About Us

Weather Atlas provides detailed weather forecasts and climate information for over 700.000 locations worldwide.

Founded in Serbia in 2002, our company had several projects and initially published weather information as a "side-job."
The weather obsession began a few years later, with a severe rainfall that caused a flood, entirely destroying our offices and, most devastatingly, all personal photos, effectively erasing my personal history.
This event led to a vow to provide clear, accurate, and timely weather information to help prepare for any day-to-day meteorological surprises from Mother Earth.

Over 20 years later, our company operates internationally and the fight the gods of the skies is still on.
And every time we save someone from having a ruined holiday, wedding, or a spoiled BBQ, or keep one more person from getting caught in the rain without an umbrella, we count it as another divine victory - take that, Zeus!

For information about our team and headquarters, please visit the contact page.

Weather_Atlas @ X

Weather Atlas Widget

We are providing a free weather widget for the WordPress platform, designed for webmasters to seamlessly integrate weather forecasts into their websites.

The Weather Atlas Widget is the most popular weather widget on WordPress.org, boasting over 10,000 active installations. With over 700,000 locations across 238 countries, the widget allows websites to stylishly display the most relevant and accurate numerical and textual weather information to their users.

Weather forecasting & Climate

Every day, around the globe, people rely on weather forecasts to make choices that impact their comfort, well-being, and safety.
How hot is it expected to get today?
Will it rain tomorrow?
What is the forecast for the weekend?
What time will the thunderstorm hit?
How long will the heatwave last?
Is a cold front approaching?
Are we in for a dry spell?
Will it be sunny for the outdoor event?
Is it safe to go boating in this weather?
Will it rain on my wedding day in September?
What are the conditions for skiing in December?

A weather forecasts represents the scientific prediction of forthcoming atmospheric patterns based on meticulous scrutiny of meteorological data.
Weather forecasting is intrinsically fraught with uncertainty due to the chaotic properties of the atmosphere and the constraints of observational data and numerical models. This intrinsic uncertainty results in forecast accuracy diminishing as the prediction timeframe extends.

Short-Term Forecasts: This category of forecasts aims at predicting weather conditions spanning from a few hours up to a maximum of two days. Characterized by relatively high accuracy, short-term forecasts present a detailed picture of impending local weather.
Medium-Range Forecasts: Medium-range forecasts extend the predictive view to a timeframe ranging from three days up to ten days. These forecasts provide a broader, albeit less precise, understanding of the prospective weather patterns.
Long-Range Forecasts: Focusing on a time stretch of several weeks to months, long-range forecasts trade off precision for the ability to discern broader trends and seasonal shifts in weather.

Simply put - weather forecasting is uncertain because of the chaotic nature of the atmosphere and the limitations of data and models. As the prediction timeframe extends, forecast accuracy decreases.

Overall, use this as a rule of thumb:

1-2 days (24-48 hours) - Weather forecasts are generally very accurate, with a high level of certainty. Most meteorological models can predict weather patterns with around 85-90% accuracy within this short-term period.
3-5 days - Forecasts are still quite reliable but the certainty starts to decrease slightly. The accuracy is usually around 70-80%.
6-10 days - The accuracy of forecasts decreases further, often dropping to about 50-60%. Predictions become less reliable due to the increasing complexity and variability of atmospheric conditions.
10 days and beyond - Forecasts for this period are generally much less certain, with accuracy often falling below 50%. Long-term weather predictions are challenging due to the chaotic nature of the atmosphere and the limitations of current meteorological models.

The term climate characterizes the enduring patterns of atmospheric variables, including temperature, humidity, wind, and precipitation, in a designated region. It symbolizes weather patterns averaged over an extended period, traditionally taken as 30 years, and its formation is influenced by parameters like latitude, elevation, the closeness of significant water bodies, and the behavior of currents within them.

Simplified essence:
Climate and weather forecasts are related but distinct.
Weather forecasts predict short-term atmospheric conditions (hours to weeks), while climate describes the long-term average of weather patterns over extended periods.

Sources

What is Weather Data?

Weather data is the collection and analysis of meteorological elements, providing valuable information about the current state and forecasted changes in weather patterns. Accurate and timely data is crucial for meteorologists, researchers, and organizations to understand and predict weather conditions, enabling better planning for everyday tasks and decision-making in various sectors such as disaster management, transportation, and agriculture.

How is Data Collected and Measured?

Weather data is collected and measured using a variety of modern and traditional methods, leveraging cutting-edge technology for accuracy.

