- Created by Sarah Keeley, last modified by Lars Isaksen on Mar 02, 2018
| Time | Monday | Tuesday | Wednesday | Thursday | Friday |
|---|---|---|---|---|---|
| 9.15 | Introductions | The aim of this set of lectures 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 lectures you should be able to:
Piotr Smolarkiewicz see first lecture for handout | 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:
Michail Diamantakis
| 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:
Willem Deconinck | 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
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| 10.45 | 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:
Nils Wedi Animation 1 (Plumb-McEwan laboratory experiment): Animation 2 (DNS simulation of laboratory experiment):
Animation 3 (equatorial stratosphere):
| The aim of this set of lectures 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 lectures you should be able to:
Piotr Smolarkiewicz see first lecture for handout | Practical Session Willem Deconinck, Christian Kühnlein |
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 you should be able to:
Sarah Keeley and Erland Källén | The aim of this session is to understand how numerical precision can be traded against computational performance in Earth System modelling. It will be discussed how a reduction in numerical precision will influence model quality and how the minimal level of precision that will still allow simulations at high accuracy can be identified. We will give an overview about existing hardware options to adjust numerical precision to the need of the application. By the end of this session you should be able to
Peter Düben |
| 11.55 | The aim of this set of lectures 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 lectures you should be able to:
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Practical Session (elliptic solvers) Andreas Müller, Willem Deconinck, Christian Kühnlein | Practical Session Willem Deconinck, Christian Kühnlein | 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:
See first lecture for handout
| Course wrap up and Certificates |
| 14.00 | 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. By the end of the session you should be able to:
Nils Wedi Lecture_2_wedi.pptx | The aim of this session is to describe Eulerian based numerical techniques for integrating the equation sets encountered in NWP models. We will present an overview of different time-stepping techniques and discuss the advantages and disadvantages of each approach. By the end of the session you should be able to:
Michail Diamantakis | 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:
By the end of the presentation, you should be able to:
| 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:
Joanna Szmelter | |
| 15.30 | 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:
| 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:
Christian Kühnlein See first lecture for handout | 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:
By the end of the presentation, you should be able to:
Sylvie Malardel | 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:
Joanna Szmelter See first lecture for handout |
| Time | Monday | Tuesday | Wednesday | Thursday | Friday |
|---|---|---|---|---|---|
| 9.15 | Introduction to the course Erland Källén / Students
| This session describes the representation of subgrid-scale variability of humidity, cloud and precipitation and how this can be parametrized in atmospheric models. By the end of the session you should be able to: • recognise the reasons for representing the subgrid variability of humidity and cloud in an atmospheric model • explain how the key quantity of cloud fraction is related to subgrid heterogeneity assumptions • describe the different types of subgrid cloud parametrization schemes. Richard Forbes | This session will have two main components:
By the end of the session, the students should be able:
Souhail Boussetta | By the end of the session, the students should be able:
Gianpaolo Balsamo | This three-hour lecture will start by explaining the role and main ingredients of data assimilation in general. The widely used framework of variational data assimilation will then be gradually introduced. The challenges associated with the necessary inclusion of physical parametrizations in the data assimilation process will be highlighted. The concept of adjoint model as well as the techniques to derive it will be introduced. 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 then be briefly presented. Finally, various examples of the use of physical parametrizations in variational data assimilation and its impact on weather forecast quality will be given. By the end of the session, the students should be able: • to name the main ingredients of a data assimilation system. • to tell why physical parametrizations are needed in data assimilation. • to identify the role of the adjoint code in 4D-Var. • to recognize the importance of the regularization of the linearized code. Philippe Lopez see first lecture for handouts |
| 10.45 | This module aims to introduce the fundamentals of radiative transfer theory and its role within the global atmospheric circulation. The lectures will also cover the techniques of numerical modelling of the radiative transfer equations in global-circulation models with a particular focus on the code in use in the ECMWF Integrated Forecasting System. By the end of the session students should be able to: • Identify the key processes controlling the atmospheric radiative balance • Recognize the role of the radiative transfer in the Earth energy balance • Estimate the impact of changes in the radiative parameterizations on climate Additional outcomes: • Develop skills in data analysis and numerical modelling Robin Hogan
