SCENARIO NERC DTP - How can the stratosphere help us predict the weather several weeks ahead?

There is huge international interest in improving our ability to predict climate on the sub-seasonal timescale, from two to six weeks ahead of the present time (e.g. White et al., 2017, http://onlinelibrary.wiley.com/doi/10.1002/met.1654/epdf). This timescale has received less attention than both medium-range and seasonal-ahead forecasting and has the potential to provide forecasts that aid planning for a range of different consumers and sectors including energy, health and agriculture. For the wintertime Atlantic sector, the two pre-dominant sources of sub-seasonal predictability in the atmosphere are the Madden-Julian Oscillation and the variability of the stratospheric polar vortex. This project builds on recent work at Reading which highlights the differing sensitivity of tropospheric circulation regimes to stratospheric anomalies. Our recent work has developed a detailed statistical framework and a basic understanding of the regime dependent predictability available from the stratosphere. The proposed PhD project will capitalize on this work so that it can be used practically by forecasters and by operational centres to characterize and optimize their forecast systems.

The project will have three aims:
• Quantify the influence of stratosphere-troposphere coupling on sub-seasonal predictability in different North Atlantic weather regimes
• Develop theories for why stratosphere-troposphere coupling is stronger in the negative NAO regime than other tropospheric regimes
• Assess the impact of remote drivers of stratospheric winter climate including the QBO, MJO and ENSO on stratosphere-troposphere coupling

During the first year of the project, the student will examine sub-seasonal hindcasts of the stratosphere and extra-tropical troposphere from 10 different operational sub-seasonal prediction systems available through the sub-seasonal to seasonal prediction database (http://s2sprediction.net). The student will apply the statistical methodology developed in collaboration between ECMWF and the University of Reading to diagnose North Atlantic weather regimes and their connection to the stratosphere in each of the models. By applying these techniques across a large range of models they will be able to both quantify the impact of stratosphere-troposphere coupling on sub-seasonal predictability in each of the models and develop understanding of why some models appear to be able to represent this connection better than others.

In the second year of the project, the student will develop additional dynamical diagnostics to aid understanding of why particular tropospheric weather regimes are more sensitive to stratospheric perturbations than others. An initial investigation would focus on the role of Rossby wave breaking since this has recently been shown to be a useful way to characterize regime transitions in the North Atlantic (Swanson and Straus, 2017) and has been previously shown to play an important role in stratosphere-troposphere coupling (e.g. Ndarana and Waugh, 2011). There will be time and flexibility for the student to develop their own ideas, theories and diagnostics in this phase of the project.

In the third year of the project, the student will use the OpenIFS model to understand the influence of remote drivers such as the QBO and MJO on the character and persistence of stratosphere anomalies and the resulting influence on stratosphere-troposphere coupling. Inspired by the work of Hitchcock and Simpson (2014), the student will perform a large number of short simulations (30 day) in which the phase of the QBO or MJO is damped towards observed conditions so that the influence of particularly noteworthy events such as the 2016 disruption to the QBO can be examined in detail.

TRAINING:
The student will work closely with Dr Furtado and his group at the University of Oklahoma throughout the PhD, working on areas of shared interest in sub-seasonal predictability and stratosphere-troposphere coupling. To facilitate this exchange of ideas, the student will spend 1-2 months each summer based at the University of Oklahoma working on the project and interacting with researchers.

The main supervisor is the co-lead of the SPARC SNAP project and is helping to coordinate analysis of the S2S dataset as part of this initiative. There will be significant opportunities for the student to participate in this project and to contribute to co-authored papers during their PhD. This will be a significant additional benefit to the student, training them in interacting with a broad international community and co-working on shared problems early in their career.

To hear more about this project please follow the link: https://www.youtube.com/watch?v=ytdvIUI5nZg&list=PLZWYaq_mWwsEM5dH1abHjYIgU2EVaegT9&index=1

To read more about this project please follow the link: http://www.met.reading.ac.uk/nercdtp/home/available/desc/entry2018/SC201838.pdf