Publications by Antje Weisheimer

Seasonal forecasts of the 20th century

Bulletin of the American Meteorological Society American Meteorological Society 101 (2020) E1413-E1426

A Weisheimer, D Befort, D Macleod, T Palmer, C O’Reilly, K Strømmen

<p>New seasonal retrospective forecasts for 1901-2010 show that skill for predicting ENSO, NAO and PNA is reduced during mid-century periods compared to earlier and more recent high-skill decades.</p> <p>Forecasts of seasonal climate anomalies using physically-based global circulation models are routinely made at operational meteorological centers around the world. A crucial component of any seasonal forecast system is the set of retrospective forecasts, or hindcasts, from past years which are used to estimate skill and to calibrate the forecasts. Hindcasts are usually produced over a period of around 20-30 years. However, recent studies have demonstrated that seasonal forecast skill can undergo pronounced multi-decadal variations. These results imply that relatively short hindcasts are not adequate for reliably testing seasonal forecasts and that small hindcast sample sizes can potentially lead to skill estimates that are not robust. Here we present new and unprecedented 110-year-long coupled hindcasts of the next season over the period 1901 to 2010. Their performance for the recent period is in good agreement with those of operational forecast models. While skill for ENSO is very high during recent decades, it is markedly reduced during the 1930s to 1950s. Skill at the beginning of the 20th Century is, however, as high as for recent high-skill periods. Consistent with findings in atmosphere-only hindcasts, a mid-century drop in forecast skill is found for a range of atmospheric fields including large-scale indices such as the NAO and the PNA patterns. As with ENSO, skill scores for these indices recover in the early 20th Century suggesting that the mid-century drop in skill is not due to lack of good observational data.</p> <p>A public dissemination platform for our hindcast data is available and we invite the scientific community to explore them.</p>

Anthropogenic influence on the 2018 summer warm spell in Europe: the impact of different spatio-temporal scales

Bulletin of the American Meteorological Society American Meteorological Society 101 (2020) S41-S46

N Leach, S Li, S Sparrow, GJ Van Oldenborgh, FC Lott, A Weisheimer, Allen

We demonstrate that, in attribution studies, events defined over longer time scales generally produce higher probability ratios due to lower interannual variability, reconciling seemingly inconsistent attribution results of Europe’s 2018 summer heatwaves in reported studies.

SEAS5: the new ECMWF seasonal forecast system


SJ Johnson, TN Stockdale, L Ferranti, MA Balmaseda, F Molteni, L Magnusson, S Tietsche, D Decremer, A Weisheimer, G Balsamo, SPE Keeley, K Mogensen, H Zuo, BM Monge-Sanz

Factors Influencing the Seasonal Predictability of Northern Hemisphere Severe Winter Storms

Geophysical Research Letters (2019)

F Hansen, T Kruschke, RJ Greatbatch, A Weisheimer

©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.

The importance of stratospheric initial conditions for winter North Atlantic Oscillation predictability and implications for the signal‐to‐noise paradox

Quarterly Journal of the Royal Meteorological Society John Wiley and Sons, Ltd. 145 (2018) Part A, 131-146

C O'Reilly, A Weisheimer, T Woollings, L Gray, D Macleod

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.

How confident are predictability estimates of the winter North Atlantic Oscillation?

Quarterly Journal of the Royal Meteorological Society Wiley (2018) qj.3446

A Weisheimer, D Decremer, D MacLeod, C O’Reilly, TN Stockdale, S Johnson, TN Palmer

Seasonal predictability of the winter North Atlantic Oscillation from a jet stream perspective

Geophysical Research Letters Wiley 46 (2019) 10159-10167

T Parker, T Woollings, A Weisheimer, C O'Reilly, L Baker, L Shaffrey

The winter North Atlantic Oscillation (NAO) has varied on interannual and decadal timescales over the last century, associated with variations in the speed and latitude of the eddy driven jet stream. This paper uses hindcasts from two operational seasonal forecast sys tems (the European Centre for Medium-range Weather Forecasts (ECMWF)’s seasonal forecast system, and the UK Met Office global seasonal forecast system) and a century long atmosphere-only experiment (using the ECMWF’s Integrated Forecasting System model) to relate seasonal prediction skill in the NAO to these aspects of jet variability. This shows that the NAO skill realised so far arises from interannual variations in the jet, largely associated with its latitude rather than speed. There likely remains further potential for predictability on longer, decadal timescales. In the small sample of mod els analysed here, improved representation of the structure of jet variability does not trans late to enhanced seasonal forecast skill.