| Convection affects all atmospheric scales. Therefore, the convection session aims to provide a deeper understanding of the atmospheric general circulation and its interaction with convective heating and vertical transports. The notions and techniques acquired during the course should be useful for developers of convective parametrizations, forecasters and for analysing ouput from high-resolution convection resolving models. By the end of the session you should become familiarised with • the interaction between the large-scale circulation and the convection including radiative-convective equilibrium and convectively-coupled large-scale waves • the notion of convective adjustment and the mass flux concept in particular • the basic concepts behind the ECMWF convection parametrization and some useful numerical tricks • forecasting convection including convective systems and the diurnal cycle • diagnose forecast errors related to convection. Peter Bechtold | This module aims to introduce the fundamentals of radiative transfer theory and its role within the global atmospheric circulation. The lectures will also cover the techniques of numerical modelling of the radiative transfer equations in global-circulation models with a particular focus on the code in use in the ECMWF Integrated Forecasting System. By the end of the session students should be able to: • Identify the key processes controlling the atmospheric radiative balance • Recognize the role of the radiative transfer in the Earth energy balance • Estimate the impact of changes in the radiative parameterizations on climate Additional outcomes: • Develop skills in data analysis and numerical modelling Alessio Bozzo | Convection affects all atmospheric scales. Therefore, the convection session aims to provide a deeper understanding of the atmospheric general circulation and its interaction with convective heating and vertical transports. The notions and techniques acquired during the course should be useful for developers of convective parametrizations, forecasters and for analysing ouput from high-resolution convection resolving models. By the end of the session you should become familiarised with • the interaction between the large-scale circulation and the convection including radiative-convective equilibrium and convectively-coupled large-scale waves • the notion of convective adjustment and the mass flux concept in particular • the basic concepts behind the ECMWF convection parametrization and some useful numerical tricks • forecasting convection including convective systems and the diurnal cycle • diagnose forecast errors related to convection. Peter Bechtold | This short lecture is an introduction to the questions of time splitting and process splitting in a numerical weather prediction model and to the problems resulting from the interaction of different numerical solvers inside the same model. After this introduction, you should • be fully aware that each parametrisation is only a small part of a much larger system, usually one term in the full system of equations which needs to be solved by the forecast model, • remember, when working on your own parametrisation(s), that parametrisations are also subject to the constraints imposed by numerical analysis and algorithmic, as is the solver in the dynamical core. Sylvie Malardel |
| 11.55 | This session gives a theoretical introduction of the planetary boundary layer, including its definition, classification, notions about turbulence within the boundary layer, differences between clear and cloudy boundary layers, and equations used to describe the mean state in a numerical model. Expected outcomes: • understand what is the boundary layer, its characteristics and why it is important to study it and represent it correctly in numerical models • understand the difference between the various boundary layer types Irina Sandu | This module aims to introduce the fundamentals of radiative transfer theory and its role within the global atmospheric circulation. The lectures will also cover the techniques of numerical modelling of the radiative transfer equations in global-circulation models with a particular focus on the code in use in the ECMWF Integrated Forecasting System. By the end of the session students should be able to: • Identify the key processes controlling the atmospheric radiative balance • Recognize the role of the radiative transfer in the Earth energy balance • Estimate the impact of changes in the radiative parameterizations on climate Additional outcomes: • Develop skills in data analysis and numerical modelling Robin Hogan | Convection affects all atmospheric scales. Therefore, the convection session aims to provide a deeper understanding of the atmospheric general circulation and its interaction with convective heating and vertical transports. The notions and techniques acquired during the course should be useful for developers of convective parametrizations, forecasters and for analysing ouput from high-resolution convection resolving models. By the end of the session you should become familiarised with • the interaction between the large-scale circulation and the convection including radiative-convective equilibrium and convectively-coupled large-scale waves • the notion of convective adjustment and the mass flux concept in particular • the basic concepts behind the ECMWF convection parametrization and some useful numerical tricks • forecasting convection including convective systems and the diurnal cycle • diagnose forecast errors related to convection. Peter Bechtold | Building on the previous two Cloud sessions, the practical implementation of a cloud parametrization is described, using the ECMWF global model as an example appropriate for global weather forecasting. By