Page History

...

Extended Range Structure

The extended range (monthly) ensemble is run daily based on 00UTC data.  The products cover the period up to Day46 and are derived from a 100 member ensemble with a control and has a resolution of 36km.   The extended range ENS is independent of the medium range ENS and has it's own control and extended range model climate (ER-M-climate).

The extended range ENS covers a time scale lying between:

• medium range forecasts (ENS to day 10 and to day15).  These are mainly governed by atmospheric initial values (background plus new observed data) but less so on ocean temperature information.
• seasonal forecasts. These are more reliant on predictability of the oceans and on the impact that tropical sea-surface temperatures have on the atmospheric circulation.

...

• can influence the development of synoptic-scale systems (e.g. tropical cyclones)
• influences meteorological evolution and predictability in the extra-tropics
• helps capture the propagation of Madden-Julian Oscillation (MJO) events, notably in the equatorial Indian Ocean and western Pacific ocean. 

The LIM2 subprogram (within NEMO) forecasts changes in the sea-surface temperature and sea-ice evolution.   Note: ECMWF uses LIM2 which is an earlier version of the Louvain-la-Neuve sea ice model currently available (Version 3.6).

The oceanic ensemble has been introduced to enable representation of the uncertainty of the sea-surface temperature and associated heat and moisture fluxes.  The initial conditions of the oceanic ensemble are perturbed using five ocean assimilations (1 control and 4 perturbed) produced by addition and subtraction of two randomly selected wind stress perturbations.  The same perturbations cannot be chosen for 2 consecutive months.  

Re-forecasts provide an Extended Range climate (ER-M-climate) and associated probability distribution functions (pdfs) for several variables.  The latest extended range ensemble forecasts and the associated probability density functions can be compared with the ER-M-Climate.  The differences between the two are used as the basis of model products any model drift is effectively removed. 

...

The extended range model climate (ER-M-climate) drifts towards becoming rather too cold at longer lead-times in wintertime high latitudes.  Hence the anomaly in forecast temperatures against ER-M-climate temperatures may be too large.  The magnitude of the drift is not uniform.  At longer lead-times the trend in northern China is towards colder values but less so in Siberia and Canada.  The variation may be due to the analysed initial snowpack conditions and/or snowmelt in marginal snow cover areas in these areas.  Issues regarding this are being addressed. A multi-layer snow scheme is incorporated.  

...

After about 10 days of forecasts, the spread of the ensemble can become very large.  A significant shift can be detected by comparing probability distribution functions of the latest model and the ER-M-climate.

The re-forecasts are created twice a week (Mondays and Thursdays) and are ready a week before the real-time forecasting suite starts.  Real-time forecasts are calibrated using all the re-forecasts available in a one week window centred on the forecast start day and month. 

...