An interdecadal shift of the extratropical teleconnection from the tropical Pacific during boreal summer

Geophysical Research Letters American Geophysical Union 46 (2019) 13379-13388

C O'Reilly, T Woollings, L Zanna, A Weisheimer

The extratropical teleconnection from the tropical Pacific in boreal summer exhibits a significant shift over the past 70 years. Cyclonic circulation anomalies over the North Atlantic and Eurasia associated with El Niño in the later period (1978‐2014) are absent in the earlier period (1948‐1977). An initialised atmospheric model ensemble, performed with prescribed sea surface temperature (SST) boundary conditions, replicates some key features of the shift in the teleconnection, providing clear evidence that this shift is not simply due to internal atmospheric variability or random sampling. Additional ensemble simulations, one with detrended tropical SSTs and another with constant external forcing are analysed. In the model, the teleconnection shift is associated with climatological atmospheric circulation changes, which are substantially reduced in the simulation with detrended tropical SSTs. These results demonstrate that the climatological atmospheric circulation and associated teleconnection changes are largely forced by tropical SST trends.

The northern hemisphere circumglobal teleconnection in a seasonal forecast model and its relationship to European summer forecast skill

Climate Dynamics Springer Verlag 52 (2018) 3759–3771-

JD Beverley, SJ Woolnough, LH Baker, SJ Johnson, A Weisheimer

Forecasting seasonal variations in European summer weather represents a considerable challenge. Here, we assess the performance of a seasonal forecasting model at representing a major mode of northern hemisphere summer climate variability, the circumglobal teleconnection (CGT), and the implications of errors in its representation on sea7 sonal forecasts for the European summer (June, July, August). Using seasonal hindcasts initialised at the start of May, we find that the model skill for forecasting the interannual variability of 500 hPa geopotential height is poor, particularly over Europe and several other “centres of action” of the CGT. The model also has a weaker CGT pattern than is observed, particularly in August, when the observed CGT wavetrain is strongest. We investigate several potential causes of this poor skill. First, model variance in geopotential height in west-central Asia (an important region for the maintenance of the CGT) is lower than observed in July and August, associated with a poor representation of the link between this region and Indian monsoon precipitation. Second, analysis of the Rossby wave source shows that the source associated with monsoon heating is both too strong and displaced to the northeast in the model. This is related to errors in monsoon precipitation over the Bay of Bengal and Arabian Sea, where the model has more precipitation than is observed. Third the model jet is systematically shifted northwards by several degrees latitude over large parts of the northern hemisphere, which may affect the propagation characteristics of Rossby waves in the model.

Seasonal forecast skill for extra‐tropical cyclones and windstorms

Quarterly Journal of the Royal Meteorological Society Wiley 145 (2018) 92-104

DJ Befort, S Wild, Knight, JF Lockwood, HE Thornton, L Hermanson, PE Bett, A Weisheimer, GC Leckebusch

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.

Predicting El Niño in 2014 and 2015

Scientific Reports Springer Nature 8 (2018) 10733

S Ineson, M Balmaseda, MK Davey, D Decremer, N Dunstone, M Gordon, H Ren, A Scaife, A Weisheimer

Early in 2014 several forecast systems were suggesting a strong 1997/98-like El Niño event for the following northern hemisphere winter 2014/15. However the eventual outcome was a modest warming. In contrast, winter 2015/16 saw one of the strongest El Niño events on record. Here we assess the ability of two operational seasonal prediction systems to forecast these events, using the forecast ensembles to try to understand the reasons underlying the very different development and outcomes for these two years. We test three hypotheses. First we find that the continuation of neutral ENSO conditions in 2014 is associated with the maintenance of the observed cold southeast Pacific sea surface temperature anomaly; secondly that, in our forecasts at least, warm west equatorial Pacific sea surface temperature anomalies do not appear to hinder El Niño development; and finally that stronger westerly wind burst activity in 2015 compared to 2014 is a key difference between the two years. Interestingly, in these years at least, this interannual variability in wind burst activity is predictable. ECMWF System 4 tends to produce more westerly wind bursts than Met Office GloSea5 and this likely contributes to the larger SST anomalies predicted in this model in both years.

