Publications


Patterns in Wall-Bounded Shear Flows

, 2020

LS Tuckerman, M Chantry, D Barkley


Seasonal forecasts of the 20th century

Bulletin of the American Meteorological Society American Meteorological Society (2020) BAMS-D-19-0019.1

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

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. 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. A public dissemination platform for our hindcast data is available and we invite the scientific community to explore them.


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.


Tropical atmospheric drivers of wintertime European precipitation events

Quarterly Journal of the Royal Meteorological Society Wiley 146 (2019) 780-794

KKR Li, T Woollings, C O'Reilly, A Scaife

From observations, we identify a wave‐like pattern associated with northwestern European seasonal precipitation events. These events are associated with tropical precipitation anomalies, prompting us to investigate if there are any tropical–extratropical teleconnections, in particular the role of tropical anomalies in driving extratropical dynamics through Rossby wave propagation. Using a hierarchy of models from ray tracing to barotropic and baroclinic models, we investigate the Rossby wave mechanism and test potential tropical drivers and yield qualitative results. Using a barotropic model, we identify potential Rossby wave source regions which are consistent between the observations and the model. These regions include the tropical western and eastern Atlantic, the subtropical eastern Atlantic and, to a smaller degree, the subtropical eastern Pacific. Zonal wavenumber 2 and 3 components of the barotropic model responses match well with the observations and ray tracing supports the importance of these components. We use a baroclinic model to investigate the link between the observed Rossby wave source anomalies and the observed tropical precipitation anomalies. The reduced precipitation observed in the tropical Atlantic just north of the Equator can generate some of the observed Rossby wave source anomalies in the tropical Atlantic, while the increased precipitation observed in the tropical eastern Pacific can generate some of the observed Rossby wave source anomalies in the subtropical eastern Pacific. Our results can also be applied to European drought events because of the qualitative linearity in the observations and in our linear methods.


Euro-Atlantic weather Regimes in the PRIMAVERA coupled climate simulations: impact of resolution and mean state biases on model performance

Climate Dynamics Springer Science and Business Media LLC 54 (2020) 5031-5048

F Fabiano, H Christensen, K Strommen, P Athanasiadis, A Baker, R Schiemann, S Corti


Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz’96 Model

Journal of Advances in Modeling Earth Systems American Geophysical Union 12 (2020) e2019MS001896

DJ Gagne, HM Christensen, AC Subramanian, AH Monahan

Stochastic parameterizations account for uncertainty in the representation of unresolved subgrid processes by sampling from the distribution of possible subgrid forcings. Some existing stochastic parameterizations utilize data‐driven approaches to characterize uncertainty, but these approaches require significant structural assumptions that can limit their scalability. Machine learning models, including neural networks, are able to represent a wide range of distributions and build optimized mappings between a large number of inputs and subgrid forcings. Recent research on machine learning parameterizations has focused only on deterministic parameterizations. In this study, we develop a stochastic parameterization using the generative adversarial network (GAN) machine learning framework. The GAN stochastic parameterization is trained and evaluated on output from the Lorenz '96 model, which is a common baseline model for evaluating both parameterization and data assimilation techniques. We evaluate different ways of characterizing the input noise for the model and perform model runs with the GAN parameterization at weather and climate time scales. Some of the GAN configurations perform better than a baseline bespoke parameterization at both time scales, and the networks closely reproduce the spatiotemporal correlations and regimes of the Lorenz '96 system. We also find that, in general, those models which produce skillful forecasts are also associated with the best climate simulations.


Reduced-precision parametrization: lessons from an intermediate-complexity atmospheric model

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY (2020)

L Saffin, S Hatfield, P Duben, T Palmer

© 2020 Royal Meteorological Society Reducing numerical precision can save computational costs which can then be reinvested for more useful purposes. This study considers the effects of reducing precision in the parametrizations of an intermediate complexity atmospheric model (SPEEDY). We find that the difference between double-precision and reduced-precision parametrization tendencies is proportional to the expected machine rounding error if individual timesteps are considered. However, if reduced precision is used in simulations that are compared to double-precision simulations, a range of precision is found where differences are approximately the same for all simulations. Here, rounding errors are small enough to not directly perturb the model dynamics, but can perturb conditional statements in the parametrizations (such as convection active/inactive) leading to a similar error growth for all runs. For lower precision, simulations are perturbed significantly. Precision cannot be constrained without some quantification of the uncertainty. The inherent uncertainty in numerical weather and climate models is often explicitly considered in simulations by stochastic schemes that will randomly perturb the parametrizations. A commonly used scheme is stochastic perturbation of parametrization tendencies (SPPT). A strong test on whether a precision is acceptable is whether a low-precision ensemble produces the same probability distribution as a double-precision ensemble where the only difference between ensemble members is the model uncertainty (i.e., the random seed in SPPT). Tests with SPEEDY suggest a precision as low as 3.5 decimal places (equivalent to half precision) could be acceptable, which is surprisingly close to the lowest precision that produces similar error growth in the experiments without SPPT mentioned above. Minor changes to model code to express variables as anomalies rather than absolute values reduce rounding errors and low-precision biases, allowing even lower precision to be used. These results provide a pathway for implementing reduced-precision parametrizations in more complex weather and climate models.


