My goal with
this post is not to refute the validity of climate change modeling, but to
highlight that there are still significant uncertainties about modeling
assumptions that can affect predictions. Computer-based modeling has worked and
continues to work very well in science. While climate, as a global system with
many variables, does lend itself well to modeling, there are so many variables,
locally, regionally, and globally, that there are also many model assumptions
made. Model accuracy is dependent on the accuracy of those model assumptions. Climate
models in general have gotten better through time.
Source: Wikipedia
Most climate
models are quantitative. One type of global climate model is a general
circulation model (GCM) that mathematically models the circulation of the
atmosphere or the ocean. “It uses the Navier–Stokes equations on a rotating
sphere with thermodynamic terms for various energy sources (radiation, latent
heat).” The GCM acronym can also stand for global climate model, which is a
more general use of it. GCMs usually refer to ocean circulation (OGCM), atmospheric
circulation (AGCM), or a coupled model with both (AOGCM). According to
Wikipedia: “AOGCMs internalise as many processes as are sufficiently
understood. However, they are still under development and significant
uncertainties remain. They may be coupled to models of other processes in Earth
system models, such as the carbon cycle, so as to better model feedbacks. Most
recent simulations show "plausible" agreement with the measured
temperature anomalies over the past 150 years, when driven by observed changes
in greenhouse gases and aerosols. Agreement improves by including both natural
and anthropogenic forcings.” The effects of clouds in modeling are one of
the main areas of uncertainty and debate. More recent climate models have
matched observed cloud data as well.
Some Model Predictions of Past Warming Events
Refuted by Data
In 2020 a
paper came out in Nature Climate Change where researchers from the University
of Michigan concluded that model projections from one of the leading models,
CESM2, are not supported by the geological evidence from the Eocene, approximately
50 million years ago. According to Science Daily: “the CESM2 model projected
Early Eocene land temperatures exceeding 55 degrees Celsius (131 F) in the
tropics, which is much higher than the temperature tolerance of plant
photosynthesis -- conflicting with the fossil evidence. On average across the
globe, the model projected surface temperatures at least 6 C (11 F) warmer than
estimates based on geological evidence.” The fossil evidence showed
abundant tropical rainforest plant material. The implication is that those
models are too sensitive to increase in atmospheric CO2 which is why they
predict too much warming. The study focused on how geological data can benchmark
paleoclimate models. The CESM2 model has a very high equilibrium climate
sensitivity (ECS) of 5.3 degrees Celsius, which is higher than the typical
range given between 1.5 degrees Celsius and 4.5 degrees Celsius. The predecessor
to the CESM2, the CESM1 used an ECS of 4.2 degrees Celsius, which is plausible
according to the geological data, while still being at the higher end of the typical
sensitivity range. Of course, this doesn’t refute all climate models, but it
does show that it is very unlikely that climate sensitivity is higher than the
normal (1.5-4.5) range given. The CESM2 model is part of the Coupled Model
Intercomparison Project (CMIP), is an internationally coordinated effort
between climate-science institutions. Of 27 CMIP models, 10, or 37% have an ECS
above 4.5 degrees Celsius, or beyond the normal range given. CO2 predictions
for the Eocene long predate ice cores and are thus determined by proxies but
the geological and botanical evidence does suggest a sensitivity range well below
that predicted by the CESM2 model or any of the 10 models above the top of the
normal range given.
