SGAM

satterc.pipeline.models.sgam

disturbances_daily

disturbances_daily(
    temperature_celcius_daily: DataArray,
    gpp_daily: DataArray,
    lai_daily: DataArray,
    plant_type: DataArray,
    latitude: DataArray,
) -> DataArray

Calculate daily disturbance events.

Parameters:

temperature_celcius_daily (DataArray) –

Daily air temperature (degrees Celsius).
gpp_daily (DataArray) –

Daily gross primary productivity (gC/m²).
lai_daily (DataArray) –

Daily leaf area index.
plant_type (DataArray) –

Plant functional type.
latitude (DataArray) –

Latitude.

Returns:

DataArray –

Daily disturbance indicators.

disturbances_weekly

disturbances_weekly(disturbances_daily: DataArray) -> DataArray

Aggregate daily disturbances to weekly maximum.

Parameters:

disturbances_daily (DataArray) –

Daily disturbance indicators.

Returns:

DataArray –

Weekly maximum disturbance indicators.

leaf_area_index_weekly

leaf_area_index_weekly(leaf_pool_weekly: DataArray, pft_params: Dataset) -> DataArray

Compute leaf area index from leaf carbon pool.

Parameters:

leaf_pool_weekly (DataArray) –

Weekly leaf pool size (gC). Shape: (time, pixel).
pft_params (Dataset) –

PFT parameters for each pixel. Contains leaf_carbon_area.

Returns:

DataArray –

Weekly leaf area index. Shape: (time, pixel).

pft_params

pft_params(plant_type: DataArray) -> Dataset

Get PFT parameters for each pixel based on plant_type.

Parameters:

plant_type (DataArray) –

Plant functional type as integer (0=tree, 1=grass, 2=shrub, 3=crop). Dims: ["pixel"].

Returns:

Dataset –

Dataset with dimension (pixel) containing PFT parameters for each pixel.

sgam

sgam(
    plant_type: DataArray,
    pft_params: Dataset,
    temperature_celcius_weekly: DataArray,
    gpp_weekly: DataArray,
    soil_moisture_weekly: DataArray,
    vpd_pa_weekly: DataArray,
    lue_weekly: DataArray,
    iwue_weekly: DataArray,
    disturbances_weekly: DataArray,
    dates_weekly: Index,
    leaf_pool_init: DataArray,
    stem_pool_init: DataArray,
    root_pool_init: DataArray,
) -> dict[str, DataArray]

Run the Storage Gap Model (SGAM) vegetation model.

Parameters:

plant_type (DataArray) –

Plant functional type as integer (0=tree, 1=grass, 2=shrub, 3=crop).
pft_params (Dataset) –

PFT parameters for each pixel. Output of pft_params node.
temperature_celcius_weekly (DataArray) –

Weekly air temperature (degrees Celsius).
gpp_weekly (DataArray) –

Weekly gross primary productivity (gC/m²).
soil_moisture_weekly (DataArray) –

Weekly soil moisture (mm).
vpd_pa_weekly (DataArray) –

Weekly vapor pressure deficit (Pa).
lue_weekly (DataArray) –

Weekly light use efficiency (gC/MJ).
iwue_weekly (DataArray) –

Weekly intrinsic water use efficiency (Pa).
disturbances_weekly (DataArray) –

Weekly disturbance indicators.
dates_weekly (Index) –

Weekly datetime index.
leaf_pool_init (DataArray) –

Initial leaf pool size.
stem_pool_init (DataArray) –

Initial stem pool size.
root_pool_init (DataArray) –

Initial root pool size.

Returns:

dict[str, DataArray] –

Dictionary containing vegetation pool sizes and fluxes.