Publications


It's all just physics

PHYSICS WORLD 27 (2014) 18-19

T Palmer


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.


More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 372 (2014) 20130391-

TN Palmer

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic-dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only.


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

Physical Review Letters American Physical Society 112 (2014)

M Chantry, A Willis, R 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


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


Automating the solution of PDEs on the sphere and other manifolds in FEniCS 1.2

GEOSCIENTIFIC MODEL DEVELOPMENT 6 (2013) 2099-2119

ME Rognes, DA Ham, CJ Cotter, ATT McRae


Should weather and climate prediction models be deterministic or stochastic?

Weather Wiley 68 (2013) 264-264

HM Arnold


Singular vectors, predictability and ensemble forecasting for weather and climate

Journal of Physics A: Math. Theor. 46 (2013) 254018

TN Palmer, L Zanna


Impact of snow initialization on sub-seasonal forecasts

Climate Dynamics 41 (2013) 1969-1982

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

The influence of the snowpack on wintertime atmospheric teleconnections has received renewed attention in recent years, partially for its potential impact on seasonal predictability. Many observational and model studies have indicated that the autumn Eurasian snow cover in particular, influences circulation patterns over the North Pacific and North Atlantic. We have performed a suite of coupled atmosphere-ocean simulations with the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecast system to investigate the impact of accurate snow initialisation. Pairs of 2-month ensemble forecasts were started every 15 days from the 15th of October through the 1st of December in the years 2004-2009, with either realistic initialization of snow variables based on re-analyses, or else with "scrambled" snow initial conditions from an alternate autumn date and year. Initially, in the first 15 days, the presence of a thicker snowpack cools surface temperature over the continental land masses of Eurasia and North America. At a longer lead of 30-day, it causes a warming over the Arctic and the high latitudes of Eurasia due to an intensification and westward expansion of the Siberian High. It also causes a cooling over the mid-latitudes of Eurasia, and lowers sea level pressures over the Arctic. This "warm Arctic-cold continent" difference means that the forecasts of near-surface temperature with the more realistic snow initialization are in closer agreement with re-analyses, reducing a cold model bias over the Arctic and a warm model bias over mid-latitudes. The impact of realistic snow initialization upon the forecast skill in snow depth and near-surface temperature is estimated for various lead times. Following a modest skill improvement in the first 15 days over snow-covered land, we also find a forecast skill improvement up to the 30-day lead time over parts of the Arctic and the Northern Pacific, which can be attributed to the realistic snow initialization over the land masses. © 2013 Springer-Verlag Berlin Heidelberg.


Stochastic Parameterisations and Model Uncertainty in the Lorenz '96 system

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Royal Society 371 (2013) 20110479

HM Arnold, IM Moroz, TN Palmer


REVOLUTIONIZING CLIMATE MODELING WITH PROJECT ATHENA A Multi-Institutional, International Collaboration

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 94 (2013) 231-245

KJL III, B Cash, D Achuthavarier, J Adams, E Altshuler, P Dirmeyer, B Doty, B Huang, EK Jin, L Marx, J Manganello, C Stan, T Wakefield, T Palmer, M Hamrud, T Jung, M Miller, P Towers, N Wedi, M Satoh, H Tomita, C Kodama, T Nasuno, K Oouchi, Y Yamada, H Taniguchi, P Andrews, T Baer, M Ezell, C Halloy, D John, B Loftis, R Mohr, K Wong


Near-term climate change: Projections and predictability

in Climate Change 2013 the Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 9781107057999 (2013) 953-1028

NL Bindoff, PJ Durack, A Slater, P Cameron-Smith, Y Chikamoto, O Clifton, P Ginoux, M Holland, C Holmes, J Infanti, D Jacob, J John, T Knutson, D Lawrence, J Lu, D Murphy, V Naik, A Robock, S Vavrus, M Ishii, S Corti, T Fichefet, J García-Serrano, V Guemas, L Rodrigues, L Gray, E Hawkins, D Smith, DS Stevenson, A Voulgarakis, A Weisheimer, O Wild, T Woollings, P Young, G Krinner, Z Klimont, J Sedláček, B van den Hurk, T van Noije

