Publications


The Gulf Stream influence on wintertime North Atlantic jet variability

Quarterly Journal of the Royal Meteorological Society Wiley 143 (2016) 173-183

C O'Reilly, S Minobe, A Kuwano-Yoshida, T Woollings

In this paper we investigate the influence of the Gulf Stream SST front on the North Atlantic eddy-driven jet and its variability, by analysing the NCEP-CFSR dataset and a pair of AGCM simulations forced with realistic and smoothed Gulf Stream SST boundary conditions. The Gulf Stream SST front acts to generate stronger meridional eddy heat flux in the lower-troposphere and an eddy-driven jet over the eastern North Atlantic that is located further polewards, compared to the simulation with smoothed SST. The strong Gulf Stream SST gradient is found to be crucial in more accurately capturing the trimodal distribution of the eddy-driven jet latitude, with the more poleward climatological jet being the result of the jet occupying the northern jet position more frequently in the simulation forced with observed SSTs. The more frequent occurence of the northern jet location is associated with periods of high eddy heat flux over the Gulf Stream region. Composite analysis of high eddy heat flux events reveals that the significantly higher heat flux is followed by larger and more persistient poleward jet excursions in the simulations with realistic SSTs compared to the simulation with smoothed SSTs, with upper-tropospheric eddy momentum fluxes acting to maintain the more poleward eddy-driven jet. Periods of high eddy heat flux over the Gulf Stream region are also shown to be associated with increased blocking frequency over Europe, which are clearly distinct from periods with a northern jet position.


Seasonal and decadal forecasts of Atlantic Sea surface temperatures using a linear inverse model

Climate Dynamics Springer Verlag 49 (2016) 1833–1845-

B Huddart, A Subramanian, L Zanna, T Palmer

Predictability of Atlantic Ocean sea surface temperatures (SST) on seasonal and decadal timescales is investigated using a suite of statistical linear inverse models (LIM). Observed monthly SST anomalies in the Atlantic sector (between 22(Formula presented.)S and 66(Formula presented.)N) are used to construct the LIMs for seasonal and decadal prediction. The forecast skills of the LIMs are then compared to that from two current operational forecast systems. Results indicate that the LIM has good forecast skill for time periods of 3–4 months on the seasonal timescale with enhanced predictability in the spring season. On decadal timescales, the impact of inter-annual and intra-annual variability on the predictability is also investigated. The results show that the suite of LIMs have forecast skill for about 3–4 years over most of the domain when we use only the decadal variability for the construction of the LIM. Including higher frequency variability helps improve the forecast skill and maintains the correlation of LIM predictions with the observed SST anomalies for longer periods. These results indicate the importance of temporal scale interactions in improving predictability on decadal timescales. Hence, LIMs can not only be used as benchmarks for estimates of statistical skill but also to isolate contributions to the forecast skills from different timescales, spatial scales or even model components.


Remote control of North Atlantic Oscillation predictability via the stratosphere

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 143 (2017) 706-719

F Hansen, RJ Greatbatch, G Gollan, T Jung, A Weisheimer


Firedrake: Automating the finite element method by composing abstractions

ACM Transactions on Mathematical Software 43 (2016)

F Rathgeber, DA Ham, L Mitchell, M Lange, F Luporini, ATT McRae, GT Bercea, GR Markall, PHJ Kelly

Firedrake is a new tool for automating the numerical solution of partial differential equations. Firedrake adopts the domain-specific language for the finite element method of the FEniCS project, but with a pure Python runtime-only implementation centered on the composition of several existing and new abstractions for particular aspects of scientific computing. The result is a more complete separation of concerns that eases the incorporation of separate contributions from computer scientists, numerical analysts, and application specialists. These contributions may add functionality or improve performance. Firedrake benefits from automatically applying new optimizations. This includes factorizing mixed function spaces, transforming and vectorizing inner loops, and intrinsically supporting block matrix operations. Importantly, Firedrake presents a simple public API for escaping the UFL abstraction. This allows users to implement common operations that fall outside of pure variational formulations, such as flux limiters.


