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“Behind good forecast practices are often hidden good theories; equally, good theories should provide a basis for good forecast practices.”     Professor Tor Bergeron, personal communication, 1974                                         

                                   

This edition of the Forecaster User Guide applies to the ECMWF Integrated Forecast System (IFS) and meteorological products after June 2023 using IFS Cycles 48r1 and later.

Aim of the Forecaster User Guide

The aim of this User Guide is to help meteorologists make the best use of the forecast products from ECMWF - to increase understanding of the ensemble forecast process, to develop new products, to reach new sectors of society, to satisfy new demands.  The User Guide presents the Integrated Forecasting System (IFS) and advises on how best to use the output, not least on how to build up trust in the forecast information.  A good forecast that is not trusted is a worthless forecast.  The emphasis is on the medium-range forecast products, as this is ECMWF’s primary goal, and because medium-range NWP output generally differs significantly from that dealing with short-range or seasonal NWP.   Extended range forecast (days 16 to 42) output concentrates on the probabilities of anomalies from the norm during a 5-7day forecast period at a given location for any time of year.  Seasonal forecasts give an indication of likely conditions beyond six weeks ahead.  These are run monthly giving forecasts to 7 months ahead, and run quarterly with forecasts extended to 12 months ahead.  Output concentrates on the anomalies relative to the seasonal climate.  

The ECMWF IFS is upgraded at roughly half yearly intervals to incorporate better representation of physical processes and/or higher vertical or horizontal resolution.   New products increasingly aid early warning of severe or hazardous weather.  Information on the latest upgrade is given below.

This guide is intended to give an outline of structure and use of the ECMWF IFS.  It also aims to show how the IFS models inter-depend and interact.

The IFS models are:

Links to more detailed descriptions of processes are given, mainly at the end of each section, whilst separate online ECMWF training resources are also available to explain aspects of the ECMWF IFS more visually.  Education is a key component of the work at ECMWF and further educational material is available through the web site (e.g. Webinars (recordings), Slidecasts (slides and audio recordings), Tutorials, Training lectures (presentations in PDF)).  ECMWF Newsletters issued quarterly give information on IFS models and applications and ECMWF plans.

The User Guide is broadly divided into two parts.  Sections 2 to 5 describe the structure of the ECMWF Integrated Forecasting System, while Sections 6 to 11 describe how the IFS may be used to best advantage by forecasters.

A glossary is included in an Appendix.

Section2: The ECMWF Integrated Forecasting System (IFS)

Section 2 describes in broad, non-technical terms the ECMWF Integrated Forecast System (IFS) which comprises the global atmospheric model, the wave and the oceanic dynamical models, and the data assimilation systems.  It gives an overview of the way the atmospheric model uses sub-gridscale parameterisations for processes within the atmosphere and at the surface.  There are large differences in energy fluxes between land or sea and the atmosphere. Thus the definition of the model coastline by the land-sea mask is extremely important, not least in the way data is presented (e.g. for meteograms in coastal areas or on islands).

Numerical weather prediction (NWP) output is complicated by its often counter-intuitive and non-linear behaviour.   Understanding model processes enables forecasters to assess model output critically.

Section3: Availability and interpolation of NWP output

Section 3 gives an overview of the way ECMWF graphical forecast products are presented to the forecaster.  It gives some insights into ways the analysed and forecast data may be reduced in accuracy by the way it is presented.

Section4: NWP evolution versus reality

Section 4 discusses model error growth with time and the relationship between predictability and scale.  An indication is given of how anomalies propagate downstream and gives some pointers towards recognition of these in the analysis.

Section5: Forecast ensemble (ENS) - rationale and construction

Section 5 describes the way the members of the ensemble are generated.  The use of ENS allows assessment of uncertainty in the model forecast by giving a range of results.  Each ensemble member starts from slightly perturbed initial data and evolves a little differently from the other members of the ensemble to give a range of possible forecast results.  The variation seen within the ensemble forecasts gives an indication of predictability of the atmosphere.

Section6: Using ENS forecasts

Section 6 discusses the reliance that can be placed upon the ensemble as the forecast lead-time increases.  Each ENS member starts from slightly perturbed initial data and evolves a little differently from the other members of the ensemble to give a range of possible forecast results.  The variation seen within the ensemble forecasts gives an indication of predictability of the atmosphere.  The use of probabilities or other risk assessments is an essential part of building forecasts useful to the customer.  This section emphasizes the benefit of using ensemble products to get the best description of evolution and uncertainty of the forecast state of the atmosphere.

Section7: Dealing with uncertainty

Section 7 concentrates on methods that may be used to assess confidence in model results.   This section gives guidance on interpretation of latest and previous ENS output to allow insight into the uncertainty of the forecast.  It also gives guidance on assessing the skill of a forecast and how to use run-to-run variability in the forecasts to best advantage.  The continuing role of the human forecaster is emphasized.

