DMAP-AI Research Version

Overview

DMAP-AI is an AI-powered drought analysis system inside ChatGPT using SPI-based scientific workflows.

Capabilities

• SPI drought index analysis (1981–2024)
• Drought event detection
• Wavelet scalogram & global spectrum
• Climate variability diagnostics
• AI interpretation

⚠️ Tool Limitations (IMPORTANT)

• Only SPI is supported (no PDSI, SPEI, or multi-index fusion)
• Data sources: NASA POWER + ERA5-Land/CDS only
• Analysis type: yearly & point-based only
• No forecasting or future prediction
• Wavelet analysis is descriptive, not predictive
• Results depend on single-location time series

🧠 Best Practice for Prompts

For best results, explicitly request that DMAP-AI run the analysis.

• Start prompts with Run, Perform, Generate, or Analyze.
• Specify the location.
• Specify the time period.
• Specify NASA POWER or ERA5-Land.
• Describe the exact output you want (events, SPI table, wavelet results, report, etc.).

📊 Ready-to-use Scientific Prompts

These prompts are designed for the DMAP-AI app. Include the phrase "Use DMAP-AI" in your request so ChatGPT knows to run the DMAP-AI analysis tools rather than answering from general knowledge.

• Use DMAP-AI to analyze drought severity events for Ames, Iowa (1981–2025) using NASA POWER data. Return the drought-event table with duration, minimum SPI, magnitude, and severity.
• Use DMAP-AI to generate the SPI table for Ames, Iowa (1981–2025) using NASA POWER data and classify each period.
• Use DMAP-AI to run a wavelet scalogram analysis for Ames, Iowa (1981–2025) using NASA POWER data and identify high-power zones.
• Use DMAP-AI to analyze drought periodicity for Ames, Iowa (1981–2025) using NASA POWER data and identify dominant drought cycles.
• Use DMAP-AI to generate a scientific drought report for Ames, Iowa (1981–2025) using NASA POWER data.

Launch