The first part of this thesis is an assessment of the ability of global climate models
to reproduce observed features of the leading Empirical Orthogonal Function (EOF)
mode of North Pacific sea surface temperature (SST) anomalies known as the Pacific Decadal Oscillation (PDO). The simulations from 13 global climate models I am
analyzing were performed under phase 3 of the coupled model intercomparison project
(CMIP3). In particular, I am investigating whether these climate models capture
tropical influences on the PDO, and the influences of the PDO on North American
surface temperature and precipitation.
My results are that 1) the models as group produce a realistic pattern of the
PDO. The simulated variance of the PDO index is overestimated by roughly 30%. 2)
The tropical influence on North Pacific SSTs is biased systematically in these models.
The simulated response to El Niño-Southern Oscillation (ENSO) forcing is delayed
compared to the observed response. This tendency is consistent with model biases
toward deeper oceanic mixed layers in winter and spring and weaker air-sea feedbacks in the winter half-year. Model biases in mixed layer depths and air-sea feedbacks
are also associated with a model mean ENSO-related signal in the North Pacific
whose amplitude is overestimated by roughly 30%. Finally, model power spectra of
the PDO signal and its ENSO-forced component are “redder” than observed due to
errors originating in the tropics and extratropics. 3) The models are quite successful
at capturing the influence of both the tropical Pacific related and the extratropical
part of the PDO on North American surface temperature. 4) The models capture
some of the influence of the PDO on North American precipitation mainly due to its
tropical Pacific related part.
In the second part of this thesis, I investigate the ability of one such coupled ocean-
atmosphere climate model, carefully initialized with observations, to dynamically
predict the future evolution of the PDO on seasonal to decadal time scales. I am using
forecasts produced by the Canadian climate data assimilation and prediction system
employing the Canadian climate model CanCM3 for seasonal (CHFP2) and CanCM4
for decadal (DHFP1) predictions. The skill of this system in predicting the future
evolution of the PDO index is then inferred from a set of historical “forecasts” called
hindcasts. In this manner, hindcasts are issued over the past 30 years (seasonal),
or over the past 50 years (decadal) when they can be verified against the observed
historical evolution of the PDO index.
I find that 1) CHFP2 is successful at predicting the PDO at the seasonal time
scale measured by mean-square skill score and correlation skill. Weather “noise”
unpredictable at the seasonal time scale generated by substantial North Pacific storm
track activity that coincides with a shallow oceanic mixed layer in May and June
appear to pose a prediction barrier for the PDO. PDO skill therefore depends on
the start season of the forecast. PDO skill also varies as a function of the target
month. Variations in North Pacific storminess appear to impact PDO skill by means
of a lagged response of the ocean mixed layer to weather “noise”. In CHFP2, times
of increasing North Pacific storm track activity are followed by times of reduced
PDO skill, while the North Pacific midwinter suppression of storm track activity
with decreasing storminess is followed by a substantial recovery in PDO skill. 2)
This system is capable of forecasting the leading 14 EOF modes of North Pacific SST
departures, that explain roughly three quarters of the total SST variance. CHFP2
is less successful at predicting North Pacific SSTs, i.e., the combination of all the
EOF modes, at the seasonal time scale. 3) Besides the skill in Pacific SST, CHFP2
skillfully predicts indices that measure the atmospheric circulation regime over the
North Pacific and North America such as the Pacific/North American pattern (PNA)
(skillful for three out of four start seasons) and the North Pacific index (NPI) (skillful
for all four start seasons). 4) CHFP2 is successful at forecasting part of the influence
of Pacific SST on North American climate at the seasonal time scale. Measured
by 12-month average anomaly correlation skill, in this system the PDO is a better
predictor for North American precipitation (skillful for all four start seasons) than
temperature (skillful for one out of four start seasons). In CHFP2, ENSO is a better
predictor for North American temperature (skillful for all four start seasons) than the
PDO. Both ENSO and the PDO are, however, good predictors for North American
precipitation (skillful for all four start seasons).
Finally, DHFP1 is less successful at forecasting the PDO at the decadal time
scale. Ten-year forecasts of the PDO index exhibit significantly positive correlation
skill exclusively in the first year of the forecast. When the correlation skill of the
predicted index averaged over lead years is considered, the PDO skill in this system
stays significantly positive during the first three years of the decadal forecast. In
other words, this climate data assimilation and prediction system is expected to
skillfully predict the future three year averaged evolution of the PDO index, but not
the evolution of the index in each year individually. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/3387 |
| Date | 24 June 2011 |
| Creators | Lienert, Fabian |
| Contributors | Fyfe, John, Weaver, Andrew J. |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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