Greenhouse Gases (GHG) Forcing Specifications¶

The Greenhouse Gas (GHG) forcing pipeline ingests CMIP7 global-mean annual surface volume mixing ratios for 9 primary greenhouse gas species, converts them into mass mixing ratios (MMR), linearly interpolates values to January 1, and directly updates the model climate forcing namelist (&clmchfcg) in the downstream ACCESS-ESM1.6 configurations.

Physical Domain & Scientific Scope¶

Species Modeled (9 gases): Carbon Dioxide (co2), Methane (ch4), Nitrous Oxide (n2o), CFC-11 (cfc11), CFC-12 (cfc12), CFC-113 (cfc113), HCFC-22 (hcfc22), HFC-125 (hfc125), and HFC-134a (hfc134a).
Source Representation: Global-mean annual timeseries (yr, gm) distributed in NetCDF format via input4MIPs.
Target Representation: In-memory array of mass mixing ratios written into the Unified Model &clmchfcg namelist group, dimensioned (nyears, 11) across the 11 UM radiatively active gases.
Temporal Interpolation Scheme: CMIP7 source concentrations represent annual means centered at mid-year. Because the UM radiation scheme linearly interpolates between specified annual control points, mid-year values are interpolated to January 1 ($t_{Jan1} = 0.5 \times (t_{yr} + t_{yr+1})$) so that UM monthly integration reproduces the annual means.

Provenance & Dataflow Architecture¶

The greenhouse gas pipeline follows the W3C PROV framework, ingesting global-mean volume mixing ratios, realigning temporal coordinates, and synchronizing configuration patches into the downstream model repository. The architecture separates by experiment requirements: * Pre-Industrial Control (PI): Extracts 1850 single-year scalar concentrations, converts them to mass mixing ratios (MMR), and patches model coupling namelists. See Pre-Industrial Experiment Dataflow Architecture. * Historical (HI): Ingests historical global-mean time series (1750–2022), realigns annual points to January 1, extrapolates backward to 1850, and injects 175-year MMR arrays into Rose app configurations. See Historical Experiment Dataflow Architecture. * ScenarioMIP (SM): Ingests baseline projection time series (2022–2100) alongside 22nd-century extension chunks (CR-<scen>-ext-1-1-0, 2101–2200), concatenates time series to 2150, realigns to January 1, and patches scenario Rose configurations. See ScenarioMIP Experiment Dataflow Architecture.

Controlling Suite Switches¶

The execution, scenario extension, and downstream configuration synchronization for greenhouse gases are controlled by parameters in rose-suite.conf:

Master Activation Switch: ANCIL_CREATE_GHG = true
When set to false, greenhouse gas processing and associated namelist patching tasks are excluded from the execution graph.
Experiment Activation: Governed by USE_EXP['PI'], USE_EXP['HI'], and USE_EXP['SM'].
Scenario Extension Controls (EXTEND_SM_GHG):
Controls whether future pathways concatenate extension files (2101–2200) to cover up to 2150 with --ext:
- 'h': True (Extended to 2150 via CR-h-ext-1-1-0)
- 'hl': False (Bounded to 2100)
- 'm': False (Bounded to 2100)
- 'vl': True (Extended to 2150 via CR-vl-ext-1-1-0)
Downstream Configuration Branching:
Greenhouse gases directly patch the &clmchfcg namelist in clones of access-esm1.6-configs. The source branches are configured via GIT_CONFIG_BRANCH_PRE (dev for PI/HI, pl for SM) and suffixes GIT_CONFIG_BRANCH_SUF (piControl, historical) / GIT_SM_CONFIG_BRANCH_SUF (scen7-<scen>). Remote push is gated by GIT_CONFIG_BRANCH_PUSH = false.
Reference: See Suite Configuration & Parameters Reference for full object definitions.

