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Title: sympl (v. 0.4.0) and climt (v. 0.15.3) – towards a flexible framework for building model hierarchies in Python

Journal Article · · Geoscientific Model Development (Online)
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]
  1. Stockholm Univ. (Sweden)
  2. Univ. of Washington, Seattle, WA (United States)
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sympl (System for Modelling Planets) andclimt (Climate Modelling and Diagnostics Toolkit) are anattempt to rethink climate modelling frameworks from the ground up. The aimis to use expressive data structures available in the scientific Pythonecosystem along with best practices in software design to allow scientists toeasily and reliably combine model components to represent the climate systemat a desired level of complexity and to enable users to fully understandwhat the model is doing. sympl is a framework which formulates the model in terms of astate that gets evolved forward in time or modified within a specifictime by well-defined components. sympl's design facilitates buildingmodels that are self-documenting, are highly interoperable, and providefine-grained control over model components and behaviour. symplcomponents contain all relevant information about the input they expect andoutput that they provide. Components are designed to be easily interchanged,even when they rely on different units or array configurations.sympl provides basic functions and objects which could be used inany type of Earth system model. climt is an Earth system modelling toolkit that contains scientificcomponents built using sympl base objects. These include both purePython components and wrapped Fortran libraries. climt providesfunctionality requiring model-specific assumptions, such as stateinitialization and grid configuration. climt's programming interfacedesigned to be easy to use and thus appealing to a wide audience. Model building, configuration and execution are performed through a Pythonscript (or Jupyter Notebook), enabling researchers to build an end-to-endPython-based pipeline along with popular Python data analysis andvisualization tools.

Research Organization:
Univ. of Washington, Seattle, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
SC0016433
OSTI ID:
1511001
Journal Information:
Geoscientific Model Development (Online), Vol. 11, Issue 9; ISSN 1991-9603
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

References (12)

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Reproducible Research in Computational Science journal December 2011
The Gap between Simulation and Understanding in Climate Modeling journal November 2005
Idealized tropical cyclone simulations of intermediate complexity: A test case for AGCMs journal February 2012
xarray: N-D labeled Arrays and Datasets in Python journal April 2017
A perspective on climate model hierarchies: MODEL HIERARCHIES journal August 2017
A Gray-Radiation Aquaplanet Moist GCM. Part I: Static Stability and Eddy Scale journal October 2006
The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability journal July 2016
OpenMP: an industry standard API for shared-memory programming journal January 1998

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A Python-enhanced urban land surface model SuPy (SUEWS in Python, v2019.2): development, deployment and demonstration journal January 2019

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