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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.

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titleAdvanced Numerical Methods


Multiexcerpt
MultiExcerptNameNMtime


TimeMondayTuesdayWednesdayThursdayFriday
9.15

Introductions


Expand
titleAlgorithms for semi-implicit integrations of nonhydrostatic PDEs of atmospheric dynamics (1)

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:

  • 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.

Piotr Smolarkiewicz

see first lecture for handout



Expand
titleThe semi-Lagrangian, semi-implicit technique of the ECMWF model
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.

Michail Diamantakis

 


Expand
titleDiscontinuous higher order discretization methods

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

 

Willem Deconinck

 


Expand
titleMassively parallel computing for NWP and climate

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

Andreas Müller

 
35
45


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titleNumerics + Discretization in NWP today
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

Nils Wedi

Lecture_1_wedi.pptx

Animation 1 (Plumb-McEwan laboratory experiment):

View file
nameQBOoriginal_short.gif.mp4
height250

Animation 2 (DNS simulation of laboratory experiment):

Image Added


Animation 3 (equatorial stratosphere):

Image Added

 


Expand
titleAlgorithms for semi-implicit integrations of nonhydrostatic PDEs of atmospheric dynamics (2)

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:

  • 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.

Piotr Smolarkiewicz

see first lecture for handout

Practical Session

Willem Deconinck, Christian Kühnlein


 

Expand
title
Discontinuous higher order discretization methods
Operational and research activities at ECMWF now/in the future

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

By the end of the session Willem Deconinck

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

  • List the main research areas at ECMWF and describe the latest model developments.

Sarah Keeley and Erland Källén

ECMWF-Past-FutureNM_2017fin.pptx



Expand
titleReduced Precision Computing for Earth System Modelling

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

  • describe how rounding errors will impact model simulations that show chaotic dynamics

  • describe the connection between numerical precision, computational performance and predictability
  • recall how a trade off between precision and performance can be realised in Earth System modelling today and in the future

Peter Düben

 
45
55


Expand
titleIntroduction to semi-implicit integrations of nonhydrostatic PDEs of atmospheric dynamics

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:

  • 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.

Piotr Smolarkiewicz

 

 

Practical Session (elliptic solvers)

Andreas Müller, Willem Deconinck, Christian Kühnlein

Practical


Tuesday-Exercises-Handout.pdf

Practical Session

Willem Deconinck, Christian Kühnlein


Expand
title
Operational and research activities at ECMWF now/in the future

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.

Discontinuous higher order discretization methods

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

By the end of the lecture

you should be able to:

  • List the main research areas at ECMWF and describe the latest model developments.
  • 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

Willem Deconinck

See first lecture for handout


 

Sarah Keeley and Erland Källén

 

Course wrap up and Certificates
14.00


Expand
titleThe spectral transform method
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:
  •   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.

Nils Wedi

Lecture_2_wedi.pptx




Expand
titleEulerian time-stepping schemes for NWP and climate
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:
  • obtain a good understanding of the minimum theoretical properties required by time-stepping schemes
     
  • 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

Michail Diamantakis

 


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titleHydrostatic/Non-hydrostatic dynamics, resolved/permitted convection and interfacing to physical parameterizations

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

Sylvie Malardel
 


Expand
titleIntroduction to element based computing, finite volume and finite element methods

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.

Joanna Szmelter

JoannaSzmelter2017.ppt

 
15.30


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titleVertical discretisation

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

Christian Kühnlein
 


Expand
titleMesh adaptivity using continuous mappings

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

Christian Kühnlein

Christian Kühnlein

See first lecture for handout


Expand
titleHydrostatic/Non-hydrostatic dynamics, resolved/permitted convection and interfacing to physical parameterizations

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

Sylvie Malardel

 


Expand
titleMesh generation

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.

Joanna Szmelter

 

See first lecture for handout

 




 

 

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
Expand
titleData Assimilation
Parametrization of sub-grid scale processes


Multiexcerpt
MultiExcerptName
DAtime
PAtime


TimeMondayTuesdayWednesdayThursdayFriday
9.15

Introduction to the course

Erland Källén / Students

 


 


Expand
title
Introduction. Operational and research activities at ECMWF now/in the future
Clouds (2)

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

lecture

session you should be able to:

  • List the main research areas at ECMWF and describe the latest model developments.

