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A well-known exception to rising sea surface temperatures (SST) across the globe is the subpolar North Atlantic, where SST has been declining at a rate of 0.39 ( $$\pm$$ 0.23) K century−1 during the 1900–2017 period. This cold blob has been hypothesized to result from a slowdown of the Atlantic Meridional Overturning Circulation (AMOC). Here, observation-based evidence is used to suggest that local atmospheric forcing can also contribute to the century-long cooling trend. Specifically, a 100-year SST trend simulated by an idealized ocean model forced by historical atmospheric forcing over the cold blob region matches 92% ( $$\pm$$ 77%) of the observed cooling trend. The data-driven simulations suggest that 54% ( $$\pm$$ 77%) of the observed cooling trend is the direct result of increased heat loss from the ocean induced by the overlying atmosphere, while the remaining 38% is due to strengthened local convection. An analysis of surface wind eddy kinetic energy suggests that the atmosphere-induced cooling may be linked to a northward migration of the jet stream, which exposes the subpolar North Atlantic to intensified storminess.

Based on our previous study (Yu et al., Clim Dyn 49:1139–1156, 2017), this paper further investigates the interdecadal change in the relationship between the Kuroshio Extension (KE; 27°–37°N, 140°–158°E) and the East Asian summer monsoon (EASM) in the late 1980s. The summer KE sea surface temperature anomalies (SSTAs) show a significant positive relationship with the EASM over the period 1968–1987 (P1), but a significant negative connection with the EASM between 1991 and 2010 (P2). This interdecadal change in the KE–EASM relationship can be interpreted by considering the difference in the relationships of summer KE SSTAs with the East Asian subtropical westerly jet (EASWJ) and western North Pacific subtropical high (WNPSH) during the two periods. During P1, summertime KE SST warming is significantly related to the strengthened EASWJ and WNPSH, but it has close relationships with the weakened and northward-moving EASWJ and WNPSH during P2. These anomalous EASWJ and WNPSH associated with the summertime KE SST warming in P1 (P2) then favors increased (reduced) rainfall over the Yangtze River Valley that corresponds to a strong (weak) EASM, thereby leading to the significant positive (negative) KE–EASM relationship during this period. This change in the relationships of summer KE SSTAs with the EASWJ and WNPSH may be attributed to the increased KE SST variability associated with an enhanced Pacific Decadal Oscillation (PDO) in summer during P2, which is most probably induced by the stronger North Pacific Oscillation (NPO)-like atmospheric forcing, especially its southern pole (SP), in the preceding spring during this period. The spring NPO-like SP forces the KE SSTAs and PDO more directly during the following summer and can thus have been a better precursor for the following EASM than the full NPO-like dipole after the late 1980s.

The Community Land Model version 3.5 is driven by an observation-based meteorological dataset to simulate soil moisture over China for the period 1951–2008. A method for identifying the patterns of interannual variability that arise from slow (potentially predictable) and intraseasonal (unpredictable) variability is also applied; this allows identification of the sources of the predictability of seasonal soil moisture in China, during March–April–May (MAM), June–July–August (JJA), September–October–November (SON) and December–January–February (DJF). The potential predictability (slow-to-total) of the soil moisture above 1 m is high, with lowest value of 0.76 in JJA and highest value of 0.94 in DJF. The spatial distribution of the potential predictability comprises a northwest–southeast gradient, with a minimum center over East China and a maximum center over the northwest. The most important source of predictability is from the soil moisture persistence, which generally accounts for more than 50 % of the variability in soil moisture. The SSTs in the Indian Ocean, the North Atlantic and the eastern tropical Pacific Oceans are also identified as important sources of variability in the soil moisture, during MAM, JJA and SON/DJF, respectively. In addition, prolonged linear trends in each season are an important source. Using the slow principal component time series as predictands, a statistical scheme for the seasonal forecasting of soil moisture across China is developed. The prediction skills, in terms of the percentage of explained variance for the verification period (1992–2008), are 59, 51, 62 and 77 % during MAM–DJF, respectively. This is considerably higher than a normal grid prediction scheme.

The mean and variability of the Atlantic meridional overturning circulation (AMOC), as represented in six ocean reanalysis products, are analyzed over the period 1960–2007. Particular focus is on multi-decadal trends and interannual variability at 26.5°N and 45°N. For four of the six reanalysis products, corresponding reference simulations obtained from the same models and forcing datasets but without the imposition of subsurface data constraints are included for comparison. An emphasis is placed on identifying general characteristics of the reanalysis representation of AMOC relative to their reference simulations without subsurface data constraints. The AMOC as simulated in these two sets are presented in the context of results from the Coordinated Ocean-ice Reference Experiments phase II (CORE-II) effort, wherein a common interannually varying atmospheric forcing data set was used to force a large and diverse set of global ocean-ice models. Relative to the reference simulations and CORE-II forced model simulations it is shown that (1) the reanalysis products tend to have greater AMOC mean strength and enhanced variance and (2) the reanalysis products are less consistent in their year-to-year AMOC changes. We also find that relative to the reference simulations (but not the CORE-II forced model simulations) the reanalysis products tend to have enhanced multi-decadal trends (from 1975–1995 to 1995–2007) in the mid to high latitudes of the northern hemisphere.

