About WeatherLens

Our Mission

WeatherLens was built with a simple goal: make travel weather planning free and accessible to everyone.

Planning a trip shouldn't require hours of research across scattered weather sites, travel blogs, and forum threads. Most existing weather resources either focus on hyper-local forecasts (helpful if you are already at your destination, not so helpful if you are deciding where to go) or provide only basic averages without the context needed to compare destinations meaningfully.

WeatherLens addresses this gap by bringing together decades of climate data into one clear, visual comparison tool. You can see at a glance whether Bali or Bangkok is the better bet in August, whether Paris or Rome has more sunshine in October, or whether the shoulder season in Lisbon is warm enough for your trip. All of the core data — temperature, rainfall, sunshine, humidity, and comfort scores — is free and available without sign-up or registration.

We believe that good weather data should be free, easy to understand, and available to every traveler — whether you are planning a honeymoon, a backpacking trip, a family holiday, or a business trip. Weather is one of the biggest factors in trip enjoyment, and it should not be an afterthought.

Our Data Sources

WeatherLens aggregates weather data from multiple trusted meteorological sources to provide the most comprehensive picture possible. We do not generate original weather measurements — instead, we curate, process, and present data from established scientific agencies in a format optimized for travel planning decisions.

OpenWeatherMap

Current weather conditions are retrieved via the OpenWeatherMap API, updated every 3 hours for all listed destinations. This powers the temperature badges on destination cards, the live weather comparison mode (for cities not in our database), and the temperature-sorted "Explore Destinations" grid. OpenWeatherMap aggregates data from over 40,000 weather stations and uses satellite data and meteorological models to provide global coverage.

NOAA Global Historical Climatology Network (GHCN)

The NOAA GHCN dataset provides long-term historical weather station data used to calculate monthly climate averages for temperature, rainfall, and humidity across our destination database. GHCN is maintained by the National Centers for Environmental Information (NCEI) and includes data from over 100,000 stations in 180 countries and territories, with some records extending back more than 175 years. We use the 1991 to 2020 period to compute climate normals.

ERA5 / Copernicus Climate Change Service

The ERA5 reanalysis dataset from the Copernicus Climate Change Service supplements station data with satellite-derived climate records. ERA5 provides global hourly estimates of atmospheric and surface variables on a 30km grid, ensuring coverage for destinations where ground-level weather stations are sparse or where historical records have gaps. This is particularly valuable for island destinations, remote tropical locations, and regions with limited ground-station infrastructure.

How We Combine Data

For each destination in our database, we start with the nearest reliable GHCN station data and cross-reference it with the corresponding ERA5 grid cell. When station data and ERA5 agree within expected margins, we use the station data (which is typically more precise at the local level). When discrepancies arise — often due to altitude differences between the station and the city center, or station relocations — we apply corrections using the ERA5 data as a reference baseline. This hybrid approach gives us both the precision of ground-level observations and the consistency of reanalysis data.

Our Methodology

30-Year Climate Normals

Monthly averages on WeatherLens are calculated using 30-year climate normals (1991–2020), the standard reference period recommended by the World Meteorological Organization (WMO). This period is long enough to smooth out year-to-year variability while remaining recent enough to reflect current climate conditions, including the warming trends observed over recent decades.

The 30-year period is a deliberate choice. Shorter averaging periods (10 or 15 years) would be more sensitive to recent trends but also more volatile and susceptible to outlier years. Longer periods would include climate conditions from an era that is no longer representative of what travelers will actually experience. The 1991 to 2020 window strikes a balance between stability and relevance.

