Sentences with phrase «on sea ice trends»

In order to make improved projections, scientists are fine - tuning their understanding of the many influences on sea ice trends, including both manmade global warming and natural climate variability.

Not exact matches

Since at least 1979, Arctic sea ice has generally been on a downward slope, trending 4.5 percent lower per decade overall and 13.7 percent lower per decade during the September summer minimum.

The authors of a new study reviewing the volume data, detailed on Monday in the journal Nature Geoscience, are quick to caution, though, that one single year of rebound doesn't suggest any sea ice recovery, as the overall trend is still downward.

But as an explanation of what they're up to: «ICES 1999 Annual Science Conference CM 1999 / L: 19 Nordic Seas Exchanges The Deep Overflow through the Faroe Bank Channel» In this paper he doesn't make any firm commitment to trends, but notes «a slight indication of a decreasing trend in ISOW transport»; «as yet the ADCP measurements in the Faroe Bank Channel are of too short duration to allow any conclusions on this important question.»

IPCC / NSIDC trends [based on SIE sea ice extent] underestimate the real speed of ASI loss — true / false / maybe.

Those who think that there's nothing to worry about, because sea ice might recover on its own accord, are requiring some negative forcing or feedback effect to come into play, to make the PIOMAS trend line do a U-turn.

andy, from your above - referenced article on sea - ice trends: «But another factor was probably involved, one with roots going back to about 1989.

I recommend you check out my recent piece on sea - ice trends in Science Times.

However your comment on Maslowski has combined with my scanning the papers Hank linked to earlier in this thread; trend extrapolation using both PIOMAS and NPS are being used to assert that the Arctic is on a fast track to seasonally sea - ice free state.

[Andy Revkin — On Arctic ice trends, I have a post coming shortly on the latest update from the world's leading teams of sea ice experts, showing this year's retreat is unlikely to match last year's, while the long - term trend is still heading toward ever less summer icOn Arctic ice trends, I have a post coming shortly on the latest update from the world's leading teams of sea ice experts, showing this year's retreat is unlikely to match last year's, while the long - term trend is still heading toward ever less summer icon the latest update from the world's leading teams of sea ice experts, showing this year's retreat is unlikely to match last year's, while the long - term trend is still heading toward ever less summer ice.

On Mr. Will's defense of his accuracy, particularly on trends in sea ice at both poles as they related to global warming, it's worth pointing out a few thingOn Mr. Will's defense of his accuracy, particularly on trends in sea ice at both poles as they related to global warming, it's worth pointing out a few thingon trends in sea ice at both poles as they related to global warming, it's worth pointing out a few things.

It's also interesting to read the caution with which scientists discussed Arctic sea ice in this August 2000 NYT article — they clearly expect to see interannual variations superimposed on a longer - term trend.

Unfortunately, the tough scientific work to clarify ice and sea trends and dynamics has largely been obscured online by coverage focused on an error on Greenland ice loss that many polar scientists say made it into the new edition of the Times Comprehensive Atlas of the World (that's the British Times, just to be clear).

If you plot the average Arctic Sea Ice extent for 20 years, the you should also plot the monthly maximum and minimum values on the same figure so that we can get some perspective on where the 2007 and 2008 data falls in the context of annual variability, or examine for trends.

A significant northward trend (reduction of ice) in the winter - maximum ice edge is apparent, however, and appears to be caused by the gradual warming of sea - surface temperatures in the region (paper available on this if you want it).

The Arctic Climate Impact Assessment, the Intergovernmental Panel on Climate Change (whose reports are conservative by nature), and a range of other assessments all conclude with high confidence that — for better or worse — the long - term Arctic trend for summer sea ice is down, given the projected buildup of greenhouse gases and tendency of the Arctic to amplify warming.

So the main issue for me is that all «serious» studies show only «statistical trends» having some effects on some measurable quantities, (slight increase of average temperature, slight increase of sea level, slight decrease of northern, but not southern, sea ice,..)

You can find out more (and see links to my earlier coverage of Arctic sea - ice trends, and what's going on with sea ice at the other end of the planet) in my latest post on Dot Earth.

Published trends in peer - reviewed articles on Antarctic sea ice extent (all on annual average extent):

None of the sea - ice specialists I've interviewed since 2000 on Arctic trends ever predicted a straight - line path to an open - water Arctic, but quite a few have stressed the longstanding idea that as white ice retreats, solar energy that would have been reflected back into space is absorbed by the dark sea, with that heat then melting existing ice and shortening the winter frozen season.

Here's the global sea ice trend, combining what's going on up north and down south.

The sea ice grows and recedes with the seasons every year and has been on the decline since spring... and the overall trend over time is definitely downward.

Canadian Ice Service, 4.7, Multiple Methods As with CIS contributions in June 2009, 2010, and 2011, the 2012 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoIce Service, 4.7, Multiple Methods As with CIS contributions in June 2009, 2010, and 2011, the 2012 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoSea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoIce Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictosea ice predictoice predictors.

Individual responses continue to be based on a range of methods: statistical, numerical models, comparison with previous rates of sea ice loss, composites of several approaches, estimates based on various non sea ice datasets and trends, and subjective information (the heuristic category).

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.

Canadian Ice Service, 4.7 (+ / - 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoIce Service, 4.7 (+ / - 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoSea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictosea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictosea ice predictoice predictors.

Individual responses continue to be based on a range of methods: statistical, numerical models, comparison with previous rates of sea ice loss, estimates based on various non-sea ice datasets and trends, and subjective information (the «heuristic» category).

