Sarah-Jane Lock

SCIENTIST
Research Department, Earth System Modelling Section, Model Uncertainty Group

page tabs

Profile
Summary: 

Sarah-Jane Lock works in the Model Uncertainty Team. She maintains and develops the stochastic representations of model uncertainty, which form part of the forecast and assimilation systems.

 

Professional interests: 
  • Stochastic representations of model uncertainty, e.g. the Stochastically Perturbed Parametrization Tendencies (SPPT) scheme
  • Bringing greater physical consistency to model uncertainty representations
  • Exploring sources of model uncertainty across the forecasting system: atmospheric physics, atmospheric dynamics, coupled processes
  • Numerical methods for atmospheric models, e.g. time-integration methods
Career background: 
Education

PhD (2008), "Development of a new numerical model for studying microscale atmospheric dynamics"; Institute for Climate & Atmospheric Science (ICAS), University of Leeds, UK; Supervisors: Alan Gadian, Alison Coals

MSci Theoretical Physics (I) (1999); Queen Mary, University of London, UK

 

Professional

2013 -- present: Scientist, Research Department, ECMWF

2011 -- 2012: Post-Doctoral Research Assistant (Co-PI), ICAS, University of Leeds, UK; Gung-Ho project (with UK Met Office)

2008 -- 2010: Post-Doctoral Research Assistant, ICAS, University of Leeds, UK; COPS project

1999 -- 2004: Assistant Statistician, Department for Education & Skills, UK

 

External recognitions: 

Member of Royal Meteorological Society & Institute of Physics

Publications
Peer-reviewed publications
  • Mengaldo, G., Wyszogrodzki, A., Diamantakis, M., Lock, S.-J., Giraldo, F. X., Wedi, N. P., Current and emerging time-integration strategies in global numerical weather and climate prediction. Arch. Comput. Methods Eng., accepted
  • Leutbecher, M., Lock, S.-J., Ollinaho, P., Lang, et al. (2017), Stochastic representations of model uncertainties at ECMWF: state of the art and future vision. Q.J.R. Meteorol. Soc, 143: 2315–2339. doi:10.1002/qj.3094
  • Christensen, H. M., Lock, S.-J., Moroz, I. M. and Palmer, T. N. (2017), Introducing independent patterns into the Stochastically Perturbed Parametrization Tendencies (SPPT) scheme. Q.J.R. Meteorol. Soc., 143: 2168–2181. doi:10.1002/qj.3075
  • Ollinaho, P., Lock, S.-J., Leutbecher, M., Bechtold, P., Beljaars, A., Bozzo, A., Forbes, R. M., Haiden, T., Hogan, R. J. and Sandu, I. (2017), Towards process-level representation of model uncertainties: stochastically perturbed parametrizations in the ECMWF ensemble. Q.J.R. Meteorol. Soc., 143: 408–422. doi:10.1002/qj.2931
  • Good, B., Gadian, A., Lock, S.-J. and Ross, A. (2014), Performance of the cut-cell method of representing orography in idealized simulations. Atmos. Sci. Lett., 15: 44–49. doi:10.1002/asl2.465
  • Lock, S.-J., Wood, N. and Weller, H. (2014), Numerical analyses of Runge–Kutta implicit–explicit schemes for horizontally explicit, vertically implicit solutions of atmospheric models. Q.J.R. Meteorol. Soc., 140: 1654–1669. doi:10.1002/qj.2246
  • Weller, H., Lock, S.-J. and Wood, N. (2013), Runge–Kutta IMEX schemes for the Horizontally Explicit/Vertically Implicit (HEVI) solution of wave equations. J. Comp. Phys., 252: 365-381, https://doi.org/10.1016/j.jcp.2013.06.025.
  • Lock, S., H. Bitzer, A. Coals, A. Gadian, and S. Mobbs, 2012: Demonstration of a Cut-Cell Representation of 3D Orography for Studies of Atmospheric Flows over Very Steep Hills. Mon. Wea. Rev., 140, 411–424, https://doi.org/10.1175/MWR-D-11-00069.1
  • Bennett, L. J., Blyth, A. M., Burton, R. R., Gadian, A. M., Weckwerth, T. M., Behrendt, A., Di Girolamo, P., Dorninger, M., Lock, S.-J., Smith, V. H. and Mobbs, S. D. (2011), Initiation of convection over the Black Forest mountains during COPS IOP15a. Q.J.R. Meteorol. Soc., 137: 176–189. doi:10.1002/qj.760
Other publications:

thumbnail photo of Sarah-Jane Lock
Contact Details:
sarah-jane . lockecmwf . int