EGU22-10340, updated on 09 Jan 2024
EGU General Assembly 2022
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

On the seasonal prediction and predictability of winter temperature swings over North America

Xiaosong Yang1, Tom delworth1, Liwei Jia1,2, Nathaniel Johnson1, Feiyu Lu1,3, and Colleen MacHugh1
Xiaosong Yang et al.
  • 1GFDL, Princeton, NJ, United States of America (
  • 2UCAR, Boulder, CO, United States of America
  • 3Princeton University, Princeton, NJ, United States of America

A novel temperature swing index (TSI) is formed to measure the extreme surface temperature variations associated with the winter extratropical storms. The seasonal prediction skill of the winter TSI over North America was assessed versus ERA5 data using GFDL’s new SPEAR seasonal prediction system. The location with the skillful TSI prediction shows distinctive geographic pattern from that with skillful seasonal mean temperature prediction, thus the skillful prediction of TSI provides additive predictable climate information beyond the traditional seasonal mean temperature prediction. The source of the seasonal TSI prediction can be attributed to year-to-year variations of ENSO, North Pacific Oscillation and NAO. These results point towards providing skillful prediction of higher-order statistical information related to winter temperature extremes, thus enriching the seasonal forecast products for the research community and decision makers beyond the seasonal mean.

How to cite: Yang, X., delworth, T., Jia, L., Johnson, N., Lu, F., and MacHugh, C.: On the seasonal prediction and predictability of winter temperature swings over North America, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10340,, 2022.

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