Scale-Selective Precision for Weather and Climate Forecasting
MONTHLY WEATHER REVIEW 147:2 (2019) 645-655
How confident are predictability estimates of the winter North Atlantic Oscillation?
Quarterly Journal of the Royal Meteorological Society Wiley 145:S1 (2018) 140-159
Abstract:
Atmospheric seasonal predictability in winter over the Euro-Atlantic region is studied with an emphasis on the signal-to-noise paradox of the North Atlantic Oscillation. Seasonal hindcasts of the ECMWF model for the recent period 1981-2009 show, in agreement with other studies, that correlation skill over Greenland and parts of the Arctic is higher than the signal-to-noise ratio implies. This leads to the paradoxical situation where the real world appears more predictable than the models suggest, with the forecast ensembles being overly dispersive (or underconfident). However, it is demonstrated that these conclusions are not supported by the diagnosed relationship between ensemble mean RMSE and ensemble spread which indicates a slight underdispersion (overconfidence). Furthermore, long atmospheric seasonal hindcasts suggest that over the 110-year period from 1900 to 2009 the ensemble system is well calibrated (neither over- nor underdispersive). The observed skill changed drastically in the middle of the 20th Century and paradoxical regions during more recent hindcast periods were strongly underdispersive during mid-Century decades.Due to non-stationarities of the climate system in the form of decadal variability, relatively short hindcasts are not sufficiently representative for longer-term behaviour. In addition, small hindcast sample size can lead to skill estimates, in particular of correlation measures, that are not robust. It is shown that the relative uncertainty due to small hindcast sample size is often larger for correlation-based than for RMSE-based diagnostics. Correlation-based measures like the RPC are shown to be highly sensitive to the strength of the predictable signal, implying that disentangling of physical deficiencies in the models on the one hand, and the effects of sampling uncertainty on the other hand, is difficult. Given the current lack of a causal physical mechanism to unravel the puzzle, our hypotheses of non-stationarity and sampling uncertainty provide simple yet plausible explanations for the paradox.
The ECMWF ensemble prediction system: Looking back (more than) 25 years and projecting forward 25 years
Quarterly Journal of the Royal Meteorological Society (2018)
Abstract:
© 2018 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. This paper has been written to mark 25 years of operational medium-range ensemble forecasting. The origins of the ECMWF Ensemble Prediction System are outlined, including the development of the precursor real-time Met Office monthly ensemble forecast system. In particular, the reasons for the development of singular vectors and stochastic physics – particular features of the ECMWF Ensemble Prediction System - are discussed. The author speculates about the development and use of ensemble prediction in the next 25 years.Estimates of flow-dependent predictability of wintertime Euro-Atlantic weather regimes in medium-range forecasts
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 144:713 (2018) 1012-1027
Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty
Quarterly Journal of the Royal Meteorological Society Wiley 144:715 (2018) 1947-1964