Sentences with phrase «of sea level variability»

Not exact matches

Researchers from the University of Southampton, the National Oceanography Centre and the Australian National University developed a new method for determining sea - level and deep - sea temperature variability over the past 5.3 million years.

«The important point here is that smooth projections of sea level rise do not capture this variability, so adverse effects of sea level rise may occur before they are predicted to happen,» Dutton said.

The centre runs research programmes in climate variability and change, the monitoring of sea levels, ocean uptake of carbon dioxide, and Antarctic marine ecosystems.

Episodes like volcanic eruptions can create variability: the eruption of Mount Pinatubo in 1991 decreased global mean sea level just before the Topex / Poseidon satellite launch, for example.

In the past 15 years, the oceans have warmed, the amount of snow and ice has diminished and sea levels have risen, explains Lisa Goddard, an expert in climate variability at Columbia University.

The CTD sections show that the deeper layers are also warmer and slightly saltier and the observed sea level can be explained by steric expansion over the upper 2000 m. ENSO variability impacts on the northern part of the section, and a simple Sverdrup transport model shows how large - scale changes in the wind forcing, related to the Southern Annular Mode, may contribute to the deeper warming to the south.

Abstract: Mid - to late - Holocene sea - level records from low - latitude regions serve as an important baseline of natural variability in sea level and global ice volume prior to the Anthropocene.

Suzuki, T., et al., 2005: Projection of future sea level and its variability in a high - resolution climate model: Ocean processes and Greenland and Antarctic ice - melt contributions.

«The impacts of sea level change will be felt most acutely during periods of high sea level, both from this type of interannual (and decadal) variability as well as extreme events,» Church said.

For birds and amphibians, we considered exposure to five components of climate change, namely changes in mean temperature, temperature variability, mean precipitation, precipitation variability and sea level rise.

The imprint of SAM variability on the Southern Ocean system is observed as a coherent sea level response around Antarctica (Aoki, 2002; Hughes et al., 2003) and by its regulation of Antarctic Circumpolar Current flow through the Drake Passage (Meredith et al., 2004).

«[B] y making use of 21 CMIP5 coupled climate models, we study the contribution of external forcing to the Pacific Ocean regional sea level variability over 1993 — 2013, and show that according to climate models, externally forced and thereby the anthropogenic sea level fingerprint on regional sea level trends in the tropical Pacific is still too small to be observable by satellite altimetry.»

Our framework links innovative approaches for (1) generating high - resolution, probabilistic projection of future climate and sea - level changes and (2) empirically identifying robust statistical relationships characterizing how humans have responded to past climate variability and past climate change, in order to (3) project how humans may respond to uncertain future changes.

There is nothing there beyond the regular short - term variability primarily due to ENSO, and of course we should smooth enough to get rid of this short - term variability when testing for the kind of long - term linkage between global temperature and sea level that we expect.

Periods that are of possibly the most interest for testing sensitivities associated with uncertainties in future projections are the mid-Holocene (for tropical rainfall, sea ice), the 8.2 kyr event (for the ocean thermohaline circulation), the last two millennia (for decadal / multi-decadal variability), the last interglacial (for ice sheets / sea level) etc..

Zhang, J., M. Steele, and A. Schweiger (2010), Arctic sea ice response to atmospheric forcings with varying levels of anthropogenic warming and climate variability, Geophys.

Mike's work, like that of previous award winners, is diverse, and includes pioneering and highly cited work in time series analysis (an elegant use of Thomson's multitaper spectral analysis approach to detect spatiotemporal oscillations in the climate record and methods for smoothing temporal data), decadal climate variability (the term «Atlantic Multidecadal Oscillation» or «AMO» was coined by Mike in an interview with Science's Richard Kerr about a paper he had published with Tom Delworth of GFDL showing evidence in both climate model simulations and observational data for a 50 - 70 year oscillation in the climate system; significantly Mike also published work with Kerry Emanuel in 2006 showing that the AMO concept has been overstated as regards its role in 20th century tropical Atlantic SST changes, a finding recently reaffirmed by a study published in Nature), in showing how changes in radiative forcing from volcanoes can affect ENSO, in examining the role of solar variations in explaining the pattern of the Medieval Climate Anomaly and Little Ice Age, the relationship between the climate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measurements).

Geoff Beacon, before betting too much check papers like Zhang et al. «Arctic sea ice response to atmospheric forcings with varying levels of anthropogenic warming and climate variability».

Those projections are detailed in Zhang et al, 2010 «Arctic sea ice response to atmospheric forcings with varying levels of anthropogenic warming and climate variability.»

The differences between the quadratic acceleration numbers come from differences in the decadal to multidecadal variability in the curves which I don't consider very robust (we have shown in Rahmstorf et al. 2012 how strongly these can be affected by a small amount of «noise» in the sea - level data).

Nevertheless such variability induced by winds or currents may give a false impression of global sea level fluctuations in analyses of tide gauge data.

It uses the satellite data of sea level to determine the typical variability patterns of the sea surface and thus to establish the link between the locally measured tide gauge values and the global sea level.

There are many patterns of behaviour particularly in the Pacific, associated with El Nino variability — possibly related to Vanuatu's lack of actual sea level rise over the last 40 years.

Variability in the prevailing winds (which can extend over decades, England et al. 2014) will therefore lead to variability in the water level along the coasts — but of course we know that the wind can not change global sea level at all as it merely redistributesVariability in the prevailing winds (which can extend over decades, England et al. 2014) will therefore lead to variability in the water level along the coasts — but of course we know that the wind can not change global sea level at all as it merely redistributesvariability in the water level along the coasts — but of course we know that the wind can not change global sea level at all as it merely redistributes the water.

