Ice‐Dynamical Glacier Evolution Modeling—A Review

Abstract

Glaciers play a crucial role in the Earth System: they are important water suppliers to lower‐lying areas during hot and dry periods, and they are major contributors to the observed present‐day sea‐level rise. Glaciers can also act as a source of natural hazards and have a major touristic value. Given their societal importance, there is large scientific interest in better understanding and accurately simulating the temporal evolution of glaciers, both in the past and in the future. Here, we give an overview of the state of the art of simulating the evolution of individual glaciers over decadal to centennial time scales with ice‐dynamical models. We hereby highlight recent advances in the field and emphasize how these go hand‐in‐hand with an increasing availability of on‐site and remotely sensed observations. We also focus on the gap between simplified studies that use parameterizations, typically used for regional and global projections, and detailed assessments for individual glaciers, and explain how recent advances now allow including ice dynamics when modeling glaciers at larger spatial scales. Finally, we provide concrete recommendations concerning the steps and factors to be considered when modeling the evolution of glaciers. We suggest paying particular attention to the model initialization, analyzing how related uncertainties in model input influence the modeled glacier evolution and strongly recommend evaluating the simulated glacier evolution against independent data.

Remote Sensing and Modeling of the Cryosphere in High Mountain Asia: A Multidisciplinary Review

“…However, models suffer from significant uncertainties due to oversimplifying key dynamics, inaccurate boundaries, initial conditions, and other energy balance terms and their temporal evolution. Hence, it is essential to disclose the mass redistribution process caused by glacier change to project the multi-decadal glacier evolution [230]. Studies now use glacier models coupled with MB and ice flow dynamics for long-term projections of glacier evolution.…”

“…It is vital to evaluate model performance to lower the uncertainty of future glacier change modeling. Model validation should be independent of the calibration procedure [230]. For instance, the runoff dataset should not be used for validation if it has been utilized for calibration.…”

Ice Thickness Measurement and Volume Modeling of Muztagh Ata Glacier No.16, Eastern Pamir

“…Glacier motion encompasses internal deformation, basal sliding, and the deformation of the subglacial sediment. The velocities at the ice surface, denoted as u(h), are a sum of the velocities from internal deformation (u d ) and the basal movement (u b ) [12,56,61].…”

“…Various methods can be used to measure ice thickness, including radio echo sounding [6,7], drilling [8], seismic surveys [9], and gravity measurements [10][11][12][13]. Given the substantial electrical resistivity of glacier ice and the pronounced contrast in electromagnetic impedance between ice and bedrock, ground-penetrating radar (GPR) technology is frequently employed to assess ice thickness [14][15][16][17].…”

Response of Two Glaciers in Different Climate Settings of the Tibetan Plateau to Climate Change Through Year 2100 Using a Hybrid Modeling Approach

“…As in the case of glacier dynamic models, physically‐based glacier dynamic models need a large number of glacier observations (e.g., ice thickness, glacier surface velocity, surface temperature, and glacier bedrock map) as forcing input, and the numerical simulation process is generally computationally expensive. But with the increasing availability of regional/global data sets such as glacier mass loss rates (Hugonnet et al., 2021), glacier terminus position (Kochtitzky & Copland, 2022), ice velocity (Millan et al., 2022) and ice thickness (Farinotti et al., 2019a), regional/global glacier dynamic modeling approaches have been increasingly applied in studies (Maussion et al., 2019; Wijngaard et al., 2019; Zekollari et al., 2022).…”