Its not. Its mostly observations and basic physics.
" the close match between projected and observed warming since 1970 suggests that estimates of future warming may prove similarly accurate."
CLIMATE PREDICTIONS HAVE BEEN VERY ACCURATE:
NASA scientist Gavin Schmidt:
Factcheck: Climate models have not 'exaggerated' global warming
Here are some actual predictions from Global Climate Models all of which have proven correct. Im even linking to the paper directly so you can go and read for yourself.
- - That the Earth would warm, and about how fast, and about how much
(Arrhenius 1896, Callendar 1938, Plass 1956, Sawyer 1972, Broecker 1975; validated by Crowley 2000, Philipona et al 2004, Evans and Puckrin 2006, Lean and Rind 2008, Mann et al. 2008, etc) - - That nighttime temperatures would increase more than daytime temperatures
(Arrhenius 1896; validated by Dai et al. 1999, Sherwood et al. 2005, etc) - - That winter temperatures would increase more than summer temperatures
(Arrhenius 1896, Manabe and Stouffer 1980, Rind et al 1989; validated by Balling et al 1999, Volodin and Galin 1999, Crozier 2003, etc) - - Polar amplification (that temperatures increase more as you move toward the poles)
(Arrhenius 1896, Manabe and Stouffer 1980; validated by Polyakov et al 2001, Holland and Bitz 2003, etc) - - That the Arctic would warm faster than the Antarctic
(Arrhenius 1896, Manabe and Stouffer 1980; validated by Doran et al 2002, Comisa 2003, Turner et al 2007, etc) - - That the Earth’s troposphere would warm and the stratosphere would cool
(Manabe and Wetherald 1967, Manabe and Stouffer 1980; validated by Ramaswamy et al. 1996, 2006, De F. Forster et al 1999, Langematz et al 2003, Vinnikov and Grody 2003, Fu et al 2004, Thompson and Solomon 2005, etc) - - The near constancy of relative humidity on global average
(Manabe and Wetherall 1967; validated by Minschwaner and Dessler 2004, Soden et al 2005, Gettelman and Fu 2008, etc) - - Scientists made a retrodiction (a model prediction based on established physics) for Last Glacial Maximum sea surface temperatures which was inconsistent with the paleo evidence for those times; better paleo evidence showed the models were right
(Rind and Peteet 1985; validated by Farreral et al 1999, Melanda et al 2005, etc) - - The clear sky super greenhouse effect from increased water vapor in the tropics
(Vonder Haar 1986; validated by Lubin 1994, etc) - - That coastal upwelling of ocean water would increase
(Bakun 1990; validated by Goes et al 2005, McGregor et al 2007, etc) - - The magnitude (0.3 C) and duration (two years) of the cooling from the Mt. Pinatubo eruption
(Hansen et al 1992; validated by Hansen et al 1996, Soden et al 2002, etc) - - The amount of water vapor feedback due to ENSO
(Lau et al 1996; validated by Soden 2000, Dessler and Wong 2009, etc) - - The rising of the tropopause and the effective radiating altitude
(Thuburn and Craig 1997, Kushner et al 2001; validated by Santer et al 2003, Seidel and Randel 2006, etc) - - The response of southern ocean winds to the ozone hole
(Fyfe et al 1999, Kushner et al 2001, Sexton 2001; validated by Thompson and Solomon 2002, etc) - - The expansion of the Hadley cells
(Quan et al 2002; validated by Fu et al 2006, Hu and Fu 2007, etc) - - They predicted a trend significantly different in amount and different in nature from UAH satellite temperatures, and then a bug was found in the satellite data which showed that surface temperatures were more accurate and reliable than UAH temperature data.