Stochastic parameterization and El Niño–Southern Oscillation

Journal of Climate American Meteorological Society 30 (2016) 17–38-

H Christensen, TN Palmer, DRB Coleman, J Berner

El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical Pacific. However, the models in the ensemble from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have large deficiencies in ENSO amplitude, spatial structure, and temporal variability. The use of stochastic parameterizations as a technique to address these pervasive errors is considered. The multiplicative stochastically perturbed parameterization tendencies (SPPT) scheme is included in coupled integrations of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4). The SPPT scheme results in a significant improvement to the representation of ENSO in CAM4, improving the power spectrum and reducing the magnitude of ENSO toward that observed. To understand the observed impact, additive and multiplicative noise in a simple delayed oscillator (DO) model of ENSO is considered. Additive noise results in an increase in ENSO amplitude, but multiplicative noise can reduce the magnitude of ENSO, as was observed for SPPT in CAM4. In light of these results, two complementary mechanisms are proposed by which the improvement occurs in CAM. Comparison of the coupled runs with a set of atmosphere-only runs indicates that SPPT first improve the variability in the zonal winds through perturbing the convective heating tendencies, which improves the variability of ENSO. In addition, SPPT improve the distribution of westerly wind bursts (WWBs), important for initiation of El Niño events, by increasing the stochastic component of WWB and reducing the overly strong dependency on SST compared to the control integration.


Atmospheric seasonal forecasts of the twentieth century: Multi-decadal variability in predictive skill of the winter North Atlantic Oscillation (NAO) and their potential value for extreme event attribution

Quarterly Journal of the Royal Meteorological Society Wiley 143 (2016) 917–926-

A Weisheimer, N Schaller, DA Macleod, TN Palmer, C O'Reilly

Based on skill estimates from hindcasts made over the last couple of decades, recent studies have suggested that considerable success has been achieved in forecasting winter climate anomalies over the Euro-Atlantic area using current-generation dynamical forecast models. However, previous-generation models had shown that forecasts of winter climate anomalies in the 1960s and 1970s were less successful than forecasts of the 1980s and 1990s. Given that the more recent decades have been dominated by the North Atlantic Oscillation (NAO) in its positive phase, it is important to know whether the performance of current models would be similarly skilful when tested over periods of a predominantly negative NAO. To this end, a new ensemble of atmospheric seasonal hindcasts covering the period 1900–2009 has been created, providing a unique tool to explore many aspects of atmospheric seasonal climate prediction. In this study we focus on two of these: multi-decadal variability in predicting the winter NAO, and the potential value of the long seasonal hindcast datasets for the emerging science of probabilistic event attribution. The existence of relatively low skill levels during the period 1950s–1970s has been confirmed in the new dataset. The skillof the NAO forecasts is larger, however, in earlier and later periods. Whilst these inter-decadal differences in skill are, by themselves, only marginally statistically significant, the variations in skill strongly co-vary with statistics of the general circulation itself suggesting that such differences are indeed physically based. The mid-century period of low forecast skill coincides with a negative NAO phase but the relationship between the NAO phase/amplitude and forecast skill is more complex than linear. Finally, we show how seasonal forecast reliability can be of importance for increasing confidence in statements of causes of extreme weather and climate events, including effects of anthropogenic climate change.


On the use of scale-dependent precision in Earth System modelling

Quarterly Journal of the Royal Meteorological Society John Wiley & Sons Ltd 143 (2017) 897-908

T Thornes, P Düben, T Palmer

Increasing the resolution of numerical models has played a large part in improving the accuracy of weather and climate forecasts in recent years. Until now, this has required the use of ever more powerful computers, the energy costs of which are becoming increasingly problematic. It has therefore been proposed that forecasters switch to using more efficient ‘reduced precision’ hardware capable of sacrificing unnecessary numerical precision to save costs. Here, an extended form of the Lorenz ‘96 idealized model atmosphere is used to test whether more accurate forecasts could be produced by lowering numerical precision more at smaller spatial scales in order to increase the model resolution. Both a scale-dependent mixture of single- and half-precision – where numbers are represented with fewer bits of information on smaller spatial scales – and ‘stochastic processors’ – where random ‘bit-flips’ are allowed for small-scale variables – are emulated on conventional hardware. It is found that high-resolution parametrized models with scale-selective reduced precision yield better short-term and climatological forecasts than lower resolution parametrized models with conventional precision for a relatively small increase in computational cost. This suggests that a similar approach in real-world models could lead to more accurate and efficient weather and climate forecasts.


