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Tim
Barnett and David Pierce, Scripps Institution of Oceanography
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Initializing
a coupled model to observed initial conditions is a difficult challenge,
and critical to climate predictions. Sea ice is one of the most
sensitive model components to an incorrect initial state. This figure
shows a successful initialization of the PCM to observed conditions
of 1995. Panel A: Model sea ice cover in January 1995 � the initial
state. Panel B: Model sea ice cover in January after running the
model forward for 30 years with no constraints. The good agreement
with the initial conditions is just one indication that the model
drift away from the imposed initial conditions based on observations
is small.
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Research
Objectives
To
predict natural climate variability in the North Pacific on the decadal
time scale. This is a key region, as it is known that the state of the
North Pacific sea surface temperature (SST) field is well correlated
with wintertime precipitation and temperatures over the U.S.
Computational Approach
Our primary tool is the Parallel Climate Model (PCM), a fully coupled
general circulation model. The individual ocean and atmosphere components
from this model are used separately as well. The resolution of the atmospheric
component of the models used in this study is T42, while that of the ocean
components varies from about 0.5� to 1�, depending on the latitude and
longitude.
Accomplishments
In previous work we had identified a preferred
20-year timescale of climate variability in the North Pacific in a coupled
ocean-atmosphere general circulation model. Our objective in FY 2000
was to show whether or not this preferred timescale arises out of coupled
ocean-atmosphere interactions (and therefore might be predictable by
a coupled model) or is a manifestation of various so-called �stochastic
resonance� mechanisms, which can give enhanced spectral variability
at a preferred timescale even in the absence of coupled ocean-atmosphere
interactions.
We ran the ocean model component
from the fully coupled model in standalone mode, forced first with the
saved surface flux fields (heat, fresh water, and momentum) from the
fully coupled model. This control run showed that if the ocean model
is driven by these saved flux fields, it reproduces the enhanced spectral
peak at the same timescale (20 years/cycle) as found in the fully coupled
model. Next, we forced the ocean model with the saved flux fields, but
scrambled randomly in time by month. We found that the spectral peak
is still present in the scrambled forcing run, indicating that most,
if not all, of the enhanced energy at a preferred timescale of 20 years/cycle
comes from stochastic resonance mechanisms, and therefore is inherently
unpredictable. Further analysis of this data in under way.
Significance
Determining the levels of natural climate variability, and being
able to understand the physical processes responsible for this natural
noise, are a requirement of any attempt to make an early detection of
mankind�s impact on climate.
Publications
T. P. Barnett, D. W. Pierce, M. Latif, D. Dommenget, and R. Saravanan,
�Interdecadal interactions between the tropics and midlatitudes in the
Pacific basin,� Geophys. Rev. Lett. 26, 615 (1999).
T. P. Barnett, D. W. Pierce, R. Saravanan, N. Schneider,
D. Dommenget, and M. Latif, �Origins of the midlatitude Pacific decadal
variability,� Geophys. Rev. Lett. 26, 1453 (1999).
D. W. Pierce, T. P. Barnett, and M. Latif, �Connections
between the Pacific Ocean tropics and midlatitudes on decadal time scales,�
J. Climate 13, 1173 (2000).
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