Long-range Forecasting

The second version of the National Centers for Environmental Prediction (NCEP)'s Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. It is a fully coupled model representing the interaction between the Earth's atmosphere, oceans, land and sea-ice. For forecast products issued in May 2022 onwards, Copernicus C3S-NCEP data are used.

Forecasts: The NCEP CFSv2 forecasts are generated using ensembles of 50 members, or 50 model runs. As four model runs are available each day, the current practice is to use the latest 12/13 days’ forecast to the 1st of each month to build the ensemble for the nominal start date on the first of that month.

Re-forecasts: The re-forecast data are also used in the verification of the forecasts, as well as for creating the climatology. We use a re-forecast period of 1993-2016, with five to seven start days (4 model runs every 5 days day) made available depending on the calendar start month. Our current practice is to use all available start days' runs for each calendar month to create an ensemble of 20 to 28 members. 

Further information on NCEP CFSv2 (C3S dataset) can be found in Copernicus Services link. More information on NCEP CFSv2 can also be found in Saha et al. 2014:

Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., Chuang, H.Y, Iredell, M., et al. 2014. The NCEP Climate Forecast System Version 2. Journal of Climate, Volume 27, pp. 2185-2208.

ECMWF is the European Centre for Medium-Range Weather Forecasts. The fifth generation of the ECMWF seasonal forecasting system, SEAS5 was introduced in November 2017, replacing System 4. ECMWF SEAS5 includes updated versions of the atmospheric (IFS) and ocean (NEMO) models and adds the interactive sea ice model LIM2.

Forecasts: ECMWF SEAS5 forecasts are generated using ensembles of 51 members, or 51 model runs initiating on the first day of each month.

Re-forecasts: The re-forecast data are also used in the verification of the forecasts, as well as for creating the climatology. We use a re-forecast period of 1993-2016 (from the available 1981 – 2016 period), with 25 runs made available on the first day of each month.

Further information on ECMWF SEAS5 (C3S dataset) can be found in Copernicus Services link.

The CMCC Climate Model is a coupled Earth System Model developed by the Centro Euro-Mediterraneo sui Cambiamenti Climatici. The current version of the CMCC Seasonal Prediction System (CMCC-SPS3.5) is a fully coupled atmosphere-ocean-land-sea ice model used for seasonal to decadal climate predictions, climate change projections and impact studies. It is operational since 1^st October 2020. It has flexible resolution options depending on application needs. The core components of CMCC are Atmosphere (ECHAM5), Ocean (OPA/NEMO), Land Surface (SILVA), carbon cycle processes and PELAGOS for ocean biogeochemistry.

The 10 atmospheric perturbed initial conditions, the 3 land perturbed initial conditions and the 9 ocean initial conditions (8 perturbed plus the unperturbed, only 4 perturbed in hindcast mode) are combined to yield 270 possible perturbed forecast system initial conditions.

Forecasts: CMCC SPS3.5 forecasts are generated using ensembles of 50 members (chosen at random from the 270 possible perturbed forecast system initial conditions), initiating on the first day of each month.

Re-forecasts: The re-forecast data are also used in the verification of the forecasts, as well as for creating the climatology. 40 ensemble members, with the 40 initial conditions chosen at random similar to the forecasts, although with only 4 perturbed ocean initial conditions for a total of 120 possible perturbed re-forecasts initial conditions. The static hindcast set is available for the period 1993-2016. 

Further information on the CMCC-SPS3.5 (C3S dataset) can be found in Copernicus Services link.

The German Climate Forecast System (GCFS) is operated jointly by the Deutscher Wetterdienst (DWD), the Center for Earth System Research and Sustainability (CEN) at Universität Hamburg and the Max Planck Institute for Meteorology (MPI-M). It is the first system in Germany that generates worldwide seasonal forecasts on a routine basis and makes them available to the public. The seasonal forecast system is based on the Earth system model of the Max Planck Institute for Meteorology (MPI-ESM). It comprises of the atmospheric component (extending up to at least 80 km height), the land surface component (including soil and land-use), the ocean component and the sea-ice component.

Forecasts: DWD GCFS forecasts are generated using ensembles of 50 members, or 50 model runs initiating on the first day of each month.

