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

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

<jats:p> Capsule Summary </jats:p><jats: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. </jats:p>

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

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

AC Subramanian, AH Monahan, HM Christensen, DJ Gagne

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

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

TN 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'.

Forced summer stationary waves: the opposing effects of direct radiative forcing and sea surface warming

Climate Dynamics Springer Nature 53 (2019) 4291-4309

H Baker, T Woollings, C Mbengue, M Allen, C O'Reilly, H Shiogama, S Sparrow

We investigate the opposing effects of direct radiative forcing and sea surface warming on the atmospheric circulation using a hierarchy of models. In large ensembles of three general circulation models, direct CO2 forcing produces a wavenumber 5 stationary wave over the Northern Hemisphere in summer. Sea surface warming produces a similar wave, but with the opposite sign. The waves are also present in the Coupled Model Inter comparison Project phase 5 ensemble with opposite signs due to direct CO2 and sea surface warming. Analyses of tropical precipitation changes and equivalent potential temperature changes and the results from a simple barotropic model show that the wave is forced from the tropics. Key forcing locations are the Western Atlantic, Eastern Atlantic and in the Indian Ocean just off the east coast of Africa. The stationary wave has a significant impact on regional temperature anomalies in the Northern Hemisphere summer, explaining some of the direct effect that CO2 concentration has on temperature extremes. Ultimately, the climate sensitivity and future changes in the land-sea temperature contrast will dictate the balance between the opposing effects on regional changes in mean and extreme temperature and precipitation under climate change.

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

T Woollings, L Zanna, C O'Reilly

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.

Climate Services and Communication for Development: The Role of Early Career Researchers in Advancing the Debate


FK Donkor, C Howarth, E Ebhuoma, M Daly, C Vaughan, L Pretorius, J Mambo, D MacLeod, A Kythreotis, L Jones, S Grainger, N Golding, JA Anderson

Seasonal forecasts of the East African long rains: insight from atmospheric relaxation experiments

Climate Dynamics (2019)

D MacLeod

© 2019, The Author(s). The impacts of recent droughts and floods over East Africa may have been avoided with accurate and timely early warnings. However skillful predictions for the long rains season from dynamical seasonal forecasts have long proved elusive and understanding of the drivers of interannual variability of this season is incomplete. Although recent work has highlighted several candidates for key drivers of variability during March–April, the representation of East African precipitation and links to remote processes in seasonal climate models is relatively unknown. This is investigated here through use of the atmospheric relaxation technique in coupled seasonal climate hindcast experiments, which also provide an estimate of the upper bound of seasonal predictability from remote sources. Results highlight the key role of the lower troposphere in the northwest Indian Ocean in controlling interannual variability, particularly in March and April. This is in support of recent work suggesting ascent-induced boundary-layer heating this region as a key driver of interannual variability. Results from single-variable relaxation experiments also reveal the importance of correct simulation of humidity for the proper representation of this link. Processes in the southwest Indian Ocean provide a control on May precipitation over southwest Kenya and northern Tanzania, highlighting the role of Somali jet variability in long rains cessation. Relaxation in more remote regions over the Pacific is unable to improve the representation of interannual variability over East Africa in general, although variability in the east Pacific appears to provide a weak control on March rainfall, consistent with previous hypotheses linking decaying ENSO events to early season rainfall. Finally, modelled precipitation anomalies are found to be insufficiently constrained to the coast of Africa. Relaxation (particularly in the northwest Indian Ocean) can improve these spatial biases, however the variance explained by these modes is systematically underestimated in the model and appears insensitive to remote processes. Inadequate representation of local processes over East Africa is proposed as the cause of this underestimation and several candidates are outlined.

Stochastic weather and climate models

Nature Reviews Physics Springer Science and Business Media LLC 1 (2019) 463-471

TN Palmer

Correction to: The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model (Climate Dynamics, (2019), 10.1007/s00382-019-04660-0)

Climate Dynamics (2019)

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

© 2019, The Author(s). The article The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model, written by Chunxue Yang, Hannah M. Christensen, Susanna Corti, Jost von Hardenberg and Paolo Davini, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 07 February 2019 without open access.

The Sensitivity of Euro-Atlantic Regimes to Model Horizontal Resolution

Geophysical Research Letters American Geophysical Union (2019)

K Strommen, I Mavilia, S Corti, M Matsueda, P Davini, JV Hardenberg, P-L Vidale, R Mizuta

There is growing evidence that the atmospheric dynamics of the Euro-Atlantic sector during winter is driven in part by the presence of quasi-persistent regimes. However, general circulation models typically struggle to simulate these, with e.g. an overly weakly persistent blocking regime. Previous studies have showed that increased horizontal resolution can improve the regime structure of a model, but have so far only considered a single model with only one ensemble member at each resolution, leaving open the possibility that this may be either coincidental or model-dependent. We show that the improvement in regime structure due to increased resolution is robust across multiple models with multiple ensemble members. However, while the high resolution models have notably more tightly clustered data, other aspects of the regimes may not necessarily improve, and are also subject to a large amount of sampling variability that typically requires at least three ensemble members to surmount.

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

Journal of Geophysical Research: Atmospheres American Geophysical Union (2019)

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.

Accelerating high-resolution weather models with deep-learning hardware

PASC '19 Proceedings of the Platform for Advanced Scientific Computing Conference Association for Computing Machinery (2019)

S Hatfield, M Chantry, P Duben, T Palmer

The next generation of weather and climate models will have an unprecedented level of resolution and model complexity, and running these models efficiently will require taking advantage of future supercomputers and heterogeneous hardware. In this paper, we investigate the use of mixed-precision hardware that supports floating-point operations at double-, single- and half-precision. In particular, we investigate the potential use of the NVIDIA Tensor Core, a mixed-precision matrix-matrix multiplier mainly developed for use in deep learning, to accelerate the calculation of the Legendre transforms in the Integrated Forecasting System (IFS), one of the leading global weather forecast models. In the IFS, the Legendre transform is one of the most expensive model components and dominates the computational cost for simulations at a very high resolution. We investigate the impact of mixed-precision arithmetic in IFS simulations of operational complexity through software emulation. Through a targeted but minimal use of double-precision arithmetic we are able to use either half-precision arithmetic or mixed half/single-precision arithmetic for almost all of the calculations in the Legendre transform without affecting forecast skill.

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 (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.

Progress Towards a Probabilistic Earth System Model: Examining The Impact of Stochasticity in EC-Earth v3.2

Geoscientific Model Development European Geosciences Union 12 (2019) 3099-3118

K Strommen, H Christensen, D Macleod, T Palmer, S Juricke

We introduce and study the impact of three stochastic schemes in the EC-Earth climate model: two atmospheric schemes and one stochastic land scheme. These form the basis for a probabilistic Earth system model in atmosphere-only mode. Stochastic parametrization have become standard in several operational weather-forecasting models, in particular due to their beneficial impact on model spread. In recent years, stochastic schemes in the atmospheric component of a model have been shown to improve aspects important for the models long-term climate, such as El Niño–Southern Oscillation (ENSO), North Atlantic weather regimes, and the Indian monsoon. Stochasticity in the land component has been shown to improve the variability of soil processes and improve the representation of heatwaves over Europe. However, the raw impact of such schemes on the model mean is less well studied. It is shown that the inclusion of all three schemes notably changes the model mean state. While many of the impacts are beneficial, some are too large in amplitude, leading to significant changes in the model's energy budget and atmospheric circulation. This implies that in order to maintain the benefits of stochastic physics without shifting the mean state too far from observations, a full re-tuning of the model will typically be required.

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


K Strommen, PAG Watson, TN Palmer