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This paper provides the first description of the open-source Glacier Energy and Mass Balance model. GEMB models the ice sheet and glacier surface–atmospheric energy and mass exchange, as well as the firn state. It is a column model (no horizontal communication) of intermediate complexity that includes those processes deemed most relevant to glacier studies. GEMB prioritizes computational efficiency to accommodate the very long (thousands of years) spin-ups necessary for initializing deep firn columns and sensitivity experiments needed to characterize model uncertainty on continental scales. The model is one-way coupled with the atmosphere, which allows the model to be run offline with a diversity of climate forcing but neglects feedback to the atmosphere. GEMB provides numerous parameterization choices for various key processes (e.g., albedo, subsurface shortwave absorption, and compaction), making it well suited for uncertainty quantification and model exploration. The model is evaluated against the current state of the art and in situ observations and is shown to perform well. [ABSTRACT FROM AUTHOR]

This paper provides the first description of version 1.0 of the open-source Glacier Energy and Mass Balance model. GEMB models the ice sheet and glacier surface-atmospheric energy and mass exchange, and firn state. It is a column model (no horizontal communication) of intermediate complexity that includes those processes deemed most relevant to glacier studies with the goal of retaining computational efficiency that can accommodate the very long (thousands of years) spin-ups necessary for initializing deep firn columns and for running sensitivity experiments to characterize model uncertainty on continental scales. The model is one-way coupled with the atmosphere which allows the model to be run off-line with a diversity of climate forcing but neglects feedback to the atmosphere. GEMB provides numerous parameterization choices for various key processes (e.g. albedo, subsurface shortwave absorption, and compaction), making it well suited for uncertainty quantification and model exploration. The model is evaluated against the current state-of-the-art and in situ observations and is shown to perform well. [ABSTRACT FROM AUTHOR]