Overview
1. Ensemble Version | ||
|---|---|---|
| Version Identifier Code | 40r1 | 31r1 |
| Date of first implementation of this version |
|
|
| Please provide a short description of the Ensemble Prediction System | Global ensemble system that simulates initial uncertainties using singular vectors and perturbations from an ensemble of data assimiliations. Model uncertainties represented with SPPT and SKEB. Based on 51 members, run twice-a-day up to day 15, (extended to 32 days twice weekly, on Mondays and Thursdays). | Global ensemble system that simulates initial uncertainties using singular vectors and model uncertainties due to physical parameterisations using a stochastic scheme. Based on 51 members, run twice-a-day up to day 15, with at 00UTC a coupled ocean system from day 10 to day 15 (extended to 32 days once a week, on Thursdays). |
| Research or Operational? If not operational, are there any plans to become so? | Operational | |
| Global or Regional EPS? (See section 7 for items specific to regional EPS) | Global | |
| Data time of first forecast run | ||
| Date of last forecast with this version (if applicable) | ||
| Data time of last forecast run (if applicable) | ||
| Is there a higher-resolution control forecast available? (If yes, this should be described in a separate sheet of this spreadsheet.) | No | |
| Brief summary of main changes from previous version (keywords). | Coupling to NEMO ocean model, 91 levels with top a 1 Pa, higher horizontal resolution, EDA initial perturbations, revised model uncertainty representation | N/A - First version listed |
2. Configuration of the EPS | ||
| Horizontal resolution of the model. (Where variable resolution is used, please describe in full.) | TL639 | TL399 |
| Horizontal configuration and resolution of the output grid | TL639 L91 for day 1 to day 10 (leg 1) and TL319 L91 after day 10 (leg 2) The resolution archived is N320 reduced gaussian grid for leg1 and N160 reduced gaussian grid for leg2. | T399 L62 for day 1 to day 10 (leg 1) and T255 L62 for T+246 to day 15 (leg 2) The resolution archived is N200 reduced gaussian grid for leg1 and N128 reduced gaussian grid for leg2. |
| Number of model levels | 91 | 62 |
| Type of model levels (eg sigma) | sigma | |
| Forecast length and forecast step interval | T+0h to T+360h at 6h | |
| Runs per day (Times in UTC) | 2 (00, 12) | |
| Is there an unperturbed control forecast included? (Y/N) | Y | |
| Number of perturbed ensemble members (excluding control) | 50 | |
| Integration time step | 20 min for leg 1 and 45 min for leg 2 | 30 min |
| Top of model - model section | ~0.01hPa | ~5hPa |
| Is model coupled to an ocean model? | Yes | No |
| If yes, please describe ocean model briefly including any ensemble perturbations applied | NEMO 1deg, 5 different ocean analyses | |
| Additional comments | ||
3. Initial conditions and Perturbations | ||
| Data assimilation method for control analysis | 4D-Var 12h window | |
| Resolution of model used to generate control analysis | TL1279L137 | TL799L91 |
| Control variables used in data assimilation | N/A | N/A |
| Ensemble initial perturbation strategy | Singular Vectors (Total energy norm) and ensemble of data assimilations (EDA) | Singular Vectors (Total energy norm) |
| Optimisation time in forecast (if applicable) | T+48 | |
| Horizontal resolution of perturbations (if different from model resolution) | singular vectors T42L91 and TL399L137 for EDA | T42L62 |
| Initial perturbed area | global | Extra tropical (<30S, >30N) + up to 6 tropical areas |
| Are perturbations to observations employed? (Y/N) | Yes | No |
| Perturbations added to control analysis or derived directly from ensemble analysis | Added | Added |
| Perturbations in +/- pairs? (Y/N) | Yes | |
| Additional comments | N/A | N/A |
4. Model Uncertainty Perturbations | ||
| Is model physics perturbed? If yes, briefly describe method(s). | Y. Uses Stochastically Perturbed Parameterization Tendencies (SPPT) and Stochastic Kinetic Energy Backscatter (SKEB) | Y. Stochastic perturbation of physics tendency by factor in range [0.5,1.5] |
| Do all ensemble members use exactly the same model version, or are, for example, different parameterisation schemes used? Please describe any differences. | Same | |
