Along the same lines, I'd much appreciate a close look at the conclusions reached by Vinos and May. If warming effects of the CO2 blanket are dwarfed by variations in heat loss at the poles, and - as is becoming apparent - the CO2 effects themselves look to be less than originally thought, that's important.
I've come up with a general metric I use when I read climate science, something to capture the level of "trust" I have in its scientific integrity. Tier 1 science are those things that investigate the past, like observations and measurements and things we can generally prove; I rate this between an 8 and 10. Tier 2 science is modeled science where the scientist is projecting past data forward and making guesses; so that's between a 4 and 8 on the scale. And then Tier 3 science is attribution/even attribution science, as I trust almost none of it - between a 1 and 4 on the scale. Honestly, attribution science feels like a sophisticated game of pin the tail on the climate donkey.
This discussion you've laid out about the relative validity of satellite observations and on-ground measurements seems like it falls somewhere close up to Tier 1: as in, this is truly for the scientists to debate. It does certainly take more of the legs out of the "the apocalypse is nigh" argument, but as you've pointed out those scenarios are not even worth talking about more (were they ever?) I trust that these scientific metrics will be debated between those who understand it the most - namely you scientists - and then put it into words most of us can understand. Maybe wishful thinking...
More importantly Marc, many of the papers out there are wrong or hopelessly biased. I discussed this last January in a long post at Climate, Etc. This fact is very well known even by many scientists themselves, yet there are immense structural problems that block any effective action to make the literature more reliable. There are even now according to Ioannidis hundreds of thousands of zombie trials out there in the literature where there is no real data that underlies the conclusions.
Marc: It's not just whether the data is past or present or future. Its whether the data covers the necessary span of geography and time, and whether the interpretation of the data requires leaps of faith. For example, consider the estimation of past average earth temperatures back a thousand or even two thousand years. Some climate scientists use "proxies" to infer ancient temperatures. A proxy is physical evidence today of climate many years ago (like tree rings, or isotopic differences in ice, or many others). A few decades ago, Michael Mann and several others, combined several proxies from different locations across different time intervals and came up with charts of earth average temperature over the past couple of thousand years (the so-called "hockey stick"). Unfortunately, the geographical and time coverage was grossly inadequate. In addition, the method to statistically combine the individual proxy data was faulty. But worse than that, many proxies don't fundamentally work well. Nevertheless, this group aggressively published and disseminated their hockey stick and it became widely accepted within the alarmist community. It was later shown that the whole study was highly dubious, and the revelation of emails in "climategate" showed these scientists were highly biased to alarmism. The point is that past or future, most climate data is not simple to interpret, is often severely lacking in coverage, and requires many decades to derive a signal above and beyond the ordinary fluctuations in weather. So I maintain that most science data is in tier 3 - between 1 and 4 on a scale of 10.
Very good then, all the more reason to assign those trust levels to it. I remember the crazy hockey stick discussion and all that came of it. I'd be interested to hear Dr. Pielke's response to it all...
You can find a full discussion of the hockey stick and climate gate in (pardon the shameless push): D. Rapp: Assessing Climate Change: Temperatures, Solar Radiation and Heat Balance (Springer Praxis Books) 3rd ed. 2014 Edition
Clayton: The exact way that increasing CO2 produces an imbalance in the earth's power budget is complex, and there have been many simplistic reductions of this complexity, with variable degrees of credibility.
One simplistic approach was to note that absorption of IR by CO2 in the 13-17 micron band in the atmosphere is saturated, and as the CO2 concentration is increased, additional absorption occurs in the "wings" of the main absorption band, and as the CO2 concentration increases further, the gains in absorption per unit increase in CO2 concentration decrease. Hansen et al. (2000) derived a logarithmic function for increased absorptivity vs. increased CO2 that has been quoted widely. Hansen et al. converted that increase in absorptivity to an increase in "downward forcing". I wish I could post the plot! But that logarithmic curve looks pretty linear from CO2 going from 400 ppm to 550 ppm.
