EPIC is happy to announce that we will be presenting at the AGU Fall Meeting, December 12 – 16, 2022. It is the most influential event in the world dedicated to the advancement of Earth and space sciences.
Earth Prediction Innovation Center (EPIC) Workshop: Running the Unified Forecast System (UFS) Short-Range Weather Application in the Cloud
Saturday, December 10th from 1:00pm – 5pm CT
The meeting will be held in Chicago and online everywhere. More than 25,000 attendees from more than 100 countries will convene to explore how Science Leads the Future. AGU will host a diverse community of scientists, students, journalists, policymakers, educators and organizations who are working toward a world where scientific discovery leads to scientific solutions, and where our global collaborations and partnerships can carry us into a sustainable future.
EPIC's Workshop at AGU
Earth Prediction Innovation Center (EPIC) Workshop: Running the Unified Forecast System (UFS) Short-Range Weather Application in the Cloud
Saturday, December 10th from 1:00pm – 5pm CT
McCormick Place – S103ab (South, Level 1)
This short course will teach students how to configure and run NOAA’s Unified Forecast System’s (UFS) Short Range Weather (SRW) Application on the Amazon Web Service (AWS) cloud computing platform. The UFS SRW App is a numerical weather prediction framework that targets predictions of atmospheric behavior on a limited spatial domain and on time scales from less than an hour out to several days. It is the foundation for improving NOAA’s predictions of hazardous convective storms made by convection-allowing ensemble forecast systems. The application does this by bringing together the essential components of the UFS regional modeling system under a single umbrella that runs these components as separate but interdependent tasks. These components include the Finite Volume Cubed (FV3) based prognostic UFS Weather Model, pre- and post-processing codes, verification, and a workflow for running the system end-to-end. The App is designed to be used by both researchers and in operations.
Outcome
Presenters
Technical Trainer
NOAA/Raytheon
Mandy graduated from the University of Massachusetts, Amherst with a B.A. in Communications and Information Technology. She has also completed the Flatiron Full-Stack Software Engineering Program as of August 2021. Before coming onto the EPIC program, Mandy taught STEM to middle and high school students. Currently, she is teaching community modeling basics on the EPIC program.
AUS Team Member
NOAA/Redline
Performance Solutions
Dr. Natalie Perlin has a background in engineering meteorology, atmospheric sciences, and modeling, and she received her Ph.D. from Tel-Aviv University. Dr. Perlin brings more than 25 years of experience in numerical modeling and data analysis in the areas of atmospheric and ocean sciences. She has worked on many projects that included model improvement and software development for users’ community, design, and implementation of coupled modeling systems, developing post-processing algorithms, and visualization methods applied to observational and modeling data in environmental sciences. Dr. Perlin started to work on NOAA EPIC program in 2022 as a Sr. Systems Engineer.
SME
NOAA/Tomorrow.io
Dr. Yi-Cheng Teng graduated from Virginia Institute of Marine Science (VIMS), College of William and Mary, with a PhD degree in Marine Science. Yi-Cheng has more than 10 years of experience in physical oceanography and numerical modeling. Before joining Tomorrow.io and EPIC program, Yi-Cheng has been an assistant professor and a principal investigator for multiple projects supported by NSF, DOE, and NOAA. Currently, he is a senior software engineer and working on infrastructure development of UFS Hierarchical Testing Framework.
Workshop Agenda
| Activity/Method | Content Description |
|---|---|
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Introductions |
Introduce speakers and their backgrounds. Let students know how they can ask questions and to whom they should direct questions. Introduce slack and how to use it. |
|
The UFS, EPIC, and the Short Range Weather Application |
Discuss the Short Range Weather App and it’s uses. |
|
Log In and Run Control Case |
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Modify Test Case |
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Modify Test Case Again |
|
|
Compare Outputs |
Have students run python scripts to compare the forecast outputs produced by their previous two cases. |
|
Application |
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Wrap-Up |
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Abstracts
The following abstracts from The EPIC Team were accepted for submission:
Continuous Integration Using Jenkins for the UFS Weather Model Development
by Jong Kim
Monday, December 12, 2022, 1:55pm – 2:05pm CST
Online Only
Summary: Jenkins offers a transparent and continuous integration (CI) framework for the UFS Weather Model and application codebases. As key components in the EPIC platform and infrastructure services to the UFS community, the Jenkins CI pipelines are reviewed in the presentation.
Building the Community Infrastructure for the Unified Forecast System
by Stelios Flampouis
Monday, December 12, 2022, 2:45pm – 6:15pm CST
McCormick Place – Poster Hall, Hall – A (South, Level 3)
Summary: EPIC’s Platform Team, led by Stelios Flampouris, will discuss the transformation and evolution of the infrastructure required for the UFS Weather Model (WM) and applications to provide the necessary support to the UFS community. The presentation will focus on the main developments and upgrades to code management, continuous integration and deployment, data management, and testing capabilities of the UFS WM, components, and applications.
Presenters
Product Owner/Vice President
EPIC Platform Team/Tomorrow.io
Stylianos “Stelios” Flampouris, Ph.D. (University of Hamburg), is the Vice President of Science and Technology for Tomorrow.io, leading edge-cutting multi-disciplinary (Numerical Weather Forecasting Modeling and Data Assimilation, Machine Learning Modeling, and Image Processing) research and operational teams and activities focused on Weather Prediction.
In parallel, Stelios is in charge of designing, implementing, and scaling the infrastructure required for the UFS Weather Model and Applications in support of the UFS Community within the EPIC Contract. The dual role of Stelios is the first demonstration of the first public-private development of the UFS Weather Model.
Over the past two decades, Stelios has served at NOAA (USA) in multiple roles, Naval Research Lab (USA), and Heron Center (Germany), leading innovation and teams on the subjects of Coupled Modeling and Data Assimilation, High-Performance Computing, and Signal Processing.
Product Owner/Vice President
EPIC Platform Team/Tomorrow.io
Stylianos “Stelios” Flampouris, received his Ph.D. from the University of Hamburg. He is currently the Vice President of Science and Technology for Tomorrow.io, leading cutting-edge multi-disciplinary research and operational teams and activities focused on Weather Prediction (particularly numerical weather forecasting, modeling, and data assimilation; machine learning modeling; and image processing).
Over the past two decades, Stelios has served in the U.S. at NOAA (in multiple roles) and at the Naval Research Lab, as well as at Germany’s Heron Center, leading teams and innovation on the subjects of coupled modeling and data assimilation, high-performance computing, and signal processing.
For the EPIC program, Stelios is in charge of designing, implementing, and scaling the infrastructure required for the UFS Weather Model and related applications in support of the UFS community.
Lead Configuration/Code Manager
NOAA/Raytheon
Jong Kim works as a lead configuration and code manager for the NOAA EPIC program to support the UFS Weather Model and application releases.
Before joining EPIC, he led the Marine Data Assimilation Team at NOAA Environmental Modeling Center (EMC). Through the UFS-R2O marine reanalysis project, the Next Generation Global Ocean Data Assimilation System (NG-GODAS) was successfully demonstrated in the JEDI-based Sea-Ice Ocean and Coupled Assimilation (SOCA) framework.
Jong also spent about 12 years as a lead software engineer for the Global Modeling and Assimilation Office (GMAO) at NASA. His early career included a computational scientist position at the Mathematics and Computer Science Division of the DOE Argonne National Lab. He holds a Ph.D. in Chemical Engineering from the University of Utah.
