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Powering Our Predictions: A Look at Our Data Sources ​

At pvnode, we believe in transparency for the data and open source software we use in order to provide our services. That's why we want to shed light on the powerful data sources that fuel our photovoltaic (PV) models and drive the accuracy of our predictions. We're grateful to the data providers and research communities who make our work possible.

Combining the Best of Both Worlds: Ground and Satellite Data ​

Our PV models are built on a foundation of extensive research, blending the precision of ground-based weather station data with the broad perspective of satellite observations, where available. This unique approach allows us to:

  • Capture local nuances: Ground stations provide highly accurate, localized information about weather conditions that directly impact solar energy production.
  • See the bigger picture: Satellite data gives us a comprehensive view of weather patterns and solar irradiance across wide areas.

By combining these two powerful data sources, we create a refined, internal data reference that ensures our predictions and analyses are both reliable and adaptable to diverse locations and conditions.

Honoring Our Data Providers ​

We deeply value the contributions of our data providers and are committed to adhering to their usage policies and terms. Every data point, whether it comes from a local weather station or a global satellite feed, plays a vital role in enhancing our services.

We meticulously integrate these diverse data sources to achieve the highest possible precision.

Please find a list of all data sources we use below. We are continuously adding new sources to our platform and will update the list accordingly.

Always Evolving: Our Commitment to Improvement ​

We're passionate about constantly refining our models. That means regularly updating our data processing techniques and algorithms to reflect the latest research findings and data enhancements. This ongoing evolution ensures our clients always receive the most accurate and actionable insights.

Data Sources ​

UK Met Office - Atmospheric forecasts ​

  • Author: UK Met Office
  • Data basis: UK Met Office, own elements added. Used in calculations.
  • Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
  • License

Canadian Meteorological Centre CMC - Atmospheric, ensemble and wave forecasts ​

GeoNames ​

  • Author: GeoNames
  • Data basis: GeoNames, own elements added. Used in calculations.
  • Creative Commons Attribution 4.0 International (CC BY 4.0)
  • License

Aster DEM (GDEM 003) ​

Japan Meteorological Agency JMA - Atmospheric forecasts ​

Deutscher Wetterdienst DWD - Atmospheric, ensemble and wave forecasts ​

  • Author: Deutscher Wetterdienst DWD
  • Data basis: Deutscher Wetterdienst, own elements added. Used in calculations.
  • Creative Commons Attribution 4.0 International (CC BY 4.0)
  • License

European Center for Medium-Range Weather Forecasts ECMWF - Atmospheric, ensemble and wave forecasts ​

  • Author: ECMWF
  • Data basis: ECMWF, own elements added. Used in calculations.
  • Creative Commons Attribution 4.0 International (CC BY 4.0)
  • License

National Centers for Environmental Prediction - Atmospheric, ensemble and wave forecasts ​

  • Author: NOAA NCEP
  • Data basis: NOAA NCEP, own elements added. Used in calculations.
  • License

Météo-France - Atmospheric, ensemble and wave forecasts ​

Norwegian Meteorological Institute - Atmospheric forecasts ​

Chinese Meteorological Administration CMA - Atmospheric forecasts ​

Australian Bureau of Meteorology BOM - Atmospheric forecasts ​

Royal Netherlands Meteorological Institute KNMI - Atmospheric forecasts ​

Danish Meteorological Institute DMI - Atmospheric forecasts ​

Copernicus Marine Service - Wave forecasts ​

EUMETSAT ​

  • Author: EUMETSAT
  • Data basis: EUMETSAT, own elements added. Used in calculations.
  • Copyright (2024) EUMETSAT
  • The calculations performed were done (i.a.) by using data from EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF).
  • Reference
Tsamalis, Christoforos; King, Robert; Good, Elizabeth; John, Viju; Hollmann, Rainer; Selbach,
Nathalie; Werscheck, Martin (2019): CM SAF Microwave Upper Tropospheric Humidity (UTH)
Data Record - Edition 1, Satellite Application Facility on Climate Monitoring,
DOI:10.5676/EUM_SAF_CM/UTH/V001, https://doi.org/10.5676/EUM_SAF_CM/UTH/V001

Copernicus Climate Change Service C3S Reanalysis ​

Global Flood Awareness System GloFAS - Flood Events ​

Weather Icons ​

  • Author: Weather Icons
  • Data basis: Weather Icons, own elements added. Used in calculations.
  • The SIL Open Font License
  • License

Deutscher Wetterdienst DWD ​

Copernicus Atmosphere Monitoring Service Products ​

OpenMeteo ​

  • Author: Patrick Zippenfenig
  • Data basis: OpenMeteo, own elements added. Used in calculations.
  • Creative Commons Attribution 4.0 International (CC BY 4.0)
  • License

NREL National Solar Radiation Database ​

Copernicus Land ​

  • Author: Copernicus Land
  • Data basis: Copernicus Land, own elements added. Used in calculations.
  • Copernicus data and information policy Regulation (EU) No 1159/2013 of 12 July 2013
  • License