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Wind Gust Speed (Hanging Stick Move)
Rain/Snow Probability (Particles)
Cloud Cover, Day/Night (Color)
°C
°C
Felt Temperature (Color)
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Rain/Snow Sum (Height)
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Weathersquare is a minimalist, intuitive, and contextual weather visualization platform uniquely designed to provide high-resolution information of past and future conditions at a glance. Each square represents a day or hour, with colors, shapes, and movement mapped to real-time meteorological data.

Unlike existing weather graphics that can be too complex or too simplistic, Weathersquare tries to find the sweet spot with a visualization system designed with two main criteria: (1) to show only what matters for everyday use, in an intuitive visual language, but without losing detail, and (2) to show data in temporal or locational context in order to provide experiential references.

Weathersquares show cloud cover percentage and sunset-sunrise times (because these affect people’s moods and plans), precipitation probability and rain/snowfall sums, felt temperature, and wind gust speed (but not its direction). This informational and visual minimalism makes it easy to see the relevant parameters for our everyday concerns, in one place instead of separate graphs and modules, and in intuitive visual detail instead of generic illustrations (one big cloud with rain, one wind icon, etc.). Weathersquare strives for simple, friendly, at-a-glance visualization, but it still respects data resolution with continuous scales and representations.

Context is also key in Weathersquare. Forecast apps usually show today/now and the future days/hours. Seeing the past few days/hours within the same system in Weathersquare allows us to get a sense of what’s to come based on our fresh experience of those days/hours (“Today will feel like yesterday, but with a bit more wind”) and to better understand the temporal trends. In addition, we can easily compare the long-term weather and daylight experiences (“atmospheres”) of different cities, or compare the current weather of a city with last year or with decades ago.

I created Weathersquare because I needed it. I hope it will be as useful to others as it is to me.

Deniz Cem Önduygu
February 2026


Acknowledgements

I thank Gizem Kendik Önduygu, Amaç Herdağdelen, Eser Aygün, Korcan Akyıldız, and Emre Parlak for their helpful suggestions; Patrick Zippenfenig (Open-Meteo) for their support.

Weather Data

Open-Meteo

Contact

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Mean wind gust speed is shown with the angle of the “hanging stick” that looks vertical when there is no wind. Wind direction is not shown; the stick always moves towards right. This is a deliberate choice to make it more intuitive and relevant for lay people.

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The heights of the rain/snow rectangles on the ground represent the rain+showers sum and snowfall sum (they use different scales to accommodate the different ranges). The number of rain/snow particles in the sky is proportional to the mean precipitation probability (and the rain/snow ratio there is taken from the sums). The rain particles are also rotated according to the wind gust speed. (In the historical data in Compare Past, the particles also show the sums, not probabilities.)

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Sky color is calculated with a multi-step algorithm that takes into account the mean cloud cover, sunset-sunrise hours, and the long twilights in Arctic cities. (In the daily squares, the skies are colored based on the solar noon state for Arctic cities, with daylight if there is sunrise, and twilight colors if not.)

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The positions of the Sun and the Moon are not dynamic (except for sunset-sunrise hours). Their visibility is affected by the cloud cover, and the Moon is only there when the Sun is down. (It’s also not shown in civil twilights in Arctic cities.) The eight lunar phases are (discretely) calculated according to the date and the city’s hemisphere.

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Mean felt (apparent) temperature is shown with a color scale. (In the mobile app preferences, you can choose to show a color gradient with minimum-maximum felt temperature values for each day.)

All visual parameters are normalized to use global scales and are comparable across cities (except for extreme values which look the same over the global maximum thresholds).

All weather data is from Open-Meteo.

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Preferences

device_thermostatTemperature Unit
airWind Gust Speed Unit
water_dropPrecipitation Unit
scheduleTime Format
cadenceDaily Temperature Coloring
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