The same is true for one source of sea - level rise, Greenland melting measured by GRACE: GRACE is a new instrument demanding calibration and Greenland a region known for its marked pluridecadal variability.

That approach, from Katrina forward, was bound to fail, given the variability of conditions year to year and persistent (and non-manufactured) uncertainty surrounding some of the most consequential impacts (for instance, the pace and extent of warming and sea - level rise in this century).

WMO will issue its full Statement on the State of the Climate in 2017 in March which will provide a comprehensive overview of temperature variability and trends, high - impact events, and long - term indicators of climate change such as increasing carbon dioxide concentrations, Arctic and Antarctic sea ice, sea level rise and ocean acidification.

Spatial variability of the rates of sea level rise is mostly due to non-uniform changes in temperature and salinity and related to changes in the ocean circulation.

Quadrelli and Wallace (2004) found that many patterns of NH interannual variability can be reconstructed as linear combinations of the first two Empirical Orthogonal Functions (EOFs) of sea level pressure (approximately the NAM and the PNA).

Much of what is of concern to the military is extreme weather events (e.g. Pakistan floods) driven by natural climate variability and random weather roulette (concerns about sea level rise and the opening of the Arctic Ocean are linked more closely to AGW)

The overarching goal of this WCRP research effort, led by WCRP's Core Project «Climate and Ocean Variability, Predictability and Change» (CLIVAR) as a Research Focus, is to establish a quantitative understanding of the natural and anthropogenic mechanisms of regional to local sea level variability; to promote advances in observing systems required for an integrated sea level monitoring; and to foster the development of sea level predictions and projections that are of increasing benefit for coastal zone Variability, Predictability and Change» (CLIVAR) as a Research Focus, is to establish a quantitative understanding of the natural and anthropogenic mechanisms of regional to local sea level variability; to promote advances in observing systems required for an integrated sea level monitoring; and to foster the development of sea level predictions and projections that are of increasing benefit for coastal zone variability; to promote advances in observing systems required for an integrated sea level monitoring; and to foster the development of sea level predictions and projections that are of increasing benefit for coastal zone management.

In order to use tidal gauges to reliably estimate global sea level changes, researchers have to successfully separate the components of shifting land heights and local sea level variability from any global trends.

The evolution of El Niño - Southern Oscillation (ENSO) variability can be characterized by various ocean - atmosphere feedbacks, for example, the influence of ENSO related sea surface temperature (SST) variability on the low - level wind and surface heat fluxes in the equatorial tropical Pacific, which in turn affects the evolution of the SST.

Its estimated ice volume and contribution to mean global sea level reside well within their ranges of natural variability, and from the current looks of things, they are not likely to depart from those ranges any time soon.

Its six chapters cover temperature assessment, precipitation assessment, large - scale climate variability modes and related oscillation indices, extreme events, climate and composition of the atmosphere and cryosphere and sea level.

variability of sea level pressure over the Pacific etc..

The combination of predicted astronomical tides with projected weather forcing, El Niño related variability, and secular SLR, gives a series of hourly sea level projections for 2005 — 2100.

The study demonstrates that observation - based interpretations, highlighting the role of winds in past regional sea level variability, are not inconsistent with the dominance of AMOC - associated changes in the 21st century.

J. T. Fasullo, R. S. Nerem & B. Hamlington Scientific Reports 6, Article number: 31245 (2016) doi: 10.1038 / srep31245 Download Citation Climate and Earth system modellingProjection and prediction Received: 13 April 2016 Accepted: 15 July 2016 Published online: 10 August 2016 Erratum: 10 November 2016 Updated online 10 November 2016 Abstract Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time.

At the core of the issue is the fact that, as far as we know, CO ₂ levels are currently very unusual for the Late Pleistocene, about twice the average, while temperatures, sea levels, and ice are within Holocene variability range.

A: «Internal variability versus anthropogenic forcing on sea level and its components» B: «The rate of sea - level rise» C: «Quantifying anthropogenic and natural contributions to thermosteric sea level rise» D: «Detection and attribution of global mean thermosteric sea level change» E: «Long - term sea level trends: Natural or anthropogenic?»

Abstract: «Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time.

Extending the sea level record back over the entire century suggests that the high variability in the rates of sea level change observed over the past 20 years were not particularly unusual.

Regionally, climate models underestimate the amount of sea level rise that occured, but do show reasonable agreement for interannual and multidecadal variability.

People are already experiencing the impacts of climate change through slow onset changes, for example sea level rise and greater variability in the seasonality of rainfall, and through extreme weather events, particularly extremes of heat, rainfall and coastal storm surges.

''... when correcting for interannual variability, the past decade's slowdown of the global mean sea level disappears, leading to a similar rate of sea - level rise (of 3.3 ± 0.4 mm yr − 1) during the first and second decade of the altimetry era.

Here we present an analysis based on sea - level data from the altimetry record of the past ~ 20 years that separates interannual natural variability in sea level from the longer - term change probably related to anthropogenic global warming.

Obviously you are not aware that the decadal variability of ENSO is not in synch with the PDO: The graph is from this post: http://bobtisdale.wordpress.com/2011/06/30/yet-even-more-discussions-about-the-pacific-decadal-oscillation-pdo/ The reasons for the differences are of course due to the influence of sea level pressure on the PDO.

«Here we present an analysis based on sea - level data from the altimetry record of the past ~ 20 years that separates interannual natural variability in sea level from the longer - term change probably related to anthropogenic global warming... Our results confirm the need for quantifying and further removing from the climate records the short - term natural climate variability if one wants to extract the global warming signal.»

Specifically, smoothing sea - level data (adjusting for natural variability of ENSO) over the past century fits most closely with a 4th degree polynomial model, and there has very likely not been any slowing in the longer - term background rate of sea level rise over the period of the tropospheric «pause».