Historical Data (ERA5)
📜 All historical data is derived from the ERA5 reanalysis dataset. The ERA5 reanalysis dataset is a global atmospheric reanalysis dataset that provides hourly estimates of a range of atmospheric, land, and oceanic climate variables. It is the fifth generation of ECMWF atmospheric reanalyses of the global climate, and it provides a detailed view of the global weather conditions at a high temporal and spatial resolution.
Reanalysis and historical observations serve complementary roles in climate science. While reanalysis blends past observational data from various sources with modern weather models to offer a consistent, comprehensive view of past atmospheric conditions, historical observations represent direct, unaltered records from specific points in time and space. Though reanalysis offers continuous datasets in areas with sparse observations, it's crucial to remember that it's a modeled representation, which may introduce biases or inaccuracies. Therefore, while reanalysis provides broader coverage and fills gaps, direct historical observations remain vital for their inherent accuracy and validation purposes. Both are essential tools, and understanding their differences ensures effective use in climate studies.
⚙️ Model Details
- ERA5 Standard
- ERA5 Land
- Further Reading
- Time Period: January 1979 to December 2022
- Timestep: Monthly Averages (hourly and daily available upon request)
- Resolution: 0.25 degree (25 km)
- Update Frequency: Quarterly with little delay to relative time
- Geographic Coverage: Europe and Ontario
- Time Period: January 1950 to December 2022
- Timestep: Monthly Averages
- Resolution: 0.1 degree (9 km)
- Update Frequency: Quarterly with a three month delay to relative time
- Geographic Coverage: Global
🔍 More About ERA5
What is ERA5?
ERA5 is the fifth-generation atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). It serves as a comprehensive digital database that details the state of the global atmosphere, land surface, and oceans, providing meteorological variables for researchers and industry to utilize.
Key Features of ERA5:
Temporal Resolution: ERA5 offers hourly outputs, an improvement from its predecessor, ERA-Interim, which had a 3-hourly temporal resolution.
Spatial Resolution: It boasts a higher spatial resolution of about 0.25 degrees on the global scale, allowing for more detailed insights into localized meteorological phenomena.
Coverage: ERA5 provides data coverage from 1940 to the present. A separate dataset, ERA5-Land, even provides a higher resolution (9 km) reanalysis just for the land components.
Data Assimilation: ERA5 employs 4D-Var data assimilation, making it possible to account for observations from various sources across the time dimension.
ERA5 is utilized in numerous applications, including:
- Climate Research: It helps researchers to understand long-term climate trends and variations. ERA5 is often considered the 'go-to' dataset for studying the climate and is among the most trusted datasets in the world.
- Weather Forecasting: For refining prediction models and understanding past weather events.
- Energy Industry: Used in wind farm site selection and other renewable energy applications where understanding past weather patterns is essential.
- Agriculture: Helps in understanding soil moisture, temperature, and other factors critical for crop planning.
Compared to its predecessors, ERA5 provides a more accurate and detailed picture of the atmosphere. It incorporates more modern and varied observation types and uses a newer version of the ECMWF forecast model.
📝 Acknowledgments and Legal Information
The data provided through this API is based on the Copernicus ERA5 dataset.
The Copernicus ERA5 data is published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. For more information, visit CC BY 4.0 License.
Disclaimer: Copernicus does not accept any liability whatsoever for any error or omission in the data, their availability, or for any loss or damage arising from their use.
Where applicable, if the data has been modified, those modifications will be indicated in this section.