The positive Indian Ocean Dipole (IOD) is associated with negative sea surface temperature (SST) anomalies in the southeastern tropical Indian Ocean and positive SST anomalies in the western tropical Indian Ocean. Anomalies with opposite signs appear during the negative IOD. One of the important features of the Indian Ocean Dipole (IOD) is its asymmetry; negative sea surface temperature (SST) anomalies in the eastern pole during the positive IOD are stronger than positive SST anomalies during the negative IOD. Based on a completely closed mixed layer heat budget analysis using the Regional Ocean Modeling System, it is shown that the vertical diffusion term plays an important role in generating this asymmetry in addition to the contributions from the nonlinear advection and the thermocline feedback proposed by some previous studies. A further decomposition of the vertical diffusion term reveals that the anomalous vertical temperature gradient due mainly to subsurface temperature anomalies strengthens the SST asymmetry, while the anomalous vertical diffusion coefficient weakens the asymmetry. Negative subsurface temperature anomalies during the positive IOD are larger than the positive anomalies during the negative IOD due to the asymmetry in the thermocline feedback. On the other hand, due to stronger cancellation between effects of anomalous vertical shear generated by southeasterly trade wind anomalies and anomalous stratification, the amplitude of positive vertical diffusion coefficient anomalies during the positive IOD is weaker than that of negative vertical diffusion coefficient anomalies during the negative IOD. Therefore, our results propose that the thermocline feedback contributes to the SST asymmetry not through the vertical advection as previously suggested, but via the turbulent vertical diffusion.

Many parts of East Asia, including Japan, experienced extremely warm conditions during the 2019–2020 winter. These were successfully predicted in October of 2019 by the 108‐member ensemble seasonal prediction system based on the SINTEX‐F climate model. By analyzing covariability of intermember anomalies defined as deviations from the ensemble mean, we have found that the active convection over the western pole of the Indian Ocean Dipole (IOD) caused these unusual conditions over East Asia by generating the meander of the subtropical jet.

Based on the observed and reanalysis data, this study investigates variations in frequency of summer extreme hot days (SEHD) in the Asian monsoon region (AMR) during 1979-2017. Results show that the leading EOF mode presents south-north opposite anomalies in the SEHD frequency and explains 15.3% of total variances. The mode is closely related to ENSO in the preceding winter with the lagged correlation coefficient up to 0.6, significant at the 99% confidence level. The lagged ENSO influences are executed by provoking the Indian Ocean basin mode (IOBM) that can persist from the ENSO mature winter to the subsequent summer when the ENSO itself demises in the tropical Pacific. The IOBM in the ENSO decaying summer induces an anomalous anticyclone with reduced convective activities in the western North Pacific, which on one hand generates westward propagating Rossby wave and causes positive, quasi-barotropic geopotential height anomalies extending from the Indian subcontinent to the western North Pacific. The corresponding descending motion reduces the cloud cover, raises the surface temperature and thus increases the frequency of SEHD in the southern part of AMR. On the other hand, the anomalous anticyclone can trigger the Pacific-Japan pattern along the East Asian coast with cyclonic circulation anomalies around northeastern Asia and deepen the tough there. The consequent anomalous ascending motion enhances the local cloud cover, together with the cold air intrusion by the northwesterly behind the trough, decrease the surface temperature and reduce the frequency of SEHD in the mid latitude of AMR. As such, the ENSO introduces the south-north contrasted anomalies in the SEHD frequency in the AMR in its decaying summer.

Identification of El Niño warm events and their types has traditionally been deterministic, based mainly on whether a pre-defined index exceeded a critical value. However, uncertainties in both sea surface temperature (SST) measurements and their interpolation into a gridded analysis can impact identification of and confidence in El Niño variability, particularly earlier in the record. Although several different classification methods for El Niño exist, researchers lack an effective reference and evaluation system to identify advantages and disadvantages of a given index for a given application. Therefore, this study quantifies the impacts of both data- and method-related uncertainties on different El Niño classification methods, considering different types of uncertainty, different types of analysis, different teleconnection mechanisms and expressions of El Niño impact and different types of climate data. To aid in these objectives, El Niño classification methods are evaluated from five aspects: reliability, accuracy, precision, flexibility, and simplicity. The core analysis is based on probabilistic, uncertainty-aware classifications applied to a large ensemble of historical SST realizations. The results are then used to conduct a more general evaluation of how different types of uncertainty propagate through the different classification methods, and provide guidance on the strengths and weaknesses of these indices for different applications. 

