GloSea4 is the seasonal prediction system developed and run operationally at the Met Office.
GloSea4 stands for Met Office Global Seasonal forecasting system version 4. It became operational in September 2009.
GloSea4 is an ensemble prediction system (Arribas et al, 2011) built around the first release of the HadGEM3 atmosphere-ocean coupled climate model. GloSea4 has been designed to be more flexible and better integrated within the rest of the Met Office systems than its predecessor was and the development of GloSea4 and HadGEM3 are intrinsically linked. First, interim coupled model versions are tested using the GloSea4 framework as well as in long climate integrations. Second, the seasonal forecasting system is intended to use the latest HadGEM3 release available at the highest resolution affordable in order to provide feedback for further model development.
GloSea4 has two components: the forecast itself and an associated set of hindcasts, also called historical re-forecasts, used for calibration purposes and for skill assessment. In the case of GloSea4 the hindcast covers the period 1996 - 2009. Both forecast and hindcast are performed using the same configuration of the GloSea4 ensemble prediction system but, obviously, with different initial conditions.
A lagged initialisation approach, with all simulations being initialised daily (2 ensemble members initialised every day in the case of the forecast and 3 members initialised on fixed calendar dates - 1st, 9th, 17th and 25th - for the hindcast) is followed to represent the uncertainties in the initial conditions. In a similar manner to the Met Office short- and medium-range ensembles, model uncertainties are represented through the use of stochastic physics schemes (Bowler et al 2008; Shutts, 2005). All climate forcings (aerosols, methane, CO2 concentrations, etc) are set to observed values for the period 1960-2000 and follow the emissions scenario A1B afterwards. Ozone is fixed to observed climatological values and includes a seasonal cycle.
Every month, a 42-member ensemble seasonal forecast for the next six months is generated by combining and bias correcting all forecast members available from the most recent three weeks.