Re-forecasts: The re-forecast data are also used in the verification of the forecasts, as well as for creating the climatology. We use a re-forecast period of 1993-2016  (from the available 1993 – 2019 period), with 30 members per run made available on the first day of each month. Available data from 1990 to 2019.

 Further information on the DWD (C3S dataset) can be found in Copernicus Services link.

The Environment and Climate Change Canada (ECCC) forecast system includes two modelling systems:  Canadian Earth System Model (CanESM) and GEM5.2-NEMO.

CanESM is a fully coupled atmosphere-ocean-land-sea ice-biochemical climate  model operational since 30 June 2024. GEM5.2-NEMO, like its predecessor GEM-NEMO versions, is developed at the Recherche en Prévision Numérique (RPN), and is a fully coupled model with the atmospheric component of GEM (Côté et al. 1998) and the ocean component of NEMO (Nucleus for European Modelling of the Ocean, http://www.nemo-ocean.eu ).

Forecasts: Both the models are initialised on the last day of previous month and 5th to last day of previous month.  The 20 ensemble members (10 members per day) from each of the two systems are simply averaged to have the combined ECCC products.

Re-forecasts: The re-forecast data are used in the verification of the forecasts, as well as for creating the climatology. We use re-forecast for 1993-2016 for both models (from the available 1980 – 2023 period) and are initialised on the last day of previous month and 5th to last day of previous month. The 20 ensemble members (10 members per day) from each of the two systems are simply averaged to have the combined ECCC products.

Further information on the ECCC(C3S dataset) can be found in Copernicus Services link.

The Japan Meteorological Agency (JMA) operates the seasonal ensemble prediction system (MRI-CPS3 or Meteorological Research Institute-Coupled Prediction System version 3). Operational since February 2022, it is used for rainfall and temperature monthly forecasts and ENSO outlook. It is a coupled atmosphere/ocean/land/sea ice-coupled prediction system consisting of an initialization system and a forecast model.

The ensemble prediction system involves a combination of lagged average forecast (LAF) and initial perturbation as in the previous system (Takaya et al. 2018). Five-member ensemble predictions are made every day from 00UTC, and perturbed atmospheric conditions are determined for each initial time using BGM (Toth and Kalnay 1993, Chikamoto et al. 2007). Ocean perturbations are calculated using 4DVAR minimization history, by which daily analysis error covariance can be approximated (Niwa and Fujii 2020).

Forecasts: The JMA MRI-CPS3 forecasts are generated using ensembles of 50 members, or 50 model runs. As five model runs are available each day, the current practice is to use the latest 10 days’ forecast to the 1st of each month to build the ensemble for the nominal start date on the first of that month.

Re-forecasts: The re-forecast data are used in the verification of the forecasts, as well as for creating the climatology. The JMA MRI-CPS3 re-forecast is available for 1993-2016 , with 2 start dates lagged by 15 days and 5 members for each start date for a total of 10 members.

Further information on the JMA (C3S dataset) can be found in Copernicus Services link.

The Météo-France (MF) Seasonal Prediction System, known as Système 9 (System 9), has the following components: Atmospheric Model (ARPEGE-Climat v6.5), Ocean Model (NEMO v4.2), Sea Ice Model (GELATO v6), Land Surface (SURFEX v8) and River Routing (TRIP). The ensemble members are generated with Initial Perturbations of Singular vectors for Atmosphere along with ocean analysis perturbations and SURFEX offline simulation for land surface. Stochastic physics (SPPT scheme) is used for model uncertainty.

Forecasts: The MF Seasonal Prediction System 9 forecasts are generated using ensembles of 51 members. The forecast uses three start dates: the penultimate Thursday of the previous month (25 members), the last Thursday of the previous month (25 members) and the 1st of the month (1 member in the forecast).

Re-forecasts: The re-forecast data are also used in the verification of the forecasts, as well as for creating the climatology. We use a re-forecast period of 1993-2016  (from the available 1993 – 2018 period), with total of 31 members. The re-forecast uses three start dates: the penultimate Thursday of the previous month (15 members), the last Thursday of the previous month (15 members) and the 1st of the month (1 member in the forecast/hindcast).

 Further information on the MF Système 9 (C3S dataset) can be found in Copernicus Services link.