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| 9.15 | Introductions | | Expand |
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| title | Introduction. Operational and research activities at ECMWF now/in the future | Vertical discretisation |
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| The goal of this session is to provide an overview of the use of generalised curvilinear coordinates in atmospheric numerical models. In this lecture we will give you a brief history of ECMWF and present the main areas of NWP research that is currently being carried out in the centre. We then look at current research challenges and present some of the latest developments that will soon become operational.By the end of the lecture session you should be able to: - List the main research areas at ECMWF and describe the latest model developments.
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Erland Källén, Sarah Keeley | Expand |
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| title | Assimilation Algorithms: (2) 3D-Var |
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Mike Fisher | Expand |
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| title | Assimilation Algorithms: (3) 4D-Var |
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Mike Fisher | Expand |
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| title | Data Assimilation Diagnostics: Forecast Sensitivity |
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Carla Cardinali - Lecture will be given by Andras Horanyi | View file |
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| name | FSOI_Lecture_AHCC.pptx |
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| height | 250 |
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| Expand |
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| title | Parameterization and Data Assimilation |
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| This one-hour lecture will identify the challenges associated with the use of physical parametrizations in the context of four-dimensional variational data assimilation (4D-Var). The importance of the linearity constraint in 4D-Var and the methods to address it will be detailed. The set of linearized physical parametrizations used at ECMWF will be briefly presented. Examples of the use of physical parametrizations in variational data assimilation and its impact on forecast quality will be given. By the end of the lecture, the students should be able: - to tell why physical parametrizations are needed in data assimilation.
- to recognize the importance of the regularization of the linearized code
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Philippe Lopez | View file |
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| name | TC_DA_lopez_2016_main.ppt |
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| height | 250 |
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| 10.35 | | Expand |
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| title | Assimilation Algorithms (1): Basic Concepts |
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TC_lecture_1.pdf Mike Fisher | Expand |
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| title | Land Data Assimilation - Soil moisture |
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| The aim of these sessions is to understand the role of land surface data assimilation on medium range weather forecasts. We will give an overview of the different approaches used to assimilate land surface data and to initialise model variables in NWP. We will present the current observing systems and describe the land data assimilation structure within ECMWF system. By the end of the session you should be able to: - identify the different observations used for snow and soil moisture data assimilation
- define land surface data assimilation approaches used for NWP
- describe the role of land surface data assimilation on medium-range weather forecasts
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Patricia de Rosnay | View file |
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| name | Land_data_assimilation_2016_part2.pptx |
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| height | 250 |
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| Expand |
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| title | Ensemble of Data Assimilations and uncertainty estimation |
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| The Ensemble of Data Assimilations (EDA) technique is used for the estimation of the analysis and background errors of the ECMWF assimilation system. This lecture describes the EDA formulation and implementation, and how it interacts with ECMWF 4DVar analysis and ECMWF Ensemble Prediction System. By the end of the lecture the participants should be able to: - Describe the theoretical basis and practical implementation of the EDA
- Explain the use of the EDA in the ECMWF analysis and ensemble prediction systems
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Massimo Bonavita
| PDF |
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| name | Bonavita_EDA_TC2016.pdf |
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| Expand |
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| title | Analysis of Satellite Data |
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| The primary purpose of this lecture is explore the implications of the fact that satellites can only measure radiation at the top of the atmosphere and do not measure the geophysical variables we require for NWP (e.g. temperature, humidity and wind). The link between the atmospheric variables and the measured radiances is the radiative transfer equation - the key elements of which are discussed. It is shown how - with careful frequency selection - satellite measurements can be made for which the relationship to geophysical variables is greatly simplified. Despite these simplifications, it is shown that the extraction of detailed profile information from downward looking radiance measurements is a formally ill posed inverse problem. Data assimilation is introduced as the solution to this inverse problem, where background information and satellite observations are combined to produce a best or optimal estimate of the atmospheric state. The main elements of the assimilation scheme (such as the chain of observation operators for radiances) and its key statistical inputs are examined. In particular it is shown that incorrect specification of observation errors (R) and background errors (B) can severely limit the successful exploitation of satellite data. By the end of this lecture you will: - understand exactly what a satellite actually measures (radiance)
- appreciate the complex relationship between what is measured and what we wish to know for NWP
- how information is extracted from satellite measurements in data assimilation
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describe some important aspects of the formulation and implementation of the governing equations in generalised coordinates describe various vertical coordinates employed in atmospheric models indicate the use of generalised coordinates to employ moving mesh adaptivity
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Christian Kühnlein | | Expand |
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| title | Hydrostatic/Non-hydrostatic dynamics, resolved/permitted convection and interfacing to physical parameterizations |
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| During this presentation, we will discuss two of the questions faced by numerical weather prediction scientists as forecast models reach horizontal resolutions of 6 to 2 km: Do we need to abandon the primitive equations for a non-hydrostatic system of equations? Do we still need a deep convection parametrisation? and we will show what answers to these questions are given by very high resolution simulations of the IFS.
