Publications


Systematic Errors in Weather and Climate Models: Nature, Origins, and Way Forward

Bulletin of the American Meteorological Society (2017)

A Zadra, K Williams, A Frassoni, M Rixen, Á Adames, J Berner, F Bouyssel, B Casati, HM Christensen, MB Ek, G Flato, Y Huang, F Judt, H Lin, E Maloney, W Merryfield, A van Niekerk, T Rackow, K Saito, N Wedi, P Yadav


A power law for reduced precision at small spatial scales: Experiments with an SQG model

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 144 (2018) 1179-1188

T Thornes, P Duben, T Palmer


The impact of stochastic parametrisations on the representation of the Asian summer monsoon

CLIMATE DYNAMICS 50 (2018) 2269-2282

K Strommen, HM Christensen, J Berner, TN Palmer


Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users

Climate Dynamics (2017) 1-20

A Alessandri, MD Felice, F Catalano, JY Lee, B Wang, DY Lee, JH Yoo, A Weisheimer

© 2017 Springer-Verlag GmbH Germany Multi-model ensembles (MMEs) are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single-model ensembles. Previous works suggested that the potential benefit that can be expected by using a MME amplifies with the increase of the independence of the contributing Seasonal Prediction Systems. In this work we combine the two MME Seasonal Prediction Systems (SPSs) independently developed by the European (ENSEMBLES) and by the Asian-Pacific (APCC/CliPAS) communities. To this aim, all the possible multi-model combinations obtained by putting together the 5 models from ENSEMBLES and the 11 models from APCC/CliPAS have been evaluated. The grand ENSEMBLES-APCC/CliPAS MME enhances significantly the skill in predicting 2m temperature and precipitation compared to previous estimates from the contributing MMEs. Our results show that, in general, the better combinations of SPSs are obtained by mixing ENSEMBLES and APCC/CliPAS models and that only a limited number of SPSs is required to obtain the maximum performance. The number and selection of models that perform better is usually different depending on the region/phenomenon under consideration so that all models are useful in some cases. It is shown that the incremental performance contribution tends to be higher when adding one model from ENSEMBLES to APCC/CliPAS MMEs and vice versa, confirming that the benefit of using MMEs amplifies with the increase of the independence the contributing models. To verify the above results for a real world application, the Grand ENSEMBLES-APCC/CliPAS MME is used to predict retrospective energy demand over Italy as provided by TERNA (Italian Transmission System Operator) for the period 1990–2007. The results demonstrate the useful application of MME seasonal predictions for energy demand forecasting over Italy. It is shown a significant enhancement of the potential economic value of forecasting energy demand when using the better combinations from the Grand MME by comparison to the maximum value obtained from the better combinations of each of the two contributing MMEs. The above results demonstrate for the first time the potential of the Grand MME to significantly contribute in obtaining useful predictions at the seasonal time-scale.


Ensemble sensitivity analysis of Greenland blocking in medium-range forecasts

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 144 (2018) 2358-2379

T Parker, T Woollings, A Weisheimer


Flow dependent ensemble spread in seasonal forecasts of the boreal winter extratropics

ATMOSPHERIC SCIENCE LETTERS 19 (2018) UNSP e815

D MacLeod, C O'Reilly, T Palmer, A Weisheimer


Stochastic representations of model uncertainties at ECMWF: state of the art and future vision

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 143 (2017) 2315-2339

M Leutbecher, S-J Lock, P Ollinaho, STK Lang, G Balsamo, P Bechtold, M Bonavita, HM Christensen, M Diamantakis, E Dutra, S English, M Fisher, RM Forbes, J Goddard, T Haiden, RJ Hogan, S Juricke, H Lawrence, D MacLeod, L Magnusson, S Malardel, S Massart, I Sandu, PK Smolarkiewicz, A Subramanian, F Vitart, N Wedi, A Weisheimer


The impact of stochastic physics on tropical rainfall variability in global climate models on daily to weekly time scales

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 122 (2017) 5738-5762

PAG Watson, J Berner, S Corti, P Davini, J von Hardenberg, C Sanchez, A Weisheimer, TN Palmer


Remote control of North Atlantic Oscillation predictability via the stratosphere

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 143 (2017) 706-719

F Hansen, RJ Greatbatch, G Gollan, T Jung, A Weisheimer


Stochastic Parameterization and El Nino-Southern Oscillation

JOURNAL OF CLIMATE 30 (2017) 17-38

HM Christensen, J Berner, DRB Coleman, TN Palmer


Introducing independent patterns into the Stochastically Perturbed Parametrization Tendencies (SPPT) scheme

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 143 (2017) 2168-2181

HM Christensen, S-J Lock, IM Moroz, TN Palmer


Variability in seasonal forecast skill of Northern Hemisphere winters over the twentieth century

