Seasonal predictability of baroclinic wave activity

Gan Zhang, Hiroyuki Murakami, William F. Cooke, Zhuo Wang, Liwei Jia, Feiyu Lu, Xiaosong Yang, Thomas L. Delworth, Andrew T. Wittenberg, Matthew J. Harrison, Mitchell Bushuk, Colleen McHugh, Nathaniel C. Johnson, Sarah B. Kapnick, Kai Chih Tseng, Liping Zhang

Research output: Contribution to journalArticlepeer-review


Midlatitude baroclinic waves drive extratropical weather and climate variations, but their predictability beyond 2 weeks has been deemed low. Here we analyze a large ensemble of climate simulations forced by observed sea surface temperatures (SSTs) and demonstrate that seasonal variations of baroclinic wave activity (BWA) are potentially predictable. This potential seasonal predictability is denoted by robust BWA responses to SST forcings. To probe regional sources of the potential predictability, a regression analysis is applied to the SST-forced large ensemble simulations. By filtering out variability internal to the atmosphere and land, this analysis identifies both well-known and unfamiliar BWA responses to SST forcings across latitudes. Finally, we confirm the model-indicated predictability by showing that an operational seasonal prediction system can leverage some of the identified SST-BWA relationships to achieve skillful predictions of BWA. Our findings help to extend long-range predictions of the statistics of extratropical weather events and their impacts.

Original languageEnglish (US)
Article number50
Journalnpj Climate and Atmospheric Science
Issue number1
StatePublished - Dec 2021

ASJC Scopus subject areas

  • Global and Planetary Change
  • Environmental Chemistry
  • Atmospheric Science


Dive into the research topics of 'Seasonal predictability of baroclinic wave activity'. Together they form a unique fingerprint.

Cite this