The use of imprecise processing to improve accuracy in weather & climate prediction

Journal of Computational Physics 271 (2014) 2-18

PD Düben, H McNamara, TN Palmer

The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing bit-reproducibility and precision in exchange for improvements in performance and potentially accuracy of forecasts, due to a reduction in power consumption that could allow higher resolution. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud-resolving atmospheric modelling. The impact of both hardware induced faults and low precision arithmetic is tested using the Lorenz '96 model and the dynamical core of a global atmosphere model. In the Lorenz '96 model there is a natural scale separation; the spectral discretisation used in the dynamical core also allows large and small scale dynamics to be treated separately within the code. Such scale separation allows the impact of lower-accuracy arithmetic to be restricted to components close to the truncation scales and hence close to the necessarily inexact parametrised representations of unresolved processes. By contrast, the larger scales are calculated using high precision deterministic arithmetic. Hardware faults from stochastic processors are emulated using a bit-flip model with different fault rates. Our simulations show that both approaches to inexact calculations do not substantially affect the large scale behaviour, provided they are restricted to act only on smaller scales. By contrast, results from the Lorenz '96 simulations are superior when small scales are calculated on an emulated stochastic processor than when those small scales are parametrised. This suggests that inexact calculations at the small scale could reduce computation and power costs without adversely affecting the quality of the simulations. This would allow higher resolution models to be run at the same computational cost. © 2013 The Authors.

The real butterfly effect

NONLINEARITY 27 (2014) R123-R141

TN Palmer, A Doering, G Seregin

Build high-resolution global climate models

NATURE 515 (2014) 338-339

T Palmer

It's all just physics

PHYSICS WORLD 27 (2014) 18-19

T Palmer

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

Scientific reports 4 (2014) 7264-

DA MacLeod, AP Morse

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Stochastic modelling and energy-efficient computing for weather and climate prediction.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 372 (2014) 20140118-

T Palmer, P Düben, H McNamara

On the use of inexact, pruned hardware in atmospheric modelling.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 372 (2014) 20130276-

PD Düben, J Joven, A Lingamneni, H McNamara, G De Micheli, KV Palem, TN Palmer

Inexact hardware design, which advocates trading the accuracy of computations in exchange for significant savings in area, power and/or performance of computing hardware, has received increasing prominence in several error-tolerant application domains, particularly those involving perceptual or statistical end-users. In this paper, we evaluate inexact hardware for its applicability in weather and climate modelling. We expand previous studies on inexact techniques, in particular probabilistic pruning, to floating point arithmetic units and derive several simulated set-ups of pruned hardware with reasonable levels of error for applications in atmospheric modelling. The set-up is tested on the Lorenz '96 model, a toy model for atmospheric dynamics, using software emulation for the proposed hardware. The results show that large parts of the computation tolerate the use of pruned hardware blocks without major changes in the quality of short- and long-time diagnostics, such as forecast errors and probability density functions. This could open the door to significant savings in computational cost and to higher resolution simulations with weather and climate models.

Towards seasonal forecasting of malaria in India.

Malaria journal 13 (2014) 310-

JM Lauderdale, C Caminade, AE Heath, AE Jones, DA MacLeod, KC Gouda, US Murty, P Goswami, SR Mutheneni, AP Morse

Malaria presents public health challenge despite extensive intervention campaigns. A 30-year hindcast of the climatic suitability for malaria transmission in India is presented, using meteorological variables from a state of the art seasonal forecast model to drive a process-based, dynamic disease model.The spatial distribution and seasonal cycles of temperature and precipitation from the forecast model are compared to three observationally-based meteorological datasets. These time series are then used to drive the disease model, producing a simulated forecast of malaria and three synthetic malaria time series that are qualitatively compared to contemporary and pre-intervention malaria estimates. The area under the Relative Operator Characteristic (ROC) curve is calculated as a quantitative metric of forecast skill, comparing the forecast to the meteorologically-driven synthetic malaria time series.The forecast shows probabilistic skill in predicting the spatial distribution of Plasmodium falciparum incidence when compared to the simulated meteorologically-driven malaria time series, particularly where modelled incidence shows high seasonal and interannual variability such as in Orissa, West Bengal, and Jharkhand (North-east India), and Gujarat, Rajastan, Madhya Pradesh and Maharashtra (North-west India). Focusing on these two regions, the malaria forecast is able to distinguish between years of "high", "above average" and "low" malaria incidence in the peak malaria transmission seasons, with more than 70% sensitivity and a statistically significant area under the ROC curve. These results are encouraging given that the three month forecast lead time used is well in excess of the target for early warning systems adopted by the World Health Organization. This approach could form the basis of an operational system to identify the probability of regional malaria epidemics, allowing advanced and targeted allocation of resources for combatting malaria in India.

Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 372 (2014) 20130290-

A Weisheimer, S Corti, T Palmer, F Vitart

The finite resolution of general circulation models of the coupled atmosphere-ocean system and the effects of sub-grid-scale variability present a major source of uncertainty in model simulations on all time scales. The European Centre for Medium-Range Weather Forecasts has been at the forefront of developing new approaches to account for these uncertainties. In particular, the stochastically perturbed physical tendency scheme and the stochastically perturbed backscatter algorithm for the atmosphere are now used routinely for global numerical weather prediction. The European Centre also performs long-range predictions of the coupled atmosphere-ocean climate system in operational forecast mode, and the latest seasonal forecasting system--System 4--has the stochastically perturbed tendency and backscatter schemes implemented in a similar way to that for the medium-range weather forecasts. Here, we present results of the impact of these schemes in System 4 by contrasting the operational performance on seasonal time scales during the retrospective forecast period 1981-2010 with comparable simulations that do not account for the representation of model uncertainty. We find that the stochastic tendency perturbation schemes helped to reduce excessively strong convective activity especially over the Maritime Continent and the tropical Western Pacific, leading to reduced biases of the outgoing longwave radiation (OLR), cloud cover, precipitation and near-surface winds. Positive impact was also found for the statistics of the Madden-Julian oscillation (MJO), showing an increase in the frequencies and amplitudes of MJO events. Further, the errors of El Niño southern oscillation forecasts become smaller, whereas increases in ensemble spread lead to a better calibrated system if the stochastic tendency is activated. The backscatter scheme has overall neutral impact. Finally, evidence for noise-activated regime transitions has been found in a cluster analysis of mid-latitude circulation regimes over the Pacific-North America region.