(Christy et al 2003; validated by Santer et al 2003, Mears and Wentz 2005, Santer et al 2005, Sherwood et al 2005, etc) - - The poleward movement of storm tracks
(Trenberth and Stepaniak 2003; validated by Yin 2005, etc)
Climate Models - OSS Foundation
Slow climate mode reconciles historical and model-based estimates of climate sensitivity
Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures
Reality check december 2018:
"Twenty years ago in Nature we concluded that recent warming was unprecedented in at least six centuries"
https://www.nature.com/articles/33859
This year in Nature, scientists concluded it's unprecedented in at least eleven millennia
https://www.nature.com/articles/nature25464
Latest:
Humans Have Caused the Most Dramatic Climate Change in 3 Million Years
1. By including dropping CO2 levels and the removal of the sediment overburden atop the bedrock underneath the ice sheets and glaciers (the ice scoured the sediments down & into the bedrock itself), scientists were able to successfully reproduce the observed climate as found in the various proxy records over that same time interval
2. The mid-Pleistocene transition from 40,000 year glacial phases to 100,000 year phases was successfully replicated using the new forcing values
3. The Earth's climate system has a strong response to even small variations in CO2 (3 C climate sensitivity in the model)
4. CO2 levels during that interval have never been as high as they are today (~410 ppm)
5. A continuance of Business As Usual Emissions Pathways, as at present, would push our climate beyond the bounds of climate experienced over the Quaternary Period (the period covered by this study).
First successful model simulation of the past 3 million years of climate change
Humans Have Caused the Most Dramatic Climate Change in 3 Million Years
Mid-Pleistocene transition in glacial cycles explained by declining CO2 and regolith removal
LETS TAKE A LOOK AT THE HISTORY OF CLIMATE MODELS:
The First Climate Model Turns 50, And Predicted Global Warming Almost Perfectly
Modeling the Earth's climate is one of the most daunting, complicated tasks out there. If only we were more like the Moon, things would be easy. The Moon has no atmosphere, no oceans, no icecaps, no seasons, and no complicated flora and fauna to get in the way of simple radiative physics. No wonder it's so challenging to model! In fact, if you google "climate models wrong", eight of the first ten results showcase failure. But headlines are never as reliable as going to the scientific source itself, and the ultimate source, in this case, is the first accurate climate model ever: by Syukuro Manabe and Richard T. Wetherald. 50 years after their groundbreaking 1967 paper, the science can be robustly evaluated, and they got almost everything exactly right.
The effects and dangers of human made climate change was well known and understood by the US military and the president already in the 1960s.
Fifty years ago: The White House knew all about climate change
On November 5, 1965, President Lyndon B. Johnson’s White House released “Restoring the Quality of our Environment”, a report that described the impacts of climate change, and foretold dramatic Antarctic ice sheet loss, sea level rise, and ocean acidification.
That 1965 White House report stated:
“Carbon dioxide is being added to the earth’s atmosphere by the burning of coal, oil, and natural gas at the rate of 6 billion tons a year. By the year 2000 there will be about 25 percent more CO2 in our atmosphere than present.”[…] “This will modify the heat balance of the atmosphere to such an extent that marked changes in climate, not controllable through local or even national efforts, could occur.
On the 50th anniversary of the White House report, CO2 concentrations in the atmosphere are indeed at 399 ppm: 25 percent over 1965 levels, exactly as predicted 50 years ago.
http://ourchildrenstrust.org/sit...
Scientists warned the President about global warming 50 years ago today | Dana Nuccitelli
Comparing what climate scientists said in the early 80s with today:
Comparing what climate scientists said in the early 80s with today:
Listening to James Hansen on Climate Change, Thirty Years Ago and Now
IPCC PREDICTIONS:
Assessment of the first consensus prediction on climate change
https://skepticalscience.com/ipcc-overestimate-global-warming.htm
Some people argue that climate models are unreliable if they don't make perfect short-term predictions. However, a number of unpredictable influences such as ocean and solar cycles have short-term influences on climate. Over the long term, these effects average out, which is why climate models do so well at long-term predictions.
IPCC explains this difference here:
IPCC confirms that short term internal climate variability, in any given 15-year period is hard to predict.
