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# What is QuickView?
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**EAM QuickView** is an open-source, interactive visualization tool designed for
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scientists working with the atmospheric component of the
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[Energy Exascale Earth System Model (E3SM)](https://e3sm.org/), known as the
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E3SM Atmosphere Model (EAM). Its Python- and
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[Trame](https://www.kitware.com/trame/)-based Graphical User Interface (GUI)
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**QuickView** is an open-source, interactive visualization tool designed for
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scientists working with the
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[Energy Exascale Earth System Model (E3SM)](https://e3sm.org/),
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with an initial focus on the horizontal meshes used by the atmosphere component, EAM.
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QuickView's Python- and
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[trame](https://www.kitware.com/trame/)-based User Interface (UI)
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provides intuitive access to [ParaView](https://www.paraview.org/)'s powerful
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analysis and visualization capabilities, without the steep learning curve.
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![E3SM QuickView](/banner.png){ width="100%" }
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analysis and visualization capabilities without requiring a steep learning curve.
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## Quick Start
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- Optional: download
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[sample simulation output](https://zenodo.org/records/16922607) to test the
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app.
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- For EAMv2 and v3 developers and users: if your simulation data files are _not_
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the original files written out by the model, i.e., if your files were
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generated by NCO, CDO, etc. check QuickView's
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[data format requirements](../data).
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- For EAMxx developers and users: EAMxx's most recent output format changes
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might not have been accommodated. If your run into problems opening your data
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files, please check the
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[Issues tab on GitHub](https://github.com/Kitware/QuickView/issues) and open a
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new issue if needed.
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For more details, go to the navigation bar of this website and look for our
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User's Guide.
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functions, and jargon. Moreover, these general-purpose tools may lack
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out-of-the-box support for key requirements in atmospheric sciences, such as
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globe and map projections or support for specific data formats and structures,
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leading to time-consuming customization or feature requests. EAM QuickView was
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leading to time-consuming customization or feature requests. QuickView was
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developed to address these limitations by offering a focused, user-friendly
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platform that streamlines the analysis of atmospheric simulations. It minimizes
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the need for EAM developers and users to write custom scripts, thereby
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the need for E3SM developers and users to write custom scripts, thereby
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shortening the path from data to insight.
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The core goal of EAM QuickView is a first glance at the contents in a simulation
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The core goal of QuickView is a first glance at the contents in a simulation
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data file, i.e., a first inspection of the characteristic values of physical
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quantities and their variations with respect to geographical location, altitude,
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and time, as well as a quick inspection across different physical quantities for
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similarities or distinctions. Compared to earlier and widely used tools like
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[ncview](https://cirrus.ucsd.edu/ncview/) and
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[ncvis](https://github.com/SEATStandards/ncvis), QuickView has an emphasis on
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multivariate visualization and is currently focused on the EAM model.
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multivariate visualization and is currently focused on E3SM.
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## Key Features
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## Project Background
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The lead developer of EAM QuickView is
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[Abhishek Yenpure (abhi.yenpure@kitware.com)](https://www.kitware.com/abhishek-yenpure/)
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at [Kitware, Inc.](https://www.kitware.com/). Other key contributors at Kitware,
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Inc. include Berk Geveci and Sebastien Jourdain. Key contributors on the
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atmospheric science side are Hui Wan and Kai Zhang at
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The lead developer of QuickView version 2 is
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[Sebastien Jourdain (sebastien.jourdain@kitware.com)](https://www.kitware.com/sebastien-jourdain/)
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at [Kitware](https://www.kitware.com/). Other key contributors at Kitware
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include Berk Geveci, Dan Lipsa, and Will Dunklin.
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Key contributors on the atmospheric science side are Hui Wan and Kai Zhang at
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[Pacific Northwest National Laboratory](https://www.pnnl.gov/atmospheric-climate-and-earth-sciences-division).
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EAM QuickView is a product of an interdisciplinary collaboration supported by
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QuickView is a product of an interdisciplinary collaboration supported by
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the U.S. Department of Energy Office of Science’s
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[Advanced Scientific Computing Research (ASCR)](https://www.energy.gov/science/ascr/advanced-scientific-computing-research)
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and

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