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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 location and the time of year.   Seasonal forecasts give an indication of likely conditions beyond 6 six weeks ahead.  These are run monthly giving forecasts to 7 months ahead, and run quarterly with forecasts extended to 12 13 months ahead.  Output concentrates on the anomalies relative to the seasonal climate.

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This guide is intended to give an outline of structure and use of the ECMWF IFS.  It also aims to show how the high-resolution forecast (HRES), ensemble forecast (ENS), extended range forecast and seasonal forecast models inter-depend and interact.  Links to more detailed descriptions of processes are given, mainly at the end of each section, whilst separate online .  Online ECMWF training resources (eLearning)  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))


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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.

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