By Andy May
Christian Freuer has translated this post into German here.
In the latest IPCC major report, AR6, they report: “a best estimate of equilibrium climate sensitivity of 3°C, with a very likely range of 2°C to 5°C”. They also report that CO2 concentration might control climate change. This estimate includes the laboratory estimate that CO2 alone, if doubled in the atmosphere, would increase the average global surface temperature about 1.2°C. The remaining 1.8°C (60%) is supposedly achieved through feedbacks to the initial CO2-caused warming. The main proposed feedback mechanism is an increase in atmospheric water vapor caused by the CO2 warmed air. Water vapor is a more powerful greenhouse gas than CO2, due to its greater abundance, and can cause more warming.
The IPCC estimates the water vapor feedback using the Clausius-Clapeyron relation. The relation states that as temperature increases, more evaporation occurs and atmospheric water vapor increases, especially in the upper atmosphere. Models suggest that relative humidity should remain “roughly constant,” as climate changes. According to AR5 and AR6:
“… total column water vapour (TCWV) very likely increased since the 1970s, at a rate that was overall consistent with the Clausius-Clapeyron relationship (about 7% per °C) given the observed increase in atmospheric temperature.”(IPCC 2021, p 330).
Later in the report they write this:
“The Clausius–Clapeyron equation determines that low-altitude specific humidity increases by about 7% °C–1 of warming, assuming that relative humidity remains constant, which is approximately true at a global scale but not necessarily valid regionally.”(IPCC 2021, p 1065).
A corollary to the Clausius-Clapeyron relationship is that as the specific humidity (total water vapor in the air, the units used here are kg of water vapor per kg of dry air) goes up precipitation also increases by about the same amount, keeping relative humidity about the same. Model studies suggest that the increase in precipitation is less, around 3%. These assumptions make some sense logically, but they are not definitively supported by real world data. Further, it appears that the rate of evaporation is strongly influenced by wind speed, as well as temperature in the real world.
AR6 makes an oblique reference to the evaporation and total atmospheric precipitable water (TPW, shown here as kg/m2) dependence upon wind speed but refers to it as a “dynamical process.”
“According to theory, observations and models, the water vapour increase approximately follows the Clausius–Clapeyron relationship at the global scale with regional differences dominated by dynamical processes …. Greater atmospheric water vapour content, particularly in the upper troposphere, results in enhanced absorption of LW [longwave] and SW [shortwave] radiation and reduced outgoing radiation. This is a positive feedback.”(AR6, p 969).
The Clausius-Clapeyron relationship between specific humidity and temperature is sound in the laboratory, but observations show the relationship between humidity, temperature, and precipitation in the real world is more complex. Benestad (2016) reported that the European Centre for Medium-range Weather forecasts (ECMWF) interim reanalysis shows the total volume of water vapor in the atmosphere decreasing by -0.018 kg/m2 per decade from 1979-2011, a period of rapid global warming. This is a decrease of about .07%/decade or 0.007%/year (1979-2011). Miskolczi (2014) reports that the NOAA R1 dataset shows that global surface air temperature has increased 0.687K between 1948 and 2008, but the water content has decreased by 0.636% or -0.0106%/year, like what is seen in the ECWMF dataset.
The NOAA R1 dataset still exists and is a weather reanalysis dataset maintained by NCEP, it has been updated since Miskolczi used it in 2014. Figure 1 shows it and its successor NCEP R2, as well as the HadCRUT4 global surface temperature dataset.
In figure 1 we see that before 1978, NCEP R1 TPW declines more steeply than temperature, but both decline. After 2005, temperature and both NCEP reanalysis datasets increase, but again at different rates. Between 1978 and 2005 TPW declines in both datasets and temperature increases quickly. This is a 27-year period, why opposite trends? Obviously, global temperatures are not the only thing influencing TPW and the impact of temperature is not that significant. Yu and Weller emphasize that wind speed is a strong modulator of surface latent heat flux (evaporation). Wind moves saturated air out of the way, so that evaporation can continue. Evaporation stimulates circulation since water vapor is less dense than dry air and humid air usually rises as a result.
NCEP reanalysis 1 and 2 are separated when plotted in kg/m2, but they look much more alike when plotted as anomalies from the 1988-2022 mean as shown in figure 2. We have also added the HadCRUT4 global temperature anomaly from the 1988-2021 mean. The difference between the temperature anomaly and the TPW anomalies in the blue shaded area is more dramatic between 1978 and 2005 in this plot.
Carl Mears and colleagues have published a satellite microwave brightness record of TPW over the world’s ice-free oceans, from roughly 60°S to 60°N. In addition, to covering only the ice-free oceans, heavy rain affects the signal, and these areas must be excluded. Since it is not truly a global dataset, like NCEP R1 and R2, and it excludes the drier land and polar areas, it has a much higher absolute TPW than the NCEP datasets. But we can compare it to NCEP as an anomaly to the 1988-2022 mean, see Figure 3.
The more recent ECMWF-ERA5 specific humidity plotted in figure 3 has different units than the NCEP or RSS datasets. The ECMWF-ERA5 values plotted are the global area-weighted average specific humidity (kg water vapor per kg of dry air) from 1000 mbar to 1 mbar (roughly .1 km to 32 km altitude). Figure 3 is quite busy, so to make the relationship between the modern ECMWF-ERA5 specific humidity and HadCRUT4 clearer, I include Figure 4 below.
Figure 3 shows that the apparent correlation between global temperature and the RSS TPW dataset is just that—an apparent correlation. The RSS TPW rises much faster than temperatures, and the comparison ignores both polar regions. Figure 5 shows where the RSS data comes from in brighter colors. The darker blue and black areas are not used in the RSS “global” average.
It is pretty clear that while temperature must have some influence on total precipitable water, it isn’t the only influence. Many will argue that TPW estimates from NOAA, ECMWF, and the satellite measurements by RSS are all poor, and they would be correct. But the trends in all the datasets agree after 1960, except in the blue anomalous area. NCEP R1 and the AMO (Atlantic Multidecadal Oscillation) have similar trends as shown in Figure 6. Figure 6, is the straight AMO, and not the detrended AMO index you often see, thus the units are degrees C. It is the area-weighted average sea surface temperature from, roughly, 0 to 70°N latitude and 0-80°W longitude (see here).
The AMO and other ocean oscillations might influence TPW, but it is hard to tell since many have questioned the quality of the early weather balloon hygrometer data, and modern estimates of TPW, like ECMWF-ERA5 show less of a correlation.
Over the short term, say 3-4 years (ENSO spans of time), the correlation between TPW and temperature trends is good, as shown in Figure 3. Figure 3 shows that El Niños and ENSO in general, have a large influence on TPW, but since these oscillations affect the transfer of both heat and moisture from the ocean to the atmosphere, this is not surprising. Over the blue shaded 27-year period, using the ECMWF-ERA5, NCEP R1 and R2 data, the correlation is poor. In this period TPW trends downward as temperature increases, why? I don’t think anyone knows. As seen in figures 2 and 3, the correlation deteriorates in earlier time periods, probably due to poor data quality. The correlation is visually good after 2005. The time period and the data selected matters. We can see why AR5 and AR6 do not provide plots that compare global surface temperature to TPW.
