Publications by Tim Palmer


Improving Weather Forecast Skill through Reduced-Precision Data Assimilation

MONTHLY WEATHER REVIEW 146 (2018) 49-62

S Hatfield, A Subramanian, T Palmer, P Duben


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


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

Atmospheric Science Letters (2018)

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

© 2018 Royal Meteorological Society. Flow-dependent spread (FDS) is a desirable characteristic of probabilistic forecasts; ensemble spread should represent the expected forecast error. However this is difficult to estimate for seasonal hindcasts as they tend to have a relatively small sample size. Here we use a long (110year) seasonal hindcast dataset to evaluate FDS in forecasts of boreal winter North Atlantic Oscillation (NAO) and Pacific North American pattern (PNA). A good FDS relationship is found for interannual variations in both the NAO and PNA, with mild underdispersion for negative NAO and PNA events and slight overdispersion for positive NAO. Decadal-scale variability is seen in forecast errors but not in ensemble spread, which shows little variation on this timescale. Links between forecast errors and tropical heating anomalies are also investigated, though no strong links are found. However, a weak link between strong El Niño warming in the East Pacific and reduced PNA error is suggested.


Seasonal and decadal forecasts of Atlantic Sea surface temperatures using a linear inverse model

CLIMATE DYNAMICS 49 (2017) 1833-1845

B Huddart, A Subramanian, L Zanna, T Palmer


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


Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

GEOSCIENTIFIC MODEL DEVELOPMENT 10 (2017) 1383-1402

P Davini, J von Hardenberg, S Corti, HM Christensen, S Juricke, A Subramanian, PAG Watson, A Weisheimer, TN Palmer


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


Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures

COMPUTER PHYSICS COMMUNICATIONS 221 (2017) 160-173

FP Russell, PD Duben, X Niu, W Luk, TN Palmer


Reliable low precision simulations in land surface models

Climate Dynamics (2017) 1-10

A Dawson, PD Düben, DA MacLeod, TN Palmer

© 2017 The Author(s) Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.


Atmospheric seasonal forecasts of the twentieth century: multi-decadal variability in predictive skill of the winter North Atlantic Oscillation (NAO) and their potential value for extreme event attribution

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 143 (2017) 917-926

A Weisheimer, N Schaller, C O'Reilly, DA MacLeod, 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


On the use of scale-dependent precision in Earth System modelling

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 143 (2017) 897-908

T Thornes, P Duben, T Palmer


Single Precision in Weather Forecasting Models: An Evaluation with the IFS

MONTHLY WEATHER REVIEW 145 (2017) 495-502

F Vana, P Duben, S Lang, T Palmer, M Leutbecher, D Salmond, G Carver


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


A study of reduced numerical precision to make superparameterization more competitive using a hardware emulator in the OpenIFS model

JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 9 (2017) 566-584

PD Duben, A Subramanian, A Dawson, TN Palmer


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

JOURNAL OF CLIMATE 30 (2017) 4997-5019

S Juricke, TN Palmer, L Zanna


Impact of stochastic physics on tropical precipitation in the coupled ECMWF model

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 143 (2017) 852-865

A Subramanian, A Weisheimer, T Palmer, F Vitart, P Bechtold

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