Sensitivities of Subseasonal Unified Forecast System Simulations to Changes in Parameterizations of Convection, Cloud Microphysics, and Planetary Boundary Layer

Benjamin W. Green aCooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
bNOAA/OAR/Global Systems Laboratory, Boulder, Colorado

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Eric Sinsky cI. M. System Group, Inc., College Park, Maryland
dNOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland

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Shan Sun bNOAA/OAR/Global Systems Laboratory, Boulder, Colorado

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Vijay Tallapragada dNOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland

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Georg A. Grell bNOAA/OAR/Global Systems Laboratory, Boulder, Colorado

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Abstract

NOAA has been developing a fully coupled Earth system model under the Unified Forecast System framework that will be responsible for global (ensemble) predictions at lead times of 0–35 days. The development has involved several prototype runs consisting of bimonthly initializations over a 7-yr period for a total of 168 cases. This study leverages these existing (baseline) prototypes to isolate the impact of substituting (one-at-a-time) parameterizations for convection, microphysics, and planetary boundary layer on 35-day forecasts. Through these physics sensitivity experiments, it is found that no particular configuration of the subseasonal-length coupled model is uniformly better or worse, based on several metrics including mean-state biases and skill scores for the Madden–Julian oscillation, precipitation, and 2-m temperature. Importantly, the spatial patterns of many “first-order” biases (e.g., impact of convection on precipitation) are remarkably similar between the end of the first week and weeks 3–4, indicating that some subseasonal biases may be mitigated through tuning at shorter time scales. This result, while shown for the first time in the context of subseasonal prediction with different physics schemes, is consistent with findings in climate models that some mean-state biases evident in multiyear averages can manifest in only a few days. An additional convective parameterization test using a different baseline shows that attempting to generalize results between or within modeling systems may be misguided. The limitations of generalizing results when testing physics schemes are most acute in modeling systems that undergo rapid, intense development from myriad contributors—as is the case in (quasi) operational environments.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Sinsky’s current affiliation: Lynker at NOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland.

Corresponding author: Benjamin W. Green, ben.green@noaa.gov

Abstract

NOAA has been developing a fully coupled Earth system model under the Unified Forecast System framework that will be responsible for global (ensemble) predictions at lead times of 0–35 days. The development has involved several prototype runs consisting of bimonthly initializations over a 7-yr period for a total of 168 cases. This study leverages these existing (baseline) prototypes to isolate the impact of substituting (one-at-a-time) parameterizations for convection, microphysics, and planetary boundary layer on 35-day forecasts. Through these physics sensitivity experiments, it is found that no particular configuration of the subseasonal-length coupled model is uniformly better or worse, based on several metrics including mean-state biases and skill scores for the Madden–Julian oscillation, precipitation, and 2-m temperature. Importantly, the spatial patterns of many “first-order” biases (e.g., impact of convection on precipitation) are remarkably similar between the end of the first week and weeks 3–4, indicating that some subseasonal biases may be mitigated through tuning at shorter time scales. This result, while shown for the first time in the context of subseasonal prediction with different physics schemes, is consistent with findings in climate models that some mean-state biases evident in multiyear averages can manifest in only a few days. An additional convective parameterization test using a different baseline shows that attempting to generalize results between or within modeling systems may be misguided. The limitations of generalizing results when testing physics schemes are most acute in modeling systems that undergo rapid, intense development from myriad contributors—as is the case in (quasi) operational environments.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Sinsky’s current affiliation: Lynker at NOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland.

Corresponding author: Benjamin W. Green, ben.green@noaa.gov
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