Linden (2007) objected to the simplistic notion that greenhouse gases “inhibit cooling of the Earth by thermal radiation, and serves as a blanket which causes the Earth to be warmer than it otherwise would be". The lower atmosphere is relatively opaque to IR radiation but as the altitude increases, the density decreases and transmission of IR improves. Lindzen defined an altitude sufficiently high that the optical depth for IR is about 1 so that transmission of IR is attenuated roughly as e^-1. This is a region of the atmosphere that can radiate power from the Earth to space. He described the effect of CO2 as raising the principal altitude where the earth radiates thermal power to space, and when that region is cooler, the earth radiates less power.
Whatever the actual physical mechanism is, the IPCC used some method to convert CO2 increase to temperature increase. Empirically, if you examine the SSP scenarios they are linear in delta-T from delta-CO2 and the linearity is essentially the same as that prior to 2015.
I would like to post a general question I've had for some time regarding urban heating and its effect on temperature estimates. People seem to interpret the urban impact on temperature as being a result of albedo changes due to buildings, asphalt etc. My question is what contribution does the vast energy consumption that occurs within cities play relative to albedo effects. Cities consume energy heating homes, cooling homes, in transportation systems, manufacturing, and lighting etc which I assume eventually turns into heat. A city consumes a known amount of electricity each day. If you know the area of the city one could easily calculate the watts per square meter that gets added to incoming solar energy within the city limits. Of course you would need to add energy consumption from the direct burning of fossil fuels to the total. Is this significant? Is there a flaw in my reasoning that I'm missing?
One of the main reasons for using satellites for temperatures sounding is that you get a uniformity of reading in space and time that you cannot achieve through using individual measurements across the earths surface by different nations. Therefore, to degrade the value of the satellite measurements because they happen to run against the results you are trying to propound sounds a bit sick to me.
I can understand how a large number of temperature measurement sites, however faulty for one reason or another, can come up with an approximate answer. Believing that good temperatures can be extracted from spectral measurements in the troposphere requires an act of faith.
I worked on the selective chopper radiometer which was flown on ERTS Nimbus 4 and 5 satellites around 1975 and the whole point of the exercise was to carry out temperature sensing of the atmosphere at specific levels. You would need to look it up to learn more. I believe that the temperatures derived were accurate and consistent across the whole globe which was covered once per day. Obviously the temperatures were for a specific height above the earth. Whether there was criticism of the method I cannot say because I moved off the project after a few years. This was a joint project between the Clarendon Lab, Oxford, and Heriott Watt university Physics Dept involving John Houghton and S D Smith.
Climate science generally does not have an adequate theory for the tropics. The moist adiabat theory is what suggests the hot spot and that theory is pretty badly wrong. Climate models use very coarse grids and simply cannot resolve tropical convection. This phenomenon is what determines the response to greenhouse gases in the tropics.
What is amazing is that climate scientists and modelers have surely known this for a very long time. Why hasn't it received adequate attention?
People who's career and livelihood depend on pursuing a field of endeavor of dubious veracity continue to do so because they don't have a better option, and besides, they are p]aid to do it. I used to know a fellow who had a black attributed to Ken Kruishank that said:
If a committee is allowed to discuss a bad idea long enough, they will eventually adopt it because of all the work they put in.
The equatorial tropical ocean is where the energy is concentrated and thus a convective source. Need to read my Sub(Surface)Stack articles on how to model ENSO in the Pacific and AMO in the Atlantic to understand how the most significant source of climate variability arises.
Back in the 1990s, I went to talk with Inez Fung and Andrew Weaver about possibly doing a PhD in climate science. Inez mentioned to me that one of the hardest problems they were trying to figure out was the modelling of clouds. Tropical convection as it relates to the creation of thunderheads and storms probably fits into one of the hard to model cloud problems.