Erland Källén, Sarah Keeley

Expand
titleAssimilation Algorithms: (2) 3D-Var

 

Mike

 

 

Expand
titleAssimilation Algorithms: (3) 4D-Var

 

Mike

Expand
titleData Assimilation Diagnostics: Forecast Sensitivity

 

Carla Cardinali - Lecture will be given by Andras Horanyi

Expand
titleParameterization and Data Assimilation
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

•    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

TC2017_Forbes_L2_cloud_coldphase.pptx


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titleLand Surface (2):

This session will have two main components:

  • An overview of the role of snow in the climate system from observations, models and forecasts; with a description of the current representation of snow in the ECMWF model.
  • An overview of the role of vegetation in NWP with a description of the evolution of vegetation representation in the ECMWF model, supported by some evaluation examples
physical parametrizations in variational data assimilation and its impact on forecast quality will be given
  • .

By the end of the

lecture

session, 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
  • Identify the main processes associated with snow and vegetation in NWP
  • Describe the main components related to snow and vegetation scheme in the ECMWF land surface model

Souhail Boussetta

TC2017_PA_Surf_partII.pptx

Philippe Lopez

10.35


Expand
title
Assimilation Algorithms
Land Surface (
1): Basic Concepts
3): Surface Energy, Water Cycle

 By the end of the session, the students should be able:

  • relate flux and storage
  • recognise land surface predictors and land diagnostic quantities

Gianpaolo Balsamo

new_surf2.pptx

 

 

 

Mike


Expand
title
Land Data Assimilation - Soil moisture

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

Patricia de Rosnay

Expand
titleEnsemble of Data Assimilations and uncertainty estimation

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

Massimo Bonavita

 

 

Expand
titleAnalysis of Satellite Data

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

Tony McNally

Expand
titleOcean Data Assimilation

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.

Magdalena Alonso-Balmaseda

11.45
Expand
titleThe Global Observing System

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.

Steve English

Expand
titleBackground error modeling and non-Gaussian aspects of data assimilation

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

Expand
titleEnsemble Kalman filters
 

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

 

 

Expand
titleModel error

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.
Yannick Tremolet - Lecture will be given by Mike Fisher

 

 

Expand
titleData Assimilation of Atmospheric Composition

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

Antje Inness

 

 

14.00
Expand
titleAspects of using observations in data assimilation

 

Lars Isaksen

Expand
titleBias Correction

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.

Dick Dee

Toy Model Practice Session (1) 

Mike Fisher, Yannick Tremolet, Martin Leutbecher

OR

 

Expand
titleTangent Linear and Adjoints

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.

Angela Benedetti

 

Toy Model Practice Session (1) 

Mike Fisher, Yannick Tremolet, Martin Leutbecher

OR

 

Expand
titleTangent Linear and Adjoints

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.

Angela Benedetti

 

 

Expand
titleReanalysis

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

Patrick Laloyaux

15.30
Expand
titleLand Data Analysis System - screen level parameters and snow

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

Patricia de Rosnay

Followed by drinks reception and poster session

Expand
titleQuality Control of observations

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

 

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

Question/answer session
Elias Holm, Lars Isaksen, Tony McNally, Mike Fisher

Course evaluation 16:-16:30

Sarah Keeley

Expand
titleSatellite Data Assimilation (EUMETSAT/ECMWF))
Multiexcerpt
MultiExcerptNameSATtime
TimeMondayTuesdayWednesdayThursdayFriday9:30 -10:45Meet the students
The infrared spectrum- measurement, modelling and
information content
Tony McNally
GPS Radio Occulation: Extended applications
Sean Healy
Observation errors for satellite
data assimilation
Niels Bormann
Satellites for environmental
monitoring and forecasting

Richard Engelen

NWP_SAF_Engelen.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

Dahoui_Satellite_2016.pptx

14:00...15:15
Theoretical background (2)
Data assimilation algorithms, Key elements and inputs
Tony McNally
Satellite information on the ocean surface (SCAT)
Giovanna De Chiara
The detection and assimilation of clouds and rain in microwave radiances
Alan Geer
Satellite information on the land surface
Patricia de Rosnay
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
James Hocking (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

 

 

Parametrization and Data Assimilation

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


Expand
titleRadiation (1)

