Datasets

This page lists datasets that we have produced and are freely available as part as the GlobalMass project.

DescriptionDatasetDOIAssociated paperDateVisualisations
Bayesian hierarchical model annual mass trends for the Antarctic Peninsular, including constituent processes.Mass evolution of the Antarctic Peninsula over the last 2 decades from a
joint Bayesian inversion
n/aChuter S et al. (2022) Mass evolution of the Antarctic Peninsula over the last 2 decades from a joint Bayesian inversion The Cryosphere, (doi:10.5194/tc-16-1349-2022).April 2022
Antarctic mass trends, produced using a Bayesian hierarchical model (BHM) approach, for the period 2003-2015Antarctic BHM mass trends for the period 2003-2015n/aMartín‐Español A 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, JGR: Earth Surface, 121, 182– 200 (doi:10.1002/2015JF003550).May 2019Click here
Supporting data and files for PNAS paper that provides predictions of future ice sheet contribution to sea level rise from Structured Expert Judgement (SEJ)Data from GlobalMass (02-2019)10.5523/bris.23k1jbtan6sjv2huakf63cqgavBamber JL et al. (2019) Ice sheet contributions to future sea-level rise from structured expert judgment PNAS (doi:10.1073/pnas.1817205116).February 2019
A synthesis of global land ice mass trend results published, primarily, since the IPCC AR5 (2013) drawing on i) the published literature, ii) expert assessment of that literature, and iii) a new analysis of Arctic glacier and ice cap trends combined with statistical modelling.A new synthesis of annual land ice mass trends 1992 to 201610.1594/PANGAEA.890030Bamber, JL et al. (2018): The land ice contribution to sea level during the satellite era. Environmental Research Letters 13(6). doi: 10.1088/1748-9326/aac2f0May 2018Click here
A global dataset of ~4000 GPS vertical velocities that can be used as observational estimates of glacial isostatic adjustment (GIA) uplift rates.A new global GPS dataset for testing and improving modelled GIA uplift rates10.1594/PANGAEA.889923Schumacher, M et al. (2018): A novel global GPS dataset for glacio isostatic adjustment assessments. Geophysical Journal InternationalMay 2018Click here