1. Pre-Industrial Experiment (PI)¶

Dataflow Architecture¶

The pre-industrial GHG pipeline extracts 1850 perpetual concentrations, converts volume mixing ratios to mass mixing ratios (MMR), and patches the model namelist:

flowchart TD
    %% Custom Styles for W3C PROV Semantics
    classDef inputStyle fill:#e1f5fe,stroke:#0288d1,stroke-width:1.5px,color:#01579b
    classDef activityStyle fill:#e8f5e9,stroke:#2e7d32,stroke-width:1.5px,color:#1b5e20
    classDef outputStyle fill:#fff3e0,stroke:#e65100,stroke-width:1.5px,color:#bf360c
    classDef agentStyle fill:#f3e5f5,stroke:#7b1fa2,stroke-width:1.5px,color:#4a148c
    classDef targetStyle fill:#ede7f6,stroke:#4527a0,stroke-width:2px,color:#311b92

    %% Top Level: Inputs and Agents
    subgraph S_TOP["1. Source Inputs and Agents"]
        direction LR
        subgraph Inputs["Input Entities (prov:Entity)"]
            direction TB
            E_GHG[("input4MIPs GHG NetCDFs<br><code>CR-CMIP-1-0-0 (year 1850)</code>")]:::inputStyle
        end

        subgraph Agents["Agents (prov:Agent)"]
            direction TB
            AgCylc{{"Cylc 8 Suite Scheduler"}}:::agentStyle
            AgPy{{"esm1p6_ancil.ghg (Iris and f90nml)"}}:::agentStyle
        end
    end

    %% Middle Level: Transformation Pipeline
    subgraph Activities["2. Transformation Pipeline (prov:Activity)"]
        direction TB
        A_Extract["1850 Mean Extraction<br><i>iris.analysis.MEAN on year 1850</i>"]:::activityStyle
        A_MMR["MMR Conversion<br><i>mole fraction (mol/mol) -> Mass Mixing Ratio (kg/kg)</i>"]:::activityStyle
        A_PI_Patch["Constant Namelist Patch<br><i>f90nml: &clmchfcg scalar concentrations</i>"]:::activityStyle
        A_Extract --> A_MMR --> A_PI_Patch
    end

    %% Lower Level: Output Entities
    subgraph Outputs["3. Output Entities (prov:Entity)"]
        direction TB
        E_PI_Nml[["Pre-Industrial Model Namelist<br><code>atmosphere/input_atm.nml</code>"]]:::outputStyle
    end

    %% Bottom Level: Model Target
    subgraph S_DEPLOY["4. Downstream Deployment"]
        E_Model[["ACCESS-ESM1.6 Configs<br><code>ACCESS-NRI/access-esm1.6-configs (piControl)</code>"]]:::targetStyle
    end

    %% Relationships
    E_GHG -->|prov:used| A_Extract
    A_PI_Patch -->|prov:wasGeneratedBy| E_PI_Nml
    E_PI_Nml -->|Git commit and push| E_Model

    %% Agent Associations
    AgPy -.->|prov:wasAssociatedWith| A_Extract
    AgPy -.->|prov:wasAssociatedWith| A_MMR
    AgPy -.->|prov:wasAssociatedWith| A_PI_Patch
    AgCylc -.->|orchestrates| Activities

`PI_ancil_ghg`¶

1. Description & Purpose:
Extracts perpetual pre-industrial (year 1850) global-mean greenhouse gas concentrations for the 9 species from the CMIP7 historical dataset, converts them to mass mixing ratios, and patches the &clmchfcg namelist in the pre-industrial configuration branch.

2. CLI Arguments Passed:

python -m esm1p6_ancil.ghg.cmip7_PI_ghg_generate \
    --ancil-target-dirname "${VAR.ANCIL_TARGET_PATH}" \
    # Current: "/g/data/${PROJECT}/${USER}/CMIP7/esm1p6_ancil/$(isodatetime -f CCYY.MM.DD)"
    --cmip7-source-data-dirname "${VAR.CMIP7_SOURCE_PATH}" \
    # Current: "/g/data/qv56/replicas/input4MIPs/CMIP7"
    --esm15-inputs-dirname "${VAR.ESM15_INPUTS_PATH}" \
    # Current: "/g/data/vk83/configurations/inputs/access-esm1p5"
    --dataset-version "${CMIP7_GHG_VERSION}" \
    # Current: "CR-CMIP-1-0-0"
    --dataset-vdate "${CMIP7_GHG_VDATE}" \
    # Current: "v20250228"
    --dataset-date-range "${CMIP7_GHG_DATE_RANGE}"
    # Current: "1750-2022"

