scholarly journals Forecasting seasonal to interannual variability in extreme sea levels

2009 ◽  
Vol 66 (7) ◽  
pp. 1490-1496 ◽  
Author(s):  
Melisa Menendez ◽  
Fernando J. Mendez ◽  
Inigo J. Losada
Keyword(s):  
Interannual Variability ◽  
North Atlantic ◽  
Secular Trends ◽  
Linear Quadratic ◽  
Sea Levels ◽  
The North ◽  
Extreme Sea Levels ◽  
The North Atlantic Oscillation ◽  
Climate Events ◽  
Best Fit

Abstract Menendez, M., Mendez, F. J., and Losada, I. J. 2009. Forecasting seasonal to interannual variability in extreme sea levels. – ICES Journal of Marine Science, 66: 1490–1496. A statistical model to predict the probability of certain extreme sea levels occurring is presented. The model uses a time-dependent generalized extreme-value (GEV) distribution to fit monthly maxima series, and it is applied for a particular time-series record for the Atlantic Ocean (Newlyn, UK). The model permits the effects of seasonality, interannual variability, and secular trends to be identified and estimated in the probability distribution of extreme sea levels. These factors are parameterized as temporal functions (linear, quadratic, exponential, and periodic functions) or covariates (for instance, the North Atlantic Oscillation index), which automatically yield the best-fit model for the variability present in the data. A clear pattern of within-year variability and significant effects resulting from astronomical modulations (the nodal cycle and perigean tides) are detected. Modelling different time-scales helps to gain a better understanding of recent secular trends regarding extreme climate events, and it allows predictions to be made (for example, up to 2020) about the probability of the future occurrence of a particular sea level.

The dependence of UK extreme sea levels and storm surges on the North Atlantic Oscillation

2007 ◽  
Vol 27 (7) ◽  
pp. 935-946 ◽  
Author(s):  
P.L. Woodworth ◽  
R.A. Flather ◽  
J.A. Williams ◽  
S.L. Wakelin ◽  
S. Jevrejeva
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Storm Surges ◽  
Sea Levels ◽  
The North ◽  
Extreme Sea Levels ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

scholarly journals Interannual Variability of High-Wind Occurrence over the North Atlantic*

2011 ◽  
Vol 24 (24) ◽  
pp. 6515-6527 ◽  
Author(s):  
Xuhua Cheng ◽  
Shang-Ping Xie ◽  
Hiroki Tokinaga ◽  
Yan Du
Keyword(s):  
Interannual Variability ◽  
North Atlantic ◽  
Gulf Stream ◽  
Storm Track ◽  
Surface Air Temperature ◽  
High Wind ◽  
The North ◽  
The North Atlantic ◽  
The Difference ◽  
The North Atlantic Oscillation

Abstract Interannual variability of high-wind occurrence over the North Atlantic is investigated based on observations from the satellite-borne Special Sensor Microwave Imager (SSM/I). Despite no wind direction being included, SSM/I data capture major features of high-wind frequency (HWF) quite well. Climatology maps show that HWF is highest in winter and is close to zero in summer. Remarkable interannual variability of HWF is found in the vicinity of the Gulf Stream, over open sea south of Iceland, and off Cape Farewell, Greenland. On interannual scales, HWF south of Iceland has a significant positive correlation with the North Atlantic Oscillation (NAO). An increase in the mean westerlies and storm-track intensity during a positive NAO event cause HWF to increase in this region. In the vicinity of the Gulf Stream, HWF is significantly correlated with the difference between sea surface temperature and surface air temperature (SST − SAT), indicative of the importance of atmospheric instability. Cross-frontal wind and an SST gradient are important for the instability of the marine atmospheric boundary layer on the warm flank of the SST front. Off Cape Farewell, high wind occurs in both westerly and easterly tip jets. Quick Scatterometer (QuikSCAT) data show that variability in westerly (easterly) HWF off Cape Farewell is positively (negatively) correlated with the NAO.

scholarly journals An assessment of the Atlantic and Arctic sea–air CO<sub>2</sub> fluxes, 1990–2009

