Storm-based verification and intercomparison of forecasts during May and June 2023 from the HRRR, RRFS, NSSL MPAS, and C-SHiELD models
Potvin, C. K., Reames, L. J., Clark, A. J., Knopfmeier, K. H., Wang, Y., et al. (2026). Storm-based verification and intercomparison of forecasts during May and June 2023 from the HRRR, RRFS, NSSL MPAS, and C-SHiELD models. Weather and Forecasting, doi:https://doi.org/10.1175/waf-d-25-0019.1
| Title | Storm-based verification and intercomparison of forecasts during May and June 2023 from the HRRR, RRFS, NSSL MPAS, and C-SHiELD models |
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| Genre | Article |
| Author(s) | C. K. Potvin, L. J. Reames, A. J. Clark, K. H. Knopfmeier, Y. Wang, D. C. Dowell, Michael G. Duda, T. A. Jones, E. R. Mansell, William Skamarock, L. J. Wicker, N. Yussouf |
| Abstract | Most current convection-allowing models (CAMs) in the United States use one of three dynamical cores: the Advanced Research version of the Weather Research and Forecasting (ARW) Model, the Finite-Volume Cubed-Sphere (FV3) model, or the Model for Prediction Across Scales (MPAS). The NSSL Warn-on-Forecast System (WoFS), a rapidly updating storm-scale ensemble targeting 0–6-h lead times, uses the ARW. However, with NSF NCAR ending support of ARW, and NOAA’s transition to the Unified Forecast System (UFS), WoFS will need a new dynamical core. Given recently identified limitations of the FV3 for storm-scale prediction, NSSL began running three daily MPAS CAMs to assess MPAS as a next-generation dynamical core for both WoFS and Environmental Modeling Center (EMC)’s contiguous United States (CONUS)-domain Rapid Refresh Forecast System (RRFS). The three MPAS models differ only in microphysics and driving model—the RRFS or the High-Resolution Rapid Refresh (HRRR)—and all five models share similar physics. These models, along with GFDL’s FV3-based CONUS System for High-Resolution Prediction on Earth-to-Local Domains (C-SHiELD), were evaluated and compared in the 2023 Hazardous Weather Testbed Spring Forecasting Experiment (SFE). We complement the subjective SFE findings using a storm object framework to verify and compare the models’ 0000 UTC forecasts of convective environments and storm morphology. We analyze 1–36-h forecast times over May–June 2023. Our results are consistent with the SFE findings, supporting consideration of MPAS for the WoFS and other next-generation CAMs and illuminate the systematic impacts of dynamical core, driving model, and microphysics scheme in CAMs. Significance Statement Optimizing weather modeling systems requires understanding the impacts of key model design choices. We compared forecasts from six high-resolution models to identify differences in their representation of thunderstorms and thunderstorm environments. We found that the Model for Prediction Across Scales (MPAS) is competitive with the Advanced Research version of the Weather Research and Forecasting (ARW) Model, the dynamical core used by the leading operational high-resolution model. We also estimated systematic impacts on forecasts of different choices for dynamical core, microphysics scheme, and the parent model used to provide the initial and lateral boundary conditions for the high-resolution model. |
| Publication Title | Weather and Forecasting |
| Publication Date | Jan 1, 2026 |
| Publisher's Version of Record | https://doi.org/10.1175/waf-d-25-0019.1 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d7tf02wj |
| OpenSky Listing | View on OpenSky |
| MMM Affiliations | WMR |