Revisiting the Identification ofWintertime Atmospheric Circulation Regimes in the Euro‐Atlantic Sector

Quarterly Journal of the Royal Meteorological Society Wiley (2020) qj.3818

SKJ Falkena, J de Wiljes, A Weisheimer, TG Shepherd


Constraining stochastic parametrisation schemes using high-resolution simulations

Quarterly Journal of the Royal Meteorological Society Wiley 146 (2020) 938-962

H Christensen

Stochastic parametrisations can be used in weather and climate models to improve the representation of unpredictable unresolved processes. When compared with a deterministic model, a stochastic model represents “model uncertainty”, that is, sources of error in the forecast due to the limitations of the forecast model. A technique is presented for systematically deriving new stochastic parametrisations or constraining existing stochastic approaches. A high‐resolution model simulation is coarse‐grained to the desired forecast model resolution. This provides the initial conditions and forcing data needed to drive a single‐column model (SCM). Comparing the SCM parametrised tendencies with the evolution of the high‐resolution model provides an estimate of the error in the SCM tendencies that a stochastic parametrisation seeks to represent. This approach is used to assess the physical basis of the widely used stochastically perturbed parametrisation tendencies (SPPT) scheme. Justification is found for the multiplicative nature of SPPT, along with some evidence for the use of spatio‐temporally correlated stochastic perturbations. Evidence that the stochastic perturbation should be positively skewed is found, indicating that occasional large‐magnitude positive perturbations are physically realistic. However, other key assumptions of SPPT are less well justified, including coherency of the stochastic perturbations with height, coherency of the perturbations for different physical parametrisation schemes, and coherency for different prognostic variables. Relaxing these SPPT assumptions allows for an error model that explains a larger fractional variance than traditional SPPT. In particular, it is suggested that independently perturbing the tendencies associated with different parametrisation schemes is justifiable and would improve the realism of the SPPT approach.


Discretization of the Bloch sphere, fractal invariant sets and Bell's theorem.

Proceedings. Mathematical, physical, and engineering sciences 476 (2020) 20190350-

TN Palmer

An arbitrarily dense discretization of the Bloch sphere of complex Hilbert states is constructed, where points correspond to bit strings of fixed finite length. Number-theoretic properties of trigonometric functions (not part of the quantum-theoretic canon) are used to show that this constructive discretized representation incorporates many of the defining characteristics of quantum systems: completementarity, uncertainty relationships and (with a simple Cartesian product of discretized spheres) entanglement. Unlike Meyer's earlier discretization of the Bloch Sphere, there are no orthonormal triples, hence the Kocken-Specker theorem is not nullified. A physical interpretation of points on the discretized Bloch sphere is given in terms of ensembles of trajectories on a dynamically invariant fractal set in state space, where states of physical reality correspond to points on the invariant set. This deterministic construction provides a new way to understand the violation of the Bell inequality without violating statistical independence or factorization, where these conditions are defined solely from states on the invariant set. In this finite representation, there is an upper limit to the number of qubits that can be entangled, a property with potential experimental consequences.


The physics of numerical analysis: a climate modelling case study.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 378 (2020) 20190058-

T Palmer

The case is made for a much closer synergy between climate science, numerical analysis and computer science. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.


Human creativity and consciousness: Unintended consequences of the brain's extraordinary energy efficiency?

Entropy 22 (2020)

T Palmer

© 2020 by authors. It is proposed that both human creativity and human consciousness are (unintended) consequences of the human brain's extraordinary energy efficiency. The topics of creativity and consciousness are treated separately, though have a common sub-structure. It is argued that creativity arises from a synergy between two cognitive modes of the human brain (which broadly coincide with Kahneman's Systems 1 and 2). In the first, available energy is spread across a relatively large network of neurons, many of which are small enough to be susceptible to thermal (ultimately quantum decoherent) noise. In the second, available energy is focussed on a smaller subset of larger neurons whose action is deterministic. Possible implications for creative computing in silicon are discussed. Starting with a discussion of the concept of free will, the notion of consciousness is defined in terms of an awareness of what are perceived to be nearby counterfactual worlds in state space. It is argued that such awareness arises from an interplay between memories on the one hand, and quantum physical mechanisms (where, unlike in classical physics, nearby counterfactual worlds play an indispensable dynamical role) in the ion channels of neural networks, on the other. As with the brain's susceptibility to noise, it is argued that in situations where quantum physics plays a role in the brain, it does so for reasons of energy efficiency. As an illustration of this definition of consciousness, a novel proposal is outlined as to why quantum entanglement appears to be so counter-intuitive.


