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91̽»¨
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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

Understanding the atmospheric kinetic energy spectrum

Copernicus Publications (2024)

Authors:

Salah Kouhen, Benjamin Storer, Hussein Aluie, David Marshall, Hannah Christensen

Improving and Assessing Organized Convection Parameterization in the Unified Model

Copernicus Publications (2024)

Authors:

Zhixiao Zhang, Hannah Christensen, Mark Muetzelfeldt, Tim Woollings, Bob Plant, Alison Stirling, Michael Whitall, Mitchell Moncrieff, Chih-Chieh Chen

Multifractal Analysis for Evaluating the Representation of Clouds in Global Kilometre-Scale Models

(2024)

Authors:

Lilli Johanna Freischem, Philipp Weiss, Hannah Christensen, Philip Stier

Using probabilistic machine learning to better model temporal patterns in parameterizations: a case study with the Lorenz 96 model

Geoscientific Model Development Copernicus Publications 16:15 (2023) 4501-4519

Authors:

Raghul Parthipan, Hannah M Christensen, J Scott Hosking, Damon J Wischik

On the relationship between reliability diagrams and the ‘signal-to-noise paradox’

Geophysical Research Letters American Geophysical Union 50:14 (2023) e2023GL103710

Authors:

Kristian Strommen, Molly MacRae, Hannah Christensen

Abstract:

The ‘signal-to-noise paradox’ for seasonal forecasts of the winter NAO is often described as an ‘underconfident’ forecast and measured using the ratio-of-predictable components metric (RPC). However, comparison of RPC with other measures of forecast confidence, such as spread-error ratios, can give conflicting impressions, challenging this informal description. We show, using a linear statistical model, that the ‘paradox’ is equivalent to a situation where the reliability diagram of any percentile forecast has a slope exceeding 1. The relationship with spread-error ratios is shown to be far less direct. We furthermore compute reliability diagrams of winter NAO forecasts using seasonal hindcasts from the European Centre for Medium-range Weather Forecasts and the UK Meteoro logical Office. While these broadly exhibit slopes exceeding 1, there is evidence of asymmetry between upper and lower terciles, indicating a potential violation of linearity/Gaussianity. The limitations and benefits of reliability diagrams as a diagnostic tool are discussed.

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