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Preamble

History of modifications

Related documents

Acronyms

About the dataset

Introduction

E-OBS is a land-only gridded daily observational dataset for precipitation, temperature, sea level pressure,global radiation, wind speed and relative humidity in Europe. This dataset is based on observations from meteorological stations across Europe which are provided by the National Meteorological and Hydrological Services (NMHSs) and other data holding institutes. The station data network is accessible through the webpages of the European Climate Assessment & Dataset (ECA&D, https://www.ecad.eu, Klein Tank et al. 2002).

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ECA&D and E-OBS are the backbone for the Climate Data node of the Regional Climate Centre for WMO RA VI (Europe and the Middle East, https://www.ecad.eu/RCC-CD).E-OBS daily gridded observations for Europe from 1950 to present: Product user guide Skip to end of metadata

Main variables

The underlying station dataset

The station data are provided by 79 participants and the ECA&D dataset contains over 20000 meteorological stations (status May 2021). Metadata of the series, including the source and metadata of the meteorological stations are provided through the ECA&D website.

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Figure 1: Map with the station coverage in ECA&D which is the basis for the E-OBS precipitation dataset v20.0e (left). The number of stations which provide precipitation (red) and temperature (green, blue, purple) vs. time (right).

User community and user feed-back

Initially (Haylock et al. 2008), this gridded dataset was developed to provide a validation dataset for the suite of Europe-wide climate model simulations produced as part of the EU ENSEMBLES project. While E-OBS remains an important data set for model validation, it is also used more generally for monitoring the climate across Europe, particularly with regard to the assessment of the magnitude and frequency of daily extremes.

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Figure 7: The number of drizzle-days in E-OBSv8.0 before (left) and after (right) the modification in the gridding method. Problem noticed by a colleague from SMHI.

Methodology and the uncertainty estimation

E‐OBS is calculated by adopting a two‐stage process to produce the daily fields: (1) the daily values are aggregated to monthly values that are initially fitted with a deterministic model, to capture the long‐range spatial trend in the data, and (2) the residuals from this model are then interpolated using a stochastic technique (Gaussian Random Field, GRF) to produce the daily ensemble. Monthly values are used in the first step of the interpolation, since the relationship of altitude to the meteorological fields can be difficult to discern in daily resolution data, particularly for precipitation.

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Earlier versions of E-OBS (up to v17.0) used for the interpolation of temperature , precipitation and sea-level pressure the method described by Haylock et al. (2008) and Van den Besselaar et al. (2011).

Additional post-processing for the relative humidity and global radiation datasets

An additional quality control has been performed on the relative humidity fields where unphysically low values for relative humidity have been observed as a consequence of scarce station density in combination with the gridding method. As of E-OBSv24.0e, the grid boxes with values below 5% are set to missing in each of the 20 ensemble members. This additional check mirrors the quality check applied to the input stations. The ensemble mean and ensemble spread are derived from these adjusted ensemble members, making sure that all humidity values are above 5%. Note that the approach to grid transformed values of humidity (rather than humidity directly) already makes sure that no humidity values higher than 100% are possible.

Similarly, the global radiation dataset has been post-processed in the areas and in the periods where it suffers from unrealistic values. This problem occurs in areas and periods where the station network is of low density. Following a similar procedure as with relative humidity, the same quality-control rules are applied to the grids as are applied to the stations. This means that any daily global radiation sum in each of the E-OBS ensemble members is set to missing where it falls below the 3% TOA (Top Of Atmosphere) level or exceeds the maximum expected global radiation of the earth surface on a clear sky day. The quality control procedure is detailed in the ATBD(2021). This additional post-processing is in place as of E-OBSv24.0e.

Comparison with other datasets

E-OBS is used routinely in monitoring the European climate and contributes to the monthly and annual State-of-the-Climate bulletins issued through C3S, and to the State-of-the-Climate bulletins published annually in The Bulletin of the American Meteorological Society (Europe section).

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Figure 10: European averaged annual temperatures as calculated from E-OBS version 6.0 (in black), including the error margins in grey boxes, and the European averaged annual temperature as calculated using the CRUTS3.1 temperature dataset (in red).

Guidance on the use of an ensemble dataset

Ensemble datasets are climate datasets that consist of a number of equally probable realizations, and relate to data in gridded format. The ensemble aims to give a measure of uncertainty in the data field; such datasets are widely used in a number of areas of climate change science, like perturbed physics simulations of climate models or numerical weather prediction.
The term "ensemble" is also used when referring to multiple realizations from gridded observed datasets. Such datasets, like E-OBS, are formed from the interpolation of station values. Although the aim is the same as ensembles calculated for model simulations – to quantify uncertainty in the data – the generation and hence interpretation of the realizations is quite different. With gridded observational datasets, decisions have to be made for a number of features that affect the final gridded field of the key parameters involved in the gridding algorithm. These could include:

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The individual ensemble members are mainly intended for users who require the uncertainty in the gridded fields to propagate through to various other applications. If a user requires this rainfall data for hydrological modelling then each of the ensemble members could be fed into the hydrological model. In this way the uncertainty in the rainfall interpolation would propagate through to the hydrological model output.

Specifics for E-OBSv20.0e and E-OBSv19.0e

Subsequent versions of E-OBS are updated using recent data from the European national meteorological services and by inclusion of new series. It is the amount of input station data that explain the differences between subsequent versions of E-OBS.

E-OBSv20.0e is released in October 2019 and spans the period 1950-01-01 to 2019-07-31. New series and updates have been included for Italy, Croatia, Norway and Russia. Monthly, half-yearly and yearly updates are continued for Germany, Czech Republic, Bosnia and Herzegovina, Norway, Slovenia, Finland, Ireland, Sweden, Luxembourg, Netherlands, Portugal, Spain, Switzerland, France, Denmark, UK and the regional meteorological service of Catalonia (Spain).

Figure 11 and 12 give an indication of the differences between v20.0e and v19.0e for precipitation and temperature for the year 2000. The areas where new station data has been added are immediately recognizable in these figures. This holds perhaps even more so for the standard deviation of the daily differences between the datasets.

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Data licence

The data licence for E-OBS is more restrictive than for other CDS products. In this paragraph, the background for this difference is explained.

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The situation that only part of the data supplying institutes have agreed to an open data licence of derived data, makes that the data licence of E-OBS needs to resort to the rather strict licence currently in use, meaning that the dataset can only be used for non-commercial research and education.

Technical summary

E-OBS has been in operational production since 2009 with bi-annual updates. The Technology Readiness Level for E-OBS is TRL 9 – Actual system proven in operational environment.

The E-OBS dataset is provided in the NetCDF-4 format.

References

Cornes, R. C., & Jones, P. D. (2013). How well does the ERA‐Interim reanalysis replicate trends in extremes of surface temperature across Europe?. J. Geophys. Res. (Atmospheres), 118(18), 10-262.van der Schrier, G., Knap, W., Dirksen, M., 

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Van den Besselaar, E.J.M., van der Schrier, G., de Baar, J. (2021) Daily relative humidity maps for Europe based on in-situ observations (in preparation)

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