| |
|---|---|
| System name (version) | JRA-3Q |
| Date of implementation | November 2022 |
2. Configuration | |
|---|---|
Earth system components included in the analysis system (e.g., ocean, sea-ice, land, etc.) | Atmosphere, land. |
Horizontal resolution of the model, with indication of grid spacing in km (for the different Earth system component included in the model) | TL479 (~40km) for the atmospheric and land models. |
Number of levels in the different Earth system components (for the different Earth system component included in the model) | 100 levels for the atmospheric model. 7 levels for the land model. |
| Frequency of the outputs | Every 6 hours (hourly or daily for some types), monthly statistics. |
| Top of the atmospheric model | 0.01 hPa. |
| Number of analysis cycle per day | 4 |
| Earliest start date | September 1, 1947 |
| Integration time step | 720 seconds for outer model with TL479 resolution, 600 seconds for inner model with TL319 resolution. |
| Length and frequency of the longest forecast | Not applicable |
| Dataset latency | 3 days |
Additional comments:
| 3. Analysis system | |
| Data assimilation method | 4D-Var |
| Length of the analysis window | 6 hours |
| Number of ensemble members and their resolution | Not applicable |
Additional comments:
| 4. Externally prescribed boundary conditions and their source | |
| Sea surface temperature | Until May 1985: COBE-SST2 (Hirahara et al. 2014) From June 1985 onward: MGDSST (Kurihara et al. 2006) |
| Sea-ice | Until May 1985: COBE-SST2 (Hirahara et al. 2014) From June 1985 onward: MGDSST (Kurihara et al. 2006) |
| Snow | Snow depth analysis is performed daily. |
| Vegetation | GLC2000 |
| Land use (and its evolution in time) | Not applicable |
| Aerosols | Five types of aerosols (sulfate, black carbon, organic carbon, sea salt, and mineral dust) are considered to account for the direct effects of aerosols (Yabu et al. 2017). The three-dimensional monthly mean climatology of aerosol mass concentration was derived from a calculation that makes use of the Model of Aerosol Species in the Global Atmosphere (MASINGAR; Tanaka et al. 2003). |
| Green House Gases | CO2: -1983: CMIP6 Historical (Meinshausen et al. 2017) 1984-2016: WDCGG (World Meteorological Organization 2018) 2017-: CMIP6 SSP2-4.5 (O'Neill et al. 2016) CH4: -1983: CMIP6 Historical (Meinshausen et al. 2017) 1984-2016: WDCGG (World Meteorological Organization 2018) 2017-: CMIP6 SSP2-4.5 (O'Neill et al. 2016) N2O: -1983: CMIP6 Historical (Meinshausen et al. 2017) 1984-2016: WDCGG (World Meteorological Organization 2018) 2017-: CMIP6 SSP2-4.5 (O'Neill et al. 2016) CFC-11, CFC-12, HCFC-22: -1954: CMIP6 Historical (Meinshausen et al. 2017) 1955-: A1 scenario: 2014 (World Meteorological Organization 2014) |
| Solar forcing | Constant at 1365 W m-2 |
Additional comments:
| 5. Details of model | |
| Dynamical core (e.g., semi-Lagrangian) | Semi-implicit, semi-Lagrangian |
| Grid structure | Quasi-regular Gaussian latitude/longitude grids |
| Hydrostatic or nonhydrostatic | Hydrostatic |
| Radiations parameterization | Long wave radiation: Two-stream absorption approximation Correlated k-distribution method Short wave radiation: Two-stream with delta-Eddington approximation Cloud radiation: Maximum-random overlap (short wave) |
| Boundary layer parameterization | Monin-Obukhov similarity theory |
| Convection parameterization | Prognostic Arakawa-Schubert (1974) scheme |
| Cloud parameterization | Smith (1990) scheme Stratocumulus: Kawai and Inoue (2006) |
| Land surface parameterization | Improved SiB |
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