geo-infer-climate

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.

10 stars

byActiveInferenceInstitute

View on GitHub Installation ↓

Best use case

geo-infer-climate is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Teams using geo-infer-climate should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/GEO-INFER-CLIMATE/SKILL.md --create-dirs "https://raw.githubusercontent.com/ActiveInferenceInstitute/GEO-INFER/main/GEO-INFER-CLIMATE/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/GEO-INFER-CLIMATE/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How geo-infer-climate Compares

Feature / Agent	geo-infer-climate	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

```python
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

```python
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`

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