© Intergovernmental Panel on Climate Change 2014. Executive Summary. This chapter assesses the scientific literature describing expectations for near-term climate (present through mid-century). Unless otherwise stated, ‘near-term’ change and the projected changes below are for the period 2016-2035 relative to the reference period 1986-2005. Atmospheric composition (apart from CO2; see Chapter 12) and air quality projections through to 2100 are also assessed. Decadal Prediction. The nonlinear and chaotic nature of the climate system imposes natual limits on the extent to which skilful predictions of climate statistics may be made. M.del-based ‘predictability’ studies, which probe these limits and investigate the physical mechanisms involved, support the potential for the skilful prediction of annual to decadal average temperature and, to a lesser extent precipitation. Predictions for averages of temperature, over large regions of the planet and for the global mean, exhibit positive skill when verified against observations for forecast periods up to ten years (high confidence). Predictions of precipitation over some land areas also exhibit positive skill. Decadal prediction is a new endeavour in climate science. The level of quality for climate predictions of annual to decadal average quantities is assessed from the past performance of initialized predictions and non-initialized simulations. {11.2.3, Figures 11.3 and 11.4}. In current results, observation-based initialization is the dominant contributor to the skill of predictions of annual mean temperature for the first few years and to the skill of predictions of the global mean surface temperature and the temperature over the North Atlantic, regions of the South Pacific and the tropical Indian Ocean for longer periods (high confidence).


Aspects of weather parameters at Neumayer station, Antarctica, and their representation in reanalysis and climate model data

METEOROLOGISCHE ZEITSCHRIFT 22 (2013) 699-709

M Kloewer, T Jung, G Koenig-Langlo, T Semmler


Predicting multiyear North Atlantic Ocean variability

Journal of Geophysical Research: Oceans 118 (2013) 1087-1098

W Hazeleger, B Wouters, GJ Van Oldenborgh, S Corti, T Palmer, D Smith, N Dunstone, J Kröger, H Pohlmann, JS Von Storch

We assess the skill of retrospective multiyear forecasts of North Atlantic ocean characteristics obtained with ocean-atmosphere-sea ice models that are initialized with estimates from the observed ocean state. We show that these multimodel forecasts can skilfully predict surface and subsurface ocean variability with lead times of 2 to 9 years. We focus on assessment of forecasts of major well-observed oceanic phenomena that are thought to be related to the Atlantic meridional overturning circulation (AMOC). Variability in the North Atlantic subpolar gyre, in particular that associated with the Atlantic Multidecadal Oscillation, is skilfully predicted 2-9 years ahead. The fresh water content and heat content in major convection areas such as the Labrador Sea are predictable as well, although individual events are not captured. The skill of these predictions is higher than that of uninitialized coupled model simulations and damped persistence. However, except for heat content in the subpolar gyre, differences between damped persistence and the initialized predictions are not significant. Since atmospheric variability is not predictable on multiyear time scales, initialization of the ocean and oceanic processes likely provide skill. Assessment of relationships of patterns of variability and ocean heat content and fresh water content shows differences among models indicating that model improvement can lead to further improvements of the predictions. The results imply there is scope for skilful predictions of the AMOC. © 2013. American Geophysical Union. All Rights Reserved.


Climate extremes and the role of dynamics.

Proc Natl Acad Sci U S A 110 (2013) 5281-5282

TN Palmer


Impact of snow initialization on sub-seasonal forecasts

Climate Dynamics (2013) 1-14

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

The influence of the snowpack on wintertime atmospheric teleconnections has received renewed attention in recent years, partially for its potential impact on seasonal predictability. Many observational and model studies have indicated that the autumn Eurasian snow cover in particular, influences circulation patterns over the North Pacific and North Atlantic. We have performed a suite of coupled atmosphere-ocean simulations with the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecast system to investigate the impact of accurate snow initialisation. Pairs of 2-month ensemble forecasts were started every 15 days from the 15th of October through the 1st of December in the years 2004-2009, with either realistic initialization of snow variables based on re-analyses, or else with "scrambled" snow initial conditions from an alternate autumn date and year. Initially, in the first 15 days, the presence of a thicker snowpack cools surface temperature over the continental land masses of Eurasia and North America. At a longer lead of 30-day, it causes a warming over the Arctic and the high latitudes of Eurasia due to an intensification and westward expansion of the Siberian High. It also causes a cooling over the mid-latitudes of Eurasia, and lowers sea level pressures over the Arctic. This "warm Arctic-cold continent" difference means that the forecasts of near-surface temperature with the more realistic snow initialization are in closer agreement with re-analyses, reducing a cold model bias over the Arctic and a warm model bias over mid-latitudes. The impact of realistic snow initialization upon the forecast skill in snow depth and near-surface temperature is estimated for various lead times. Following a modest skill improvement in the first 15 days over snow-covered land, we also find a forecast skill improvement up to the 30-day lead time over parts of the Arctic and the Northern Pacific, which can be attributed to the realistic snow initialization over the land masses. © 2013 Springer-Verlag Berlin Heidelberg.

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