Abstract
Stratospheric ozone recovery and increasing greenhouse gases are anticipated to have a large impact on the Southern Hemisphere extratropical circulation, shifting the jet stream and associated storm tracks. Models participating in phase 5 of the Coupled Model Intercomparison Project poorly simulate the austral jet, with a mean equatorward bias and 10° latitude spread in their historical climatologies, and project a wide range of future trends in response to anthropogenic forcing in the representative concentration pathway (RCP) scenarios. Here, the question is addressed whether the unweighted multimodel mean (uMMM) austral jet projection of the RCP4.5 scenario can be improved by applying a process-oriented multiple diagnostic ensemble regression (MDER). MDER links future projections of the jet position to processes relevant to its simulation under present-day conditions.MDERis first targeted to constrain near-term (2015-34) projections of the austral jet position and selects the historical jet position as the most important of 20 diagnostics. The method essentially recognizes the equatorward bias in the past jet position and provides a bias correction of about 1.5° latitude southward to future projections.When the target horizon is extended to midcentury (2040- 59), the method also recognizes that lower-stratospheric temperature trends over Antarctica, a proxy for the intensity of ozone depletion, provide additional information that can be used to reduce uncertainty in the ensemble mean projection. MDER does not substantially alter the uMMM long-term position in jet position but reduces the uncertainty in the ensemble mean projection. This result suggests that accurate observational constraints on upper-tropospheric and lower-stratospheric temperature trends are needed to constrain projections of the austral jet position.
Original language | English (US) |
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Pages (from-to) | 673-687 |
Number of pages | 15 |
Journal | Journal of Climate |
Volume | 29 |
Issue number | 2 |
DOIs | |
State | Published - 2016 |
Keywords
- Bayesian methods
- Circulation/Dynamics
- Climate variability
- Dynamics
- Mathematical and statistical techniques
- Optimization
- Regression analysis
- Variability
- Wind stress
ASJC Scopus subject areas
- Atmospheric Science