9.2 Cycling MPAS+JEDI developments for the new regional Rapid Refresh Forecast System (RRFS)

Wednesday, 15 January 2025: 8:45 AM
232 (New Orleans Ernest N. Morial Convention Center)
Guoqing Ge, CIRES and NOAA/GSL, Boulder, CO; and M. Hu, S. Liu, D. Dowell, C. Zhou, J. Hu, S. Pan, H. Lin, T. lei, D. E. Lippi, X. Zhang, S. K. Degelia, H. Liu, D. T. Kleist, B. J. Jung, T. Sun, Z. Liu, C. Snyder, T. T. Ladwig, and S. S. Weygandt

NOAA’s Global Systems Laboratory (GSL), Environmental Modeling Center (EMC), NSF NCAR/MMM, JCSDA, and other partners, have been collaborating on the development of a new version of the Rapid Refresh Forecast System (RRFS). This version will incorporate the Model for Prediction Across Scales (MPAS) atmospheric model as its dynamic core and utilize the Joint Effort for Data-assimilation Integration (JEDI) system as the analysis framework.

The MPAS model has demonstrated significant potential during the recent NOAA Spring Forecast Experiments. It delivered storm forecasts comparable to the current NOAA operational regional model, HRRRv4, when initialized from HRRRv4 or RRFSv1 analyses. Integrating a data assimilation component and coupling MPAS with advanced GSL physics are expected to yield substantial improvements in storm forecasting capabilities.

The JCSDA JEDI system is a cutting-edge, unified data assimilation framework that delivers advanced data assimilation techniques, excellent interoperability, and robust scalability. This system is expected to enhance the overall performance and accuracy of the RRFS system.

Efforts have been made to establish a cycling MPAS+JEDI framework, based on the MPAS model and the JEDI-powered RDASApp. This framework is designed to facilitate scientific advancements in both modeling and data assimilation research. Three different domain and grid configurations—Conus 12km, Conus 3km, and Atlantic 12km—are now available to support various applications, enabling scientific progress on multiple fronts.

The experiments can be conducted in both real-time and retrospective modes, allowing for comprehensive testing and validation of the RRFS system. Efforts have been devoted to testing, tuning, and improving the data assimilation and model configurations. Preliminary results from these efforts will be presented at the conference, showcasing the potential of the new RRFS system to deliver superior storm forecasting and improve our understanding of the atmosphere. These advancements represent a good step in operational weather prediction and scientific research, contributing to the overall NOAA mission to provide accurate and timely weather forecasts and warnings.

List of acronyms:

NSF: National Science Foundation

NCAR: National Center for Atmospheric Research

MMM: Mesoscale and Microscale Meteorology

JCSDA: Joint Center for Satellite Data Assimilation

NOAA: National Oceanic and Atmospheric Administration

GSL: Global Systems Laboratory

NWS: National Weather Service

NCEP: National Centers for Environmental Prediction

EMC: Environmental Modeling Center

CIRES: Cooperative Institute for Research in Environmental Sciences

HRRR: High-Resolution Rapid Refresh

RRFS: Rapid Refresh Forecast System

MPAS: Model for Prediction Across Scales

JEDI: Joint Effort for Data-assimilation Integration

RDASApp: App for the RRFS Data Assimilation System

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