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Title: The role of atmospheric feedbacks during ENSO
Author: Lloyd, James
ISNI:       0000 0004 2717 6639
Awarding Body: University of Reading
Current Institution: University of Reading
Date of Award: 2011
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Present-day general circulation models (GeMs) exhibit a large diversity in the strength, time scale and spatial pattern of the simulated El Nino-Southern Oscillation (ENSO). Many recent studies attribute these ENSO biases to the atmosphere component of GeMs, motivating a better understanding of the role of the atmosphere during ENSO. Theory separates the ENSO atmospheric processes into two linear feedbacks: 1) the Bjerknes positive feedback (u), and 2) the thermodynamical damping (a), respectively measuring the remote zonal wind stress and local heat flux response to eastern equatorial Pacific sea surface temperature (SST) anomalies. This thesis presents an in-depth analysis of u and a in 12 state-of-the-art GeMs, using coupled and atmosphere-only simulations. In the coupled simulations, both u and a are underestimated with respect to the re- analysis values, and a relationship is found between a and the modelled ENSO amplitude. Splitting up a into its four components reveals that the latent heat and shortwave flux feedbacks, aLH and asw, dominate the net feedback. All models successfully simulate a thermodynamical LH flux damping mechanism (driven by specific humidity processes), but exhibit large errors in asw, the main source of the overall a underestimation. In most models, biases in aSW are characterised by an erroneous positive feedback in the eastern equatorial Pacific region. A 'feedback decomposition method', developed to elucidate the aSw biases, shows that cloud-related errors over the eastern equatorial Pacific account for the asw biases in the atmosphere-only simulations, but that an underestimated dynamical response to SST anomalies is also important in the coupled simulations. A large nonlinearity is found in the observed and modelled SW flux feedback, showing that the linear heat flux parameterisation used in simple ENSO models is masking important processes. The process-based methodology presented in this thesis will help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GeMs.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available