TPW in the Upper Troposphere
As Garth Paltridge, et al. have noted climate models predict that specific humidity will increase in the upper troposphere as global warming continues. Yet, this is not what they see in the NCEP reanalysis 1 data as shown in Figure 7. Paltridge, et al. found that all levels above 850 mbar (~1.5 km) have a negative trend through 2007 in the tropics and southern midlatitudes in that dataset.
Remember the quote from AR6 from earlier in the post? I repeat part of it here:
“Greater atmospheric water vapour content, particularly in the upper troposphere, results in enhanced absorption of LW and SW radiation and reduced outgoing radiation. This is a positive feedback.”(AR6, p 969).
Specific humidity from the more modern ECMWF-ERA5 dataset correlates better with surface temperature at 500 mbar (~5.6 km). This point is made by Dessler and Davis in a rebuttal to Paltridge, et al. However, the correlation between 1985 and 2008 is still poor and neither Dessler and Davis, nor the IPCC address this problem. The area of poor correlation is highlighted in this post with blue shading. At 500 mbar, the poor correlation is moved forward about seven years, as shown in figure 8, but it is still there.
In many ways the opposite trends in figure 7 are counterintuitive since logically we would expect more evaporation with warming. More evaporation should cause a higher TPW, unless rain efficiency increases. From Paltridge, et al.:
“Negative trends in q [TPW] as found in the NCEP data would imply that long-term water vapor feedback is negative—that it would reduce rather than amplify the response of the climate system to external forcing such as that from increasing atmospheric CO2.”(Paltridge, Arking and Pook 2009).
This was also the conclusion reached by Ferenc Miskolczi (Miskolczi 2014). Others, such as Roy Spencer and Richard Lindzen, have suggested that warmer temperature will cause more clouds, which will increase the albedo of the Earth and lower temperatures or reduce the rate of warming (provide negative feedback) as a result. David Enfield, et al. show that rainfall patterns in the United States are closely related to the AMO, yet the climate models do not take the AMO into account. Obviously, rainfall affects TPW. The world is more complicated than the Clausius-Clapeyron relation suggests.
Dessler and Davis rebuttal
AR6 has very little discussion of the Clausius-Clapeyron relation and refers to AR5:
“According to AR5, radiosonde, Global Positioning System (GPS) and satellite observations of tropospheric water vapour indicate very likely increases at near global scales since the 1970s occurring at a rate that is generally consistent with the Clausius–Clapeyron relation (about 7% °C–1 at low altitudes) and the observed atmospheric warming”(IPCC 2021, p 1080).
AR6 provides no chapter number, section or page number in AR5, but we were able to find the following:
“Because global temperatures have been rising, the above arguments imply WVMR [water vapor mixing ratio, that is the specific humidity] should be rising accordingly, and multiple observing systems indeed show this … A study challenging the water vapour increase (Paltridge et al., 2009) used an old reanalysis product, whose trends are contradicted by newer ones (Dessler and Davis, 2010) and by actual observations.”AR5 p 586 Ch 7.
Dessler and Davis point out that the newer reanalysis datasets, like ECMWF, do not show a downward trend in specific humidity and that ENSO is reflected in the specific humidity. This is true. However, AR5, AR6, and Dessler and Davis, do not plot surface temperature versus specific humidity as we have done here. Thus, they do not explain why the trends do not correlate well over the 1978-2008 period. Dessler and Davis point out that:
“Our understanding of upper tropospheric water vapor suggests that it should be in relatively close thermodynamic equilibrium with the surface temperature on time scales of longer than about 1 month [e.g., Minschwaner and Dessler, 2004]. Thus, the water vapor response to a climate fluctuation with a time scale of a few years (e.g., ENSO) should be about the same as for long‐term warming.”(Dessler and Davis 2010)
We have no problem with the one-month equilibrium period, but concluding that ENSO-related warming should be the same as long-term warming is inconsistent with the data shown above for the 1978-2008 period. Data that the IPCC and Dessler and Davis ignore.
Conclusions and Summary
The various estimates of total atmosphere TPW and specific humidity available do not agree with one another very well. Even the two NCEP estimates, both global, vary by 3% over 1988-2022. The NCEP R1 data gathering and processing procedures were very complex and prone to error, which was why NCEP R2 was developed. NCEP R2 was of much higher quality than NCEP R1, but since NCEP R1 goes back to 1948, it has been cleaned up as much as possible, and is still used. It must be viewed with the understanding that the data prior to 1979 is of lower quality.
These global estimates are 16% lower than the RSS ocean-only ~60S to 60N TPW estimate. However, this is explainable. The atmospheric water vapor content over oceans and in the lower latitudes is much higher than over land and in the higher latitudes. The three estimates are compared in Figure 9.
Since about 2005 all the total atmospheric water vapor estimates trend upward, as the AMO begins to flatten at a high level. Prior to 2005, the story is more complex. The longer NCEP reanalysis 1 estimate trends down from 1948 to 1975 in sync with the AMO, but different from the HADCRUT4 and ECMWF trends. All datasets agree that short term ENSO changes (~5 years) are reflected in total atmosphere TPW, but it is not clear that longer-term changes (>30 years) in TPW are related solely to global surface temperatures, they seem to be impacted by other factors as well, perhaps including the AMO.
Global climate models predict that global warming will increase upper tropospheric specific humidity, but reanalysis, based mainly on weather balloon data, shows a decline in specific humidity and in TPW from 1978 to 2005 in the global atmosphere, and a flattening from 1985 to 2008 in the upper troposphere, both are periods of rapid surface warming. The humidity data declines in quality with altitude and lower temperatures, but even in the tropics where water vapor concentration is high at high altitudes, this trend persists. This also contradicts satellite data, but the ability of satellites to separate the signal of the upper troposphere water vapor from the lower is unclear. The accuracy of the specific humidity calculations in the upper troposphere can be questioned. However, both the NCEP reanalysis and the European reanalysis show a decline or flattening during the period of interest.
Consider this quote from Pierrehumbert (Pierrehumbert 2011):
“For present Earth conditions, CO2 accounts for about a third of the clear-sky greenhouse effect in the tropics and for a somewhat greater portion in the drier, colder extratropics; the remainder is mostly due to water vapor.”(Pierrehumbert 2011).
So, we see the crucial role assumed for water vapor in the entire man-made climate change catastrophe hypothesis. CO2 has only a minor role to play in warming the Earth. It is only the assumed, but poorly measured, feedback from water vapor that allows a possibly large impact on our climate to be calculated. Yet, as shown above, this assumed feedback cannot be measured with any accuracy with the data we have available. In fact, over some climate-relevant time scales (~30 years) we cannot even be sure the net feedback is positive. There is a strong correlation between surface temperature and total atmospheric water vapor concentration over short time periods, but it falls apart over, at least some, longer periods. I agree some of the data presented in this post is questionable, but it is data, and data trumps IPCC models. From Paltridge, et al.
