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Model Information Inputs Outputs Workflow
Name (e.g., CRHM)
Cosipy
Full Name (e.g., Cold Regions Hydrological Model)
COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY)
Description
Cosipy is a framework for modeling distributed snow and glacier mass changes. Cosipy has a modular structure so that an exchange of routines or parameterizations of physical processes is possible with little effort. 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. https://cryo-tools.org/tools/cosipy
Institution
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Purpose
Provides a 1D-energy and mass balance model for glacier ice bodies.
Contact Persons
NameRoleContact Information
Tobias Sauter
Primary Contact
tobias.sauter@fau.de
Minimum Input Data
Input DataUnits (if specific or preferred)Additional Information
Shortwave Radiation In
W m-2
Temperature
K
2 m
Relative Humidity
%
2 m
Pressure
hPa
Wind Speed
m s-1
2 m
all-phase precipitation
mm
cloud cover fraction
Calibration Data
No calibration
Validation Data
SWE , runoff and satellite data derived snow cover, and snow height from point recordings and laser scans. See https://doi.org/10.5194/tc-10-1859-2016
Model Outputs
OutputsAdditional Information
1D snow cover evolution
glacier mass balance
Source Code Availability
https://github.com/cryotools/cosipy
Model Workflow
https://gmd.copernicus.org/articles/13/5645/2020/
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T-2022-09-06-n1HEn32SCsZkKEjKn3CBHZRvQ Model 1.0