scholarly journals ENSO components of the Atlantic multidecadal oscillation and their relation to North Atlantic interannual coastal sea level anomalies

Ocean Science ◽  
2013 ◽  
Vol 9 (3) ◽  
pp. 535-543 ◽  
Author(s):  
J. Park ◽  
G. Dusek
Keyword(s):  
Sea Level ◽  
North Atlantic ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
The United States ◽  
Empirical Orthogonal Functions ◽  
Water Levels ◽  
Total Contribution ◽  
Sea Level Anomalies ◽  
Coastal Sea

Abstract. The El Niño Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO) are known to influence coastal water levels along the East Coast of the United States. By identifying empirical orthogonal functions (EOFs), which coherently contribute from the Multivariate ENSO Index (MEI) to the AMO index (AMOI), we characterize both the expression of ENSO in the unsmoothed AMOI, and coherent relationships between these indices and interannual sea level anomalies at six stations in the Gulf of Mexico and western North Atlantic. Within the ENSO band (2–7 yr periods) the total contribution of MEI to unsmoothed AMOI variability is 79%. Cross correlation suggests that the MEI leads expression of the ENSO signature in the AMOI by six months, consistent with the mechanism of an atmospheric bridge. Within the ENSO band, essentially all of the coupling between the unsmoothed AMOI and sea level anomalies is the result of ENSO expression in the AMOI. At longer periods we find decadal components of sea level anomalies linked to the AMOI at three southern stations (Key West, Pensacola, Charleston), but not at the northern stations (Baltimore, Boston, Portland), with values of coherence ranging from 20 to 50%. The coherence of MEI to coastal sea level anomalies has a different structure and is generally weaker than that of the ENSO expressed AMOI influence, suggesting distinct physical mechanisms are influencing sea level anomalies due to a direct ENSO teleconnection when compared to teleconnections based on ENSO expression in the AMOI. It is expected that applying this analysis to extremes of sea level anomalies will reveal additional influences.

scholarly journals ENSO components of the Atlantic multidecadal oscillation and their relation to North Atlantic interannual coastal sea level anomalies

2012 ◽  
Vol 9 (6) ◽  
pp. 3673-3699
Author(s):  
J. Park ◽  
G. Dusek
Keyword(s):  
Sea Level ◽  
North Atlantic ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
The United States ◽  
Empirical Orthogonal Functions ◽  
Water Levels ◽  
Total Contribution ◽  
Sea Level Anomalies ◽  
Coastal Sea

Abstract. The El Niño Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO) are known to influence coastal water levels along the east coast of the United States. By identifying empirical orthogonal functions (EOFs) which coherently contribute from the Multivariate ENSO Index (MEI) to the AMO index (AMOI), we characterize both the expression of ENSO in the unsmoothed AMOI, and coherent relationships between these indices and interannual sea level anomalies at six stations in the Gulf of Mexico and Western North Atlantic. Within the ENSO band (2–7 yr periods) the total contribution of MEI to unsmoothed AMOI variability is 79%. Cross correlation suggests that the MEI leads expression of the ENSO signature in the AMOI by six months, consistent with the mechanism of an atmospheric bridge. Within the ENSO band, essentially all of the coupling between the unsmoothed AMOI and sea level anomalies is the result of ENSO expression in the AMOI. At longer periods we find decadal components of sea level anomalies linked to the AMOI at three southern stations (Key West, Pensacola, Charleston), but not at the northern stations (Baltimore, Boston, Portland), with values of coherence ranging from 20 to 50%. The coherence of MEI to coastal sea level anomalies has a different structure and is generally weaker than that of the ENSO expressed AMOI influence, suggesting distinct physical mechanisms are influencing sea level anomalies due to a direct ENSO teleconnection when compared to teleconnections based on ENSO expression in the AMOI. It is expected that applying this analysis to extremes of sea level anomalies will reveal additional influences.

scholarly journals Cool-Season Sea Level Anomalies and Storm Surges along the U.S. East Coast: Climatology and Comparison with the 2009/10 El Niño

