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91探花
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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
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  • Publications

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

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 Fu膷kar, 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

Interpretable Deep Learning for Probabilistic MJO Prediction

Authors:

Antoine Delaunay, Hannah Christensen

Interpretable Deep Learning for Probabilistic MJO Prediction

Authors:

Antoine Delaunay, Hannah Christensen

Introducing the Probabilistic Earth-System Model: Examining The Impact of Stochasticity in EC-Earth v3.2

Geoscientific Model Development European Geosciences Union

Authors:

Kristian Strommen, Hannah M Christensen, David MacLeod, Stephan Juricke, Tim N Palmer

Abstract:

<p><strong>Abstract.</strong> We introduce and study the impact of three stochastic schemes in the EC-Earth climate model, two atmospheric schemes and one stochastic land scheme. These form the basis for a probabilistic earth-system model in atmosphere-only mode. Stochastic parametrisations have become standard in several operational weather-forecasting models, in particular due to their beneficial impact on model spread. In recent years, stochastic schemes in the atmospheric component of a model have been shown to improve aspects important for the models long-term climate, such as ENSO, North Atlantic weather regimes and the Indian monsoon. Stochasticity in the land-component has been shown to improve variability of soil processes and improve the representation of heatwaves over Europe. However, the raw impact of such schemes on the model mean is less well studied, It is shown that the inclusion all three schemes notably change the model mean state. While many of the impacts are beneficial, some are too large in amplitude, leading to large changes in the model's energy budget. This implies that in order to keep the benefits of stochastic physics without shifting the mean state too far from observations, a full re-tuning of the model will typically be required.</p>

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