tessl/pypi-xclim
Climate indices computation package based on Xarray with extensive climate analysis capabilities
ensemble-analysis.mddocs/
Ensemble Analysis
Multi-model climate ensemble processing and analysis tools for climate projection assessment and uncertainty quantification. Essential for climate change impact studies and decision-making under uncertainty.
Capabilities
Ensemble Creation and Management
Tools for creating and managing climate model ensembles.
def create_ensemble(datasets, multiindex=True, resample_freq=None, **kwargs):
"""
Create ensemble dataset from multiple climate model datasets.
Parameters:
- datasets: list or dict, climate model datasets to combine
- multiindex: bool, use multiindex for ensemble dimensions
- resample_freq: str, optional resampling frequency
- **kwargs: additional ensemble creation parameters
Returns:
xr.Dataset: Combined ensemble dataset
"""
def ensemble_mean_std_max_min(ens, weights=None, **kwargs):
"""
Calculate ensemble statistics (mean, std, max, min).
Parameters:
- ens: xr.Dataset, ensemble dataset
- weights: xr.DataArray, optional weights for ensemble members
- **kwargs: additional statistical parameters
Returns:
xr.Dataset: Ensemble statistics
"""
def ensemble_percentiles(ens, values=[10, 25, 50, 75, 90], weights=None, **kwargs):
"""
Calculate ensemble percentiles.
Parameters:
- ens: xr.Dataset, ensemble dataset
- values: list, percentile values to calculate (0-100)
- weights: xr.DataArray, optional weights for members
- **kwargs: additional parameters
Returns:
xr.Dataset: Ensemble percentiles
"""Ensemble Agreement and Robustness
Methods for assessing ensemble agreement and robustness of climate projections.
def robustness_fractions(ens, test="threshold", **kwargs):
"""
Calculate robustness fractions for ensemble agreement.
Parameters:
- ens: xr.Dataset, ensemble dataset
- test: str, robustness test ("threshold", "sign", "range")
- **kwargs: test-specific parameters
Returns:
xr.Dataset: Robustness fraction statistics
"""
def change_significance(ens, baseline_period, projection_period, **kwargs):
"""
Test significance of projected changes across ensemble.
Parameters:
- ens: xr.Dataset, ensemble dataset
- baseline_period: slice, baseline time period
- projection_period: slice, projection time period
- **kwargs: significance test parameters
Returns:
xr.Dataset: Change significance statistics
"""Usage Examples
import xarray as xr
import xclim.ensembles as xce
# Load multiple model datasets
models = [
xr.open_dataset(f"model_{i}.nc") for i in range(1, 11)
]
# Create ensemble
ensemble = xce.create_ensemble(models, multiindex=True)
# Calculate ensemble statistics
ens_stats = xce.ensemble_mean_std_max_min(ensemble)
ens_percentiles = xce.ensemble_percentiles(ensemble, values=[10, 50, 90])
# Assess robustness
robustness = xce.robustness_fractions(ensemble, test="threshold")