“… it is important that the trends of water vapor shown by the NCEP data for the middle and upper troposphere should not be ‘written off’ simply on the basis that they are not supported by climate models—or indeed on the basis that they are not supported by the few relevant satellite measurements.”(Paltridge, Arking and Pook 2009).
Bottom line, water vapor feedback is a huge (66% according to Pierrehumbert) part of the dangerous greenhouse gas hypothesis. Total atmospheric water vapor content is very difficult to measure accurately, but the measurements and trends we have today do not support the hypothesis over all time periods. It seems likely that the Clausius-Clapeyron relation is not the only factor affecting TPW. This casts considerable doubt on the CMIP6 model results, which rely only on Clausius-Clapeyron, human activities, and sporadic volcanism.
AR5 and Dessler and Davis claimed in 2013 and 2010 respectively, that:
“In summary, radiosonde, GPS and satellite observations of tropospheric water vapour indicate very likely increases at near global scales since the 1970s occurring at a rate that is generally consistent with the Clausius-Clapeyron relation (about 7% per degree Celsius) and the observed increase in atmospheric temperature.”(IPCC 2013, p 208)
AR6 simply references these sources and assumes that specific humidity (TPW) responds to temperatures and is a positive feedback. However, the data shown in this post casts doubt on the quote above and the AR6 assumption. Thus, the data we have, poor as it is, does not support the idea that the Clausius-Clapeyron relation works at all time scales.
The R code and other information, including spreadsheets containing the data used to make the figures in the post can be downloaded here.
Download the bibliography here.
(IPCC 2021, p 93) ↑
(IPCC 2021, p 179), (Manabe and Wetherald 1967), and the National Research Council Charney Report (Charney, et al. 1979) ↑
(Lacis, et al. 2010), (Lacis, et al. 2013), (Dessler 2013), (Wijngaarden and Happer 2020) ↑
(Lacis, et al. 2010) ↑
(Wijngaarden and Happer 2020) ↑
(IPCC 2021, p 969) ↑
(Allen and Ingram 2002) ↑
(Allen and Ingram 2002) ↑
(Yu and Weller 2007) ↑
(Mears, et al. 2018) ↑
(Paltridge, Arking and Pook 2009) ↑
(Dessler and Davis 2010) ↑
(Enfield, Mestas-Nunez and Trimble 2001) ↑
(Kanamitsu, Ebisuzaki, et al., NCEP-DOE AMIP-II Reanalysis (R-2) 2002) ↑
(Dessler and Davis 2010) ↑
As a Colorado resident, I want to know what heat and moisture are. But really, it’s frigging cold here and we need all the snow we can get.
I know we could all use the moisture but we are looking at 50% mortality among game animals up here in southern Wyoming because its cold and the snow is exceptionally deep and crusty.
“This was also the conclusion reached by Ferenc Miskolczi (Miskolczi 2014). Others, such as Roy Spencer and Richard Lindzen, have suggested that warmer temperature will cause more clouds, which will increase the albedo of the Earth and lower temperatures or reduce the rate of warming (provide negative feedback) as a result.”
Besides that more clouds causes more precipitation as was pointed out elsewhere, but no mention of latent heat transporting energy out of the global climate system as a negative feedback. Trenberth’s famous radiation budget gives it 80 w/m². That should increase if global precipitation increases.
Yes, it is known as (negative) “lapse rate feedback” and well known and considered by “consensus science”. Does not mean they would have it right.
Prove it wrong.
We know for sure the water vapor positive feedback, with CO2 levels up to 10x higher than today, did NOT cause runaway warming.
More clouds are a reasonable a good guess why.
That’s my guess.
But we don’t need to know why — we just need to know runaway warming never happened, so something limits the water vapor positive feedback.
Just like we don’t need to know exactly why Antarctica does not warm and melt from more CO2 in the atmosphere … as long as we recognize that is exactly what has (not) happened since the 1970s.
Not every climate observation has an explanation.
“we just need to know ….something limits the water vapor positive feedback.”
What if the feedback mechanisms saturate? at different conditions? so that cancellation of some effects is (become) not mutual?
We do know the climate observations, a warming planet, is caused by humans.
You may know it in your heart, but there’s no proof. Changes in aerosols, magnetic field, and solar output all have a better correlation with observed warming than human activity. Unless you are talking about adjusted records as opposed to data; we do know that human mathematical fiddling has caused significant increases to reported temperatures.
In addition to the increase in latent heat transport, I would think an increase in the amount of rain would also result in an increase in the amount of clouds.
Not the thin cirrus type that traps heat, but the thick cumulus type that reflects sunlight.
which will increase the albedo of the Earth and lower temperatures or reduce the rate of warming (provide negative feedback) as a result.”
Looks like they got that wrong.
WV feedback is of course negative, but that is for different reasons.
Thanks for the links, good essays. The IPCC model assumptions cannot withstand close scrutiny.
The IPCC models are programmed to scare people
Not to make accurate predictions
The Russian INM model is the exception
Those pesky Russians just won’t get with the program
(climate scaremongering), so they will be sanctioned and thrown out of CMIP7
INM CM5 is the ONLY CMIP6 model that does not produce a tropical troposphere hotspot. (INM published a paper on this important fact.) Its ocean atmosphere parameterization was carefully tuned to ARGO findings that ocean precipitation is about twice what climate models typically have. So its water vapor feedback is significantly lower, and its ECS is only 1.8C, within the range of estimate error for the observational energy budget ECS estimates.
+1.8 degrees C. is below the IPCC preferred wild guessed ECS range. We can’t have that. What a travesty — a climate model programmed with the goal of making reasonable predictions! That is a sin in modern climate “science”.
If accurate predictions were a goal, the INM model would get 99% of the attention, instead of 1%
Think of weather models.
If there was one weather model that made predictions closer to reality than all the others, would meteorologists ignore their best model? Of course not. But that is exactly what happens with climate (junk) science).
WR: Rud, a question. Are Energy Budgets like Trenberth Fasullo‘s wrong or do most models simply tune ocean precipitation to the wanted result? Or is there something like a ‘standard module’ used for precipitation in most models, one that is not reflecting reality?
Wim, Trenberth’s budget diagram is obviously false. You can tell because he has arrows labeled in Watts that travel from colder areas to warmer ones. That is not how Watts work.
Not to mention that power and energy have different units…
WR: Both cold and warm radiate. But I agree that the makers should have used net radiation to avoid confusion and to show how the surface loses solar-absorbed energy. Doing so would correctly have drawn attention to the most dynamic surface cooler: temperature-dependent evaporation.
Wim, yes, both cold and warm objects radiate energy. Power is another animal…. and “net radiation” is a term only used by folks who don’t seem to understand the difference.