3. Input4MIPs Versions & Temporal Metadata:
- Dataset Version: ${CMIP7_GHG_VERSION} (CR-CMIP-1-0-0)
- Version Date (vdate): ${CMIP7_GHG_VDATE} (v20250228)
- Input Date Range: ${CMIP7_GHG_DATE_RANGE} (1750-2022)
- Extracted Year: 1850
4. Input4MIPs Directory Path & Filenames:
- Directory Path: ${VAR.CMIP7_SOURCE_PATH}/CMIP/CR/${CMIP7_GHG_VERSION}/atmos/yr/{ghg}/gm/${CMIP7_GHG_VDATE}/
  (Evaluated: /g/data/qv56/replicas/input4MIPs/CMIP7/CMIP/CR/CR-CMIP-1-0-0/atmos/yr/{ghg}/gm/v20250228/)
- Filenames (9 gases): {ghg}_input4MIPs_GHGConcentrations_CMIP_${CMIP7_GHG_VERSION}_gm_${CMIP7_GHG_DATE_RANGE}.nc
5. Python Scripts & Functions:
- Main Script / Entrypoint: esm1p6_ancil.ghg.cmip7_PI_ghg_generate
- Key Functions Called: load_cmip7_ghg_point_mmr, cmip7_ghg_mmr, cmip7_scale, cmip7_pro_greg_date_constraint_from_years, cmip7_ghg_update_namelists_file, format_namelist
- Shared Libraries: iris, cftime, numpy, f90nml
6. Function-Level Cube Transformations & Constraints:
- Input Cubes & Coordinates: 1D NetCDF cubes loaded via iris.load_cube per gas species with 1D Proleptic Gregorian time coordinate. Validates attribute assert ghg == cube.metadata.attributes["variable_id"].
- Constraints Applied: Date constraint cmip7_pro_greg_date_constraint_from_years(1850, 1850) filtering point cftime.DatetimeProlepticGregorian(1850, 1, 1) <= cell.point <= cftime.DatetimeProlepticGregorian(1850, 12, 31).
- Coordinate Bounds & Manipulation: Single annual point extracted without bounds. Scaled from volume mixing ratio (parts per volume) to mass mixing ratio via molar mass ratios: $$\text{MMR} = \text{VMR} \times \frac{M_{\text{gas}}}{M_{\text{air}}}$$
- Created / Output Cubes: Scalar float values assembled into an 11-species row vector passed to cmip7_ghg_update_namelists_file.
7. Produced File Versions & Date Ranges:
None (Direct namelist generation). Represents perpetual year 1850 conditions.
8. Produced File Directory Paths & Filenames:
None. No .anc or binary data files created.

9. Namelist File & Variable Updates:

Target File: ${GIT_PI_CONFIG_DIR}/atmosphere/namelists
Namelist Group: &clmchfcg

Variables Updated:

l_clmchfcg = .TRUE.
clim_fcg_nyears = 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
clim_fcg_years = 1850
clim_fcg_levls = <1850 MMR values for 11 species>
clim_fcg_rates = -32768.0

2. Historical Experiment (HI)¶

Dataflow Architecture¶

The historical GHG pipeline ingests historical global-mean time series (1750–2022), realigns annual points to January 1, extrapolates backward to 1850, and serializes multi-year mass mixing ratio arrays into the Rose application configuration:

flowchart TD
    %% Custom Styles for W3C PROV Semantics
    classDef inputStyle fill:#e1f5fe,stroke:#0288d1,stroke-width:1.5px,color:#01579b
    classDef activityStyle fill:#e8f5e9,stroke:#2e7d32,stroke-width:1.5px,color:#1b5e20
    classDef outputStyle fill:#fff3e0,stroke:#e65100,stroke-width:1.5px,color:#bf360c
    classDef agentStyle fill:#f3e5f5,stroke:#7b1fa2,stroke-width:1.5px,color:#4a148c
    classDef targetStyle fill:#ede7f6,stroke:#4527a0,stroke-width:2px,color:#311b92

