ATTP has a new post which highlights a fundamental problem with increasing complexity of AR6 climate models. This is based on a new article in Nature by Zeke Hausfather et al . Some of the latest models in AR6 are running far too hot. The more sophisticated they try to become so the hotter they seem to run. Modellers introduce new complexity through informed guesswork to parameterise it. The article notes however that such “hot models ‘ have problems.
“Numerous studies have found that these high-sensitivity models do a poor job of reproducing historical temperatures over time and in simulating the climates of the distant past. Specifically, they often show no warming over the twentieth century and then a sharp warming spike in the past few decades, and some simulate the last ice age as being much colder than palaeoclimate evidence indicates”
ATTP summarises the article as follows
The Hausfather et al. article was basically suggesting that researchers who use climate model output to assess the impact of climate change should aim to follow a similar practice to what was presented in the most recent IPCC report. Use GWLs, rather than simply focussing on scenarios going to 2100, weight the models if the warming trajectory is relevant, and try to consider which models may be best suited to the problem that is being considered.
So I thought it would be interesting instead to go right back to basics and use the simplest CO2 green house climate “model” possible. From this we can derive the radiative forcing due to rising levels of CO2 giving a logarithmic dependence
Following this we can simply make an estimate for the net change in surface temperature due to CO2.
Averaging over clouds(
If we assume that each increment in forcing DS is offset by the same increase in Black Body radiation due to a small surface temperature rise DT, then we can iterate through the temperature rise due to increases in CO2 concentrations. We take Pre-industrial CO2 levels as 280 ppm with an associated temperature of 288 K
Here is the result of this “model”.
Simplest possible Climate Model.
We can see that temperatures should rise by ~1C since pre-industrial times which proves to be surprisingly accurate! A doubling of CO2 levels would then lead to a net temperature rise of just 1.5C due to the logarithmic increase in forcing. This is not a “climate breakdown”.
I once worked on Magnetohydrodynamic (MHD) code for modelling Tokamak plasmas. That too was immensely complicated but recent breakthroughs in fusion have mainly been experimental. So I suspect the same will apply to our current dependence on ever more complex climate models predicting imminent doom.
Hello Clive,
Thanks for the post . One wonders when this simplied model will change government position . I think it will be ignored as there;s too much invested in the old models and could be embarrising,
Regards
Forbin
There are vested interests din keeping the doom “narrative” going in the short term.
We’re all about “narratives” now and not logic or evidence.
Sadly, I’d say you are very right.
Thank you, most interesting
Climate sensitivity?
Climate sensitivity is ~ 1.5C
Your climate sensitivity of 1.5 seems low. Consider the temperature formulation of the CO2 forcing equation.
?T=5.35ln(C/Co) climate sensitivity/warming effect of forcing
(IPCC quote a warming effect of forcing of 3.7W/C)
Due to lag we don’t see the full effect of CO2 increase in real time. We can calculate transient climate response using ?T to date.
TCR= ?T*warming effect/5.35ln(C/Co)
1.2*3.7/5.35ln(420/280) =2.05
TCR to date is 2.05, larger than your 1.5 estimate, so the full ECS will be larger again.
Your browser failed to parse deltaT. Instead it out up ?T.
I was simply using Stefan Boltzmann to estimate the temperature rise needed to offset the CO2 forcing where I estimated the emissivity.
IPCC instead talk of a sensitivity parameter lambda where Delta T = lambda DS and quote lambda = 0.8 K/(W/m2). So that indeed gives much higher values (for ECS) = 4C
So if I take epsilon as 0.95 instead of 0.65 TCR rises to 2.2C
That sounds more likely..
The low climate sensitivities discussed by writes such as Nic Lewis always seemed too low to account for the warming already observed.
If the low sensitivity were genuine it required that either that CO2 forcing was a lot greater than expected or that an unknown factor was doing a lot of the warming. The former disagrees with the physics and the latter would be hard to miss in this highly monitored era.
Clive,
I think your comparison between your model and observations ignores that we’re not currently in energy balance/equilibrium. If we were in energy balance at today’s atmospheric CO2 concentration, warming would probably be closer to something like 1.5 – 1.7C, than 1C.
