Sentences with phrase «large scale variability»

Not exact matches

Specifically designed to have two generous sizes, the Thirsties Duo All In One Diaper offers the same variability as a one size diaper system, as well as a more comfortable, snugger, leakproof fit for babies on both sides of the size scale; Thirsties will fit a tiny newborn, as well as a much larger, potty training Toddler.

This variability from site to site and state to state inspired the research team to conduct this study on a much larger scale.

Lozier (p. 1507) discusses how recent studies have challenged our view of large - scale ocean circulation as a simple conveyor belt, by revealing a more complex and nuanced system that reflects the effects of ocean eddies and surface atmospheric winds on the structure and variability of the ocean's overturning.

This was enabled by creating autonomous robots designed to operate in large groups and to cooperate through local interactions and by developing a collective algorithm for shape formation that is highly robust to the variability and error characteristic of large - scale decentralized systems.

However, the devices still can not be fabricated with low variability and low spread of electronic properties as required for large scale production.

«Africa has the greatest amount of phenotypic variability in skin color, and yet it's been underrepresented in large scale endeavors,» said Alicia Martin, a postdoctoral scientist in the lab of Broad Institute member Mark Daly.

By leading to variability in the density and size of trees that grow during recovery, large fires reduce the future vulnerability of forests to bark beetle attacks and broad - scale outbreaks.

«When we see variability on such a large scale, we should worry that some people are not getting the best, most appropriate treatment.»

Nonetheless, even if the substantial recent trend in the AO pattern is simply a product of natural multidecadal variability in North Atlantic climate, it underscores the fact that western and southern Greenland is an extremely poor place to look, from a signal vs. noise point of view, for the large - scale polar amplification signature of anthropogenic surface warming.

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.

While this leads to an elevation in the level of scientific understanding from very low in the TAR to low in this assessment, uncertainties remain large because of the lack of direct observations and incomplete understanding of solar variability mechanisms over long time scales.»

On decadal time scales, annual streamflow variation and precipitation are driven by large - scale patterns of climate variability, such as the Pacific Decadal Oscillation (see teleconnections description in Climate chapter)(Pederson et al. 2011a; Seager and Hoerling 2014).

Large scale genomic and transcriptomic interrogation of cancer has confirmed the incredible variability of the genomic landscape of many tumors including hepatocellular carcinoma (HCC), in which more than 28,000 different somatic mutations have been identified.

Furthermore, since the end of the 19th century, we find an increasing variance in multidecadal hydroclimatic winter and spring, and this coincides with an increase in the multidecadal North Atlantic Oscillation (NAO) variability, suggesting a significant influence of large - scale atmospheric circulation patterns.

Jiacan has worked on several projects on climate dynamics, including the response of large - scale circulations in the warming climate, its effects on regional weather patterns and extreme events, tropical influence on mid-latitude weather, and dynamical mechanisms of sub-seasonal variability of mid-latitude jet streams.

Spectral analyses suggested that the reconstructed annual mean temperature variation may be related to large - scale atmospheric — oceanic variability such as the solar activity, Pacific Decadal Oscillation (PDO) and El Niño — Southern Oscillation (ENSO).

In this region, much of the year - to - year temperature variability is associated with the leading mode of large - scale circulation variability in the North Atlantic, namely, the North Atlantic Oscillation.

Tompkins, A., 2002: A prognostic parameterization for the subgrid - scale variability of water vapor and clouds in large - scale models and its use to diagnose cloud cover.

However, the large - scale nature of heat content variability, the similarity of the Levitus et al. (2005a) and the Ishii et al. (2006) analyses and new results showing a decrease in the global heat content in a period with much better data coverage (Lyman et al., 2006), gives confidence that there is substantial inter-decadal variability in global ocean heat content.

In sharp contrast, model simulations of internal and total natural variability can not produce the same sustained, large - scale warming of the troposphere and cooling of the stratosphere.

The upper tail is particularly long in studies using diagnostics based on large - scale mean data because separation of the greenhouse gas response from that to aerosols or climate variability is more difficult with such diagnostics (Andronova and Schlesinger, 2001; Gregory et al., 2002a; Knutti et al., 2002, 2003).

It is, however, the variability on large scales influenced by interactions of the atmosphere with other components of the climate system that is predictable.

That happens to coincide with the region where the largest waves in the atmosphere (called Rossby waves) propagate, so therefore snow cover variability can have a direct impact and those waves, which dominate the large - scale atmospheric circulation.

And since key aspects of those large - scale scenarios as far as Atlantic TC activity is concerned (i.e. what really happens to the ENSO mean state and amplitude of variability) are currently not confidently known, neither can we be confident using the model projections to say what will happen to Atlantic TC activity in the future.

Patterns of variability that don't match the predicted fingerprints from the examined drivers (the «residuals») can be large — especially on short - time scales, and look in most cases like the modes of internal variability that we've been used to; ENSO / PDO, the North Atlantic multidecadal oscillation etc..