Travel Comfort Scoring Algorithm

Our travel comfort score (0–100) combines four weather metrics into a single, easy-to-understand number that reflects how pleasant a destination's weather is for general tourism activities. The algorithm uses the following weights and approach:

Temperature comfort (40% weight): Scores highest when daily highs are in the 20–28°C (68–82°F) range, based on thermal comfort research that consistently identifies this window as optimal for outdoor activity. Scores taper off symmetrically for extremes in either direction, reaching near-zero at sub-freezing temperatures and above 42°C.
Rainfall probability (25% weight): Fewer rainy days per month scores higher. This metric uses total monthly precipitation as a proxy, which means destinations with brief tropical downpours are weighted similarly to those with persistent drizzle. We acknowledge this as a simplification — an area for future refinement.
Humidity (20% weight): The 40–60% relative humidity range is scored as ideal. Both very dry air (below 25%, which causes skin irritation and respiratory discomfort) and very humid air (above 80%, which inhibits perspiration and makes moderate temperatures feel much hotter) reduce the score.
Sunshine hours (15% weight): More daily sunshine hours scores higher, reflecting clear skies and outdoor-friendly conditions. This metric differentiates between a 20°C overcast day and a 20°C sunny day — a distinction that matters significantly for travel enjoyment.

A score above 75 indicates excellent travel conditions. Scores between 50 and 75 suggest decent weather with some caveats. Scores below 50 indicate challenging conditions for most general travelers, though specialized trips (skiing, storm watching, aurora viewing) may find low-scoring months ideal.

For a deeper explanation of how to interpret these scores in your travel planning, read our Complete Guide to Travel Weather Planning.

Destination Selection

WeatherLens currently includes 77 destinations in its climate database, selected based on a combination of tourism volume, geographic diversity, and traveler interest. We prioritize destinations that rank highly in global travel trend reports (Kayak, Conde Nast Traveler, Travel+Leisure, American Express Travel) and ensure representation across all major climate zones — tropical, arid, temperate, and continental — so the tool is useful regardless of what type of weather you are seeking.

New destinations are added regularly based on emerging travel trends and user requests. If a destination you are interested in is not in the database, you can still compare it using the live weather mode, which pulls current conditions from OpenWeatherMap for any city worldwide.

Editorial Standards

WeatherLens is committed to accuracy, transparency, and editorial independence. The following principles guide how we collect, present, and maintain data:

Data accuracy: All climate data is sourced from established meteorological agencies (NOAA, Copernicus). We do not fabricate, extrapolate, or estimate data without disclosing the method. When data for a specific destination is limited, we note this rather than presenting unreliable figures.
Transparency: Our data sources, methodology, and limitations are fully documented on this page. The Data Update Log on the homepage records every change we make, including new destinations added, data corrections, and notable climate events.
Regular updates: The destination database is reviewed and updated weekly. Current temperature data is refreshed via the OpenWeatherMap API every 3 hours. New destinations are added based on emerging travel trends. The update log provides a public record of all changes.
Corrections: If you identify inaccurate data for any destination, please contact us. We investigate all data correction reports and update the database when warranted. Corrections are noted in the Data Update Log.
Limitations acknowledged: Weather averages have inherent limitations. Individual years may deviate significantly from the 30-year mean. Microclimates, altitude effects, and urban heat islands can cause local conditions to differ from the reported averages. We encourage travelers to treat our data as a planning baseline rather than a guarantee.

Vendor Neutrality

WeatherLens is an independent weather data project. We are not affiliated with, endorsed by, or sponsored by any airline, hotel chain, travel agency, or tourism board. Our destination recommendations and comfort scores are based solely on weather data — we have no commercial incentive to promote any particular destination over another.

Advertisements displayed on WeatherLens are served by Google AdSense and are selected based on your browsing interests, not based on our editorial content or weather recommendations. Ad placement does not influence which destinations we recommend or how we calculate comfort scores.

The Team

WeatherLens is an independent project built by a small team passionate about making climate data useful for everyday travel decisions. We combine expertise in meteorological data processing, web development, and user experience design to deliver a tool that is both powerful and approachable.

The project launched in March 2026 and is actively maintained with weekly data updates, new features, and expanded destination coverage. Our goal is to become the most trusted free resource for travel weather comparison on the web.

We are always looking to improve. If you have feedback, feature requests, or data corrections, we would love to hear from you on our contact page. You can also read our Complete Guide to Travel Weather Planning for detailed advice on using weather data to plan better trips.