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🌦️ Weather Underground Scraper

Extract high-quality weather data from Weather Underground (Wunderground) for analytics, trading models, forecasting pipelines, and automation.

If you track prediction markets, this actor is built around a clear thesis: Wunderground is the single source of truth for Polymarket weather bets.

Why this scraper

• Built for clean, structured weather datasets (one datapoint per row)
• Fast API-backed extraction discovered from Wunderground state
• Designed for production use on Apify
• Supports both short-term forecasting and historical analysis

🔍 Supported modes

Choose one mode per run for clean outputs:

• current — 📍 latest weather observation
• forecast_hourly — 🕐 hourly forecast datapoints
• forecast_daily — 📅 daily forecast datapoints
• history_hourly — 🧾 historical hourly observations
• history_daily — 📊 historical daily aggregates

🧩 Input fields

• mode (required)
• locations (e.g., Dallas, TX, Incheon, KR, RKSI:9:KR)
• urls (optional Wunderground URLs)
• historyStartDate, historyEndDate (for history modes)
• units (m metric, e imperial)
• language (default en-US)

📤 Output schema (row-based)

Common columns:

• mode
• locationQuery
• locationName
• scrapedAt
• pointType
• pointDate
• pointTime
• temperature
• condition
• humidity
• wind
• pressure
• precip

Forecast modes may include:

• precipChance

History daily mode may include:

• temperatureAvg, temperatureMin, temperatureMax
• humidityAvg, windAvg, pressureAvg
• precipTotal, samples

Example: hourly forecast

{
"mode":"forecast_hourly",
"locations":["Dallas, TX"],
"units":"m"
}

Example: historical daily range

{
"mode":"history_daily",
"locations":["Dallas, TX"],
"historyStartDate":"2026-01-01",
"historyEndDate":"2026-02-23",
"units":"m"
}

Example: Polymarket weather validation workflow

1. Select market location and date window
2. Run history_hourly or history_daily
3. Use returned rows as your settlement/verification dataset

Built for weather intelligence, market validation, and repeatable data workflows on Apify.