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


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

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

Stratospheric Response to the 11-Yr Solar Cycle: Breaking Planetary Waves, Internal Reflection, and Resonance

JOURNAL OF CLIMATE 30 (2017) 7169-7190

H Lu, LJ Gray, IP White, TJ Bracegirdle

A family of super congruences involving multiple harmonic sums

International Journal of Number Theory 13 (2017) 109-128

M McCoy, K Thielen, L Wang, J Zhao

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.

A deformation-based parametrization of ocean mesoscale eddy reynolds stresses

Ocean Modelling 112 (2017) 99-111

JA Anstey, L Zanna

© 2017 The Authors Ocean mesoscale eddies strongly affect the strength and variability of large-scale ocean jets such as the Gulf Stream and Kuroshio Extension. Their spatial scales are too small to be fully resolved in many current climate models and hence their effects on the large-scale circulation need to be parametrized. Here we propose a parametrization of mesoscale eddy momentum fluxes based on large-scale flow deformation. The parametrization is argued to be suitable for use in eddy-permitting ocean general circulation models, and is motivated by an analogy between turbulence in Newtonian fluids (such as water) and laminar flow in non-Newtonian fluids. A primitive-equations model in an idealised double-gyre configuration at eddy-resolving horizontal resolution is used to diagnose the relationship between the proposed closure and the eddy fluxes resolved by the model. Favourable correlations suggest the closure could provide an appropriate deterministic parametrization of mesoscale eddies. The relationship between the closure and different representations of the Reynolds stress tensor is also described. The parametrized forcing possesses the key quasi-geostrophic turbulence properties of energy conservation and enstrophy dissipation, and allows for upgradient fluxes leading to the sharpening of vorticity gradients. The implementation of the closure for eddy-permitting ocean models requires only velocity derivatives and a single parameter that scales with model resolution.

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


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

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


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

Nonstationarity in Southern Hemisphere Climate Variability Associated with the Seasonal Breakdown of the Stratospheric Polar Vortex

JOURNAL OF CLIMATE 30 (2017) 7125-7139

NJ Byrne, TG Shepherd, T Woollings, RA Plumb

Impact of Atmospheric Blocking on South America in Austral Summer

JOURNAL OF CLIMATE 30 (2017) 1821-1837

RR Rodrigues, T Woollings

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.

Transforming climate model output to forecasts of wind power production: How much resolution is enough?

Meteorological Applications (2017)

D Macleod, V Torralba, M Davis, F Doblas-Reyes

© 2017 Royal Meteorological Society. Wind power forecasts are useful tools for power load balancing, energy trading and wind farm operations. Long range monthly-to-seasonal forecasting allows the prediction of departures from average weather conditions beyond traditional weather forecast timescales, months in advance. However, it has not yet been demonstrated how these forecasts can be optimally transformed to wind power. The predictable part of a seasonal forecast is for longer monthly averages, not daily averages, but to use monthly averages misses information on variability. To investigate, here a model relating average weather conditions to average wind power output was built, based on the relationship between instantaneous wind speed and power production and incorporating fluctuations in air density due to temperature and wind speed variability. Observed monthly average power output from UK stations was used to validate the model and to investigate the optimal temporal resolution for the data used to drive the model. Multiple simulations of wind power were performed based on reanalysis data, making separate simulations based on monthly, daily and sub-daily averages, using a distribution defined by the mean across the period to incorporate information on variability. Basing the simulation on monthly averages alone is sub-optimal: using daily average winds gives the highest correlation against observations. No improvement over this is gained by using sub-daily averages or including temperature variability. This signifies that to transform seasonal forecasts to wind power a compromise must be made between using the daily averages with debatable skill and the more predictable monthly averages, losing information on day-to-day variability.

Scale-aware deterministic and stochastic parametrizations of eddy-mean flow interaction

Ocean Modelling 111 (2017) 66-80

L Zanna, PGL Porta Mana, J Anstey, T David, T Bolton

© 2017 The Authors The role of mesoscale eddies is crucial for the ocean circulation and its energy budget. The sub-grid scale eddy variability needs to be parametrized in ocean models, even at so-called eddy permitting resolutions. Porta Mana and Zanna (2014) propose an eddy parametrization based on a non-Newtonian stress which depends on the partially resolved scales and their variability. In the present study, we test two versions of the parametrization, one deterministic and one stochastic, at coarse and eddy-permitting resolutions in a double gyre quasi-geostrophic model. The parametrization leads to drastic improvements in the mean state and variability of the ocean state, namely in the jet rectification and the kinetic-energy spectra as a function of wavenumber and frequency for eddy permitting models. The parametrization also appears to have a stabilizing effect on the model, especially the stochastic version. The parametrization possesses attractive features for implementation in global models: very little computational cost, it is flow aware and uses the properties of the underlying flow. The deterministic coefficient is scale-aware, while the stochastic parameter is scale- and flow-aware with dependence on resolution, stratification and wind forcing.

Universal continuous transition to turbulence in a planar shear flow


M Chantry, LS Tuckerman, D Barkley

Drivers of uncertainty in simulated ocean circulation and heat uptake

Geophysical Research Letters 44 (2017) 1402-1413

MB Huber, L Zanna

©2017. The Authors. The impact of uncertainties in air-sea fluxes and ocean model parameters on the ocean circulation and ocean heat uptake (OHU) is assessed in a novel modeling framework. We use an ocean-only model forced with the simulated sea surface fields of the CMIP5 climate models. The simulations are performed using control and 1% CO 2 warming scenarios. The ocean-only ensemble adequately reproduces the mean Atlantic Meridional Overturning Circulation (AMOC) and the zonally integrated OHU. The ensemble spread in AMOC strength, its weakening, and Atlantic OHU due to different air-sea fluxes is twice as large as the uncertainty range related to vertical and mesocale eddy diffusivities. The sensitivity of OHU to uncertainties in air-sea fluxes and model parameters differs vastly across basins, with the Southern Ocean exhibiting strong sensitivity to air-sea fluxes and model parameters. This study clearly demonstrates that model biases in air-sea fluxes are one of the key sources of uncertainty in climate simulations.

Eddy-Driven Jet Sensitivity to Diabatic Heating in an Idealized GCM

JOURNAL OF CLIMATE 30 (2017) 6413-6431

HS Baker, T Woollings, C Mbengue

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


PD Duben, A Subramanian, A Dawson, TN Palmer

Vortex disruption by magnetohydrodynamic feedback


J Mak, SD Griffiths, DW Hughes

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


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