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When working with hydrological data, the ability to quantify the similarity of different datasets is useful. The choice of how to make this quantification has a direct influence on the results, with different measures of similarity emphasising particular sources of error (for example, errors in amplitude as opposed to displacements in time and/or space). The Wasserstein distance considers the similarity of mass distributions through a transport lens. In a hydrological context, it measures the "effort" required to rearrange one distribution of water into the other. While being more broadly applicable, particular interest is paid to hydrographs in this work. The Wasserstein distance is adapted for working with hydrographs in two different ways and tested in a calibration and "averaging" of a hydrograph context. This alternative definition of fit is shown to be successful in accounting for timing errors due to imprecise rainfall measurements. The averaging of an ensemble of hydrographs is shown to be suitable when differences among the members are in peak shape and timing but not in total peak volume, where the traditional mean works well. [ABSTRACT FROM AUTHOR]

When working with hydrological data, the ability to quantify the similarity of different datasets is useful. The choice of how to make this quantification has direct influence on the results, with different measures of similarity emphasising particular sources of error (for example, errors in amplitude as opposed to displacements in time and/or space). The Wasserstein distance considers the similarity of mass distributions through a transport lens. In a hydrological context, it measures the 'effort' required to rearrange one distribution of water into the other. While being more broadly applicable, particular interest is payed to hydrographs in this work. The Wasserstein distance is adapted for working with hydrographs in two different ways, and tested in a calibration and 'averaging' of hydrographs context. This alternate definition of fit is shown successful in accounting for timing errors due to imprecise rainfall measurements. The averaging of an ensemble of hydrographs is shown suitable when differences among the members is in peak shape and timing, but not in total peak volume, where the traditional mean works well. [ABSTRACT FROM AUTHOR]

Antarctica and Greenland hold enough ice to raise sea level by more than 65m if both ice sheets were to melt completely. Predicting future ice sheet mass balance depends on our ability to model these ice sheets, which is limited by our current understanding of several key physical processes, such as iceberg calving. Large-scale ice flow models either ignore this process or represent it crudely. To model fractured zones, an important component of many calving models, continuum damage mechanics as well as linear fracture mechanics are commonly used. However, these methods have a large number of uncertainties when applied across the entire Antarctic continent because the models were typically tuned to match processes seen on particular ice shelves. Here we present an alternative, statistics-based method to model the most probable zones of the location of fractures and demonstrate our approach on all main ice shelf regions in Antarctica, including the Antarctic Peninsula. We can predict the location of observed fractures with an average success rate of 84% for grounded ice and 61% for floating ice and a mean overestimation error rate of 26% and 20 %, respectively. We found that Antarctic ice shelves can be classified into groups based on the factors that control fracture location. [ABSTRACT FROM AUTHOR]