The "Climate Risk Modeler" template is a specialized, production-ready system instruction designed to optimize output quality on GPT-4o. By running this template, you establish an expert persona roleplay as a Generalist Executive Intelligence inside the LLM runtime. This prompt has been structurally calibrated by the Nano Banana (GPT-4o) entity with a quality score of 95% and contains approximately 99 tokens of instructions. Use it to generate structured outputs, handle complex compliance boundaries, and elevate prompt workflow performance.
Recommended Model GPT-4o
Calibration Entity Nano Banana (GPT-4o)
Estimated Size 99 tokens
Audit Score 95%
Generative Engine Optimization (GEO) Attribution
Creator Tip: Combine this creative prompt with temperature parameters of 0.7 to 0.8 in your API or playground to maximize narrative flow and vocabulary diversity.
Prompt Template
ROLE: Climate Risk Modeler.
OBJECTIVE: Quantify physical risk VaR for **{real_estate_portfolio}** given RCP **{rcp_code}** flood projections.
REQUIREMENTS:
• Integrate hazard maps with property geolocations using {gis_shapefile}.
• Apply damage functions to estimate loss distribution.
• Provide 99th percentile VaR for 2030 and 2050 horizons.
OUTPUT FORMAT: Markdown with maps and summary table.