| Is model dynamics perturbed? If yes, briefly describe method(s). | No | |
| Are the above model uncertainty perturbations applied to the control forecast? | No | |
| Additional comments | N/A | N/A |
5. Surface Boundary Perturbations | ||
| Perturbations to sea-surface temperature? If yes, briefly describe method(s). | Yes, 5 different ocean analyses | No |
| Perturbations to soil moisture? If yes, briefly describe method(s). | Yes, from EDA | No |
| Perturbations to surface wind stress or roughness? If yes, briefly describe method(s). | No | |
| Any other surface perturbations? If yes, briefly describe method(s). | No | |
| Are the above surface perturbations applied to the control forecast? | N/A | |
| Additional comments | N/A | N/A |
6. Other details of model | ||
| Description of model grids. | Linear grid | |
| List of model levels in appropriate coordinates | Operational configurations of the ECMWF Integrated Forecasting System | |
| What kind of Large scale dynamics is in use (e.g. gridpoint semi-Lagrangian)? | Spectral semi-lagrangian | |
| What kind of boundary layer parametrization is in use? | Moist EDMF with Klein/Hartmann stratus/shallow convection criteria | |
| What kind of convection parametrization is in use? | Tiedtke 89, Bechtold et al 2004 (QJ) which improved the triggering | |
| What kind of large-scale precipitation scheme is in use? | IFS documentation | |
| What Cloud scheme is in use? | Tiedtke 93 prognostic cloud fraction | |
| What kind of land-surface scheme is in use? | HTESSEL | |
| How is radiation parametrized? | IFS documentation | |
| Other relevant details? | N/A | |
7. Regional Ensemble specifics | N/A | |
| Regional domain descriptor (lat/long of boundaries) | ||
| Normal source of boundary conditions | ||
| Are boundary conditions perturbed? | ||
| Specification of boundary conditions required. | ||
| Are boundary condition requirements compatible with any other global models or standards? If so, please describe | ||
| Are initial conditions downscaled from a global analysis or is a regional analysis used? | ||
| Is regional ensemble a downscaling of global ensemble perturbations, or are specific regional perturbations calculated? | ||
| Additional comments | ||
8. Further Information | ||
| Scientific contact | ECMWF Service Desk | |
| URLs for Scientific documentation | IFS documentation | |
| Technical contact point | ECMWF Service Desk | |
| URLs for Technical documentation | IFS documentation | |
| Other contact points | ECMWF Service Desk | |
| URLs for system documentation | User guide to ECMWF forecast products | |
| Data policy of originating centre for usage of data in TIGGE | Users of the ECMWF data sets are requested to reference the source of the data in any publication, e.g. "ECMWF ERA-40 data used in this study/project have been provided by ECMWF/have been obtained from the ECMWF Data Server". | |
9. TIGGE Specific Information | ||
| Version Identifier Code | ||
| Date of first forecast in TIGGE | 1st October 2006 | |
| Data time of first forecast run in TIGGE | 0 Z | |
| Date of last forecast in TIGGE | N/A | |
| Data time of last forecast run in TIGGE | N/A | |
| Is there a higher-resolution control forecast included in TIGGE? If so give tab name where it is described. | Yes, there is a control forecast run at TL639 and a high resolution forecast run at TL1279 | Yes, there is a control forecast run at T399 and a high resolution forecast run at T799 |
Key reference papers for EPS
- Buizza, R., & Palmer, T. N., 1995: The singular-vector structure of the atmospheric general circulation. J. Atmos. Sci., 52, 9, 1434-1456.
- Molteni,F., Buizza,R., Palmer,T.N. and Petroliagis,T., 1996: The ECMWF Ensemble Prediction System: Methodology and Validation Q.J.R Meteorol.Soc. (1996) Vol 122, pp 73-119.
- Buizza, R., Miller, M., & Palmer, T. N., 1999a: Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc., 125, 2887-2908.
- Buizza, R., Bidlot, J.-R., Wedi, N., Fuentes, M., Hamrud, M., Holt, G., & Vitart, F., 2007: The new ECMWF VAREPS (Variable Resolution Ensemble Prediction System). Q. J. Roy. Meteorol. Soc., 133, 681-695.