the end of the session you should be able to: • explain the key sources and sinks of cloud and precipitation required in a parametrization • describe the main components of the ECMWF stratiform cloud parametrization • recognise the limitations of approximating complex processes. Richard Forbes | This session will give an overview of techniques and data sources used for the verification of the boundary layer scheme. We will use examples from the IFS to explore how verification methods can help to identify systematic errors in the model's boundary layer parameterization, and guide future model development. By the end of this session you should be able to: • Identify data sources and products suitable for BL verification • Recognize the strengths and limitations of the verification strategies discussed • Choose a suitable verification method to investigate model errors in boundary layer height, transport and cloudiness. Maike Ahlgrimm |
| 14.00 | This session gives a brief overview of cloud parametrization issues and an understanding of the basic microphysics of liquid, ice and mixed phase cloud and precipitation processes. By the end of the session you should be able to: • recall the basic concepts for the design of a cloud parametrization • describe the key microphysical processes in the atmosphere • recognize the important microphysical processes that need to be parametrized in a global NWP model. Richard Forbes | This session focuses on representation of the surface layer, i.e. the layer between the surface and the first model level. More particularly, it explains how the surface fluxes are parametrized, and it gives insights on the representation of the surfaces roughness lengths which are one of the crucial aspects of the formulation of the surface fluxes. Expected outcomes: • be aware of the difficulties related to the representation of the surface layer in a numerical model • understand how the surface fluxes are parametrized Irina Sandu | This session explains the different approaches used in numerical models to parametrize the turbulent mixing taking place at the subgrid scale, above the surface layer. Various turbulence closures are presented before describing closure currently used in the ECMWF model. Expected outcomes: • understand what a turbulence closure is and what are the types of closures encountered in numerical models • have an overview of the parameterization of turbulent mixing in the ECMWF model Irina Sandu | This three-hour lecture will start by explaining the role and main ingredients of data assimilation in general. The widely used framework of variational data assimilation will then be gradually introduced. The challenges associated with the necessary inclusion of physical parametrizations in the data assimilation process will be highlighted. The concept of adjoint model as well as the techniques to derive it will be introduced. 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 then be briefly presented. Finally, various examples of the use of physical parametrizations in variational data assimilation and its impact on weather forecast quality will be given. By the end of the session, the students should be able: • to name the main ingredients of a data assimilation system. • to tell why physical parametrizations are needed in data assimilation. • to identify the role of the adjoint code in 4D-Var. • to recognize the importance of the regularization of the linearized code. Philippe Lopez TC_PA_lopez_2017_main.ppt | On the basis of simple gravity wave theory, the concepts of sub-grib turbulent form drag, flow blocking, and gravity wave excitation will be introduced. The ECMWF formulations will be described, and the impact will be discussed. By the end of the session students should be able to: • Describe the relevant physical mechanisms related to sub-grid orography that have impact on flow in the atmosphere. • Describe the impact of sub-grid orography.
Anton Beljaars |
| 15.30 | By the end of the session students should be able to:
Gianpaolo Balsamo | Introduction to the Single Column Model Filip Vana Introduction to Metview and SCM interface Iain Russell 2016-03-21-Metview-SCM-Overview.pptx Radiation exercises Alessio Bozzo and Robin Hogan
| Land Surface exercises Gianpaolo Balsamo and Souhail Boussetta | Boundary Layer & Cloud exercises Irina Sandu, Maike Ahlgrimm and Richard Forbes
| Moist Processes Exercises Richard Forbes and Peter Bechtold |
| 16.40 | Moist Processes Games Richard Forbes and Peter Bechtold | Radiation exercises Alessio Bozzo and Robin Hogan | Land Surface exercises Gianpaolo Balsamo and Souhail Boussetta | Boundary Layer & Cloud exercises Irina Sandu, Maike Ahlgrimm and Richard Forbes | Course wrap up and certificates |
| Time | Monday | Tuesday | Wednesday | Thursday | Friday |
|---|---|---|---|---|---|
| 9.15 | 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 you should be able to:
Erland Källén, Sarah Keeley | This lecture will present the 3D-Var assimilation algorithm. This algorithm is based in the formulation of a cost function to minimize. Minimization methods will be presented together with some information on how to improve their efficiency. By the end of the lecture the participants should be able to:
Sebastien Massart
| 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:
Patrick Laloyaux | 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:
Niels Bormann | 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:
Patricia de Rosnay |