Net radiation W/m2 is used for the difference between radiative energy in (W/m2) and radiative energy out (W/m2).
Wim, we told you that energy and power are different. Then you wrote “energy in (W/m^2)”. Are you paying attention?
So why don’t you write a paper and show it is false. Oh you can’t, OK then.
Jubbly, the paper I would have to write would look a lot like a physics textbook. Plenty have been written, I don’t see a need to write another one.
your fig 8 actually confirms the Clausius Clapeyron 7% increase in water vapor per degree. Considering the wide range of sea surface temperatures and the data is half way to the top of Troposphere, that is an amazingly close approximation.
Assumptions were preserved, so results were replicated.
The point of the post was that relation does not hold for all time periods. The relation does not hold in Figure 8 from 1987 to 2005, does it? This is a climatically significant period with rapid warming. And, as Dessler and Davis, and the IPCC claim, the time to equilibrium is only one month. Something else is happening, it isn’t just Clausius-Clapeyron. That said, I’m sure you can cherry-pick an interval that has a 7% increase per degree of warming. The IPCC is also good at that. I do not find that convincing, details matter.
If you assume, what they assume, you have to be able to explain all exceptions to the rule. Otherwise, abandon or modify the rule.
The peaks match nicely and the lines aren’t very far apart.
You are looking at a difference of .0005 kg/kg only. Just not much on a SkewT diagram at 500 mB
So why don’t you go ahead and show that assumption is true?
If a warmer atmosphere holds more water vapor, the feedback effect has to be positive not negative. You are wrong.
RG, but suddenly convection causes clouds to form and reflect hundred of watts of sunlight back to outer space, compared to a few tens of watts of net IR longwave exchange between surface and water vapour, or even surface and low cloud base. When balance is achieved, the clouds dissipate. So yes WV alone is a positive feedback while proper evaluation of clear sky to cloudy transition during daylight is definitely a cooling effect of large magnitude for a duration of “as long as required” to meet a surface evaporation/cloud Albedo balance.
Maybe we said the same thing differently?.
I call the increased cloudiness (response to the water vapor positive feedback) a negative feedback to the positive water vapor feedback? Say that three times fast. The net result is a smaller effect on the temperature from more water vapor.
Maybe the water vapor positive feedback has a strict limit upper limit. Or maybe it is gradually offset by more clouds. I doubt if the water vapor positive feedback, and whatever effect offsets it, are simultaneous, but they could be.
More clouds in the day would probably block more sunlight
Causing global cooling in the daytime
More clouds at night would probably increase the greenhouse effect of clouds. Causing global warming at night
Everything about the climate gets complicated quickly. … But that doesn’t matter. because we’re all going to die in 10 years after +1.5 degrees C. is exceeded.
You are missing the effect of condensation at higher altitudes. The GHE for water vapor is only important at these altitudes. More low altitude water vapor increases the speed of convective currents which drives those currents higher into the colder regions of the troposphere. The result is increased condensation which ends up reducing the high altitude water vapor. This turns it into a negative feedback.
Increasing water vapor at higher altitudes may not be that important. With CO2 a large percentage of the radiated energy from the surface is absorbed in the low troposphere. This is surely true for water vapor also. The higher the altitude the less radiated energy available for absorption.
And how do we know the water vapor GHE isn’t well saturated?
Read the articles to learn..
RG, due to imprecise language use and comment sorting it is no clear what feedback you are calling positive and what commenter you are calling wrong. In some interpretations of language, your thesis could broadcast a complete misunderstanding of how feedback systems work.
This is as direct and clear as I can write my theory
(1) INITIAL CAUSE OF SOME GLOBAL WARMING
Manmade CO2 emissions cause some amount of troposphere warming (CO2 impedes cooling, to be precise)
(2) POSITIVE FEEDBACK TO (1)
Troposphere warming increases troposphere water vapor, causing more troposphere warming than from (1) manmade CO2 emissions alone
(3) NEGATIVE FEEDBACK TO (2)
A warmer troposphere forms more clouds, which has a net cooling effect, offsetting some of the troposphere warming from (1) + (2),
or limiting the maximum warming effect of (1) + (2).
Andy you said “I agree some of the data presented in this post is questionable, but it is data, and data trumps IPCC models”
IPCC motto appears to be “Never let data get in the way of a good model”
How true. Time and again, I see the IPCC not making the obvious plot (in this case plotting surface temperature and TPW on the same plot) for the topic they are discussing. Then I make the obvious plot, and it shows the opposite of their stated conclusion.
Before I retired, I always made obvious plots, whether needed or not to make my point. If I didn’t someone else would and make me appear careless or lazy. Word to the wise, always make the obvious plot, not doing so is a blazing red flag.
I have the same problem with glacier and sea level data. CMIP6 model ensemble mean shows no warming from 1850 – 1910 but glaciers retreating and sea level clearly rising much earlier.
In the following plot I have calibrated via linear regression (C20th) sea level rise and glacier retreat and introduced a lag (via cross-correlation). All series are baselined to the period 1961-1990. Note how badly the CMIP6 fits HadCRUT4 when re-baselined and how the glacier retreat/sea level rise (presented calibrated to temperature via a lag and regression) are (a) linear for a long period and (b) appear to both rise prior to the CMIP6 temperature increase post 1910 by anywhere between 60 – 100 years.
That’s why IPCC largely ignore glacier data and mostly dropped sea level, especially rate change arguments, after AR5 Figure TFE.2 Figure clearly showed the sea level rate was higher or similar in the earlier part of the C20th as compared to late C20th and the models only fitted the latter.
Its also why the IPCC largely ignores the Holocene.
Moral – if you want to know where to look for data contradicting the IPCC look at what they don’t talk about.
That’s not right
Models are used for predictions of the future climate
There are no data for the future climate
Therefore, models are not based on relevant data.
Models are based on theories and assumptions,
They could also be based on high level data from present and past climates, but with no ability to know exactly how much climate change was caused by each climate change variable. Just a list of the usual suspects.
Whatever theories, assumptions and high level historical data are used to program models, the result is predictions of a global warming rate twice as fast as even the cherry picked 1975 to 2023 period. With the exception of the Russian INM model.
Models predict a fast warming rate not observed in recent centuries, that allegedly takes 200 to 400 years (ECS)
It’s misleading to claim the climate confuser games are based on data.
But maybe you could say that about the Russian INM model?
tl;dr. but the simple fact is that the climate is stable.
stable systems have negative feedback loops; items that return the system to stability after a change. they also have buffers that resist change in the first place.
and yet all we hear about is positive feedback loops – ones that destabilise the system further.
this imbalance in scientific reporting is clearly bullshit, and is the fundamental clue that climate change reporting is fake.
(nb, negative and positive are interchangeable relative vectors but must be used consistently)
There can be positive climate related feedbacks that cause negative feedbacks to limit their effect.
An unlimited positive feedback would have ended all life on our planet.
that didn’t happen.
