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Why Seas Are Rising Ahead of Predictions
http://www.geosociety.org/news/pr/12-82.htm[font face=Serif][font size=5]Why Seas Are Rising Ahead of Predictions[/font]
[font size=4]GSA Annual Meeting Presentation: Could Estimates of the Rate of Future Sea-Level Rise Be Too Low?[/font]
[font size=3]Boulder, Colorado, USA - Sea levels are rising faster than expected from global warming, and University of Colorado geologist Bill Hay has a good idea why. The last official IPCC report in 2007 projected a global sea level rise between 0.2 and 0.5 meters by the year 2100. But current sea-level rise measurements meet or exceed the high end of that range and suggest a rise of one meter or more by the end of the century.
"What's missing from the models used to forecast sea-level rise are critical feedbacks that speed everything up," says Hay. He will be presenting some of these feedbacks in a talk on Sunday, 4 Nov., at the meeting of The Geological Society of America in Charlotte, North Carolina, USA.
...
"You can lose most of the Greenland ice cap in a few hundred years, not thousands, just under natural conditions," says Hay. "There's no telling how fast it can go with this spike of carbon dioxide we are adding to the atmosphere."
...
Hay notes, "Ten years ago we didn't know much about water under the Antarctic ice cap." But it is there, and it allows the ice to move -- in some places even uphill due to the weight of the ice above it.
...[/font][/font]
[font size=4]GSA Annual Meeting Presentation: Could Estimates of the Rate of Future Sea-Level Rise Be Too Low?[/font]
[font size=3]Boulder, Colorado, USA - Sea levels are rising faster than expected from global warming, and University of Colorado geologist Bill Hay has a good idea why. The last official IPCC report in 2007 projected a global sea level rise between 0.2 and 0.5 meters by the year 2100. But current sea-level rise measurements meet or exceed the high end of that range and suggest a rise of one meter or more by the end of the century.
"What's missing from the models used to forecast sea-level rise are critical feedbacks that speed everything up," says Hay. He will be presenting some of these feedbacks in a talk on Sunday, 4 Nov., at the meeting of The Geological Society of America in Charlotte, North Carolina, USA.
...
"You can lose most of the Greenland ice cap in a few hundred years, not thousands, just under natural conditions," says Hay. "There's no telling how fast it can go with this spike of carbon dioxide we are adding to the atmosphere."
...
Hay notes, "Ten years ago we didn't know much about water under the Antarctic ice cap." But it is there, and it allows the ice to move -- in some places even uphill due to the weight of the ice above it.
...[/font][/font]
21 replies
= new reply since forum marked as read
= new reply since forum marked as read
(That's called "Whistling past the graveyard"
to whistle past the graveyard
1. (idiomatic, US) To attempt to stay cheerful in a dire situation; to proceed with a task, ignoring an upcoming hazard, hoping for a good outcome.
2. (idiomatic, US) To enter a situation with little or no understanding of the possible consequences.
We have weather models, like the ones which attempted to predict the course of the storm. You may have seen maps with several possible trajectories (so called “spaghetti maps.”)
http://www.npr.org/2012/10/26/163725684/computers-pinch-of-art-aid-hurricane-forecasters
The various lines come from different models. Each model is an approximation, based on certain assumptions and parameters. At this time, it is impossible to precisely model the entire weather system, not even a single storm, like Sandy. Instead, forecasters look at the output from the various models and make their own best guess based upon them.
We also have climate models, which attempt to predict the climate moving forward. They don’t even attempt to predict individual storms like Sandy. Like weather models, climate models give us predictions, based on assumptions and parameters. They cannot hope to model the entire earth at extremely high precision. Instead, they use grids:
http://celebrating200years.noaa.gov/breakthroughs/climate_model/modeling_schematic.html
Like weather forecasters, climatologists generally look at the output of a number of models, to make predictions.
http://www.csa.com/discoveryguides/models/reviewf.php
[font face=Serif][font size=5]Climate Models in Action[/font]
[font size=3]As early as the 1960s the question of what rising levels of carbon dioxide might do to climate began to be raised. The best method to determine an answer was to be found in climate models with the aid of various types of proxy data, and with data collected from meteorological networks around the world.
As the leading climate change research group in the world, the Nobel Prize winning International Panel on Climate Change (IPCC), established in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP), places great emphasis on GCMs to forecast the possible changes caused by increased levels of carbon dioxide. The latest publication by the IPCC, the Fourth Assessment Report (AR4), outlines the improvements made to the more than 20 computer models since the Third Assessment Report (TAR) from 2001, and discusses in detail the results of the GCMs used in the experiments.