| 10.45 | The goal of the ECMWF Earth System data assimilation is to provide an accurate and physically coherent description of the state of the atmosphere, ocean, sea ice and land surface as an initial point for our forecasts. This requires blending in a statistically optimal way information from a huge variety of observations and our prior knowledge about the physical laws of the Earth system, which is encapsulated in our models. In this lecture we will lay the general conceptual framework on how to achieve this from a Bayesian perspective. We will then highlight the approximations and hypotheses which are required to make the assimilation problem computationally tractable and which underlie the practical data assimilation algorithms which will be described in detail in this training course. By the end of lecture you should be able to:
Massimo Bonavita |
| 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
| 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:
Angela Benedetti | |
| 11.55 | This lecture will introduce how observations are an essential part of the data assimilation system. It will focus on in situ (also called conventional) observations, from surface stations, drifters, aircraft and radiosondes. They are important both for direct use in the data assimilation system and for diagnostics. Radiosonde and surface observations also help to control the biases in the assimilation system. However they are diverse and hey can be complex, so close attention to quality control, observation uncertainty and (in some cases) bias correction is needed to optimise their use. The lecture will also introduce the actively sensed satellite observations used for data assimilation at ECMWF: radio occultation data, scatterometer winds, and altimeter wind/significant wave height. By the end of the lecture the student should be able to:
Lars Isaksen LI_DA_TC_2017_Insitu_actively_sensed_Observations.pptx | 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 | 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:
Philippe Lopez
| 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:
Patrick Laloyaux
| Practical Session: Tangent Linear and Adjoints |
| 14.00 | 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:
| The aim of this lecture is to By the end of the lecture the participants should be able to:
Massimo Bonavita | Practical Session with OOPS Marcin Chrust Sebastien Massart Patrick Laloyaux
| 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:
Antje Inness
| At ECMWF we are striving to move towards an Earth System approach to our data assimilation techniques. We currently have models not only of the atmosphere, but of the ocean, the land surface, sea ice, waves, and atmospheric composition. These systems interact with each other in different ways and all need to be initialised through the incorporation of observational data.
The aim of this lecture is to recognise the benefits and challenges associated with data assimilation in coupled models.
By the end of the lecture the participants should be able to:
Phil Browne
|
| 15.30 | This lecture will explain the basic concepts of the assimilation algorithms. The terminology used in the next lectures will be introduced. Simple examples will conduce towards the formulation of the optimal minimum-variance analysis. The optimal interpolation method will finally be presented. By the end of the lecture the participants should be able to:
Sebastien Massart Followed by drinks reception and poster session | 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. Massimo Bonavita
| Practical Session with OOPS continued
| 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:
| Question/answer session
Course evaluation 16:-16:30 Sarah Keeley |
| Time | Monday | Tuesday | Wednesday | Thursday | Friday |
|---|---|---|---|---|---|
| 9:30 -10:45 | Meet the students | The infrared spectrum- measurement, modelling and information content Tony McNally | GPS Radio Occulation: Extended applications Sean Healy | Satellites for environmental monitoring and forecasting Antje Inness | Satellite information on the ocean surface (SCAT) Giovanna De Chiara GDeChiara_surface_obs_2017_1.1.pptx |
| 11:15...12:30 | Theoretical background (1) What do satellites measure ? Tony McNally | GPS Radio Occulation: Principles and NWP use Sean Healy | The detection and assimilation of clouds in infrared radiances Tony McNally | Background errors for satellite data assimilation Tony McNally | Systematic errors, monitoring and auto-alert systems Mohamed Dahoui |
| 14:00...15:15 | Theoretical background (2) Data assimilation algorithms, Key elements and inputs Tony McNally | The detection and assimilation of clouds and rain in microwave radiances Alan Geer | Observation errors for satellite data assimilation Peter Weston ObsErrors_2017.pptx | Current satellite observing network and its future evolution Stephen English | |
| 15:45...17:00 | The microwave spectrum, measurement, modelling and information content Alan Geer | A Practical guide to IR and MW radiative transfer – using the RTTOV model and GUI David Rundle (UK Met Office) | Wind information from satellites (Atmospheric Motion Vectors) Katie Lean | 1DVar theory, simulator + practical session on background and observation errors Tony McNally | Question and answer session, course evaluation |
Time: | Monday | Tuesday | Wednesday | Thursday | Friday |
|---|---|---|---|---|---|
| 9.15-10.15 | Introduction to the course with Computer Hall tour | The aim of this session is to introduce the ECMWF ensemble of data assimilation (EDA). The rationale and methodology of the EDA will be illustrated, and its use in to simulate initial uncertainties in the ECMWF ensemble prediction system (ENS) will be presented. By the end of the session you should be able to:
Simon Lang | Increasing observation volumes and model complexity, decreasing errors, and a growing desire for uncertainty information, all necessitate developments in our diagnostic tools. The aim of these lectures is to discuss some of these tools, the dynamical insight behind them, and the residual deficiencies that they are highlighting. By the end of the lectures you should be aware of:
