Publications


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


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.


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


Systematic Model Error: The Impact of Increased Horizontal Resolution versus Improved Stochastic and Deterministic Parameterizations

JOURNAL OF CLIMATE 25 (2012) 4946-4962

J Berner, T Jung, TN Palmer


Useful decadal climate prediction at regional scales? A look at the ENSEMBLES stream 2 decadal hindcasts

Environmental Research Letters 7 (2012)

DA MacLeod, C Caminade, AP Morse

Decadal climate prediction is a branch of climate modelling with the theoretical potential to anticipate climate impacts years in advance. Here we present analysis of the ENSEMBLES decadal simulations, the first multi-model decadal hindcasts, focusing on the skill in prediction of temperature and precipitation - important for impact prediction. Whilst previous work on this dataset has focused on the skill in multi-year averages, we focus here on the skill in prediction at smaller timescales. Considering annual and seasonal averages, we look at correlations, potential predictability and multi-year trend correlations. The results suggest that the prediction skill for temperature comes from the long-term trend, and that precipitation predictions are not skilful. The potential predictability of the models is higher for annual than for seasonal means and is largest over the tropics, though it is low everywhere else and is much lower for precipitation than for temperature. The globally averaged temperature trend correlation is significant at the 99% level for all models and is higher for annual than for seasonal averages; however, for smaller spatial regions the skill is lower. For precipitation trends, the correlations are not skilful on either annual or seasonal scales. Whilst climate models run in decadal prediction mode may be useful by other means, the hindcasts studied here have limited predictive power on the scales at which climate impacts and the results presented suggest that they do not yet have sufficient skill to drive impact models on decadal timescales. © 2012 IOP Publishing Ltd.


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


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


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


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.


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

(2012)

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


The emergence of zonal ocean jets under large-scale stochastic wind forcing

Geophysical Research Letters 39 (2012) n/a-n/a

CH O'Reilly, A Czaja, JH LaCasce


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

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

R MIZUTA, H YOSHIMURA, H MURAKAMI, M MATSUEDA, H ENDO, T OSE, K KAMIGUCHI, M HOSAKA, M SUGI, S YUKIMOTO, S KUSUNOKI, A KITOH


High-Resolution Global Climate Simulations with the ECMWF Model in Project Athena: Experimental Design, Model Climate, and Seasonal Forecast Skill

JOURNAL OF CLIMATE 25 (2012) 3155-3172

T Jung, MJ Miller, TN Palmer, P Towers, N Wedi, D Achuthavarier, JM Adams, EL Altshuler, BA Cash, KJL III, L Marx, C Stan, KI Hodges


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.


Simulating regime structures in weather and climate prediction models

Geophysical Research Letters 39 (2012) L21805

A Dawson, TN Palmer, S Corti


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

Quarterly Journal of the Royal Meteorological Society 138 (2012) 841-861

TN Palmer

There is no more challenging problem in computational science than that of estimating, as accurately as science and technology allows, the future evolution of Earth's climate; nor indeed is there a problem whose solution has such importance and urgency. Historically, the simulation tools needed to predict climate have been developed, somewhat independently, at a number of weather and climate institutes around the world. While these simulators are individually deterministic, it is often assumed that the resulting diversity provides a useful quantification of uncertainty in global or regional predictions. However, this notion is not well founded theoretically and corresponding 'multi-simulator' estimates of uncertainty can be prone to systemic failure. Separate to this, individual institutes are now facing considerable challenges in finding the human and computational resources needed to develop more accurate weather and climate simulators with higher resolution and full Earth-system complexity. A new approach, originally designed to improve reliability in ensemble-based numerical weather prediction, is introduced to help solve these two rather different problems. Using stochastic mathematics, this approach recognizes uncertainty explicitly in the parametrized representation of unresolved climatic processes. Stochastic parametrization is shown to be more consistent with the underlying equations of motion and, moreover, provides more skilful estimates of uncertainty when compared with estimates from traditional multi-simulator ensembles, on time-scales where verification data exist. Stochastic parametrization can also help reduce long-term biases which have bedevilled numerical simulations of climate from the earliest days to the present. As a result, it is suggested that the need to maintain a large 'gene pool' of quasi-independent deterministic simulators may be obviated by the development of probabilistic Earth-system simulators. Consistent with the conclusions of the World Summit on Climate Modelling, this in turn implies that individual institutes will be able to pool human and computational resources in developing future-generation simulators, thus benefitting from economies of scale; the establishment of the Airbus consortium provides a useful analogy here. As a further stimulus for such evolution, discussion is given to a potential new synergy between the development of dynamical cores, and stochastic processing hardware. However, it is concluded that the traditional challenge in numerical weather prediction, of reducing deterministic measures of forecast error, may increasingly become an obstacle to the seamless development of probabilistic weather and climate simulators, paradoxical as that may appear at first sight. Indeed, going further, it is argued that it may be time to consider focusing operational weather forecast development entirely on high-resolution ensemble prediction systems. Finally, by considering the exceptionally challenging problem of quantifying cloud feedback in climate change, it is argued that the development of the probabilistic Earth-system simulator may actually provide a route to reducing uncertainty in climate prediction. © 2012 Royal Meteorological Society.


A discontinuous/continuous low order finite element shallow water model on the sphere

Journal of Computational Physics 231 (2012)

Dueben, P Korn, V Aizinger


A CERN for climate change

PHYSICS WORLD 24 (2011) 14-15

T Palmer


Predictability of an Atmospheric Blocking Event that Occurred on 15 December 2005

Monthly weather review American Meteorological Society 139 (2011) 2455-2470

M MATSUEDA

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.


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.