Section8: ENS products - what they are and how to use them

Section 8 concentrates on making best use of the extensive range of products that are available.  The IFS produces a very wide range of products which is delivered in the form of charts or GRIB format datasets.  It is readily available to forecasters via:

Model climates are an important product produced within the IFS.  These are: M-climate for ENS, ER-M-climate for Extended Range ENS, S-M-climate for Seasonal forecasting.  They are a wholly model-based assessment of worldwide climatology based on analyses and re-forecasts over a period of years (currently 20 years, but 30 years for seasonal forecasting).  Model products may be deterministic, probabilistic, or in the form of anomalies from normal where normal is defined by  the model climates.  ENS output in the form of charts, plumes, meteograms (and wave meteograms), and charts showing the various evolutions of tropical cyclonesand extratropical depressions all give an easy-to-use presentation of data.  Other charts give indication of the variability and uncertainty among the basic model forecasts or compare the latest model output with its predecessors.  The model climates are used extensively to highlight occasions when weather conditions that have been forecast by the ENS are locally extreme for that time of year and for the given forecast lead time.  The Extreme Forecast Index (EFI), pioneered at ECMWF, compares the forecast probability distribution with the corresponding model climate distribution.  The Shift of Tails (SOT) index complements the Extreme Forecast Index (EFI) by providing information about how extreme an event might be by comparing the tail of the ENS distribution with the tail of the M-climate.   The overall aim is to allow assessment of uncertainty to provide the customer with the best and most useful guidance possible. 

Section9: Physical considerations when interpreting model output

Section 9 gives pointers towards features which can have an impact on model output and allow users to modify and improve forecasts for issue to customers.  Some other short-comings of the models are noted which will be addressed in the future but which meanwhile need to be considered by the forecaster.  It is through forecaster user feedback that important points will be identified and addressed.  The importance of critical assessment of model output by human forecasters cannot be understated.

Section10: Interfaces for displaying model output

Section10 gives an outline of the way forecast data may be presented to the user.  ECMWF Web Charts (Open Access) give easy access to ECMWF IFS output.  The more flexible and interactive ecCharts allows users to pick-and-mix the IFS data.

Section11: Conclusion

Section11 highlights the continuing importance of the forecaster in providing a consistent and useful product to the customer.

Section12: Appendices

Section12 contains additional detail on statistical concepts for verifying model forecasts, the current structure of IFS, a list of acronyms, and some references.


The forecaster is not a computer but is employed to add value to model forecasts, and to identify and quantify uncertainties.  Daily operational forecasting work is largely a matter of assessing, interpreting, combining and correcting NWP information.  Also vital is the ability to identify quickly those products that are particularly relevant for a given synoptic situation.  In the medium-range especially, the use of statistical know-how counts as much as synoptic experience. 

Throughout this User Guide forecasters are advised not to try to imitate or simply follow NWP, but to act quite differently by surveying and questioning results from many sources and to produce forecasts with fewer details, greater assessment of uncertainty, and ideally no sudden “U-turns”.  The philosophy is that all forecasts have uncertainty, that uncertainty increases with forecast lead-time, and that forecasters are employed to provide a balanced assessment of the probability of an event that is relevant to customer requirements.

The ECMWF model output is delivered in the form of charts or GRIB format datasets.  It is readily available to forecasters via:


Latest cycle of Integrated Forecast System (IFS) model upgrades. 

Some major changes were made to the IFS with the introduction of Cy48r1 in June 2023.  These are:

  • For the medium range ensemble forecast system:
    • the horizontal resolution is increased to 9 Km
    • the vertical resolution remains unchanged at 137 model levels. 
    • the number of ensemble members remains unchanged at 50 members plus a control member.
    • the horizontal and vertical resolutions are identical to those of the High Resolution (HRES) in earlier versions of IFS.
    • the medium range ensembles are run twice daily from Day0-Day10 and slightly later from Day-0 to Day15.  
  • For the extended range ensemble forecast system:
    • the horizontal resolution remains unchanged at 36 km.
    • the vertical resolution is increased to 137 model levels.  This is the same as the medium range ensemble (and the High Resolution (HRES) in earlier versions of IFS).
    • the number of ensemble members is 100 members plus a control member.
    • the extended range ensemble is run daily from Day0-Day46.
  • A multi-layer snow scheme was introduced.

Note: The extended range forecasts are not just an extension of the medium-range forecasts but are completely separate forecast systems.  However, both start from very similar analyses.  There are two sets of re-forecasts, one for the medium range and one for the extended range. 

The HRES and medium range control member of the medium range ensemble (CTRL) have the same horizontal and vertical resolution and are virtually identical.   Nevertheless the HRES will continue for the time being for ease of use by customers and users.

Full details of the current Integrated Forecast System (IFS) is given in the official ECMWF IFS documentation of CY48r1.


Users are advised to keep themselves updated about changes and improvements to products and model processes through the ECMWF Newsletter and web site (e.g. via the Forecast User portal)



This User Guide has been compiled  by Bob Owens, with assistance from Tim Hewson, and with contributions from many other scientists and ex-forecasters at ECMWF. It is an updated version of the "User Guide to ECMWF Forecast Products" written originally by Anders Persson and published in 2011 (that had minor adjustments in 2013 and 2015).

The User Guide should be cited as follows:           Owens, R G, Hewson, T D (2018). ECMWF Forecast User Guide. Reading: ECMWF. doi: 10.21957/m1cs7h





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