ENSO Tracker

Track global city temperatures and analyze El Niño/La Niña (ENSO) phenomena. Generate publication-quality charts using the Imperial Modernity color palette.

Overview

ENSO Tracker is an OpenClaw skill for:

• Tracking the hottest cities worldwide with real-time temperature data
• Showing current ENSO status (ONI index + phase classification)
• Analyzing correlation between ENSO cycles and extreme heat events
• Generating beautiful charts with the Imperial Modernity design system

Run enso_tracker.py correlate to generate an ENSO–India extreme heat correlation chart with gradient lines, danger zones, and key record annotations.

Data Sources

NOAA ONI Index

The Oceanic Niño Index (ONI) is the standard monitoring metric for ENSO, published by NOAA CPC. Data is provided as 3-month running means, organized by meteorological season.

OpenWeatherMap API

The free tier provides 1,000 calls per day — sufficient for tracking major cities worldwide. Supports current weather, forecasts, and historical data.

Berkeley Earth

Provides global and regional temperature anomaly records for long-term trend analysis.

API Key Setup

OpenWeatherMap Configuration

1. Sign up: Visit https://openweathermap.org/api and click "Sign Up"
2. Get your key: After logging in, go to "API Keys" and copy your key
3. Create config file:

mkdir -p ~/.openclaw/workspace/skills/enso-tracker
cat > ~/.openclaw/workspace/skills/enso-tracker/config.json << 'EOF'
{
  "openweather_api_key": "YOUR_API_KEY_HERE"
}
EOF

4. Replace YOUR_API_KEY_HERE with your actual API key

The config file is excluded from version control via .gitignore.

Commands

Track Hottest Cities

Fetch real-time temperatures and generate a ranking chart:

python enso_tracker.py cities --top 20 --output ~/Downloads/hottest_cities.png

Options:

• --top N — Show top N hottest cities (default: 10)
• --output — Output file path (default: ~/Downloads/city_ranking.png)
• --lang — Chart language: zh or en (default: zh)
• --rate-limit — API request interval in seconds (default: 1.0)

Show ENSO Status

Fetch current ONI index and phase classification:

python enso_tracker.py status

Sample output:

📊 Current ENSO Status
======================
ONI Index: +1.2°C
Phase: El Niño
Intensity: Moderate
Season: DJF 2023

Correlate ENSO with Extreme Heat

Generate an overlay chart of ENSO cycles and extreme heat records:

python enso_tracker.py correlate --output ~/Downloads/enso_india_heat.png

Chart features:

• Dual Y-axis: ONI index (left) and temperature (right)
• El Niño phases highlighted in red
• La Niña phases highlighted in blue
• Extreme heat event annotations

Generate Temperature Anomaly Chart

Plot regional or global temperature anomalies over time:

python enso_tracker.py anomaly --region "India" --output ~/Downloads/india_anomaly.png

Options:

• --region — Region name (e.g. "India", "Global", "Europe")
• --start-year — Start year (default: 1950)
• --end-year — End year (default: current year)

Compare Years

Compare temperature data between two years:

python enso_tracker.py compare --year1 2023 --year2 2024 --output ~/Downloads/year_comparison.png

ENSO Timeline

Generate a timeline chart of ONI values over a date range:

python enso_tracker.py timeline --start-year 2015 --output ~/Downloads/enso_timeline.png

Color Palette

The Imperial Modernity color system draws from traditional Chinese court aesthetics, fused with modern data visualization principles.

Core Colors

Gradient System

• Temperature gradient line: YlOrRd colormap, normalized to data range
• ENSO phases:
  • El Niño (ONI > +0.5): Red #BD1020
  • La Niña (ONI < −0.5): Blue #2171B5
  • Neutral: Gray #6B7280

Chart Style

• Background: Rice Paper #faf9f5
• No top/right spines
• Grid lines: light gray, semi-transparent
• CJK font support: PingFang HK, Hiragino Sans GB, STHeiti, Arial Unicode MS
• Output resolution: 180 DPI

Usage Examples

Quick Query

User: What are the hottest cities in the world right now?
→ Run: enso_tracker.py cities --top 10
→ "Current global hottest city ranking has been generated..."

ENSO Analysis

User: Is it El Niño or La Niña right now?
→ Run: enso_tracker.py status
→ "Currently in El Niño phase, ONI index at +1.2°C..."

Deep Analysis

User: Analyze the relationship between ENSO and India heat waves
→ Run: enso_tracker.py correlate
→ "Data shows extreme heat events in India increase by 23% during El Niño years..."

File Structure

enso-tracker/
├── SKILL.md              # This document
├── enso_tracker.py       # Main entry point with CLI
├── sources.py            # Data source adapters
├── viz.py                # Visualization module
└── config.json           # API key config (gitignored, user-created)

Security

• All API keys stored in config.json — never hardcoded in source
• Config file excluded from version control via .gitignore
• All network calls use HTTPS
• Berkeley Earth uses HTTP (legacy academic server) — only read-only temperature data, no sensitive information transmitted
• No personal paths hardcoded — all paths use ~/ or relative paths
• Security audit script: .security-check.sh

Dependencies

pip install pandas matplotlib numpy scipy

Note: The code uses Python standard library urllib for HTTP requests — no need to install requests.

License

This skill is part of the OpenClaw project. Data sourced from public APIs. For educational and research use.