Updates to NOAA’s Unified Forecast System’s Cumulus Convection Parameterization Scheme between GFSv16 and GFSv17

Abstract This study outlines the updates made to cumulus convection parameterizations between Global Forecast System, version 16 (GFSv16), and the forthcoming GFSv17 which will be the first global forecast application to become operational under the Unified Forecast System infrastructure. The updates, addressing known systematic errors and biases, incorporate innovations such as stochasticity, three-dimensional subgrid organizational effects, and a prognostic closure evolution. The changes are shown to improve tropical temperature/humidity biases, convective available potential energy (CAPE) forecasts, CONUS precipitation, and tropical variability. By examining individual updates’ impact on temperature, humidity profiles, and precipitation power spectra, we find that the new prognostic closure and stricter precipitation evaporation criteria alleviate a dry and cold bias in the tropical boundary layer and enhance precipitation variability in the tropics. Stricter triggering criteria also allow for more CAPE buildup, particularly over the tropics. The cumulus convection updates have a modest impact on precipitation skill scores over CONUS, but overall, there is an improvement when comparing GFSv16 and the latest GFSv17 prototype configurations, in particularly for larger thresholds. The study also highlights the challenges in developing convection parameterizations suitable for both coupled and uncoupled model configurations. Evaluation of the MJO shows varying responses to cumulus convection changes depending on whether the model is coupled with a dynamic ocean model.

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Publication Details

Journal
Weather and Forecasting
Published
2024-08-23
DOI
https://doi.org/10.1175/waf-d-23-0232.1
Citations
6
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
2.26
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article

Updates to NOAA’s Unified Forecast System’s Cumulus Convection Parameterization Scheme between GFSv16 and GFSv17

Lisa Bengtsson, Jongil Han
6 citations
Weather and Forecasting
Meteorological Phenomena and Simulations
2.26
article

Updates to NOAA’s Unified Forecast System’s Cumulus Convection Parameterization Scheme between GFSv16 and GFSv17

Lisa Bengtsson, Jongil Han
article en
6 citations

Abstract

Abstract This study outlines the updates made to cumulus convection parameterizations between Global Forecast System, version 16 (GFSv16), and the forthcoming GFSv17 which will be the first global forecast application to become operational under the Unified Forecast System infrastructure. The updates, addressing known systematic errors and biases, incorporate innovations such as stochasticity, three-dimensional subgrid organizational effects, and a prognostic closure evolution. The changes are shown to improve tropical temperature/humidity biases, convective available potential energy (CAPE) forecasts, CONUS precipitation, and tropical variability. By examining individual updates’ impact on temperature, humidity profiles, and precipitation power spectra, we find that the new prognostic closure and stricter precipitation evaporation criteria alleviate a dry and cold bias in the tropical boundary layer and enhance precipitation variability in the tropics. Stricter triggering criteria also allow for more CAPE buildup, particularly over the tropics. The cumulus convection updates have a modest impact on precipitation skill scores over CONUS, but overall, there is an improvement when comparing GFSv16 and the latest GFSv17 prototype configurations, in particularly for larger thresholds. The study also highlights the challenges in developing convection parameterizations suitable for both coupled and uncoupled model configurations. Evaluation of the MJO shows varying responses to cumulus convection changes depending on whether the model is coupled with a dynamic ocean model.

Weather and ForecastingVol. 39(11)
NOAA National Centers for Environmental Prediction (US), NOAA Physical Sciences Laboratory (US), NOAA Environmental Modeling Center
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Meteorological Phenomena and Simulations
2.26
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