58 research outputs found
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The influence of pacific winds on ENSO diversity
The differences in ENSO sea surface temperature (SST) spatial patterns, whether centered in the Eastern Pacific (EP), Central Pacific (CP) or in the eastern-central equatorial region ("canonical") have been associated to differences in atmospheric teleconnections and global impacts. However, predicting different types of ENSO events has proved challenging, highlighting the need for a deeper understanding of their predictability. Given the key role played by wind variations in the development and evolution of ENSO events, this study examines the relationship between the leading modes of Pacific surface wind speed variability and ENSO diversity using three different state-of-the-art wind products, including satellite observations and atmospheric reanalyses. Although previous studies have associated different ENSO precursors to either EP or CP events, our results indicate that the most prominent of those ENSO precursors are primarily related to canonical and CP events, and show little correlation with EP events. The latter are associated with tropical Pacific conditions favoring equatorial westerly wind and precipitation anomalies that extend all the way to the eastern Pacific. Results over the entire twentieth century period versus those during the satellite era also suggest that the influences from the Southern Hemisphere may be more robust than those from the Northern Hemisphere.
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Linear or Nonlinear Modeling for ENSO Dynamics?
The observed ENSO statistics exhibits a non-Gaussian behavior, which is indicative of the presence of nonlinear processes. In this paper, we use the Recharge Oscillator Model (ROM), a largely used Low-Order Model (LOM) of ENSO, as well as methodologies borrowed from the field of statistical mechanics to identify which aspects of the system may give rise to nonlinearities that are consistent with the observed ENSO statistics. In particular, we are interested in understanding whether the nonlinearities reside in the system dynamics or in the fast atmospheric forcing. Our results indicate that one important dynamical nonlinearity often introduced in the ROM cannot justify a non-Gaussian system behavior, while the nonlinearity in the atmospheric forcing can instead produce a statistics similar to the observed. The implications of the non-Gaussian character of ENSO statistics for the frequency of extreme El Nino events is then examined
A multi-modal representation of El Ni\~no Southern Oscillation Diversity
The El Ni\~no-Southern Oscillation (ENSO) is characterized by alternating
periods of warm (El Ni\~no) and cold (La Ni\~na) sea surface temperature
anomalies (SSTA) in the equatorial Pacific. Although El Ni\~no and La Ni\~na
are well-defined climate patterns, no two events are alike. To date, ENSO
diversity has been described primarily in terms of the longitudinal location of
peak SSTA, used to define a bimodal classification of events in Eastern Pacific
(EP) and Central Pacific (CP) types. Here, we use low-dimensional
representations of Pacific SSTAs to argue that binary categorical memberships
are unsuitable to describe ENSO events. Using fuzzy unsupervised clustering, we
recover the four known ENSO categories, along with a fifth category: an Extreme
El Ni\~no. We show that Extreme El Ni\~nos differ both in their intensity and
temporal evolution from canonical EP El Ni\~nos. We also find that CP La
Ni\~nas, EP El Ni\~nos, and Extreme El Ni\~nos contribute the most to
interdecadal ENSO variability
Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System
The improvement in the climatological behavior of a numerical model as a consequence of the assimilation of surface data is investigated. The model used for this study is a quasigeostrophic (QG) model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height that have been obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. Comparisons of the assimilation results with available in situ observations show a significant improvement in the degree of realism of the climatological model behavior, with respect to the model in which no data are assimilated. The remaining discrepancies in the model mean circulation seem to be mainly associated with deficiencies in the mean component of the