2011 ◽  
Vol 139 (7) ◽  
pp. 2290-2299 ◽  
Author(s):  
William V. Sweet ◽  
Chris Zervas
Keyword(s):  
Sea Level ◽  
El Niño ◽  
East Coast ◽  
El Nino ◽  
Southern Oscillation ◽  
Storm Surges ◽  
The United States ◽  
Atlantic City ◽  
Cool Season ◽  
Sea Level Anomalies

Abstract Climatologies of sea level anomalies (>0.05 m) and daily-mean storm surges (>0.3 m) are presented for the 1960–2010 cool seasons (October–April) along the East Coast of the United States at Boston, Massachusetts; Atlantic City, New Jersey; Sewells Point (Norfolk), Virginia; and Charleston, South Carolina. The high sea level anomaly and the number of storm surges, among the highest in the last half century during the 2009/10 cool season, are comparable during strong El Niño cool seasons. High numbers of daily storm surges occur in response to numerous East Coast extratropical cool-season storms and have a positive correlation with the El Niño phase of the El Niño–Southern Oscillation (ENSO). Patterns of anomalously high sea levels are attributed to El Niño–related changes to atmospheric pressure over the Gulf of Mexico and eastern Canada and to the wind field over the Northeast U.S. continental shelf.

scholarly journals Economic damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Benjamin H. Strauss ◽  
Philip M. Orton ◽  
Klaus Bittermann ◽  
Maya K. Buchanan ◽  
Daniel M. Gilford ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
East Coast ◽  
The United States ◽  
Hurricane Sandy ◽  
Water Levels ◽  
Anthropogenic Climate Change ◽  
Economic Damage ◽  
Sea Levels

AbstractIn 2012, Hurricane Sandy hit the East Coast of the United States, creating widespread coastal flooding and over $60 billion in reported economic damage. The potential influence of climate change on the storm itself has been debated, but sea level rise driven by anthropogenic climate change more clearly contributed to damages. To quantify this effect, here we simulate water levels and damage both as they occurred and as they would have occurred across a range of lower sea levels corresponding to different estimates of attributable sea level rise. We find that approximately $8.1B ($4.7B–$14.0B, 5th–95th percentiles) of Sandy’s damages are attributable to climate-mediated anthropogenic sea level rise, as is extension of the flood area to affect 71 (40–131) thousand additional people. The same general approach demonstrated here may be applied to impact assessments for other past and future coastal storms.

scholarly journals Alongshore Wind Forcing of Coastal Sea Level as a Function of Frequency

2006 ◽  
Vol 36 (11) ◽  
pp. 2173-2184 ◽  
Author(s):  
Holly F. Ryan ◽  
Marlene A. Noble
Keyword(s):  
United States ◽  
Frequency Response ◽  
Sea Level ◽  
Response Function ◽  
Wind Field ◽  
Frequency Response Function ◽  
The United States ◽  
The West ◽  
Coastal Sea ◽  
Alongshore Wind

Abstract The amplitude of the frequency response function between coastal alongshore wind stress and adjusted sea level anomalies along the west coast of the United States increases linearly as a function of the logarithm (log10) of the period for time scales up to at least 60, and possibly 100, days. The amplitude of the frequency response function increases even more rapidly at longer periods out to at least 5 yr. At the shortest periods, the amplitude of the frequency response function is small because sea level is forced only by the local component of the wind field. The regional wind field, which controls the wind-forced response in sea level for periods between 20 and 100 days, not only has much broader spatial scales than the local wind, but also propagates along the coast in the same direction as continental shelf waves. Hence, it has a stronger coupling to and an increased frequency response for sea level. At periods of a year or more, observed coastal sea level fluctuations are not only forced by the regional winds, but also by joint correlations among the larger-scale climatic patterns associated with El Niño. Therefore, the amplitude of the frequency response function is large, despite the fact that the energy in the coastal wind field is relatively small. These data show that the coastal sea level response to wind stress forcing along the west coast of the United States changes in a consistent and predictable pattern over a very broad range of frequencies with time scales from a few days to several years.

scholarly journals Data-Driven Interpolation of Sea Level Anomalies Using Analog Data Assimilation