Luca: I think we must distinguish between climate models (CMIPs) and IPCC scenarios (SSPs). For some time, the climate models have been widely thought to overestimate temperature rise. I agree that the satellite temperature data (as well as the ground data) refute the climate models.
The SSP scenarios lay out expectations for future emissions and they convert future cumulative emissions (after 2015) to changes in temperature (since 1800s). I have demonstrated that the IPCC converts cumulative emissions since 2015 (Gt) to temperature rise since 1800s using this simple equation: delta-T = 1.15 + 0.000893 (Gt) where "delta T" is the temperature increase from some base point in the 1800s (I am not sure what they chose). This equation is used for the future, and it is derived from the past: divide the IPCC estimated temperature gain from 1800s to 2015 (about 1.15 C) by estimated cumulative emissions from 1800s to 2015 (about 1,280 Gt) to get the above formula.
The IPCC then uses this same formula to convert cumulative emissions to delta-T in the future. So, when the IPCC uses a SSP scenario for the future and claims any given delta-T per decade, they are really claiming cumulative emissions per decade and using the above equation as a transfer function to convert cumulative emissions to temperature.
If you think that some SSPs overestimate delta-T in the future, that is because you think that they overestimate cumulative emissions.
Finally, is it proper to use the correlation of delta-T vs. Gt from the past to project delta-T vs. Gt to the future? One thought is that the effect of rising CO2 ought to produce gradually diminishing returns as it increases because the main IR absorption bands are saturated, and the effect of increased CO2 is in the wings of the bands. Counter to that is the thought that the global sinks for CO2 might be losing capacity as they absorb more and more CO2.
Thank you! I didn't realize what they did was this straightforward. The assumption is that all of the temperature increase since the 1800's is due to CO2 then. Correct?
Clayton: I am not sure I fully understand the machinations that the IPCC went through. However, if I simply assume that all the net temperature gain since the 1800s to 2015 was due to carbon emissions, and I use IPCC data for the temperature gain (1.15 C) and a reasonable estimate for total cumulative CO2 from 1800s to 2015, and I divide delta-T by cumulative emissions, I get the temperature rise per Gt of CO2. Then when I examine the various IPCC scenarios that go into the future, they show delta-T and Gt CO23 in the future in separate graphs. If I divide one by the other, voila, I find essentially the same ratio as from the 1800s to 2015. So, regardless of what complex analysis the IPCC might have done, at the bottom line it is equivalent to saying 1 Gt of CO2 produces so much warming, and whatever that amount was going from the 1800s to 2015, it is also projected into the future. And YES, the assumption (always by IPCC) is the all net warming is due to greenhouse gases.
Thanks again. I realized after my original reply that you were independently trying to assess how they did their predictions, as opposed to the IPCC admitting to a particular methodology. I thought that there was general agreement that the relationship between CO2 concentration and temperature was logarithmic in that a fixed temperature increase would be achieved by a doubling of CO2 in the atmosphere. If true that would be inconsistent with the approach they seem to be using.
I've been interested the climate change the science and politics for a long time now but I'm firmly on the natural variability side. I've more recently come to the conclusion that there is no one study or groups of studies that will win the scientific argument, although I lean strongly towards the natural variability side. My reasons are as follows;
Here in the UK AGW has been aggressively promoted by all Govts and the media for 30+yrs. All, and I mean all, Govts backed horses have turned into net failures for society. I used to trust the media but Brexit and especially Covid told me I was wrong to do so. The media clearly works on hype - one reason I've moved to Substack!
Every major scare prediction never comes true but AGW proponents simply reset the clock and start again (Hansen said the UK would be a series of islands by the yr 2000, Gore said no arctic ice by c2010, I could go on). The observational predictions never match reality.
Climate change scenarios have huge amounts of complexity it them. Most people I speak to have no idea they are founded on
different economic scenarios. Most economic scenarios are widely out beyond 1yr. The data gaps are massive so huge assumptions are made. It's no wonder they are wrong.