So all feedbacks combined have to be neutral or negative.
But that does not mean a water vapor positive feedback can’t exist.
The EMCWF atmosphere dataset breaks atmospheric water into 5 categories, cloud ice, cloud liquid water, specific humidity, rainwater, and snow water. Your conclusion depends upon the variation in these proportions. If clouds increase and/or change altitude, if rain and snow change, the feedback can go from negative to positive and back again, even if the total atmospheric water stays the same. Making categorical statements about water vapor being positive or negative is not possible, a critical flaw in the IPCC reasoning.
Satellite data (CERES) says it is negative overall, but how it responds to surface temperature is hard to say overall. See figure 4 here:
Clouds and Global Warming – Andy May Petrophysicist
It is about -19 W/m^2 overall the past 20 years, but in response to surface temperatures globally, no one knows.
That said, I think Lindzen’s work on the tropical Pacific is pretty good, his “iris effect.” It suggests that, in that location, surface temperatures cause a reduction in cirrus, which allows more surface IR to escape, a negative feedback. See here:
Climate Sensitivity to CO2, what do we know? Part 1. – Andy May Petrophysicist
Here’s a big adventure for us all – we’re going to The Moon.
And even more adventurous, in or roundabout the year 1850.
Bring some bionculears, we’re gonna do some Earth spotting.
(All through this, the absolute values are irrelevant, we’re looking for differences and will calculate an absolute at the very end.
To see if it is reasonable and makes sense – as Monckton would say: an Arguementeum Absurdium
‘Differences’ are TheNameOfTheGame here aren’t they = that Earth will be ‘different’ from SomeTimePast compared to SomeTimeFuture)
So and in 1850 as viewed from The Moon:
From that we can calculate an Emissivity figure for Earth = 0.8716
That *must* apply. There is no other way Earth can dissipate Sol’s input. No convection. No conduction.
It is proposed that in SomeFutureTime:
So what we now do is assume that Earth’s Emissivity is unchanged (The GreatAndTheGood are not saying otherwise)
…and we run Stefan’s formula (he is the ultimate authority in all this) and we discover that for the new temperature and an unchanged Emissivity:
Earth will be radiating an extra 14.4Watts
(For the Trivia Obsessed, I make that to be 10 Million Hiroshimas daily
(Taking 1H = 60TeraJoules. Some say 50, some say 75)
How does that work – where are the extra Watts coming from?
It is in fact all quite reasonable, there’s nothing absurd in there:
Strangely absurdly, we were told recently by A Sputnik (effectively a Moon-based observer) that Albedo over the last 20 years has dropped – allowing in an extra 8Watts
To first approximation, would that give half of the proposed 3°C temp rise and is seemingly, exactly what we’ve got.
Methinks ‘Houston’ has the problem, not everybody else.
The problem with albedo is that the planet absorbs energy at near visible wavelengths, and emits long wave infrared (LWIR). The absorption/emissivity of the planet at those wavelengths doesn’t have to be the same.
On the other hand, having said the above, that which affects albedo also affects LWIR emissivity. So, you can’t say that, if the albedo changes, that the change won’t be offset by a change in emissivity.
Is this what “Newark” means?
Newark-on-Trent, also called Newark, town, Newark and Sherwood district, administrative and historic county of Nottinghamshire, east-central England. It lies along the River Trent at the crossing of the Roman Fosse Way road with the modern Great North Road (A1).
I know you’re not from Newark, Nu Joisey,
Thanks for an interesting analysis, and for the source data and R code.
The focal point is the poor or contra-intuitive correlation between TPW and temperature over some periods, such as 1978 – 2005.
However, I believe a lot of essential information is lost in the global averaging.
I’d suggest to look at the gridded data, and check for correlations on a map. Maybe we have some patterns there, e.g. some latitudes show correlations going one way and other latitudes going another way. Differences between land and ocean.
I made a lot of maps during my study, I just didn’t put them in this post. I may use them for another post in the future. The R code will allow you to make more, if you like. Here is one, it is specific humidity in 2022, at 1000 mbar (about 100 meters above the surface.
Here is another, at 250 mbar, when water vapor first appears. 250 mbar is about 10.5 km. Lots we can do with the ECMWF-ERA5 data!
Why people use the adjusted hadcrut 4 data is beyond me. It is outright fraud in my view. 1921 and 1934 were cooler than the 70s? I don’t think do.
You might be correct, but the HadCRUT4 data is much better than the clearly fraudulent HadCRUT5 data.
I’m with you, Nelson.
My main gripe with the bastardized Hockey Sticks like the Hadcruts is with how the Early Twentieth Century is portrayed, not so much with them after 1979. After 1979 the Hockey Sticks do continue to bastardize the temperature record, as compared to the UAH satellite record, but at least we can all see these differences and they are not that much different anyway.
The only thing the climate change alarmist temperature mannipulators got out of the modern-day (satellite era) bastardization is it enabled them to dethrone 1998, as the warmest year in the satellite era, which then enabled them to claim that the temperatures in the years after 1998, were the “hottest year evah!” year after year (about 10 “hottest year evah!” claims during the period from 1998 to 2016) as they bastardized the temperature record by a tenth of a degree or two.
See if you can find any years after 1998 that could be described as the “hottest year evah! when viewing the UAH satellite chart:
As you can see, none of the years between 1998 and 2016 can be described as the “hottest year evah!” going by the UAH satellite chart. That’s why NOAA and NASA Climate don’t use the UAH chart. They can’t lie about the climate if they use UAH data. They can’t scare little children and clueless adults if they use the UAH data.
“The various estimates .. of TPW … do not agree with one another very well.”
Kip, over the last year WUWT has kindly hosted a number of discussions about uncertainty in measurement (and deduction). Many of us have stressed that a central use of uncertainty is the rejection of submitted papers that handle uncertainty and its deductions wrongly. We have seen two camps, one of academics advocating calculation of uncertainties using Law of Large Number type reductions of estimated uncertainty while the other camp objects to this reduction in practical cases where the numbers come from non-IID sources – not Independent identically distributed random variables.
If authors like Drs Dessler and Davis had calculated proper uncertainties, they might have found their numbers did not tell a story that would pass peer review (if the reviewers also understood uncertainty).
So, the papers would not be published. Think as well about the persist authors pointing out uncertainties with global temperature estimates like HadCRUT. Some critics.might hold that the temperature errors alone are large enough to explain why matches with TPW are mismatches.
But then, the standard of Establishment climate research started off poorly and has not got better. Senior people who could lead improvement are sitting on their hands. Geoff S
Establishment climate “research” started with a conclusion and worked backwards to support it: “Manmade CO2 is evil”
Starting with a conclusion converts science into politics.
Who is “Kip”
I seem to get confused with Kip and other editors a lot. Not sure why.
“We have seen two camps, one of academics advocating calculation of uncertainties using Law of Large Number type reductions of estimated uncertainty while the other camp objects to this reduction in practical cases where the numbers come from non-IID sources – not Independent identically distributed random variables.”
