GEOPHYSICAL RESEARCH LETTERS 38 (2011) ARTN L06801
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369 (2011) 4751-4767
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.
Decadal climate prediction with the European Centre for Medium-Range Weather Forecasts coupled forecast system: Impact of ocean observations
Journal of Geophysical Research: Atmospheres Blackwell Publishing Ltd 116 (2011)
Three 10 year ensemble decadal forecast experiments have been performed with the European Centre for Medium-Range Weather Forecasts coupled forecast system using an initialization strategy common in seasonal forecasting with realistic initial conditions. One experiment initializes the ocean in a standard way using an ocean-only simulation forced with an atmospheric reanalysis and with strong relaxation to observed sea surface temperatures. The other two experiments initialize the ocean from a similar ocean-only run that, in addition, assimilates subsurface observations. This is the first time that these experiments were performed. The system drifts from the realistic initial conditions toward the model climate, the drift being of the same order as, if not larger than, the interannual signal. There are small drift differences in the three experiments that reflect mainly the influence of dynamical ocean processes in controlling the adjustment between the initialized state and the model climate in the extratropics. In spite of the drift, the predictions show that the system is able to skillfully predict some of the interannual variability of the global and regional air and ocean temperature. No significant forecast quality benefit of the assimilation of ocean observations is found over the extratropics, although a negative impact of the assimilation of incorrect expendable bathythermograph profiles has been found for the global mean upper ocean heat content and the Atlantic multidecadal oscillation. The results illustrate the importance of reducing the important model drift and the ocean analysis uncertainty. Copyright 2011 by the American Geophysical Union.
Geophysical and Astrophysical Fluid Dynamics 105 (2011) 351-365
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.
Mon. Wea. Rev. American Meteorological Society 139 (2011) 2455-2470
Atmospheric blocking occurred over the Rocky Mountains at 1200 UTC 15 December 2005. The operational medium-range ensemble forecasts of the Canadian Meteorological Center (CMC), the Japan Meteorological Agency (JMA), and the National Centers for Environmental Prediction (NCEP), as initialized at 1200 UTC 10 December 2005, showed remarkable differences regarding this event. All of the NCEP members failed to predict the correct location of the blocking, whereas almost all of the JMA members and most of the CMC members were successful in predicting the correct location. The present study investigated the factors that caused NCEP to incorrectly predict the blocking location, based on an ensemble-based sensitivity analysis and the JMA global spectral model (GSM) multianalysis ensemble forecasts with NCEP, regionally amplified NCEP, and globally amplified NCEP analyses.A sensitive area for the blocking formation was detected over the central North Pacific. In this area, the NCEP control analysis experienced problems in the handling of a cutoff cyclone, and the NCEP initial perturbations were ineffective in reducing uncertainties in the NCEP control analysis. The JMA GSM multianalysis ensemble forecasts revealed that regional amplification of initial perturbations over the sensitive area could lead to further improvements in forecasts over the blocking region without degradation of forecasts over the Northern Hemisphere (NH), whereas the global amplification of initial perturbations could lead to improved forecasts over the blocking region and degraded forecasts over the NH. This finding may suggest that excessive amplification of initial perturbations over nonsensitive areas is undesirable, and that case-dependent rescaling of initial perturbations may be of value compared with climatology-based rescaling, which is widely used in current operational ensemble prediction systems.
Geophysical Research Letters 38 (2011)
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.
Analyzing precipitation projections: A comparison of different approaches to climate model evaluation
Journal of Geophysical Research 116 (2011)
Extended warming of the northern high latitudes due to an overshoot of the Atlantic meridional overturning circulation
Geophysical Research Letters 38 (2011) n/a-n/a
CLIMATE DYNAMICS 37 (2011) 455-471
JOURNAL OF CLIMATE 24 (2011) 6456-6470
Geophysical Research Letters 38 (2011)
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.
GEOPHYSICAL RESEARCH LETTERS 38 (2011) ARTN L11801
GEOPHYSICAL RESEARCH LETTERS 38 (2011) ARTN L16703
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 91 (2010) 1493-U121
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
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.
Forecast quality assessment of the ENSEMBLES seasonal-to-decadal Stream 2 hindcasts. ECMWF Tech Memo.
ECMWF (2010) 621
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
Bulletin of the American Meteorological Society 91 (2010) 1407-1412
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.