Reanalysis
A reanalysis is a complete record of past weather, rebuilt by combining millions of observations with a weather forecast model. The model fills the gaps between weather stations, satellites and balloons, so the result covers every point of a regular grid, every hour, over several decades, with the same method throughout. That makes a reanalysis the usual stand-in for observations where weather stations are few or their records short.
ERA5 vs ERA5-Land
Section titled “ERA5 vs ERA5-Land”The reference reanalyses today are ERA5 and ERA5-Land, produced by ECMWF for the Copernicus Climate Change Service, which updates them daily, a few days behind real time.
Table 1. The two reanalyses (Hersbach et al., 2020; Muñoz-Sabater et al., 2021).
| ERA5 | ERA5-Land | |
|---|---|---|
| Resolution | 0.25°, about 30 km | 0.1°, about 9 km |
| Coverage | the whole globe, atmosphere, land and ocean | land surfaces only |
| Time step | hourly | hourly |
| Period | 1940 to present | 1950 to present |
ERA5-Land is not a separate reanalysis of observations: it reruns the land component of ERA5 at a finer resolution, driven by ERA5’s weather. Its gain is the finer detail of land-surface variables such as temperature and precipitation, for example in mountains.
How we use it
Section titled “How we use it”ERA5-Land is the reference of our climate projections: each climate model is bias-adjusted against it over 1981–2010, which brings the projections to its 0.1° grid (see Bias adjustment and downscaling and Data processing). Our earlier CMIP5 projections used ERA5 at 0.25° (Noël et al., 2022). For the data themselves, see our climate projections on the main site.
A reanalysis is only as good as the observations behind it: its quality varies by variable and region, with how many observations it rests on. We recommend checking ERA5-Land against local data over the historical period before using projections built on it (Noël et al., 2022). For the historical data we provide, see Do you provide historical observations?
References
Section titled “References”- Noël, T., Loukos, H., Defrance, D., Vrac, M., & Levavasseur, G. (2022). Extending the global high-resolution downscaled projections dataset to include CMIP6 projections at increased resolution coherent with the ERA5-Land reanalysis. Data in Brief, 45, 108669. https://doi.org/10.1016/j.dib.2022.108669
- Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., et al. (2021). ERA5-Land: a state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13, 4349–4383. https://doi.org/10.5194/essd-13-4349-2021
- Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049. https://doi.org/10.1002/qj.3803