The Law of Large Numbers (LLN) is only an indication of how close you are to the population distribution. If the population mean is uncertain or inaccurate the LLN can’t reduce that uncertainty or inaccuracy. If your measurements are uncertain or inaccurate then the population mean will be uncertain or inaccurate. You can’t fix that by averaging.
The *only* time the average is the true value is if you are measuring the same thing multiple times using the same device with no systematic bias and under repeatability conditions. That should, in theory, generate a Gaussian distribution of random error which would cancel, i.e. plus errors and minus errors are equal.
This is the problem with climate science. They *always* assume measurement uncertainty is random and Gaussian with no systematic bias so the measurement uncertainty cancels and can be ignored. That just isn’t likely when using thousands of field measurement devices measuring different things.
“Senior people who could lead improvement are sitting on their hands.”
They’re reading web comments while they should be working…
My apologies for confusing your name with Kip’s.
I might have been concentrating too much on writing the story.
If water vapor feedback was positive, then the “runaway greenhouse effect” would have occurred long ago.
As a (unfortunately not named, so he/she cannot get the proper recognition) geologist put it:
“If CO2 could do what they say it can do, then the oceans would have boiled away or frozen over a long time ago.”
The water vapor feedback is positive
Your conclusion is wrong
Something else limits that positive feedback
So that total, net feedbacks of all kinds are neutral or negative.
Nope, your conclusion is wrong. It is the high altitude water vapor that matters and it is doing down.
From the article: “The longer NCEP reanalysis 1 estimate trends down from 1948 to 1975 in sync with the AMO, but different from the HADCRUT4 and ECMWF trends.”
The AMO has it right. The cyclical movement of the AMO is very similar to the cyclical movement of the U.S. regional chart, Hansen 1999:
From the article: “So, we see the crucial role assumed for water vapor in the entire man-made climate change catastrophe hypothesis. CO2 has only a minor role to play in warming the Earth. It is only the assumed, but poorly measured, feedback from water vapor that allows a possibly large impact on our climate to be calculated. Yet, as shown above, this assumed feedback cannot be measured with any accuracy with the data we have available. In fact, over some climate-relevant time scales (~30 years) we cannot even be sure the net feedback is positive.”
Obviously, the science isn’t anywhere near settled, yet our fearless leaders are bankupting our nations in an effort to reduce CO2, when there is no evidence that reducing CO2 will have any discernable effect on the Earth’s climate.
We are engulfed in a huge mass delusion about the Earth’s climate fueled by liars and distorters of the truth, who do so for various selfish reasons.
Our governments have been caught lying so often recently, usually to make politicians rich, I’ve wondered if it is unusual. Or, perhaps, modern communications have just allowed us to catch them lying more often? Hard to say, but we need to make sure they’re not allowed to control much of anything. As a long-time investor, I’ve noticed that we need to consider government much more in investing these days, a dangerous sign.
The AMO does appear to be one of the key factors driving climate. If you look at Miskolczi’s analysis it started with 14 years of +AMO then 33 years of -AMO, finally ending with 13 years of +AMO. I think this is why his opacity trend came out almost perfectly flat. If you look at satellite data, it misses the early +AMO, starts in the -AMO phase and ends with about 25 years of +AMO data. This skews the trend upwards.
I suspect the early radiosonde data is perfectly fine. Once you realize it is different due to the AMO phase, it all makes perfect sense. If the AMO is key then we will find out fairly soon. The current ~30 year warm phase should end in the latter half of the 2020s.
I have only read the beginning of the article and will read the rest later.
After so many years at +1.5 to +4.5 degrees C. ECS, the IPCC arbitrarily changed to +2.5 to +4.0 a few years ago … and now it appears they are at +2 to +5 according to this article.
That’s news to me. Not that a new wild guess of ECS is any better than the old wild guess of ECS.
What was not included at the beginning of this article is to specify that ECS takes about 400 years to fully develop, with most of the alleged warming in the first 200 years. And the worst case RCP 8.5 CO2 growth rate scenario is usually used.
The TCS prediction for 70 years in the future, when using the reasonable RCP 4.5 CO2 growth rate scenario, predicts about half the warming rate at ECS with RCP 8.5.
Due to deliberate IPCC propaganda techniques, very few people realize the +3.0 ECS is a worst case estimate (aka wild guess) for 400 years in the future.
People are led to believe ECS is for 50 to 100 years in the future, and they are never told about the TCS prediction for 70 years in the future..
People are not told there are many natural causes of climate change that can add to the warming effect of, CO2 or reduce the effect of CO2.
People should be told that from 2015 to 2023 other causes of climate change completely offset any warming caused by CO2. The result is no warming at all for the past 101 months (UAH data)
People are also not told the next +50% CO2 increase will cause LESS global warming than the last +50% increase of CO2. And that we can only guess what warming was caused by the last +50% increase, because there are so many other causes of climate change, it’s impossible to measure exactly what any specific cause of climate change. We know the greenhouse effect increased, for example, and more CO2 is a likely cause, but increased cloudiness can also increase the greenhouse effect.
Comment says”…add to the warming effect of, CO2…”
There is no warming effect of CO2.
A science denier strikes again
Radiative effects notwithstanding, water vapor represents massive dynamical heat transport. A non trivial hydro dynamic response.
Does the hydrostatic equilibrium height of the convecting troposphere change, or does the fluid system reconfigure (rearrange)?
The water vapor a non-well mixed gas, and highly variable in space and time. Not like a blanket, but like a series of concentrated strings or rivers in the sky, surrounded by relatively dry air (above and adjacent). Moist dynamics.
Practically limitless degrees of freedom there in the associated thermodynamic mechanisms. A difficult challenge for global circulation computationalists. Edward Lorenz recognized the challenge.
Good review, Andy May. Thank you.
The Clausius-Clapeyron relation is discussed.
I would like to point out numerically how energy transport effectiveness is powerfully influenced by atmospheric water vapor. I refer to this reanalysis web page for visualization. It’s not animated, but even so the variations and circulations over the surface are obvious.
A Precipitable Water value of 25 kg/m^2 represents latent energy storage of about 17,400 Watt-hours per m^2. Roughly, the assumed 7% per deg C increase would be a boost of a bit over 1,200 Watt-hours per m^2.
So what? The carrying capacity of the atmosphere to transport absorbed energy poleward is boosted by that amount. And at any location, the capacity to convert latent energy into overturning motion (especially in convective weather) is likewise boosted by that amount. The dynamic performance of the atmosphere as the working fluid of a heat engine is promoted strongly.
So about water vapor and its radiative feedback effect, we can be emphatic that it’s not static. The motion changes everything about where to expect the absorbed energy to end up. In my view, this is evidence of a strongly self-regulating characteristic of the climate system in respect to surface temperature.