There were approximately 23 different models that were used in AR4 and all were evaluated extensively before inclusion in the report. In the evaluations, models are run for historical periods to assess their ability to simulate known conditions as well as climatic variability and extremes. In addition they are often compared against periods from the distant past to assess how they handle climates that are very different from today. To participate, models run specific experiments designed to assess how much influence CO2 has on global averaged temperatures, sea level, droughts, extreme temperatures, etc., for specific periods in the future. The results of all the models are then evaluated using several techniques, including looking at all of the results together and determining the "ensemble mean." That is, since it is difficult to determine which model performs best, the average of all of the models is taken for the most robust result.
…[/font][/font]
[font size=3]As early as the 1960s the question of what rising levels of carbon dioxide might do to climate began to be raised. The best method to determine an answer was to be found in climate models with the aid of various types of proxy data, and with data collected from meteorological networks around the world.
As the leading climate change research group in the world, the Nobel Prize winning International Panel on Climate Change (IPCC), established in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP), places great emphasis on GCMs to forecast the possible changes caused by increased levels of carbon dioxide. The latest publication by the IPCC, the Fourth Assessment Report (AR4), outlines the improvements made to the more than 20 computer models since the Third Assessment Report (TAR) from 2001, and discusses in detail the results of the GCMs used in the experiments.
There were approximately 23 different models that were used in AR4 and all were evaluated extensively before inclusion in the report. In the evaluations, models are run for historical periods to assess their ability to simulate known conditions as well as climatic variability and extremes. In addition they are often compared against periods from the distant past to assess how they handle climates that are very different from today. To participate, models run specific experiments designed to assess how much influence CO2 has on global averaged temperatures, sea level, droughts, extreme temperatures, etc., for specific periods in the future. The results of all the models are then evaluated using several techniques, including looking at all of the results together and determining the "ensemble mean." That is, since it is difficult to determine which model performs best, the average of all of the models is taken for the most robust result.
…[/font][/font]
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch8s8-8.html
[font face=Serif][font size=5]8.8 Representing the Global System with Simpler Models[/font]
[font size=4]8.8.1 Why Lower Complexity?[/font]
[font size=3]An important concept in climate system modelling is that of a spectrum of models of differing levels of complexity, each being optimum for answering specific questions. It is not meaningful to judge one level as being better or worse than another independently of the context of analysis. What is important is that each model be asked questions appropriate for its level of complexity and quality of its simulation.
The most comprehensive models available are AOGCMs. These models, which include more and more components of the climate system (see Section 8.2), are designed to provide the best representation of the system and its dynamics, thereby serving as the most realistic laboratory of nature. Their major limitation is their high computational cost. To date, unless modest-resolution models are executed on an exceptionally large-scale distributed computed system, as in the climateprediction.net project (http://climateprediction.net; Stainforth et al., 2005), only a limited number of multi-decadal experiments can be performed with AOGCMs, which hinders a systematic exploration of uncertainties in climate change projections and prevents studies of the long-term evolution of climate.
At the other end of the spectrum of climate system model complexity are the so-called simple climate models (see Harvey et al., 1997 for a review of these models). The most advanced simple climate models contain modules that calculate in a highly parametrized way (1) the abundances of atmospheric greenhouse gases for given future emissions, (2) the radiative forcing resulting from the modelled greenhouse gas concentrations and aerosol precursor emissions, (3) the global mean surface temperature response to the computed radiative forcing and (4) the global mean sea level rise due to thermal expansion of sea water and the response of glaciers and ice sheets. These models are much more computationally efficient than AOGCMs and thus can be utilised to investigate future climate change in response to a large number of different scenarios of greenhouse gas emissions. Uncertainties from the modules can also be concatenated, potentially allowing the climate and sea level results to be expressed as probabilistic distributions, which is harder to do with AOGCMs because of their computational expense. A characteristic of simple climate models is that climate sensitivity and other subsystem properties must be specified based on the results of AOGCMs or observations. Therefore, simple climate models can be tuned to individual AOGCMs and employed as a tool to emulate and extend their results (e.g., Cubasch et al., 2001; Raper et al., 2001). They are useful mainly for examining global-scale questions.
