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ERA5 uses weather observations where such observations are available. On top of these observations ERA5 uses a weather forecasting model to produce a spatially and temporally continuous data. Like a weather forecast, the resulting data contains some uncertainty.
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The main problem with the extra-tropical and tropical cyclones in terms of uncertainty is the fact that due to the lower resolution of the EDA system, the EDA members systematically overestimate the central pressure of the cyclone (i.e. the pressure is not sufficiently low). This means that the spread among the members remains small and consequently the EDA shows lower uncertainties than in reality. On the other hand the spatial pattern of the uncertainties correspond rather well with the actual cyclones. This is demonstrated for some extra-tropical cyclones like cyclone Desmond: 2015120500, cyclone Xaver: 2013120500 or the Great Storm of 1987 in the UK. In all of these cases the maximum spread values don't exceed 1 hPa, which is quite small. The pattern of large spread values is scattered throughout the domain, though the primary cyclones are reasonably well-marked in the uncertainty field (particularly for the 1987 storm). For tropical cyclones the spread values can be larger, as it is for a cyclone near to Japan in 1987 or for the Haiyan typhoon near to the Philippines. It is very interesting to see the case of Hurricane Sandy, where the region with the largest uncertainties is not fully in agreement with the location of the hurricane's eye, but with some peaks to the east and west of it (the values are larger to the east). This indicates the uncertainties related to the position of the hurricane. So overall the EDA spread can give a qualitative idea of the uncertainties relating to active systems such as cyclones, but it is unable to provide the right uncertainty amplitude due to the lower resolution of the EDA system.
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Yes. Uncertainty indicators are available on the same model levels (137 model levels, as in the high resolution operational IFS model), pressure, potential temperature and potential vorticity levels as the ensemble members. The raw ensemble data (all members) are available for the users to compute any processed information.
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This document has been produced in the context of the Copernicus Climate Change Service (C3S). The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation agreement signed on 11/11/2014). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The users thereof use the information at their sole risk and liability. For the avoidance of all doubt, the European Commission and the European Centre for Medium-Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view. |
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