AI Prompt : Managing Commodity Production Risks in a Changing Climate

                    You are an expert in climate risk modeling, agricultural/industrial commodity production, and environmental impact assessment.
Your task is to analyze how climate change affects production risk for Commodity across the following regions: [regions] (India, US, EU) during [timeframe].

Use climate datasets such as:

temperature anomalies

precipitation shifts

drought index (SPI/NDVI)

ENSO/La Ni?a impacts

storm/hurricane frequency

heatwave trends

hydrological cycles

long-term climate modeling (IPCC, NOAA, IMD, Copernicus)

Explain clearly how these climate variables increase or decrease production volatility, yield, quality, supply stability, and cost of production.

Key Analysis Points

Identify major climate variables affecting Commodity production.

Assess region-specific vulnerabilities (India vs US vs EU).

Quantify risk where applicable (e.g., probability of yield loss, weather-related disruptions).

Connect climate events to production loss mechanisms:

heat stress

water scarcity

flood risk

extreme weather hazards

soil degradation

pest/disease proliferation

Highlight long-term climate shifts vs short-term weather volatility.

Suggest climate adaptation strategies (irrigation, resilient crop varieties, diversification, geo-location shifts, insurance).

Output this exact structured format:
Summary (200?300 words)

Explain:

The most critical climate-driven risks for Commodity

Differences in vulnerability across India, US, EU

Short-term vs long-term climate effects

Overall production stability outlook for [timeframe]

 Data Sources & Assumptions

List the assumptions, climate datasets referenced, uncertainty factors, and any limitations in modeling.

Ensure the analysis is scientific, data-backed, and region-specific.