We are pleased to announce the last session of the webinar series “MPE Webinars: Analysis and Modelling” scheduled for Friday, 24th July.

3.00 pm CEST time

Darryl Holm (Imperial College London)
“Stochastic Upper Ocean Dynamics (STUOD)”

Abstract:
The STUOD ERC Synergy project aims to enhance our capabilities for dealing with the uncertainty in prediction of upper ocean transport of heat, salinity and acidity. The project is based on a data driven approach for parameterizing the small fast scales of GFD flows by using temporal homogenization of Lagrangian paths. This approach leads to stochastic transport, instead of stochastic forcing or diffusion. The approach is called SALT (Stochastic Advection by Lie Transport). It is consistent with Newton’s force law and Kelvin’s circulation theorem. It can also be derived via a stochastic variational principle. The physics packages inherit stochasticity from the stochastically advected material properties. The methodology calibrates the stochastic parameters using data analysis, quantifies the resulting uncertainty, and then reduces the uncertainty by using a further data assimilation step based on particle filtering. After sketching the development of the SALT approach we will state one of the first fundamental questions at the beginning of the STUOD project. Namely, how is fluid
circulation affected in rotating shallow water in the presence of strong horizontal buoyancy gradients produced by spatially heterogeneous heat absorption? This question raises issues of how buoyancy fronts affect geostrophic balance, which in turn affects interactions among waves, currents and bathymetry.

The recording of this lecture is avaiable here: MPE webinars – week 12: Darryl Holm – Stochastic Upper Ocean Dynamics (STUOD) – YouTube

4.00 pm CEST time
Valerio Lucarini (University of Reading & University of Hamburg)
“A new mathematical framework for atmospheric blockings”

Abstract:
We use a simple yet Earth-like atmospheric model to propose a new framework for understanding the mathematics of blocking events, which are associated with low frequency, large scale waves in the atmosphere. Analysing error growth rates along a very long model trajectory, we show that blockings are associated with conditions of anomalously high instability of the atmosphere. Additionally, the lifetime of a blocking is positively correlated with the intensity of such an anomaly, against intuition. In the case of Atlantic blockings, predictability is especially reduced at the onset and decay of the blocking, while a relative increase of predictability is found in the mature phase, while the opposite holds for Pacific blockings, for which predictability is lowest in the mature phase. We associate blockings to a specific class of unstable periodic orbits (UPOs), natural modes of variability that cover the attractor of the system. The UPOs differ substantially in terms of instability, which explains the diversity of the atmosphere in terms of predictability. The UPOs associated with blockings are indeed anomalously unstable, which leads to them being rarely visited. The onset of a blocking takes place when the trajectory of the system hops into the neighbourhood of one of these special UPOs. The decay takes place when the trajectory hops back to the neighbourhood of usual, less unstable UPOs associated with zonal flow. This justifies the classical Markov chains-based analysis of transitions between weather regimes. The existence of UPOs differing in the dimensionality of their unstable manifold indicates a very strong violation of hyperbolicity in the model, which leads to a lack of structural stability. We propose that this could be a generic feature of atmospheric models and might be a fundamental cause behind difficulties in representing blockings for the current climate and uncertainties in predicting how their statistics will change as a result of climate change.
Reference
Lucarini, V., Gritsun, A. A new mathematical framework for atmospheric blocking events. Clim Dyn 54, 575–598 (2020). https://doi.org/10.1007/s00382-019-05018-2

The Zoom link and password are:
Link: https://chalmers.zoom.us/j/62899878599
Meeting ID: 628 9987 8599
Password: 496589