1. Forecast system version
System name: GloSea6-GC3.2
First operational forecast run: 2 Feb 2021
2. Configuration of the forecast model
Is it a coupled model? Yes: Atmosphere, land, ocean and sea-ice.
Coupling frequency: Hourly coupling between atmosphere-land and ocean-sea-ice.
The coupled model Global Coupled 3.2 (GC3.2) is described in Williams et al, 2019.
2.1 Atmosphere and land surface
| Model | Met Office Unified Model (UM) - Global Atmosphere 7.2 Joint UK Land Environment Simulator (JULES) - Global Land 8.0 |
|---|---|
| Horizontal resolution and grid | N216: 0.83 degrees x 0.56 degrees (approx 60km in mid-latitudes) |
| Atmosphere vertical resolution | 85 levels |
| Top of atmosphere | 85km |
| Soil levels | 4 Level 1 : 0 - 0.1 m Level 2 : 0.1 - 0.35 Level 3 : 0.35 - 1.0 m Level 4 : 1.0 - 3.0 m |
| Time step | 15 minutes |
Detailed documentation:
Global Atmosphere 7.0/7.1 & Global Land 7.0: Walters et al, 2017
2.2 Ocean and cryosphere
| Ocean model | NEMO v3.6 - Global Ocean 6.0 |
|---|---|
| Horizontal resolution | ORCA 0.25 |
| Vertical resolution | L75 |
| Time step | 20 minutes |
| Sea ice model | CICE v5.1.2 - Global Sea-Ice 8.1 |
| Sea ice model resolution | ORCA 0.25 |
| Sea ice model levels | 5 categories + open water |
| Wave model | N/A |
| Wave model resolution | N/A |
Detailed documentation: NEMO documentation, CICE documentation
Global Ocean 6.0: Storkey et al, 2017.
Global Sea Ice 8.0: Ridley et al, 2017
3. Initialization and initial condition (IC) perturbations
3.1 Atmosphere and land
| Hindcast | Forecast | |
|---|---|---|
| Atmosphere initialization | ERA-Interim | Met Office Global Hybrid 4D-VAR |
| Atmosphere IC perturbations | None | None |
| Soil moisture & temperature initialization | Met Office JULES-JRA55 analysis | Met Office JULES-JRA55 analysis |
| Snow initialization | Met Office JULES-JRA55 analysis | Met Office JULES-JRA55 analysis |
| Unperturbed control forecast? | No | No |
Detailed documentation:
Met Office Global Hybrid 4D-VAR: Clayton et al, 2013
JRA55 analysis: Kobayashi et al. 2015, Kobayashi et al. 2016
3.2 Ocean and cryosphere
| Hindcast | Forecast | |
|---|---|---|
| Ocean initialization | GloSea Ocean Sea-Ice Analysis (GS-OSIA) | Forecast Ocean Assimilation Model (FOAM) |
| Ocean IC perturbations | No | No |
| Unperturbed control forecast? | No | No |
Detailed documentation:
The GS-OSIA and the FOAM system both use the Nucleus for European Modelling of the Ocean data assimilation system (NEMOVAR). This is a 3d-VAR data assimilation scheme. The GS-OSIA uses different surface forcing (ERA-interim) and observation sets as it is a historical analysis. FOAM uses surface forcing from the Met Office Global NWP model and real-time observations.
The common NEMOVAR system is described in Blockley et al, 2014. Details of the GS-OSIA can be found in MacLachlan et al, 2015.
4. Model uncertainties perturbations:
| Model dynamics perturbations | None |
|---|---|
| Model physics perturbations | Atmosphere stochastic physics scheme, SKEB2 |
If there is a control forecast, is it perturbed? | No control |
Detailed documentation:
5. Forecast system and hindcasts
| Forecast frequency | daily |
|---|---|
| Forecast ensemble size | 2 per day |
| Hindcast years | 24 (1993-2016) |
| Hindcast ensemble size | 7 per start date |
| Hindcast start dates | 1, 9, 17, 25 of each month |
| On-the-fly or static hindcast set? | on-the-fly |
6. Where to find more information
GloSea5 system:
- MacLachlan, C., Arribas, A., Peterson, K. A., Maidens, A., Fereday, D., Scaife, A. A., Gordon, M., Vellinga, M., Williams, A., Comer, R. E., Camp, J., Xavier, P. and Madec, G. (2015), Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Q.J.R. Meteorol. Soc., 141: 1072–1084. doi:10.1002/qj.2396
- Seasonal prediction at the Met Office
- Upgrades to the Met Office Seasonal Forecast System
Model description references:
- Ridley, J., Blockley, E., Keen, A., Rae, J., Schroder, D., West, A., & Schroeder, D. (2017). The sea ice model component of HadGEM3‐GC3.1. Geoscientific Model Development. https://doi.org/10.5194/gmd-2017-212
- Storkey, D., Megann, A., Mathiot, P., Sinha, B., Calvert, D., Hewitt, H., Blaker, A., Kuhlbrodt, T., Graham, T., & Hyder, P. (2017). UK Global Ocean GO6 and GO7: A traceable hierarchy of model resolutions. Geoscientific Model Development. https://doi.org/10.5194/gmd-2017-263
- Walters, D. N., A., Baran, I., Boutle, M. E., Brooks, P., Earnshaw, J., Edwards, K., Furtado, K., Hil,l P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jone,s A., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams K., Zerroukat, M, (2017). The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations. Geoscientific Model Development. https://doi.org/10.5194/gmd-2017-291
- Williams, K. D., Copsey, D., Blockley, E.W., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H. T., Hill, R., Hyder P., Ineson, S., Johns, T. C., Keen, A. B., Lee, R. W., Megann, A., Milton, S. F., Rae, J. G. L., Roberts, M. J., Scaife, A. A., Shiemann, R., Storkey, D., Thorpe, L., Watterson, I. G., Walters, D.N., West, A., Wood, R. A., Woolings, T., Xaivier, P. K. (2017) The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations. Journal of Advances in Modeling Earth Systems, https://doi.org/10.1002/2017MS001115
Initialisation references:
- Clayton, A. M., Lorenc, A. C. and Barker, D. M. (2013), Operational implementation of a hybrid ensemble/4D-Var global data assimilation system at the Met Office. Q.J.R. Meteorol. Soc., 139: 1445–1461. doi:10.1002/qj.2054
- Blockley, E. W., Martin, M. J., McLaren, A. J., Ryan, A. G., Waters, J., Lea, D. J., Mirouze, I., Peterson, K. A., Sellar, A., and Storkey, D.: Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts, Geosci. Model Dev., 7, 2613-2638, https://doi.org/10.5194/gmd-7-2613-2014, 2014.
- Shinya KOBAYASHI, Yukinari OTA, Yayoi HARADA, Ayataka EBITA, Masami MORIYA, Hirokatsu ONODA, Kazutoshi ONOGI, Hirotaka KAMAHORI, Chiaki KOBAYASHI, Hirokazu ENDO, Kengo MIYAOKA, Kiyotoshi TAKAHASHI (2015), The JRA-55 Reanalysis: General Specifications and Basic Characteristics, Journal of the Meteorological Society of Japan. Ser II. https://doi.org/10.2151/jmsj.2015-001
