| name | geo-infer-climate |
| description | Climate modeling and environmental analysis. Use when analyzing climate data, projecting future climate scenarios (RCP/SSP), computing climate indices (SPI, PDSI), performing statistical downscaling, or assessing climate change impacts on geographic regions. |
| prerequisites | {"required":["geo-infer-space","geo-infer-time"],"recommended":["geo-infer-bayes","geo-infer-data"]} |
| difficulty | intermediate |
| estimated_time | 45min |
| examples_dir | ../GEO-INFER-EXAMPLES/examples/ |
GEO-INFER-CLIMATE
Instructions
Core Capabilities
- Climate projections: RCP/SSP scenario modeling with ensemble methods
- Climate indices: SPI, PDSI, heat wave indices, frost days, growing degree days
- Downscaling: Statistical (bias correction, delta method) and dynamical downscaling
- Impact assessment: Sector-specific climate vulnerability and adaptation planning
- Data integration: CMIP6, ERA5, observational station networks, gridded datasets
Key Imports
from geo_infer_climate.core.projections import ClimateProjection
from geo_infer_climate.core.indices import ClimateIndexCalculator
from geo_infer_climate.core.downscaling import StatisticalDownscaler
from geo_infer_climate.core.impact import ImpactAssessment
Examples
from geo_infer_climate.core.indices import ClimateIndexCalculator
calculator = ClimateIndexCalculator()
spi = calculator.compute_spi(precipitation_series, scale=3)
pdsi = calculator.compute_pdsi(precip, temp, latitude)
Guidelines
Integrations
- Integrates with WATER for hydrological climate impacts
- Integrates with AG for agricultural climate adaptation
- Integrates with ENERGY for renewable resource projections
- Test:
uv run python -m pytest GEO-INFER-CLIMATE/tests/ -v
