simply multiply by the density of ice.
Mass smb = dh/dt smb * d surf
Mass ice = dh/dt ice * d ice (not provided)
Mass gia = dh/dt gia * d rock
NERC grant: NE/I027401/1
Keywords:
Antarctic Ice Sheet, Elevation, Mass balance, Remote sensing
Espanol, A., & Bamber, J. (2017). Spatiotemporal mass balance trends for the Antarctic Ice Sheet, 2003-2013 (Version None) [Data set]. Polar Data Centre; British Antarctic Survey, Natural Environment Research Council; Cambridge, CB3 0ET, UK.. https://doi.org/10.5285/f657816c-dc0c-41ca-945d-a08620494d5b
| Access Constraints: | No restrictions apply. |
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| Use Constraints: | This data is governed by the NERC data policy http://www.nerc.ac.uk/research/sites/data/policy/ and supplied under Open Government Licence v.3 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
| Creation Date: | 2016-10-11 |
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| Dataset Progress: | Complete |
| Dataset Language: | English |
| ISO Topic Categories: |
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| Parameters: |
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| Personnel: | |
| Name | UK PDC |
| Role(s) | Metadata Author |
| Organisation | British Antarctic Survey |
| Name | Dr Alba Martin-Espanol |
| Role(s) | Technical Contact |
| Organisation | University of Bristol |
| Name | Prof Jonathan Bamber |
| Role(s) | Investigator |
| Organisation | University of Bristol |
| Parent Dataset: | N/A |
| Reference: | Zammit-Mangion, A., J. C. Rougier, J. L. Bamber, and N. W. Schoen (2014), Resolving the Antarctic contribution to sea-level rise: A hierarchical modelling framework, Environmetrics, 25, 245 to 264. Zammit-Mangion et al (2014) Zammit-Mangion, A., J. Rougier, N. Schoen, F. Lindgren, and J. Bamber (2015a), Multivariate spatio-temporal modelling for assessing Antarctica's present-day contribution to sea-level rise, Environmetrics, 26(3), 159 to 177. Zammit-Mangion et al (2015) Schoen, N., A. Zammit-Mangion, J. C. Rougier, T. Flament, F. Rémy, S. Luthcke, and J. L. Bamber (2015), Simultaneous solution for mass trends on the West Antarctic Ice Sheet, The Cryosphere, 9(2), 805 to 819. Schoen et al (2015) Zammit-Mangion, A., J. L. Bamber, N. W. Schoen, and J. C. Rougier (2015b), A data-driven approach for assessing ice-sheet mass balance in space and time, Ann. Glaciol., 56(70), 175 to 183. Zammit-Mangion et al (2015) Martín-Español, A., A. Zammit-Mangion, P. J. Clarke, T. Flament, V. Helm, M. A. King, S. B. Luthcke, E. Petrie, F. Rémy, N. Schön, et al. (2016), Spatial and temporal Antarctic Ice Sheet mass trends, glacio-isostatic adjustment, and surface processes from a joint inversion of satellite altimeter, gravity, and GPS data, J. Geophys. Res. Earth Surf.,121, 182 to 200, doi:10.1002/2015JF003550. Martin-Español et al (2016) |
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| Quality: | Uncertainty maps are provided for each of the variables, which are estimated within the Bayesian inversion method taking into account the full error covariance matrices for each data set. Further details are described in the publications related to the project (see references). | |
| Lineage: | The data used a Bayesian Hierarchical Model driven by different remote sensing datasets: ICESat, Envisat, Cryosat-2, GRACE and a network of elastic-corrected GPS stations. The methodology is described in detail in the following papers: Zammit-Mangion et al (2014), Zammit-Mangion et al. (2015a), Zammit-Mangion et al. (2015b) and Martin-Espanol et al (2016). | |
| Temporal Coverage: | |
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| Start Date | 2003-01-01 |
| End Date | 2013-12-31 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | -90 |
| Northernmost | -52.3 |
| Longitude | |
| Westernmost | -180 |
| Easternmost | 180 |
| Altitude | |
| Min Altitude | N/A |
| Max Altitude | N/A |
| Depth | |
| Min Depth | N/A |
| Max Depth | N/A |
| Location: | |
| Location | Antarctica |
| Detailed Location | N/A |
| Data Collection: | Information about the processing of the different datasets can be found partially in Schoen et al. (2015) (not all data sets are used) and completely in Martin-Espanol et al (2016). Details on the architecture and characteristics of the Bayesian framework can be found in Zammit-Mangion et al (2014) and Zammit-Mangion et al. (2015). |
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| Data Storage: | The dataset is approximately 30MB and is in NetCDF format. |
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