    %% Top Level: Inputs and Agents
    subgraph S_TOP["1. Source Inputs and Agents"]
        direction LR
        subgraph Inputs["Input Entities (prov:Entity)"]
            direction TB
            E_HI_GHG[("Historical GHG NetCDFs<br><code>CR-CMIP-1-0-0 (1750-2022)</code>")]:::inputStyle
        end

        subgraph Agents["Agents (prov:Agent)"]
            direction TB
            AgCylc{{"Cylc 8 Suite Scheduler"}}:::agentStyle
            AgPy{{"esm1p6_ancil.ghg (Iris and Git)"}}:::agentStyle
        end
    end

    %% Middle Level: Transformation Pipeline
    subgraph Activities["2. Transformation Pipeline (prov:Activity)"]
        direction TB
        A_MMR["MMR Conversion<br><i>dry air mass mixing ratio scaling (9 gases)</i>"]:::activityStyle
        A_Align["Jan 1 Realignment and Extrapolation<br><i>shift mid-year points to Jan 1 | 1850-2024 span</i>"]:::activityStyle
        A_Rose["Rose App Config Patching<br><i>serialize 175-year annual arrays into clmchfcg</i>"]:::activityStyle
        A_MMR --> A_Align --> A_Rose
    end

    %% Lower Level: Output Entities
    subgraph Outputs["3. Output Entities (prov:Entity)"]
        direction TB
        E_Rose[["Rose Application Configuration<br><code>app/um/opt/rose-app.conf (historical)</code>"]]:::outputStyle
    end

    %% Bottom Level: Model Target
    subgraph S_DEPLOY["4. Downstream Deployment"]
        E_Model[["ACCESS-ESM1.6 Configs<br><code>ACCESS-NRI/access-esm1.6-configs (historical)</code>"]]:::targetStyle
    end

    %% Relationships
    E_HI_GHG -->|prov:used| A_MMR
    A_Rose -->|prov:wasGeneratedBy| E_Rose
    E_Rose -->|Git commit and push| E_Model

    %% Agent Associations
    AgPy -.->|prov:wasAssociatedWith| A_MMR
    AgPy -.->|prov:wasAssociatedWith| A_Align
    AgPy -.->|prov:wasAssociatedWith| A_Rose
    AgCylc -.->|orchestrates| Activities

`HI_ancil_ghg`¶

1. Description & Purpose:
Reads CMIP7 historical annual global-mean surface concentrations for the 9 GHG species from 1750 to 2022, converts volume mixing ratios to mass mixing ratios, linearly interpolates values to January 1 across the model timeframe 1850–2024, and patches the &clmchfcg namelist in the historical configuration branch.

2. CLI Arguments Passed:

python -m esm1p6_ancil.ghg.cmip7_HI_ghg_generate \
    --ancil-target-dirname "${VAR.ANCIL_TARGET_PATH}" \
    # Current: "/g/data/${PROJECT}/${USER}/CMIP7/esm1p6_ancil/$(isodatetime -f CCYY.MM.DD)"
    --cmip7-source-data-dirname "${VAR.CMIP7_SOURCE_PATH}" \
    # Current: "/g/data/qv56/replicas/input4MIPs/CMIP7"
    --esm15-inputs-dirname "${VAR.ESM15_INPUTS_PATH}" \
    # Current: "/g/data/vk83/configurations/inputs/access-esm1p5"
    --dataset-version "${CMIP7_GHG_VERSION}" \
    # Current: "CR-CMIP-1-0-0"
    --dataset-vdate "${CMIP7_GHG_VDATE}" \
    # Current: "v20250228"
    --dataset-date-range "${CMIP7_GHG_DATE_RANGE}"
    # Current: "1750-2022"

