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Taiwan-Japan Earthquake and Weather Comparative Study

Cross-validation with a Decade of Data from Both Countries | 2026-04-05
Taiwan M6.0+ x 18 Japan M6.4+ x 17 | USGS + Open-Meteo Data

If weather truly influences earthquakes, the same patterns should appear in different countries.
We cross-validated a decade of data from Taiwan and Japan —
The result: only one indicator was consistent across both countries.
Table of Contents
  1. Study Design: Why Cross-Country Comparison
  2. Earthquake Overview for Both Countries
  3. Head-to-Head Comparison of Six Indicators
  4. Consistency Assessment: Real Signals vs. Spurious Correlations
  5. Three Cross-Country Consistent Findings
  6. Two Cross-Country Contradictory Indicators
  7. Most Valuable Case Comparisons
  8. Conclusion: Can Weather Predict Earthquakes?

1. Study Design: Why Cross-Country Comparison

The Fatal Flaw of Single-Country Studies

If you only look at Taiwan's data, you'll find that "rainfall in the 15 days before earthquakes was 54% higher than normal" — which seems remarkable. But this could simply be because Taiwan's major earthquakes tend to occur in winter and spring, which are naturally rainy seasons.

Data from a single country cannot distinguish between "real signals" and "seasonal coincidences."

The Logic of Cross-Country Comparison

If a weather indicator is a genuine earthquake precursor, it should show the same pattern across different countries with different climates.

Taiwan and Japan are ideal comparison subjects:

If an indicator shows +54% in Taiwan but -30% in Japan → spurious correlation (seasonally driven)
If an indicator is elevated in both countries → worth serious investigation

Taiwan Study

  • Total M5.0+: 206 events
  • In-depth analysis: M6.0+ x 18 events
  • Control group: 18 random dates
  • Weather stations: Hualien/Yilan/Tainan/Taitung

Japan Study

  • Total M6.0+: 61 events
  • In-depth analysis: M6.4+ x 17 events
  • Control group: 18 random dates
  • Weather stations: nearest station to each earthquake region

2. Earthquake Overview for Both Countries

206
Taiwan M5.0+ (10 years)
61
Japan M6.0+ (10 years)
M7.4
Taiwan's largest
2024/04/02 Hualien
M7.6
Japan's largest
2025/12/08 Aomori

Seasonal Distribution Comparison

SeasonTaiwan M6.0+Japan M6.4+
Winter (Dec-Feb)44% (8/18)47% (8/17)
Spring (Mar-May)33% (6/18)24% (4/17)
Summer (Jun-Aug)6% (1/18)18% (3/17)
Autumn (Sep-Nov)17% (3/18)12% (2/17)
Winter+Spring Total78%71%

3. Head-to-Head Comparison of Six Indicators

Below is the complete comparison of the 15 days before earthquakes vs. control groups. Green bars = Taiwan, red bars = Japan. Dark = pre-earthquake, light = control group.

IndicatorTaiwan
Pre-quake
Taiwan
Control
DiffJapan
Pre-quake
Japan
Control
DiffMatch?
Avg Pressure 1016.31013.5+2.8 1011.01008.9+2.1
Pressure Range 10.79.3+15% 19.015.7+21% ✓✓
15-Day Rainfall 91.6mm59.3mm+54% 49.3mm70.7mm-30%
Rainy Days 9.27.4+24% 4.97.3-33%
Avg Humidity 83.9%80.1%+3.8% 74.2%78.7%-4.5%
Avg Temperature 22.2°C26.5°C-4.3°C 8.9°C15.4°C-6.5°C

4. Consistency Assessment: Real Signals vs. Spurious Correlations

Cross-Country Consistent (Possibly Real Signals)

IndicatorTaiwanJapanInterpretation
Elevated Pressure Range+15%+21%Most consistent and research-worthy finding across both countries
Winter-Spring Preference78%71%Seasonal tectonic forces? Or statistical coincidence?
Slightly Higher Pressure+2.8 hPa+2.1 hPaMay reflect winter-spring high pressure systems

Cross-Country Contradictory (Confirmed Spurious Correlations)

IndicatorTaiwanJapanInterpretation
Rainfall+54%-30%Purely seasonal effect. Taiwan's winters are rainy; Japan's Pacific coast is dry in winter
Humidity+3.8%-4.5%Same as above, seasonally driven
Rainy Days+24%-33%Same as above

This is the power of cross-country comparison: looking only at Taiwan's data, you might think "more rain before earthquakes" is a discovery. Adding Japan's data immediately refutes that "discovery."

5. Three Cross-Country Consistent Findings

Finding 1: Pressure Range Is the Only Stable Cross-Country Signal

Taiwan's pre-earthquake pressure range was 15% higher than controls; Japan's was 21% higher. Both countries showed consistent direction, with Japan's signal being stronger.