Businesses are in place to provide services and goods for profits - the green agenda is unbelievably profitable for them.
History is littered with failed 'settled issues' - anyone who says science is settled I don't think understands it as the paper cited suggests.
Energy policy, in the pursuit of green tech, has been a disaster - we are now on x3 - x5 costs compared to 3yrs ago
We were promised cheaper energy and lots of green jobs but neither have arrived here in the UK dispite all the tax payer subsidies
Green tech is incredibly polluting and harmful for the environment- leaching pads and mine tailings are very destructive. There appears to be a lot of child labour and forced labour used in its making. Stores or rare earn a will deplete pretty quickly if we transition as the pace AGW believers want (although physics will prohibit that).
The cost of transition is only just beginning and most people have no idea about the ruinous scale (I ask people how long is a billion seconds after telling them a million is c11days - they are gobsmacked). If we are going to transition we need to be certain we are investing wisely given all competing demands for our taxes.
Why has no town, city, state or even small country tried a full transition experiment, say for 1 - 5yrs? We can then assess it's impact more objectively.
Every advocate of AGW I've met is not willing to give up their mobile phone but they have no appreciation of how it's made directly and indirectly by fossil fuels.
Lifting people out of poverty has been done using CO2 producing fossil fuels. Billions of people continue to need this.
Where are all the fossil fuel derivatives going to come from? Plastics, clothing, fertiliser, glass, etc etc etc We should transition only when we have replacements if we want to maintain our lifestyles.
The paleoclimatic proxy data must be averaged sometimes over multiple decades or multiple centuries but we compare them to modern measurements that strike at less than a second interval.
Historic reports of extreme hot weather from old newspapers no longer correlate with the homogenized data presented today.
Every slightly out of the ordinary weather event is now used as a battering ram for AGW, but the cold events are generally ignored. You have written some great stuff on weather extremes that appears very objective (but not to the believers).
It's rare to find debates between the different views but when you do after debate polls generally seem to favour the skeptics.
Most people prefer warmer to colder climates and the UEA arbitrary 2°C 'tipping point' doesn't seem problematic to me given we experience maybe 10 - 20°C variances each day and maybe 30 - 40°C seasonally.
There's clearly lots more to include but like I said, I think there is so much political capital invested and dark money funding AGW that it will be a decade or more before people simply reject it on the basis of cost.
Maybe not quite what you wanted to read but I remain extremely skeptical and whilst I welcome new scientific papers like Zetal I don't think they will change the views of the key opinion formers, but we must keep producing them. Physics and cost will win out.
It's not natural variability because natural variability reverts to a mean of zero. Just as with ocean tides, it ebbs and flows but always reverts back. Need to read my Sub(Surface)Stack articles on how to model ENSO in the Pacific and AMO in the Atlantic using tidal forcing.
The STAR team is to be commended for this extraordinarily careful effort to look at all the satellite data. As they point out, their earlier Star 4.1 model and the RSS models both predicted >50% higher warming than their new STAR 5.0. So for about 20 years, it seemed as if RSS and STAR were agreeing on about a 50% higher rate of warming compared to UAH. Now, however, the STAR 5.0 agrees very closely with UAH across the entire 30+ years of measurement (Figure 13). It requires real devotion to scientific integrity to report a result that for decades was used to argue against the UAH results.
That's the major part of this study. The other major finding is the possible recent acceleration of warming. but that is based on splitting the data in two, and thus we have only 15 or 20 years of observation of a highly noisy time series. Interesting to be sure, but hardly a secure hook to hang our hat on.
Hopefully not going too Off Topic here: we know ice ages happen. We know they are likely to happen again. Would an ice age kill more or melting the ice caps? my belief is the ice age would - cold weather kills far more than warm, has far less growing capacity and far less water for the same energy.
Have the ice caps ever been completely melted?
Would it be possible to prevent the next ice age?