By the end of the presentation, you should be able to: discuss the limits of the hydrostatic approximation for numerical weather prediction explain the dilemma of parametrizing deep convection versus permitting explicit deep convection at resolution in the grey zone of convection
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Sylvie Malardel | | Expand |
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| title | Semi-implicit integrations of nonhydrostatic PDEs of atmospheric dynamics |
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| The aim of this lecture is to systematically build theoretical foundations for Numerical Weather Prediction at nonhydrostatic resolutions. In the first part of the lecture, we will discuss a suite of all-scale nonhydrostatic PDEs, including the anelastic, the pseudo-incompressible and the fully compressible Euler equations of atmospheric dynamics. First we will introduce the three sets of nonhydrostatic governing equations written in a physically intuitive Cartesian vector form, in abstraction from the model geometry and the coordinate frame adopted. Then, we will combine the three sets into a single set recast in a form of the conservation laws consistent with the problem geometry and the unified solution procedure. In the second part of the lecture, we will build and document the common numerical algorithm for integrating the generalised set of the governing PDEs put forward in the first part of the lecture. Then, we will compare soundproof and compressible solutions and demonstrate the efficacy of this unified numerical framework for two idealised flow problems relevant to weather and climate. By the end of the lecture you should be able to: explain the form, properties and role of alternative systems of nonhydrostatic PDEs for all scale atmospheric dynamics; explain the importance and key aspects of continuous mappings employed in all-scale atmospheric models; explain the difference between the explicit and semi-implicit algorithms for integrating nonhydrostatic PDEs, the importance of consistent numerical approximations, and the fundamental role of transport and elliptic solvers.
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Piotr Smolarkiewicz Course2016_smolar.pdf
| | Expand |
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| title | Discontinuous higher order discretization methods |
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| The aim of this session is to learn about recent developments in discontinuous higher order spatial discretization methods, such as the Discontinuous Galerkin method (DG), and the Spectral Difference method (SD). These methods are of interest because they can be used on unstructured meshes and facilitate optimal parallel efficiency. We will present an overview of higher order grid point methods for discretizing partial differential equations (PDE's) with compact stencil support, and illustrate a practical implementation. By the end of the session you should be able to: ell what are the advantages offered by discontinuous higher order methods describe how to solve PDE's with discontinuous methods identify the key elements that contribute to a PDE solver
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Willem Deconinck | | 10.35 | | Expand |
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| title | Numerics + Discretization in NWP today |
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| Using the 30-year history of ECMWF's Integrated Forecasting System (IFS) as an example, thelecture is an introduction to the development and current state-of-the-art of global numerical weather prediction (NWP), as well as to the challenges faced in the future. It is intended to provide an overview and context for the topics covered in more detail during the course.
By the end of the session you should be able to: - describe the development of global NWP, the current-state-of-the-art, and future challenges
- identify relevant areas of research in numerical methods for Earth-System Modelling
- put into context every subsequent lecture and its purpose
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Nils Wedi Lecture_1_wedi.pptx | | Expand |
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| title | Mesh adaptivity using continuous mappings |
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| The goal of this session is to provide an overview of the use of generalised curvilinear coordinates in atmospheric numerical models. By the end of the session you should be able to: describe some important aspects of the formulation and implementation of the governing equations in generalised coordinates describe various vertical coordinates employed in atmospheric models indicate the use of generalised coordinates to employ moving mesh adaptivity
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Christian Kühnlein
kuehnlein_EC_TC2016_W.pdf | Practical Session Willem Deconinck, Christian Kühnlein
| | Expand |
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| title | Semi-implicit integrations of nonhydrostatic PDEs of atmospheric dynamics |
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| The aim of this lecture is to systematically build theoretical foundations for Numerical Weather Prediction at nonhydrostatic resolutions. In the first part of the lecture, we will discuss a suite of all-scale nonhydrostatic PDEs, including the anelastic, the pseudo-incompressible and the fully compressible Euler equations of atmospheric dynamics. First we will introduce the three sets of nonhydrostatic governing equations written in a physically intuitive Cartesian vector form, in abstraction from the model geometry and the coordinate frame adopted. Then, we will combine the three sets into a single set recast in a form of the conservation laws consistent with the problem geometry and the unified solution procedure. In the second part of the lecture, we will build and document the common numerical algorithm for integrating the generalised set of the governing PDEs put forward in the first part of the lecture. Then, we will compare soundproof and compressible solutions and demonstrate the efficacy of this unified numerical framework for two idealised flow problems relevant to weather and climate. By the end of the lecture you should be able to: explain the form, properties and role of alternative systems of nonhydrostatic PDEs for all scale atmospheric dynamics; explain the importance and key aspects of continuous mappings employed in all-scale atmospheric models; explain the difference between the explicit and semi-implicit algorithms for integrating nonhydrostatic PDEs, the importance of consistent numerical approximations, and the fundamental role of transport and elliptic solvers.
