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Variability and climate change signals in the Southern Ocean in the CSIRO and Antarctic CRC coupled ocean-atmosphere model.

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Catchpole, Ann-Maree (2007) Variability and climate change signals in the Southern Ocean in the CSIRO and Antarctic CRC coupled ocean-atmosphere model. Research Master thesis, University of Tasmania.

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Abstract

To investigate the variability and potential climate change impacts in the
Southern Ocean I use output from the c10, c15 and c16 model runs of the
CSIRO and Antarctic CRC coupled ocean-atmosphere model. 300 years of
the output is reported here, after a spin up of approximately 1000 years.
Modifications over the earlier versions of this model (c10 and c15), including
improved topography in waters south of Australia make the c16 model run
more suitable for examining natural variability in the southern ocean. We
use potential temperature, salinity and velocity (21 depths, 66 longitudes
and 29 latitudes in the Southern Hemisphere Ocean) and surface heat flux
(66 longitudes and 29 latitudes in the Southern Hemisphere).
Hovmoeller diagrams of potential temperature anomalies along a streamline
show circumnavigating propagation. At 400m, the strongest anomaly
timescales are 4-5 years (interannual anomalies) and take approximately 20
years to travel around the globe. The anomaly strength is not uniform along
this streamline and the strongest anomalies occur in the longitude band 100
to 200°E. Below 1000m, decadal variability is the dominant signal and persists
to at least 2000m. Scatterplots show a clear relationship between ACC
current speed and phase speed throughout the water column. This relationship
is strongest at intermediate depths (500 to 1500m) where anomalies are
most strongly advected and least subject to other influences such as convection,
mixing and mid-ocean ridges.
Using HEOF analysis revealed two dominant modes of variability in the
Southern Ocean. First, a mode characterised by zonal wavenumber 3, interannual
anomaly in temperature and salinity on shallow to intermediate
depth and density surfaces. Interannual variability of wavenumber 2 or 3
has been described in studies using observations or models of the Southern
Ocean. Also, significant correlation between temperature and pressure
anomalies occurred on density surfaces. The pressure pattern is 180˚ out of
phase with the temperature changes on density surfaces. This is similar to a
mechanism proposed by (White et al., 1998) for the ACW. The second mode
is characterised by zonal wavenumber 2, decadal variation at all intermediate
to deep depths and density surfaces. Overall, the decadal signal is the dominant
feature of the Southern Ocean, with more total energy in this mode
throughout most of the water column.
Variability in several atmospheric properties including wind stress, heat and
salinity fluxes is examined. The heat flux and meridional wind component
showed dominant modes of interannual variability with zonal wavenumber 3.
These two properties have been shown to play a significant role in determining
SSTs in the Southern Ocean. The results indicates that heat flux and
meridional wind are important for creating zonal wavenumber 3 interannual
variability in resultant SSTs. The second mode, consists of a decadal signal
with dominant zonal wavenumber 2. This suggests that slower timescales
may occur in the ocean due to natural filtering of anomalies such that interannual
signals are absorbed and only the longer term decadal signals remain.
The change in dominance from a signal with spatial structure zonal wavenumber 3
to zonal wavenumber 2 is more complex. Exploring the possible reasons
for a zonal wavenumber 2 structure required investigation of convection regions
in the Southern Ocean. An estimate of mixed layer depth revealed two
dominant regions of wintertime convection. The first begins in the southeast
Indian Sector of the Southern Ocean and continues to below Australia.
The second region is the Pacific Ocean to the east of Drake Passage. These
two regions are important for generation of SAMW and AAIW respectively.
In essence, these two regions of convection act like highways in a myriad of
surburban streets whereby anomalies at the surface can quickly access the
deeper depths (compared with anomalies at the surface in adjacent regions of
low convection). A simple model is used to test the assumption (Chapter 4).
Forcing this model with interannual, zonal wavenumber 3 heat flux anomalies
and applying a convection system of two convective regions, we obtain
a resultant subsurface anomaly with zonal wavenumber 2. The hypothesis
that the distribution of convection regions influences the zonal wavenumber
structure of anomaly was shown to be reasonable.
For the third aim, I compared warming and deepening signals seen in the
transient model run with a control run. There is a consistent pattern of
cooling on isopycnals in shallow/Mode waters and warming on isopycnals
in AAIW in the transient run. This coincides with a general deepening of
density surfaces. The fingerprint experiment reveals statistical significance in
these results indicating that the simulation of CO₂ changes indeed produces
changes to Southern Hemisphere water masses with the described spatial
pattern. Qualitative comparison with studies of observed changes show a
similar pattern of change.

Item Type: Thesis (Research Master)
Keywords: Climatic changes, Ocean-atmosphere interaction, Global warming
Copyright Holders: The Author
Copyright Information:

Copyright 2007 the Author - The University is continuing to endeavour to trace the copyright
owner(s) and in the meantime this item has been reproduced here in good faith. We
would be pleased to hear from the copyright owner(s).

Additional Information:

Available for library use only and copying in accordance with the Copyright Act 1968, as amended. Thesis (MSc)--University of Tasmania, 2007. Includes bibliographical references. 1. Introduction -- 2. Dataset description and mean fields -- 3. Variability and spatial propagation of anomalies in the Antarctic circumpolar current -- 4. Characterising natural variability of water masses in the modelled ocean -- 5. Atmosphere and ocean interaction and ocean variability -- 6. Detection of climate change -- 7. Conclusions

Date Deposited: 25 Nov 2014 00:56
Last Modified: 11 Mar 2016 05:53
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