10 Joint Special Session: The Earth Prediction Innovation Center to Accelerate Community-Developed Scientific and Technological Enhancements into the Operational Applications for Numerical Weather Prediction


Description:

The Earth Prediction Innovation Center (EPIC) was created in response to the congressional charge to accelerate the development of the U.S. capacity to make early, accurate, and effectively communicated environmental predictions. It is designed to support, sustain, and foster the collaborative work being done by the participating members of the Unified Forecast System (UFS). EPIC is designed to be the catalyst for community research and modeling advances that continually inform and accelerate advances in our nation’s operational forecast modeling systems. Additionally, EPIC ensures that NOAA’s operational needs and the research and development community are supported by an effective research to operations to research (R2O2R) process resulting in improved numerical weather prediction (NWP) capacity and a more streamlined R2O2R process. EPIC will meet this goal by improving accessibility and usability of the UFS for community members.

This special session on the Earth Prediction Innovation Center to Accelerate Community-Developed Scientific and Technological Enhancements into the Operational Applications for Numerical Weather Prediction, Joint between the Second Symposium on Earth Prediction Innovation and Community Modeling and the 13th Conference on Transition of Research to Operations, is aimed at providing highlights on the accomplishments thus far, and how EPIC is enabling and extending infrastructure and user support for the UFS to fully coupled Earth system prediction, transforming the operational suite of models into one modeling system.
Conveners: Vijay S. Tallapragada, NOAA, and Jose-Henrique G. M. Alves, NOAA/OAR


Papers:
Activities and preliminary results from the 1st Hybrid NOAA/Hazardous Weather Testbed Spring Forecasting Experiment
Adam J. Clark, NSSL, Norman, OK; and I. L. Jirak, T. A. Supinie, J. Vancil, D. E. Jahn, K. H. Knopfmeier, Y. Wang, P. Heinselman, L. J. Reames, P. S. Skinner, P. C. Burke, K. A. Hoogewind, J. Martin, M. L. Flora, L. J. Wicker, B. C. Matilla, M. Krocak, D. Dowell, C. Schwartz, M. G. Duda, W. Skamarock, A. L. Brannan, C. Karstens, E. D. Loken, N. A. Dahl, D. R. Harrison, D. A. Imy, A. Wade, J. Picca, and J. Milne

Alleviation of low humidity biases in WRF-ARW and UFS-SRW model simulations over complex terrain
Max R. Marchand, Tomorrow.io, Naples, FL; and S. Davis, A. Pattantyus, P. P. Rama Durga Surya, and S. Flampouris

Upgrade the Chemistry Component of the Next Generation Regional Air Quality Forecast System: UFS-AQM
Wei Li, George Mason University, Fairfax, VA; NOAA, College Park, MD; and B. Tang, Y. Tang, P. C. Campbell, Z. Moon, B. Baker, I. Stajner, and R. Montuoro

Submission Deadline: Thursday, 31 August 2023