2013 ◽  
Vol 10 (1) ◽  
pp. 607-627 ◽  
Author(s):  
U. Schuster ◽  
G. A. McKinley ◽  
N. Bates ◽  
F. Chevallier ◽  
S. C. Doney ◽  
...  
Keyword(s):  
Interannual Variability ◽  
North Atlantic ◽  
Seasonal Cycle ◽  
Co2 Flux ◽  
Equatorial Region ◽  
The Arctic ◽  
The North ◽  
Biogeochemical Models ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Abstract. The Atlantic and Arctic Oceans are critical components of the global carbon cycle. Here we quantify the net sea–air CO2 flux, for the first time, across different methodologies for consistent time and space scales for the Atlantic and Arctic basins. We present the long-term mean, seasonal cycle, interannual variability and trends in sea–air CO2 flux for the period 1990 to 2009, and assign an uncertainty to each. We use regional cuts from global observations and modeling products, specifically a pCO2-based CO2 flux climatology, flux estimates from the inversion of oceanic and atmospheric data, and results from six ocean biogeochemical models. Additionally, we use basin-wide flux estimates from surface ocean pCO2 observations based on two distinct methodologies. Our estimate of the contemporary sea–air flux of CO2 (sum of anthropogenic and natural components) by the Atlantic between 40° S and 79° N is −0.49 ± 0.05 Pg C yr−1, and by the Arctic it is −0.12 ± 0.06 Pg C yr−1, leading to a combined sea–air flux of −0.61 ± 0.06 Pg C yr−1 for the two decades (negative reflects ocean uptake). We do find broad agreement amongst methodologies with respect to the seasonal cycle in the subtropics of both hemispheres, but not elsewhere. Agreement with respect to detailed signals of interannual variability is poor, and correlations to the North Atlantic Oscillation are weaker in the North Atlantic and Arctic than in the equatorial region and southern subtropics. Linear trends for 1995 to 2009 indicate increased uptake and generally correspond between methodologies in the North Atlantic, but there is disagreement amongst methodologies in the equatorial region and southern subtropics.

scholarly journals Atlantic and Arctic sea-air CO<sub>2</sub> fluxes, 1990–2009

2012 ◽  
Vol 9 (8) ◽  
pp. 10669-10724 ◽  
Author(s):  
U. Schuster ◽  
G. A. McKinley ◽  
N. Bates ◽  
F. Chevallier ◽  
S. C. Doney ◽  
...  
Keyword(s):  
Interannual Variability ◽  
North Atlantic ◽  
Seasonal Cycle ◽  
Co2 Flux ◽  
Equatorial Region ◽  
The Arctic ◽  
The North ◽  
Biogeochemical Models ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Abstract. The Atlantic and Arctic oceans are critical components of the global carbon cycle. Here we quantify the net sea-air CO2 flux, for the first time, across different methodologies for consistent time and space scales, for the Atlantic and Arctic basins. We present the long-term mean, seasonal cycle, interannual variability and trends in sea-air CO2 flux for the period 1990 to 2009, and assign an uncertainty to each. We use regional cuts from global observations and modelling products, specifically a pCO2-based CO2 flux climatology, flux estimates from the inversion of oceanic and atmospheric data, and results from six ocean biogeochemical models. Additionally, we use basin-wide flux estimates from surface ocean pCO2 observations based on two distinct methodologies. Our best estimate of the contemporary sea-to-air flux of CO2 (sum of anthropogenic and natural components) by the Atlantic between 40° S and 79° N is −0.49 ± 0.11 Pg C yr−1 and by the Arctic is −0.12 ± 0.06 Pg C yr−1, leading to a combined sea-to-air flux of −0.61 ± 0.12 Pg C yr−1 for the two decades (negative reflects ocean uptake). We do find broad agreement amongst methodologies with respect to the seasonal cycle in the subtropics of both hemispheres, but not elsewhere. Agreement with respect to detailed signals of interannual variability is poor; and correlations to the North Atlantic Oscillation are weaker in the North Atlantic and Arctic than in the equatorial region and South Subtropics. Linear trends for 1995 to 2009 indicate increased uptake and generally correspond between methodologies in the North Atlantic, but there is disagreement amongst methodologies in the equatorial region and South Subtropics.