This is not true in this model. At all stages there is a balance between incoming energy from the sun (constant) and outgoing energy including CO2 molecules in the upper atmosphere. The temperature change at the surface is just calculated using the Stefan Boltzmann.
The energy imbalance balance you refer to is the deep ocean equilibrium. Radiative balance depends only on surface temperature.
Clive,
Yes, I realise it’s not true in this model. That’s essentially my point. Your model predicts ~1C of warming today, relative to pre-industrial, which you suggest is “surprisingly accurate”. However, this is essentially equilibrium warming. The warming since pre-industrial is not warming to equilibrium. Given today’s level of atmosopheric CO2, we’d probably expect something closer to 1.5 – 1.7C if the system warmed to equilibrium.
Additionally, the change in forcing we’ve experienced since pre-industrial is not simply CO2. There are other GHGs and there are aerosols. So, there is quite a large uncertainty in the change in forcing, which is one reason why there is an uncertainty in climate sensitivity.
The climate never really is in equilibrium. Seasons affect the northern and southern hemispheres differently. Volcanic eruptions change aerosols as much if not more than humans. There are oceanic oscillations like El Nino and AMO. Farming and cities change the Albedo etc.
I have my doubts that ECS really has any meaning in this context. Otherwise you could argue that the warming today includes the latent warming playing out today from the early industrial revolution. The only measure we have a handle on is the measured global temperature at one time.
Wow.
No use arguing over ECS as there is simply not enough discriminatory power to claim one model over another. It’s just a trend with the limitations inherent in that, and with the climate variations due to ENSO creating havoc every few years (cf. the AGW “pause”).
OTOH, geophysics and geophysical fluid dynamics is providing all the variation in which we can discriminate the models against much more complex time series. If the climate scientists would get their heads out of the sand and acknowledge what some of the obviously disenchanted former NASA JPL scientists are suggesting regarding the impact of torque on the Earth’s dynamics we can start filling in the missing pieces. See research by James H. Shirley, Claire Perigaud, Steven L. Marcus. I can also fill in the gaps but have even less pull.
In addition to volcanoes, farming, cities I would also add Mantle Plumes. Seems to me earth is like a tea kettle letting off steam right now.
I don’t think there is any valid climate model without including natural variability. I know Dr. Curry and others are proponents of this. I think the current models are close to worthless and are unworthy to be used for policy decisions.
To add further from what you have posted, I added what you see below. This comes from Prof. Scafetta;
I take this opportunity to share my latest article on “Geophysical Research Letters”:
Advanced Testing of Low, Medium, and High ECS CMIP6 GCM Simulations Versus ERA5?T2m – Scafetta – 2022 – Geophysical Research Letters – Wiley Online Library
I test all the CMIP6 GCMs used now by the IPCC (the CMIP6s) from 1980 to today and show that the great majority of these models are incompatible with the observed warming trends. Essentially the models show excessive warming which is not observed.
Those that seem to better agree with the data are those with low equilibrium climate sensitivity, even though these too have conspicuous deficiencies.
In any case, only the low ECS models could at most be used for policy, but these models only predict moderate warming for the next few decades even in the worst-case emission scenario. Thus, climate adaptation policies should be sufficient to address future climate changes.
Plain Language Summary
The last-generation Coupled Model Intercomparison Projects (CMIP6) global circulation models (GCMs) are used by scientists and policymakers to interpret past and future climatic changes and to determine appropriate (adaptation or mitigation) policies to optimally address scenario-related climate-change hazards. However, these models are affected by large uncertainties. For example, their equilibrium climate sensitivity (ECS) varies from 1.83°C to 5.67°C, which makes their 21st-century predicted warming levels very uncertain. This issue is here addressed by testing the GCMs’ global and local performance in predicting the 1980–2021 warming rates against the ERA5-T2m records and by grouping them into three equilibrium climate sensitivity (ECS) classes (low-ECS, 1.80–3.00°C; medium-ECS, 3.01–4.50°C; high-ECS, 4.51–6.00°C). We found that: (a) all models with ECS > 3.0°C overestimate the observed global surface warming; (b) Student t-tests show model failure over 60% (low-ECS) to 81% (high-ECS) of the Earth’s surface. Thus, the high and medium-ECS GCMs do not appear to be consistent with the observations and should not be used for implementing policies based on their scenario forecasts. The low-ECS GCMs perform better, although not optimally; however, they are also found unalarming because for the next decades they predict moderate warming: ?Tpreindustrial?2050 ? 2°C.
