Weather and Climate Data for Analysts

Can't find the right time-series weather data for your analysis?

Access historical and forecast weather data for any location with a single API call.

Explore APIs


Access weather data in seconds without searching for weather stations or processing gigabytes of raw data


Get unadulterated weather data from authoritative sources such as ECMWF and NOAA


Hundreds of data analysts trust OikoLab to perform business-critical analyses

Use Cases


Building Energy

Create custom weather files for building energy simulations

  • drybulb temperature

  • 10m wind speed

  • shortwave/longwave radiation

  • soil temperature

Try it out.


Smart Grid

Simplify grid load analysis and predict solar/wind generations

  • dewpoint temperature

  • 100m wind speed

  • urban temperature

  • heating/cooling degree days

Try it out.


Time-series Forecast

Analyze and forecast weather dependent metrics with ease

  • surface pressure

  • relative humidity

  • total precipitation

  • snowfall

Try it out.


Case Studies

Electricity Load Disaggregation

EPRI has partnered with OikoLab to develop electricity load disaggregation engine based on the weather and AMI meter data. The model has been validated for residential homes in US North West regions (RBSA dataset) and Phoenix, Arizona (Salt River Project).


Analyzing Effects of Weather on Mental Well-being

Neurem is using weather data provided by OikoLab to assess how various components of weather, ranging from temperature and humidity to amount of sunlight, affect the mental well-being of individuals.


Why OikoLab?

Finding the right weather data needed for your analysis can be surprisingly time consuming and difficult. We've processed hundreds of terabytes of the latest weather reanalysis dataset for fast time-series query so that you don't have to.


Imagine a typical use case for an analyst, looking to correlate weather and building energy usage history for the past three years to build a prediction model. Using weather data service designed for weather apps is not ideal for this use case.

Other weather service providers emphasize the inadequateness of public weather dataset but the truth is that all weather service providers are dependent on the same data sources. Using machine learning models, they use regression-based methods to sometimes refine the Numerical Weather Prediction (NWP) model output data to improve resolution but this process is quite opaque.

In contrast, OikoLab provides direct access to unmodified NWP data to maximise traceability. When parameters are derived or simulated, such as wet-bulb temperature or urban temperature, we indicate that they are. We provide NWP data reference time so you know how recent the data is, when the next update will be, and if needed, the data can be validated against the original source.  

Also, we focus on saving time for data analysts: instead of providing one screen-shot worth of weather data at a time, our users can quickly get all the data they need in a single API call for any location.


Our Changing Climate

The climate is changing. Let us help you understand the impact of the changing climate on your business.


Copyright © OikoLab Ltd. 2020