2019 ◽  
Vol 11 (7) ◽  
pp. 858 ◽  
Author(s):  
Redouane Lguensat ◽  
Phi Huynh Viet ◽  
Miao Sun ◽  
Ge Chen ◽  
Tian Fenglin ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Large Scale ◽  
Empirical Orthogonal Functions ◽  
Data Driven ◽  
Optimal Interpolation ◽  
Observation System ◽  
Orthogonal Functions ◽  
Sea Level Anomalies ◽  
Recent Developments

From the recent developments of data-driven methods as a means to better exploit large-scale observation, simulation and reanalysis datasets for solving inverse problems, this study addresses the improvement of the reconstruction of higher-resolution Sea Level Anomaly (SLA) fields using analog strategies. This reconstruction is stated as an analog data assimilation issue, where the analog models rely on patch-based and Empirical Orthogonal Functions (EOF)-based representations to circumvent the curse of dimensionality. We implement an Observation System Simulation Experiment (OSSE) in the South China Sea. The reported results show the relevance of the proposed framework with a significant gain in terms of Root Mean Square Error (RMSE) for scales below 100 km. We further discuss the usefulness of the proposed analog model as a means to exploit high-resolution model simulations for the processing and analysis of current and future satellite-derived altimetric data with regard to conventional interpolation schemes, especially optimal interpolation.

scholarly journals Dynamic wavelet correlation analysis for multivariate climate time series

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Josué M. Polanco-Martínez ◽  
Javier Fernández-Macho ◽  
Martín Medina-Elizalde
Keyword(s):  
Time Series ◽  
Tropical Cyclone ◽  
North Atlantic ◽  
Large Scale ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
Last Millennium ◽  
Climate Data ◽  
The North ◽  
Climate Time Series

AbstractThe wavelet local multiple correlation (WLMC) is introduced for the first time in the study of climate dynamics inferred from multivariate climate time series. To exemplify the use of WLMC with real climate data, we analyse Last Millennium (LM) relationships among several large-scale reconstructed climate variables characterizing North Atlantic: i.e. sea surface temperatures (SST) from the tropical cyclone main developmental region (MDR), the El Niño-Southern Oscillation (ENSO), the North Atlantic Multidecadal Oscillation (AMO), and tropical cyclone counts (TC). We examine the former three large-scale variables because they are known to influence North Atlantic tropical cyclone activity and because their underlying drivers are still under investigation. WLMC results obtained for these multivariate climate time series suggest that: (1) MDRSST and AMO show the highest correlation with each other and with respect to the TC record over the last millennium, and: (2) MDRSST is the dominant climate variable that explains TC temporal variability. WLMC results confirm that this method is able to capture the most fundamental information contained in multivariate climate time series and is suitable to investigate correlation among climate time series in a multivariate context.

scholarly journals Using Teleconnections to Predict Wildfires in Mississippi

2008 ◽  
Vol 136 (7) ◽  
pp. 2804-2811 ◽  
Author(s):  
P. Grady Dixon ◽  
Gregory B. Goodrich ◽  
William H. Cooke
Keyword(s):  
United States ◽  
North Atlantic ◽  
Southern Oscillation ◽  
Southeastern United States ◽  
Fire Risk ◽  
The United States ◽  
Risk Models ◽  
Wildfire Occurrence ◽  
Atmospheric Teleconnections ◽  
Fire Risk Models

Abstract Previous wildfire research in the United States has been focused primarily on the western states. Much of this research has discovered relationships between wildfire variability and atmospheric teleconnections. Thus far, few published projects have addressed the effects of various teleconnections on wildfire in the southeastern United States. Index values for the El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific decadal oscillation (PDO), and Pacific–North American (PNA) pattern are all tested for relationships with fire variables in the state of Mississippi. Each of the indices displays significant correlations with wildfire occurrence and/or size in Mississippi. The findings of this research suggest that it might be feasible to create predictive fire-risk models for the southeastern United States based on the combination of these teleconnection indices.