Climate Skeptics Have Long Dissed Climate Modeling as
Inaccurate
Skeptical climate scientist Patrick Michaels, considered to be a “lukewarmer,” or one who thinks that climate change is not as bad as often predicted, wrote in a 2019 Washington Examiner article that climate models are a great failure. He cited the “pause” in the satellite data of the upper levels of the lower atmosphere by conservative evangelical climate scientists John Christy and Roy Spencer as well as the failure of some of the early climate models that over estimated future temperature increases. While those are fair assertions, even in the 4.5 years since then, climate models continue to be refined and are now considered more accurate. Christy and Spencer’s predictions have been revised downward a bit but still do not match the higher warming observed in both surface data and ocean temperature data. Michaels noted that Christy’s data showed that heating predicted by models was 3 times what was observed in satellite data. Michaels wrote: “This is a critical error. Getting the tropical climate right is essential to understanding climate worldwide. Most of the atmospheric moisture originates in the tropical ocean, and the difference between surface and upper atmospheric temperature determines how much of the moisture rises into the atmosphere. That’s important. Most of Earth’s agriculture is dependent upon the transfer of moisture from the tropics to temperate regions.” Michaels also claimed that ocean surface temperatures from buoys were adjusted upward to match those of ship water intakes which are more susceptible to heating in the sun, which led to overestimated heating. I am unsure if this is true, and I admit I am a bit skeptical that this is the case. Michaels also claimed that a second adjustment occurred in the Arctic Ocean where there are few weather stations, so that the temperatures were adjusted to match those of land stations in the Arctic. He notes that temperatures over the Arctic Ocean are colder than those on land since as is well known there is ice in the Arctic Ocean even in summer. Again, I am unsure how much this would affect projections and I wonder why other climate scientists have not echoed such concerns if they are indeed warranted. It is also known that Arctic temperatures everywhere have risen much faster than in other parts of the world. Michaels also claimed that adjustments of early data to lower temperatures as was done means that temperatures through time could be seen as warming faster than otherwise may be the case. Michaels also noted that sea level rise was not accelerating as much as predicted in models and that instrument shelters were not standardized so that those in poorer tropical countries heating is overestimated. I admit I don’t know of Michaels’ assertions are true, have been taken into consideration, have been considered, rejected, or accepted. He thinks Christy’s data is the best data we have. Is he right? I don’t know, but I do know that most climate scientists consider the IPCC’s estimations reasonable. Michaels wrote a book called Scientocracy around this time. I have not read it but I am guessing that he believes science, particularly climate science, has become politicized.
Atmospheric Moisture in Dry Regions Defies Modeling
Research
led by the National Science Foundation published in late 2023 has revealed that
predictions for increasing atmospheric moisture in arid areas were not matching
climate models. The study shows that the Clausius-Clapeyron relationship, which
suggests that there should be more water vapor in a warmer atmosphere, has not
held true in arid and semi-arid areas. Dry and semi-dry areas have been getting
drier rather than wetter, as climate models have predicted, leading to more
susceptibility to droughts and wildfires. The study measured atmospheric water vapor
amounts from 1980 to 2020 from weather stations, weather balloons, and
satellites. The Clausius-Clapeyron relationship, well regarded in climate
science, suggests that with every 1°C rise in temperature, atmospheric moisture
should increase by about 7%. That has not been the case in arid and semi-arid
areas with many having no change in moisture and some losing moisture through
time. According to the paper’s authors: "This is contrary to all
climate model simulations in which it rises at a rate close to theoretical
expectations, even over dry regions. Given close links between water vapor and
wildfire, ecosystem functioning, and temperature extremes, this issue must be
resolved in order to provide credible climate projections for dry and semi-arid
regions of the world." That is pretty stark evidence that climate
modeling is still subject to considerable uncertainties. The data also showed
that while atmospheric moisture did increase in wetter areas it did so less in
the drier months of those regions. The data suggests that atmospheric moisture
dynamics are not as well understood as previously thought. Discrepancies were
too consistent across regions to attribute them to measurement errors. Possible
explanations suggest that the transfer of moisture from the earth to the
atmosphere is not occurring as modeling suggests, that atmospheric circulation
may not be occurring as modeling suggests, or that the earth is retaining more
moisture than expected. In all of those suggestions is the implication that modeling
is not matching real data. The findings underscore the complexity of the global
climate system. The researchers also noted: "But we absolutely need to
figure out what's going wrong because the situation is not what we expected and
could have very serious implications for the future." According to the
paper. Published in PNAS: “This may indicate a major model misrepresentation
of hydroclimate-related processes; models increase water vapor to satisfy the
increased atmospheric demand, while this has not happened in reality.” The
research calculated dew point temperatures and average mean vapor pressure data
to arrive at their conclusions as shown in the figures below from the paper.
