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\begin{document}

\title{Mapping dynamic mass loss by fully decomposing glacier elevation change}



\author[1]{Whyjay Zheng}%
\author[1]{Facundo Sapienza}%
\author[2]{Matthew Siegfried}%
\author[3]{Shane Grigsby}%
\author[2]{Tasha Snow}%
\author[1]{Fernando Perez}%
\author[4]{Jonathan Taylor}%
\affil[1]{University of California Berkeley}%
\affil[2]{Colorado School of Mines}%
\affil[3]{NASA Goddard Space Flight Center}%
\affil[4]{Stanford University}%


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  \date{May 24, 2024}


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\begin{abstract}
Glaciers and ice sheets lose their mass by ablation (the output term of
their surface mass balance) and discharging into a water body (dynamic
loss). The latter is associated with multiple physical characteristics
such as bed geometry, inland thinning, terminus stability, and basal
conditions. Better assessing the dynamic loss, especially its
spatiotemporal variability within a drainage basin, will help improve
our understanding of the underlying processes and quantify the future
contribution of sea level rise. We propose a new inverse model to
decompose glacier elevation change and optimize the dynamic mass loss
components for each pixel of the elevation data grid. The model unmixes
the observed elevation change from remote sensing data using the modeled
surface mass balance and the ice flux as constraints. We use two
approaches to design the ice flux term; one is based on glacier surface
velocity and the conservation of mass, and the other builds on the flow
law and the Shallow Ice Approximation. We test the model for selected
marine-terminating glacier outlets in the Greenland ice sheet. If the
surface velocity can be decomposed into short-term (seasonal) and
multi-year signals, our model may be able to further resolve the dynamic
loss components of different physical processes.%
\end{abstract}%



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