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
hogan_ecmwf_radiation_lecture1.pptx

 


Expand
titleConvection (1)

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

CONVECTION_T1_2017.ppt


Expand
titleRadiation (3)

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

AB_TC_Radiation_Lecture3a.pptx


Expand
titleConvection (3)

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
CONVECTION_T3_2017.ppt


Expand
titleNumerics of Parameterization

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

PDC_2017.pdf

11.55


Expand
titleBoundary Layer (1)

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
pbl1_is_2017.ppt


Expand
titleRadiation (2)

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

hogan_ecmwf_radiation_lecture2.pptx


Expand
titleConvection (2)

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
CONVECTION_T2_2017.ppt


Expand
titleClouds (3)

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

TC2017_Forbes_L3_cloud_subgrid.pptx


Expand
titleModel Evaluation: Clouds and Boundary Layer

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

CldPblVeri2017.ppt

14.00


Expand
titleClouds (1)

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

TC2017_Forbes_L1_cloud_warmphase.pptx


Expand
titleBoundary Layer (2)

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

pbl2_is_2017.pptx


Expand
titleBoundary Layer (3)

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

pbl3_is_2017.ppt



Expand
titleParametrization and Data Assimilation

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
TC_PA_lopez_2017_ex.ppt



Expand
titleParameterization of Sub-grid Orography

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

subgrid_orography_2017.ppt

15.30


Expand
titleLand Surface (1): Introduction

By the end of the session students should be able to:

  • recognise land elements relevant to weather,
  • review land modelling strategies to heterogeneity

Gianpaolo Balsamo

new_surf1.pptx

Introduction to the Single Column Model

Filip Vana

SCM_intro.pdf

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




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
Expand
titleData Assimilation


Multiexcerpt
MultiExcerptNameDAtime


Time

Monday

TuesdayWednesdayThursdayFriday
9.15


Expand
titleIntroduction. Operational and research activities at ECMWF now/in the future

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:

  • List the main research areas at ECMWF and describe the latest model developments.

Erland Källén, Sarah Keeley


Expand
titleAssimilation Algorithms: (2) 3D-Var

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:

  • Recognize the 3D-Var cost function
  • Explain the various terms of the cost function
  • Question the efficiency of methods designed to find the mimimum of the cost function

Sebastien Massart

TC_lecture_2.pdf

 

 


Expand
titleReanalysis

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

Patrick Laloyaux
Laloyaux_Reanalysis_2017.pptx



Expand
titleBias Correction

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

Expand
titleParametrization of sub-grid scale processes
Multiexcerpt
MultiExcerptNamePAtime
MondayTuesdayWednesdayThursdayFriday
Expand
titleClouds (2)

.

By the end of the session you should be able to realize that:

•    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.

  • 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.

Niels Bormann
Bormann_2017_TC_BiasCorrection

Richard Forbes

TC2016_Forbes_L2_cloud_coldphase


Expand
titleLand
Surface (2):Snow
This session will have two mains components:
  • An overview of the role of snow in the climate system from observations, models and forecasts.
  • Data Assimilation

    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

    Description of the current representation of snow in the ECMWF model, evaluation examples and ongoing developments

    .

    By the end of the session

    , the students

    you should be able to:

    • Identify the main processes associated with snow in the climate system
    • Describe the main components of the snow scheme in the ECMWF model

    Emanuel Dutra

    pa_surf_2_cold_20160518.pptx

    Expand
    titleLand Surface (3): Surface Energy, Water Cycle

     By the end of the session, the students should be able:

    • relate flux and storage
    • recognise land surface predictors and land diagnostic quantities

    Gianpaolo Balsamo

    surf2.pptx

    Expand
    titleParametrization and Data Assimilation

    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_2016_main.ppt

    Expand
    titleRadiation (1)

    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

    hogan_ecmwf_radiation_lecture1.pptx

    Expand
    titleConvection (1)

    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

    CONVECTION_T1_2016.ppt

    Expand
    titleRadiation (3)

    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

    hogan_ecmwf_radiation_lecture2.pptx

    Expand
    titleConvection (3)

    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

    CONVECTION_T3_2016.ppt

    Expand
    titleNumerics of Parameterization

    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

    PDC_2016.pdf

    Expand
    titleBoundary Layer (1)

    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

    pbl1_is_2016.pdf

    Expand
    titleRadiation (2)

