Simulation and prediction of North Pacific sea surface temperature

Date

2011-06-24

Authors

Lienert, Fabian

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Abstract

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.

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Keywords

climate variability, North Pacific, climate prediction

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