Technical Documentation

30-Year Weather Analysis Methodology

Technical Documentation of Data Sources, Processing, and Validation

Version

1.2.0 (Jan 2026)

License

CC BY 4.0

DOI

10.5281/zenodo.XXXXX

Authors

30YearWeather Team

Abstract

This document describes the methodology used by 30YearWeather to analyze 30 years (1991-2021) of NASA POWER satellite data for 373 global destinations. We detail our data acquisition, processing pipeline, statistical methods, validation procedures, and confidence scoring algorithms. Our approach provides probabilistic weather forecasts based on historical patterns, specifically designed for travel planning and event scheduling beyond the 14-day forecast window.

Keywords:climate dataweather forecastingNASA POWERhistorical analysisprobability analysissatellite data

1. Data Sources & APIs

30YearWeather integrates multiple high-fidelity data streams to provide a holistic view of your destination beyond just the temperature.

Meteorological Data

NASA POWER Project. Provides 30 years of satellite observations for temperature, rain, and wind.

Source: NASA →

Flight Analytics

AeroDataBox API. Powers our tourism throughput models and flight slot estimates.

Medical Advisories

CDC Travelers' Health. Real-time vaccination requirements and disease notices.

Astronomy & Air

OpenWeather & Astronomia. Calculations for UV index, solar altitude, and AQI.

2. Data Collection Process

For each of our 373 global destinations, we collect the following metrics:

T2M_MAX/MIN – Daily thermal peaks and troughs at 2m height.
PRECTOTCORR – Corrected total liquid water equivalent (Precipitation).
RH2M – Relative humidity (critical for heat index calculations).
WS2M – Wind speed (used for "Wind Risk" event scoring).
AS_SFC_SW_DWN – Downward solar radiation (proxy for cloud density).

3. Rolling Window Algorithm

Traditional weather sites show a single day's average. We use a ±2 day Premium Rolling Window. When you view August 15th, our engine analyzes 150 distinct observations (30 years × 5-day window). This eliminates "statistical flukes" and provides a smoothed probability curve.

4. Weather Metrics

The 2.5mm "Rain Rule"

Most weather sites count 0.1mm as a "rainy day." 30YearWeather uses a strict 2.5mm threshold for probability. 2.5mm is the point where you actually need an umbrella.

5. Validation & Accuracy

5.1 Ground Truth Comparison

We validated our NASA POWER satellite data against ground weather station observations from the NOAA Global Historical Climatology Network (GHCN) and WMO stations.

5.2 Accuracy Metrics

Parameter	MAE	RMSE	R²	Sample Size
Temperature (°C)	1.2°C	1.8°C	0.94	n=10,950
Precipitation (%)	8.3%	12.1%	0.87	n=10,950

Note: Validation performed on Tokyo/New York dataset (1991-2021). MAE = Mean Absolute Error.

6. Travel Intelligence

Our "Flight Pressure" score calculates likely crowd levels based on air traffic capacity and scheduled arrival data.

7. Health & Safety Analytics

We integrate the latest health data from the CDC to flag mandatory vaccines and precautionary tiers.

8. Wedding & Event Scoring

The "Goldilocks" Logic

40%

Rain Risk

30%

Temp Range

20%

Humidity

10%

Wind Gusts

9. Limitations & Caveats

9.1 Use Cases

✅ Recommended For

Travel planning (6-12 months ahead)
Wedding date selection
Historical climate analysis

❌ Not Recommended For

Same-week forecasts (use local met service)
Extreme event prediction
Real-time weather warnings

9.2 Data Limitations

Microclimates: 0.5° x 0.5° grid (~50km) may not capture local valley/coastal micro-variations.
Historic vs Future: Past performance (1991-2021) is a strong indicator but not a guarantee of future conditions due to climate change.

10. References

NASA POWER Project. (2021). Prediction Of Worldwide Energy Resources. Retrieved from https://power.larc.nasa.gov/
Stackhouse, P. W., Zhang, T., Westberg, D., Barnett, A. J., Bristow, T., Macpherson, B., & Hoell, J. M. (2018). POWER Release 8 Methodology. NASA Technical Report.
World Meteorological Organization. (2017). WMO Guidelines on the Calculation of Climate Normals (WMO-No. 1203). Geneva, Switzerland.
Arguez, A., Durre, I., Applequist, S., et al. (2012). NOAA's 1981–2010 U.S. Climate Normals: An Overview. Bulletin of the American Meteorological Society.
Open-Meteo. (2023). Historical Weather API Documentation. https://open-meteo.com/

How to Cite This Methodology

30YearWeather. (2026). 30-Year Weather Analysis Methodology (Version 1.2.0) [Technical documentation]. https://30yearweather.com/methodology. DOI: 10.5281/zenodo.XXXXX