    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

    Bozzo_Radiation_Lecture3.pptx

    Expand
    titleConvection (2)

    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

    CONVECTION_T2_2016.ppt

    Expand
    titleClouds (3)
    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
    • 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

    Patricia de Rosnay

    deRosnay_TC_NWP_DA_2017.pdf

    10.45


    Expand
    titleOverview of Assimilation Methods

    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:

    • understand the basics of how a geophysical data assimilation system works;
    • understand the main approximations and hypotheses which are required to build practical data assimilation algorithms for large geophysical systems

    Massimo Bonavita


    DataAssim_Overview_Bonavita_2017_1.pptx


    Expand
    titleAssimilation Algorithms: (3) 4D-Var

     

    Sebastien Massart

    TC_lecture_3.pdf


    Expand
    titleData Assimilation Diagnostics: Forecast Sensitivity

     

     

    Cristina Lupu

    FSOI_DALecture_CLupu.pptx

     

     

     


     

     


    Expand
    titleQuality Control of observations

    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

    Holm_VarQC_lecture.pdf

     


    Expand
    titleTangent Linear and Adjoints

    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.

    Angela Benedetti

    Training_course_2017_TLAD.pptx

    11.55


    Expand
    titleConventional and actively sensed observations

    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:

    • understand how in situ and actively sensed observations are used in data assimilation, including bias aspects and observation uncertainty aspects.
    • appreciate the diverse and complex range of in situ observations used in modern NWP.

    • understand how radio occultation data, scatterometer winds and altimeter data are used in data assimilation.

    Lars Isaksen

    LI_DA_TC_2017_Insitu_actively_sensed_Observations.pptx



    Expand
    titleAssimilation Algorithms: (4) Ensemble Kalman filters

    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

    Bonavita_ENKF_TC2017.pptx






    Expand
    titleParameterization and Data Assimilation

    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

    Philippe Lopez

    TC_DA_lopez_2017_main.ppt

     


     

     


    Expand
    titleModel error

    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.

    Patrick Laloyaux

    Weak_Constraint.pptx

     

    Practical Session: Tangent Linear and Adjoints

    Training_course_2017_AD_handson.pptx

    14.00


    Expand
    titleAnalysis of Radiance Observations

    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


    Expand
    titleAssimilation Algorithms: (5) Hybrid Data Assimilation methods

    The aim of this lecture is to

    By the end of the lecture the participants should be able to:

     

    Massimo Bonavita

    Bonavita_EDA_HYBRID_DA_TC2017.pptx

    Practical Session with OOPS


    Marcin Chrust

    Sebastien Massart

    Patrick Laloyaux

     

     


    Expand
    titleData Assimilation of Atmospheric Composition

    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

    be able to

    :

    • have some understanding of the work carried out at ECMWF to assimilate data of atmospheric composition

    Antje Inness

    Inness_envi2017.ppt.pptx

     




    Expand
    titleCoupled Data Assimilation: opportunities and challenges

    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:

    • Recall the challenges associated with variational data assimilation in systems with different timescales and computer codes.
    • Describe the benefits of having more consitently balanced coupled systems from coupled data assimilation.
    • Explain the differences between weakly and strongly coupled data assimilation approaches.
    • Discuss the various methods that are in use at ECWMF and explain the planned developments of the systems.

     

    Phil Browne

    coupled_da_presentation.pdf

     


    15.30


    Expand
    titleAssimilation Algorithms (1): Basic Concepts

    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:

    • Recognize the notations used for the rest of the week
    • Solve the optimal minimum-variance analysis problem
    • Apply the optimal interpolation method

    Sebastien Massart
    TC_lecture_1.pdf

    Followed by drinks reception and poster session



    Expand
    titleBackground error modeling in data assimilation

    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

    BGErr_lecture_2017.ppt



     

    Practical Session with OOPS continued


     


    Expand
    titleOcean Data Assimilation

    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.