Single Precision in Weather Forecasting Models: An Evaluation with the IFS

MONTHLY WEATHER REVIEW 145 (2017) 495-502

F Vana, P Duben, S Lang, T Palmer, M Leutbecher, D Salmond, G Carver


Impact of stochastic physics on tropical precipitation in the coupled ECMWF model

Quarterly Journal of the Royal Meteorological Society Wiley 143 (2016) 852-865

A Subramanian, A Weisheimer, T Palmer, F Vitart, P Bechtold

Uncertainties in parametrized processes in general circulation models can be represented as stochastic perturbations to the model formulation. The European Centre for Medium-Range Weather Forecasts (ECMWF) has pioneered approaches to represent these model errors in forecasting systems. In particular, the stochastically perturbed physical tendency (SPPT) scheme for the atmosphere is used in their operational ensemble system for medium- and long-range predictions. Recent studies have shown that these stochastic approaches can both increase the reliability of the probabilistic forecasts and reduce long-term mean biases of the model climate. Towards developing a seamless prediction system in the future, these benefits of stochastic parametrization for both short-term and long-term forecasts make it an essential component of the next generation Earth System models. We present results of the impact of different configurations of the SPPT scheme in ECMWF's seasonal forecasting System 4 on the mean and variability in tropical precipitation. Small-scale perturbations in the SPPT scheme play a significant role in reducing the mean biases in tropical precipitation. The stochastic physics also nonlinearly rectify the convection and precipitation during different phases of El Niño Southern Oscillation events and improve the reliability of the ensemble forecasts for the Madden–Julian Oscillation (MJO). They impact the MJO dynamics by modulating the convective and suppressed phases of the MJO. Finally, we discuss some of the caveats to this analysis and some future prospects.


A structure-exploiting numbering algorithm for finite elements on extruded meshes, and its performance evaluation in Firedrake

Geoscientific Model Development 9 (2016) 3803-3815

GT Bercea, ATT McRae, DA Ham, L Mitchell, F Rathgeber, L Nardi, F Luporini, PHJ Kelly

We present a generic algorithm for numbering and then efficiently iterating over the data values attached to an extruded mesh. An extruded mesh is formed by replicating an existing mesh, assumed to be unstructured, to form layers of prismatic cells. Applications of extruded meshes include, but are not limited to, the representation of three-dimensional high aspect ratio domains employed by geophysical finite element simulations. These meshes are structured in the extruded direction. The algorithm presented here exploits this structure to avoid the performance penalty traditionally associated with unstructured meshes. We evaluate the implementation of this algorithm in the Firedrake finite element system on a range of low compute intensity operations which constitute worst cases for data layout performance exploration. The experiments show that having structure along the extruded direction enables the cost of the indirect data accesses to be amortized after 10-20 layers as long as the underlying mesh is well ordered. We characterize the resulting spatial and temporal reuse in a representative set of both continuous-Galerkin and discontinuous-Galerkin discretizations. On meshes with realistic numbers of layers the performance achieved is between 70 and 90% of a theoretical hardware-specific limit.


A personal perspective on modelling the climate system

Animal Behaviour Royal Society 472 (2016)

T Palmer

Given their increasing relevance for society, I suggest that the climate science community itself does not treat the development of error-free ab initio models of the climate system with sufficient urgency. With increasing levels of difficulty, I discuss a number of proposals for speeding up such development. Firstly, I believe that climate science should make better use of the pool of post-PhD talent in mathematics and physics, for developing next-generation climate models. Secondly, I believe there is more scope for the development of modelling systems which link weather and climate prediction more seamlessly. Finally, here in Europe, I call for a new European Programme on Extreme Computing and Climate to advance our ability to simulate climate extremes, and understand the drivers of such extremes. A key goal for such a programme is the development of a 1km global climate system model to run on the first exascale supercomputers in the early 2020s.


Oceanic stochastic parametrizations in a seasonal forecast system

Monthly Weather Review American Meteorological Society 144 (2016) 1867-1875

M Andrejczuk, FC Cooper, S Juricke, TN Palmer, A Weisheimer, L Zanna

Stochastic parametrization provides a methodology for representing model uncertainty in ensemble forecasts. Here we study the impact of three existing stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean where ensemble spread is increased. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.