Variability of sea surface temperature (SST) in mid-latitude Northwest Pacific Ocean was analyzed using Sparse Principal Component Analysis (Sparse PCA). Sparse PCA is a variant of Principal Component Analysis (PCA) or Empirical Orthogonal Function (EOF) analysis. In Sparse PCA, sparser principal component patterns are sought to reconstruct the data than in EOF.  While the patterns of SST variability in EOF are difficult to interpret, those in Sparse PCA were much simpler. With little assumption except sparseness, Sparse PCA identified key variations around the Kuroshio and Oyashio Extensions suggested in past studies.  The patterns found in Sparse PCA are simpler than in Rotated EOF, which is traditionally used to obtain more physically interpretable patterns than EOF.

The leading ocean-atmosphere coupled mode in the tropical Pacific is the El Niño-Southern Oscillation (ENSO), a zonal mode that has a profound impact on the global climate via atmospheric bridge. The second coupled mode is called the Pacific meridional modes (PMM). The main loadings of the PMM sea surface temperature anomalies locate in the subtropical northeastern (NPMM) and southeastern Pacific (SPMM), respectively. The NPMM and SPMM have been suggested to markedly affect ENSO variability, which subsequently influences the extratropical climate. In addition to this PMM-to-ENSO pathway, recent studies also pointed out that the NPMM and SPMM can directly feed back to the atmosphere through influencing the intertropical convergence zone and South Pacific convergence zone, respectively. These studies, however, only focused on the local atmospheric response over the subtropical Pacific; whether the NPMM and SPMM can affect the extratropical climate remotely remains unknown. To address this question, we conduct a mechanically decoupled experiment, in which the climatological wind stress is prescribed over the tropical Pacific. This configuration effectively removes the dynamically coupled ENSO variability and thus can be used for exploring the atmospheric response to the PMM variability without the influence of ENSO. Our result shows that in addition to the local atmospheric response, both NPMM and SPMM can also excite atmospheric teleconnections emanating from the subtropical Pacific to the Northern and Southern Hemisphere extratropics, respectively, and thereby affect the extratropical climate. We highlight this direct pathway that the PMM influences extratropical climate, which needs to be further investigated in future research.

The Northeast U.S. shelf (NES) is an oceanographically dynamic marine ecosystem and supports some of the most valuable demersal fisheries in the world. A reliable prediction of NES environmental variables, particularly ocean bottom temperature, could lead to a significant improvement in demersal fisheries management. However, the current generation of climate model-based seasonal-to-interannual predictions exhibit limited prediction skill in this continental shelf environment. Here we have developed a hierarchy of statistical seasonal predictions for NES bottom temperatures using an eddy-resolving ocean reanalysis dataset. A simple, damped local persistence prediction model produces significant skill for lead times up to ~6 months in the Mid-Atlantic Bight and up to ~11 months in the Gulf of Maine, although the prediction skill varies notably by season. Considering temperature from a nearby or upstream (i.e. more poleward) region as an additional predictor generally improves prediction skill, presumably as a result of advective processes. Large-scale atmospheric and oceanic indices, such as Gulf Stream path indices (GSIs) and the North Atlantic Oscillation index, are also tested as predictors for NES bottom temperatures. Only the GSI constructed from temperature observed at 200 m depth significantly improves the prediction skill relative to local persistence. However, the prediction skill from this GSI is not larger than that gained using models incorporating nearby or upstream shelf/slope temperatures. Based on these results, a simplified statistical model has been developed, which can be tailored to fisheries management for the NES. 

A new air‐sea coupled mode is discovered off the coast of northern Chile and named Chile Niño/Niña. It shows remarkable interannual variability in sea surface temperature (SST) with the peak in austral summer from January to March. The related warm (cold) SST anomalies are mainly generated by anomalous southward (northward) alongshore surface winds that suppress (enhance) the coastal upwelling and subsurface mixing and, in turn, reinforce the wind anomalies by heating (cooling) the overlying atmosphere and strengthening the anomalous cross‐shore pressure contrast. The positive feedback is called the coastal Bjerknes feedback in analogy to the equatorial Bjerknes feedback that is responsible for generation of El Niño–Southern Oscillation. The anomalous surface shortwave radiation through the SST‐low stratus cloud thermodynamic feedback and the variation in the mixed‐layer depth play positive roles in the evolution of Chile Niño (Niña). In contrast, the wind‐evaporation‐SST feedback plays almost no role in the evolution.