Jet Stream Variability Across Timescales: Interannual Drivers, Future Projections, and Short-Term Cloud-Radiative Feedbacks in a Changing Climate

Author: ORCID icon orcid.org/0000-0002-6431-8136
Liu, Xinhuiyu, Environmental Sciences - Graduate School of Arts and Sciences, University of Virginia
Advisor:
Grise, Kevin, AS-Environmental Sciences (ENVS) Arts & Sciences Graduate, University of Virginia
Abstract:

Jet streams are important components of atmospheric circulations and play a fundamental role in shaping regional climate. Their variability spans multiple timescales, from daily and weekly fluctuations to interannual variability and long-term climate change responses. However, the mechanisms governing jet stream shift and strengthening are not well understood and there are still large uncertainty in their future projections simulated by the latest state-of-art global climate models (GCMs). Understanding the mechanisms governing jet stream shift and strengthening, as well as their interactions with tropical convection, extratropical dynamics, and cloud-radiative processes, is essential for improving climate predictions. This dissertation investigates jet stream variability across different timescales using a combination of reanalysis data, satellite observations, and evaluate how those relevant processes are represented in Coupled Model Intercomparison Project phase 6 (CMIP6) climate simulations. Our findings shed light on the dynamical processes underlying jet stream variability on different timescales and suggest potential pathways to improve the representations of the jet streams in a changing climate in GCMs.

The first study focuses on interannual variability of the Northern Hemisphere (NH) wintertime subtropical jet (STJ) and polar front jet (PFJ) at individual longitudes, extending previous studies on the zonal-mean jets. Using ERA-Interim reanalysis and CMIP6 models, this work examines how tropical outgoing longwave radiation (OLR) and midlatitude lower-tropospheric temperature gradients influence jet fluctuations. Teleconnections, particularly the El Niño–Southern Oscillation (ENSO), play a significant role in modulating STJ variability across different regions. While CMIP6 models capture these relationships, systematic biases in simulated tropical convection lead to errors in ENSO-induced jet shifts.

The second study investigates future projections of the STJ in relation to biases in the Indo-Pacific Warm Pool, a key region of tropical convection serving as a heat engine of the global climate. The size of the warm pool influences Rossby wave propagation and tropical-extratropical interactions, affecting the STJ’s response to climate change. By analyzing CMIP6 models, this study finds that models with a more realistic warm pool representation better capture future subtropical jet shifts and precipitation changes over Asia, the Atlantic, and the Americas. Emergent constraints are developed to reduce uncertainty in future projections, highlighting the importance of accurately simulating present-day tropical convection for robust climate predictions.

The third study examines short-term (daily to weekly) variability in the Southern Hemisphere (SH) midlatitude jet and its interactions with cloud-radiative processes. Using CloudSat/CALIPSO satellite data, reanalysis, and CMIP6 models, this research shows that poleward jet shifts displace storm-track clouds, leading to distinct atmospheric radiative heating and cooling patterns. These anomalies influence the persistence of the Southern Annular Mode (SAM), the dominant mode of variability in the SH extratropical atmosphere. Models with more realistic cloud responses exhibit reduced SAM persistence, suggesting that cloud-radiative feedbacks play a critical role in modulating midlatitude circulation variability.

Together, these studies provide a comprehensive view of jet stream variability across different temporal scales, from interannual variability to long-term climate projections and short-term feedbacks. The findings improve our understanding of jet dynamics and highlight key model biases that influence large-scale climate variability and climate predictions, with implications for improving future projections of atmospheric circulation and regional climate change.

Degree:
PHD (Doctor of Philosophy)
Keywords:
Jet streams, Climate variability, Cloud-radiative feedbacks, Tropical-extratropical interactions, El Niño–Southern Oscillation (ENSO), CMIP6, Climate change, Emergent constraints, CloudSat
Sponsoring Agency:
National Science Foundation (NSF)National Aeronautics and Space Administration (NASA)
Language:
English
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2025/04/24