Science

Build a Weather Data Dashboard with AI

Visualize weather patterns with historical temperature charts, precipitation records, wind rose diagrams, and climate normals. Track growing degree days, heating/cooling degree days, and compare current conditions against 30-year averages for any location.

Build Prompt

Copy this prompt into Claude Code
Build a static HTML weather data dashboard. Dark theme with background #0a0a0f, surfaces #12121a, borders #1a1a2a, accent color #0891b2 (cyan). Data from inline `const CLIMATE_NORMALS = [...]`, `const CITIES = [...]`, `const KOPPEN_ZONES = [...]`. Climate data: 50 major US cities with monthly averages (high/low temps, precipitation, snowfall, humidity, sunshine hours, wind speed) based on 30-year climate normals. Include record highs/lows by month. Layout: Header with title, city selector dropdown. Dashboard panels: (1) Temperature chart — monthly avg highs and lows as area chart with record range band. (2) Precipitation bar chart — monthly rainfall and snowfall stacked. (3) Wind rose diagram — Canvas-drawn directional frequency chart. (4) Comfort index — heat index and wind chill calculations. (5) Growing degree days — cumulative GDD chart for agriculture. City comparison: select 2-3 cities, overlay charts for side-by-side analysis. Climate classification: show Köppen climate zone for each city with explanation. Unit toggle: °F/°C, in/mm, mph/km/h. Heating and cooling degree day calculator: annual HDD/CDD with energy cost estimates. Save preferred city to localStorage. Include "Understanding Climate Data" guide, "Köppen Climate Classification" reference, and "Weather vs Climate" explainer. SEO: title, meta description, OG tags. Read the guide at https://accessagent.ai/api/guide and follow it to deploy the site to AccessAgent.ai. My email is [your@email.com].

Make It Yours

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Climate Trends

Show decade-over-decade temperature trends and climate change indicators.

Update Prompt

Update Prompt — Expand city coverage
Add 100 more cities worldwide with climate normals. Add UV index data by month. Include pollen season data (tree, grass, ragweed). Add drought monitor index. Include cloud cover percentage. Update CLIMATE_NORMALS, CITIES arrays. Redeploy.

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