This page gives a short description of the extended forecast graphical products available on the web.
Ensemble mean anomaly
These products are similar to seasonal forecasting graphical products but with weekly means instead of monthly means. Over each point of the map, atmospheric variables such as 2metre temperature, total precipitation, mean sealevel pressure or surface temperature, have been averaged over a weekly period:
Runs  Period 
Thursdays 

Mondays: 

The weekly means have been averaged over the 51 members of the realtime forecast and the 660 members of the back statistics (11 members x 20 years x 3 forecast runs). The weekly anomaly charts charts display the difference between the ensemble mean of the realtime forecast and the ensemble mean of the backstatistics. The graphical products therefore displays the shift of the forecast ensemble mean from the estimated "climatological" mean (created from ensemble runs over the past 20 years).
A WilcoxonMannWhitney test (WMWtest), see for instance Wonacott and Wonacott 1977), has been applied to estimate whether the ensemble distribution of the realtime forecast is significantly different from the ensemble distribution of the backstatistics.
 Regions where the WMWtest displays a significance less than 90% are blank.
 Regions where the WMWtest displays a significance exceeding 99% are delimited by a solid contour (blue or red depending on whether the anomaly is positive or negative respectively).
The blanking of "nonsignificant" shifts does not mean that there is no signal in the blanked regions, but only that, with the particular sampling we have, we cannot be sure that there is a signal. For this reason, there are likely to be many areas where a signal is real but remains undetected.
This product is currently limited to surface temperature, 2metre temperature, total precipitation and mean sea level pressure.
Probability
Probabilities for the weekly mean anomalies to be in the lower or upper third of the model climate distribution (terciles), lower or upper fifth of the model climate distribution (quintiles) and lower or upper tenth of the model climate distribution (deciles) are displayed. Three, five and ten equally probable categories are calculated from the 20year model climatology for each distribution group. The forecast probabilities are calculated from the proportion of ensemble members in each category.
See corresponding charts for weekly probability for mean sea level pressure, precipitation, surface temperature and 2metre temperature
Multiparameter outlook
This products displays geopotential height at 500 hPa and anomalies of 10metre wind, 2metre wind and sunshine duration on the same plot. This product is available only for Europe.
See corresponding charts: Multiparameter outlook Extended range forecast
Plumes
This product displays the time evolution of the ensemble forecast of geopotential at 500 hPa, 12hour accumulated precipitation and temperature at 850 hPa over several European cities. The 51ensemble distribution of realtime monthly forecasts has been categorised in 12.5% intervals (shading) together with the median (solid line).
See corresponding charts: Monthly forecast plumes Extended range forecast
Members
This graphical products (also called stamp maps) is also an extension of an ENS product. It contains 51 stamps. Each stamp represents one ensemble member forecast of geopotential at 500 hPa or mean sealevel pressure. For mean sealevel pressure stamps, the 8 and 16 degree isolines of temperature at 850 hPa are also displayed as cyan and red lines respectively. The stamp maps display the instantaneous fields at days 5, 10, 15, 20, 25 and 30. Weekly means (defined as week1: day 5:11, week2: day 12:18, week3: day 19:25 and week4 day 26:32) are also displayed. As for the plumes, this product is not biascorrected.
See corresponding charts: Mean sea level pressure and z500 stamps Extended range forecast
Clusters
This graphical products is based on a method of regime clusterization used in ENS (see ECMWF Technical Memorandum 317). Six predefined patterns for the Atlantic/Europe region of geopotential at 500 hPa have been determined using several years of ERA15 data. The patterns represent different equiprobable weather regimes. Each member of the ensemble realtime monthly forecast of geopotential at 500 hPa is assigned to the closest pattern for different time steps (5, 10, 15, 20, 25 and 30 days). The products display the patterns computed by averaging all the ensemble members that fall within the same cluster, along with the number of ensemble members that fall within each cluster.This product has also been extended to weekly means. The variability in the population of each cluster from one week to the next is also displayed. This product is not biascorrected.
See corresponding charts: Weather regime clusters Extended range forecast
Hovmoeller diagram
The Hovmoeller diagram displays the time evolution of the ensemble mean anomaly of geopotential height at 500 hPa or 1000 hPa , averaged over the latitude band 35N60N (Northern Extratropics) or 25S and 50S (Southern Extratropics). The anomaly has been computed by averaging all the members of the realtime forecast and subtracting the ensemble mean of the backstatistics (model climatology). Therefore, the graphics display anomalies with respect to the climate of the past 20 years. The xaxis represents the longitude, and the yaxis represents the time evolution (from top to bottom). Since it is an ensemble mean, the structures are much more detailed in the first days of the forecast (top part of the graphics) than in the last days (bottom part). Contours are plotted every metre. Shaded areas represent the ensemble spread and are displayed only when the amplitude of the anomaly exceeds 2 metres. The value of the spread increases sharply during forecast.
See corresponding charts: Timelongitudes diagram Extended range forecast
Large scale mean flow
"Large scale mean flow" shows 500 hPa geopotential anomaly of the ensemble mean averaged over periods of one week.
See corresponding charts: Large scale mean flow Extended range forecast
MJO graphical products
The MaddenJulian Oscillation (MJO) is a main source of predictability on the monthly time scale. The MJO is characterized by an eastward propagation of convection along the tropical band, typically initiated over the Indian Ocean. Several MJO forecast products are available:
 MJO index plot which displays the time evolution of the MJO predicted by ENS. described by a multivariate MJO index (Wheeler and Hendon 2004 Mon. Wea. Rev. vol. 132, 8 p 19171932).
 Timelongitudes section of ensemble mean anomalies of outgoing longwave radiation, zonal wind at 850 hPa and velocity potential at 200 hPa averaged over a tropical band (15N15S).
 Stamp maps of the timelongitudes sections of anomalies of outgoing longwave radiation, zonal wind at 850 hPa and velocity potential at 200 hPa averaged over a tropical band (15N15S) for each ensemble member (51 stamps).
See corresponding charts: MJO index, Timelongitude sections and Stamp maps of the timelongitudes sections
Tropical storm
Two graphical products display monthly forecast of tropical storms:
 Tropical storm frequency or accumulated cyclone energy. This product shows the predicted tropical storm frequency or accumulated cyclone energy (sum of the square of the estimated maximum sustained velocity of every active tropical storm at sixhour intervals) calculated over the same weekly periods than the other monthly forecast products and averaged over an ocean basin. The forecasts have been calibrated using the ensemble reforecasts and past observed tropical storm data. This product is very similar to the seasonal outlook of tropical storm frequency but for a weekly period instead of a full season.
 Tropical storm probabilities. This product shows a grid point map of tropical storm strike probability (probability of a tropical storm passing within 300km), calculated over weekly periods. This product is similar to the tropical cyclone activity maps produced for the mediumrange forecasts.
References:
Wonacott, T.H. and R.J. Wonacott, 1977: Introductory statistics.John Wiley, 650 pp.
See corresponding tropical storm charts.
Last review June 2018