…
Earth System Models of Intermediate Complexity are reduced-resolution models that incorporate most of the processes represented by AOGCMs, albeit in a more parametrized form. They explicitly simulate the interactions between various components of the climate system. Similar to AOGCMs, but in contrast to simple climate models, the number of degrees of freedom of an EMIC exceeds the number of adjustable parameters by several orders of magnitude. However, these models are simple enough to permit climate simulations over several thousand of years or even glacial cycles (with a period of some 100 kyr), although not all are suitable for this purpose. Moreover, like simple climate models, EMICs can explore the parameter space with some completeness and are thus appropriate for assessing uncertainty. They can also be utilised to screen the phase space of climate or the history of climate in order to identify interesting time slices, thereby providing guidance for more detailed studies to be undertaken with AOGCMs. In addition, EMICs are invaluable tools for understanding large-scale processes and feedbacks acting within the climate system. Certainly, it would not be sensible to apply an EMIC to studies that require high spatial and temporal resolution. Furthermore, model assumptions and restrictions, hence the limit of applicability of individual EMICs, must be carefully studied. Some EMICs include a zonally averaged atmosphere or zonally averaged oceanic basins. In a number of EMICs, cloudiness and/or wind fields are prescribed and do not evolve with changing climate. In still other EMICs, the atmospheric synoptic variability is not resolved explicitly, but diagnosed by using a statistical-dynamical approach. A priori, it is not obvious how the reduction in resolution or dynamics/physics affects the simulated climate. As shown in Section 8.8.3 and in Chapters 6, 9 and 10, at large scales most EMIC results compare well with observational or proxy data and AOGCM results. Therefore, it is argued that there is a clear advantage in having available a spectrum of climate system models.[/font][/font]
[font size=4]8.8.1 Why Lower Complexity?[/font]
[font size=3]An important concept in climate system modelling is that of a spectrum of models of differing levels of complexity, each being optimum for answering specific questions. It is not meaningful to judge one level as being better or worse than another independently of the context of analysis. What is important is that each model be asked questions appropriate for its level of complexity and quality of its simulation.
The most comprehensive models available are AOGCMs. These models, which include more and more components of the climate system (see Section 8.2), are designed to provide the best representation of the system and its dynamics, thereby serving as the most realistic laboratory of nature. Their major limitation is their high computational cost. To date, unless modest-resolution models are executed on an exceptionally large-scale distributed computed system, as in the climateprediction.net project (http://climateprediction.net; Stainforth et al., 2005), only a limited number of multi-decadal experiments can be performed with AOGCMs, which hinders a systematic exploration of uncertainties in climate change projections and prevents studies of the long-term evolution of climate.
At the other end of the spectrum of climate system model complexity are the so-called simple climate models (see Harvey et al., 1997 for a review of these models). The most advanced simple climate models contain modules that calculate in a highly parametrized way (1) the abundances of atmospheric greenhouse gases for given future emissions, (2) the radiative forcing resulting from the modelled greenhouse gas concentrations and aerosol precursor emissions, (3) the global mean surface temperature response to the computed radiative forcing and (4) the global mean sea level rise due to thermal expansion of sea water and the response of glaciers and ice sheets. These models are much more computationally efficient than AOGCMs and thus can be utilised to investigate future climate change in response to a large number of different scenarios of greenhouse gas emissions. Uncertainties from the modules can also be concatenated, potentially allowing the climate and sea level results to be expressed as probabilistic distributions, which is harder to do with AOGCMs because of their computational expense. A characteristic of simple climate models is that climate sensitivity and other subsystem properties must be specified based on the results of AOGCMs or observations. Therefore, simple climate models can be tuned to individual AOGCMs and employed as a tool to emulate and extend their results (e.g., Cubasch et al., 2001; Raper et al., 2001). They are useful mainly for examining global-scale questions.
