There's a problem in all of the climate predictions people have made over the last few years - we just don't know who to trust. Some experts remind us that since we can't predict the weather more than 10 days from now making economy-shattering policy decisions on such incomplete science is a bad idea. One prominent politician says he took a random sample of all the climate studies out there and that 928 out of 12,000 articles agreed with him, so he must be right. How are we to know?
Global warming is more politics than science and I don't want to get into whether it is happening or not, or how much, because that's not science, it's advocacy no matter what I say. The operative question is, how do we make it complete science?
This article from a national lab says climate models are accurate while another national lab says they've found a way to finally make climate models accurate.
Who's right? The worst person to ask may be a climate scientist.
Why so? We wouldn't go to a tobacco company employee to get objective information on cigarettes or an Exxon employee to get information on pollution so it doesn't seem to make sense to rely exclusively on researchers getting paid to investigate global warming.
The climate has varied a lot over millions of years, sometimes wildly. During the last 300 million years, atmospheric carbon dioxide levels have swung back and forth from 250 parts per million, about what they are today, to more than 2,000 parts per million.
So if scientists take a 50 million year range and 500 data points in that time, where they pick them is not only important, it's absolutely essential to know which ones they picked and why.
Almost no one would take scientific data at face value without asking who was making the analysis and where they got funding yet it seems to happen with climate studies all of the time. A scientist accepting a grant from Union of Concerned Scientists may not be dishonest, any more than a scientist getting a grant from Exxon is dishonest, but neither of those corporations are funding work they dislike. Union of Concerned Scientists alone spends $12 million per year talking about the consensus on global warming. That's real money.
Conservative websites and individual science writers have plenty to say about the flaws in climate science but where do we go to get answers free of bias?
The answer is calibration. Unfortunately we can't do calibration for ancient periods but we can do it for modern times and, provided the researchers aren't tweaking the algorithm to match the data, it can show us if we are on the right path.
Computer scientists at Oak Ridge National Lab think they have a way to create an accurate model and it can be used for in estimates of water resources, hydrologic sciences, climate science and ecology.
They used extremes in real data from between 1940 and 2005 and combined them with numerical tools so they could determine how climate models fared when compared to actual observations.
“Once we understand the nature of these connections our hope is that we will be able to determine if there is a relation between two extreme weather events – like heat waves and droughts,” said Auroop Ganguly, a member of the ORNL Computational Sciences and Engineering Division. “We may then be able to determine whether there will be more intense storms, hurricanes or floods, and this information could perhaps be used as an early warning tool or to help develop policies.”
Let's hope so. Everyone agrees the environment is important. Everyone agrees we are warmer. The 'why' of that warmth is the question of the decade and objective, scientific answers to that question could be the most important research of this century.
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Georg von Hippel | 07/01/07 | 16:51 PM
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The IPCC stated that they didn't understand 6 of the 9 factors in global warming. If we don't even understand the impact of 66% of the factors, we have a science problem to deal with before we impose solutions.
Methane is 20X the warming effect of CO2 and a cow puts out enough to fill a hot air balloon each year but the French, who subsidize each cow by $900 to keep farmers happy, didn't think methane was the problem - that is suspicious. Likewise the Germans cut a few Soviet factories and met the convenient Kyoto CO2 target date (right after the merger with East Germany) easily, but they couldn't have done it if the focus had not been CO2 or that target date in Kyoto had been a few months earlier.
So we should worry about greenhouse gases but we should be making cuts based on science, not global politics and competition. Until the modelling is solid, we could be making changes and still have global warming increasing.
Cash S | 07/01/07 | 18:05 PM
But the crux of the issue is indeed which greenhouse agent gets blamed.
If the fault is with CO2 and we're supposed to expect drastic climate change then society has to work to mitigate CO2.
If on the other hand if CO2-driven warming is leveling off to a modest level and the more pernicous ice-melting and air-cooking heating agent is soot, and it's easier to mitigate soot, then we can tackle industrial and deisel soot emissions at far lower costs while we ease into a low-carbon culture.
And FWIW, atmospheric methane levels are falling which is unexpected.
Lee Rodgers | 04/09/08 | 10:44 AM
Ray Kurzweil has pointed out that computer modeling should evolve away from equation-based data processing and more into modeling discrete automata, or cell-based processing units that describe a functional spatial area with known properties (much the way that fluid dynamic modeling is done now).
Current General Circulation Models (aka climate models) are a mix of both, applying a mixture of known formulas across a global dataset with limited granularity in terms of altitude (atmospheric strata), conditions (clouds, moisture, temperature) and region.
The problem here is computational power, the limits of existing models and the relative state of the science as a whole. It is generally agreed that clouds are poorly modeled and it will require far more field data to shore up cloud models. Up until recently airborne soot was poorly modeled until field data demonstrated tropospheric soot actually has a net heating effect that exceeds its shading effect. Likewise for land use and ocean subvection/circulation and dust clouds. And again, recent field data on windborne dust has shown that the models weren't just off by some margin -- the models were completely wrong.
There's a trend here, it's called SCIENCE. The progress of any science evolves with empirical study based on real field data. There's no replacement for it and computer models are no better than the supporting field data.
As for the most profound piece of field data, global temperatures have roughly stabilized since the 1998 el Nino. This was unexpected and the warming models didn't initially anticipate such a long interregnum in temperature rise. The simplest model, however, is generally accepted, that a doubling of CO2 would cause a 1 degree C rise in temperatures. The existing observed temperature trend fits most closely with the simple CO2 case. That is, we are 3/4's of the way to doubling of CO2 levels and the trend shows a 0.7 Celsius increase in global temperatures.