An intercomparison of skill and over/underconfidence of the wintertime North Atlantic Oscillation in multi-model seasonal forecasts

Geophysical Research Letters American Geophysical Union 45 (2018) 7808-7817

LH Baker, LC Shaffrey, A Weisheimer, AA Scaife

Recent studies of individual seasonal forecast systems have shown that the wintertime North Atlantic Oscillation (NAO) can be skilfully forecast. However, it has also been suggested that these skilful forecasts tend to be underconfident, meaning that there is too high a proportion of unpredictable noise in the forecasts. We assess the skill and over/underconfidence of the seasonal forecast systems contributing to the EUROSIP multi‐model ensemble system. Five of the seven systems studied have significant skill for forecasting the wintertime NAO at 2–4 month lead‐times. Four of these skilful systems are underconfident for forecasting the NAO. A multi‐model ensemble (ensemble size 126 members) is both skilful and clearly underconfident. Underconfidence becomes more pronounced as the ensemble size increases. Certain years in the hindcast period are well forecast by all or most models. This implies that common teleconnections and drivers of the NAO are being captured by the EUROSIP seasonal forecasts.

Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users

Climate Dynamics (2017) 1-20

A Alessandri, MD Felice, F Catalano, JY Lee, B Wang, DY Lee, JH Yoo, A Weisheimer

© 2017 Springer-Verlag GmbH Germany Multi-model ensembles (MMEs) are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single-model ensembles. Previous works suggested that the potential benefit that can be expected by using a MME amplifies with the increase of the independence of the contributing Seasonal Prediction Systems. In this work we combine the two MME Seasonal Prediction Systems (SPSs) independently developed by the European (ENSEMBLES) and by the Asian-Pacific (APCC/CliPAS) communities. To this aim, all the possible multi-model combinations obtained by putting together the 5 models from ENSEMBLES and the 11 models from APCC/CliPAS have been evaluated. The grand ENSEMBLES-APCC/CliPAS MME enhances significantly the skill in predicting 2m temperature and precipitation compared to previous estimates from the contributing MMEs. Our results show that, in general, the better combinations of SPSs are obtained by mixing ENSEMBLES and APCC/CliPAS models and that only a limited number of SPSs is required to obtain the maximum performance. The number and selection of models that perform better is usually different depending on the region/phenomenon under consideration so that all models are useful in some cases. It is shown that the incremental performance contribution tends to be higher when adding one model from ENSEMBLES to APCC/CliPAS MMEs and vice versa, confirming that the benefit of using MMEs amplifies with the increase of the independence the contributing models. To verify the above results for a real world application, the Grand ENSEMBLES-APCC/CliPAS MME is used to predict retrospective energy demand over Italy as provided by TERNA (Italian Transmission System Operator) for the period 1990–2007. The results demonstrate the useful application of MME seasonal predictions for energy demand forecasting over Italy. It is shown a significant enhancement of the potential economic value of forecasting energy demand when using the better combinations from the Grand MME by comparison to the maximum value obtained from the better combinations of each of the two contributing MMEs. The above results demonstrate for the first time the potential of the Grand MME to significantly contribute in obtaining useful predictions at the seasonal time-scale.

Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty

Quarterly Journal of the Royal Meteorological Society Wiley 144 (2018) 1947-1964

S Juricke, D Macleod, A Weisheimer, L Zanna, T Palmer

Accurate forecasts of the ocean state and the estimation of forecast uncertainties are crucial when it comes to providing skilful seasonal predictions. In this study we analyse the predictive skill and reliability of the ocean component in a seasonal forecasting system. Furthermore, we assess the effects of accounting for model and observational uncertainties. Ensemble forcasts are carried out with an updated version of the ECMWF seasonal forecasting model System 4, with a forecast length of ten months, initialized every May between 1981 and 2010. We find that, for essential quantities such as sea surface temperature and upper ocean 300 m heat content, the ocean forecasts are generally underdispersive and skilful beyond the first month mainly in the Tropics and parts of the North Atlantic. The reference reanalysis used for the forecast evaluation considerably affects diagnostics of forecast skill and reliability, throughout the entire ten‐month forecasts but mostly during the first three months. Accounting for parametrization uncertainty by implementing stochastic parametrization perturbations has a positive impact on both reliability (from month 3 onwards) as well as forecast skill (from month 8 onwards). Skill improvements extend also to atmospheric variables such as 2 m temperature, mostly in the extratropical Pacific but also over the midlatitudes of the Americas. Hence, while model uncertainty impacts the skill of seasonal forecasts, observational uncertainty impacts our assessment of that skill. Future ocean model development should therefore aim not only to reduce model errors but to simultaneously assess and estimate uncertainties.