3. Input4MIPs Versions & Temporal Metadata:
- Dataset Version: ${CMIP7_GHG_VERSION} (CR-CMIP-1-0-0)
- Version Date (vdate): ${CMIP7_GHG_VDATE} (v20250228)
- Input Date Range: ${CMIP7_GHG_DATE_RANGE} (1750-2022)
- Processed Model Timeline: 1850-2024 (175 annual points)
4. Input4MIPs Directory Path & Filenames:
- Directory Path: ${VAR.CMIP7_SOURCE_PATH}/CMIP/CR/${CMIP7_GHG_VERSION}/atmos/yr/{ghg}/gm/${CMIP7_GHG_VDATE}/
  (Evaluated: /g/data/qv56/replicas/input4MIPs/CMIP7/CMIP/CR/CR-CMIP-1-0-0/atmos/yr/{ghg}/gm/v20250228/)
- Filenames (9 gases): {ghg}_input4MIPs_GHGConcentrations_CMIP_${CMIP7_GHG_VERSION}_gm_${CMIP7_GHG_DATE_RANGE}.nc
5. Python Scripts & Functions:
- Main Script / Entrypoint: esm1p6_ancil.ghg.cmip7_HI_ghg_generate
- Key Functions Called: load_cmip7_ghg_series_mmr, cmip7_ghg_update_namelists_file, cmip7_ghg_namelist_str, cmip7_ghg_mmr, cmip7_scale, cmip7_pro_greg_date_constraint_from_years, read_namelists_lines_up_to, format_namelist
- Shared Libraries: iris, cftime, numpy, f90nml
6. Function-Level Cube Transformations & Constraints:
- Input Cubes & Coordinates: 1D NetCDF cubes loaded via iris.load_cube per gas species, with time coordinate defined on the Proleptic Gregorian calendar. Validates attribute assert ghg == full_cube.metadata.attributes["variable_id"].
- Constraints Applied:
  - Date range constraint: cmip7_pro_greg_date_constraint_from_years(1850, 2024) filtering points within 1850-01-01 to 2024-12-31.
  - Annual point constraint: cmip7_pro_greg_date_constraint_from_years(year, year) in extraction loop.
- Coordinate Bounds & Manipulation:
  - Mid-year values interpolated to Jan 1 (0.5 * (val[:-1] + val[1:])).
  - Backwards extrapolation for first year (beg_year_cube.data[0] = val[0] + 0.5 * (val[0] - val[1])), setting time point to January 1, 00:00:00.
  - Time bounds dropped completely (beg_year_cube_time.bounds = None, new_cube_time.bounds = None).
  - Concatenates backwards-extrapolated cube with main cube via iris.cube.CubeList.concatenate_cube() after iris.util.unify_time_units and iris.util.equalise_attributes.
- Created / Output Cubes: Produces sliced scalar year_cube instances converted via cmip7_ghg_mmr into mass mixing ratio floating point series passed directly to namelist construction.
7. Produced File Versions & Date Ranges:
None (Direct namelist generation). Temporal coverage encoded into namelist: 1850–2024 (175 annual points).
8. Produced File Directory Paths & Filenames:
None. No .anc or binary data files created.

9. Namelist File & Variable Updates:

Target File: ${GIT_HI_CONFIG_DIR}/atmosphere/namelists
Namelist Group: &clmchfcg

Variables Updated:

l_clmchfcg = .TRUE.
clim_fcg_nyears = 175, 175, 175, 175, 175, 175, 175, 175, 175, 175, 175
clim_fcg_years = 1850..2024
clim_fcg_levls = <175 rows of MMR values for 11 species>
clim_fcg_rates = -32768.0