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I noticed that my comment did not include the link to Prof. Scafetta;s article.
This is what you need.
Advanced Testing of Low, Medium, and High ECS CMIP6 GCM Simulations Versus ERA5-T2m
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL097716
Or we could just use the raw data and average the global temperature over a 12 month rolling average and find that the current global average temperature is 13.66C or 287K.
Not much of a trend or a threat. refer Temperature.Global website (no .com or .org)
“The more sophisticated they try to become so the hotter they seem to run.”
A clear indication of a troubled paradigm.
Models and ECS studies assume all the warming is coming from changes in GHGs, since natural factors and internal variability have been ruled out without evidence. They are all worthless despite costing a huge amount of money.
“We can see that temperatures should rise by ~1C since pre-industrial times which proves to be surprisingly accurate!”
Don’t get your hopes too high. Your model, as everyone else’s, assumes that the location where the radiation exchange at the ToA happens has no effect, and that the GHG effect (in your case just CO2) is global and doesn’t change over time except through their concentration changes. The truth is that GHG concentration is VERY DIFFERENT at different parts of the globe (that pesky H2Ov) and experiments not well constrained changes over time. As an example, OLR over the winter North Pole depends exclusively on the amount of heat transported there, that changes over time. And in the polar atmosphere conditions an increase in CO2 results in a higher emissivity, because the atmospheric CO2 is warmer that the surface (as per van Wijngaarden & Happer 2021). The amount of energy transported to the North Pole has a huge effect on the Earth’s energy budget and its changes are neglected in every GC model.
Have you checked monthly changes in ToA OLR for the 70-90ºN region? Very ilustrative.
All those assumptions are wrong. Climate science has become the equivalent to the discussion about how many angels can dance on a pinhead. Reality is being ignored while climatology more and more resides inside computers.
“Climate science has become the equivalent to the discussion about how many angels can dance on a pinhead.”
Javier seems somewhat confused, as angels don’t play ClimateBall.
The climate playbook writing classes , pro and con, focus instead on how many pinheads deliverables can persuade to dance to the tune of an imp.
Entropic man (June 13): “If the low sensitivity were genuine it required that either that CO2 forcing was a lot greater than expected or that an unknown factor was doing a lot of the warming. The former disagrees with the physics and the latter would be hard to miss in this highly monitored era.”
And this unknown factor is something everybody interested in climate change should know. It is about more sunshine reaching the surface the last 40 years. And it is highly monitored: CERES and earlier satellite measurements. Cloud cover isn`t usually seen as part of climate sensitivity. Is this faked ignorance, or what?
I think there is a problem with the simple climate model of Clive Best. Like in the orthodox climate science trace gases are responsible for all the global warming we see. That is the Great Mantra On Repeat. The CO2 molecules, with their friend Methane; are hot and greedy creatures, that warm the sea surface and eat the clouds.
I would like to present climate feedbacks, illustrated by the change of the most important components for the last 20 years. Measured from satellites from 2000 to 2020.
From Loeb et al 2021: Trend in EEI During the CERES Period
https://ceres.larc.nasa.gov/documents/STM/2021 05/35_Loeb_contrib_science_presentation.pdf
For the radiation at the earth`s surface we have the following numbers (Wild et al. 2019):
Solar radiation absorbed: 160 W/m2 with an increasing trend.
Longwave cooling from increased temperature: -56W/m2 with a cooling trend.
Evaporation, without presentation of trend: -82W/m2
Sensible heat, conduction/ convection from surface: -21W/m2
Earth Energy Imbalance measurements tell us that there is a warming of 0,51 W/m2/dec from change in these variables, SWsurf down, LWsurf up, Evaporation, Sensible heat. The components behind these changes are Temperature change, Albedo change, Cloud radiation change, Water vapor Change, and Trace gases change. These are also the feedback components of climate change.