| Increasing observation volumes and model complexity, decreasing errors, and a growing desire for uncertainty information, all necessitate developments in our diagnostic tools. The aim of these lectures is to discuss some of these tools, the dynamical insight behind them, and the residual deficiencies that they are highlighting. By the end of the lectures you should be aware of:
Mark Rodwell | |
| 10.45 | The aim of this session is to introduce the idea of chaos. We will discuss the implications this has for numerical weather prediction. By the end of the session you should be able to:
Antje Weisheimer | Abstract: The lectures introduce methods of ensemble verification. They cover the verification of discrete forecasts (e.g. dry/wet) and continuous scalar forecasts (e.g. temperature). Various scores such as the Brier score and the continuous ranked probability score are introduced. After the lectures you should be able to
Martin Leutbecher | Franco Molteni TCPR_Molteni_Vitart_2017_MJO.pdf
| The aim of this session is to provide a general overview of monthly forecasting at ECMWF. We will review the main sources of predictability for the sub-seasonal time scale, including the Madden Julian Oscillation, sudden stratospheric warmings (SSWs), land initial conditions and their simulation by the coupled IFS-NEMO system. The skill of the ECMWF operational monthly forecasts will also be discussed. By the end of the session you should be able to:
Magdalena Balmaseda | |
| 11.55 | The aim of this session is to introduce the main sources of uncertainty that lead to forecast errors. The weather prediction problem will be discussed, and stated it in terms of an appropriate probability density function (PDF). The concept of ensemble prediction based on a finite number of integration will be introduced, and the reason why it is to be the only feasible method to predict the PDF beyond the range of linear growth will be illustrated. By the end of the session you should be able to:
Antje Weisheimer | After this lecture, students will be able to:
Sarah-Jane Lock | The aim of this session is to understand the ECMWF clustering products. By the end of the session you should be able to:
Laura Ferranti | Land surface is a potential source of predictability of weather variability, such as warm or cold spells or precipitation. We will review the way land surface affects the atmospheric conditions, and the criteria that need to be fulfilled to contribute to predictability. A number of land-atmosphere coupling metrics are discussed, as well as a number of studies on the effect of realistic land surface initialization reported in literature. Bart van den Hurk | This lecture covers the essentials of building a numerical seasonal forecast system, as exemplified by the present prediction system at ECMWF.
By the end of this lecture, you should be able to:
Tim Stockdale
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| 2.00 | The aim of this session is to understand how we are able to provide forecasts at long time horizons given the chaotic nature of the atmosphere. After this session you should be able to:
Sarah Keeley
| This lecture gives an overview of ensemble and post-processing and calibration techniques. The presentation is made from the medium-range forecast perspective. The (relative) benefits of calibration and multi-model combination for medium-range forecasting are also discussed.
By the end of this lecture, you should be able to:
| 2.45pm Discussion Session in the Weather Room The latest medium, monthly and seasonal forecasts will be discussed in terms of out look and performance. This is a combined event with the weekly weather discussion that ECMWF staff attend.
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| 3.30 | In this session the generation of the perturbed initial condition of the ECMWF ensemble will be presented. We will discuss the ratio behind using singular vectors in the ensemble and how they are calculated. Then it will be explained how the singular vectors are combined with perturbations from the ensemble of data assimilations to construct the perturbations for the ensemble. By the end of the session you should be able to:
SImon Lang | Abstract: The lectures introduce methods of ensemble verification. They cover the verification of discrete forecasts (e.g. dry/wet) and continuous scalar forecasts (e.g. temperature). Various scores such as the Brier score and the continuous ranked probability score are introduced. After the lectures you should be able to
Martin Leutbecher | Practice Session:
You get the opportunity to experiment yourself with an ensemble prediction system for a chaotic low-dimensional dynamical system introduced by Edward Lorenz in 1995. Experiments permit to study the role of the initial condition perturbations and the representation of model uncertainties. Various metrics introduced in the ensemble verification lectures will be applied in this session.
After the practice session, you will be able to use the toy model as an educational tool.
Martin Leutbecher |
Practice Session:
Louise Arnal, Sarah Keeley and Sarah-Jane Lock |
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| 4.30-5.15 | Computer hall and Weather Room Tours
5.15 ice breaker | Lecture and Practice Session: Abstract: The lecture is a short introduction to operational hydrological ensemble prediction systems, with focus on flooding. The European Flood Awareness System (EFAS) is described. The lecture also contains a short interactive exercise in decision making under uncertainty using prbabilistic forecasts as an example. By the end of the session you should be able to:
Fredrik Wetterhall | Practical extension | Practical extension |