Toward Convective-Scale Prediction within the Next Generation Global Prediction System

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new variable-resolution global model with the ability to represent convective-scale features that serves as a prototype of the Next Generation Global Prediction System (NGGPS). The goal of this prediction system is to maintain the skill in large-scale features while simultaneously improving the prediction skill of convectively driven mesoscale phenomena. This paper demonstrates the new capability of this model in convective-scale prediction relative to the current operational Global Forecast System (GFS). This model uses the stretched-grid functionality of the Finite-Volume Cubed-Sphere Dynamical Core (FV3) to refine the global 13-km uniform-resolution model down to 4-km convection-permitting resolution over the contiguous United States (CONUS), and implements the GFDL single-moment 6-category cloud microphysics to improve the representation of moist processes. Statistics gathered from two years of simulations by the GFS and select configurations of the FV3-based model are carefully examined. The variable-resolution FV3-based model is shown to possess global forecast skill comparable with that of the operational GFS while quantitatively improving skill and better representing the diurnal cycle within the high-resolution area compared to the uniform mesh simulations. Forecasts of the occurrence of extreme precipitation rates over the southern Great Plains are also shown to improve with the variable-resolution model. Case studies are provided of a squall line and a hurricane to demonstrate the effectiveness of the variable-resolution model to simulate convective-scale phenomena.

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Related Dataset #1 : GCIP/EOP Surface: Precipitation NCEP/EMC 4KM Gridded Data (GRIB) Stage IV Data. Version 1.0

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Author Zhou, Linjiong
Lin, Shian-Jiann
Chen, Jan-Huey
Harris, Lucas M.
Chen, Xi
Rees, Shannon L.
Publisher UCAR/NCAR - Library
Publication Date 2019-07-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T19:08:47.538392
Metadata Record Identifier edu.ucar.opensky::articles:22701
Metadata Language eng; USA
Suggested Citation Zhou, Linjiong, Lin, Shian-Jiann, Chen, Jan-Huey, Harris, Lucas M., Chen, Xi, Rees, Shannon L.. (2019). Toward Convective-Scale Prediction within the Next Generation Global Prediction System. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d71j9dqr. Accessed 31 January 2025.

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