Modeling Climate Misinformation (But Is It All
Misinformation?)
This section is more of an aside, but it also involves modeling. According to a 2021 study in Nature Scientific Reports, summarized in an article in Forbes, that attempted to model climate change denialism, researchers expected to find science myths as the main issue but that turned out not to be the case. What they found was that climate change denial has morphed mainly into climate change solutions denial. According to Forbes’ analysis of the research: “Looking at climate-related content from 33 prominent climate contrarian blogs and 20 conservative think-tanks produced between 1998 and 2020, the team began by sorting the climate claims into brackets. “They ultimately came up with five major themes of climate misinformation, namely: 1) Global warming is not happening; 2) Human-produced greenhouse gases are not causing global warming; 3) Climate impacts are not bad; 4) Climate solutions won’t work; and 5) Climate science or scientists are unreliable.” As the graph below from the paper shows number 4 is the most prominent, followed by number 5. Even so, it can be argued that the feeling that climate solutions won’t work is not always misinformation. This is due to the fact that ensuring reliable electricity and reliable transport with existing low carbon solutions is not at all guaranteed to work. It is often more expensive and more difficult than existing higher carbon solutions. Thus, I would argue that this study has some potential flaws that should be considered. Apparently, the study did not consider some versions of climate alarmism as a kind of misinformation as well, which can be reasonably argued.
Michaels and other skeptics like Roger Pielke Jr. and
Bjorn Lomborg have noted that the IPCC has pointed out that extreme weather events
have not been as frequent or severe as predicted even though the media emphasis
on such events may make it seem otherwise. Again, I am not saying we should
believe climate skeptics over mainstream climate scientists, but we should expect
mainstream climate scientists to be able to explain discrepancies and modeling
irregularities when they are pointed out. There is no question that climate
science has become politicized, and it should be in the interest of all climate
scientists, both mainstream and skeptical, to reduce such politicization as much
as possible and to honor real data over modeled data as any scientist should.
References:
Weather
in dry regions isn't behaving as climate models predict. Eric Ralls. Earth.
January 20, 2024. Weather in dry regions isn't behaving
as climate models predict (msn.com)
5 Big
Lies About Climate Change, And How Researchers Trained A Machine To Spot Them. David
Vetter. Forbes. November 19, 2021. 5 Big Lies About Climate Change, And
How Researchers Trained A Machine To Spot Them (forbes.com)
Some
of the latest climate models provide unrealistically high projections of future
warming. University of Michigan, April 30. 2020. Science Daily. Some of the latest climate models
provide unrealistically high projections of future warming | ScienceDaily
High
climate sensitivity in CMIP6 model not supported by paleoclimate. Jiang Zhu,
Christopher J. Poulsen & Bette L. Otto-Bliesner. Nature Climate Change
volume 10, pages 378–379 (2020). High climate
sensitivity in CMIP6 model not supported by paleoclimate | Nature Climate
Change
The
great failure of the climate models. Patrick Michaels. Washington Examiner. August
25. 2019. The great failure of the climate
models - Washington Examiner
Climate
model. Wikipedia. Climate model - Wikipedia
General
circulation model. Wikipedia. General circulation model - Wikipedia
Observed
humidity trends in dry regions contradict climate models. Isla R. Simpson,
Karen A. McKinnon, Daniel Kennedy,, and Richard Seager. Edited by Sonia I.
Seneviratne, Eidgenossische Technische Hochschule, Zurich, Switzerland; PNAS. received
February 12, 2023; accepted November 13, 2023. December 26, 2023. 121 (1)
e2302480120. Observed
humidity trends in dry regions contradict climate models | PNAS
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