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SYSTEM | FORECASTS | HINDCASTS | |||
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ENSEMBLE SIZE and START DATES | PRODUCTION | ENSEMBLE SIZE and START DATES | PRODUCTION | ||
ECMWF | System 4 (CDS system: 4) | 51 members start on the 1st | real-time | 15 members start on the 1st | fixed dataset |
SEAS5 | 51 members start on the 1st | real-time | 25 members start on the 1st | fixed dataset | |
Météo-France | System 5 | 51 members (a) 26 start on the first Wednesday after the 19th | real-time | 15 members start on the first Wednesday after the 19th (a) | fixed dataset |
System 6 (CDS system: 6) | 51 members 1 starts on the 1st | real-time | 25 members 1 starts on the 1st | fixed dataset | |
System 7 | 51 members 1 starts on the 1st | real-time | 25 members 1 starts on the 1st | fixed dataset | |
Met Office | GloSea5 (b) (CDS system: 12,13, 14, 15 (d)) | 2 members start each day (c) | real-time | 7 members on the 1st | on-the-fly produced around 4-6 weeks in advance |
CMCC | SPSv3 | 50 members start on the 1st | real-time | 40 members start on the 1st | fixed dataset |
DWD | GCFS2.0 (CDS system: 2) | 50 members start on the 1st | real-time | 30 members start on the 1st | fixed dataset |
NCEP | CFSv2(b) | 4 members start each day 1 member per start hour: 0, 6, 12, 18 | real-time | 4 members start every 5 days (e) 1 member per start hour: 0, 6, 12, 18 | fixed dataset |
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(b) The production schedules of forecasting system with lagged start dates don't prescribe how to build an ensemble for a specific nominal start date. The choices currently in use for the C3S products for those forecasting systems can be found within the information about the concept of nominal start date.
(c) Due to the flexibility of the Met Office forecasting system, forecast failures on a given date are not usually recovered by re-running the missed forecasts at a later date, but by running more members with initial conditions of the day of recovery.
Example: An incident affected the 22 August 2017 forecast so no members are available for that date. Instead, 4 members were initialised on 23 August 2017.
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