scholarly journals Seasonal and Interannual Variability of the Barents Sea Temperature

2019 ◽  
Vol 25 ◽  
pp. 1-13
Author(s):  
Ilya V. Serykh ◽  
Andrey G. Kostianoy
Keyword(s):  
Interannual Variability ◽  
North Atlantic ◽  
Barents Sea ◽  
Southern Oscillation ◽  
North Atlantic Current ◽  
Sea Temperature ◽  
The North ◽  
The Barents Sea ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Analysis of the monthly average temperature data of the Barents Sea at various depths for the period 1948-2016 showed its growth, which accelerated significantly since the mid-1980s. Against the background of this growth, interannual variability was found over periods of 2 to 7 years and about 10 years. It is shown that periods of this variability can be associated, respectively, with El Nino - Southern Oscillation and the North Atlantic Oscillation. It has been hypothesized that the Global Atmospheric Oscillation may be the synchronizing mechanism of the interannual variability of the tropics of the Pacific Ocean, the North Atlantic and the Barents Sea. Interdecadal changes with a period of about 15 years were also found, which are most likely related to surface temperature anomalies carried by the North Atlantic Current.

Extreme sea levels in the context of climate change

2020 ◽  
Author(s):  
Lucia Pineau-Guillou ◽  
Pascal Lazure ◽  
Guy Wöppelmann
Keyword(s):  
Climate Change ◽  
North Atlantic ◽  
Tide Gauge ◽  
Storm Surges ◽  
Sea Levels ◽  
The North ◽  
Extreme Sea Levels ◽  
Centennial Time Scale ◽  
The North Atlantic ◽  
Phd Thesis

&lt;p&gt;The objective of this study is to investigate how extreme sea levels are changing, at a centennial time scale, in the context of climate change. We focus on Brest tide gauge (France), one of the longest time series in the world. First observations were recorded in 1701, and hourly data have been registered continuously since 1846 with little gaps. These data have been &amp;#160;carefully processed, in order to ensure good quality, especially regarding the datum continuity (Pouvreau, 2008) and stability (Poitevin, 2019).&lt;/p&gt;&lt;p&gt;Here, we investigate the evolution of the storm surges over the last 170 years. We focus on the skew surge, defined as the difference between the maximum observed water level and the maximum predicted tidal level (taking into account the mean sea level rise). This parameter is directly linked to the atmosphere variations, and may be correlated with regional climate parameters, such as the North Atlantic Oscillation (Men&amp;#233;ndez and Woodworth, 2010). But it is also correlated with the evolution of the storminess in the North Atlantic. One of the challenges is to separate the natural interannual variability of the sea level from the long term trends at a centennial time scale.&lt;/p&gt;&lt;p&gt;We will discuss the variability of the storm surges, in terms of changes in the 99th percentile and the 5-year return period level. Statistical analysis will be based on extreme values theory (e.g. Generalized Extreme Value distribution, General Pareto Distribution). Correlation with other parameters such as the significant wave height (from buoys) and the wind and storm tracks (from global reanalysis, e.g. ERA5 from ECMWF) will also be investigated.&lt;/p&gt;&lt;p&gt;References&lt;br&gt;Men&amp;#233;ndez M., Woodworth P. L. (2010). Changes in extreme high water levels based on a quasi-global tide-gauge dataset. J Geophys Res 115:C10011.&lt;br&gt;Poitevin (2019). Variabilit&amp;#233; du niveau marin relatif le long du littoral de Brest (France) par combinaison de m&amp;#233;thodes g&amp;#233;od&amp;#233;siques spatiales (altim&amp;#233;trie radar, InSAR et GPS). PhD thesis, University of La Rochelle.&lt;br&gt;Pouvreau N. (2008). Trois cents ans de mesures mar&amp;#233;graphiques en France : outils, m&amp;#233;thodes et tendances des composantes du niveau de la mer au port de Brest. PhD thesis, University of La Rochelle.&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

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