Loeb et al, 20 years of energy imbalance from 2000 to 2020:
Temperature surface radiation, Net LW cooling: -0,51 W/m2/dec
Albedo reduction. SW solar warming: 0,19 W/m2/dec
Cloud LW cooling (less clouds) -0,23 W/m2/dec
Cloud SW decreased absorption 0.44 W/m2/dec
Water vapor LW warming 0,33 W/m2/dec
Water vapor SW warming and latent heat. 0,05 W/m2/dec
Trace gas, aerosole LW warming 0,237 W/m2/dec
Trace gas, aerosole SW warming 0,002 W/m2/dec
If we assume that most trace gases and aerosols don`t make much difference, and Methane stands for 22,9 % of trace gas warming, we get:
CO2 LW warming 0,185 W/m2/dec
Methane LW warming 0,055 W/m2/dec
With a warming of 0,19 degC/decade since 2000, we get the folowing feedbacks:
Temperature feedback (radiation from warmer surface): -2,68 W/m2/degree
Albedo feedback (Less reflection from atmosphere and surf)1,00 W/m2/degree
Cloud LW feedback (Less backradiation from Thiner clouds)-1,21 W/m2/degree
Cloud SW feedback (Less solar absorption of clouds) 2,31 W/m2/degree
SW water vapor warming feedback/forcing 0,26 W/m2/degree
LW water vapor absorption feedback/forcing 1,74 W/m2/degree
SW trace gas and aerosol warming feedback/forcing 0.01 W/m2/degree
LW trace gas and aerosol absorption feedback/forcing 1,25 W/m2/degree
Methane part of trace gas LW «trapping» «forcing» 0,29 W/m2/degree
CO2 part of trace gas LW «trapping» «forcing» 0,97 W/m2/degree
Sum of all feedbacks and forcings 2,68 W/m2/degree
A very little part of forcings and feedbacks has a warming effect on the atmosphere and earth`s surface (about 2% of total heat uptake, so about 0,01 W/m2/dec). Nearly all the absorbed energy becomes reradiated. But they have some impotant work to do. They have effects on the lapse rate. And shortwave radiation is warming liquid water and ice in clouds, resulting in evaporation and melting, potential heat and cloud dissipation. This may be the greatest contribution to global brightening, and is not a linear function of trace gases. CO2 stands for less than 20% of all positive forcings/feedbacks. So CO2 make only up a minor direct contribution to global warming.
It seems that much of this global warming comes from a decreasing trend in relative humidity.
From my discussion at: https://scienceofdoom.com/2017/12/24/clouds-and-water-vapor-part-eleven-ceppi-et-al-zelinka-et-al/
Are all the speculations on climate sensitivity and CO2 effect on surface temperatures a waste of time? And is it a futile task to judge models from how they fit with surface temperatures? Is our knowledge and understanding of climate processes still at an immature state?
There seems to be some regime shift in climate change, as the brightening period from ca 1983, and the dimming from about 1950 to 1980, and perhaps a brightening period in the warming years from about 1920 and foreward (melting of the northern hemisphere).
Where to look for the causes of global warming the last 40 years? Well, the increasing CO2 is surely one important factor. And models pretend covering this. But may be the atmospheric humidity has an even stronger effect. And it seems that models have this entirely wrong.
From Allan et al 2022. Global Changes in Water Vapor 1979-2020:
“Tropical ocean near-surface relative humidity in ERA5 decreases by more than 1% from 1979 to 2015 —“. “This is at odds with amip simulations which display a slight increase and small year to year variability in anomalies of order 0.5% RH.”
This implicates that models have a great attribution problem when it comes to global warming.
From the physics of clouds: “The basics of cloud formation and disappearance is temperature and relative humidity, RH (not specific humidity). Clouds form with combinations of lowering temperature and higher RH approaching the dew point; and disappear with combinations of higher temperatures and lower RH moving away from the dew point. Cold air meeting warm humid air is the most common way clouds are formed.”