Tucker - EXPLORING EARTH'S SURFACE WITH COMMUNITY MODELS: THE CSDMS PYTHON MODELING TOOL
|Resource type:||Composite Resource|
|Created:||Dec 06, 2018 at 6:29 p.m.|
|Last updated:||Dec 06, 2018 at 6:30 p.m. by Leslie Hsu|
TUCKER, Gregory E., CIRES & Department of Geological Sciences, University of Colorado, 2200 Colorado Ave, Boulder, CO 80309-0399; Community Surface Dynamics Modeling System (CSDMS), University of Colorado, Campus Box 399, Boulder, CO 80309, HUTTON, Eric, Community Surface Dynamics Modeling System (CSDMS), University of Colorado, Cam, Boulder, CO 80309 and PIPER, Mark, Community Surface Dynamics Modeling System (CSDMS), University of Colorado, Campus Box 399, Boulder, CO 80309; Instaar, University of Colorado, campus Box 450, 1560 30th St, Boulder, CO 80303
Our planet’s surface is a restless place. Understanding the processes of weathering, erosion, and deposition that shape it is critical for applications ranging from short-term hazard analysis to long-term sedimentary stratigraphy and landscape/seascape evolution. Improved understanding requires computational models, which link process mechanics and chemistry to the observable geologic and geomorphic record. Historically, earth-surface process models have often been complex and difficult to work with. To help improve this situation and make the discovery process more efficient, the CSDMS Python Modeling Tool (PyMT) provides an environment in which community-built numerical models and tools can be initialized and run directly from a Python command line or Jupyter notebook. By equipping each model with a standardized set of command functions, known collectively as the Basic Model Interface (BMI), the task of learning and applying models becomes much easier. Using BMI functions, models can also be coupled together to explore dynamic feedbacks among different earth systems. To illustrate how PyMT works and the advantages it provides, we present an example that couples a terrestrial landscape evolution model (CHILD) with a marine sediment transport and stratigraphy model (SedFlux3D). Experiments with the resulting coupled model provide insights into how terrestrial “signals,” such as variations in mean precipitation, are recorded in deltaic stratigraphy. The example also illustrates the utility of PyMT’s tools, such as the ability to map variables between a regular rectilinear grid and an irregular triangulated grid. By simplifying the process of learning, operating, and coupling models, PyMT frees researchers to focus on exploring ideas, testing hypotheses, and comparing models with data.
How to cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/
|Greg Tucker||University of Colorado at Boulder;Cooperative Institute for Research in Environmental Sciences;Community Surface Dynamics Modeling System (CSDMS)|
Select content in the file browser to see metadata specific to that content. Metadata will only display here when the the content is selected above. Content specific metadata does not display on the Discover page.
Please wait for the process to complete.