GEOPHYSICAL RESEARCH LETTERS 44 (2017) 5729-5738

CH O'Reilly, J Heatley, D MacLeod, A Weisheimer, TN Palmer, N Schaller, T Woollings


Processes Maintaining Tropopause Sharpness in Numerical Models

Journal of Geophysical Research: Atmospheres 122 (2017) 9611-9627

L Saffin, SL Gray, J Methven, KD Williams

©2017. The Authors. Recent work has shown that the sharpness of the extratropical tropopause declines with lead time in numerical weather prediction models, indicating an imbalance between processes acting to sharpen and smooth the tropopause. In this study the systematic effects of processes contributing to the tropopause sharpness are investigated using daily initialized forecasts run with the Met Office Unified Model over a three-month winter period. Artificial tracers, each forced by the potential vorticity tendency due to a different model process, are used to separate the effects of such processes. The advection scheme is shown to result in an exponential decay of tropopause sharpness toward a finite value at short lead times with a time scale of 20–24 h. The systematic effect of nonconservative processes is to sharpen the tropopause, consistent with previous case studies. The decay of tropopause sharpness due to the advection scheme is stronger than the sharpening effect of nonconservative processes leading to a systematic decline in tropopause sharpness with forecast lead time. The systematic forecast errors in tropopause level potential vorticity are comparable to the integrated tendencies of the parametrized physical processes suggesting that the systematic error in tropopause sharpness could be significantly reduced through realistic adjustments to the model parametrization schemes.


The primacy of doubt: Evolution of numerical weather prediction from determinism to probability

JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 9 (2017) 730-734

T Palmer


Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 9 (2017) 1231-1250

AC Subramanian, TN Palmer


Potential applications of subseasonal-to-seasonal (S2S) predictions

METEOROLOGICAL APPLICATIONS 24 (2017) 315-325

CJ White, H Carlsen, AW Robertson, RJT Klein, JK Lazo, A Kumar, F Vitart, EC de Perez, AJ Ray, V Murray, S Bharwani, D MacLeod, R James, L Fleming, AP Morse, B Eggen, R Graham, E Kjellstrom, E Becker, KV Pegion, NJ Holbrook, D McEvoy, M Depledge, S Perkins-Kirkpatrick, TJ Brown, R Street, L Jones, TA Remenyi, I Hodgson-Johnston, C Buontempo, R Lamb, H Meinke, B Arheimer, SE Zebiak


Bitwise efficiency in chaotic models.

Proceedings. Mathematical, physical, and engineering sciences 473 (2017) 20170144-

S Jeffress, P Düben, T Palmer

Motivated by the increasing energy consumption of supercomputing for weather and climate simulations, we introduce a framework for investigating the bit-level information efficiency of chaotic models. In comparison with previous explorations of inexactness in climate modelling, the proposed and tested information metric has three specific advantages: (i) it requires only a single high-precision time series; (ii) information does not grow indefinitely for decreasing time step; and (iii) information is more sensitive to the dynamics and uncertainties of the model rather than to the implementation details. We demonstrate the notion of bit-level information efficiency in two of Edward Lorenz's prototypical chaotic models: Lorenz 1963 (L63) and Lorenz 1996 (L96). Although L63 is typically integrated in 64-bit 'double' floating point precision, we show that only 16 bits have significant information content, given an initial condition uncertainty of approximately 1% of the size of the attractor. This result is sensitive to the size of the uncertainty but not to the time step of the model. We then apply the metric to the L96 model and find that a 16-bit scaled integer model would suffice given the uncertainty of the unresolved sub-grid-scale dynamics. We then show that, by dedicating computational resources to spatial resolution rather than numeric precision in a field programmable gate array (FPGA), we see up to 28.6% improvement in forecast accuracy, an approximately fivefold reduction in the number of logical computing elements required and an approximately 10-fold reduction in energy consumed by the FPGA, for the L96 model.


STOCHASTIC PARAMETERIZATION Toward a New View of Weather and Climate Models

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 98 (2017) 565-587

J Berner, U Achatz, L Batte, L Bengtsson, A de la Camara, HM Christensen, M Colangeli, DRB Coleman, D Crommelin, SI Dolaptchiev, CLE Franzke, P Friederichs, P Imkeller, H Jarvinen, S Juricke, V Kitsios, F Lott, V Lucarini, S Mahajan, TN Palmer, C Penland, M Sakradzija, J-S von Storch, A Weisheimer, M Weniger, PD Williams, J-I Yano


Universal continuous transition to turbulence in a planar shear flow

JOURNAL OF FLUID MECHANICS 824 (2017) ARTN R1

M Chantry, LS Tuckerman, D Barkley


Stochastic Subgrid-Scale Ocean Mixing: Impacts on Low-Frequency Variability

JOURNAL OF CLIMATE 30 (2017) 4997-5019

S Juricke, TN Palmer, L Zanna

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