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Article Type:
Research Article

The Impact of Tropical SST Biases on the S2S Precipitation Forecast Skill over the Contiguous United States in the UFS Global Coupled Model

Hedanqiu Bai aDepartment of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, Virginia

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https://orcid.org/0000-0002-3310-2770
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Bin Li bIMSG at NOAA/NCEP/EMC, College Park, Maryland

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Avichal Mehra cNOAA/NCEP/EMC, College Park, Maryland

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Jessica Meixner cNOAA/NCEP/EMC, College Park, Maryland

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Shrinivas Moorthi cNOAA/NCEP/EMC, College Park, Maryland

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Sulagna Ray dSRG at NOAA/NCEP/EMC, College Park, Maryland

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Lydia Stefanova bIMSG at NOAA/NCEP/EMC, College Park, Maryland

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Jiande Wang bIMSG at NOAA/NCEP/EMC, College Park, Maryland

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Jun Wang cNOAA/NCEP/EMC, College Park, Maryland

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Denise Worthen bIMSG at NOAA/NCEP/EMC, College Park, Maryland

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Fanglin Yang cNOAA/NCEP/EMC, College Park, Maryland

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Cristiana Stan aDepartment of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, Virginia

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Online Publication:
14 Jun 2023
Print Publication:
01 Jun 2023
DOI:
https://doi.org/10.1175/WAF-D-22-0162.1
Page(s):
937–952
Companion to this article
Restricted access

Abstract

This work investigates the impact of tropical sea surface temperature (SST) biases on the Subseasonal to Seasonal Prediction project (S2S) precipitation forecast skill over the contiguous United States (CONUS) in the Unified Forecast System (UFS) coupled model Prototype 6. Boreal summer (June–September) and winter (December–March) for 2011–18 were analyzed. The impact of tropical west Pacific (WP) and tropical North Atlantic (TNA) warm SST biases is evaluated using multivariate linear regression analysis. A warm SST bias over the WP influences the CONUS precipitation remotely through a Rossby wave train in both seasons. During boreal winter, a warm SST bias over the TNA partly affects the magnitude of the North Atlantic subtropical high (NASH)’s center, which in the reforecasts is weaker than in reanalysis. The weaker NASH favors an enhanced moisture transport from the Gulf of Mexico, leading to increased precipitation over the Southeast United States. Compared to reanalysis, during boreal summer, the NASH’s center is also weaker and in addition, its position is displaced to the northeast. The displacement further affects the CONUS summer precipitation. The SST biases over the two tropical regions and their impacts become stronger as the forecast lead increases from week 1 to 4. These tropical biases explain up to 10% of the CONUS precipitation biases on the S2S time scale.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Hedanqiu Bai, hbai2@gmu.edu

Abstract

This work investigates the impact of tropical sea surface temperature (SST) biases on the Subseasonal to Seasonal Prediction project (S2S) precipitation forecast skill over the contiguous United States (CONUS) in the Unified Forecast System (UFS) coupled model Prototype 6. Boreal summer (June–September) and winter (December–March) for 2011–18 were analyzed. The impact of tropical west Pacific (WP) and tropical North Atlantic (TNA) warm SST biases is evaluated using multivariate linear regression analysis. A warm SST bias over the WP influences the CONUS precipitation remotely through a Rossby wave train in both seasons. During boreal winter, a warm SST bias over the TNA partly affects the magnitude of the North Atlantic subtropical high (NASH)’s center, which in the reforecasts is weaker than in reanalysis. The weaker NASH favors an enhanced moisture transport from the Gulf of Mexico, leading to increased precipitation over the Southeast United States. Compared to reanalysis, during boreal summer, the NASH’s center is also weaker and in addition, its position is displaced to the northeast. The displacement further affects the CONUS summer precipitation. The SST biases over the two tropical regions and their impacts become stronger as the forecast lead increases from week 1 to 4. These tropical biases explain up to 10% of the CONUS precipitation biases on the S2S time scale.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Hedanqiu Bai, hbai2@gmu.edu
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