Score Methodology
How TripTimi calculates a 0–100 score for every city-month combination — the data sources, the weighting model, and the tier thresholds.
Score formula
The TripTimi Score is a weighted sum of five component scores, each normalised to 0–100:
Score =
temperature_comfort × 0.30
+ precipitation × 0.30
+ sunshine × 0.20
+ crowd_level × 0.10
+ price_level × 0.10
Component details
Temperature comfort (30%)
Scores daytime and night-time averages against an optimal curve for walking-heavy city travel. Peak comfort at 22°C day / 14°C night. Both extremes (below 0°C and above 35°C) are penalised non-linearly. Day temperature counts for 75% of the component, night for 25%.
Source: Open-Meteo historical monthly averages
Precipitation (30%)
Combines rainy-day frequency (65% weight) and total monthly rainfall in mm (35% weight). Rainy-day count matters more than total volume because a single heavy storm affects city travel less than 15 drizzly days. Threshold: 10+ rainy days or 130+ mm triggers significant penalties.
Source: Open-Meteo historical monthly averages
Sunshine hours (20%)
Daily average sunshine hours. Scoring curve: 0h = 0, rising linearly to 100 at 12h+. Sunshine affects mood, outdoor photography light, and the practical usability of parks and viewpoints.
Source: Open-Meteo historical monthly averages
Crowd level (10%)
A seasonal demand model built from European tourism seasonality by month, scaled by city population (larger cities attract proportionally more tourists year-round). Output: low / medium / high, mapped to fixed scores (low = 92, medium = 74, high = 52).
Source: Seasonal demand model + city population data
Price level (10%)
Relative seasonal price index — whether a given month sits above or below the city's own annual average for mid-range accommodation. Built from the same seasonal demand model. Output: low / medium / high, mapped to fixed scores (low = 92, medium = 74, high = 56).
Source: Seasonal demand model
Score tiers
| Score | Label | Interpretation |
|---|---|---|
| 80–100 | Excellent | Strong weather, manageable crowds, reasonable prices. Easy to recommend broadly. |
| 68–79 | Very Good | Good conditions with minor trade-offs — typically one factor below ideal. |
| 55–67 | Solid | Worth visiting with realistic expectations. Usually a weather or crowd compromise. |
| 45–54 | Mixed | Noticeable trade-offs. Still suits specific traveller types (budget, indoor-focused). |
| < 45 | Only if the timing fits | Significant limitations. Works only for very specific trip profiles. |
Limitations
- Climate data is historical averages — any given year will differ due to weather variability.
- Crowd and price models are heuristic, not live market data. Actual prices vary with booking lead time and specific accommodation type.
- The score is calibrated for walking-heavy city trips. It does not account for skiing, beach holidays, or festival-specific travel.
- Cities with fewer data years in the Open-Meteo record may have less reliable averages.