How much CO2 would it take, assuming that is indeed the cause of global warming.
From my albeit naive holistic view of the planet, I know these things to be true:
* the population is increasing
* increased populations require increased food
* increased populations require increased water
* growing food requires warmth, water and CO2
* increased CO2 reduces the amount of water for food growth + increases food production efficiency / crop yield
It seems to me that the ideal scenario would be an increase in warmth, water and CO2 - naturally - as a population on a planet increased. Without even trying, that is exactly the scenario we see happening now. As if nature itself understands what is required for humans to thrive and provides it. Humans and their processes being part of that nature.
Not only do fossil fuels help this CO2 increase but they improve a host of other elements of living across the board and across the globe.
People already live in floating villages eg Bajau, Venice is on water, and the Chinese simply created / stabilised islands in the South Pacific sea, the Dutch have had dykes for centuries.
The more well funded a people are, the more likely they can come up with solutions to problems that may be elicited by a global temperature change, as opposed to barely being able to afford to heat their homes or being restricted to a 15 minute city.
Three nuances regarding the last point in this list:
1. If this paper is at least mostly correct, some plants which grow faster, with increased atmospheric CO2 concentrations, in turn have lower protein concentrations:
"Crops particularly affected include rice and wheat, which are primary sources of dietary protein for many countries."
2. While C3 plants (about 90% of those on Earth) experience increased photosynthesis with higher atmospheric concentrations of CO2, that effect is lessened for C4 plants, which "include most tropical and sub-tropical grasses and several important crops, including maize (corn), sugar cane, sorghum, and the millets."
There's limited data on these plants, but from what we know to date, increased CO2 concentrations (above current ambient) don't increase either plant growth or crop yield.
3. As well, per the second paper linked above, legumes (which are C3 plants), in particular, benefit from higher CO2 concentrations. However, that may only affect growth and not crop yield.
These are three examples of how initial impressions can take on greater form, when diving down from an intuitive, holistic view into some of the relevant details.
There are some points I would like to make on the nature paper above which was very detailed and nicely written but was shall we say information dense which required almost forensic reading skill and I have to admit I reread some parts several times.
1) I was aware that enhanced CO2 reduced the proportion of protein in many crops as the amount of CO2 was raised hence they are able if they want to produce much more carbohydrates and other none nitrogenous materials.
However its interesting to note the the paper quotes in paras 5 to 7 that plant growth and productivity are almost exactly balanced by the decrease in nitrogenous material mainly proteins I would assume.
The fall in concentration does not mean a reduction in the absolute amount of protein produced. For most people with a balanced mixed diet this is not a problem as they will not be deficient in protein. Similarly for phosphorous and calcium.
Obviously for people who are malnourished this argument may not hold but the greater productivity will reduce there number.
2)As C4 plant corn and sugarcane are already extremely productive crops because they use the CO2 more efficiently than C3. It would be really helpful to boost the C3 levels up to the C4 level and 90% of plants are C3.
3) Para group heading "Differences among Plant Functional Types in Response to Rlevated CO2" Last para in the group. On the legumes the paper seems a little convoluted but my reading is that soya experience a more photosynthetic activity and plant growth in response to increased CO2 say wheat or rice but this is not reflected in an increase in final productive yield over and above that of wheat and rice.
"this analysis is also consistent with the other part of the paper and quoting here:
this increased growth is also reflected in the harvestable yield of crops, with wheat, rice and soybean all showing increases in yield of 12–14% under elevated CO2 in FACE experiments (Ainsworth 2008; Long et al. 2006)."
As a last point I would note that we have already genetically engineered rice to have vitamin A, so potentially relieving millions of people of eye conditions due to its deficiency. With enhanced CO2 levels we could add nitrogen fixing abilities to plants that currently lack it and improve the nutritional value of many plants. Currently we use huge amounts of fossil fuels for nitrogen fixation and this would reduce the amounts used and free poorer people of the need to buy fertilisers.