Common collection methods are:

Thermometers for temperature
Barometers for atmospheric pressure
Hygrometers for humidity
Wind vanes and anemometers to gauge wind speed and direction
Radar systems to track rain cloud movement
Transmissometers to measure atmospheric visibility
Weather satellites to locate clouds, snow cover, wildfires, ocean temperatures, and tidal patterns
Radiosondes (balloons) to measure atmospheric characteristics as they move through the air

The data is constantly updated from sources like satellites, airport observation stations, and drone sensors, and with sophisticated technology and weather models, it provides increasingly accurate and detailed information.

What Are the Types of Weather Data?

Real-time Weather Data vs Historical Weather Data
Real-time weather data provides the most up-to-date information on weather conditions as they are occurring, allowing for tracking hour-to-hour or day-to-day changes in the weather. Historical weather data offers insights into weather patterns and conditions from previous days, months, years, or decades.

Local Weather Data vs Global Weather Data
Local weather data provides information about weather conditions in a specific localized area, such as a city. Checking your city's daily forecast in the morning is a prime example of using local weather data. Global weather data covers weather and climate patterns for entire continents or the planet. Tracking global temperatures or measuring wind patterns between continents are examples of using global weather data.

What Types of Weather Attributes Can Be Presented?

Temperature: Average, median, minimum/maximum temperature, in degrees Celsius or Fahrenheit.
Air Pressure: Millibars or mm/inches of mercury, air current.
Humidity: Absolute humidity, relative humidity (percentage).
Dew Point: In degrees Celsius or Fahrenheit.
Precipitation: Type (rain, snow, hail, sleet), amount, probability.
Daylight Hours: Sunrise and sunset times, moon phase.
Cloud Coverage: Expressed in oktas.
Wind: Speed (mph or km/h), direction.
Ozone Information: Levels of ozone concentration.
UV Index: Measurement of ultraviolet radiation.
Pollen Concentration: Per cubic meter.
Solar Radiation: Typically measured in watts per square meter (w/m²).
Severe Weather Risks and Events: Hurricanes, tornadoes, storms, floods, wildfires, and other "freak" weather phenomena.

What Are Well-Known Sources of Weather Data?

National Oceanic and Atmospheric Administration (NOAA): A key source of weather data in the United States.
European Centre for Medium-Range Weather Forecasts (ECMWF): Provides extensive weather data and forecasts for Europe and beyond.
Private Weather Companies: Companies such as The Weather Channel and AccuWeather offer detailed weather information and forecasts.
Crowd-Sourced Weather Data: Science projects that gather weather data from the public.

πάντα ῥεῖ / Panta Rhei / Everything flows

Weather Forecasting Accuracy

Numerous scientists work diligently to produce the best weather forecasting models. These forecasts are not guesswork - they are the result of analyzing vast amounts of weather data.
Organizations like the National Weather Service (NWS) and major weather providers like AccuWeather and The Weather Channel employ advanced models that simulate atmospheric behavior based on billions of data points. These models require massive computing power to process the data and generate accurate forecasts.

Different prediction models produce different forecasts, and there will always be discrepancies between predictions and actual outcomes. The goal in weather forecasting is to achieve the highest accuracy (lowest error rate). By comparing predictions and outcomes, the accuracy of the weather models can be evaluated.

Independent Global and Regional Weather Forecast Accuracy Overview, 2017-2022 study from ForecastWatch reported that The Weather Channel is the world’s most accurate forecaster overall.
The report was an assessment of 250 million forecasts over 6 years, 2,182 global locations across 8 global regions, 23 different weather providers, and 84 accuracy metrics covering precipitation, temperature, cloud cover and wind variables.

Major highlights of the report include:

The Weather Company is the world's most accurate weather forecaster overall of the providers studied.
The Weather Company was over 3 times more likely to be the most accurate forecaster than any other provider studied.
The accuracy gap between The Weather Channel and the next best provider has increased, from being twice as likely to be the most accurate in 2017 to over three times more likely in 2022.
The Weather Channel was the most accurate provider in each region studied, including the U.S., Canada, Central America, South America, Europe, Africa, the Middle East, and Asia-Pacific.

Where Does Weather Atlas Get Its Data From?

Are we one of the major providers of weather data? Unfortunately, we are not one of the "heavyweights".
However, the ability to choose and cross-reference multiple sources of weather data simultaneously certainly has its advantages.

Current weather - for hyperlocal forecasting (depending on availability for a location)

Today (hourly) / Tomorrow (hourly) / 10 days Weather Forecast

The Weather Channel

Weather Radar
RainViewer and it's sources:

Monthly (Historical) Weather Data
The process for retrieving historical weather data involves sourcing information from multiple providers, preferably from national weather services (listed below), and as a fallback from the U.S. NCEI's Climate Data Online.
The minimum required span for historical data is 10 years, but the vast majority of data spans at least 30 years. We are in a year-by-year race to retrieve and update historical data with the latest information.