Era5Edit
ERA5 is a global atmospheric reanalysis dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) as part of the Copernicus Climate Change Service program. It offers a continuous, consistent record of the Earth's atmosphere from the mid-20th century to the present by combining a state-of-the-art forecast model with a broad array of observations. ERA5 represents a high-water mark in open, long-term weather and climate data, designed to support everything from weather prediction verification to risk-aware decision making in energy, agriculture, and infrastructure.
Built to supersede earlier reanalysis efforts, ERA5 strives for homogeneity and completeness in the face of changing observing systems. It provides hourly estimates of a wide range of atmospheric, land-surface, and ocean parameters on a dense spatial grid, enabling researchers and practitioners to study climate variability, trends, and extremes with a level of detail that was not feasible with older products. ERA5 data and related products are openly accessible through the Copernicus Climate Data Store (Copernicus Climate Data Store), reflecting a commitment to transparency and broad utility across public and private sectors.
This article surveys what ERA5 is, how it is built, how it is used, and the debates around reanalysis-driven climate interpretation from a policy-relevant, market-oriented perspective. It discusses data structure, access, practical applications, and the main controversies that users sometimes raise when interpreting long-term climate information for decision making.
Data and construction
ERA5 is a global atmospheric reanalysis at approximately 0.25-degree horizontal resolution with about 137 vertical levels reaching up to around 80 kilometers in the upper atmosphere. In addition to atmospheric variables, ERA5 provides surface and near-surface fields such as temperature, humidity, wind, geopotential, and precipitation-related metrics. The data are available on an hourly timescale, enabling detailed diurnal analyses and improved attribution of weather events.
The reanalysis workflow relies on the Integrated Forecast System of ECMWF and a sophisticated data assimilation to combine a wide array of observations with a model-based background. ERA5 uses a form of Four-dimensional variational data assimilation to optimally blend observations across space and time, yielding a physically consistent picture of the atmosphere.
Observational input spans surface observations, radiosondes, aircraft, and increasingly distributed satellite data, along with marine and land-surface measurements. The goal is to leverage all available information to produce a coherent, cross-validated history of atmospheric states.
ERA5 is designed to be more accurate and consistent than its predecessor, ERA-Interim, particularly in representing precipitation, near-surface variables, and extreme events. The shift to ERA5 reflects ongoing improvements in model physics, data assimilation techniques, and the integration of new observation types.
In addition to the atmospheric component, a parallel product, ERA5-Land, provides high-resolution land-surface variables by running a dedicated land-surface model with atmospheric forcing from ERA5. This division acknowledges the different sources of uncertainty and observational coverage in land versus atmosphere.
Access to ERA5 is coordinated through Copernicus Climate Data Store, which provides data in multiple formats suitable for research, engineering, and operational use. Users can retrieve single-level (surface) variables as well as pressure-level data that resolve the vertical structure of the atmosphere.
Data products and access
ERA5 offers both single-level and pressure-level data, enabling analyses from near-surface conditions up through the upper atmosphere. Examples of commonly used fields include 2 m temperature, 2 m dew point temperature, 10 m wind, sea level pressure, geopotential height, and a suite of humidity and wind variables across multiple vertical levels.
Because ERA5 is a reanalysis, the data are inherently retrospective in nature but are continually updated with near-real-time processing, maintaining a seamless historical record. This makes ERA5 especially valuable for long-baseline climate studies, model evaluation, and retrospective event analysis.
The data policy emphasizes openness and reuse. Researchers, energy traders, and policymakers can download ERA5 fields for regional studies, global assessments, or time-series analyses. The availability of hourly data at a global scale supports applications such as weather risk assessment, hydrological modeling, and climate monitoring.
Typical usage scenarios include verification of numerical weather prediction systems, validation of climate model output, and construction of climate indicators for sectors like agriculture, aviation, and transportation. The combination of high temporal resolution and broad spatial coverage makes ERA5 particularly suitable for event attribution studies and impact assessments.
Important related products include ERA5-Land for high-resolution land data and the historical reanalysis family that includes predecessors like ERA-Interim. The ongoing development of ERA5 reflects commitments to improving uncertainty characterization, bias correction, and integration with other data streams.
For practitioners, the data workflow often involves scripting against the CDS API, downloading NetCDF or GRIB files, and using standard climate and meteorological toolchains to extract time series, composites, and trend metrics. The availability of programmatic access accelerates incorporation into analytics pipelines and operational tools.
Applications and implications
ERA5 serves a broad ecosystem of users: meteorologists validating forecasts, climate scientists analyzing trends and extremes, water managers forecasting runoff, and energy sectors managing weather-related risk. The dataset underpins numerical weather prediction verification, climate monitoring, and long-term risk assessment.
In a market-oriented policy environment, ERA5 is valued for its transparent and traceable record of atmospheric states. This supports risk-informed decision making in sectors such as power generation, agricultural planning, and insurance, where weather and climate factors directly influence costs and reliability.
Policymakers and planners rely on ERA5 to quantify exposure to weather-related hazards, design adaptation measures, and evaluate the cost-effectiveness of interventions. The open data policy reduces barriers to independent analysis and fosters competition and innovation in weather-sensitive industries.
Climate research benefits from ERA5’s consistent historical record, which assists in benchmarking climate models, understanding natural variability, and attributing certain events to broader climatic drivers. The high-quality data also support cross-disciplinary studies in hydrology, forestry, aviation safety, and disaster risk reduction.
Critics of climate policy sometimes argue that long-term projections should be interpreted with caution and that policy should be anchored in robust, verifiable data. Proponents counter that datasets like ERA5 provide a transparent basis for risk management and evidence-based decision making, reducing reliance on uncertain narratives and enabling performance-based planning.
Controversies and debates
One area of discussion concerns how to interpret long-term trends and extremes in reanalysis data. While ERA5 improves consistency and coverage relative to earlier products, some researchers caution that reanalysis is still influenced by historical gaps in observations, changes in satellite calibration, and evolving assimilation techniques. This underscores the importance of cross-checking ERA5 results with independent sources, such as dedicated climate model runs or regional observations.
From a policy and economics perspective, the question is how best to translate reanalysis-derived metrics into concrete actions. Skeptics may worry about overreliance on a single data backbone for decision making, while advocates emphasize the need for transparent, traceable data streams to inform risk management and resilience planning. ERA5’s openness and reproducibility are often cited as advantages in this debate, enabling independent validation and critical scrutiny.
The debate around extreme events and attribution is nuanced in the ERA5 context. Some critics argue that attributing specific extremes to anthropogenic forcing can be overstated or misinterpreted when framed purely through a single reanalysis dataset. Proponents maintain that ERA5 provides a robust platform for attribution studies when used in conjunction with dedicated attribution methodologies and multiple data sources. The key point is that reanalysis is a tool for understanding broad patterns and risks, not a crystal-ball forecast of every event.
A broader tension in climate discourse concerns the balance between precaution, cost, and resilience. ERA5 supports risk-aware planning by improving the fidelity of historical baselines and the reliability of near-term forecasts, but the policy choices that follow—such as infrastructure upgrades or emission-reduction measures—require careful weighing of economic costs and societal objectives. Advocates for market-based, innovation-driven solutions point to ERA5 as a reliable input that helps avoid overreaction and fosters targeted investments.
Overall, ERA5 is widely regarded as a robust, transparent, and useful resource for both science and practice. Its ongoing development— including enhancements to bias characterization, uncertainty quantification, and data assimilation techniques—reflects the field’s effort to provide stakeholders with credible information for informed decision making.