"For the period from 1998 to 2012, 111 of the 114 available climate-model simulations show a surface warming trend larger than the observations"
Then they confirms their CMIP5 models are accurate and explains recent 15-year period short term predictions, showing a surface warming trend larger than the observations, was because of El Ninò:
"There is hence very high confidence that the CMIP5 models show long-term GMST trends consistent with observations, despite the disagreement over the most recent 15-year period. Due to internal climate variability, in any given 15-year period the observed GMST trend sometimes lies near one end of a model ensemble, an effect that is pronounced in Box TS.3, Figure 1a, b as GMST was influenced by a very strong El Niño event in 1998."
https://www.ipcc.ch/pdf/assessme...
Risbey et al (2014) found that climate models actually generate good estimates of recent and past trends provided they also took into account natural variability, particularly the key El Nino-La Nina phases in the Pacific.
“You’re always going to get periods when the warming slows down or speeds up relative to the mean rate because we have these strong natural cycles,” Dr Risbey said.
In roughly 30-year cycles, the Pacific alternates between periods of more frequent El Ninos - when the ocean gives back heat to the atmosphere - to La Ninas, when it acts as a massive heat sink, setting in train relatively cool periods for surface temperatures.By selecting climate models in phase with natural variability, the research found that climate models have provided good estimates of 15-year trends, including for recent periods and for Pacific spatial trend patterns.
By selecting climate models in phase with natural variability, the research found that climate models have provided good estimates of 15-year trends, including for recent periods and for Pacific spatial trend patterns.
Well-estimated global surface warming in climate projections selected for ENSO phase
Comparing CMIP5 & observations
A global perspective on CMIP5 climate model biases
A study in the journal Science Advances, joins a growing body of literature that suggests the models are on track after all. And while that may be worrisome for the planet, it’s good news for the scientists working to understand its future. Climate models are even more accurate than you thought The difference between modeled and observed global surface temperature changes is 38% smaller than previously thought. Global climate models aren’t given nearly enough credit for their accurate global temperature change projections.
As the 2014 IPCC report showed, observed global surface temperature changes have been within the range of climate model simulations.
Worrisome first quarter of 2017 climate trends » Yale Climate Connections
Factcheck: Climate models have not 'exaggerated' global warming
IPCC PREDICTIONS HAVE DONE WELL AND MUCH BETTER THAN CONTRARIANS PREDICTIONS:
BONUS 1:
DENIERS ATTACK ON CLIMATE MODELS WAS BASED ON FALSELY CALIBRATED DATA : ROY SPENCERS BIG LIE AND CHEAT:
Climate scientists have been terrible at predicting temperatures.
“This is a claim that's often made by climate skeptics: that predictions about the near-term future have been bad, so we shouldn't trust predictions about the longer-term future. But is that true? Have predictions historically been bad?
The evidence they cite is from Dr. Roy Spencer, who showed in 2013 that 95% of climate models over predict the temperature rises due to greenhouse gases. The chart showing that is above. Unfortunately, that chart itself is based on falsely calibrated data.
Have predictions historically been bad? The evidence they (deniers) cite is from Dr. Roy Spencer, who showed in 2013 that 95% of climate models over predict the temperature rises due to greenhouse gases.”
Unfortunately, that chart itself is based on falsely calibrated data.
“In 2014, the truth came out: Spencer’s UAH team had made a huge mistake in the calibration of their data. Instead of negligible upper-atmosphere warming, they found that the upper atmosphere had been warming at +0.14 degrees per decade, double the 1880-2014 rate of 0.07 degrees per decade. The other major satellite data set, RSS, also found a calibration error, meaning the Earth warmed 140% faster since 1998 than previous conclusions indicated. At the same time, the ground-based data from NOAA, NASA, the Hadley center and BEST all displayed agreement with one another. Once the 2014, 2015 and 2016 data are also included, the graph shows the scientific truth: the models are very much in line with what we observe.”
JOHN CHRISTYS LYING non-peer reviewed GRAPH:
DEBUNKED:
- "Christy showed a graph of only mid-troposphere temperatures. The mid-troposphere is the atmospheric layer from about 25,000–50,000 feet, or about 8–15km in altitude. One might reasonably ask why Christy only showed data for such high altitudes. For perspective, the highest point on the Earth’s surface is on Mount Everest at 29,000 feet (8.8km), and the highest elevation city in the world is La Rinconada, Peru at 16,700 feet (5.1km). Humans live in the lower troposphere, not the mid-troposphere.