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Piotr Smolarkiewicz | | Expand |
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| title | Discontinuous higher order discretization methods |
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| The aim of this session is to learn about recent developments in discontinuous higher order spatial discretization methods, such as the Discontinuous Galerkin method (DG), and the Spectral Difference method (SD). These methods are of interest because they can be used on unstructured meshes and facilitate optimal parallel efficiency. We will present an overview of higher order grid point methods for discretizing partial differential equations (PDE's) with compact stencil support, and illustrate a practical implementation. By the end of the session you should be able to: ell what are the advantages offered by discontinuous higher order methods describe how to solve PDE's with discontinuous methods identify the key elements that contribute to a PDE solver
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Willem Deconinck | | 11.45 |
| Expand |
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| title | The spectral transform method |
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| The success of the spectral transform method in global NWP in comparison to alternative methods has been overwhelming, with many operational forecast centres (including ECMWF) having madethe spectral transform their method of choice. The lecture will introduce the basic elements of the spectral transform, explain why it has been successful and describe recent developments such as the fast Legendre transform |
| Tony McNally | View file |
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| name | DA_TC_satellite.ppt |
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| height | 250 |
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| Expand |
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| title | Ocean Data Assimilation |
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| This lecture provides an overview of a typical ocean data assimilation system for initialization and re-analyses application. The lecture uses as an example the ECMWF ocean data assimilation system, which is based the NEMOVAR (3Dvar FGAT). This will be used to discuss design of the assimilation cycle, formulation of error covariances, observations assimilated and evaluation procedure, among others. By the end of the lecture students should be able to: - describe the different components involved in a an ocean data assimilation system
- list the commonalities and and differences between ocean and atmosphere data assimilation
- describe the basics of the physical ocean observing system
- explain the essential multivariate relationships between ocean variables
- identify the limitations of the existing systems.
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Magdalena Alonso-Balmaseda | View file |
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| name | tcourse16_da_ocean.pptx |
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| height | 250 |
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11.45 | | Expand |
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| title | The Global Observing System |
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| | The aim of this session is to present an overview of the current observing systems used in Numerical Weather Prediction. We will discuss our observational requirement, and how close the current observing system is to meeting our needs. We will also discuss areas where our requirements are evolving. We will learn about WMO's OSCAR database that describes the Global Observing System. We will learn how the large diversity of observations now available, are monitored to ensure only good observations are presented to an operational system .
By the end of the session you should be able to: - be able to describe the main types of observations used in data assimilation for Numerical Weather Prediction;
- be aware of how large volumes of observations are exchanged, implemented and monitored in operational systems;
- be aware of WMO's OSCAR database, how to access it and what type of information it can provide.
