New radar altimetry datasets of Greenland and Antarctic surface elevation, 1991–2012 - M. R. Suryawanshi; M. R. Suryawanshi; M. McMillan; J. Maddalena; F. Piras; J. Aublanc; J.-A. Daguzé; C. Grau; Q. Huang (The Cryosphere)
Over the past three decades, there has been a 4.5-fold increase in the loss of ice from the Greenland and Antarctic Ice Sheets, resulting in an enhanced contribution to global sea level rise. Accurately tracking these changes in ice mass requires comprehensive, long-term measurements, which are only feasible from space. Satellite radar altimetry provides the longest near-continuous record of ice sheet surface elevation and volume change, dating back to the launch of ERS-1 in 1991, and maintained through the successive ERS-2, Envisat, CryoSat-2, and Sentinel-3 missions. To reliably constrain multi-decadal trends in ice sheet imbalance, and to place current observations within a longer-term context, requires continued efforts to optimise the processing of data acquired by the older historical missions and to evaluate the accuracy of these measurements. Here, we present new ERS-1, ERS-2, and Envisat altimeter datasets, comprising measurements of ice sheet elevation spanning two decades. This new observational record has been derived using consistent and improved retrieval methods, including enhancements to key Level-2 processing steps such as waveform retracking and echo relocation. Through comparison with independent airborne datasets, we undertake a comprehensive assessment of the accuracy of these measurements and demonstrate the improvements delivered relative to previously available products. With this updated processing, we find that all missions achieve sub-metre (<0.85 m) median elevation biases and dispersion of elevation differences relative to coincident airborne data. These new along-track datasets will be of benefit to a broad range of applications, including the quantification of ice sheet mass imbalance, investigations of the processes driving contemporary ice loss, and the constraint of numerical ice sheet models.