Skip to main content
Home
Department Of Physics text logo
  • Research
    • Our research
    • Our research groups
    • Our research in action
    • Research funding support
    • Summer internships for undergraduates
  • Study
    • Undergraduates
    • Postgraduates
  • Engage
    • For alumni
    • For business
    • For schools
    • For the public
Menu
Juno Jupiter image

Hannah Christensen (she/her)

Associate Professor

Research theme

  • Climate physics

Sub department

  • Atmospheric, Oceanic and Planetary Physics

Research groups

  • Atmospheric processes
Hannah.Christensen@physics.ox.ac.uk
Telephone: 01865 (2)72908
Atmospheric Physics Clarendon Laboratory, room F52
  • About
  • Teaching
  • Talks and Media
  • DPhil applicants
  • Publications

Advancing Organized Convection Representation in the Unified Model: Implementing and Enhancing Multiscale Coherent Structure Parameterization

Journal of Advances in Modelling Earth Systems

Authors:

Hannah Christensen, Zhixiao Zhang, Mark Muetzelfeldt, Tim Woollings, Robert Plant, Alison Stirling, Michael Whitall, Mitch Moncrieff, Chih-Chih Chen, Zhe Feng
More details from the publisher

Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in climate simulations

Geoscientific Model Development European Geosciences Union

Authors:

Paolo Davini, Jost von Hardenberg, Susanna Corti, Hannah M Christensen, Stephan Juricke, Aneesh Subramanian, Peter AG Watson, Antje Weisheimer, Tim N Palmer

Abstract:

<p><strong>Abstract.</strong> The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 km up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PBytes of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Center (LRZ) in Garching, Germany. About 140 TBytes of post-processed data are stored on the CINECA supercomputing center archives and are freely accessible to the community thanks to an EUDAT Data Pilot project. This paper presents the technical and scientific setup of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given: an improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increases is observed. It is also shown that including stochastic parameterisation in the low resolution runs helps to improve some aspects of the tropical climate – specifically the Madden-Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).</p>
More details from the publisher
Details from ORA

Continuous Structural Parameterization: A method for representing different model parameterizations within one structure demonstrated for atmospheric convection

Authors:

Francis Hugo Lambert, Peter Challenor, Neil T Lewis, Douglas J McNeall, Nathan E Owen, Ian Boutle, Hannah Christensen, Richard Keane, Alison Stirling, Mark J Webb, Nathan J Mayne
More details from the publisher

High Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Authors:

Malcolm John Roberts, Kevin A Reed, Qing Bao, Joseph J Barsugli, Suzana J Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S Fučkar, Shabeh ul Hasson, Helene T Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A Ullrich, Pier Luigi Vidale, Michael F Wehner, Colin M Zarzycki, Bosong Zhang, Wei Zhang, Ming Zhao
More details from the publisher

Interpretable Deep Learning for Probabilistic MJO Prediction

Authors:

Antoine Delaunay, Hannah Christensen
More details from the publisher

Pagination

  • First page First
  • Previous page Prev
  • …
  • Page 7
  • Page 8
  • Page 9
  • Page 10
  • Page 11
  • Page 12
  • Page 13
  • Current page 14
  • Page 15
  • Next page Next
  • Last page Last

Footer Menu

  • Contact us
  • Giving to the Dept of Physics
  • Work with us
  • Media

User account menu

  • Log in

Follow us

FIND US

Clarendon Laboratory,

Parks Road,

Oxford,

OX1 3PU

CONTACT US

Tel: +44(0)1865272200

University of Oxfrod logo Department Of Physics text logo
IOP Juno Champion logo Athena Swan Silver Award logo

© University of Oxford - Department of Physics

Cookies | Privacy policy | Accessibility statement

Built by: Versantus

  • Home
  • Research
  • Study
  • Engage
  • Our people
  • News & Comment
  • Events
  • Our facilities & services
  • About us
  • Current students
  • Staff intranet