Joint WRF and MPAS Users' Workshop

Participants of 2017 WRF Workshop photo

This is a joint workshop for WRF (Weather Research and Forecasting Model) and MPAS-A. (The Model for Prediction Across Scales - Atmosphere). The MPAS-A model is a global nonhydrostatic atmospheric model that has been developed for weather, climate, and regional climate applications. Its horizontal mesh is based on an unstructured spherical centroidal Voronoi tesselation (nominally hexagons) with C-grid staggering that permit both quasi-uniform and variable-resolution configurations.  MPAS-A numerics are essentially those used in WRF-ARW adapted to the Voronoi mesh, and the model uses a subset of WRF physics.

The workshop will take place at the NCAR's Center Green Campus, Boulder, Colorado, on 11-15 June 2018.

Call for Papers

The primary objectives for the Users' Workshop are to provide updates for WRF and MPAS modeling systems, to discuss model development and issues and to present evaluations and applications of the two models. Papers focusing on development and testing of model applications in all areas are encouraged. This year we especially seek contributions on model physics development and evaluation for both regional and global applications.
Authors are given the option of requesting either a poster or an oral presentation; however, we strongly encourage authors to consider submissions for a poster presentation, due to time constraints for oral sessions. To submit an abstract please go to the registration page.

Other Activities at the Workshop

Lecture Series 

Model Unification Efforts at NCAR (Monday, June 11, 1:30 - 5:00 pm)

In order to enable frontier weather and climate science at NCAR and in the research community, NCAR recently began developing a roadmap to unify and improve its community atmospheric modeling efforts. This session will provide an overview of the evolving motivation, vision, and scope for this endeavor, followed by presentations and discussions on specific aspects of model unification. These topics will include the dynamical core, model physics, data assimilation, and the software infrastructure, and will focus on science targets, common requirements, strategies for moving forward, and implications for current modeling systems. Discussions will also explore how best to engage strong community input and involvement that is essential for the success of this project.

Five Parallel Mini-Tutorials will be held on Friday:

VAPOR (8:30 - 12:00) (limited seating) link to VAPOR: - CISL/NCAR  
VAPOR is an application developed by NCAR for 3D scientific data visualization.  It is free to use, open source, and runs on OSX, Windows, and Linux.In this session, users will be given an interactive tutorial on how to use VAPOR to produce 3D images and movies from WRF data. VAPOR contains a set of renderers that can be used to demonstrate various weather features. This tutorial will interactively demonstrate to users how these renderers can be used to visually explore the regions and features of interest within model data, and how to depict these regions in an aesthetically pleasing and scientifically publishable way.

Visualizing WRF-ARW and MPAS Data Using NCL (8:30 - 10:00) - NCAR/CISL
This tutorial introduces the use of NCL to visualize WRF-ARW and MPASdata. The tutorial will include demonstrations of creating contour andvector plots of WRF-ARW data, creating filled contours of data on MPAS meshes, and further customizing NCL graphics by adding shapefile outlines, titles, and other annotations. If time permits, the tutorial will briefly cover regridding WRF-ARW and MPAS data, using shapefilesto select areas of interest, and creating animations.
Analyzing and Visualizing WRF-ARW Data Using WRF-Python and Other Python Tools (10:30-12:00) - NCAR/CISL
This tutorial introduces the WRF-Python module, a Python implementation of the WRF-NCL diagnostics package. This package was first released in early 2017 and is developed by the same team that develops NCL. This tutorial will include a brief introduction to using Jupyter Notebook for editing and running Python scripts, along with a brief overview of commonly used scientific packages like numpy, xarray, and netcdf4-python. The focus will be on using WRF-Python to calculate a variety of WRF diagnostics, using WRF-Python's plottingutilities to help with plotting via matplotlib and cartopy, and how to improve performance using multicore support provided by OpenMP.

Proper Care and Feeding of Your Cloud-Based WRF (WRF in the Cloud) (8:30 - 10:00) - MMM/NCAR and Amazon Web Services  
This mini-tutorial is geared towards WRF users who would like an early look at what the NCAR team is planning to do in the cloud. The course will cover the basics of cloud computing, and how to do real work right away: manufacturing a cluster, looking at images, building and running the WRF system code, accessing real-time GFS and HRRR file, and archiving data. We will take you on a jargon- and acronym-filled whirlwind tour of cloud computing, with a special emphasis on the WRF system, and all you need to bring is your laptop. AWS is supplying the computational credits for our practice, and NCAR is supplying the guest logins. You will build and run WRF in the AWS cloud by the end of this class.

Simplifying End-to-end Numerical Modeling Using Software Containers (WRF in Docker) (10:30 - 12:00) - JNT/NCAR  
The goal of this instructional session is to raise awareness abouttools and facilities available to the community for testing and evaluating of numerical weather prediction (NWP) innovations, including the emerging set of software tools in Docker containers. Recently, the concept of containers has been gaining popularity because they allow for software systems to be bundled (including operating system, libraries, code, and executables) and provided directly to users, eliminating possible frustrations with up-front system setup. This session will provide information on using software containers that have been established for community use to quickly spin up an NWP forecast system [using the Weather Research and Forecasting (WRF) model] that can then be post-processed [using the Unified Post Processor (UPP)] and verified [using the Model Evaluation Tools (MET)].


Please click here or go to the registration page to register for the workshop and submit papers. 

WRF Helpdesk

During the workshop, the WRF helpdesk will be open for several sessions for users to discuss their special issues with developers. 


Registration opens 20 March.
Abstract submission deadline is 20 April.
Early registration ends: 25 May.
Late registration begins: 26 May.
If you cancel your registration prior to 25 May, we will refund your registration minus $25 to cover administrative costs. 
After 25 May, no refund will be given for cancellations.
* Please note: any abstract changes made beginning 20 April will be made online but not in the printed agenda and any abstracts submitted or changed after 25 May should be emailed to "wrfhelp at ucar dot edu".
 Workshop Publication

Workshop presentations and extended abstracts will be published on our website via links provided during the workshop. (You may indicate that you do NOT want us to publish your abstract when you submit it). Extended abstracts in PDF format can be submitted via the registration page, and will appear on the web before the workshop. 

We would like to encourage all poster presenters to provide us with an electronic (preferably .pdf format) version of their posters (or a short .pdf  file describing the poster) so that we can post it on our website prior to the workshop. Please email these to "wrfhelp at ucar dot edu". If presenters are not able to submit them to us before the workshop, we will still be accepting them afterward, and we will post them upon receipt.

Workshop Registration Fees

Early registration fee is $200.00. The late registration fee is $250.00.


Blocks of hotel rooms have been reserved at three different Boulder hotels. Please click on the "Lodging" Tab at the top of our website for details.
Workshop Planning Committee
Jimy Dudhia, Georg Grell, Joe Klemp, Cliff Mass, Louisa Nance, Jordan Powers, and Wei Wang
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