Accessibility navigation


Probabilistic causal network modelling of Southern Hemisphere jet sub-seasonal to seasonal predictability

Saggioro, E. ORCID: https://orcid.org/0000-0002-9543-6338, Shepherd, T. G. ORCID: https://orcid.org/0000-0002-6631-9968 and Knight, J. (2024) Probabilistic causal network modelling of Southern Hemisphere jet sub-seasonal to seasonal predictability. Journal of Climate, 37 (10). pp. 3055-3071. ISSN 1520-0442

[img]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

46MB
[img] Text - Accepted Version
· Restricted to Repository staff only

3MB
[img]
Preview
Text - Supplemental Material
· Please see our End User Agreement before downloading.

3MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1175/JCLI-D-23-0425.1

Abstract/Summary

Skilful prediction of the Southern Hemisphere (SH) eddy-driven jet is crucial for representation of mid-to-high latitude SH climate variability. In the austral spring-to-summer months, the jet and the stratospheric polar vortex variabilities are strongly coupled. Since the vortex is more predictable and influenced by long-lead drivers one month or more ahead, the stratosphere is considered a promising pathway for improving forecasts in the region on subseasonal to seasonal (S2S) timescales. However, a quantification of this predictability has been lacking, as most modelling studies address only one of the several interacting drivers at a time, while statistical analyses quantify association but not skill. This methodological gap is addressed through a knowledge-driven probabilistic causal network approach, quantified with seasonal ensemble hindcast data. The approach enables to quantify the jet’s long-range predictability arising from known late-winter drivers, namely El Ni˜no Southern Oscillation, Indian Ocean Dipole, upward wave activity flux and polar night jet oscillation, mediated by the vortex variability in spring. Network-based predictions confirm the vortex as determinant for skilful jet predictions, both for the jet’s poleward shift in late spring and its equatorward shift in early summer. ENSO, IOD, late-winter wave activity flux and polar night jet oscillation only provide moderate prediction skill to the vortex. This points to early spring sub-monthly variability as important for determining the vortex state leading up to its breakdown, creating a predictability bottle-neck for the jet. The method developed here offers a new avenue to quantify the predictability provided by multiple, interacting drivers on S2S timescales.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:115586
Publisher:American Meteorological Society

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation