Publications


ECMWF seasonal forecast system 3 and its prediction of sea surface temperature

CLIMATE DYNAMICS 37 (2011) 455-471

TN Stockdale, DLT Anderson, MA Balmaseda, F Doblas-Reyes, L Ferranti, K Mogensen, TN Palmer, F Molteni, F Vitart


Assessment of representations of model uncertainty in monthly and seasonal forecast ensembles

Geophysical Research Letters 38 (2011)

A Weisheimer, TN Palmer, FJ Doblas-Reyes

The probabilistic skill of ensemble forecasts for the first month and the first season of the forecasts is assessed, where model uncertainty is represented by the a) multi-model, b) perturbed parameters, and c) stochastic parameterisation ensembles. The main foci of the assessment are the Brier Skill Score for near-surface temperature and precipitation over land areas and the spread-skill relationship of sea surface temperature in the tropical equatorial Pacific. On the monthly timescale, the ensemble forecast system with stochastic parameterisation provides overall the most skilful probabilistic forecasts. On the seasonal timescale the results depend on the variable under study: for near surface temperature the multi-model ensemble is most skilful for most land regions and for global land areas. For precipitation, the ensemble with stochastic parameterisation most often produces the highest scores on global and regional scales. Our results indicate that stochastic parameterisations should now be developed for multi-decadal climate predictions using earth-system models. Copyright 2011 by the American Geophysical Union.


Uncertainty in weather and climate prediction

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369 (2011) 4751-4767

J Slingo, T Palmer

Following Lorenz's seminal work on chaos theory in the 1960s, probabilistic approaches to prediction have come to dominate the science of weather and climate forecasting. This paper gives a perspective on Lorenz's work and how it has influenced the ways in which we seek to represent uncertainty in forecasts on all lead times from hours to decades. It looks at how model uncertainty has been represented in probabilistic prediction systems and considers the challenges posed by a changing climate. Finally, the paper considers how the uncertainty in projections of climate change can be addressed to deliver more reliable and confident assessments that support decision-making on adaptation and mitigation. This journal is © 2011 The Royal Society.


A CERN for climate change

PHYSICS WORLD 24 (2011) 14-15

T Palmer


Assessment of representations of model uncertainty in monthly and seasonal forecast ensembles

GEOPHYSICAL RESEARCH LETTERS 38 (2011) ARTN L16703

A Weisheimer, TN Palmer, FJ Doblas-Reyes


The invariant set hypothesis: A new geometric framework for the foundations of quantum theory and the role played by gravity

Electronic Notes in Theoretical Computer Science 270 (2011) 115-119

TN Palmer

A new hypothesis is proposed about the nature of physical reality at its most primitive level. The hypothesis is framed in terms of invariance, a concept that forms the very bedrock of physics. Specifically, the Invariant Set Hypothesis proposes that states of physical reality are precisely those belonging to a non-computable fractal subset I of state space, invariant under the action of some subordinate deterministic causal dynamics D. The Invariant Set Hypothesis provides a geometric framework for a new perspective on quantum physics. © 2011 Elsevier B.V. All rights reserved.


Evaluation of probabilistic quality and value of the ENSEMBLES multimodel seasonal forecasts: Comparison with DEMETER

Monthly Weather Review 139 (2011) 581-607

A Alessandri, A Borrelli, A Navarra, A Arribas, M Déqué, P Rogel, A Weisheimer

The performance of the new multimodel seasonal prediction system developed in the framework of the European Commission FP7 project called ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) is compared with the results from the previous project [i.e., Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER)]. The comparison is carried out over the five seasonal prediction systems (SPSs) that participated in both projects. Since DEMETER, the contributing SPSs have improved in all aspects with the main advancements including the increase in resolution, the better representation of subgrid physical processes, land, sea ice, and greenhouse gas boundary forcing, and the more widespread use of assimilation for ocean initialization. The ENSEMBLES results show an overall enhancement for the prediction of anomalous surface temperature conditions. However, the improvement is quite small and with considerable space-time variations. In the tropics, ENSEMBLES systematically improves the sharpness and the discrimination attributes of the forecasts. Enhancements of the ENSEMBLES resolution attribute are also reported in the tropics for the forecasts started 1 February, 1 May, and 1 November. Our results indicate that, in ENSEMBLES, an increased portion of prediction signal from the single-models effectively contributes to amplify the multimodel forecasts skill. On the other hand, a worsening is shown for the multimodel calibration over the tropics compared to DEMETER. Significant changes are also shown in northern midlatitudes, where the ENSEMBLES multimodel discrimination, resolution, and reliability improve for February, May, and November starting dates. However, the ENSEMBLES multimodel decreases the capability to amplify the performance with respect to the contributing single models for the forecasts started in February, May, and August. This is at least partly due to the reduced overconfidence of the ENSEMBLES single models with respect to the DEMETER counterparts. Provided that they are suitably calibrated beforehand, it is shown that the ENSEMBLES multimodel forecasts represent a step forward for the potential economical value they can supply. A warning for all potential users concerns the need for calibration due to the degraded tropical reliability compared to DEMETER. In addition, the superiority of recalibrating the ENSEMBLES predictions through the discrimination information is shown. Concerning the forecasts started inAugust, ENSEMBLES exhibitsmixed results over both tropics and northernmidlatitudes. In this case, the increased potential predictability compared to DEMETER appears to be balanced by the reduction in the independence of the SPSs contributing to ENSEMBLES. Consequently, for the August start dates no clear advantage of using one multimodel system instead of the other can be evidenced. © 2011 American Meteorological Society.


Diagnosing the causes of bias in climate models - why is it so hard?

Geophysical and Astrophysical Fluid Dynamics 105 (2011) 351-365

TN Palmer, A Weisheimer

The equations of climate are, in principle, known. Why then is it so hard to formulate a biasfree model of climate? Here, some ideas in nonlinear dynamics are explored to try to answer this question. Specifically it is suggested that the climatic response to physically different forcings shows a tendency to project onto structures corresponding to the systems natural internal modes of variability. This is shown using results from complex climate models and from the relatively simple Lorenz three-component model. It is suggested that this behaviour is consistent with what might be expected from the fluctuation-dissipation theorem. Based on this, it is easy to see how climate models can easily suffer from having errors in the representation of two or more different physical processes, whose responses compensate one another and hence make individual error diagnosis difficult. A proposal is made to try to overcome these problems and advance the science needed to develop a bias-free climate model. The proposal utilises powerful diagnostics from data assimilation. The key point here is that these diagnostics derive from short-range forecast tendencies, estimated long before the model has asymptotically settled down to its (biased) climate attractor. However, it is shown that these diagnostics will not identify all sources of model error, and a so-called "bias of the second kind" is discussed. This latter bias may be alleviated by recently developed stochastic parametrisations. © 2011 Taylor & Francis.


Accuracy of climate change predictions using high resolution simulations as surrogates of truth

Geophysical Research Letters 38 (2011)

M Matsueda, TN Palmer

How accurate are predictions of climate change from a model which is biased against contemporary observations? If a model bias can be thought of as a state-independent linear offset, then the signal of climate change derived from a biased climate model should not be affected substantially by that model's bias. By contrast, if the processes which cause model bias are highly nonlinear, we could expect the accuracy of the climate change signal to degrade with increasing bias. Since we do not yet know the late 21st Century climate change signal, we cannot say at this stage which of these two paradigms describes best the role of model bias in studies of climate change. We therefore study this question using time-slice projections from a global climate model run at two resolutions - a resolution typical of contemporary climate models and a resolution typical of contemporary numerical weather prediction - and treat the high-resolution model as a surrogate of truth, for both 20th and 21st Century climate. We find that magnitude of the regionally varying model bias is a partial predictor of the accuracy of the regional climate change signal for both wind and precipitation. This relationship is particularly apparent for the 850 mb wind climate change signal. Our analysis lends some support to efforts to weight multi-model ensembles of climate change according to 20th Century bias, though note that the optimal weighting appears to be a nonlinear function of bias. Copyright © 2011 by the American Geophysical Union.


On the predictability of the extreme summer 2003 over Europe

Geophysical Research Letters 38 (2011)

A Weisheimer, FJ Doblas-Reyes, T Jung, TN Palmer

The European summer 2003 is a prominent example for an extreme hot and dry season. The main mechanisms that contributed to the growth of the heat wave are still disputed and state-of-the-art climate models have difficulty to realistically simulate the extreme conditions. Here we analyse simulations using recent versions of the European Centre for Medium-Range Weather Forecasts seasonal ensemble forecasting system and present, for the first time, retrospective forecasts which simulate accurately not only the abnormal warmth but also the observed precipitation and mid-tropospheric circulation patterns. It is found that while the land surface hydrology plays a crucial role, the successful simulations also required revised formulations of the radiative and convective parameterizations. We conclude that the predictability of the event was less due to remote teleconnections effects and more due to in situ processes which helped maintain the dry surface anomalies occurring at the beginning of the summer. Copyright 2011 by the American Geophysical Union.


Handling uncertainty in science.

Philos Trans A Math Phys Eng Sci 369 (2011) 4681-4684

TN Palmer, PJ Hardaker


Toward a new generation of world climate research and computing facilities

Bulletin of the American Meteorological Society 91 (2010) 1407-1412

J Shukla, TN Palmer, R Hagedorn, B Hoskins, J Kinter, J Marotzke, M Miller, J Slingo

National climate research facilities must be enhanced and dedicated multi-national facilities should be established to accelerate progress in understanding and predicting regional climate change. In addition to the merits of running climate models at a resolution comparable with that of NWP models, the continual confrontation of an NWP model with observations can provide important constraints when the same model is used for much longer-time-scale climate predictions. Short-range forecast models give encouraging results using grid lengths of close to 1 km, without parameterizing deep convection. Prediction uncertainty, a key variable can be estimated by making an ensemble of forecasts with varying initial conditions, model equations, and other input fields such as greenhouse gas concentrations. The new generation of models will yield improved statistics of daily weather and, therefore, better predictions of regional climate variations on seasonal time scales.


Is science fiction a genre for communicating scientific research? A case study in climate prediction

Bulletin of the American Meteorological Society 91 (2010) 1413-1415

TN Palmer

The author, T. N. Palmer describes a book by Isaac Asimov titled Nightfall, which describes a civilization's first encounter with darkness for thousands of years. The civilization inhabits the planet Lagash, which orbits one of six gravitationally-bound suns. Nightfall occurs during a total eclipse, when only one of the suns is above the horizon. Although in this sense climate change is inherently predictable, the author is not confirm whether how reliable the predictions of climate change are in practice. The first message of the story is that reliable predictions of regional climate change are crucially important to guide decisions on infrastructure investment for societies to adapt to future climate change. The second message of the story is that if current climate models can systematically misrepresent the regional effects of the annual cycle, they can also misrepresent the regional effects of climate change. One way to reduce these systematic deficiencies would be to simulate more of the climate system with the proper equations of motion.


An Earth-system prediction initiative for the twenty-first century

Bulletin of the American Meteorological Society 91 (2010) 1377-1388

M Shapiro, J Shukla, G Brunet, C Nobre, M Béland, R Dole, K Trenberth, R Anthes, G Asrar, L Barrie, P Bougeault, G Brasseur, D Burridge, A Busalacchi, J Caughey, D Chen, J Church, T Enomoto, B Hoskins, Ø Hov, A Laing, H Le Treut, J Marotzke, G McBean, G Meehl, M Miller, B Mills, J Mitchell, M Moncrieff, T Nakazawa, H Olafsson, T Palmer, D Parsons, D Rogers, A Simmons, A Troccoli, Z Toth, L Uccellini, C Velden, JM Wallace

Some scientists have proposed the Earth-System Prediction Initiative (EPI) at the 2007 GEO Summit in Cape Town, South Africa. EPI will draw upon coordination between international programs for Earth system observations, prediction, and warning, such as the WCRP, WWRP, GCOS, and hence contribute to GEO and the GEOSS. It will link with international organizations, such as the International Council for Science (ICSU), Intergovernmental Oceanographic Commission (IOC), UNEP, WMO, and World Health Organization (WHO). The proposed initiative will provide high-resolution climate models that capture the properties of regional high-impact weather events, such as tropical cyclones, heat wave, and sand and dust storms associated within multi-decadal climate projections of climate variability and change. Unprecedented international collaboration and goodwill are necessary for the success of EPI.


EXTENDED-RANGE PROBABILISTIC FORECASTS OF GANGES AND BRAHMAPUTRA FLOODS IN BANGLADESH

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 91 (2010) 1493-1514

PJ Webster, J Jian, TM Hopson, CD Hoyos, PA Agudelo, H-R Chang, JA Curry, RL Grossman, TN Palmer, AR Subbiah


Impact of 2007 and 2008 Arctic ice anomalies on the atmospheric circulation: Implications for long-range predictions

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 136 (2010) 1655-1664

MA Balmaseda, L Ferranti, F Molteni, TN Palmer


Model uncertainty in seasonal to decadal forecasting - insight from the ENSEMBLES project.

ECMWF Newsletter ECMWF 122 (2010) 21-26

A Weisheimer, FJ Doblas-Reyes, TN Palmer


Forecast quality assessment of the ENSEMBLES seasonal-to-decadal Stream 2 hindcasts. ECMWF Tech Memo.

ECMWF (2010) 621

FJ Doblas-Reyes, A Weisheimer, TN Palmer, JM Murphy, D Smith


Decadal climate prediction with the ECMWF coupled forecast system: Impact of ocean observations. ECMWF Tech Memo.

(2010) 633

FJ Doblas-Reyes, MA Balmaseda, A Weisheimer, TN Palmer


The Tat Protein Export Pathway.

EcoSal Plus 4 (2010)

T Palmer, F Sargent, BC Berks

Proteins that reside partially or completely outside the bacterial cytoplasm require specialized pathways to facilitate their localization. Globular proteins that function in the periplasm must be translocated across the hydrophobic barrier of the inner membrane. While the Sec pathway transports proteins in a predominantly unfolded conformation, the Tat pathway exports folded protein substrates. Protein transport by the Tat machinery is powered solely by the transmembrane proton gradient, and there is no requirement for nucleotide triphosphate hydrolysis. Proteins are targeted to the Tat machinery by N-terminal signal peptides that contain a consensus twin arginine motif. In Escherichia coli and Salmonella there are approximately thirty proteins with twin arginine signal peptides that are transported by the Tat pathway. The majority of these bind complex redox cofactors such as iron sulfur clusters or the molybdopterin cofactor. Here we describe what is known about Tat substrates in E. coli and Salmonella, the function and mechanism of Tat protein export, and how the cofactor insertion step is coordinated to ensure that only correctly assembled substrates are targeted to the Tat machinery.

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