3. ScenarioMIP Experiment (SM)¶

Dataflow Architecture¶

The ScenarioMIP GHG pipeline ingests baseline projection time series (2022–2100) alongside 22nd-century extension datasets (*-ext-*, 2101–2200) when --ext is specified, concatenates time series to 2150, realigns values to January 1, and patches scenario-specific Rose application configurations:

flowchart TD
    %% Custom Styles for W3C PROV Semantics
    classDef inputStyle fill:#e1f5fe,stroke:#0288d1,stroke-width:1.5px,color:#01579b
    classDef activityStyle fill:#e8f5e9,stroke:#2e7d32,stroke-width:1.5px,color:#1b5e20
    classDef outputStyle fill:#fff3e0,stroke:#e65100,stroke-width:1.5px,color:#bf360c
    classDef agentStyle fill:#f3e5f5,stroke:#7b1fa2,stroke-width:1.5px,color:#4a148c
    classDef targetStyle fill:#ede7f6,stroke:#4527a0,stroke-width:2px,color:#311b92

    %% Top Level: Inputs and Agents
    subgraph S_TOP["1. Source Inputs and Agents"]
        direction LR
        subgraph Inputs["Input Entities (prov:Entity)"]
            direction TB
            E_Base_GHG[("Base ScenarioMIP GHG NetCDFs<br><code>CR-SCEN-1-1-0 (2022-2100)</code>")]:::inputStyle
            E_Ext_GHG[("Extension GHG NetCDFs<br><code>CR-SCEN-ext-1-1-0 (2101-2200)</code>")]:::inputStyle
        end

        subgraph Agents["Agents (prov:Agent)"]
            direction TB
            AgCylc{{"Cylc 8 Suite Scheduler"}}:::agentStyle
            AgPy{{"esm1p6_ancil.ghg (Iris and Git)"}}:::agentStyle
        end
    end

    %% Middle Level: Transformation Pipelines
    subgraph S_ACT["2. Transformation Pipelines (prov:Activity)"]
        direction TB
        subgraph S_Ext["Extension Validation and Concatenation"]
            direction TB
            A_Concat["Concatenate Time Chunks<br><i>CubeList.concatenate_cube (2022-2200)</i>"]:::activityStyle
            A_Sub["Constrain Simulation Window<br><i>cmip7_pro_greg_date_constraint_from_years(2022, 2150)</i>"]:::activityStyle
            A_Concat --> A_Sub
        end

        subgraph S_Proc["Transformation and Namelist Generation"]
            direction TB
            A_MMR["MMR Conversion<br><i>dry air mass mixing ratio scaling (9 gases)</i>"]:::activityStyle
            A_Align["Jan 1 Realignment and Extrapolation<br><i>shift mid-year points to Jan 1 | forward extrapolate 2150</i>"]:::activityStyle
            A_Rose["Rose App Config Patching<br><i>serialize 129-year annual arrays into clmchfcg</i>"]:::activityStyle
            A_MMR --> A_Align --> A_Rose
        end

        A_Sub --> A_MMR
    end

    %% Lower Level: Output Entities
    subgraph Outputs["3. Output Entities (prov:Entity)"]
        direction TB
        E_Rose[["Rose Application Configuration<br><code>app/um/opt/rose-app.conf (scen7-SCEN)</code>"]]:::outputStyle
    end

    %% Bottom Level: Model Target
    subgraph S_DEPLOY["4. Downstream Deployment"]
        E_Model[["ACCESS-ESM1.6 Configs<br><code>ACCESS-NRI/access-esm1.6-configs (scen7-*)</code>"]]:::targetStyle
    end

    %% Relationships
    E_Base_GHG & E_Ext_GHG -->|prov:used| A_Concat
    A_Rose -->|prov:wasGeneratedBy| E_Rose
    E_Rose -->|Git commit and push| E_Model

    %% Agent Associations
    AgPy -.->|prov:wasAssociatedWith| A_Concat
    AgPy -.->|prov:wasAssociatedWith| A_Sub
    AgPy -.->|prov:wasAssociatedWith| A_MMR
    AgPy -.->|prov:wasAssociatedWith| A_Align
    AgPy -.->|prov:wasAssociatedWith| A_Rose
    AgCylc -.->|orchestrates| S_ACT

`SM_{h,hl,m,vl}_ancil_ghg`¶

Tasks generate future greenhouse gas concentration timeseries across the four ScenarioMIP pathways (h, hl, m, vl). Extension to 2150 is controlled per scenario via EXTEND_SM_GHG[SCEN].

