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Distribution Data API

Harness the power of historical climatic data with our Distribution Data API, your portal to the past, powered by the comprehensive ERA5 dataset. This API doesn't just give you data; it gives you the statistical distribution of climatic variables over time, enabling an unprecedented understanding of weather patterns.

Distribution Data: A Deeper Dive into Climate

Instead of mere averages, distribution data offers a robust picture of climatic behavior. It helps reveal patterns and probabilities, from common to rare events, which is essential for risk assessment, predictive modeling, and climate research.

Variable Selection​

You can query the API for a variety of climatic variables, each critical for different aspects of climate study:

 

See variables
Full Variable NameDescriptionShort VariableDistribution
2m TemperatureAmbient air temperature at 2 meters above the groundt2mGaussian
Total Cloud CoverProportion of the sky that is covered by clouds (0-1)tccBeta

Methodology​

Distributions are available for every hour, offering 8,760 unique snapshots per year—each one a detailed picture of climatic behavior across decades.

Inputs​

The API accepts the following parameters:

  • start_time: The start time for historical data.

  • end_time: The end time for historical data.

  • Latitude: The geographical latitude for the location.

  • Longitude: The geographical longitude for the location.

  • Variable: The climatic variable for analysis.

Interactive Endpoint​

You can access and interact with the API endpoints using our API Endpoint Directory.

Example Use Case: Zurich’s Temperature and Cloud Cover Profiles​

Let’s take Zurich as an example. What does the temperature distribution look like throughout the year? How do the months differ? Here, the API shines, offering detailed temperature distributions for every hour of the year, based on a 30-year average.

 

Visualizing Yearly Temperature Patterns​

Yearly Temperature Distribution Displayed in Kelvin, this visualization reveals the ebb and flow of Zurich's temperature throughout the year—valuable for both granular and broad-scale analyses.

 

Extracting Actionable Insights​

Hourly Temperature Distribution The real value emerges when dissecting the hourly temperature distributions. This data can empower Monte Carlo simulations, risk assessments, or bootstrap statistical predictions, providing the backbone for both climate modeling and decision-making tools.