Associating a radar scatterer to a physical object is crucial for the correct interpretation of interferometric synthetic aperture radar measurements. Yet, especially for medium-resolution imagery, this is notoriously difficult and dependent on the accurate 3-D positioning of the scatterers. Here, we investigate the 3-D positioning capabilities of ENVISAT medium-resolution data. We find that the data are perturbed by range-and-epoch-dependent timing errors and calibration offsets. Calibration offsets are estimated to be about 1.58 m in azimuth and 2.84 m in range and should be added to ASAR products to improve geometric calibration. The timing errors involve a bistatic offset, atmospheric path delay, solid earth tides, and local oscillator drift. This way, we achieve an unbiased positioning capability in 2-D, while in 3-D, a scatterer was located at a distance of 28 cm from the true location. 3-D precision is now expressed as an error ellipsoid in local coordinates. Using the Bhattacharyya metric, we associate radar scatterers to real-world objects. Interpreting deformation of individual infrastructure is shown to be feasible for this type of medium-resolution data.@en

Palaeo-ice sheets are important analogues for understanding contemporary ice sheets, offering a record of ice sheet behaviour that spans millennia. There are two main approaches to reconstructing palaeo-ice sheets. Empirical reconstructions use the available glacial geological and chronological evidence to estimate ice sheet extent and dynamics but lack direct consideration of ice physics. In contrast, numerically modelled simulations implement ice physics, but often lack direct quantitative comparison with empirical evidence. Despite being long identified as a fruitful scientific endeavour, few ice sheet reconstructions attempt to reconcile the empirical and model-based approaches. To achieve this goal, model-data comparison procedures are required. Here, we compare three numerically modelled simulations of the former British–Irish Ice Sheet with the following lines of evidence: (a) position and shape of former margin positions, recorded by moraines; (b) former ice-flow direction and flow-switching, recorded by flowsets of subglacial bedforms; and (c) the timing of ice-free conditions, recorded by geochronological data. These model–data comparisons provide a useful framework for quantifying the degree of fit between numerical model simulations and empirical constraints. Such tools are vital for reconciling numerical modelling and empirical evidence, the combination of which will lead to more robust palaeo-ice sheet reconstructions with greater explicative and ultimately predictive power.@en

Palaeo-ice sheets are important analogues for understanding contemporary ice sheets, offering a record of ice sheet behaviour that spans millennia. There are two main approaches to reconstructing palaeo-ice sheets. Empirical reconstructions use the available glacial geological and chronological evidence to estimate ice sheet extent and dynamics but lack direct consideration of ice physics. In contrast, numerically modelled simulations implement ice physics, but often lack direct quantitative comparison with empirical evidence. Despite being long identified as a fruitful scientific endeavour, few ice sheet reconstructions attempt to reconcile the empirical and model-based approaches. To achieve this goal, model-data comparison procedures are required. Here, we compare three numerically modelled simulations of the former British–Irish Ice Sheet with the following lines of evidence: (a) position and shape of former margin positions, recorded by moraines; (b) former ice-flow direction and flow-switching, recorded by flowsets of subglacial bedforms; and (c) the timing of ice-free conditions, recorded by geochronological data. These model–data comparisons provide a useful framework for quantifying the degree of fit between numerical model simulations and empirical constraints. Such tools are vital for reconciling numerical modelling and empirical evidence, the combination of which will lead to more robust palaeo-ice sheet reconstructions with greater explicative and ultimately predictive power.@en