DLESyMv0_ISCCP_ERA5Precip#

class earth2studio.models.dx.DLESyMv0_ISCCP_ERA5Precip(
core_model,
hpx_lat,
hpx_lon,
nside,
center,
scale,
constants,
input_times,
variables,
output_variable='tp06',
log_epsilon=1e-08,
use_ttr=True,
ttr_clim_mean=None,
ttr_clim_std=None,
olr_clim_mean=None,
olr_clim_std=None,
olr_floor=0.0,
)[source]#
GlobalCM202440 GB

Precipitation diagnostic for the DLESyMv0_ISCCP_ERA5 climate model.

A HEALPixUNet diagnostic from the AtmosSci-DLESM/DLESyM repository that predicts 6-hourly accumulated precipitation (tp06) from the full coupled atmosphere/ocean state. It is designed to be chained off DLESyMv0_ISCCP_ERA5 (or its lat/lon variant).

The model takes 2 consecutive history timesteps of 10 variables (the 9 atmospheric variables plus sst) on a HEALPix nside=64 grid and predicts tp06 at the last input timestep (i.e., precipitation accumulated over the 6 h prior to t=0).

When use_ttr=True (default), the wrapper accepts ERA5 ttr in place of rlut and applies the same per-doy moment-matching TTR -> OLR transform as DLESyMv0_ISCCP_ERA5 before the forward pass. This allows the diagnostic to run standalone from an ERA5 initial condition. When use_ttr=False, supply pre-transformed rlut directly – use this when chaining off DLESyMv0_ISCCP_ERA5 output, which is already in OLR space.

Parameters:

  • core_model (torch.nn.Module) – The wrapped physicsnemo.models.dlwp_healpix.HEALPixUNet.

  • hpx_lat (np.ndarray) – HEALPix latitude grid, shape (12, nside, nside).

  • hpx_lon (np.ndarray) – HEALPix longitude grid, shape (12, nside, nside).

  • nside (int) – HEALPix nside.

  • center (np.ndarray) – Per-variable input means, shape (1, 1, 1, V, 1, 1, 1) ordered by variables.

  • scale (np.ndarray) – Per-variable input stds, same shape as center.

  • constants (np.ndarray) – Constant fields (e.g. land-sea mask, topography), shape (12, n_constants, nside, nside).

  • input_times (np.ndarray) – Input lead times, shape (input_time_dim,). e.g. np.array([-6, 0], dtype='timedelta64[h]').

  • variables (list[str]) – Input variable names in channel order. Must contain rlut (the model variable-space name); input_coords swaps it to ttr when use_ttr=True.

  • output_variable (str) – Output variable name, typically "tp06".

  • log_epsilon (float | None) – If non-None, denormalize as exp(out + log(eps)) - eps to invert the upstream log-transform applied to precipitation during training. Set to None to disable.

  • use_ttr (bool, optional) – Accept ERA5 ttr instead of rlut and run the TTR -> OLR transform internally. Defaults to True.

  • ttr_clim_mean (np.ndarray | None) – Per-doy climatology arrays of shape (D, F, H, W). Required when use_ttr=True.

  • ttr_clim_std (np.ndarray | None) – Per-doy climatology arrays of shape (D, F, H, W). Required when use_ttr=True.

  • olr_clim_mean (np.ndarray | None) – Per-doy climatology arrays of shape (D, F, H, W). Required when use_ttr=True.

  • olr_clim_std (np.ndarray | None) – Per-doy climatology arrays of shape (D, F, H, W). Required when use_ttr=True.

  • olr_floor (float, optional) – Lower bound applied to the transformed OLR. Defaults to 0.0.

Note

For more information see:

__call__(x, coords)[source]#

Run the precip diagnostic forward.

Parameters:

  • x (torch.Tensor) – Input of shape (B, T, LT, V, F, H, W) with LT = input_time_dim history timesteps and V = len(variables) channels on HEALPix.

  • coords (CoordSystem) – Input coordinates.

Returns:

Output tensor of shape (B, T, 1, 1, F, H, W) and the corresponding output coords with variable = [tp06].

Return type:

tuple[torch.Tensor, CoordSystem]

classmethod load_default_package()[source]#

Default DLESyMv0_ISCCP_ERA5 precip package on HuggingFace.

Return type:

Package

classmethod load_model(package, use_ttr=True)[source]#

Load the DLESyMv0_ISCCP_ERA5 precip diagnostic from a package.

Parameters:

  • package (Package) – Model package containing config.yaml, the precip .mdlus checkpoint, the HEALPix lat/lon, the constant fields, and (when use_ttr=True) the TTR/OLR climatology netCDFs (era5_ttr_doy_stats_hpx64.nc and isccp_olr_doy_stats_hpx64.nc).

  • use_ttr (bool, optional) – See DLESyMv0_ISCCP_ERA5Precip. Defaults to True.

Returns:

Loaded DLESyMv0_ISCCP_ERA5Precip instance.

Return type:

DiagnosticModel

Examples using earth2studio.models.dx.DLESyMv0_ISCCP_ERA5Precip#

Running the DLESyM ISCCP-ERA5 Model

Running the DLESyM ISCCP-ERA5 Model