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Identifier code: JMA/MRI-CPS2CPS3
First operational forecast run: June 2015 February 2022
2. Configuration of the forecast model
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Model | JMA-GSM |
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Horizontal resolution and grid | TL159TL319 (approx. 110km55km) |
Atmosphere vertical resolution | L60L100 |
Top of atmosphere | 0.1hPa01hPa |
Soil levels | 7 Level 1 : 0 - 0.02 m Level 2 : 0.02 - 0.07 Level 3 : 0.07 – 0.19 m Level 4 : 0.19 – 0.49 m Level 5 : 0.49 – 0.99 m Level 6 : 0.99 – 1.99 m Level 7 : 1.99 – 3.49 mSoil temperature : 1 Soil moisture : 3 |
Time step | 30 20 minutes |
Detailed documentation:
JMA, 20132019: Outline of the operational numerical weather prediction at the Japan Meteorological Agency, . Appendix to WMO Technical Progress Report on the Global Data-processing and Forecasting System (GDPFS) and Numerical Weather Prediction (NWP) Research. Japan Meteorological Agency, Tokyo, JapanResearch. Appendix to WMO Technical Progress Report on the Global Data-processing and Forecasting System and Numerical Weather Prediction, Tokyo, Japan.
2.2 Ocean and cryosphere
Ocean model | MRI.COM v3v4.6 |
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Horizontal resolution | 1ºx0.3º -0.5º on a tripolar grid (See https://ds.data.jma.go.jp/tcc/tcc/products/elnino/move_mricom-g2_doc.html for more information 25ºx0.25º on a tripolar grid) |
Vertical resolution | L52 + Bottom Boundary Layer (BBL)L60 |
Time step | 20 10 minutes |
Sea ice model | part of MRI.COM v3v4.6 |
Sea ice model resolution | same as ocean model |
Sea ice model levels | 5 categories + open water |
Wave model | None |
Wave model resolution | N/A |
Detailed documentation:
Tsujino, H., H. Nakano, TK. MotoiSakamoto, IS. IshikawaUrakawa, M. Hirabara, H. NakanoIshizaki, and G. Yamanaka, T. Yasuda, and H. Ishizaki, 20102017: Reference manual for the Meteorological Research Re-search Institute Community Ocean Model version 4 (MRI.COM) version 3. Technical Reports of the Meteorological Research Institute, 59, 273ppCOMv4). Tech. Rep. MRI, 80.
3. Initialization and initial condition (IC) perturbations
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Hindcast | Forecast | |
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Atmosphere initialization | Japanese 55-year Reanalysis Reanalysis for Three Quarters of a Century (JRA-553Q)Japanese 55-year Reanalysis (JRA-55 | Global Analysis (GA) |
Atmosphere IC perturbations | Breeding Growth Method (BGM) | Breeding Growth Method (BGM) |
Land Initialization | Offline model runs forced by JRA-553Q | Offline model runs forced by JRA-553Q and GA |
Land IC perturbations | None | None |
Soil moisture initialization | Offline model runs forced by JRA-553Q | Offline model runs forced by JRA-553Q and GA |
Snow initialization | Offline model runs forced by JRA-553Q | Offline model runs forced by JRA-553Q and GA |
Unperturbed control forecast? | NoneYesNone | Yes |
Data assimilation method for control analysis: 4D 4D-VAR (atmosphere) and 3D-VAR (ocean)
Horizontal and vertical resolution of perturbations: TL159L60 TL319L100
Perturbations in +/- pairs: Yes
Detailed documentation:
Kobayashi, S., Y. OtaKosaka, YJ. HaradaChiba, AT. EbitaTokuhiro, M. Moriya, H. Onoda, K. Onogi, H. KamahoriY. Harada, C. Kobayashi , and H. Endo, K. Miyaoka, and K. Takahashi, 2015: The JRA-55 reanalysis: General specifications and basic characteristics. J. Meteor. Soc. Japan, 93, 5-48Naoe, 2021: JRA-3Q: Japanese Reanalysis for Three Quarters of a Century. WCRP-WWRP Symposium on Data Assimilation and Reanalysis/ECMWF annual seminar 2021.
3.2 Ocean and cryosphere
Hindcast | Forecast | ||
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Ocean initialization | Multivariate Ocean Variational Estimation (MOVE)/MRI.COM Global 2 3 system (MOVE/MRI.COM-G2G3) | Multivariate Ocean Variational Estimation (MOVE)/MRI.COM Global 2 3 system (MOVE/MRI.COM-G2G3) | |
Ocean IC perturbations | MOVE/MRI-COM-G2 driven by JRA-55 with BGM perturbation | ensemble perturbations approximating analysis error covariances using minimization histories | ensemble perturbations approximating analysis error covariances using minimization historiesMOVE/MRI-COM-G2 driven by JRA-55 with BGM perturbation |
Unperturbed control forecast? | NoneYesNone | Yes |
Detailed documentation:Toyoda T
Usui, N., Y. Fujii, T. Yasuda, N. Usui, T. Iwao, T. Kuragano, K. Sakamoto, and M. Kamachi, 20132015: Improved analysis Development of seasonal-interannual fields using a global ocean data assimilation system. Theor Appl Mech Jpn, 61, 31-48.a Four-Dimensional Variational Assimilation System toward Coastal Data Assimilation around Japan. Mon. Wea. Rev., 143, 3874-3892.
https://ds.data.jma.go.jp/tcc/tcc/products/elnino/move_mricom-g3_doc.html
4. Model Uncertainties perturbations:
Model dynamics perturbations | None |
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Model physics perturbations | Stochastically Perturbed Parametrization Tendencies (SPPT) scheme |
If there is a control forecast, is it perturbed? | Yes |
Detailed documentation:
5. Forecast system and hindcasts
Forecast frequency | Every 5 daysdaily |
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Forecast ensemble size | 135 per day |
Hindcast years | 19811993-2016 |
Hindcast ensemble size | 10 (5 members with 15-day Lagged Average Forecast) |
On-the-fly or static hindcast set? | static |
6. Other relevant information
The available hindcast start dates are as follows:
(NOTE: hindcasts are just available for dates highlighted in bold and underlined)
Start Month | Available Start Days |
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January | 1, 6, 11, 16 , 21, 26 and 31 |
February | 5, 10 , 15, 20 and 25 |
March | 2, 7, 12 , 17, 22 and 27 |
April | 1, 6, 11 , 16, 21 and 26 |
May | 1, 6, 11, 16 , 21, 26 and 31 |
June | 5, 10, 15 , 20, 25 and 30 |
July | 5, 10, 15 , 20, 25 and 30 |
August | 4, 9, 14, 19, 24 and 14 and 29 |
September | 3, 8, 13, 18, 23 and 13 and 28 |
October | 3, 8, 13, 18, 23 and 13 and 28 |
November | 2, 7, 12, 17, 22 and 12 and 27 |
December | 2, 7, 12, 17, 22 and 12 and 27 |
7. Where to find more information
https://ds.data.jma.go.jp/tcc/tcc/products/model/outline/cps3_description.html
https://ds.data.jma.go.jp/tcc/tcc/products/elnino/move_mricom-g3_doc.html