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Alternative names for Sub-seasonal Forecast are IFS-SUBS, IFS-SSP, or IFS-S2S

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.

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

Structure of the this guide

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

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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).  This 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. This is especially true 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.  Consequently each 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.

Model climates are an important product produced within the IFS.  These are: M-climate for ENS, ER-M-climate for sub-seasonal 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 previous period of 20 or 30 years.  

Section6: Using ENS forecasts

Section 6 discusses the reliance that can be placed upon the ensemble as the forecast lead-time increases.  Each ENS slightly perturbed member evolves a little differently from the others and gives 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 a forecast.

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:

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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.  This allows users to modify and improve forecasts for issue to customers.  Some other short-comings of the models are noted.  These will be addressed in the future but meanwhile they 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

Section 10 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

Section 11 highlights the continuing importance of the forecaster in providing a consistent and useful product to the customer.

Section12: Appendices

Section 12 contains additional detail on statistical concepts for verifying model forecasts, the current structure of IFS, and a list of acronyms.

Comments on application of IFS and the Forecaster User Guide

The forecaster is not a computer.   Instead, the forecaster is employed to add value to model forecasts, and to identify and quantify uncertainties.  Forecasters should provide a balanced assessment of the probability of an event that is relevant to customer requirements.  

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• surveying and questioning results from many sources.
• producing forecasts with fewer details.
• assessing the uncertainty.  All forecasts have uncertainty, and that uncertainty increases with forecast lead-time.

• ideally, not giving sudden “U-turns” in guidance.   

Upgrades in latest cycle of Integrated Forecast System (IFS) model Cy49r1. 

Some major model changes were made to the IFS with the introduction of Cy49r1 in October 2024.  These are:

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