But tremendous natural variability occurs in the large - scale atmospheric circulation during all seasons, and even in summer the links between Arctic warming and mid-latitude weather are not supported by other observational studies.

Nonetheless, even if the substantial recent trend in the AO pattern is simply a product of natural multidecadal variability in North Atlantic climate, it underscores the fact that western and southern Greenland is an extremely poor place to look, from a signal vs. noise point of view, for the large - scale polar amplification signature of anthropogenic surface warming.

The trees are often very closely located and so it makes sense to summarize the general information they all contain in relation to the large - scale patterns of variability.

It is quite clear that the perturbation that we are currently imposing is already large, and will be substantially larger, by up to an order of magnitude, than any plausible natural variability over this time scale.

The study demonstrates the importance of understanding how climate variability on a regional scale may at least temporarily obscure larger forces acting on the global climate system.

This in turn can have had a number of possible causes: «natural» tropical variability — for instance, the winter (DJF) tropical Pacific cooled over these two years, possibly as part of larger - scale ENSO variability.

While this leads to an elevation in the level of scientific understanding from very low in the TAR to low in this assessment, uncertainties remain large because of the lack of direct observations and incomplete understanding of solar variability mechanisms over long time scales.»

Either there's a large decadal - scale internal variability driving it, such as a large pseudo-cyclical increase in deepwater formation, or the Arctic Ocean is near marginal stability under perturbation.

While rereading the ocean heat content changes by Levitus 2005 at http://www.nodc.noaa.gov/OC5/PDF/PAPERS/grlheat05.pdf a remarkable sentence was noticed: «However, the large decrease in ocean heat content starting around 1980 suggests that internal variability of the Earth system significantly affects Earth's heat balance on decadal time - scales.»

So: The study finds a fingerprint of anthropogenic influences on large scale increase in precipitation extremes, with remaining uncertainties — namely that there is still a possibility that the widespread increase in heavy precipitation could be due to an unusual event of natural variability.The intensification of extreme rainfall is expected with warming, and there is a clear physical mechanism for it, but it is never possible to completely separate a signal of external forcing from climate variability — the separation will always be statistical in nature.

The paper... offers a useful framework for which decadal variations in the global (or northern hemisphere) may be explained via large scale modes of oceanic variability.

Indeed, the very strong interannual variability of global hurricane ACE (energy) highly correlated to ENSO, suggests that the role of tropical cyclones in climate is modulated very strongly by the big movers and shakers in large - scale, global climate.

The available data are insufficient to say if the changes in O2 are caused by natural variability or are trends that are likely to persist in the future, but they do indicate that large - scale changes in ocean physics influence natural biogeochemical cycles, and thus the cycles of O2 and CO2 are likely to undergo changes if ocean circulation changes persist in the future.

Attribution of the observed warming to anthropogenic forcing is easier at larger scales because averaging over larger regions reduces the natural variability more, making it easier to distinguish between changes expected from different external forcings, or between external forcing and climate variability.

We present a large - scale Southern Ocean observational analysis that examines the seasonal magnitude and variability CO32 − and pH. Our analysis shows an intense wintertime minimum in CO32 − south of the Antarctic Polar Front and when combined with anthropogenic CO2 uptake is likely to induce aragonite undersaturation when atmospheric CO2 levels reach ≈ 450 ppm.»

Most authors identify government practices as being far more influential drivers than climate variability, noting also that similar changes in climate did not stimulate conflicts of the same magnitude in neighboring regions, and that in the past people in Darfur were able to cope with climate variability in ways that avoided large scale violence.

The current lack of consistency between various data sets makes it difficult, based on current knowledge, to attribute the millennial time scale large - scale climate variations to external forcings (solar activity, episodes of intense volcanism), or to variability internal to the climate system.

They gather the control simulations from 14 models together into one pot and decompose the variability into patterns, isolating that pattern whose time series has the largest integral time scale (or decorrelation time).

It is interesting that the North Atlantic does not play a more important role in this largest - trend case, since it does dominate the oceanic variability on somewhat shorter ~ 20 year time scales in this model.

Overview of the tropical atmosphere, monsoons, intraseasonal variability, hurricanes, theory of tropical convection and the large - scale circulation

«Our analysis shows warming underway by 1800, large variations up and down throughout the 19th century, and that variability on the 3 - 15 year scale has been dramatically decreasing over the past two centuries.»

Several ideas have been put forward to explain this hiatus, including what the IPCC refers to as «unpredictable climate variability» that is associated with large - scale circulation regimes in the atmosphere and ocean.

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.

The calibration step is not to some amorphous «large scale pattern of climate variability» (whatever that means); the calibration is to temperature.

This has been difficult to confirm observationally because of the high spatial variability of RS, inaccessibility of the soil medium and the inability of remote - sensing instruments to measure RS on large scales.