Abstract
Abstract. Glacier changes are a vivid example of how environmental systems react to a changing climate. Distributed surface mass balance models, which translate the meteorological conditions on glaciers into local melting rates, help to attribute and detect glacier mass and volume responses to changes in the climate drivers. A well-calibrated model is a suitable test bed for sensitivity, detection, and attribution analyses for many scientific applications and often serves as a tool for quantifying the inherent uncertainties. Here, we present the open-source COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY), which provides a flexible and user-friendly framework for modeling distributed snow and glacier mass changes. The model has a modular structure so that the exchange of routines or parameterizations of physical processes is possible with little effort for the user. The framework consists of a computational kernel, which forms the runtime environment and takes care of the initialization, the input–output routines, and the parallelization, as well as the grid and data structures. This structure offers maximum flexibility without having to worry about the internal numerical flow. The adaptive subsurface scheme allows an efficient and fast calculation of the otherwise computationally demanding fundamental equations. The surface energy balance scheme uses established standard parameterizations for radiation as well as for the energy exchange between atmosphere and surface. The schemes are coupled by solving both surface energy balance and subsurface fluxes iteratively such that consistent surface skin temperature is returned at the interface. COSIPY uses a one-dimensional approach limited to the vertical fluxes of energy and matter but neglects any lateral processes. Accordingly, the model can be easily set up in parallel computational environments for calculating both energy balance and climatic surface mass balance of glacier surfaces based on flexible horizontal grids and with varying temporal resolution. The model is made available on a freely accessible site and can be used for non-profit purposes. Scientists are encouraged to actively participate in the extension and improvement of the model code.
Highlights
Glacier variations are of great interest and relevance in many scientific issues and application such as climate sciences, water resources management, and tourism
Distributed surface mass balance models, which translate the meteorological conditions on glaciers into local melting rates, help to attribute and detect glacier mass and volume responses to changes in the climate drivers
The model can be set up in parallel computational environments for calculating both energy balance and climatic surface mass balance of glacier surfaces based on flexible horizontal grids and with varying temporal resolution
Summary
Glacier variations are of great interest and relevance in many scientific issues and application such as climate sciences, water resources management, and tourism. The models range from simple degree-day models (e.g., Radicand Hock, 2006; Schuler et al, 2005) to intermediate models (e.g., Machguth et al, 2009) and complex snow cover and glacier-resolving physical models (e.g., Bartelt and Lehning, 2002; Vionnet et al, 2012; Hock and Holmgren, 2005; Klok and Oerlemans, 2002; Sicart et al, 2011; Weidemann et al, 2018; Huintjes et al, 2015b; Mölg et al, 2009; Michlmayr et al, 2008; van Pelt et al, 2012) The latter model class is usually based on the same fundamental physical principles but differs in the parameterization schemes and implementation techniques.
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