Most of the studies on the Arctic climate and ice trends cited to support the proposed listing assumed that the buildup of heat - trapping gases was probably contributing to the loss of sea ice, or that the continued buildup of these gases, left unchecked, could create ice - free Arctic summers later this century, and possibly in as little as three decades.

Generally yes, but there has been a lot of new information learned since the IPCC Third Assessment Report (e.g., on trends in hurricane intensity, the accelerated melting back of Arctic sea ice, the intensifying deterioration of the edges of the Greenland Ice Sheet, etc.) and Gore's presentation of the science has been updated to account for these, drawing from what are the really highly reviewed and high quality papers by leading scientisice, the intensifying deterioration of the edges of the Greenland Ice Sheet, etc.) and Gore's presentation of the science has been updated to account for these, drawing from what are the really highly reviewed and high quality papers by leading scientisIce Sheet, etc.) and Gore's presentation of the science has been updated to account for these, drawing from what are the really highly reviewed and high quality papers by leading scientists.

I argued that Greenland's glaciers would soon stabilize and sea ice in the Barents Sea would soon recover based on trends in the transport of warm Atlantic water into the Arctsea ice in the Barents Sea would soon recover based on trends in the transport of warm Atlantic water into the ArctSea would soon recover based on trends in the transport of warm Atlantic water into the Arctic.

Over the long - term, melting of the West Antarctic Ice Sheet could yield as much as 10 to 14 feet of global average sea level rise, with local sea level rise varying considerably depending on land elevation trends, ocean currents and other factors.

But on the contrary, the Southern Ocean has warmed by around 0.5 °C in the three decades since satellites began measuring sea ice trends.

That's consistent with other research on longer term trends in Greenland ice, and how these trends contribute to sea level rise.

Since current ice melt data could indicate variable climate trends and aren't necessarily part of an accelerating trend, the study warned that predictions of future sea - level rise should not be based on measurements of glacial loss» Daily Mail.

ocean temperatures, widespread melting of snow and ice, and rising global average sea level,» are three disjoint sources of confirmation that give us reliable enough trend information to establish consilience about what we may say after 2005 on HadCRUT4.

As of this writing, there is observational and modeling evidence that: 1) both annular modes are sensitive to month - to - month and year - to - year variability in the stratospheric flow (see section on Stratosphere / troposphere coupling, below); 2) both annular modes have exhibited long term trends which may reflect the impact of stratospheric ozone depletion and / or increased greenhouse gases (see section on Climate Change, below); and 3) the NAM responds to changes in the distribution of sea - ice over the North Atlantic sector.

These regional trends together yield a small increase, so studying each region will help scientists get a better grasp on the processes affecting sea ice there.

-- and if not, how can one zero in on an effect like trends in the amount of sea ice?

RCP 2.6 and a realistic model based on past sea ice extent and its relationship to AMO are indistinguishable and do not anticipate an Arctic free of ice within the 21st century if current trends are maintained.

Canadian Ice Service; 5.0; Statistical As with Canadian Ice Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictoIce Service; 5.0; Statistical As with Canadian Ice Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictoIce Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictoIce (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictoSea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictoIce Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictosea ice predictoice predictors.

Is there a reason why a linear trend is shown for the NH sea ice extent, where a second order polynomial fit trend is shown on the Arctic Sea Ice Escalator graphsea ice extent, where a second order polynomial fit trend is shown on the Arctic Sea Ice Escalator graphice extent, where a second order polynomial fit trend is shown on the Arctic Sea Ice Escalator graphSea Ice Escalator graphIce Escalator graphic?

This assessment is based on a subset of models that most closely reproduce the climatological mean state and 1979 to 2012 trend of Arctic sea ice cover.

2012's sea ice area and extent were already trending low this year, but damage done to the thin and low concentration of ice by this storm almost ensures that 2012 will eclipse 2007 in all categories as the lowest sea ice on record by the time the September low is set.

Not only does this low - pressure area, or cyclone, look bigger, more intense and longer - lasting than the one from last year, the ice also seems to be in a weaker state than ever, as evidenced by the fact that 2012 trend lines on both sea ice area and sea ice extent graphs track lower than previous record years, despite weather that until recently would completely stall the decline.

As for Antarctic sea ice, that's very interesting and very likely related to the wind trends and their effect on the polar gyres.

Since the tropical oceans have flattened out and solar does have its largest impact on the tropical oceans, I would expect about the same possibly some increase in Arctic sea ice over the next decade Not a consistent increase by any means, but I doubt it will make it to the 2 mkm ^ 2 and will trend towards a 6 million km ^ 2 average which is hardly «ice free».

IPCC synthesis reports offer conservative projections of sea level increase based on assumptions about future behavior of ice sheets and glaciers, leading to estimates of sea level roughly following a linear upward trend mimicking that of recent decades.

``... examination of records of fast ice thickness and ice extent from four Arctic marginal seas (Kara, Laptev, East Siberian, and Chukchi) indicates that long - term trends are small and generally statistically insignificant, while trends for shorter records are not indicative of the long - term tendencies due to strong low - frequency variability in these time series, which places a strong limitation on our ability to resolve long - term trends....

Stern: My estimate for September average sea ice extent (4.67 million square kilometers) was simply based on extrapolation of the 10 - year trend (1989 - 2008).

Actually Fielding's use of that graph is quite informative of how denialist arguments are framed — the selected bit of a selected graph (and don't mention the fastest warming region on the planet being left out of that data set), or the complete passing over of short term variability vs longer term trends, or the other measures and indicators of climate change from ocean heat content and sea levels to changes in ice sheets and minimum sea ice levels, or the passing over of issues like lag time between emissions and effects on temperatures... etc..