surface data that are assimilated. On the other hand, the possibility of building into the model more realistic eddy characteristics through the assimilation of the surface eddy field proves very successful in driving components of the mean model circulation that are in relatively good agreement with the available observations. Comparisons with current meter time series during a time period partially overlapping the Geosat mission show that the model is able to 'correctly' extrapolate the instantaneous surface eddy signals to depths of approximately 1500 m. The correlation coefficient between current meter and model time series varies from values close to 0.7 in the top 1500 m to values as low as 0.1-0.2 in the deep ocean
Low-frequency variability in the Gulf of Alaska from coarse and eddy-permitting ocean models
[1] An eddy-permitting ocean model of the northeast Pacific is used to examine the ocean adjustment to changing wind forcing in the Gulf of Alaska (GOA) at interannual-to-decadal timescales. It is found that the adjustment of the ocean model in the presence of mesoscale eddies is similar to that obtained with coarse-resolution models. Local Ekman pumping plays a key role in forcing pycnocline depth variability and, to a lesser degree, sea surface height (SSH) variability in the center of the Alaska gyre and in some areas of the eastern and northern GOA. Westward Rossby wave propagation is evident in the SSH field along some latitudes but is less noticeable in the pycnocline depth field. Differences between SSH and pycnocline depth are also found when considering their relationship with the local forcing and leading modes of climate variability in the northeast Pacific. In the central GOA pycnocline depth variations are more clearly related to changes in the local Ekman pumping than SSH. While SSH is marginally correlated with both Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO) indices, the pycnocline depth evolution is primarily related to NPGO variability. The intensity of the mesoscale eddy field increases with increasing circulation strength. The eddy field is generally more energetic after the 1976–1977 climate regime shift, when the gyre circulation intensified. In the western basin, where eddies primarily originate from intrinsic instabilities of the flow, variations in eddy kinetic energy are statistically significant correlated with the PDO index, indicating that eddy statistics may be inferred, to some degree, from the characteristics of the large-scale flow
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Predictability and empirical dynamics of fisheries time series in the North Pacific
Previous studies have documented a strong relationship between marine ecosystems and large-scale modes of sea surface height (SSH) and sea surface temperature (SST) variability in the North Pacific such as the Pacific Decadal Oscillation and the North Pacific Gyre Oscillation. In the central and western North Pacific along the Kuroshio-Oyashio Extension (KOE), the expression of these modes in SSH and SST is linked to the propagation of long oceanic Rossby waves, which extend the predictability of the climate system to ~3 years. Using a multivariate physical-biological linear inverse model (LIM) we explore the extent to which this physical predictability leads to multi-year prediction of dominant fishery indicators inferred from three datasets (i.e., estimated biomasses, landings, and catches). We find that despite the strong autocorrelation in the fish indicators, the LIM adds dynamical forecast skill beyond persistence up to 5-6 years. By performing a sensitivity analysis of the LIM forecast model, we find that two main factors are essential for extending the dynamical predictability of the fishery indicators beyond persistence. The first is the interaction of the fishery indicators with the SST/SSH of the North and tropical Pacific. The second is the empirical relationship among the fisheries time series. This latter component reflects stock-stock interactions as well as common technological and human socioeconomic factors that may influence multiple fisheries and are captured in the training of the LIM. These results suggest that empirical dynamical models and machine learning algorithms, such as the LIM, provide an alternative and promising approach for forecasting key ecological indicators beyond the skill of persistence.