Optimising the use of ensemble information in numerical weather forecasts of wind power generation

Environmental Research Letters IOP Publishing 14 (0) 124086-124086

J Stanger, I Finney, A Weisheimer, T Palmer


Machine learning and artificial intelligence to aid climate change research and preparedness

Environmental Research Letters IOP Publishing 14 (2019) 12

C Huntingford, ES Jeffers, M Bonsall, H Christensen, T Lees, H Yang


Compatible Finite Element Methods for Geophysical Flows Automation and Implementation Using Firedrake

Springer, 2019

TH Gibson, ATT McRae, CJ Cotter, L Mitchell, DA Ham

This book introduces recently developed mixed finite element methods for large-scale geophysical flows that preserve essential numerical properties for accurate simulations.


Assessing external and internal sources of Atlantic Multidecadal Variability using models, proxy data, and early instrumental indices

Journal of Climate American Meteorological Society 32 (2019) 7727-7745

C O'Reilly, L Zanna, T Woollings

Atlantic multidecadal variability (AMV) of sea surface temperature exhibits an important influence on the climate of surrounding continents. It remains unclear, however, the extent to which AMV is due to internal climate variability (e.g., ocean circulation variability) or changes in external forcing (e.g., volcanic/anthropogenic aerosols or greenhouse gases). Here, the sources of AMV are examined over a 340-yr period using proxy indices, instrumental data, and output from the Last Millennium Ensemble (LME) simulation. The proxy AMV closely follows the accumulated atmospheric forcing from the instrumental North Atlantic Oscillation (NAO) reconstruction (r = 0.65)—an “internal” source of AMV. This result provides strong observational evidence that much of the AMV is generated through the oceanic response to atmospheric circulation forcing, as previously demonstrated in targeted modeling studies. In the LME there is a substantial externally forced AMV component, which exhibits a modest but significant correlation with the proxy AMV (i.e., r = 0.37), implying that at least 13% of the AMV is externally forced. In the LME simulations, however, the AMV response to accumulated NAO forcing is weaker than in the proxy/observational datasets. This weak response is possibly related to the decadal NAO variability, which is substantially weaker in the LME than in observations. The externally forced component in the proxy AMV is also related to the accumulated NAO forcing, unlike in the LME. This indicates that the external forcing is likely influencing the AMV through different mechanistic pathways: via changes in radiative forcing in the LME and via changes in atmospheric circulation in the observational/proxy record.


The impact of a stochastic parameterization scheme on climate sensitivity in EC‐Earth

Journal of Geophysical Research: Atmospheres American Geophysical Union 124 (2019) 12726-12740

K Strommen, PAG Watson, TN Palmer

Stochastic schemes, designed to represent unresolved sub-grid scale variability, are frequently used in short and medium-range weather forecasts, where they are found to improve several aspects of the model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long term climate. In this paper, we demonstrate for the first time that the inclusion of a stochastic physics scheme can notably affect a model's projection of global warming, as well as its historical climatological global temperature. Specifically, we find that when including the 'stochastically perturbed parametrisation tendencies' scheme (SPPT) in the fully coupled climate model EC-Earth v3.1, the predicted level of global warming between 1850 and 2100 is reduced by 10% under an RCP8.5 forcing scenario. We link this reduction in climate sensitivity to a change in the cloud feedbacks with SPPT. In particular, the scheme appears to reduce the positive low cloud cover feedback, and increase the negative cloud optical feedback. A key role is played by a robust, rapid increase in cloud liquid water with SPPT, which we speculate is due to the scheme's non-linear interaction with condensation.


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

Geophysical Research Letters American Geophysical Union (2019)

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 scientific challenge of understanding and estimating climate change.

Proceedings of the National Academy of Sciences of the United States of America 116 (2019) 24390-24395

T Palmer, B Stevens

Given the slow unfolding of what may become catastrophic changes to Earth's climate, many are understandably distraught by failures of public policy to rise to the magnitude of the challenge. Few in the science community would think to question the scientific response to the unfolding changes. However, is the science community continuing to do its part to the best of its ability? In the domains where we can have the greatest influence, is the scientific community articulating a vision commensurate with the challenges posed by climate change? We think not.


The Impact of a Stochastic Parameterization Scheme on Climate Sensitivity in EC-Earth

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES (2019)

K Strommen, PAG Watson, TN Palmer

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