Scenario h (High)Scenario hl (High-Low)Scenario m (Medium)Scenario vl (Very Low)

1. Description & Purpose:
Reads ScenarioMIP high-emissions (h) greenhouse gas concentrations, concatenates extension dataset chunks (2101–2200) when EXTEND_SM_GHG['h'] is active (--ext) to cover the timeline to 2150, extrapolates annual values to January 1, and patches the &clmchfcg namelist in the gen-scen7-h-<UUID> branch.

2. CLI Arguments Passed:

python -m esm1p6_ancil.ghg.cmip7_SM_ghg_generate \
    --ancil-target-dirname "${VAR.ANCIL_TARGET_PATH}" \
    # Current: "/g/data/${PROJECT}/${USER}/CMIP7/esm1p6_ancil/$(isodatetime -f CCYY.MM.DD)"
    --cmip7-source-data-dirname "${VAR.CMIP7_SOURCE_PATH}" \
    # Current: "/g/data/qv56/replicas/input4MIPs/CMIP7"
    --esm15-inputs-dirname "${VAR.ESM15_INPUTS_PATH}" \
    # Current: "/g/data/vk83/configurations/inputs/access-esm1p5"
    --dataset-version "${CMIP7_SM_GHG_VERSION[SCEN]}" \
    # Current: "CR-h-1-1-0"
    --dataset-vdate "${CMIP7_SM_GHG_VDATE[SCEN]}" \
    # Current: "v20260327"
    --dataset-date-range "${CMIP7_SM_GHG_DATE_RANGE}" \
    # Current: "2022-2100"
    --ext \
    --dataset-ext-version "${CMIP7_SM_EXT_GHG_VERSION[SCEN]}" \
    # Current: "CR-h-ext-1-1-0"
    --dataset-ext-vdate "${CMIP7_SM_EXT_GHG_VDATE[SCEN]}" \
    # Current: "v20260327"
    --dataset-ext-date-range "${CMIP7_SM_EXT_GHG_DATE_RANGE}"
    # Current: "2101-2200"

