Seminars

Seminars / Informal seminars / Lectures by ECMWF Staff and Invited Lecturers

Seminars contribute to our ongoing educational programme and are tailored to the interests of the ECMWF scientific community.

Informal seminars are held throughout the year on a range of topics. Seminars vary in their duration, depending on the area covered, and are given by subject specialists. As with the annual seminar, this may be an ECMWF staff member or an invited lecturer.

The following is a listing of seminars/lectures that have been given this year on topics of interest to the ECMWF scientific community.  See also our past informal seminars

2019

12 March at 11:15

Room: CC  

Running serverless HPC workloads on top of Kubernetes and Jupyter notebooks

Speaker: Christopher Woods (University of Bristol)

21 January
at 11:00

Room: LT

ESSPE: Ensemble-based Simultaneous State and Parameter Estimation for Earth System Data-Model Integration and Uncertainty Quantification

Speaker: Fuqing Zhang (Pennsylvania State University)

Abstract

Building on advanced data assimilation techniques, we advocate to develop and apply a generalized data assimilation software framework on Ensemble-based Simultaneous State and Parameter Estimation (ESSPE) that will facilitate data-model integration and uncertainty quantification for the broad earth and environmental science communities. This include, but not limited to, atmospheric composition and chemistry, land surface, hydrology, and  biogeochemistry, for which many of the physical and chemical processes in their respective dynamic system models rely heavily on parametrizations. Through augmenting uncertain model parameters as part of the state vector, the ESSPE framework will allow for simultaneous state and parameter estimation through assimilating in-situ measurements such as those from the critical-zone ground-based observational  networks and/or remotely sensed observations such as those from radars and satellites. Beyond data model integration and uncertainty quantification, through systematically designed ensemble sensitivity analysis, examples will be given to the application of the ESSPE framework to: (1) identify key physical processes and their significance/impacts and to better represent and parameterize these processes in dynamical models of various earth systems; (2) design better observation strategies in locating the optimum sensitive regions, periods and variables to be measured, and the minimum accuracies and frequencies of these measurements that are required to quantify the physical processes of interest; explore the impacts of heterogeneity and equifinality; (3) understand predictability and nonlinearity of these processes, and parameter identifiability; and (4) facilitate upscale cascading of knowledge from smaller-scale process understanding to larger-scale simplified representation and parametrization. I will end the presentation with an introduction on the preliminary findings from our ongoing collaborations with ECMWF on using the data assimilation methodology to identify potential deficiencies in the convective gravity drag parametrization that led to  stratospheric temperature biases in the operational model, and the potential pathways for using SSPE to improve model physics in the future.

25 January
at 10:30

Room: LT

Windstorm and Cyclone Events: Atmospheric Drivers, Long-term Variability and Skill of current Seasonal Forecasts 

Speaker: Daniel J Befort (University of Oxford)

Abstract

In this study, observed long-term variability of wind storm events is analysed using two state-of-the-art 20th century reanalyses called ERA-20C and NOAA-20CR. Long-term trends partly differ drastically between both datasets. These differences are largest for the early 20th century, with a higher agreement for the past 30 years. However, short-term variability on sub-decadal time-scales is in much better agreement especially over parts of the northern hemisphere. This suggests that these datasets are useful to analyse drivers of interannual variability of windstorm events  as these simulations allow to extend the time-period covered by common reanalyses as e.g. ERA-Interim. 

ERA-20C is used to analyse the relationship between atmospheric and oceanic conditions on windstorm frequency over the European continent. It is found that large parts of their interannual variability can be explained by few atmospheric patterns, including the North Atlantic Oscillation (NAO) and the Scandinavian pattern. This suggests that it is crucial to capture these atmospheric modes of variability e.g. in seasonal forecast systems to reasonably represent windstorm variability over Europe. 

The skill in windstorms and cyclones is analysed for three modern seasonal forecast systems: ECMWF-S3, ECMWF-S4 and GloSea5. Whereas skill for cyclones is generally small, significant positive skill of ECMWF-S4 and GloSea5 is found for windstorms over the eastern North Atlantic/western Europe. Further to analysing skill in windstorms using a dedicated tracking algorithm, it is also tested in how far the NAO can be used as a predictor for their variability. Results suggest that using the NAO adds some skill over northern Europe, however, using the whole model information by tracking windstorm events is superior over large parts over the eastern Atlantic and western Europe. 

7 January
at 10:30

Room: LT

When fossil fuel emissions are no longer perfect in atmospheric inversion systems

Speaker: Thomas Lauvaux (LSCE, Saclay, France)

Abstract

The biogenic component of greenhouse gas fluxes remains the primary source of uncertainties in global and regional inversion systems. But recent results suggest that anthropogenic greenhouse gas emissions from fossil fuel use, so far assumed perfect at all scales, represent a larger fraction of the uncertainties in these systems, and can no longer be ignored. Inversion systems capable of reducing fossil fuel uncertainties are discussed in parallel with planned observing systems deployed across the world and in space. The remaining challenges and recent advances are presented to not only infer fossil fuel emissions but to provide support to climate policy makers at national and local scales.

 

Uncertainty quantification of pollutant source retrieval: comparison of Bayesian methods with application to the Chernobyl and Fukushima Daiichi accidental releases of radionuclides

Speaker: M Bocquet (CEREA, France)

Abstract

Inverse modeling of the emissions of atmospheric species and pollutants has significantly progressed over the past fifteen years.  However, in spite of seemingly reliable estimates, the retrievals are rarely accompanied with an objective estimate of their uncertainty, except when Gaussian statistics are assumed for the errors which is often unrealistic.  I will describe rigorous techniques meant to compute this uncertainty in the context of the inverse modeling of the time emission rates -- the so-called source term -- of a point-wise atmospheric tracer.  Lognormal statistics are used for the positive source term prior and possibly the observation errors, which precludes simple Gaussian statistics-based solutions.

Firstly, through the so-called empirical Bayesian approach, parameters of the error statistics -- the hyperparameters -- are estimated by maximizing the observation likelihood via an expectation-maximization algorithm. This enables the estimation of an objective source term.  Then, the uncertainties attached to the total mass estimate and the source rates are estimated using four Monte Carlo techniques: (i) an importance sampling based on a Laplace proposal, (ii) a naive randomize-then-optimize (RTO) sampling approach, (iii) an unbiased RTO sampling approach, (iv) a basic Markov chain Monte Carlo (MCMC) simulation. Secondly, these methods are compared to a full Bayesian hierarchical approach, using an MCMC based on a transdimensional representation of the source term to reduce the computational cost.

I will apply those methods, and improvements thereof, to the estimation of the atmospheric cesium-137 source terms from the Chernobyl nuclear power plant accident in April/May 1986 and Fukushima Daiichi nuclear power plant accident in March 2011.

LT = Lecture Theatre, LCR = Large Committee Room, MZR = Mezzanine Committee Room,
CC = Council Chamber