    Hao Zuo
    DA_course_2017_ocean_Zuo.pptx

    Question/answer session
    Elias Holm, Lars Isaksen, Tony McNally, Massimo Bonavita


    DataAssim_Final_Discussion_2017.pptx

    TC_OOPS_2017_summary.pptx

    Course evaluation 16:-16:30

    Sarah Keeley




    Expand
    titleSatellite Data Assimilation (EUMETSAT/ECMWF))


    Multiexcerpt
    MultiExcerptNameSATtime


    TimeMondayTuesdayWednesdayThursdayFriday
    9:30 -10:45Meet 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

    NWP_SAF_training_Course_April_2017_Inness.pptx

    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

    Dahoui_Satellite_2017.pptx

    14:00...15:15
    Theoretical background (2)
    Data assimilation algorithms, Key elements and inputs
    Tony McNally
    Satellite information on the land surface
    Patricia de Rosnay
    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

    •    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

    TC2016_Forbes_L3_cloud_subgrid.pptx

    Expand
    titleModel Evaluation: Clouds and Boundary Layer

    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

    CldPblVeri2016.ppt

    Expand
    titleClouds (1)

    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

    TC2016_Forbes_L1_cloud_warmphase.pptx

    Expand
    titleBoundary Layer (2)

    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

    pbl2_is_new.pdf

    Expand
    titleBoundary Layer (3)

    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

    pbl3_is_2016.pdf

    Expand
    titleParametrization and Data Assimilation

    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

    Expand
    titleParameterization of Sub-grid Orography

    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

    subgrid_orography_2016.ppt

    Expand
    titleLand Surface (1): Introduction

    By the end of the session students should be able to:

    • recognise land elements relevant to weather,
    • review land modelling strategies to heterogeneity

    Gianpaolo Balsamo

    surf1.pptx

    Introduction to the Single Column Model

    Filip Vana

    Lecture2016.pdf

    Radiation exercises

    Alessio Bozzo and Robin Hogan

     

     

    Land Surface exercises

    Gianpaolo Balsama and Emanuel Dutra

     

     

    Boundary Layer & Cloud exercises

    Irina Sandu, Maike Ahlgrimm and Richard Forbes

     

     

     

    Moist Processes Exercises

    Richard Forbes and Peter Bechtold

    Moist Processes Games

    Richard Forbes and Peter Bechtold

    Radiation exercises

    Alessio Bozzo and Robin Hogan

    Land Surface exercises

    Gianpaolo Balsama and Emanuel Dutra

    Boundary Layer & Cloud exercises

    Irina Sandu, Maike Ahlgrimm and Richard Forbes

    Course wrap up and certificates




    Expand
    titlePredictability and ocean-atmosphere ensembles


    Multiexcerpt
    MultiExcerptNamePRtime


    Time:

    MondayTuesdayWednesdayThursdayFriday
    9.15
    -10.15

    Introduction to the course

    with Computer Hall tour

    Expand
    titleInitial uncertainties in the medium-range ENS (2)

    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:

    • explain the idea behind using singular vectors in the ensemble

    • describe how singular vectors are calculated

    • describe the construction of the ensemble perturbations

    -10.15

    Introduction to the course

    with Computer Hall tour


    Expand
    titleInitial Uncertainties (2)
    ExpandtitleEnsemble data assimilation

    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:

    • know what is the ECMWF EDA

    • illustrate how the EDA is used to simulate initial uncertainty in ensemble prediction

    • understand the main differences between singular vectors and EDA-based perturbations

    Roberto Buizza

    Simon Lang

    RB
    2016_05_TCL2_SVs_EDA.pptx


    Expand
    title
    Ensemble verification
    Diagnostics (
    2)

    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

    • explain what a reliable probabilistic forecast is and how to measure reliability

    • understand why resolution and sharpness of a probabilistic forecast matter

    • compute several of the standard verification metrics used for ensemble forecasts

    1)
    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:
    •   Some of the key weakness of the ECMWF forecast system 
    •   Some of the diagnostic tools used to identify and understand these weaknesses

    Martin Leutbecher

     v2handout

    .pdf

     

     

     


    Expand
    title
    Coupled ocean-atmosphere variabilityThis lecture provides a broad overview of the role of the ocean on the predictability and prediction of weather and climate. It introduces some basic phenomena needed to to understand the time scales and nature of the ocean-atmosphere coupling.
    Diagnostics (2)
    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:
    •   Some of the key weakness of the ECMWF forecast system 
    •   Some of the diagnostic tools used to identify and understand these weaknesses

    Mark Rodwell

    20170511_TC_PR_Diags_2_03_static.pdf

     