…
Earth System Models of Intermediate Complexity are reduced-resolution models that incorporate most of the processes represented by AOGCMs, albeit in a more parametrized form. They explicitly simulate the interactions between various components of the climate system. Similar to AOGCMs, but in contrast to simple climate models, the number of degrees of freedom of an EMIC exceeds the number of adjustable parameters by several orders of magnitude. However, these models are simple enough to permit climate simulations over several thousand of years or even glacial cycles (with a period of some 100 kyr), although not all are suitable for this purpose. Moreover, like simple climate models, EMICs can explore the parameter space with some completeness and are thus appropriate for assessing uncertainty. They can also be utilised to screen the phase space of climate or the history of climate in order to identify interesting time slices, thereby providing guidance for more detailed studies to be undertaken with AOGCMs. In addition, EMICs are invaluable tools for understanding large-scale processes and feedbacks acting within the climate system. Certainly, it would not be sensible to apply an EMIC to studies that require high spatial and temporal resolution. Furthermore, model assumptions and restrictions, hence the limit of applicability of individual EMICs, must be carefully studied. Some EMICs include a zonally averaged atmosphere or zonally averaged oceanic basins. In a number of EMICs, cloudiness and/or wind fields are prescribed and do not evolve with changing climate. In still other EMICs, the atmospheric synoptic variability is not resolved explicitly, but diagnosed by using a statistical-dynamical approach. A priori, it is not obvious how the reduction in resolution or dynamics/physics affects the simulated climate. As shown in Section 8.8.3 and in Chapters 6, 9 and 10, at large scales most EMIC results compare well with observational or proxy data and AOGCM results. Therefore, it is argued that there is a clear advantage in having available a spectrum of climate system models.[/font][/font]
http://www.ipcc.ch/publications_and_data/publications_and_data.shtml
See that step near the end? “Final distribution and Government Review of SPM”
http://scienceblogs.com/islandofdoubt/2007/04/06/ipcc-warning-read-with-caution-1/
See that step near the end? “Final distribution and Government Review of SPM”
http://scienceblogs.com/islandofdoubt/2007/04/06/ipcc-warning-read-with-caution-1/
[font face=Serif][font size=5]IPCC warning: read with caution[/font]
Posted by James Hrynyshyn on April 6, 2007
[font size=3]Before anyone reads the latest Intergovernmental Panel on Climate Change Report, the one released today on the impacts, there are a few things to keep in mind. Chief among them is the level of political interference in the final document. According to the AP
Posted by James Hrynyshyn on April 6, 2007
[font size=3]Before anyone reads the latest Intergovernmental Panel on Climate Change Report, the one released today on the impacts, there are a few things to keep in mind. Chief among them is the level of political interference in the final document. According to the AP
Several scientists objected to the editing of the final draft by government negotiators but in the end agreed to compromises. However, some scientists on the Intergovernmental Panel on Climate Change vowed never to take part in the process again.[/font][/font]
“The authors lost,” said one participant. “A lot of authors are not going to engage in the IPCC process any more. I have had it with them,” he said on condition of anonymity because the proceedings were supposed to remain confidential. An Associated Press reporter, however, witnessed part of the final meeting.
…
The United States, China and Saudi Arabia raised the many of the objections to the phrasing, often seeking to tone down the certainty of some of the more dire projections.
…
Above, I pointed out how weather models are used to predict the motion of a storm a few days in advance. Some models point one way, other models point another way.
When it comes to climate change, there are a range of predicted results, where, the most “optimistic” result shows us exceeding 2°C of warming by 2100 while the most pessimistic result shows us with much more warming than that.
http://commons.wikimedia.org/wiki/File:Global_Warming_Predictions.png
Even if the increase were slightly slower than the most optimistic result, 2°C will clearly be exceeded.
A growing body of evidence suggests that 2°C of warming, rather than being a safe limit, is actually too high.
http://www.nasa.gov/topics/earth/features/rapid-change-feature.html
[font face=Serif][font size=5]Paleoclimate Record Points Toward Potential Rapid Climate Changes[/font] 12.08.11
[font size=3]New research into the Earth's paleoclimate history by NASA's Goddard Institute for Space Studies director James E. Hansen suggests the potential for rapid climate changes this century, including multiple meters of sea level rise, if global warming is not abated.
By looking at how the Earth's climate responded to past natural changes, Hansen sought insight into a fundamental question raised by ongoing human-caused climate change: "What is the dangerous level of global warming?" Some international leaders have suggested a goal of limiting warming to 2 degrees Celsius from pre-industrial times in order to avert catastrophic change. But Hansen said at a press briefing at a meeting of the American Geophysical Union in San Francisco on Tues, Dec. 6, that warming of 2 degrees Celsius would lead to drastic changes, such as significant ice sheet loss in Greenland and Antarctica.
…
"The paleoclimate record reveals a more sensitive climate than thought, even as of a few years ago. Limiting human-caused warming to 2 degrees is not sufficient," Hansen said. "It would be a prescription for disaster."
…[/font][/font]
[font size=3]New research into the Earth's paleoclimate history by NASA's Goddard Institute for Space Studies director James E. Hansen suggests the potential for rapid climate changes this century, including multiple meters of sea level rise, if global warming is not abated.
By looking at how the Earth's climate responded to past natural changes, Hansen sought insight into a fundamental question raised by ongoing human-caused climate change: "What is the dangerous level of global warming?" Some international leaders have suggested a goal of limiting warming to 2 degrees Celsius from pre-industrial times in order to avert catastrophic change. But Hansen said at a press briefing at a meeting of the American Geophysical Union in San Francisco on Tues, Dec. 6, that warming of 2 degrees Celsius would lead to drastic changes, such as significant ice sheet loss in Greenland and Antarctica.
…
"The paleoclimate record reveals a more sensitive climate than thought, even as of a few years ago. Limiting human-caused warming to 2 degrees is not sufficient," Hansen said. "It would be a prescription for disaster."
…[/font][/font]
