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.

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.

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.

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

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.

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.

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

Quarterly Journal of the Royal Meteorological Society Wiley 145 (2019) 1052-1069

H Christensen, J Berner

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.

Stochastic parameterization of subgrid-scale velocity enhancement of sea surface fluxes

Monthly Weather Review American Meteorological Society 147 (2019) 1447-1469

J Bessac, AH Monahan, H Christensen, N Weitzel

Subgrid-scale (SGS) velocity variations result in gridscale sea surface flux enhancements that must be parameterized in weather and climate models. Traditional parameterizations are deterministic in that they assign a unique value of the SGS velocity flux enhancement to any given configuration of the resolved state. In this study, we assess the statistics of SGS velocity flux enhancement over a range of averaging scales (as a proxy for varying model resolution) through systematic coarse-graining of a convection-permitting atmospheric model simulation over the Indian Ocean and west Pacific warm pool. Conditioning the statistics of the SGS velocity flux enhancement on 1) the fluxes associated with the resolved winds and 2) the precipitation rate, we find that the lack of a separation between “resolved” and “unresolved” scales results in a distribution of flux enhancements for each configuration of the resolved state. That is, the SGS velocity flux enhancement should be represented stochastically rather than deterministically. The spatial and temporal statistics of the SGS velocity flux enhancement are investigated by using basic descriptive statistics and through a fit to an anisotropic space–time covariance structure. Potential spatial inhomogeneities of the statistics of the SGS velocity flux enhancement are investigated through regional analysis, although because of the relatively short duration of the simulation (9 days) distinguishing true inhomogeneity from sampling variability is difficult. Perspectives for the implementation of such a stochastic parameterization in weather and climate models are discussed.

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 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.

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 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.

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, S Juricke, T Palmer

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.

Posits as an alternative to floats for weather and climate models

CoNGA'19 Proceedings of the Conference for Next Generation Arithmetic 2019 Association for Computing Machinery (2019)

M Klöwer, PD Düben, TN Palmer

Posit numbers, a recently proposed alternative to floating-point numbers, claim to have smaller arithmetic rounding errors in many applications. By studying weather and climate models of low and medium complexity (the Lorenz system and a shallow water model) we present benefits of posits compared to floats at 16 bit. As a standardised posit processor does not exist yet, we emulate posit arithmetic on a conventional CPU. Using a shallow water model, forecasts based on 16-bit posits with 1 or 2 exponent bits are clearly more accurate than half precision floats. We therefore propose 16 bit with 2 exponent bits as a standard posit format, as its wide dynamic range of 32 orders of magnitude provides a great potential for many weather and climate models. Although the focus is on geophysical fluid simulations, the results are also meaningful and promising for reduced precision posit arithmetic in the wider field of computational fluid dynamics.

A Stochastic Representation of Subgrid Uncertainty for Dynamical Core Development

Bulletin of the American Meteorological Society American Meteorological Society 100 (2019) 1091-1101

A Subramanian, S Juricke, P Dueben, T Palmer

Numerical weather prediction and climate models comprise a) a dynamical core describing resolved parts of the climate system and b) parameterizations describing unresolved components. Development of new subgrid-scale parameterizations is particularly uncertain compared to representing resolved scales in the dynamical core. This uncertainty is currently represented by stochastic approaches in several operational weather models, which will inevitably percolate into the dynamical core. Hence, implementing dynamical cores with excessive numerical accuracy will not bring forecast gains, may even hinder them since valuable computer resources will be tied up doing insignificant computation, and therefore cannot be deployed for more useful gains, such as increasing model resolution or ensemble sizes. Here we describe a low-cost stochastic scheme that can be implemented in any existing deterministic dynamical core as an additive noise term. This scheme could be used to adjust accuracy in future dynamical core development work. We propose that such an additive stochastic noise test case should become a part of the routine testing and development of dynamical cores in a stochastic framework. The overall key point of the study is that we should not develop dynamical cores that are more precise than the level of uncertainty provided by our stochastic scheme. In this way, we present a new paradigm for dynamical core development work, ensuring that weather and climate models become more computationally efficient. We show some results based on tests done with the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) dynamical core.