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At long lead times, particularly beyond 10 days, unphysical artefacts can emerge in the model, particularly under areas of high elevation. These are particularly visible for mean sea level pressure and temperature at 1000hPa.

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1000hPa temperature artefact beneath the surface of the Andes at 360hours 360 hours into the forecast.

On average, ensemble standard deviation is larger than the RMSE of the ensemble mean for a range of variables.

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Spread and error evolution for 850hPa temperature showing over-dispersion between days 2 and 8.

Very small values (e.g. <0.1mm/6h) of precipitation can unphysically occur in very dry arid regions, which are in what appears to be an unphysical way. This is particularly noticeable when looking at long accumulation periods.

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240h accumulated precipitation

In general, AIFS ENS significantly improves on the representation of small fine scale features compared with AIFS Single. However cloud fields display features at a lower spatial resolution than many of the other fields predicted by the AIFS ENS. Features have a resolution closer to the 1-degree resolution of the model processor grid. T+0 fields do not show this behaviour because they are imported from the IFS initialisation.

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Example of reduced spatial resolution for cloud fields over Europe in an AIFS ENS forecast.

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Energy spectra for total cloud cover in AIFS ENS at day 1 (blue line), showing reduced energy at small scales (=high wavenumbers, on the right of the plot) compared with the IFS analysis (black). Energy can be loosely interpreted as frequency of occurrence.