So the yield does go up by the same amount as wheat and rice
Thank you for the response. This protein impact on faster plant growth is very important and something of which I was unaware.
That said, I do prefer chicken, fish or steak for my protein requirements as it's more delicious, fewer calories need to be consumed and the proteins are complete.
I think that several people seem to misunderstand the import of the graph. This graph does not mean that the IPCC estimate of past warming is way off. You have to compare apples to apples. The increase in temperature since 1979 is estimated to be 0.7 C from satellite measurements. When the IPCC says that the temperature increase from the 1800s (although not specifically when) is 1.15 C, that is the sum of warming after 1979 plus warming prior to 1979. Warming prior to 1979 depends upon the year chosen for comparison and the method to estimate the temperature change. NASA and NOAA attribute about 0.4 C prior to 1979. So, when you add about 0.4 C to 0.7 C you get 1.1 C. I don't see much overall conflict between the end points of satellite measurements and the IPCC claim. However, the satellite measurements do seem to have much greater ups and downs along the way that seem to be related to El Niño/La Niña fluctuations. Since the Pacific covers 1/3 of the earth, maybe that makes sense?
So, we have numerous comments below saying this requires a revolutionary reduction in temperature. I think they are wrong.
I think you misunderstood. The problem is not the increase in temperature since 1800s, but the TTT trends used in climate models. Santer et al. (2021) reported that the multi-model averages for the TTT trends from CMIP5 and CMIP6 were 0.28–0.29 K/decade during 1979–2019. The total TTT trend found in this study was only one-half of the climate model simulations during the same period. The climate models assume faster (way faster) rates. And remember that climate models are both key piece of evidence used by IPCC to support the AGW theory and a tool for future predictions.
With this new adjusted approach, what would we expect the Climate to be in 2050 & 2100? How much less than the 1.5 degree increase that Paris Accord wants to achieve?
As a critical thinker, what this say to me is that the foundation upon which the climate alarmists built their movement continues to crumble. It is clearer with each passing day that we do not have an equation that has the right inputs and relationships to model climate; it's just too complicated for our level of understanding. Moreover, the last thing we should do is spend trillions to "transition" away from inexpensive fossil fuels to intermittent, unreliable and expensive renewables. The bogyman man of impending climate catastrophe is not what was once feared and should not drive national or global energy policy. Inexpensive, reliable clean energy, like natural gas, low sulfur coal, petroleum and nuclear should be what policy makers look to as it's what the free market would suggest. Let's have a pro human and pro plant and animal life perspective.
LOL, it's not that hard. Perhaps natural climate variability is a bit more challenging but then machine learning will eventually figure this out given the right contextual info. These 2 articles show how that will work.
I get a bad feeling when I see a big red trend lines drawn over stochastic data. Even if there is apparent good news, that slope of the line is lower than previously thought.
I was struck by the range of variability visible in the chart. Look at the spike from the 1997-98 El Niño event.
In the paper, I found the quasi-decadal time periods produced by the LOESS analysis interesting. We may be in such a decade now, and mistaking its upslope for a long-term secular trend.
Sorry to be pedantic, but in time series analysis, a time series can be decomposed into: a) a cyclical component; b) a trend component; c) a seasonal component; d) an irregular component. [The Oxford Dictionary of Statistical Terms].
Thank you Mr Pielke. Excellent idea to get back to basics.
Very much looking forward to seeing who you choose next. Happer and Wijngaarden would be fun.
https://wvanwijngaarden.info.yorku.ca/files/2021/03/WPotency.pdf?x45936
Along the same lines, I'd much appreciate a close look at the conclusions reached by Vinos and May. If warming effects of the CO2 blanket are dwarfed by variations in heat loss at the poles, and - as is becoming apparent - the CO2 effects themselves look to be less than originally thought, that's important.
