Abstract
A long-term time series of ice sheet surface elevation change (SEC) is important for study of ice sheet variation and its response to climate change. In this study, we used an updated plane-fitting least-squares regression strategy to generate a 30 year surface elevation time series for the Greenland Ice Sheet (GrIS) at monthly temporal resolution and 5 × 5 km grid spatial resolution using ERSâ1, ERSâ2, Envisat, and CryoSatâ2 satellite radar altimeter observations obtained between August 1991 and December 2020. The accuracy and reliability of the time series are effectively guaranteed by application of sophisticated corrections for intermission bias and interpolation based on empirical orthogonal function reconstruction. Validation using both airborne laser altimeter observations and the European Space Agency GrIS Climate Change Initiative (CCI) product indicated that our merged surface elevation time series is reliable. The accuracy and dispersion of errors of SECs of our results were 19.3 % and 8.9 % higher, respectively, than those of CCI SECs, and even 30.9 % and 19.0 % higher, respectively, in periods from 2006–2010 to 2010–2014. Further analysis showed that our merged time series could provide detailed insight into GrIS SEC on multiple temporal (up to 30 years) and spatial scales, thereby providing opportunity to explore potential associations between ice sheet change and climatic forcing. The merged surface elevation time series data are available at http://dx.doi.org/10.11888/Glacio.tpdc.271658 (Zhang et al., 2021).
Highlights
Over recent decades, the Greenland Ice Sheet (GrIS) has experienced increasing substantial imbalance
We developed a 30 year SE time series over the GrIS by combining ERS‐1, ERS‐2, Envisat, and CryoSat‐2 355 satellite radar altimeter observations
Validations with airborne laser altimetry observations and European Space Agency (ESA) GrIS Climate Change Initiative 15 (CCI) surface EC (SEC) indicated that our merged SE time series is reliable
Summary
The Greenland Ice Sheet (GrIS) has experienced increasing substantial imbalance. The effective life of a single satellite mission is limited, which means reconstruction of a long-term ice sheet elevation time 35 series requires observations from multiple altimeter missions to be combined. In such a process, the method adopted to eliminate system biases is a crucial factor. 60 exist in altimeter observations, especially in relation to the early altimetry missions, e.g., ERS-1 (Schröder et al, 2019) These problems will result in lack of available data values in certain cells of a joint elevation time series.
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