The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model

Climate Dynamics Springer Berlin Heidelberg 53 (2019) 2843–2859-

C Yang, H Christensen, S Corti, J Von Hardenberg, P Davini

The impact of stochastic physics on El Niño Southern Oscillation (ENSO) is investigated in the EC-Earth coupled climate model. By comparing an ensemble of three members of control historical simulations with three ensemble members that include stochastics physics in the atmosphere, we find that in EC-Earth the implementation of stochastic physics improves the excessively weak representation of ENSO. Specifically, the amplitude of both El Niño and, to a lesser extent, La Niña increases. Stochastic physics also ameliorates the temporal variability of ENSO at interannual time scales, demonstrated by the emergence of peaks in the power spectrum with periods of 5–7 years and 3–4 years. Based on the analogy with the behaviour of an idealized delayed oscillator model (DO) with stochastic noise, we find that when the atmosphere–ocean coupling is small (large) the amplitude of ENSO increases (decreases) following an amplification of the noise amplitude. The underestimated ENSO variability in the EC-Earth control runs and the associated amplification due to stochastic physics could be therefore consistent with an excessively weak atmosphere–ocean coupling. The activation of stochastic physics in the atmosphere increases westerly wind burst (WWB) occurrences (i.e. amplification of noise amplitude) that could trigger more and stronger El Niño events (i.e. increase of ENSO oscillation) in the coupled EC-Earth model. Further analysis of the mean state bias of EC-Earth suggests that a cold sea surface temperature (SST) and dry precipitation bias in the central tropical Pacific together with a warm SST and wet precipitation bias in the western tropical Pacific are responsible for the coupled feedback bias (weak coupling) in the tropical Pacific that is related to the weak ENSO simulation. The same analysis of the ENSO behaviour is carried out in a future scenario experiment (RCP8.5 forcing), highlighting that in a coupled model with an extreme warm SST, characterized by a strong coupling, the effect of stochastic physics on the ENSO representation is opposite. This corroborates the hypothesis that the mean state bias of the tropical Pacific region is the main reason for the ENSO representation deficiency in EC-Earth.

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 ECMWF ensemble prediction system: Looking back (more than) 25 years and projecting forward 25 years

Quarterly Journal of the Royal Meteorological Society (2018)

T Palmer

© 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.

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

Scale-Selective Precision for Weather and Climate Forecasting

MONTHLY WEATHER REVIEW 147 (2019) 645-655

M Chantry, T Thornes, T Palmer, P Duben

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.

Energy budget-based backscatter in a shallow water model of a double gyre basin

OCEAN MODELLING 132 (2018) 1-11

M Kloewer, MF Jansen, M Claus, RJ Greatbatch, S Thomsen

Estimates of flow-dependent predictability of wintertime Euro-Atlantic weather regimes in medium-range forecasts


M Matsueda, TN Palmer

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.

Choosing the optimal numerical precision for data assimilation in the presence of model error

Journal of Advances in Modeling Earth Systems American Geophysical Union 10 (2018) 2177-2191

S Hatfield, P Düben, M Chantry, K Kondo, T Miyoshi, T Palmer

The use of reduced numerical precision within an atmospheric data assimilation system is investigated. An atmospheric model with a spectral dynamical core is used to generate synthetic observations, which are then assimilated back into the same model using an ensemble Kalman filter. The effect on the analysis error of reducing precision from 64 bits to only 22 bits is measured and found to depend strongly on the degree of model uncertainty within the system. When the model used to generate the observations is identical to the model used to assimilate observations, the reduced‐precision results suffer substantially. However, when model error is introduced by changing the diffusion scheme in the assimilation model or by using a higher‐resolution model to generate observations, the difference in analysis quality between the two levels of precision is almost eliminated. Lower‐precision arithmetic has a lower computational cost, so lowering precision could free up computational resources in operational data assimilation and allow an increase in ensemble size or grid resolution.

The signature of oceanic processes in decadal extratropical SST anomalies

Geophysical Research Letters John Wiley & Sons 45 (2018) 7719-7730

C O'Reilly, L Zanna

The relationship between decadal SST and turbulent heat‐fluxes is assessed and used to identify where oceanic processes play an important role in extratropical decadal SST variability. In observational datasets and coupled climate model simulations from the CMIP5 archive, positive correlations between upward turbulent heat flux and SSTs indicate an active role of oceanic processes over regions in the North Atlantic, Northwest Pacific, Southern Pacific and Southern Atlantic. The contrasting nature of oceanic influence on decadal SST anomalies in the Northwest Pacific and North Atlantic is identified. Over the Northwest Pacific, SST anomalies are consistent with changes in the horizontal wind‐driven gyre circulation on timescales of between 3‐7 years, in both the observations and models. Over the North Atlantic, SST anomalies are also preceded by atmospheric circulation anomalies, though the response is stronger at longer timescales ‐ peaking at around 20‐years in the observations and at around 10‐years in the models.