    Magdalena Balmaseda

    tcourse16_ocean.pptx


    Expand
    titleInitializaton techniques in
    seasonal
    coupled forecasting
     

     

    Magdalena Balmaseda

    tcourse16
    pptx
    10.
    35-1135
    45


    Expand
    titleIntroduction to Chaos

     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:

    • describe what limits the predictability of the atmosphere
    • understand the need for probabilistic forecasting
    Sarah Keeley

    Antje Weisheimer

     
    pptxRB_2016_05_TCL3_TIGGE.pptx


    Expand
    title
    Approaches to ensemble prediction/TIGGE

    The aim of this session is to illustrate the key characteristic of the nine operational global, medium-range ensemble systems. These are the ensembles available also within the TIGGE (Thorpex Interactive Grand Global Ensemble) project data-base. Similarity and differences in the approaches followed to simulate the sources of forecast uncertainties will be discussed, and their relevance for forecast performance will be illustrated.

    By the end of the session you should be able to:

    • illustrate the main similarities and differences of the 9 TIGGE global ensembles

    • link the performance differences of TIGGE ensemble to their design

    • describe the main differences between singular vectors and EDA-based perturbations

     

    Roberto Buizza

    Ensemble verification (1)

    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

    • explain what a reliable probabilistic forecast is and how to measure reliability

    • understand why resolution and sharpness of a probabilistic forecast matter

    • compute several of the standard verification metrics used for ensemble forecasts

    Martin Leutbecher

    v1handout.pdf



    Expand
    titleWeather regimes

     

    Franco Molteni

    TCPR_Molteni_

    regimes.ppt 

     

     
    Expand
    titleCoupled ocean-atmosphere variability - MJO

    Frederic Vitart


    Franco Molteni

    TCPR_Molteni_Vitart_

    2016
    pptx

    pdf

     


    Expand
    titleThe monthly forecast system at ECMWF
    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: 
    •   List the different sources of predictability for extended-range forecasts 
    •   Describe the operational system used to produce the ECMWF monthly forecasts 
    •   Assess the skill of the monthly forecasting system
    Frederic Vitart

    Magdalena Balmaseda

     
    2016
    pptx
    11.
    45-12.45 
    55


    Expand
    titleSources of uncertainty
     

    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:

    • explain which are the main sources of forecast error

    • illustrate why numerical prediction should be stated

    in probabilistic terms
  • describe the rationale behind ensemble prediction

  • Roberto Buizza

    RB_2016_05_TCL1_sources_unc.pptx

    Expand
    titleEnsemble verification (1)

    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

    • explain what a reliable probabilistic forecast is and how to measure reliability

    • understand why resolution and sharpness of a probabilistic forecast matter

    • compute several of the standard verification metrics used for ensemble forecasts

    Martin Leutbecher

    v1handout.pdf

    • in probabilistic terms

    • describe the rationale behind ensemble prediction

    Antje Weisheimer

    sources_of_uncertainty_AW2017.pdf


    Expand
    titleUsing stochastic physics to represent model error
    • explain the physical and practical motivations for using stochastic physics in an ensemble forecast;

    • describe the two stochastic parameterization schemes used in the IFS ensemble, and their respective purposes;

    • be able to identify the improvement in forecasting skill from the inclusion of stochastic physics.

    Sarah-Jane Lock

    StochPhys2017_print.pdf



    Expand
    titleClustering techniques and their applications

    The aim of this session is to understand the ECMWF clustering products.

    By the end of the session you should be able to:

    • explain how the cluster analysis works
    • use the ECMWF clustering products

     

    Laura Ferranti

    TC_clustering_

    2016


    Expand
    title
    Diagnostics (2)
    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:
    •   Some of the key weakness of the ECMWF forecast system 
    •   Some of the diagnostic tools used to identify and understand these weaknesses

     

    Mark Rodwell

    20160512_TC_PR_Diags_2_02.pptx
    Coupled land-atmosphere variability

    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

    Land_surface_predictability_for_training_course.pdf

    tc2016



    Expand
    titleThe seasonal forecast system at ECMWF

    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:

    • explain the scientific basis of seasonal forecast systems
    • describe in outline ECMWF System 4 and its forecast performance
    • discuss the critical factors in further improving forecast systems

    Tim Stockdale

     

    pptx

    pdf


     

