Predictability of weather and climate

Abstract:

©2018. The Authors. We investigate the role of the tropics, the stratosphere, and atmosphere-ocean coupling for seasonal forecasts of strong, potentially damaging, Northern Hemisphere extratropical winter wind storm frequencies. This is done by means of relaxation experiments with the European Centre for Medium-Range Weather Forecasts model, which allow us to prescribe perfect forecasts for specific parts of the coupled atmosphere-ocean system. We find that perfect predictions of the Northern Hemisphere stratosphere significantly enhance winter storm predictive skill between eastern Greenland and Northern Europe. Correct seasonal predictions of the occurrence of stratospheric sudden warmings play a decisive role. The importance of correctly predicting the tropics and of two-way atmosphere-ocean coupling, both for forecasting stratospheric sudden warming risk and, correspondingly, severe winter storm frequency, is noted.

Abstract:

Extra‐tropical cyclones and their associated extreme wind speeds are a major cause of vast damage and large insured losses in several European countries. Reliable seasonal predictions of severe extra‐tropical winter cyclones and associated windstorms would thus have great social and economic benefits, especially in the insurance sector. We analyse the climatological representation and assess the seasonal prediction skill of wintertime extra‐tropical cyclones and windstorms in three multi‐member seasonal prediction systems: ECMWF‐System3, ECMWF‐System4 and Met Office‐GloSea5, based on hindcasts over a 20 year period (1992–2011). Small to moderate positive skill in forecasting the winter frequency of extra‐tropical cyclones and windstorms is found over most of the Northern Hemisphere. The skill is highest for extra‐tropical cyclones at the downstream end of the Pacific storm track and for windstorms at the downstream end of the Atlantic storm track. We also assess the forecast skill of windstorm frequency by using the North Atlantic Oscillation (NAO) as the predictor. Prediction skill improves when using this technique over parts of the British Isles and North Sea in GloSea5 and ECMWF‐S4, but reduces over central western Europe. This suggests that using the NAO is a simple and effective method for predicting wind storm frequency, but that increased forecast skill can be achieved in some regions by identifying windstorms directly using an objective tracking algorithm. Consequently, in addition to the large‐scale influence of the NAO, other factors may contribute to the predictability of wind storm frequency seen in existing forecast suites, across impact relevant regions of Europe. Overall, this study reveals for the first time significant skill in forecasting the winter frequency of high‐impact windstorms ahead of the season in regions that are vulnerable to such events.

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.

Abstract:

The North Atlantic Oscillation (NAO) is the leading mode of variability in the large scale circulation over the North Atlantic in winter, and strongly influences the weather and climate of Europe. On synoptic timescales, the negative phase of the NAO often corresponds to the occurrence of a blocking episode over Greenland. Hence, the dynamics and predictability of these blocking events is of interest for the prediction of the NAO and its related impacts over a wide region. Ensemble sensitivity analysis utilises the information contained in probabilistic forecast ensembles to calculate a statistical relationship between a forecast metric and some precursor condition. Here the method is applied to 15‐day forecasts of a set of 26 Greenland blocking events using the state‐of‐the‐art European Centre for Medium‐Range Weather Forecasts (ECMWF) forecasting system. The ensemble sensitivity analysis shows that Greenland blocking does not develop in isolation in these forecasts, but instead the blocking is sensitive to remote precursors, such as 500 hPa and 50 hPa geopotential height, particularly in the low‐frequency flow. In general, there are more significant sensitivities to anomalies in the tropics than in the polar regions. Stratospheric sensitivities tend to emerge at later lead times than tropospheric sensitivities. The strongest and most robust sensitivities correspond to a Rossby wave precursor reaching from the Pacific basin across North America.

Abstract:

This study investigates the influence of atmospheric initial conditions on winter seasonal forecasts of the North Atlantic Oscillation (NAO). Hindcast (or reforecast) experiments – which differ only in their initial conditions – are performed over the period 1960–2009, using prescribed sea surface temperature (SST) and sea‐ice boundary conditions. The first experiment (“ERA‐40/Int IC”) is initialized using the ERA‐40 and ERA‐Interim reanalysis datasets, which assimilate upper‐air, satellite and surface observations; the second experiment (“ERA‐20C IC”) is initialized using the ERA‐20C reanalysis dataset, which assimilates only surface observations. The ensemble mean NAO skill is largest in ERA‐40/Int IC (r = 0.54), which is initialized with the superior reanalysis data. Moreover, ERA‐20C IC did not exhibit significantly more NAO hindcast skill (r = 0.38) than in a third experiment, which was initialized with incorrect (shuffled) initial conditions. The ERA‐40/Interim and ERA‐20C initial conditions differ substantially in the tropical stratosphere, where the quasi‐biennial oscillation (QBO) of zonal winds is not present in ERA‐20C. The QBO hindcasts are highly skilful in ERA‐40/Int IC – albeit with a somewhat weaker equatorial zonal wind amplitude in the lower stratosphere – but are incorrect in ERA‐20C IC, indicating that the QBO is responsible for the additional NAO hindcast skill; this is despite the model exhibiting a relatively weak teleconnection between the QBO and NAO. The influence of the QBO is further demonstrated by regressing out the QBO influence from each of the hindcast experiments, after which the difference in NAO hindcast skill between the experiments is negligible. Whilst ERA‐40/Int IC demonstrates a more skilful NAO hindcast, it appears to have a relatively weak predictable signal; this is the so‐called “signal‐to‐noise paradox” identified in previous studies. Diagnostically amplifying the (weak) QBO–NAO teleconnection increases the ensemble‐mean NAO signal with negligible impact on the NAO hindcast skill, after which the signal‐to‐noise problem seemingly disappears.