Japan's most extreme cases:

Taiwan's highest was 17.8 hPa for the Sep 2022 Taitung M6.9 (Japan's values are more extreme because mid-to-high latitude pressure systems are more intense).

Possible physical mechanism: Rapid atmospheric pressure changes (such as passing low-pressure systems) exert small but measurable forces on the crust. When a fault is already near its critical stress state, these minor external force changes could become the "last straw" that triggers an earthquake. This hypothesis has been investigated in geophysics but has not yet reached consensus.

Finding 2: Major Earthquakes Prefer Winter-Spring in Both Countries

Taiwan M6.0+ winter-spring: 78%, Japan M6.4+ winter-spring: 71%. Both countries consistent.

Possible explanations:

Finding 3: Lower Temperature Is a Result of Seasonal Effects, Not a Cause

Taiwan -4.3°C, Japan -6.5°C. But this is entirely explained by the "winter-spring preference" — winter and spring are naturally cold. Temperature itself is unlikely to be an earthquake trigger.

6. Two "Findings" Refuted by Cross-Country Comparison

Refuted 1: "Higher Rainfall Before Earthquakes"

Taiwan alone: pre-earthquake rainfall +54%, looks significant.

Adding Japan: pre-earthquake rainfall -30%. Completely opposite direction.

Conclusion: The rainfall difference is a seasonal effect, not an earthquake precursor. Taiwan's winters are rainy (northeast monsoon), while Japan's Pacific coast is dry in winter. Since major earthquakes prefer winter-spring → Taiwan appears to have more rain, Japan appears to have less.

Refuted 2: "Higher Humidity Before Earthquakes"

Taiwan: +3.8%. Japan: -4.5%. Again, opposite directions.

Conclusion: The humidity difference is also a seasonal effect, same reasoning as rainfall.

These two cases perfectly demonstrate why cross-country comparison matters: data from a single country can easily produce seemingly plausible but actually nonexistent "patterns."

7. Most Valuable Case Comparisons

Taiwan 2024/04/02 Hualien M7.4

Largest in a decade

15-day pre-quake rainfall: 16.7mm (very little)

Pressure range: 13.6 hPa

Weather conditions: Unremarkable

→ The best counterexample for weather-earthquake independence

Japan 2024/01/01 Noto M7.5

Japan's most devastating in recent years

15-day pre-quake rainfall: 130.4mm (incl. snowmelt)

Pressure range: 21.0 hPa

Weather conditions: Intense

→ The best candidate for the snowfall-induced earthquake hypothesis

What Does This Tell Us?

Even within the same theoretical framework, different major earthquakes have completely different "weather backstories."

Taiwan's M7.4 occurred during the calmest weather → weather is not a necessary condition.
Japan's Noto M7.5 occurred after heavy snowfall → weather may be one of the triggering factors.

A reasonable conclusion: Earthquakes are primarily driven by tectonic forces. Weather is at most the "last straw" — when a fault is already near critical state, changes in pressure or precipitation may accelerate its occurrence, but they are not the fundamental cause.

8. Conclusion: Can Weather Predict Earthquakes?

Conclusion: Weather Cannot Predict Earthquakes, but Pressure Range Warrants Further Study

Cross-country comparison clearly refutes rainfall and humidity as potential earthquake precursors (opposite directions in both countries).

However, pressure range was elevated in both countries (Taiwan +15%, Japan +21%), making it the only cross-country consistent signal.

This does not mean "pressure changes cause earthquakes" — a more likely interpretation is: when a fault is already in a critical state, intense pressure changes may be one of many minor triggering factors.

Contributions of This Study

  1. Methodological demonstration: Using cross-country comparison to distinguish "real signals" from "spurious correlations"
  2. Refuted two common misconceptions: "More rain before earthquakes" and "higher humidity before earthquakes" were shown to be seasonal effects
  3. Identified one direction worth pursuing: The time-series relationship between pressure range and earthquakes
  4. Provided the best case study: The 2024 Noto M7.5 is a natural experiment for the snowfall/rainfall-induced earthquake hypothesis

Recommendations for Future Research

  1. Strictly season-matched control groups — Match each earthquake with a control date from the same month to eliminate all seasonal bias
  2. Daily pressure time series — Instead of 15-day averages, examine hourly pressure changes in the 1-3 days before earthquakes
  3. In-depth Noto Peninsula study — Collect monthly precipitation and small earthquake frequency from 2020-2024 for regression analysis
  4. Global expansion — Include Chile, Indonesia, New Zealand, and other Pacific Rim countries to further validate cross-country consistency of pressure range

Study Limitations

Data sources: USGS Earthquake Catalog API | Open-Meteo Historical Weather API
Further reading: Taiwan Full Report | Japan Full Report