Sentences with phrase «predictions of future ice»

Insight into past ice - sheet behaviour also will aid predictions of future ice - sheet stability.

I also believe that the prediction of future ice states in the Arctic is not possible in any meaningful sense.

Not exact matches

This gives confidence in the predictions of the current generation of ice - sheet models which are used to forecast future ice loss from Antarctica and resulting sea - level rise.»

The next step is to use estimates of future sea ice loss to make predictions of how further melting could influence summer rainfall in Europe in the years to come.

The paleoclimate data, which included mainly changes in the oxygen isotopes of the calcium carbonate deposits, were then compared to similar records from other caves, ice cores, and sediment records as well as model predictions for water availability in the Middle East and west central Asia today and into the future.

Kuhn, from Germany's Alfred Wegener Institute, added, «This gives confidence in the predictions of the current generation of ice sheet models which are used to forecast future ice loss from Antarctica and resulting sea - level rise.»

In no models or predictions of future warming scenarios does the Antarctic ice mass melt to any significant extent.

In no models or predictions of future warming scenarios does the Antarctic ice mass melt to any significant extent.

Does this mean that the predictions of Antarctic ice melting derive from future projections of global temperature increase, and not from existing ice data?

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 predictoIce Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice predictors.

I suspect that it looked OK in your view or you didn't check; «the paper i cited talks of the hiatus in global temperatures for the past 20 years or so, that the Little Ice Age was global in extent, and that climate models can not account for the observations we already have let alone make adequate predictions about what will happen in the future.

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 predictoice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice predictors.

There are many who will not like this recent paper published in Nature Communications on principle as it talks of the hiatus in global temperatures for the past 20 years or so, that the Little Ice Age was global in extent, and that climate models can not account for the observations we already have let alone make adequate predictions about what will happen in the future.

Studies of this kind, which explore the ice sheet's past behavior, are critical to developing better predictions of how it will evolve in the future, Csatho says.

Scientists are interested in how the shape of this hidden terrain affects how ice moves — a key factor in making predictions about the future of...

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.

Yet some kind of climate model is indispensable to make future predictions of the climate system and IPCC has identified several reasons for respect in the climate models including the fact that models are getting better in predicting what monitoring evidence is actually observing around the world in regard to temperature, ice and snow cover, droughts and floods, and sea level rise among other things.

This has several implications for predictions of future sea ice decline.

If they do so by simulating near - average conditions most of the time, they are getting the right answer for the wrong reason, and their predictions of future sea ice decline should be discounted.

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 predictoIce Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictoice predictors.

However, initialized prediction ensembles using CESM can skillfully predict low - frequency modulations in the decadal trends of Arctic sea ice, and the significant skill scores for Atlantic sector sea ice extent, in particular, suggest that CESM DP future forecasts merit serious consideration.

These new sea ice proxy records are needed (1) to fully prove the scenarios of a succession from an extended ice shelf to polynya / open - water conditions (cf., Fig. 6), (2) to reconstruct in more detail the changes in sea ice cover for early, middle and late LIG intervals characterized by very different external forcings and related internal feedback mechanisms, and (3) to allow a more fundamental proxy data / modeling comparison that results in model improvements and better reproduction of the LIG climatic evolution and prediction of future climatic scenarios20, 21,22,23, 64.

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 predictoice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictoice predictors.

As with previous CIS contributions, the 2016 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness / extent, as well as winter surface air temperature, spring ice conditions and the summer temperature forecast; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent time - series into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

The Mercer (1978) ``... a threat of disaster» paper introduced above was fraught with presumptions, guesswork, and spectacularly wrong predictions about the connections between fossil fuel consumption by humans and future carbon dioxide (CO2) parts per million (ppm) concentrations, the melting of polar ice sheets, and an impeding sea level rise disaster.

It regurgitates NSIDC graphs, complete with lines of best fit that reveal the underlying downward trend towards inevitable oblivion, without wondering why scientific predictions from the NSIDC and elsewhere about the future of Arctic ice are spread across a whole continent of ball parks each the size of Wales.

I think the projections for decades into the future will prove as sound as Malthus» projections, the great whale oil crisis of the mid-19th century, the terrible horse manure health crisis projected for cities in the early 20th century, Paul Ehrlich's predictions of doom, and the disappearance of snow and ice in the world that plagues us in 2015.

The first is that the doomsday scenario for polar bears comes, not from real - world observation but from computer - modeled predictions of what might happen in the future if the ice caps melt, etc..

That paper, which was not peer - reviewed, argued that because polar bear numbers have remained relatively stable despite faster - than - expected sea ice loss over the past decade, scientists» predictions of future population declines are flawed.

Predictions of future sea - level rise and reduction in volume of ice sheets are consistent with what the evidence indicates during the Last Interglacial.

Dr. Alley teaches, and conducts research on the climatic records, flow behavior, and sedimentary deposits of large ice sheets, to aid in prediction of future changes in climate and sea level.

13) The inability of climate models to adequately reproduce the recent states and trends of Arctic sea ice diminishes confidence in their accuracy for making future climate predictions.

Information about the melting of Arctic ice can be overwhelming, especially when trying to grasp everything from how it is measured to the impacts of ice - free summers in the Arctic to predictions about future ice melts.

Retrospective analysis and future prediction of the arctic sea ice system (Jinlun Zhang, D. Andrew Rothrock, and Michael Steele; Applied Physics Laboratory) http://psc.apl.washington.edu/zhang/IDAO/index.html

However, new research incorporating additional information, such as the fraction of ice covered by melt ponds in the spring, shows promise for improved future predictions (Schroder et al. 2014).

Indeed, working with predictions for future temperature increases and glacier melt rates generated by ten separate global climate models — all of which are also used by the Intergovernmental Panel of Climate Change - the team have concluded that these smaller ice sources will contribute around 12 centimetres to world sea - level increases over the remainder of the century, with this likely to have catastrophic consequences for numerous natural habitats as well as for hundreds of thousands of people.

It's a finding that should be reflected in current climate models to help scientists make more accurate predictions about future Greenland melt — and could become even more important in the coming years if cloud cover over the ice sheet were to increase as a result of climate change.