Lorenz, Godel and Penrose: new perspectives on determinism and causality in fundamental physics

CONTEMPORARY PHYSICS 55 (2014) 157-178

TN Palmer

Climate forecasting: build high-resolution global climate models.

Nature 515 (2014) 338-339

T Palmer

Genesis of streamwise-localized solutions from globally periodic traveling waves in pipe flow.

Phys Rev Lett 112 (2014) 164501-

M Chantry, AP Willis, RR Kerswell

The aim in the dynamical systems approach to transitional turbulence is to construct a scaffold in phase space for the dynamics using simple invariant sets (exact solutions) and their stable and unstable manifolds. In large (realistic) domains where turbulence can coexist with laminar flow, this requires identifying exact localized solutions. In wall-bounded shear flows, the first of these has recently been found in pipe flow, but questions remain as to how they are connected to the many known streamwise-periodic solutions. Here we demonstrate that the origin of the first localized solution is in a modulational symmetry-breaking Hopf bifurcation from a known global traveling wave that has twofold rotational symmetry about the pipe axis. Similar behavior is found for a global wave of threefold rotational symmetry, this time leading to two localized relative periodic orbits. The clear implication is that many global solutions should be expected to lead to more realistic localized counterparts through such bifurcations, which provides a constructive route for their generation.

Studying edge geometry in transiently turbulent shear flows

Journal of Fluid Mechanics 747 (2014) 506-517

M Chantry, TM Schneider

© 2014 Cambridge University Press.In linearly stable shear flows at moderate Reynolds number, turbulence spontaneously decays despite the existence of a codimension-one manifold, termed the edge, which separates decaying perturbations from those triggering turbulence. We statistically analyse the decay in plane Couette flow, quantify the breaking of self-sustaining feedback loops and demonstrate the existence of a whole continuum of possible decay paths. Drawing parallels with low-dimensional models and monitoring the location of the edge relative to decaying trajectories, we provide evidence that the edge of chaos does not separate state space globally. It is instead wrapped around the turbulence generating structures and not an independent dynamical structure but part of the chaotic saddle. Thereby, decaying trajectories need not cross the edge, but circumnavigate it while unwrapping from the turbulent saddle.

On the reliability of seasonal climate forecasts.

Journal of the Royal Society, Interface 11 (2014) 20131162-

A Weisheimer, TN Palmer

Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1-5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that 'goodness' should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a '5' should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of 'goodness' rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching '5' across all regions and variables in 30 years time.

Modes of climate variability and heat waves in Victoria, southeastern Australia

Geophysical Research Letters 41 (2014) 6926-6934

TJ Parker, GJ Berry, MJ Reeder, N Nicholls

Rift valley fever outbreaks in Mauritania and related environmental conditions

International Journal of Environmental Research and Public Health 11 (2014) 903-918

C Caminade, JA Ndione, M Diallo, DA Macleod, O Faye, Y Ba, I Dia, AP Morse

Four large outbreaks of Rift Valley Fever (RVF) occurred in Mauritania in 1998, 2003, 2010 and 2012 which caused lots of animal and several human deaths. We investigated rainfall and vegetation conditions that might have impacted on RVF transmission over the affected regions. Our results corroborate that RVF transmission generally occurs during the months of September and October in Mauritania, similarly to Senegal. The four outbreaks were preceded by a rainless period lasting at least a week followed by heavy precipitation that took place during the second half of the rainy season. First human infections were generally reported three to five weeks later. By bridging the gap between meteorological forecasting centers and veterinary services, an early warning system might be developed in Senegal and Mauritania to warn decision makers and health services about the upcoming RVF risk. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Atmospheric science. Record-breaking winters and global climate change.

Science (New York, N.Y.) 344 (2014) 803-804

T Palmer

How Does the Quasi-Biennial Oscillation Affect the Stratospheric Polar Vortex?


PAG Watson, LJ Gray

The influence of tropical cyclones on heat waves in Southeastern Australia

Geophysical Research Letters 40 (2013) 6264-6270

TJ Parker, GJ Berry, MJ Reeder

Trapped mountain waves during a light aircraft accident

Australian Meteorological and Oceanographic Journal Australian Bureau of Meteorology 63 (2013) 377-389

TJ Parker, TP Lane

On 31 July 2007 a fatal light aircraft crash occurred near Clonbinane, Victoria, Australia and the official investigation concluded that mountain wave turbulence was the likely cause. This study uses three-dimensional numerical modelling and linear wave theory to examine the dynamics of mountain waves during this turbulence event and their role in generating turbulence. Analysis of the observed environment and three-dimensional idealised simulations elucidate the occurrence of trapped mountain waves and their role in creating regions of enhanced turbulence in the vicinity of the aircraft accident. Specifically, these waves perturb layers of low dynamic stability in the upstream flow, promoting turbulence in those layers. A simple ensemble of these three-dimensional simulations is also used to assess the robustness of the model solutions and demonstrate the utility of high-resolution ensembles for explicit mountain wave turbulence prediction.