Bridging the gap between global weather prediction and global storm‐resolving simulation: Introducing the GFDL 6.5‐km SHiELD

We introduce a 6.5‐km version of the Geophysical Fluid Dynamics Laboratory (GFDL)'s System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD). This global model is designed to bridge the gap between global medium‐range weather prediction and global storm‐resolving simulation while remaining practical for real‐time forecast. The 6.5‐km SHiELD represents a significant advancement over GFDL's flagship global forecast system, the 13‐km SHiELD. This global model features a holistically‐developed scale‐aware suite of physical parameterizations, stepping into the formidable convective “gray zone” of resolutions below 10 km. Comparative analyses with the 13‐km SHiELD, conducted over a 3‐year hindcast period, highlight noteworthy improvements across global‐scale, regional‐scale, tropical cyclone (TC), and continental convection predictions. In particular, the 6.5‐km SHiELD excels in predicting considerably finer‐scale convective systems associated with large‐scale frontal systems and extratropical cyclones. The predictions of global temperature, wind, cloud, and precipitation are significantly improved in this global model. Regionally, over the contiguous United States and the Maritime Continent, substantial reductions in prediction biases of precipitation, cloud cover, and wind fields are also found. In the mesoscale realm, the model demonstrates prominent improvements in global TC intensity and continental convective precipitation prediction: biases are relieved, and skill is higher. These findings affirm the superiority of the 6.5‐km SHiELD compared to the current 13‐km SHiELD, which will advance weather prediction by successfully addressing both synoptic weather systems and specific storm‐scale phenomena in the same global model.

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Related Dataset #1 : Complete ERA5 global atmospheric reanalysis

Related Dataset #2 : NCEP/EMC 4KM Gridded Data (GRIB) Stage IV Data. Version 1.0

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Author ZHOU, L.
Harris, L.
Chen, J.
Gao, K.
Cheng, K.
Tong, M.
Kaltenbaugh, A.
Morin, Matthew
Mouallem, J.
Chilutti, L.
Johnston, L.
Publisher UCAR/NCAR - Library
Publication Date 2024-12-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2025-07-10T19:56:38.968930
Metadata Record Identifier edu.ucar.opensky::articles:42629
Metadata Language eng; USA
Suggested Citation ZHOU, L., Harris, L., Chen, J., Gao, K., Cheng, K., Tong, M., Kaltenbaugh, A., Morin, Matthew, Mouallem, J., Chilutti, L., Johnston, L.. (2024). Bridging the gap between global weather prediction and global storm‐resolving simulation: Introducing the GFDL 6.5‐km SHiELD. UCAR/NCAR - Library. https://n2t.net/ark:/85065/d76q22kf. Accessed 09 August 2025.

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