3. Input4MIPs Versions & Temporal Metadata:
- Base Dataset: ${CMIP7_SM_GHG_VERSION['h']} (CR-h-1-1-0), ${CMIP7_SM_GHG_VDATE['h']} (v20260327), Date Range: ${CMIP7_SM_GHG_DATE_RANGE} (2022-2100)
- Extension Dataset: ${CMIP7_SM_EXT_GHG_VERSION['h']} (CR-h-ext-1-1-0), ${CMIP7_SM_EXT_GHG_VDATE['h']} (v20260327), Date Range: ${CMIP7_SM_EXT_GHG_DATE_RANGE} (2101-2200)
- Model Target Range: 2022-2150 (129 annual values)
4. Input4MIPs Directory Path & Filenames:
- Base: ${VAR.CMIP7_SOURCE_PATH}/ScenarioMIP/CR/${CMIP7_SM_GHG_VERSION['h']}/atmos/yr/{ghg}/gm/${CMIP7_SM_GHG_VDATE['h']}/{ghg}_input4MIPs_GHGConcentrations_ScenarioMIP_${CMIP7_SM_GHG_VERSION['h']}_gm_${CMIP7_SM_GHG_DATE_RANGE}.nc
- Extension: ${VAR.CMIP7_SOURCE_PATH}/ScenarioMIP/CR/${CMIP7_SM_EXT_GHG_VERSION['h']}/atmos/yr/{ghg}/gm/${CMIP7_SM_EXT_GHG_VDATE['h']}/{ghg}_input4MIPs_GHGConcentrations_ScenarioMIP_${CMIP7_SM_EXT_GHG_VERSION['h']}_gm_${CMIP7_SM_EXT_GHG_DATE_RANGE}.nc
5. Python Scripts & Functions:
- Main Script / Entrypoint: esm1p6_ancil.ghg.cmip7_SM_ghg_generate
- Key Functions Called: load_cmip7_ghg_series_mmr, cmip7_ghg_update_namelists_file, cmip7_ghg_namelist_str, cmip7_ghg_mmr, cmip7_pro_greg_date_constraint_from_years, iris.cube.CubeList.concatenate_cube, iris.util.equalise_attributes, iris.util.unify_time_units
6. Function-Level Cube Transformations & Constraints:
- Input Cubes: Base scenario cube full_cube (2022–2100) and extension chunk ext_cube (2101–2200) loaded via iris.load_cube.
- Constraints Applied: Concatenation via CubeList([full_cube, ext_cube]).concatenate_cube() after attribute equalization. Date range constraint cmip7_pro_greg_date_constraint_from_years(2022, 2150) extracts the 2022–2150 timeline.
- Coordinate Bounds & Manipulation: Linear interpolation to Jan 1 (0.5 * (full[:-1] + full[1:])), final year forward extrapolation (full[-1] + 0.5 * (full[-1] - full[-2])), time bounds cleared (bounds = None), time points assigned Jan 1 of each year.
- Created / Output Cubes: Sliced annual year_cube instances converted via cmip7_ghg_mmr to MMR series for namelist injection.
7. Produced File Versions & Date Ranges:
None (Direct namelist generation). Temporal coverage: 2022–2150 (129 annual values).
8. Produced File Directory Paths & Filenames:
None.
9. Namelist File & Variable Updates:
- Target File: ${GIT_SM_h_CONFIG_DIR}/atmosphere/namelists
- Namelist Group: &clmchfcg
- Variables Updated: l_clmchfcg = .TRUE., clim_fcg_nyears = 129, clim_fcg_years = 2022..2150, clim_fcg_levls, clim_fcg_rates = -32768.0.

Dataset Versions: Base CR-hl-1-1-0 (v20260327, 2022-2100); Extension CR-hl-ext-1-1-0 (v20260327, 2101-2200).
Script & Invocation: esm1p6_ancil.ghg.cmip7_SM_ghg_generate with --dataset-version "CR-hl-1-1-0".
Target Branch & Namelist: ${GIT_SM_hl_CONFIG_DIR}/atmosphere/namelists (&clmchfcg).

Dataset Versions: Base CR-m-1-1-0 (v20260327, 2022-2100); Extension CR-m-ext-1-1-0 (v20260327, 2101-2200).
Script & Invocation: esm1p6_ancil.ghg.cmip7_SM_ghg_generate with --dataset-version "CR-m-1-1-0".
Target Branch & Namelist: ${GIT_SM_m_CONFIG_DIR}/atmosphere/namelists (&clmchfcg).

Dataset Versions: Base CR-vl-1-1-0 (v20260327, 2022-2100); Extension CR-vl-ext-1-1-0 (v20260327, 2101-2200).
Script & Invocation: esm1p6_ancil.ghg.cmip7_SM_ghg_generate with --dataset-version "CR-vl-1-1-0".
Target Branch & Namelist: ${GIT_SM_vl_CONFIG_DIR}/atmosphere/namelists (&clmchfcg).

Greenhouse Gases (GHG) Forcing Specifications¶

Physical Domain & Scientific Scope¶

Provenance & Dataflow Architecture¶

Controlling Suite Switches¶

1. Pre-Industrial Experiment (PI)¶

Dataflow Architecture¶

PI_ancil_ghg¶

2. Historical Experiment (HI)¶

Dataflow Architecture¶

HI_ancil_ghg¶

3. ScenarioMIP Experiment (SM)¶

Dataflow Architecture¶

SM_{h,hl,m,vl}_ancil_ghg¶

`PI_ancil_ghg`¶

`HI_ancil_ghg`¶

`SM_{h,hl,m,vl}_ancil_ghg`¶