Very good point! Variations in meridional transport, or zonal transport for that matter, of latent energy will affect emissions to space and incoming energy over time. This was on my mind as I researched this topic, but I had nothing definitive to say, so I didn’t address it in the post. But you are correct, WV feedback to warming or cooling is constantly changing. It changes with rain, snow, ice, and clouds. It is definitely not a simple function of surface warming as the models assume.
Absolutely, the atmospherical upward emission of longer waves is not coincident in time (c) nor in x,y lat/long coordinates with the initial (radiative equivalent) surface upward flux of that power.
If one wishes to conceptualize the system as merely upward and downward vertical beams of longer waves, it is only the transmitted flux density from the effective radiating surface direct to space for which the radiation enthusiasts can provide support with their averaging of variable optical depths.
While the maximum solar input power is in the tropical zone, the maximum surface transmitted flux density to space originates from about 60 degrees latitude. This zone represents the sweet spot of atmospheric transparency vs surface radiating temperature.
The bulk of the net upward emission is from atmosphere and is therefore coupled to the dynamical transport process of moist air and phases changes in the turbulent fluid atmosphere.
Overall, if a negative feedback regime exists one prediction is that the system will strive to be transporting surplus heat to around 60 degrees north where the land surface there offers the best opportunity for ballistic radiative transmission to space. The high relative efficiency of cooling there should promote the fluid dynamic transport of surplus heat to that zone.
“Ballistic” – I like that word! 🙂
Andy, thanks for all the good info, an interesting read.
Some additional thoughts – quite a bit and sorry for that – but worth reading I think:
1. The Clausius-Clapeyron relationship was established by making measurements in a laboratory at the surface level. We can use the relationship safely for the lowest layer of the atmosphere, the layer that ‘sticks’ to the surface, and the layer where convection does not play a large role: most times the lowest 100 meters of the atmosphere.
2. When large-scale convection takes place, a relatively narrow column of warm wet air rises, enhancing specific humidity over the affected part of the column. But after condensation, large quantities of dry air remain and after being cooled in the upper air those large quantities of dry air descend over a wide surface area aside from the narrow rising column. The largest scale on which this process happens is a Hadley Cell.
3. A warmer surface means a higher humidity above wet surfaces. In several ways, this humidity causes convection above 15 degrees Celsius, and above 25 degrees ‘Turbo Convection’ is caused which strongly cools the surface. The warmer the surface, the more speed and endurance of convection are enhanced, but the surface area of the wet Inter Tropical Convergence Zone (important for ‘averaging’) is not enlarged that much. One could say: “the cooling wheel just turns faster”.
4. But by enhanced convection (at least in the Hadley cells) the quantity of dry air produced is firmly enhanced and so is the surface area where it descends. Dry air enables more sunshine to enter and warm the oceans. This ocean warming happens until other correcting processes take place. For example: after ocean warming, the process of high convection will start earlier in the day, as shown by Willis Eschenbach by data of the TAO buoys.
5. As at changing temperatures and humidities high- and low-pressure areas are changing in both strength and position, winds will change and this will affect ocean currents. A reshuffle in ocean patterns will take place, in turn leading to changing weather patterns, again changing ocean currents, etc. etc.. Those processes take place on every time scale and therefore are rather ‘chaotic’ and unpredictable.
6. As a result of the change in the speed of convection the quantity of dried air is enhanced, leading to an average specific and relative humidity lower than expected for the higher temperature.
7. With respect to surface temperatures: any enhanced evaporation cools the surface. Enhanced convection results in higher wind speed over large surfaces that strongly affects surface cooling by evaporation, but does not so much affect total atmospheric specific humidity while average relative humidity even can go down because of the larger quantities of dried air.
8. Of course, clouds (H2O) play their role as well in processes cooling the surface: enhanced tropical clouds (after high convection) shade the surface and diminish solar shortwave energy reaching the surface. If greenhouse warming initially warms the surface by longwave radiation, enhanced tropical clouds eventually diminish the quantity of solar shortwave radiation reaching the surface. A stabilizing mechanism.
9. Paleo data show: over a longer time frame the tropical/subtropical zone remains incredibly stable in surface temperatures. H2O stabilizes.
10. By changes in salinity and by changes in wind patterns downwelling deep water is affected which is changing deep ocean temperatures over longer periods. Milankovitch cycles also play their role, also in changing salinity and so in changing the vertical movements in the oceans. Over Milankovitch cycles present cold deep oceans cool respectively warm enough to finally result in Glacial and Interglacial periods.
Overall: the H2O molecule sets temperatures everywhere at the surface. The H2O molecule is able to do so while in the atmosphere H2O is a non-mixed greenhouse gas. The IPCC has excluded non-mixed greenhouse gases from their study because water vapor H2O is [at] the base of all of the weather, of all ocean currents, of all clouds, and of all surface temperatures.
Understanding the cooling and temperature stabilizing role of the H2O molecule would take away all climate scares.
Thanks Wim, good comment. I agree that water vapor is the primary and strongest stabilizing agent in the atmosphere. Its many forms, clouds, ice, liquid, gas and its high latent heat capacity make it a powerful agent of stability.
As I have pointed out for years, even on this site, the use of temperature units is completely inappropriate as a measure of heat content (Q) of the air given heat energy has two components, latent and sensible. Water vapor greatly influences the latent heat content of air. The idea that the water vapor content of the atmosphere does not appreciably change from year to year is the linchpin of the fraud committed by the AGW crowd/cabal.
Anyone who is a competent meteorologist or an HVAC engineer/tech knows that heat content (Q) cannot be measured in K, C, R or F units. It (Q) must be measured in Cal or Btu, anyone who says otherwise doesn’t know what they are talking about or is being deceptive.
The reason the AGW fraud has gone on as long as it has is due to accepting the premise of using the wrong unit of measure.
Richard Lindzen made this very point recently. Average people (Policy Makers especially) are scientifically illiterate, ignorant of basic thermodynamics (but well ‘educated’ about polar bear populations) and embarrassed about it, so they seek the comfort of a simple explanation.
Once you are committed to the dogma, you can only save face by drinking the Kool-Aid.
Or as Mark Twain said “it’s easier to fool someone than to convince them they have been fooled.”
Glad you mentioned Miskolczi. His research was based on 1948-2008 radiosonde data which shows a constant overall greenhouse effect (opacity). This is achieved by a negative water vapor feedback to compensate for the increases in CO2/CH4 and is driven by enhanced convection. No actual warming occurs due to this change but you do end up with a little more precipitation.
One of the problems is the fact we have seen warming. Any changes for whatever reasons will also affect the data being collected. It all gets down to cause and effect. Climate science has predetermined the cause for political reasons. That skews everything they do. However, once you allow for natural causes, the data itself makes a lot of sense.
And then there are the clouds adding to the puzzle.
Those pesky clouds that can’t be handled directly in global circulation models and have to be parameterized, thus providing an opportunity for subjectivity to creep in and bias the other calculations.