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Steve English
| View file |
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| name | GlobalObservingSystem.pptx |
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| height | 250 |
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| Expand |
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| title | Background error modeling and non-Gaussian aspects of data assimilation |
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| The background error is central to the performance of the analysis system and tells how much confidence to put in the best available forecast which is to be updated with new observations. The lecture will review how background errors are estimated and represented for current variational algorithms. |
Elias Holm | View file |
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| name | BGErr_lecture_2016.ppt |
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| height | 250 |
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| | Expand |
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| title | Ensemble Kalman filters |
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| | The aim of this lecture is to introduce the concept of the EnKF in the context of atmospheric data assimilation. Strengths and weaknesses of the algorithm will be discussed and results of the ECMWF implementation will be presented. By the end of the lecture the participants should be able to: • Describe the basic EnKF algorithm and its connections with the Kalman Filter; • Discuss some of the advantages and the limitations of EnKF algorithms with respect to more established variational algorithms; • Be aware of recent developments in hybrid variational-EnKF data assimilation |
Massimo Bonavita | PDF |
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| name | Bonavita_ENKF_TC2016.pdf |
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| | Expand |
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| In this lecture, the impact of model error on variational data assimilation will be presented. This lecture will introduce weak-constraint 4D-Var as a way to account for model error in the data assimilation process. Several examples of results from simplified implementations in the IFS will be shown. By the end of the lecture the participants should be able to: - describe the impact of model error on the data assimilation process,
- explain the difficulties in properly accounting for model error in data assimilation.
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Yannick Tremolet - Lecture will be given by Mike Fisher
| Expand |
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| title | Data Assimilation of Atmospheric Composition |
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| At ECMWF atmospheric composition data are assimilated into the IFS as part of the MACC-II project. On a global scale, atmospheric composition represents the full state of the global atmosphere covering phenomena such as desert dust plumes, long-range transport of atmospheric pollutants or ash plumes from volcanic eruptions, but also variations and long-term changes in the background concentrations of greenhouse gases. The aim of this lecture is to give an overview of the work that is carried out at ECMWF regarding the assimilation of atmospheric composition data, and to address why this is of interest and which special challenges are faced when assimilating atmospheric composition data. By the end of the session you should: - have some understanding of the work carried out at ECMWF to assimilate data of atmospheric composition
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- explain what the spectral transform method is, how it is applied, and describe the latest developments at ECMWF.
- give reasons why it is successful for global NWP and climate.
- identify potential disadvantages of the method.
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Nils Wedi Lecture_2_wedi.pptx
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| title | Towards an Earth-System Model |
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| Recently, there is in increasing interest in trying to understand the properties of coupled atmosphere, ocean-wave, ocean/sea-ice models with an ultimate goal to start predicting weather, waves and ocean circulation on time scales ranging from the medium-range to seasonal timescale. Such a coupled system not only requires the development of an efficient coupled forecasting system but also the development of a data assimilation component. During the two lectures I will briefly describe the components of the coupled system. It will be made plausible that ocean waves are an essential element of such a coupled system as through the wave action, momentum and heat are transferred from atmosphere to ocean. Also, the sea state determines to a considerable extent the efficiency with which momentum is transferred from atmosphere to waves, while ocean waves also play a decisive role in the evolution of the sea-ice edge. Results showing the importance of ocean waves on upper-ocean mixing and on atmospheric circulation are discussed as well, while I will finish the lectures by presenting preliminary results from coupled data assimilation experiments. By the end of this session, the student will be able to: - discuss the impact of ocean waves on the coupled system
- describe the different wave processes that are modelled in the ECMWF system
- describe the impact of ocean circulation on the atmosphere
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Jean Bidlot Advance_numerical_method_for_earth_modelling_Jean_Bidlot.pptx | Practical Session Willem Deconinck, Christian Kühnlein | | Expand |
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| title | Massively parallel computing for NWP and climate |
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| The aim of this session is to understand the main issues and challenges in parallel computing, and how parallel computers are programmed today. By the end of this session you should be able to explain the difference between shared and distributed memory describe the key architectural features of a supercomputer describe the purpose of OpenMP and MPI on today’s supercomputers identify the reasons for the use of accelerator technology
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George Mozdzynski
Massively_Parallel_Computing.pdf | Course wrap up and Certificates | | 14.00 | | Expand |
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| title | The semi-Lagrangian, semi-implicit technique of the ECMWF model |
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| The aim of this session is to describe the numerical technique used in the ECMWF model for integrating the transport equations of the hydrostatic primitive equation set. We will present an overview of the semi-Lagrangian method and how it is combined with semi-implicit time-stepping to provide a stable and accurate formulation for the ECMWF Integrated Forecasting System (IFS).
By the end of this session you should be able to: - describe the fundamental concepts of semi-Lagrangian advection schemes, their strengths and weaknesses
- describe semi-implicit time-stepping and its use in IFS
- explain the important role these two techniques play for the efficiency of the current IFS system
- explain the impact that future super-computing architectures may have in the applicability of the semi-Lagrangian technique in high resolution non-hydrostatic global NWP systems.
