Use of ERA5 reanalysis to initialise re-forecasts proves beneficial
Vitart, Frédéric ; Balsamo, Gianpaolo ; Bidlot, Jean-Raymond ; Lang, Simon ; Tsonevsky, Ivan ; Richardson, David ; Balmaseda, Magdalena
Reanalysis, in other words the combination of observations with model information to reconstruct past weather and climate, plays an important role in numerical weather prediction. An example of this is the use of reanalysis to initialise re-forecasts. Re-forecasts are forecasts produced at the current time but starting from some point in the past. They are used to estimate a forecast model climate, which is needed to calibrate forecast products. Like all forecasts, re-forecasts require a set of initial conditions, which reanalysis can readily supply. ECMWF uses 11-member operational ensemble re-forecasts initialised every Monday and Thursday and covering the past 20 years to construct an extended-range model climate as a function of forecast lead time. This is in turn used to calculate extended-range forecast anomalies, e.g. weekly mean departures of predicted variables, such as 2-metre temperature or precipitation, from the model climate. A similar model climate is used to produce the Extreme Forecast Index (EFI) and the Shift of Tails (SOT) based on medium-range forecasts. Re-forecasts also serve to assess extended-range forecast skill and the evolution of forecast skill from year to year. Many years of re-forecasts are needed to accurately evaluate extended-range forecast skill. In the upgrade of ECMWF's Integrated Forecasting System to IFS Cycle 46r1 in June 2019, ECMWF's new ERA5 reanalysis replaced the older ERA-Interim to initialise re-forecasts. The change has resulted in better re-forecasts, better EFI skill scores and improvements in the prediction of extended-range anomalies.</p>
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