Impact of springtime Himalayan-Tibetan Plateau snowpack on the onset of the Indian summer monsoon in coupled seasonal forecasts

Climate Dynamics Springer Verlag 47 (2016) 2709

R Senan, Y Orsolini, A Weisheimer, D Basang, F Vitart, G Balsamo, TN Stockdale, E Dutra, FJ Doblas-Reyes

<p>The springtime snowpack over the Himalayan-Tibetan Plateau (HTP) region and Eurasia has long been suggested to be an influential factor on the onset of the Indian summer monsoon. To assess the impact of realistic initialization of springtime snow over HTP on the onset of the Indian summer monsoon, we examine a suite of coupled ocean-atmosphere 4-month ensemble reforecasts made at the European Centre for Medium-Range Weather Forecasts (ECMWF), using their Seasonal Forecasting System 4. The reforecasts were initialized on 1 April every year for the period 1981-2010. In these seasonal reforecasts, the snow is initialized “realistically” with ERA-Interim/Land Reanalysis. In addition, we carried out an additional set of forecasts, identical in all aspects except that initial conditions for snow-related land surface variables over the HTP region are randomized. </p> <p>We show that high snow depth over HTP influences the meridional tropospheric temperature gradient reversal that marks the monsoon onset. Composite difference based on a normalized HTP snow index reveal that, in high snow years, (i) the onset is delayed by about 8 days, and (ii) negative precipitation anomalies and warm surface conditions prevail over India. We show that about half of this delay can be attributed to the realistic initialization of snow over the HTP region. We further demonstrate that high April snow depths over HTP are not uniquely influenced by El Nino-Southern Oscillation, the Indian Ocean Dipole or the North Atlantic Oscillation. </p>


The signature of low frequency oceanic forcing in the Atlantic Multidecadal Oscillation

Geophysical Research Letters American Geophysical Union 43 (2016) 2810–2818-

CH O'Reilly, MB Huber, TJ Woollings, LE Zanna

The Atlantic Multidecadal Oscillation (AMO) significantly influences the climate of the surrounding continents and has previously been attributed to variations in the Atlantic Meridional Overturning Circulation. Recently, however, similar multidecadal variability was reported in climate models without ocean circulation variability. We analyse the relationship between turbulent heat fluxes and SSTs over the midlatitude North Atlantic in observations and coupled climate model simulations, both with and without ocean circulation variability. SST anomalies associated with the AMO are positively correlated with heat fluxes on decadal time-scales in both observations and models with varying ocean circulation, whereas in models without ocean circulation variability the anomalies are negatively correlated when heat flux anomalies lead. These relationships are captured in a simple stochastic model and rely crucially on low frequency forcing of SST. The fully coupled models that better capture this signature more effectively reproduce the observed impact of the AMO on European summertime temperatures.


Assessing the role of insulin-like growth factors and binding proteins in prostate cancer using Mendelian randomization: Genetic variants as instruments for circulating levels

International Journal of Cancer Wiley 139 (2016) 1520-1533

C Bonilla, M-A Rowlands, SJ Lewis, TR Gaunt, DE Neal, R Eeles, D Easton, Z Kote-Jarai, AA Al Olama, S Benlloch, K Muir, GG Giles, F Wiklund, H Grönberg, CA Haiman, J Schleutker, BG Nordestgaard, RC Travis, N Pashayan, K-T Khaw, JL Stanford, WJ Blot, S Thibodeau, C Maier, AS Kibel

Circulating insulin-like growth factors (IGFs) and their binding proteins (IGFBPs) are associated with prostate cancer. Using genetic variants as instruments for IGF peptides, we investigated whether these associations are likely to be causal. We identified from the literature 56 single nucleotide polymorphisms (SNPs) in the IGF axis previously associated with biomarker levels (8 from a genome-wide association study [GWAS] and 48 in reported candidate genes). In ∼700 men without prostate cancer and two replication cohorts (N ∼ 900 and ∼9,000), we examined the properties of these SNPS as instrumental variables (IVs) for IGF-I, IGF-II, IGFBP-2 and IGFBP-3. Those confirmed as strong IVs were tested for association with prostate cancer risk, low (&lt; 7) vs. high (≥ 7) Gleason grade, localised vs. advanced stage, and mortality, in 22,936 controls and 22,992 cases. IV analysis was used in an attempt to estimate the causal effect of circulating IGF peptides on prostate cancer. Published SNPs in the IGFBP1/IGFBP3 gene region, particularly rs11977526, were strong instruments for IGF-II and IGFBP-3, less so for IGF-I. Rs11977526 was associated with high (vs. low) Gleason grade (OR per IGF-II/IGFBP-3 level-raising allele 1.05; 95% CI: 1.00, 1.10). Using rs11977526 as an IV we estimated the causal effect of a one SD increase in IGF-II (∼265 ng/mL) on risk of high vs. low grade disease as 1.14 (95% CI: 1.00, 1.31). Because of the potential for pleiotropy of the genetic instruments, these findings can only causally implicate the IGF pathway in general, not any one specific biomarker.