This means that the computer models that predict a 3 - 4 degree C temperature increase haven't predicted the current, flatter, cooler (or should I say "less warm" ;-) trend of THE PAST TEN YEARS. These models are intentionally constructed with vapor feedback loops that model cross-band IR transfer between CO2 and water vapor. Such IR band transfer may exist but it isn't tripling CO2's known effect on a global scale. Either some mitigating factor is missing from the climate models or the actual feedback loops aren't as pronounced.
Again, we're 3/4's of the way to doubling CO2 concentrations and we've yet to see anything like a 3 - 4 degree C increase in temperatures. In fact we're seeing a modest warming only slightly above the known 1 degree C. effect of CO2. Further increases of CO2 concentration will yield less and less additional warming because CO2's heat-trapping capacity is inversely logarithmic -- that is another doubling of CO2 would only cause a 0.5 C temperature rise, another doubling would only contribute a 0.25 C temperature rise and so on.
I think the answer to your quest for better climate models is: "More field data please."
Lee Rodgers | 04/09/08 | 10:36 AM
Speaking of field data vs. models:
http://www.uah.edu/News/pdf/climatemodel.pdf
"...We examine ... 20th Century ... model simulations and try to reconcile them with ... observations (in the tropics during the satellite era). ... Model results and observed temperature trends are in disagreement ... separated by more than twice the uncertainty of the model mean ... above 8 km, modelled and observed trends have opposite signs."
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From a report by the US Climate Change Science Program (CCSP, 2006):
“For longer-timescale temperature changes over 1979 to 1999, only one of four observed upper-air data sets has larger tropical warming aloft than in the surface records. All model runs with surface warming over this period show amplified warming aloft.
“These results could arise due to errors common to all models; to significant non-climatic influences remaining within some or all of the observational data sets, leading to biased long-term trend estimates; or a combination of these factors. The new evidence in this Report (model-to-model consistency of amplification results, the large uncertainties in observed tropospheric temperature trends, and independent physical evidence supporting substantial tropospheric warming) favors the second explanation.
“A full resolution of this issue will require reducing the large observational uncertainties that currently exist. These uncertainties make it difficult to determine whether models still have common, fundamental errors in their representation of the vertical structure of atmospheric temperature change.”
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Likewise Christopher Monkton delivered this presentation at the Bali conference:
http://scienceandpublicpolicy.org/monckton_papers/greenhouse_warming_wha...
The significant shortfall between the magnitude of modeled and observed altitude-vs-latitude trends of decadal temperature increase in the tropics. Prediction and observation overlap only in the first mile of the atmosphere, demonstrating that the observed temperature forcing by anthropogenic greenhouse-gas emissions is considerably less than the forcing predicted by the models and accepted by the IPCC.
The 20-model mean predicted temperature trend (heavy red curve) ± 1 standard deviation (thin red curves) is plotted against observations from RSS 2.1 (yellow triangles); the University of Alabama at Huntsville’s UAH 5.2 (yellow diamonds) Hadley Centre’s AT2 (green curve); IGRA (light blue curve); RATPAC (dark blue curve); and Global Historical Climate Network surface trend (blue square) (Douglass et al., 2007).
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It doesn't help the credibility of IPCC climatologists when they dismiss imporant new studies out of hand. Nor are they discussing the portentous signs that solar cycle #25 may signal the onset of a solar grand minimum. This is because their bias is toward atmospheric chemistry, not exogenic drivers like long-term solar luminence.
There are signs that the sun's activity is slowing. Decreased solar wind speeds and slowed sunspot movement are amongst the indicators that the sun's magnetic dynamo is slowing. This is consistent with weaker solar cycles and perhaps a solar grand minimum of 4 or 5 weak solar cycles.
One paper by Penn & Livingstonin in 2006 concludes: 'If [trends] continue to decrease at the current rate then the number of sunspots in the next solar cycle (cycle 24) would be reduced by roughly half, and there would be very few sunspots visible on the disk during cycle 25.'
Also:
http://www.physorg.com/news66581392.html
"...The slowdown we see now means that Solar Cycle 25, peaking around the year 2022, could be one of the weakest in centuries," says Hathaway..."
"...If the trend holds, Solar Cycle 25 in 2022 could be, like the belt itself, "off the bottom of the charts."
And:
Landscheidt solar cycle theory projected that roughly every 180 years the sun enters into a long-term slump in solar activity and overall luminance, cooling the Earth. The sun's overdue for a multi-decade slacking in solar activity like the Dalton minimum, and even overdue for a an even-broader minumum akin to the Maunder. According to Landscheidt's model the ending Cycle 23's minimum should have ended a year or two earlier. But it didn't, it stalled and only now is Cycle 24 ramping up (slowly). Other solar models indicate similar trends.
This delay may be the prelude to a new broader, multi-decade minimum phase that would fully commence within the next 15 years. The resulting "grand minimum" could entail 4 or 5 very weak sunspot cycles akin to the Maunder Minimum of the Elizabethan Miniature Ice Age.
NASA/GISS researchers have modeled the effects of a long-term solar grand minimum and concluded it would precipitate another miniature ice age:
http://www.giss.nasa.gov/research/news/20011206/
http://www.giss.nasa.gov/research/briefs/shindell_06/
Lee Rodgers | 04/09/08 | 12:37 PM
