ENSO relationship to summer rainfall variability and its potential predictability over Arabian Peninsula region

npj Climate and Atmospheric Science Springer Nature 1:1 (2018) 20171

Authors:

Muhammad Adnan Abid, Mansour Almazroui, Fred Kucharski, Enda O’Brien, Ahmed Elsayed Yousef

Reliable low precision simulations in land surface models

CLIMATE DYNAMICS 51:7-8 (2017) 2657-2666

Authors:

Andrew Dawson, Peter D Dueben, David A MacLeod, Tim N Palmer

Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)

Geoscientific Model Development Discussions (2017) 1-35

Authors:

N Butchart, JA Anstey, K Hamilton, S Osprey, C McLandress, AC Bushell, Y Kawatani, Y-H Kim, F Lott, J Scinocca, T Stockdale, O Bellprat, P Braesicke, C Cagnazzo, C-C Chen, H-Y Chun, M Dobrynin, RR Garcia, J Garcia-Serrano, LJ Gray, L Holt, T Kerzenmacher, H Naoe, H Pohlmann, JH Richter, AA Scaife, V Schenzinger, F Serva, S Versick, S Watanabe, K Yoshida, S Yukimoto

Approximately right or precisely wrong? Meeting report on "Chaos and Confidence in Weather Forecasting'

WEATHER 72:10 (2017) 301-302

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

Quarterly Journal of the Royal Meteorological Society Wiley 143:707 (2017) 2315-2339

Authors:

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, R Forbes, J Goddard, T Haiden, R Hogan, Stephan Juricke, H Lawrence, Dave MacLeod, L Magnusson, S Malardel, S Massart, I Sandu, P Smolarkiewicz, Aneesh Subramanian, F Vitart, N Wedi, Antje Weisheimer

Abstract:

Members in ensemble forecasts differ due to the representations of initial uncertainties and model uncertainties. The inclusion of stochastic schemes to represent model uncertainties has improved the probabilistic skill of the ECMWF ensemble by increasing reliability and reducing the error of the ensemble mean. Recent progress, challenges and future directions regarding stochastic representations of model uncertainties at ECMWF are described in this paper. The coming years are likely to see a further increase in the use of ensemble methods in forecasts and assimilation. This will put increasing demands on the methods used to perturb the forecast model. An area that is receiving a greater attention than 5 to 10 years ago is the physical consistency of the perturbations. Other areas where future efforts will be directed are the expansion of uncertainty representations to the dynamical core and to other components of the Earth system as well as the overall computational efficiency of representing model uncertainty.