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

Climate Dynamics (2019)

C Yang, HM Christensen, S Corti, J von Hardenberg, P Davini

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. 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.

Experimental Non-Violation of the Bell Inequality

ENTROPY 20 (2019) ARTN 356

TN Palmer

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


CH O'Reilly, A Weisheimer, T Woollings, LJ Gray, D MacLeod

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

From reliable weather forecasts to skilful climate response: A dynamical systems approach

Quarterly Journal of the Royal Meteorological Society (2019)

HM Christensen, J Berner

© 2019 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. While weather forecasting models can be tested by performing and evaluating many hindcasts, the limited observational record restricts the degree to which climate projections can be evaluated. Therefore a question of interest is: to what degree can we evaluate the potential skill of a climate model's response to forcing by assessing the reliability of short-range weather and seasonal forecasts produced by the same model? We address this question using a dynamical systems framework. We use linear response theory to provide the mean climate response of a general dynamical system to a small external forcing. We relate this response to the reliability of initial value forecasts. We find that, in order to capture the mean climate response, the forecast model must correctly represent the slowest evolving modes of variability in the system. The reliability of forecasts on seasonal and longer time-scales, which is sensitive to the representation of these slow modes, could therefore indicate if the forecast model has the correct climate sensitivity and so will respond correctly to an applied external forcing. In this way, the skill of initialized forecasts could act as an ‘emergent constraint’ on climate sensitivity. However, we also highlight that unreliable seasonal forecasts do not necessarily indicate an incorrect climate projection. This is because correctly representing rapidly evolving modes is also necessary for reliable seasonal forecasts.

Scale-Selective Precision for Weather and Climate Forecasting

MONTHLY WEATHER REVIEW 147 (2019) 645-655

M Chantry, T Thornes, T Palmer, P Duben

Signal and noise in regime systems: A hypothesis on the predictability of the North Atlantic Oscillation

Quarterly Journal of the Royal Meteorological Society (2019)

K Strommen, TN Palmer

© 2018 Royal Meteorological Society Studies conducted by the UK Met Office reported significant skill in predicting the winter North Atlantic Oscillation (NAO) index with their seasonal prediction system. At the same time, a very low signal-to-noise ratio was observed, as measured using the “ratio of predictable components” (RPC) metric. We analyse both the skill and signal-to-noise ratio using a new statistical toy model, which assumes NAO predictability is driven by regime dynamics. It is shown that if the system is approximately bimodal in nature, with the model consistently underestimating the level of regime persistence each season, then both the high skill and high RPC value of the Met Office hindcasts can easily be reproduced. Underestimation of regime persistence could be attributable to any number of sources of model error, including imperfect regime structure or errors in the propagation of teleconnections. In particular, a high RPC value for a seasonal mean prediction may be expected even if the model's internal level of noise is realistic.

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

Climate Dynamics 52 (2019) 3759-3771

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

© 2018, The Author(s). 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 seasonal 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 extratropical cyclones and windstorms


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

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


M Matsueda, TN Palmer

Choosing the Optimal Numerical Precision for Data Assimilation in the Presence of Model Error


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

The benefits of global high-resolution for climate simulation: process-understanding and the enabling of stakeholder decisions at the regional scale.

Bulletin of the American Meteorological Society (2018)

MJ Roberts, PL Vidale, C Senior, HT Hewitt, C Bates, S Berthou, P Chang, HM Christensen, S Danilov, M-E Demory, SM Griffies, R Haarsma, T Jung, G Martin, S Minobe, T Ringler, M Satoh, R Schiemann, E Scoccimarro, G Stephens, MF Wehner

The Signature of Oceanic Processes in Decadal Extratropical SST Anomalies


CH O'Reilly, L Zanna

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


J Robson, RT Sutton, A Archibald, F Cooper, M Christensen, LJ Gray, NP Holliday, C Macintosh, M McMillan, B Moat, M Russo, R Tilling, K Carslaw, D Desbruyeres, O Embury, DL Feltham, DP Grosvenor, S Josey, B King, A Lewis, GD McCarthy, C Merchant, AL New, CH O'Reilly, SM Osprey, K Read, A Scaife, A Shepherd, B Sinha, D Smeed, D Smith, A Ridout, T Woollings, M Yang

Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?

CLIMATE DYNAMICS 50 (2018) 1161-1176

R Manzanas, A Lucero, A Weisheimer, JM Gutierrez

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


S Juricke, D MacLeod, A Weisheimer, L Zanna, TN Palmer

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...



ATT Mcrae, CJ Cotter, CJ Budd

On the Dynamical Mechanisms Governing El Nino-Southern Oscillation Irregularity

JOURNAL OF CLIMATE 31 (2018) 8401-8419

J Berner, PD Sardeshmukh, HM Christensen