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...

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A 'regime shift' is characterized by an abrupt transition from one quasi-steady climatic state to another, and its transition period is much shorter than the lengths of the individual epochs of each climatic state. In the present study, we investigate when regime shifts occurred and what was the difference in climatic states before and after the shifts, using the wintertime sea surface temperature (SST) field in the Northern Hemisphere. The relationship between changes in the SST field, and those in the atmospheric circulation, is also investigated.In order to detect organized patterns of the SST variations, we apply an empirical orthogonal function (EOF) analysis. As the results, the first mode is identical to El Niñ o/Southern Oscillation (ENSO) and so-called Pacific Decadal Oscillation (PDO), and corresponds to the Pacific/North American (PNA) pattern. The second mode, which relates to the Arctic Oscillation (AO), has a zonally elongated signal in both the North Atlantic, and North Pacific. EOF analyses to each oceanic basin are made separately, and the robustness of these modes is confirmed.In the present study, we define the regime shifts as the 'significant' and 'systematic' changes between the two quasi-steady states, continuing more than 5 years. Then, in order to identify the years when regime shifts occurred in the SST field, we carefully inspect the time series of original gridded SST data and those of the EOF modes. As a result, six regime shifts are detected in the study period from the 1910s to the 1990s: 1925/26, 1945/46, 1957/58, 1970/71, 1976/77 and 1988/89. It is ascertained that the shifts at almost all grids are completed within one year. All regime shifts having similar SST and atmospheric circulation pattern, including the changes in an intensity of the Aleutian Low (AL), and the corresponding SST changes in the central North Pacific. All regime shifts can be well described by the combination of the first and the second EOF modes. The duration between each regime shift is about 10 years, which are identical to the PDO. The simultaneous shifts in the first, and the second EOF modes, imply that the change in the AL activity associated with the PNA pattern, might have some connection with that of the AO.

Abstract. This study uses a neural network technique to produce maps of the partial pressure of oceanic carbon dioxide (pCO2sea) in the North Pacific on a 0.25° latitude × 0.25° longitude grid from 2002 to 2008. The pCO2sea distribution was computed using a self-organizing map (SOM) originally utilized to map the pCO2sea in the North Atlantic. Four proxy parameters – sea surface temperature (SST), mixed layer depth, chlorophyll a concentration, and sea surface salinity (SSS) – are used during the training phase to enable the network to resolve the nonlinear relationships between the pCO2sea distribution and biogeochemistry of the basin. The observed pCO2sea data were obtained from an extensive dataset generated by the volunteer observation ship program operated by the National Institute for Environmental Studies (NIES). The reconstructed pCO2sea values agreed well with the pCO2sea measurements, with the root-mean-square error ranging from 17.6 μatm (for the NIES dataset used in the SOM) to 20.2 μatm (for independent dataset). We confirmed that the pCO2sea estimates could be improved by including SSS as one of the training parameters and by taking into account secular increases of pCO2sea that have tracked increases in atmospheric CO2. Estimated pCO2sea values accurately reproduced pCO2sea data at several time series locations in the North Pacific. The distributions of pCO2sea revealed by 7 yr averaged monthly pCO2sea maps were similar to Lamont-Doherty Earth Observatory pCO2sea climatology, allowing, however, for a more detailed analysis of biogeochemical conditions. The distributions of pCO2sea anomalies over the North Pacific during the winter clearly showed regional contrasts between El Niño and La Niña years related to changes of SST and vertical mixing.

Abstract. We estimated monthly air–sea CO2 fluxes in the Arctic Ocean and its adjacent seas north of 60∘ N from 1997 to 2014. This was done by mapping partial pressure of CO2 in the surface water (pCO2w) using a self-organizing map (SOM) technique incorporating chlorophyll a concentration (Chl a), sea surface temperature, sea surface salinity, sea ice concentration, atmospheric CO2 mixing ratio, and geographical position. We applied new algorithms for extracting Chl a from satellite remote sensing reflectance with close examination of uncertainty of the obtained Chl a values. The overall relationship between pCO2w and Chl a was negative, whereas the relationship varied among seasons and regions. The addition of Chl a as a parameter in the SOM process enabled us to improve the estimate of pCO2w, particularly via better representation of its decline in spring, which resulted from biologically mediated pCO2w reduction. As a result of the inclusion of Chl a, the uncertainty in the CO2 flux estimate was reduced, with a net annual Arctic Ocean CO2 uptake of 180 ± 130 Tg C yr−1. Seasonal to interannual variation in the CO2 influx was also calculated.