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title08-07-2019 ECCC

The ECCC global ensemble prediction system (origin cwao in the TIGGE archive) was upgraded on July 3 2019.

The main changes in this upgrade are:

  • The horizontal resolution of the Global Deterministic Prediction System (SGPD) is reduced from 25km to 15km, and the number of vertical levels is increased from 80 to 84 levels.
  • The atmospheric component of the Global Ensemble Prediction System (GEPS) is now coupled with the ocean-ice model.
  • The horizontal resolution of the Regional Ensemble Prediction System (REPS) increases from 15km to 10km, with an increase in the output frequency from 2 to 4 runs per day.

Full details of the changes made to the various systems are available in this official page.


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title18-9-2018 ECCC

The ECCC global ensemble prediction system (origin cwao in the TIGGE archive) was upgraded to version 5.0.0 on 18 September 2018.

The main changes in this upgrade are:

  • The 800x400 global Gaussian grid at 50 km resolution is updated to a Yin-Yang grid at 39 km resolution
  •   The model top is raised from 2 hPa to 0.1 hPa.
  •  In the ensemble Kalman filter assimilation component, the digital filter initialization is replaced by an incremental analysis update (IAU) procedure.

Further documentation of the operational upgrade can be found at  http://collaboration.cmc.ec.gc.ca/cmc/cmoi/product_guide/docs/changes_e.html

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title21-11-2007 JMA

The resolution of one-week ensemble prediction model of JMA was upgraded on 21 November 2007.

Major changes are:

  • Increase in the resolution from TL159L40 to TL319L60 with a topmost level raised from 0.4hPa to 0.1hPa.
  • Use of a new high-resolution analysis of sea surface temperature and sea ice concentration as ocean surface boundary conditions.
  • Use of surface snow depth data from the domestic dense observational network in the global snow depth analysis.
  • Introduction of a convective triggering scheme into the deep convection parameterization.
  • Introduction of a new 2-dimensional aerosol climatology derived from satellite observations for the radiation calculation.
  • Increase in the resolution of inner loop model of the four-dimensional variational (4D-Var) data assimilation system from T106L40 to T159L60.
  • Introduction of a sigular vector method to make the initial perturbations.

Notes:

  • The resolution and parameters of TIGGE data from JMA remains unchanged.
  • Orography and Land Sea Mask in TIGGE data are slightly different from the previous data associated with the model change.

UKMO

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title04-12-2019 MetOffice

UM upgraded to version PS43 for the 12UTC cycle on 4 December 2019.

The PS43 upgrade to the Met Office global modelling capability introduces a new data assimilation system to the global ensemble and a significant upgrade to the global model physics. MOGREPS-G is now driven by an ensemble of analyses, each with its own data assimilation cycle (En-4D-en-VAR), replacing the original ETKF (Ensemble Transform Kalman Filter) method. The result is a more sophisticated ensemble with increased spread and stability.

The global model physics is upgraded to the GA7.2 configuration which is focused on improvements to physical processes. This has several significant benefits including improvements to 250hPa winds, 850hPa tropical winds and temperatures and improved tracks of Tropical Cyclones. The UM is upgraded to UM11.2.


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title11-07-2017 MetOffice

UM upgraded to version PS39 from 12UTC cycle on 11 July 2017.

TIGGE global ensemble (the Met Office MOGREPS-G) was upgraded to 20km (from 33km), N640L70, 280x960 lat-long grid, 0.1875 N-S x 0.28125 E-W degrees;  the MOGREPS-G will continue to run four times a day (00, 06, 12 and 18UTC), but the number of ensemble members per run has increased from 12 to 18, with the last two runs being combined to create a 36-member time-lagged ensemble.

Forecast length remains at 7d 6h.

Relevant associated deterministic/data assimilation changes:

  • Replace RTTOV9 by RTTOV11
  • New ground GPS observation operator
  • Improved snow analysis reconfiguration
  • Upgrade to UM10.6

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