The impact of tropical precipitation on summertime Euro-Atlantic circulation via a circumglobal wave-train

Journal of Climate American Meteorological Society 31 (2018) 6481-6504

C O'Reilly, T Woollings, L Zanna, A Weisheimer

The influence of tropical precipitation variability on summertime seasonal circulation anomalies in the Euro-Atlantic sector is investigated. The dominant mode of the maximum covariance analysis (MCA) between the Euro-Atlantic circulation and tropical precipitation reveals a cyclonic anomaly over the extratropical North Atlantic, contributing to anomalously wet conditions over western Europe and dry conditions over eastern Europe and Scandinavia (in the positive phase). The related mode of tropical precipitation variability is associated with tropical Pacific SST anomalies and is closely linked to the El Niño/Southern Oscillation (ENSO). The second MCA mode consists of weaker tropical precipitation anomalies but a stronger extratropical signal which reflects internal atmospheric variability. The teleconnection mechanism is tested in barotropic model simulations, which indicate that the observed link between the dominant mode of tropical precipitation and the Euro-Atlantic circulation anomalies is largely consistent with linear Rossby wave dynamics. The barotropic model response consists of a circumglobal wave-train in the extratropics that is primarily forced by divergence anomalies in the eastern tropical Pacific. Both the eastward and westward group propagation of the Rossby waves are found to be important in determining the circulation response over the Euro-Atlantic sector. The mechanism was also analysed in an operational seasonal forecasting system, ECMWF’s System 4. Whilst System 4 is well able to reproduce and skillfully forecast the tropical precipitation, the extratropical circulation response is absent over the Euro-Atlantic region, which is likely related to biases in the Asian jetstream.

Ensemble sensitivity analysis of Greenland blocking in medium‐range forecasts

Quarterly Journal of the Royal Meteorological Society Wiley 144 (2018) 2358-2379

T Parker, T Woollings, A Weisheimer

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.

A Simple Pedagogical Model linking Initial-Value Reliability with Trustworthiness in the Forced Climate Response.

Bulletin of the American Meteorological Society (2017)

TN Palmer, A Weisheimer

Flow dependent ensemble spread in seasonal forecasts of the boreal winter extratropics

Atmospheric Science Letters Royal Meteorological Society 19 (2018) e815

D MacLeod, C O'Reilly, T Palmer, A Weisheimer

Flow-dependent spread (FDS) is a desirable characteristic of probabilistic forecasts; ensemble spread should represent the expected forecast error. However this is difficult to estimate for seasonal hindcasts as they tend to have a relatively small sample size. Here we use a long (110 year) seasonal hindcast dataset to evaluate FDS in forecasts of boreal winter North Atlantic Oscillation (NAO) and Pacific North American pattern (PNA). A good FDS relationship is found for interannual variations in both the NAO and PNA , with mild underdispersion for negative NAO and PNA events and slight overdispersion for positive NAO. Decadal-scale variability is seen in forecast errors but not in ensemble spread, which shows little variation on this timescale. Links between forecast errors and tropical heating anomalies are also investigated, though no strong links are found. However a weak link between strong El Niño warming in the East Pacific and reduced PNA error is suggested.

Stochastic representations of model uncertainties at ECMWF: state of the art and future vision

Quarterly Journal of the Royal Meteorological Society Wiley 143 (2017) 2315-2339

M Leutbecher, S-J Lock, P Ollinaho, STK Lang, G Balsamo, P Bechtold, M Bonavita, HM Christensen, M Diamantakis, E Dutra, S English, M Fisher, R Forbes, J Goddard, T Haiden, R Hogan, S Juricke, H Lawrence, S Malardel, S Massart, I Sandu, P Smolarkiewicz, A Subramanian, F Vitart, N Wedi

Members in ensemble forecasts differ due to the representations of initial uncertainties and model uncertainties. The inclusion of stochastic schemes to represent model uncertainties has improved the probabilistic skill of the ECMWF ensemble by increasing reliability and reducing the error of the ensemble mean. Recent progress, challenges and future directions regarding stochastic representations of model uncertainties at ECMWF are described in this paper. The coming years are likely to see a further increase in the use of ensemble methods in forecasts and assimilation. This will put increasing demands on the methods used to perturb the forecast model. An area that is receiving a greater attention than 5 to 10 years ago is the physical consistency of the perturbations. Other areas where future efforts will be directed are the expansion of uncertainty representations to the dynamical core and to other components of the Earth system as well as the overall computational efficiency of representing model uncertainty.

Approximately right or precisely wrong? Meeting report on "Chaos and Confidence in Weather Forecasting'

WEATHER 72 (2017) 301-302

A Weisheimer