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Atmospheric convection and air-sea interactions over the tropical oceans: scientific progress, challenges, and opportunities
© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hagos, S., Foltz, G. R., Zhang, C., Thompson, E., Seo, H., Chen, S., Capotondi, A., Reed, K. A., DeMott, C., & Protat, A. Atmospheric convection and air-sea interactions over the tropical oceans: scientific progress, challenges, and opportunities. Bulletin of the American Meteorological Society, 101(3), (2020): E253-E258, doi:10.1175/BAMS-D-19-0261.1.Over the past 30 years, the scientific community has made considerable progress in understanding and predicting tropical convection and air–sea interactions, thanks to sustained investments in extensive in situ and remote sensing observations, targeted field experiments, advances in numerical modeling, and vastly improved computational resources and observing technologies. Those investments would not have been fruitful as isolated advancements without the collaborative effort of the atmospheric convection and air–sea interaction research communities. In this spirit, a U.S.- and International CLIVAR–sponsored workshop on “Atmospheric convection and air–sea interactions over the tropical oceans” was held in the spring of 2019 in Boulder, Colorado. The 90 participants were observational and modeling experts from the atmospheric convection and air–sea interactions communities with varying degrees of experience, from early-career researchers and students to senior scientists. The presentations and discussions covered processes over the broad range of spatiotemporal scales (Fig. 1).The workshop was sponsored by the United States and International CLIVAR. Funding was provided by the U.S. Department of Energy, Office of Naval Research, NOAA, NSF, and the World Climate Research Programme. We thank Mike Patterson, Jennie Zhu, and Jeff Becker from the U.S. CLIVAR Project Office for coordinating the workshop
ENSO diversity shows robust decadal variations that must be captured for accurate future projections
El Niño-Southern Oscillation (ENSO) shows a large diversity of events that is modulated by climate variability and change. The representation of this diversity in climate models limits our ability to predict their impact on ecosystems and human livelihood. Here, we use multiple observational datasets to provide a probabilistic description of historical variations in event location and intensity, and to benchmark models, before examining future system trajectories. We find robust decadal variations in event intensities and locations in century-long observational datasets, which are associated with perturbations in equatorial wind-stress and thermocline depth, as well as extra-tropical anomalies in the North and South Pacific. Some climate models are capable of simulating such decadal variability in ENSO diversity, and the associated large-scale patterns. Projections of ENSO diversity in future climate change scenarios strongly depend on the magnitude of decadal variations, and the ability of climate models to reproduce them realistically over the 21st century
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Predictability of US West Coast Ocean Temperatures is not solely due to ENSO
The causes of the extreme and persistent warming in the Northeast Pacific from the winter of 2013/14 to that of 2014/15 are still not fully understood. While global warming may have contributed, natural influences may also have played a role. El Niño events are often implicated in anomalously warm conditions along the US West Coast (USWC). However, the tropical Pacific sea surface temperature (SST) anomalies were generally weak during 2014, calling into question their role in the USWC warming. In this study, we identify tropical Pacific “sensitivity patterns” that optimally force USWC warming at a later time. We find that such sensitivity patterns do not coincide with the mature SST anomaly patterns usually associated with ENSO, but instead include elements associated with ENSO SST precursors and SST anomalies in the central/western equatorial Pacific. El Niño events that produce large USWC warming, irrespective of their magnitude, do project on the sensitivity pattern and are characterized by a distinct evolution of the North Pacific atmospheric and oceanic fields. However, even weak tropical SST anomalies in the right location, and not necessarily associated with ENSO, can significantly influence USWC conditions and enhance their predictability.</p
Bottom-Up Forcing And The Decline of Steller Sea Lions (Eumetopias jubatus) In Alaska: Assessing The Ocean Climate Hypothesis
Declines of Steller sea lion ( Eumetopias jubatus) populations in the Aleutian Islands and Gulf of Alaska could be a consequence of physical oceanographic changes associated with the 1976–77 climate regime shift. Changes in ocean climate are hypothesized to have affected the quantity, quality, and accessibility of prey, which in turn may have affected the rates of birth and death of sea lions. Recent studies of the spatial and temporal variations in the ocean climate system of the North Pacific support this hypothesis. Ocean climate changes appear to have created adaptive opportunities for various species that are preyed upon by Steller sea lions at mid-trophic levels. The east–west asymmetry of the oceanic response to climate forcing after 1976–77 is consistent with both the temporal aspect (populations decreased after the late 1970s) and the spatial aspect of the decline (western, but not eastern, sea lion populations decreased). These broad-scale climate variations appear to be modulated by regionally sensitive biogeographic structures along the Aleutian Islands and Gulf of Alaska, which include a transition point from coastal to open-ocean conditions at Samalga Pass westward along the Aleutian Islands. These transition points delineate distinct clusterings of different combinations of prey species, which are in turn correlated with differential population sizes and trajectories of Steller sea lions. Archaeological records spanning 4000 yr further indicate that sea lion populations have experienced major shifts in abundance in the past. Shifts in ocean climate are the most parsimonious underlying explanation for the broad suite of ecosystem changes that have been observed in the North Pacific Ocean in recent decades. [ABSTRACT FROM AUTHOR]
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