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Michail Diamantakis
SLSI.pptx | | Expand |
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| title | Towards an Earth-System Model |
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| Recently, there is in increasing interest in trying to understand the properties of coupled atmosphere, ocean-wave, ocean/sea-ice models with an ultimate goal to start predicting weather, waves and ocean circulation on time scales ranging from the medium-range to seasonal timescale. Such a coupled system not only requires the development of an efficient coupled forecasting system but also the development of a data assimilation component. During the two lectures I will briefly describe the components of the coupled system. It will be made plausible that ocean waves are an essential element of such a coupled system as through the wave action, momentum and heat are transferred from atmosphere to ocean. Also, the sea state determines to a considerable extent the efficiency with which momentum is transferred from atmosphere to waves, while ocean waves also play a decisive role in the evolution of the sea-ice edge. Results showing the importance of ocean waves on upper-ocean mixing and on atmospheric circulation are discussed as well, while I will finish the lectures by presenting preliminary results from coupled data assimilation experiments. By the end of this session, the student will be able to: - discuss the impact of ocean waves on the coupled system
- describe the different wave processes that are modelled in the ECMWF system
- describe the impact of ocean circulation on the atmosphere
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Jean Bidlot | | Expand |
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| title | Introduction to element based computing, finite volume and finite element methods |
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| The aim of two lectures is to introduce basis of finite volume and continuous finite element discretisations and relate them to corresponding data structures and mesh generation techniques. The main focus will be on unstructured meshes and their application to global and local atmospheric models. Flexibility, communication overheads, memory requirements and user friendliness of such meshes with be contrasted with those of structured meshes. The most commonly used mesh generation techniques will be highlighted, together with mesh manipulation techniques employed in mesh adaption approaches and will be followed by a discussion of alternative geometrical representations of orography. An example of unstructured meshes’ implementation to non-hydrostatic and hydrostatic atmospheric solvers will provide an illustration of their potential and challenges. By the end of the lecture you should be able to: understand applicability, advantages and disadvantages of selected mesh generation techniques for a given type of application. appreciate importance of data structures in relation to atmospheric models and mesh generation. gain awareness of issues related to flexible mesh generation and adaption.
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Joanna Szmelter 2016.ppt2016.ppt
| | Expand |
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| title | Massively parallel computing for NWP and climate |
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| The aim of this session is to understand the main issues and challenges in parallel computing, and how parallel computers are programmed today. By the end of this session you should be able to explain the difference between shared and distributed memory describe the key architectural features of a supercomputer describe the purpose of OpenMP and MPI on today’s supercomputers identify the reasons for the use of accelerator technology
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George Mozdzynski |
| | 15.30 | | Expand |
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| title | Alternative time-stepping schemes for atmospheric modelling |
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| The aim of this session is to describe alternative (to the semi-Lagrangian) numerical techniques for integrating the transport equation sets encountered in NWP models. We will present an overview of different Eulerian time-stepping techniques and discuss the advantages and disadvantages of each approach |
| Antje Inness | View file |
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| name | EnvMoni_2016.pptx |
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| height | 250 |
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14.00 | | Expand |
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| title | Aspects of using observations in data assimilation |
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Lars Isaksen | View file |
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| name | LI_DA_TC_2016_Observations1.pptx |
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| height | 250 |
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| Expand |
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| In this lecture the variational bias correction scheme (VarBC) as used at ECMWF is explained. VarBC replaced the tedious job of estimating observation bias off-line for each satellite instrument or in-situ network by an automatic self-adaptive system. This is achieved by making the bias estimation an integral part of the ECMWF variational data assimilation system, where now both the initial model state and observation bias estimates are updated simultaneously. By the end of the session you should be able to realize that: - many observations are biased, and that the characteristics of bias varies widely between types of instruments
- separation between model bias and observation bias is often difficult
- the success of an adaptive system implicitly relies on a redundancy in the underlying observing system.
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Dick Dee | View file |
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| name | Dee_2016_TC_BiasCorrection.pptx |
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| height | 250 |
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Toy Model Practice Session (1) Mike Fisher, Yannick Tremolet, Martin Leutbecher OR | Expand |
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| title | Tangent Linear and Adjoints |
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| The goal of this lecture is to familiarise the student with the notion of tangent linear and adjoint models, and their use in variational data assimilation. A general overview of the current use of tangent linear and adjoint models in the ECMWF system will also be provided. Theoretical definitions and practical examples of tangent liner and adjoint models will be given. The student will be invited to work some simple tangent linear and adjoint derivations together with the instructor. A brief introduction to automatic differentiation software will also be given./ By the end of the session you should be able to: - define what tangent linear and adjoint models are
- derive tangent linear and adjoint equations for a simple nonlinear equation
- describe the use of tangent linear and adjoint codes within the ECMWF's 4D-VAR system.
