1 / 9

PEcAn

PEcAn. The P redictive Ec osystem An alyzer. Motivation. Synthesize heterogeneous data Bridge gap between conceptual and computational models Summarize what we know, based on available data and mechanistic models

step
Télécharger la présentation

PEcAn

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PEcAn The Predictive Ecosystem Analyzer

  2. Motivation • Synthesize heterogeneous data • Bridge gap between conceptual and computational models • Summarize what we know, based on available data and mechanistic models • Identify sources of uncertainty -> prioritize data collection and model improvement • Make complex workflows accessible, reproducible, and extensible

  3. Design • Modular: • models can be coupled within PEcAn • PEcAn can be embedded into other workflows • High level functions • e.g. ‘run.meta.analysis’; ‘start.model.runs(model)’ • Web Interface • Remote execution of simulation models on HPC • Adoption of existing standards, libraries where possible • Virtual Machines easy to get up and running

  4. Modules • Analysis: • Meta-analysis • Data assimilation • Visualization • Priors • Uncertainty • more … • Utilities: • QAQC • Database • Logger • Settings • Models (min 2 functions each): • Ecosystem Demography v2 • BioCro • Sipnet • Dalec

  5. Site BETYdb: Informatics Backend • Citation Treatment Management Cultivar Traits, Yields, Ecosystem Services Species Covariates Variable Prior Functional Type

  6. Site BETYdb (part II): Model provenance • Citation Treatment Management Runs Ensembles Cultivar Workflows Posteriors Site Species Models Inputs Traits, Yields, Ecosystem Services Machines Variable Covariates Functional Type Variable Prior Functional Type

  7. PEcAn: Web Interface Configure Run Review Previous Runs Visualize, Export Results Analysis in R

  8. Future Directions • Model Intercomparisons • Integration into existing workflows • Automated ‘real-time’ data assimilation • Improved web-interface – enable end users to ask new questions

  9. More Information • Who: • David LeBauer, University of Illinois • Mike Dietze, Boston University • Rob Kooper, National Center for Supercomputing Applications • Shawn Serbin, Brookhaven National Laboratories • Where: • pecanproject.org • github.com/PecanProject • Funding: • Energy Biosciences Institute, NSF

More Related