- However, climate models have done a good job matching the observed temperature change at the surface and in the lower troposphere, where humans live. We understand the workings of the Earth’s climate much better than Christy suggests, especially where it matters most to humans."
- In addition to various statistical sizes, Christy uses different physical measures in comparison when comparing temperatures at the surface with the temperature of 15 km of the atmosphere.
- Christy compared the average of 102 climate model simulations with temperature from satellite measurements (average of three different analyses) and weather balloons (average of two analyses). This is a flawed comparison because it compares a statistical parameter with a variable.
- Temperature from satellites are also model results
It is fair to compare the satellite record with model results to explore uncertainties, but the satellite data is not the ground truth and cannot be used to invalidate the models. The microwave sounding unit (MSU), the instrument used to measure the temperature, measures light in certain wavelength bands emitted by oxygen molecules. Satellite data are 5 timers less accurate than ground data.
Different types of numbers
The upper left panel in Fig. 1 shows that Christy compared the average of 102 climate model simulations with temperature from satellite measurements (average of three different analyses) and weather balloons (average of two analyses). This is a flawed comparison because it compares a statistical parameter with a variable.
A parameter, such as the mean (also referred to as the ‘average’) and the standard deviation, describe the statistical distribution of a given variable. However, such parameters are not equivalent to the variable they describe.
The comparison between the average of model runs and observations is surprising, because it is clearly incorrect from elementary statistics (This is similar statistics-confusion as the flaw found in the Douglass et al. (2007)).
http://www.realclimate.org/index...
http://www.realclimate.org/index...
Climate scientists, using current science, are successful in predicting temperatures.
https://skepticalscience.com/gra...
https://skepticalscience.com/gra...
https://skepticalscience.com/rep...
Congress manufactures doubt and denial in climate change hearing | Dana Nuccitelli
BONUS 2:
Q&A: How do climate models work?
https://www.carbonbrief.org/qa-h...
There is an excellent description of climate models evaluation in the following IPCC report:
http://www.ipcc.ch/pdf/assessmen...
If anything else, I suggest you read page 600-601 that address how reliable current models are.
The last paragraph states:
"In summary, confidence in models comes from their physical basis, and their skill in representing observed climate and past climate changes. Models have proven to be extremely important tools for simulating and understanding climate, and there is considerable confidence that they are able to provide credible quantitative estimates of future climate change, particularly at larger scales. Models continue to have significant limitations, such as in their representation of clouds, which lead to uncer- tainties in the magnitude and timing, as well as regional details, of predicted climate change. Nevertheless, over several decades of model development, they have consistently provided a robust and unambiguous picture of significant climate warming in re-sponse to increasing greenhouse gases."
But first, lets clear up a few common mistakes:
Climate models don't "predict." They project what will happen given a set of initial conditions and may include several scenarios. If a certain scenario didnt happen, it does not mean the prediction was wrong. It means the conditions for that particular scenario didnt happen. The scenarios are often grouped as most likely and worst case etc.
All studies shows models have underestimated the realities.
Part of the problem here stems from people either misunderstanding or deliberately misrepresenting how predictive models work. Many people have the unrealistic expectation that the observed data need to be a near perfect match for the prediction line, but that’s not actually how things work.
Some are still "under the mistaken impression that concern about global warming is based on climate models, which in reality play little role in our understanding -- our understanding is based mainly on how the Earth responded to changes of boundary conditions in the past and on how it is responding to on-going changes."- Dr. James Hansen
Some people argue that climate models are unreliable if they don't make perfect short-term predictions. However, a number of unpredictable influences such as ocean and solar cycles have short-term influences on climate. Over the long term, these effects average out, which is why climate models do so well at long-term predictions.
It’s basic physics which follows the same principles as other laws of nature.
“The physics we use to understand the earth’s climate system is the same physics that explains how stoves, fridges, airplanes and more work. And most people don’t really have a problem with the physics of non-linear fluid dynamics and radiative transfer that have been well understood for decades, even centuries.” (Climate scientist Katharine Hayhoe.)