Pacific decadal oscillation hindcasts relevant to near-term climate prediction

Abstract

Decadal-scale climate variations over the Pacific Ocean and its surroundings are strongly related to the so-called Pacific decadal oscillation (PDO) which is coherent with wintertime climate over North America and Asian monsoon, and have important impacts on marine ecosystems and fisheries. In a near-term climate prediction covering the period up to 2030, we require knowledge of the future state of internal variations in the climate system such as the PDO as well as the global warming signal. We perform sets of ensemble hindcast and forecast experiments using a coupled atmosphere-ocean climate model to examine the predictability of internal variations on decadal timescales, in addition to the response to external forcing due to changes in concentrations of greenhouse gases and aerosols, volcanic activity, and solar cycle variations. Our results highlight that an initialization of the upper-ocean state using historical observations is effective for successful hindcasts of the PDO and has a great impact on future predictions. Ensemble hindcasts for the 20th century demonstrate a predictive skill in the upper-ocean temperature over almost a decade, particularly around the Kuroshio-Oyashio extension (KOE) and subtropical oceanic frontal regions where the PDO signals are observed strongest. A negative tendency of the predicted PDO phase in the coming decade will enhance the rising trend in surface air-temperature (SAT) over east Asia and over the KOE region, and suppress it along the west coasts of North and South America and over the equatorial Pacific. This suppression will contribute to a slowing down of the global-mean SAT rise.climate change | data assimilation | decadal prediction | decadal variability | global warming A near-term climate prediction covering the period up to 2030 is a major issue to be addressed in the next assessment report of the Intergovernmental Panel on Climate Change (1, 2). To make the political decisions required to solve the socioeconomic problems arising from climate change over the coming decades, we need to take into account the large-scale climate changes associated with internal climate variability as well as the global warming signals (i.e., the response to external forcing due to changes in concentrations of greenhouse gases and aerosols, volcanic activity, and solar cycle variations) (3-6). A globally averaged surface-air-temperature (SAT) forecast up to 2030 depends little on specific socioeconomic scenarios or models used in centennial climate projection experiments (7, 8). On decadal timescales, SAT changes due to internal climate variability are comparable to those associated with global warming in magnitude (9). The predictability of internal climate variations is central to validating our skills in predicting the near-term climate variations.Prediction of internal decadal variability in the climate system represents one of the newest and toughest challenges. It is only recently that near-term climate projection experiments have been carried out focusing on internal decada...

Evaluation of short‐term climate change prediction in multi‐model CMIP5 decadal hindcasts

“…The AMO and PDO are the dominant decadal oscillations over the North Atlantic Ocean [Schlesinger and Ramankutty 1994;Enfield et al, 2001] and North Pacific Ocean [Mantua et al, 1997], respectively, and are the most predictable components of internal climate variability [e.g., Keenlyside et al, 2008;Mochizuki et al, 2010]. The AMO index is defined as the area averaged annual mean sea surface temperature (SST) anomaly averaged over the North Atlantic from 80 W to 20 W and from 0 to 70 N for both the simulations and observation.…”

Climate model simulations of the observed early-2000s hiatus of global warming

“…What would have been required to predict the hiatus in advance is the application of recently developed decadal climate prediction methodology 17,18 to capture the time evolution of the interplay between externally forced response and internally generated climate variability. There are indications that the observed vertical global heat content distribution in the ocean for the hiatus 19 can be simulated in a single model 20 , as well as a negative IPO surface temperature pattern in the Pacific after the late 1990s IPO transition [21][22][23][24][25] . But could a multi-model ensemble initialized from the 1990s have predicted the transition to the negative phase of the IPO and the hiatus at the right time, involving the processes thought to produce the hiatus?…”

“…So to return to our prediction exercise in the 1990s, to illustrate the surface temperature pattern that would have been simulated for the transition to the negative phase of the IPO, we show an example for a prediction from the initial year 1996 for the 3-7 year average for years 1998-2002. Previous analyses of hindcasts showed geographical surface temperature patterns after the IPO transition occurred [21][22][23][24][25] , or analysed only globally averaged quantities across the transition 20,22 . Here the transition of the surface temperature pattern to the negative phase of the IPO is simulated with cooler than normal temperatures in the tropical Pacific (Fig.…”

How do Himalayan areas respond to global warming?

“…With equal emphasis and extension, a confounding change in the correlation patterns was also detected between Pacific Decadal Oscillation (PDO, detected as warm or cool surface waters in the Pacific Ocean) and temperature ( Figure 7A, B), and for which a high predictability was found in relation to global climate change on decadal time scales (Mochizuki et al, 2010) as above. This was, in turn, consistent with the AsianPacific Oscillation (a zonal teleconnection pattern over the extratropical Asian-Pacific region) -which is associated with the out-of-phase relationship in atmospheric heating -and that shows a decadal variation according to the high index polarity registered before 1975 and to the low index polarity registered afterwards (Zhao et al, 2007).…”