It is well understood that isolated eddies are presumed to propagate westward intrinsically at the speed of the annual baroclinic Rossby wave. This classic description, however, is known to be frequently violated in both propagation speed and its direction in the real ocean. Here, we present a systematic analysis on the divergence of eddy propagation direction (i.e., global pattern of departure from due west) and dispersion of eddy propagation speed (i.e., zonal pattern of departure from Rossby wave phase speed). Our main findings include the following: 1) A global climatological phase map (the first of its kind to our knowledge) indicating localized direction of most likely eddy propagation has been derived from twenty-eight years (1993-2020) of satellite altimetry, leading to a leaf-like full-angle pattern in its overall divergence. 2) A meridional deflection map of eddy motion is created with prominent equatorward/poleward deflecting zones identified, revealing that it is more geographically correlated rather than polarity determined as previously thought (i.e., poleward for cyclonic eddies and equatorward for anticyclonic ones). 3) The eddy-Rossby wave relationship has a duality nature (waves riding by eddies) in five subtropical bands centered around 27°N and 26°S in the two hemispheres, outside which their relationship has a dispersive nature with dominant waves (eddies) propagating faster in the tropical (extratropical) oceans. Current, wind and topographic effects are major external forcings responsible for the observed divergence and dispersion of eddy propagations. These results are expected to make a significant contribution to eddy trajectory prediction using physically based and/or data-driven models.
The inadequate spatial resolution of altimeter results in low identification efficiency of oceanic eddies, especially for small-scale eddies. It is well known that eddies can not only induce sea surface signal but more importantly have typical vertical structure characteristics. However, although the vertical structure characteristics are usually used for statistical analysis, they are seldom considered in the process of eddy recognition. This study is devoted to identifying eddies from the perspective of their vertical signal derived from the 18-year Argo data. Due to the irregular and noisy profile pattern, the direct identification of eddy core from Argo profile is deemed to be a challenge. With the popularity of artificial intelligence, a new hybrid method that combines the advantages of convolutional neural network (CNN) with extreme gradient boosting (XGBoost) is proposed to extract the representative vertical feature and identify eddy from a profile. First, CNN is employed as a feature extractor to automatically obtain vertical features from the input profile at the bottom of the network. Second, the obtained high-dimensional feature vectors are inputted into the XGBoost model, combined with other profile features for classifying profiles that are outside altimeter-identified eddies (Alt eddy). Finally, extensive experiments are implemented to demonstrate the efficiency of the proposed method. The results show that the classification accuracy of CNN-XGBoost model can reach 98%, and about 36% eddies are recaptured. These eddies, dubbed CNN-XGB eddies, are benchmarked against Alt eddies for the vertical structure and geographical distribution, demonstrating a similar or even stronger vertical signal and a prominent eddy belt in the tropical ocean. Within the proposed theory framework, there are various potentials to obtain a better outlook for eddy identification and in situ float observations.
Climate change impacts have driven a transformation of the global energy system. The utilization of renewable energies is required to meet energy demands while protecting the environment. Wind-generated waves, carrying energy from the atmosphere, are a possible energy supply. However, global and long-term variability in wave resources due to the effects of climate change remain uncertain. This study quantified the spatiotemporal patterns and availability of global wave power (GWP) based on the ERA5 hourly and monthly reanalysis products, spanning from 1979 to 2020. The most promising wave resources appeared centralized in the westerlies of both hemispheres, and the wave power exhibited a “rich-get-richer” trend in the Southern Ocean, dominating the overall distribution and variability of GWP. Significant seasonal and interannual oscillation trends in GWP were observed, but with little variations on daily and hourly time scales. We found the average GWP in ERA5 products increased by 12.89% suddenly in 1991, mainly caused by the beginning of altimeter assimilation. This also implies the potential underestimation of wave fields in the modeling results before the advent of altimeter. In the altimeter era, annual GWP exhibits (quasi-) decadal oscillation (variation near ±4%), which differed from the monotonous increases previously reported. An analysis and source tracing based on the climate teleconnections indexes revealed that the primary climate driver of the variability was the Southern Annual Mode (r = 0.84). This study provides scientific guidance for wave power utilization and helps deepen our understanding of air-sea interactions.
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