Interannual-to-decadal variability and trends of sea level in the South China Sea (SCS) are studied using altimetric data during 1993–2012 and reconstructed sea level data from 1950–2009. The interannual variability shows a strong seasonality. Surface wind anomalies associated with El Nino-Southern Oscillation explain the sea-level anomaly pattern in the interior SCS, while Rossby waves radiated from the eastern boundary dominate the sea-level variability in the eastern SCS. Decadal variability of sea level in the SCS follows that in the western tropical Pacific, with large variance found west of Luzon Island. Local atmospheric forcing makes a negative contribution to decadal variability in the central SCS, and Rossby waves radiated from the eastern boundary appear to be important. During 1993–2012, decadal sea level averaged in the SCS is significantly correlated with the Pacific Decadal Oscillation (PDO) (r = −0.96). The decadal variability associated with the PDO accounts for most part of sea-level trends in the SCS in the last two decades.

The mechanisms of coupled model bias in seasonal ENSO phase locking are investigated using versions 1.0 and 1.3 of the CSIRO–BOM ACCESS coupled model (hereafter, ACCESS1.0 and ACCESS1.3, respectively). The two ACCESS coupled models are mostly similar in construction except for some differences, the most notable of which are in the cloud and land surface schemes used in the models. ACCESS1.0 simulates a realistic seasonal phase locking, with the ENSO variability peaking in December as in observations. On the other hand, the simulated ENSO variability in ACCESS1.3 peaks in March, a bias shown to be shared by many other CMIP5 models. To explore the mechanisms of this model bias, we contrast the atmosphere–ocean feedbacks associated with ENSO in both ACCESS model simulations and also compare the key feedbacks with those in other CMIP5 models. We find evidence that the ENSO phase locking bias in ACCESS1.3 is primarily caused by incorrect simulations of the shortwave feedback and the thermocline feedback in this model. The bias in the shortwave feedback is brought about by unrealistic SST–cloud interactions leading to a positive cloud feedback bias that is largest around March, in contrast to the strongest negative cloud feedback found in ACCESS1.0 simulations and observations at that time. The positive cloud feedback bias in ACCESS1.3 is the result of a dominant role played by the low-level clouds in its modeled SST–cloud interactions in the tropical eastern Pacific. Two factors appear to contribute to the dominance of low-level clouds in ACCESS1.3: the occurrence of a stronger mean descending motion bias and, to a lesser extent, a larger mean SST cold bias during March–April in ACCESS1.3 than in ACCESS1.0. A similar association is found between the positive cloud feedback bias and the biases in spring-time mean descending motion and SST for a group of CMIP5 models that show a seasonal phase locking bias similar to ACCESS1.3. Significant differences are also found between the thermocline feedbacks simulated by ACCESS1.0 and ACCESS1.3 that appear to reinforce the seasonal ENSO phase locking bias in the latter model. We discuss a mechanism by which the thermocline feedback differences could arise from atmospheric forcing differences in the two models.

Previous studies suggested that the wintertime SST in the North Pacific that are generated by the concurrent North Pacific Oscillation (NPO) are able to force El Nino during subsequent winter via the so-called ‘seasonal footprinting mechanism’ (SFM). We examine how the NPO effectively generates the El Nino via the SFM in the observations and models. The occurrence ratio for El Nino under conditions of NPO forcing during the previous winters is about 41 % for the period of 61 years (1949–2009), indicating that the atmospheric forcing from the mid-latitudes through the SFM does not always trigger an El Nino. We observed certain favorable conditions under which the SFM may effectively induce El Nino. We directly compared these observations with two cases: when the wintertime NPO leads to El Nino during the following winter through the SFM, and when the wintertime NPO is not followed by El Nino. Our analysis demonstrates that the spatial structures of the NPO, associated wind speed and net heat flux in the northeast Pacific, differ between the two cases. Such differences determine the existence of a footprint SST in the northeastern Pacific during the late spring and summer, which plays a key role in initiating the El Nino via the projection of westerly wind stress anomalies onto the equatorial Pacific during the same seasons. By conducting linear baroclinic model experiments, it is found that the positions of La Nina SST forcing during the previous winter are able to modify the spatial structures of the NPO, which produces favorable conditions for the El Nino during subsequent winter via the SFM.

International audience; Internal variability of the Atlantic subpolar gyre is investigated in a 600 years control simulation of a comprehensive coupled climate model. The subpolar gyre shows irregular oscillations of decadal time scale with most spectral power between 15 and 20 years. Positive and negative feedback mechanisms act successively on the circulation leading to an internal oscillation. This involves periodically enhanced deep convection in the subpolar gyre center and intermittently enhanced air-sea thermal coupling. As a result, anomalies of the large-scale atmospheric circulation can be transferred to the ocean on the ocean's intrinsic time scale, exciting the oscillator stochastically. A detailed understanding of oscillatory mechanisms of the ocean and their sensitivity to atmospheric forcing holds considerable potential for decadal predictions as well as for the interpretation of proxy data records.