    2
    .00-3
    .00


    Expand
    titleSources of predictability beyond the deterministic limit

    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:

    • describe the Lorenz idea of Predictability of the first and second kind
    • list examples of the elements of the Earth system that provide predictability on longer timescales
    • understand the type of forecast that we are able to provide beyond the deterministic limit

    Sarah Keeley

    Beyond_limit

    _upd
    pptx

    pdf


     


    Expand
    title
    Using stochastic physics to represent model error
    • explain the physical and practical motivations for using stochastic physics in an ensemble forecast;

    • describe the two stochastic parameterization schemes used in the IFS ensemble, and their respective purposes;

    • be able to identify the improvement in forecasting skill from the inclusion of stochastic physics.

    Post-processing of ensemble forecasts

    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:

    • describe a wide range of possible calibration methods for ensemble systems
    • explain which methods are suitable in which circumstances
    • discuss the merits of calibration and multi-model combination

    Tim Stockdale

    tc2017_calibration

    Sarah-Jane Lock

    StochPhys2016


    Expand
    title
    Diagnostics (1)
    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:
    •   Some of the key weakness of the ECMWF forecast system 
    •   Some of the diagnostic tools used to identify and understand these weaknesses

    Mark Rodwell

    20160511_TC_PR_Diags_1_02.pptx

    Expand
    titlePost-processing of ensemble forecasts

    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:

    • describe a wide range of possible calibration methods for ensemble systems
    • explain which methods are suitable in which circumstances
    • discuss the merits of calibration and multi-model combination

     

    Tim Stockdale
     

    tc2016_calibration.pptx

    2.45pm Discussion Session in the Weather Room

    Expand
    titleLatest forecasts

    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.

    3.30-4.30
    Expand
    titleInitial uncertainties in the medium-range ENS (1)
    The aim of the this lecture is to discuss basic concepts behind initial perturbation techniques.
    After the lecture you should be able to:
    •   Understand the difference between singular vectors and breeding (ETKF) vectors 
    •   Explain why pure random perturbations do not work

    Linus Magnusson

    traning_2016_inipert1_lm.pptx

    Expand
    titleStratospheric impacts

     

    Ted Shepherd

    ECMWF_Predictability_2016_new.pdf

     

     

    Stratospheric impacts

     

    Andrew Charlton-Perez

    charlton_perez_strat.pdf


      
    Expand
    titleCoupled ocean-atmosphere variability
    This lecture provides a broad overview of the role of the ocean on the predictability and prediction of weather and climate. It introduces some basic phenomena needed to to understand the time scales and nature of the ocean-atmosphere coupling.
     

    Magdalena Balmaseda

    TCPR_Balmaseda_2017_ocean_updated.pdf

    2.45pm Discussion Session in the Weather Room

    Expand
    titleLatest forecasts

    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.

     


     

    3.30


    Expand
    titleInitial uncertainties in the medium-range ENS (2)

    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:

    • explain the idea behind using singular vectors in the ensemble

    • describe how singular vectors are calculated

    • describe the construction of the ensemble perturbations

    SImon Lang

    lang_1_2017.pdf


    Expand
    titleEnsemble verification (2)

    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

    • explain what a reliable probabilistic forecast is and how to measure reliability

    • understand why resolution and sharpness of a probabilistic forecast matter

    • compute several of the standard verification metrics used for ensemble forecasts

    Martin Leutbecher

    v2handout.pdf


    Linus Magnusson/Sarah Keeley

    Practice Session:

     

    Expand
    titleLorenz '95 model

    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:

    Ensemble Verification

     

    Expand
    titleEconomic Value of Ensembles

     

    Louise Arnal, Sarah Keeley and Sarah-Jane Lock



     


    4.30-5.15
    Understanding Ensembles Practical

    Computer hall and Weather Room Tours

     

     

     

    5.15

    Poster session and

    ice breaker

    Lecture and Practice Session:

    Expand
    titleApplication of ENS: Flood

    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:

    • Describe the components in hydrological ensemble prediction systems (HEPS).

    • Describe the major sources of uncertainty in HEPS and how they can be reduced.

    • Explain the difficulties in using probabilistic flood forecasts in decision making.

    Fredrik Wetterhall

    fred_

    flooding2016
    pptx
    Practical extensionPractical extension