Great discussion demonstrating the much higher complexity of the relationship of water in the atmosphere and temperature than the IPCC and climate alarmists admit too. The mentioned effect of varying cloud cover can clearly overide “greenhouse” warming if it is significant. Additionally increasing precipitation that comes as snow and increases surface albedo will reduce absorbed incident solar radiation (energy into our climate system) where snow and ice persist.
As is usual what we know and understand is dwarfed by the mysteries yet to unravel.
Oh, am I sick of this narrative. Clausius-Clapeyron is an equilibrium relationship. Let’s examine how the atmosphere is humidified. 1) Water vapor is transported from moist soil to the air-soil boundary. 2) Water vapor is transported across the sea-air interface. 3) Water vapor is transported out of plants and into the air. 4) Water vapor is transported from source regions (ocean,lakes,moist and vegetated places) into the air over land — maybe thousands of miles away….
Everything is transport dominated. Transport is non-equilibrium. Atmospheric water vapor has to be the result of transport processes.
“A corollary to the Clausius-Clapeyron relationship is that as the specific humidity (total water vapor in the air, the units used here are kg of water vapor per kg of dry air) goes up precipitation also increases by about the same amount, keeping relative humidity about the same.”
Sorry in advance if my issue is resolved, but my copy-paste buffer filled before I finished reading the article – the above statement holds true -only-if- air temperature remains constant.
It seems I’m about to read a proxy war between assumptions using C-C humidity relationship based on those (in the constant-temp case not-explicitly-stated) assumptions.
The precipitation corollary is obviously incorrect, but this assumption has been around since the 1960s and lots of people still believe it. It traces back to Manabe and Wetherald, 1967, Thermal Equilibrium of the Atmosphere:
The Warming Papers: The Scientific Foundation for the Climate Change Forecast – Google Books
The assumption of constant relative humidity as CO2 “warms the atmosphere” is flawed. As the atmosphere warms, the saturation humidity increases (the Clauseus-Clapeyron equation), but constant relative humidity would require a higher absolute humidity (g water vapor/m3 air).
The problem is, where does the extra water vapor come from? It is evaporated from a large body of water, from oceans or large lakes. Evaporating this water requires heat, which represents about a 50 – 70% negative feedback on the initial atmospheric warming effect of the CO2, due to the fact that the heat of vaporization of water is very large compared to the specific heat of air. This negative feedback due to heat of vaporization is often ignored in climate models.
The other problem with the “constant relative humidity” theory is what happens over land, where the sources of water for evaporation are very limited? Near the coasts, humid air can be blown from over the oceans to over land, but what happens over a large continent far inland? Raising the air temperature there decreases the relative humidity, if there is no large body of water nearby.
(PDF) Global Circulation Models (GCMs) Simulate the Current Temperature Only If the Shortwave Radiation Anomaly of the 2000s Has Been Omitted (researchgate.net)
Ollila showed that his model without water feedback matched HadCRUT4 very well.
The warming is predominantly being caused by decreasing and thinning cloud cover allowing increased downwelling short wave radiation.
“”The warming is predominantly being caused by decreasing and thinning cloud cover allowing increased downwelling short wave radiation.””
The warming is being caused by the 43% increase in co2 levels over the last 70 years, fixed it.
Attached are all the global temp data sets on the one graph. They all show there was a warming event in 1997/98 and another around 2015/16. Between 1998 and and 2015 there was no warming (a temperature hiatus). Since 2016 there has been another temperature hiatus. There was a 3rd warming event in 1983/84 but its effect is not clear because of global volcanic cooling.
The NASA CERES data between 2001 and now has shown what happened during the 2015/16 warming event.
El Nino caused a decrease and thinning of cloud cover causing an increase in absorbed shortwave radiation and also an increase in long wave radiation escaping to space. El Nino is causing these warming events.
CO2 cannot cause the sort of warming that is seen in these warming events.
The global warming is predominantly natural. Without the El Nino warming events there is little global warming in these data sets.
Articles like this make my head hurt. Not because it is wrong or poorly written. On the contrary, the content is excellent. It’s just that the focus is wildly unsuitable for convincing anybody but the already convinced.
An example… I am sure that making cake is full of wonderful science, but in the end of it all, what matters is; does the cake taste good? Nothing more is important.
We continually examine climate entrails to determine the shape of the elephant. What matters is whether or not our planet is gaining or losing energy and nobody is even measuring it. Everything else is weather.
It is definitely getting warmer, and the science says that is due to humans. It has been that way for decades and no one has proved the enhanced greenhouse effect, the reason for the warming, wrong.
Funny comment as we note that even the Adjustment Bureau couldn’t massage 2021 higher than “7th hottest ever”, which means it’s cooling.
They did massage 2022 to 4th place in the sweepstakes but that too is indicative of cooling
In the presence of steadily increasing co2.
So I do not down vote you
I simply laugh.
And it’s not up to science to disprove something that isn’t happening.
It’s up to you and the Scientologists to prove that it is.
There is no troposphere hotspot, and unadjusted temperature does not track with co2.
So your theory has already failed.
I have an issue with the initial statement by the IPCC regarding the Clasius-Clapeyron equation. their statement is quoted below from the article.
The IPCC estimates the water vapor feedback using the Clausius-Clapeyron relation. The relation states that as temperature increases, more evaporation occurs and atmospheric water vapor increases, especially in the upper atmosphere.
The Clausius-Clapeyron equation is only tangentially about that. The actual Clausius-Clapeyron equation is about thermodynamic relationships of two phases and the temperature, vapor pressure, volume, and the energy required to achieve the phase transition. The exact formula is as follows:
dP/dT = L/(TdeltaV) where P is the vapor pressure of the substance, T is the absolute temperature, L is the heat of the phase transition, and deltaV is the change in volume for the phase transition. This equation often gets approximated to dP/dT = PL/(RT^2) for liquid to gas transitions where the molar volume of the liquid is small in comparison to the molar volume of the vapor.
Integrating this equation shows that ln(P) is proportional to 1/T, which is what they are using to determine the equilibrium increase in humidity as the temperature increases. This was already known. Meteorologists have used this equation with constants for water to calculate the vapor pressure of water to calculate the saturated absolute humidity of water vapor in air as a function of temperature, in other words, what the absolute humidity of air would be at equilibrium at a given pressure and temperature, well-mixed and waiting a while. This is not equivalent to the statement quoted above because evaporation is not an equilibrium process but a complex mass and heat transfer process. This equation gives the limit. Even when it is raining, the relative humidity is rarely 100%.
Chemical engineers use a much easier equation to calculate the vapor pressure of water from 273.15 to 373.15 K. Now you can get very accurate values from the NIST webbook. Note that a different equation or constants has to be used to calculate the vapor pressure of water in equilibrium with ice.
Weaker solar wind states drive a warmer AMO via negative NAO regimes, as from 1995, and the warmer AMO is associated with a decline in low cloud cover, and an increase in surface wind speeds over the oceans.
That’s an amplified negative feedback.