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Angela Benedetti | Toy Model Practice Session (1) Mike Fisher, Yannick Tremolet, Martin Leutbecher OR | Expand |
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| title | Tangent Linear and Adjoints |
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| The goal of this lecture is to familiarise the student with the notion of tangent linear and adjoint models, and their use in variational data assimilation. A general overview of the current use of tangent linear and adjoint models in the ECMWF system will also be provided. Theoretical definitions and practical examples of tangent liner and adjoint models will be given. The student will be invited to work some simple tangent linear and adjoint derivations together with the instructor. A brief introduction to automatic differentiation software will also be given./ By the end of the session you should be able to: - define what tangent linear and adjoint models are
- derive tangent linear and adjoint equations for a simple nonlinear equation
- describe the use of tangent linear and adjoint codes within the ECMWF's 4D-VAR system.
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Angela Benedetti | View file |
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| name | Training_course_2016_TLAD.pptx |
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| height | 250 |
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| Expand |
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| | The aim of this session is to understand how data assimilation can improve our knowledge of past weather over long time-scales. We will present recent advances that help capture changes over time in observing system networks, and project this variation in information content into uncertainty estimates of the reanalysis products. We will also discuss the applications of reanalysis, which generally put weather events into the climate context .
By the end of the session you should be able to: - explain what are the goals of data assimilation in a reanalysis data assimilation system
- list the key aspects that require particular attention in reanalysis, as compared to numerical weather prediction
- describe the most common problems in reanalysis products
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Patrick Laloyaux | PDF |
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| name | Laloyaux_Reanalysis_2016.pdf |
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| 15.30 | - recognize the basic differences between semi-Lagrangian and Eulerian approaches
- describe differences, strengths-weaknesses of different time-stepping approaches such as split-explicit time-stepping, Runge-Kutta time-stepping
- describe the basic features of different time-stepping schemes used in other weather forecasting models such as WRF, ICON
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Michail Diamantakis
tstepping.pptx | | Expand |
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| title | Hydrostatic/Non-hydrostatic dynamics, resolved/permitted convection and interfacing to physical parameterizations |
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| During this presentation, we will discuss two of the questions faced by numerical weather prediction scientists as forecast models reach horizontal resolutions of 6 to 2 km: Do we need to abandon the primitive equations for a non-hydrostatic system of equations? Do we still need a deep convection parametrisation? and we will show what answers to these questions are given by very high resolution simulations of the IFS
| | Expand |
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| title | Land Data Analysis System - screen level parameters and snow |
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| The aim of these sessions is to understand the role of land surface data assimilation on medium range weather forecasts. We will give an overview of the different approaches used to assimilate land surface data and to initialise model variables in NWP. We will present the current observing systems and describe the land data assimilation structure within ECMWF systemBy the end of the session presentation, you should be able to: - identify the different observations used for snow and soil moisture data assimilation
- define land surface data assimilation approaches used for NWP
- describe the role of land surface data assimilation on medium-range weather forecasts
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Patricia de Rosnay | View file |
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| name | Land_data_assimilation_2016_part1.pptx |
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| height | 250 |
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Followed by drinks reception and poster session
| Expand |
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| title | Quality Control of observations |
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| A single observation can under some conditions undermine the quality of a global analyses. The lecture will go through methods used to make the analysis more robust against oulier or wrong observations, with focus on variational quality control. |
Elias Holm | View file |
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| name | VarQC_lecture.pptx |
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| height | 250 |
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Toy Model Practice Session (2) Mike Fisher, Yannick Tremolet, Martin Leutbecher OR Tangent linear and adjoint practical session Angela Benedetti Toy Model Practice Session (2) Mike Fisher, Yannick Tremolet, Martin Leutbecher OR Tangent linear and adjoint practical session Angela Benedetti | View file |
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| name | Training_course_2016_AD_handson.pptx |
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| height | 250 |
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| Question/answer session
Elias Holm, Lars Isaksen, Tony McNally, Mike Fisher Course evaluation 16:-16:30 Sarah Keeley
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