Recent observed changes in the North Atlantic climate system with a focus on 2005-2016

International Journal of Climatology John Wiley & Sons, Inc. 38 (2018) 5050-5076

J Robson, A Archibald, F Cooper, M Christensen, L Grey, NP Holliday, C Macintosh, M McMillan, B Moat, K Carslaw, O Embury, D Feltham, D Grosvenor, S Josey, B King, A Lewis, GD McCarthy, C Merchant, AL New, C O'Reilly, S Osprey, K Read, A Scaife, A Shepherd

Major changes are occurring across the North Atlantic climate system, including in the atmosphere, ocean and cryosphere, and many observed changes are unprecedented in instrumental records. As the changes in the North Atlantic directly affect the climate and air quality of the surrounding continents, it is important to fully understand how and why the changes are taking place, not least to predict how the region will change in the future. To this end, this article characterizes the recent observed changes in the North Atlantic region, especially in the period 2005–2016, across many different aspects of the system including: atmospheric circulation; atmospheric composition; clouds and aerosols; ocean circulation and properties; and the cryosphere. Recent changes include: an increase in the speed of the North Atlantic jet stream in winter; a southward shift in the North Atlantic jet stream in summer, associated with a weakening summer North Atlantic Oscillation; increases in ozone and methane; increases in net absorbed radiation in the mid‐latitude western Atlantic, linked to an increase in the abundance of high level clouds and a reduction in low level clouds; cooling of sea surface temperatures in the North Atlantic subpolar gyre, concomitant with increases in the western subtropical gyre, and a decline in the Atlantic Ocean's overturning circulation; a decline in Atlantic sector Arctic sea ice and rapid melting of the Greenland Ice Sheet. There are many interactions between these changes, but these interactions are poorly understood. This article concludes by highlighting some of the key outstanding questions.

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.

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 scaling and skewness of optimally transported meshes on the sphere

Journal of Computational Physics Elsevier 375 (2018) 540-564

CJ Budd, ATT McRae, CJ Cotter

In the context of numerical solution of PDEs, dynamic mesh redistribution methods (r-adaptive methods) are an important procedure for increasing the resolution in regions of interest, without modifying the connectivity of the mesh. Key to the success of these methods is that the mesh should be sufficiently refined (locally) and flexible in order to resolve evolving solution features, but at the same time not introduce errors through skewness and lack of regularity. Some state-of-the-art methods are bottom-up in that they attempt to prescribe both the local cell size and the alignment to features of the solution. However, the resulting problem is overdetermined, necessitating a compromise between these conflicting requirements. An alternative approach, described in this paper, is to prescribe only the local cell size and augment this an optimal transport condition to provide global regularity. This leads to a robust and flexible algorithm for generating meshes fitted to an evolving solution, with minimal need for tuning parameters. Of particular interest for geophysical modelling are meshes constructed on the surface of the sphere. The purpose of this paper is to demonstrate that meshes generated on the sphere using this optimal transport approach have good a-priori regularity and that the meshes produced are naturally aligned to various simple features. It is further shown that the sphere's intrinsic curvature leads to more regular meshes than the plane. In addition to these general results, we provide a wide range of examples relevant to practical applications, to showcase the behaviour of optimally transported meshes on the sphere. These range from axisymmetric cases that can be solved analytically to more general examples that are tackled numerically. Evaluation of the singular values and singular vectors of the mesh transformation provides a quantitative measure of the mesh aniso...

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.

Forcing single column models using high-resolution model simulations

Journal of Advances in Modeling Earth Systems Wiley 10 (2018) 1833-1857

HM Christensen, A Dawson, CE Holloway

To use single column models (SCMs) as a research tool for parametrisation development and process studies, the SCM must be supplied with realistic initial profiles, forcing fields and boundary conditions. We propose a new technique for deriving these required profiles, motivated by the increase in number and scale of high-resolution convection-permitting simulations. We suggest that these high-resolution simulations be coarse-grained to the required resolution of an SCM, and thereby be used as a proxy for the ‘true’ atmosphere. This paper describes the implementation of such a technique. We test the proposed methodology using high-resolution data from the UK Met Office’s Unified Model (MetUM), with a resolution of 4 km, covering a large tropical domain. This data is coarse grained and used to drive the European Centre for Medium-Range Weather Forecast’s (ECMWF) Integrated Forecasting System (IFS) SCM. The proposed method is evaluated by deriving IFS SCM forcing profiles from a consistent T639 IFS simulation. The SCM simulations track the global model, indicating a consistency between the estimated forcing fields and the ‘true’ dynamical forcing in the global model. We demonstrate the benefits of selecting SCM forcing profiles from across a large-domain, namely robust statistics, and the ability to test the SCM over a range of boundary conditions. We also compare driving the SCM with the coarse-grained dataset to driving it using the ECMWF operational analysis. We conclude by highlighting the importance of understanding biases in the high-resolution dataset, and suggest that our approach be used in combination with observationally derived forcing datasets.

On the dynamical mechanisms governing El Niño-Southern Oscillation irregularity

Journal of Climate American Meteorological Society 31 (2018) 8401-8419

J Berner, PD Sardeshmukh, H Christensen

This study investigates the mechanisms by which short-timescale perturbations to atmospheric processes can affect El Niño-Southern Oscillation (ENSO) in climate models. To this end a control simulation of NCAR’s Community Climate System Model is compared to a simulation in which the model’s atmospheric diabatic tendencies are perturbed every time step using a Stochastically Perturbed Parameterized Tendencies (SPPT) scheme. The SPPT simulation compares better with ECMWF’s 20th-century reanalysis in having lower inter-annual sea surface temperature (SST) variability and more irregular transitions between El Niño and La Niña states, as expressed by a broader, less peaked spectrum. Reduced-order linear inverse models (LIMs) derived from the 1-month lag covariances of selected tropical variables yield good representations of tropical interannual variability in the two simulations. In particular, the basic features of ENSO are captured by the LIM’s least-damped oscillatory eigenmode. SPPT reduces the damping timescale of this eigenmode from 17 to 11 months, which is in better agreement with the 8 months obtained from reanalyses. This noise-induced stabilization is consistent with perturbations to the frequency of the ENSO eigenmode and explains the broadening of the SST spectrum (that is, the greater ENSO irregularity). Although the improvement in ENSO shown here was achieved through stochastic physics parameterizations, it is possible that similar improvements could be realized through changes in deterministic parameterizations or higher numerical resolution. It is suggested LIMs could provide useful insight into model sensitivities, uncertainties, and biases also in those cases.