The Spatial Pattern of the Sun-Hurricane Connection across the North Atlantic

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Robert E. Hodges ◽  
James B. Elsner
Keyword(s):  
North Atlantic ◽  
Southern Oscillation ◽  
The United States ◽  
The Sun ◽  
Equal Area ◽  
The North ◽  
Spatial Response ◽  
The Caribbean ◽  
The North Atlantic ◽  
Eastern Seaboard

The authors define the spatial response of hurricanes to extremes in the solar cycle. Using an equal-area hexagon tessellation, regional hurricane counts are examined during the period 1851–2010. The response features fewer hurricanes across the Caribbean, Gulf of Mexico, and along the eastern seaboard of the United States when sunspots are numerous. In contrast fewer hurricanes are observed in the central North Atlantic when sunspots are few. The sun-hurricane connection is as important as the El Niño Southern Oscillation toward statistically explaining regional hurricane occurrences.

scholarly journals TIME-VARYING EMULATOR FOR SHORT- AND LONG-TERM ANALYSIS OF COASTAL FLOODING (TESLA-FLOOD)

2018 ◽  
pp. 4
Author(s):  
Dylan Anderson ◽  
Peter Ruggiero ◽  
Fernando J. Mendez ◽  
Ana Rueda ◽  
Jose A. Antolinez ◽  
...  
Keyword(s):  
Sea Level ◽  
Storm Surges ◽  
Coastal Flooding ◽  
Water Levels ◽  
Sea Level Anomalies ◽  
Extreme Water Levels ◽  
Flooding Risk ◽  
The Individual ◽  
Flooding Events

The ability to predict coastal flooding events and associated impacts has emerged as a primary societal need within the context of projected sea level rise (SLR) and climate change. The duration and extent of flooding is the result of nonlinear interactions between multiple environmental forcings (oceanographic, meteorological, hydrological) acting at varying spatial (local to global) and temporal scales (hours to centuries). Individual components contributing to total water levels (TWLs) include astronomical tides, monthly sea level anomalies, storm surges, and wave setup. Common practices often use the observational record of extreme water levels to estimate return levels of future extremes. However, such projections often do not account for the individual contribution of processes resulting in compound TWL events, nor do they account for time-dependent probabilities due to seasonal, interannual, and long-term oscillations within the climate system. More robust estimates of coastal flooding risk require the computation of joint probabilities and the simulation of hypothetical TWLs to better constrain the projection of extremes (Serafin [2014]).

scholarly journals River-discharge effects on United States Atlantic and Gulf coast sea-level changes

2018 ◽  
Vol 115 (30) ◽  
pp. 7729-7734 ◽  
Author(s):  
Christopher G. Piecuch ◽  
Klaus Bittermann ◽  
Andrew C. Kemp ◽  
Rui M. Ponte ◽  
Christopher M. Little ◽  
...  
Keyword(s):  
United States ◽  
Sea Level ◽  
River Discharge ◽  
Sea Level Change ◽  
The United States ◽  
Ocean Dynamics ◽  
Sea Level Changes ◽  
Level Change ◽  
Vertical Land Motion ◽  
Coastal Sea

Identifying physical processes responsible for historical coastal sea-level changes is important for anticipating future impacts. Recent studies sought to understand the drivers of interannual to multidecadal sea-level changes on the United States Atlantic and Gulf coasts. Ocean dynamics, terrestrial water storage, vertical land motion, and melting of land ice were highlighted as important mechanisms of sea-level change along this densely populated coast on these time scales. While known to exert an important control on coastal ocean circulation, variable river discharge has been absent from recent discussions of drivers of sea-level change. We update calculations from the 1970s, comparing annual river-discharge and coastal sea-level data along the Gulf of Maine, Mid-Atlantic Bight, South Atlantic Bight, and Gulf of Mexico during 1910–2017. We show that river-discharge and sea-level changes are significantly correlated (p<0.01), such that sea level rises between 0.01 and 0.08 cm for a 1 km3 annual river-discharge increase, depending on region. We formulate a theory that describes the relation between river-discharge and halosteric sea-level changes (i.e., changes in sea level related to salinity) as a function of river discharge, Earth’s rotation, and density stratification. This theory correctly predicts the order of observed increment sea-level change per unit river-discharge anomaly, suggesting a causal relation. Our results have implications for remote sensing, climate modeling, interpreting Common Era proxy sea-level reconstructions, and projecting coastal flood risk.

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