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

Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 379:2194 (2021) ARTN 20200083

Authors:

Matthew Chantry, Hannah Christensen, Peter Dueben, Tim Palmer

Abstract:

In September 2019, a workshop was held to highlight the growing area of applying machine learning techniques to improve weather and climate prediction. In this introductory piece, we outline the motivations, opportunities and challenges ahead in this exciting avenue of research. This article is part of the theme issue 'Machine learning for weather and climate modelling'.
More details from the publisher
Details from ORA
More details
More details

Scale‐aware space‐time stochastic parameterization of subgrid‐scale velocity enhancement of sea surface fluxes

Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU) (2021)

Authors:

Julie Bessac, Hannah M Christensen, Kota Endo, Adam H Monahan, Nils Weitzel
More details from the publisher
Details from ORA
More details

OpenEnsemble 1.0: a boon for the research community

Geoscientific Model Development Discussions Copernicus Publications (2020)
More details from the publisher
Details from ORA

Continuous structural parameterization: a proposed method for representing different model parameterizations within one structure demonstrated for atmospheric convection

Journal of Advances in Modeling Earth Systems American Geophysical Union 12:8 (2020) e2020MS002085

Authors:

Fh Lambert, Pg Challenor, Neil Lewis, Dj McNeall, N Owen, Ia Boutle, Hm Christensen, Rj Keane, Nj Mayne, A Stirling, Mj Webb

Abstract:

Continuous structural parameterization (CSP) is a proposed method for approximating different numerical model parameterizations of the same process as functions of the same grid‐scale variables. This allows systematic comparison of parameterizations with each other and observations or resolved simulations of the same process. Using the example of two convection schemes running in the Met Office Unified Model (UM), we show that a CSP is able to capture concisely the broad behavior of the two schemes, and differences between the parameterizations and resolved convection simulated by a high resolution simulation. When the original convection schemes are replaced with their CSP emulators within the UM, basic features of the original model climate and some features of climate change are reproduced, demonstrating that CSP can capture much of the important behavior of the schemes. Our results open the possibility that future work will estimate uncertainty in model projections of climate change from estimates of uncertainty in simulation of the relevant physical processes.
More details from the publisher
Details from ORA
More details

The value of initialisation on decadal timescales: state dependent predictability in the CESM Decadal Prediction Large Ensemble

Journal of Climate American Meteorological Society 33:17 (2020) 7353-7370

Authors:

Hannah Christensen, Judith Berner, Stephen Yeager

Abstract:

Information in decadal climate prediction arises from a well initialised ocean state and from the predicted response to an external forcing. The length of time over which the initial conditions benefit the decadal forecast depends on the start date of the forecast. We characterise this state-dependent predictability for decadal forecasts of upper ocean heat content in the Community Earth System Model. We find regionally dependent initial condition predictability, with extended predictability generally observed in the extra-tropics. We also detect state-dependent predictability, with the year of loss of information from the initialisation varying between start dates. The decadal forecasts in the North Atlantic show substantial information from the initial conditions beyond the ten-year forecast window, and a high degree of state-dependent predictability. We find some evidence for state dependent predictability in the ensemble spread in this region, similar to that seen in weather and subseasonal-to-seasonal forecasts. For some start dates, an increase of information with lead time is observed, for which the initialised forecasts predict a growing phase of the Atlantic Multidecadal Oscillation. Finally we consider the information in the forecast from the initial conditions relative to the forced response, and quantify the crossover timescale after which the forcing provides more information. We demonstrate that the climate change signal projects onto different patterns than the signal from the initial conditions. This means that even after the crossover timescale has been reached in a basin-averaged sense, the benefits of initialisation can be felt locally on longer timescales.
More details from the publisher
Details from ORA
More details

Pagination

  • First page First
  • Previous page Prev
  • …
  • Page 3
  • Page 4
  • Page 5
  • Page 6
  • Current page 7
  • Page 8
  • Page 9
  • Page 10
  • Page 11
  • …
  • 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