Eureka moments or hard graft?

PHYSICS WORLD 29 (2016) 15-16

T Palmer, M O'Shea


Influence of the Eurasian snow on the negative North Atlantic Oscillation in subseasonal forecasts of the cold winter 2009/2010

Climate Dynamics 47 (2016) 1325-1334

YJ Orsolini, R Senan, F Vitart, G Balsamo, A Weisheimer, FJ Doblas-Reyes

© 2015, The Author(s). The winter 2009/2010 was remarkably cold and snowy over North America and across Eurasia, from Europe to the Far East, coinciding with a pronounced negative phase of the North Atlantic Oscillation (NAO). While previous studies have investigated the origin and persistence of this anomalously negative NAO phase, we have re-assessed the role that the Eurasian snowpack could have played in contributing to its maintenance. Many observational and model studies have indicated that the autumn Eurasian snow cover influences circulation patterns over high northern latitudes. To investigate that role, we have performed a suite of forecasts with the coupled ocean–atmosphere ensemble prediction system from the European Centre for Medium-Range Weather Forecasts. Pairs of 2-month ensemble forecasts with either realistic or else randomized snow initial conditions are used to demonstrate how an anomalously thick snowpack leads to an initial cooling over the continental land masses of Eurasia and, within 2 weeks, to the anomalies that are characteristic of a negative NAO. It is also associated with enhanced vertical wave propagation into the stratosphere and deceleration of the polar night jet. The latter then exerts a downward influence into the troposphere maximizing in the North Atlantic region, which establishes itself within 2 weeks. We compare the forecasted NAO index in our simulations with those from several operational forecasts of the winter 2009/2010 made at the ECWMF, and highlight the importance of relatively high horizontal resolution.


Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach

Hydrology and Earth System Sciences Copernicus Publications 20 (2016) 2737-2743

H Cloke, F Pappenberger, D MacLeod, A Weisheimer

Soil moisture memory is a key component of seasonal predictability. However, uncertainty in current memory estimates is not clear and it is not obvious to what extent these are dependent on model uncertainties. To address this question, we perform a global sensitivity analysis of memory to key hydraulic parameters, using an uncoupled version of the H-TESSEL land surface model. Results show significant dependency of estimates of memory and its uncertainty on these parameters, suggesting that operational seasonal forecasting models using deterministic hydraulic parameter values are likely to display a narrower range of memory than exists in reality. Explicitly incorporating hydraulic parameter uncertainty into models may then give improvements in forecast skill and reliability, as has been shown elsewhere in the literature. Our results also show significant differences with previous estimates of memory uncertainty, warning against placing too much confidence in a single quantification of uncertainty.


Turbulent–laminar patterns in shear flows without walls

Journal of Fluid Mechanics Cambridge University Press 791 (2016)

M Chantry, L Tuckerman, D Barkley

Turbulent–laminar intermittency, typically in the form of bands and spots, is a ubiquitous feature of the route to turbulence in wall-bounded shear flows. Here we study the idealised shear between stress-free boundaries driven by a sinusoidal body force and demonstrate quantitative agreement between turbulence in this flow and that found in the interior of plane Couette flow – the region excluding the boundary layers. Exploiting the absence of boundary layers, we construct a model flow that uses only four Fourier modes in the shear direction and yet robustly captures the range of spatiotemporal phenomena observed in transition, from spot growth to turbulent bands and uniform turbulence. The model substantially reduces the cost of simulating intermittent turbulent structures while maintaining the essential physics and a direct connection to the Navier–Stokes equations. We demonstrate the generic nature of this process by introducing stress-free equivalent flows for plane Poiseuille and pipe flows that again capture the turbulent–laminar structures seen in transition.


Calibrating Climate Change Time-Slice Projections with Estimates of Seasonal Forecast Reliability

JOURNAL OF CLIMATE 29 (2016) 3831-3840

M Matsueda, A Weisheimer, TN Palmer

Pages