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# Spatial Analogs
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Spatial analog analysis for identifying regions with similar climate characteristics. Useful for climate adaptation, impact assessment, and identifying climate refugia or risk areas.
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## Capabilities
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### Spatial Analog Computation
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Methods for finding spatial analogs based on climate similarity metrics.
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```python { .api }
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def spatial_analogs(reference, candidates, method="kldiv", **kwargs):
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    """
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    Find spatial analogs using climate similarity metrics.
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    Parameters:
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    - reference: xr.Dataset, reference climate data
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    - candidates: xr.Dataset, candidate regions for analog search
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    - method: str, similarity metric ("kldiv", "euclidean", "mahalanobis")
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    - **kwargs: method-specific parameters
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    Returns:
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    xr.Dataset: Spatial analog results with similarity scores
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    """
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```
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## Usage Examples
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```python
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import xarray as xr
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import xclim.analog as xca
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# Load reference and candidate climate data
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reference = xr.open_dataset("reference_region.nc")
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candidates = xr.open_dataset("global_climate.nc")
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# Find spatial analogs
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analogs = xca.spatial_analogs(
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    reference, 
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    candidates, 
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    method="kldiv"
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)
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```