Climate Simulations Using MRI-AGCM3.2 with 20-km Grid

Journal of the Meteorological Society of Japan 90A (2012) 233-258


Reliability of decadal predictions

Geophysical Research Letters 39 (2012)

S Corti, A Weisheimer, TN Palmer, FJ Doblas-Reyes, L Magnusson

The reliability of multi-year predictions of climate is assessed using probabilistic Attributes Diagrams for near-surface air temperature and sea surface temperature, based on 54 member ensembles of initialised decadal hindcasts using the ECMWF coupled model. It is shown that the reliability from the ensemble system is good over global land areas, Europe and Africa and for the North Atlantic, Indian Ocean and, to a lesser extent, North Pacific basins for lead times up to 6-9years. North Atlantic SSTs are reliably predicted even when the climate trend is removed, consistent with the known predictability for this region. By contrast, reliability in the Indian Ocean, where external forcing accounts for most of the variability, deteriorates severely after detrending. More conventional measures of forecast quality, such as the anomaly correlation coefficient (ACC) of the ensemble mean, are also considered, showing that the ensemble has significant skill in predicting multi-annual temperature averages. © 2012. American Geophysical Union. All Rights Reserved.

Comparing TIGGE multimodel forecasts with reforecast-calibrated ECMWF ensemble forecasts

Quarterly Journal of the Royal Meteorological Society (2012)

R Hagedorn, R Buizza, TM Hamill, M Leutbecher, TN Palmer

The Effect of Climate Change on the Variability of the Northern Hemisphere Stratospheric Polar Vortex


Mitchell, DM, SM Osprey, Gray, LJ, Butchart, N, Hardiman, SC, Charlton-Perez, A, P Watson

Statistical analysis of global variations of atmospheric relative humidity as observed by AIRS

Journal of Geophysical Research: Atmospheres 117 (2012) n/a-n/a

J Du, F Cooper, S Fueglistaler

The Intra-Seasonal Oscillation and its control of tropical cyclones simulated by high-resolution global atmospheric models

CLIMATE DYNAMICS 39 (2012) 2185-2206

M Satoh, K Oouchi, T Nasuno, H Taniguchi, Y Yamada, H Tomita, C Kodama, J Kinter, D Achuthavarier, J Manganello, B Cash, T Jung, T Palmer, N Wedi

Towards the probabilistic Earth-system simulator: A vision for the future of climate and weather prediction

Quarterly Journal of the Royal Meteorological Society (2012)

TN Palmer

Simulating regime structures in weather and climate prediction models

Geophysical Research Letters 39 (2012) L21805

A Dawson, TN Palmer, S Corti

Quantifying uncertainty in future Southern Hemisphere circulation trends

Geophysical Research Letters 39 (2012)

PAG Watson, DJ Karoly, MR Allen, N Faull, DS Lee

The Antarctic polar night jet has intensified during spring in recent decades due to stratospheric ozone depletion and rising greenhouse gas (GHG) concentrations and this has had substantial effects on the region's climate. GHG concentrations will rise over the 21st century whereas stratospheric ozone is expected to recover and there is uncertainty in future southern hemisphere (SH) circulation trends. We examine sensitivity to the physics parameterisation of the 21st century SH circulation projection of a coupled atmosphere-ocean General Circulation Model and the sensitivity of the contribution from stratospheric ozone recovery. Different model parameterizations give a greater range of future trends in the position of the tropospheric jet than has been found in previous multi-model comparisons. Ozone recovery causes a weakening and northward shift of the DJF tropospheric jet. Varying the physics parameterization affects the zonal wind response to ozone recovery of the SON stratosphere by ∼10% and that of the DJF troposphere by ∼25%. The projected future SAM index changes with and without ozone recovery and the SAM index response to ozone recovery alone are found to be strongly positively correlated with projected 21st century global warming. © 2012. American Geophysical Union. All Rights Reserved.

Rossby wave dynamics of the North Pacific extra-tropical response to El Niño: Importance of the basic state in coupled GCMs

Climate Dynamics 37 (2011) 391-405

A Dawson, AJ Matthews, DP Stevens

Decadal climate prediction with the European Centre for Medium-Range Weather Forecasts coupled forecast system: Impact of ocean observations


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

Decadal climate prediction with the European Centre for Medium-Range Weather Forecasts coupled forecast system: Impact of ocean observations

Journal of Geophysical Research Atmospheres 116 (2011)

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

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.

Verification of medium-range MJO forecasts with TIGGE


M Matsueda, H Endo

Predictability of Euro-Russian blocking in summer of 2010


M Matsueda

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.

Future Change in Extratropical Cyclones Associated with Change in the Upper Troposphere

JOURNAL OF CLIMATE 24 (2011) 6456-6470

R Mizuta, M Matsueda, H Endo, S Yukimoto

Climate Sensitivity via a Nonparametric Fluctuation–Dissipation Theorem

Journal of the Atmospheric Sciences 68 (2011) 937-953

FC Cooper, PH Haynes

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.

Handling uncertainty in science.

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

TN Palmer, PJ Hardaker