4.7 Article

Subseasonal Week 3-5 Surface Air Temperature Prediction During Boreal Wintertime in a GFDL Model

Journal

GEOPHYSICAL RESEARCH LETTERS
Volume 46, Issue 1, Pages 416-425

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2018GL081314

Keywords

subseasonal prediction; surface air temperature; ENSO; NAO; MJO; average predictability time

Funding

  1. NOAA Climate Program Office [NA15OAR4310177, NA17OAR4310261]

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With a Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the subseasonal prediction of wintertime (December-February) surface air temperature (SAT) is investigated through the analysis of 11-year hindcasts. Significant subseasonal week 3-5 correlation skill exists over a large portion of the global land domain, and the predictability originates primarily from the eight most predictable SAT modes. The first three modes, identified as the El Nino-Southern Oscillation mode, the North Atlantic Oscillation mode, and the Eurasia Meridional Dipole mode, can be skillfully predicted more than 5weeks in advance. The North Atlantic Oscillation and Eurasia Meridional Dipole modes are strongly correlated with the initial stratospheric polar vortex strength, highlighting the role of stratosphere in subseasonal prediction. Interestingly, the Madden-Julian Oscillation is not essential for the subseasonal land SAT prediction in the Northern Hemisphere extratropics. The spatial correlation skill exhibits considerable intraseasonal and interannual fluctuations, indicative of the importance to identify the time window of opportunity for subseasonal prediction. Plain Language Summary Subseasonal prediction has important societal and economic impacts, while it remains very challenging as a prediction frontier. In this study, we use a dynamic model with simple initialization method to investigate the subseasonal week 3-5 prediction of the surface air temperature (SAT) in boreal winter. It is encouraging to note that the model has a significant week 3-5 SAT prediction skill over a large portion of the land regions. Using a statistical method, we further examine the potential predictability sources and find eight most predictable modes with the first three identified as the El Nino/Southern Oscillation, the North Atlantic Oscillation, and the Eurasia Meridional Dipole Mode. Interestingly, although the Madden-Julian Oscillation is the dominant intraseasonal mode over the tropics, it has relatively weak impacts on the SAT prediction in the Northern Hemisphere extratropics. The strong fluctuation of the prediction skill varies from week to week and year to year highlighting the importance to identify the time window of opportunity for subseasonal prediction. The role of stratospheric polar vortex in subseasonal SAT prediction is also shown.

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