Summary on Climate Etc. at this link:
https://judithcurry.com/2022/09/22/the-winter-gatekeeper-hypothesis-vii-a-summary-plus-qa/
I've come up with a general metric I use when I read climate science, something to capture the level of "trust" I have in its scientific integrity. Tier 1 science are those things that investigate the past, like observations and measurements and things we can generally prove; I rate this between an 8 and 10. Tier 2 science is modeled science where the scientist is projecting past data forward and making guesses; so that's between a 4 and 8 on the scale. And then Tier 3 science is attribution/even attribution science, as I trust almost none of it - between a 1 and 4 on the scale. Honestly, attribution science feels like a sophisticated game of pin the tail on the climate donkey.
This discussion you've laid out about the relative validity of satellite observations and on-ground measurements seems like it falls somewhere close up to Tier 1: as in, this is truly for the scientists to debate. It does certainly take more of the legs out of the "the apocalypse is nigh" argument, but as you've pointed out those scenarios are not even worth talking about more (were they ever?) I trust that these scientific metrics will be debated between those who understand it the most - namely you scientists - and then put it into words most of us can understand. Maybe wishful thinking...
More importantly Marc, many of the papers out there are wrong or hopelessly biased. I discussed this last January in a long post at Climate, Etc. This fact is very well known even by many scientists themselves, yet there are immense structural problems that block any effective action to make the literature more reliable. There are even now according to Ioannidis hundreds of thousands of zombie trials out there in the literature where there is no real data that underlies the conclusions.
Marc: It's not just whether the data is past or present or future. Its whether the data covers the necessary span of geography and time, and whether the interpretation of the data requires leaps of faith. For example, consider the estimation of past average earth temperatures back a thousand or even two thousand years. Some climate scientists use "proxies" to infer ancient temperatures. A proxy is physical evidence today of climate many years ago (like tree rings, or isotopic differences in ice, or many others). A few decades ago, Michael Mann and several others, combined several proxies from different locations across different time intervals and came up with charts of earth average temperature over the past couple of thousand years (the so-called "hockey stick"). Unfortunately, the geographical and time coverage was grossly inadequate. In addition, the method to statistically combine the individual proxy data was faulty. But worse than that, many proxies don't fundamentally work well. Nevertheless, this group aggressively published and disseminated their hockey stick and it became widely accepted within the alarmist community. It was later shown that the whole study was highly dubious, and the revelation of emails in "climategate" showed these scientists were highly biased to alarmism. The point is that past or future, most climate data is not simple to interpret, is often severely lacking in coverage, and requires many decades to derive a signal above and beyond the ordinary fluctuations in weather. So I maintain that most science data is in tier 3 - between 1 and 4 on a scale of 10.
Very good then, all the more reason to assign those trust levels to it. I remember the crazy hockey stick discussion and all that came of it. I'd be interested to hear Dr. Pielke's response to it all...
You can find a full discussion of the hockey stick and climate gate in (pardon the shameless push): D. Rapp: Assessing Climate Change: Temperatures, Solar Radiation and Heat Balance (Springer Praxis Books) 3rd ed. 2014 Edition
I've read various accounts of it...I'll read yours...
Ross McKitrick on claims of accelerating warming in Zetal23:
https://judithcurry.com/2023/04/19/is-warming-accelerating-in-the-troposphere/
Clayton: The exact way that increasing CO2 produces an imbalance in the earth's power budget is complex, and there have been many simplistic reductions of this complexity, with variable degrees of credibility.
One simplistic approach was to note that absorption of IR by CO2 in the 13-17 micron band in the atmosphere is saturated, and as the CO2 concentration is increased, additional absorption occurs in the "wings" of the main absorption band, and as the CO2 concentration increases further, the gains in absorption per unit increase in CO2 concentration decrease. Hansen et al. (2000) derived a logarithmic function for increased absorptivity vs. increased CO2 that has been quoted widely. Hansen et al. converted that increase in absorptivity to an increase in "downward forcing". I wish I could post the plot! But that logarithmic curve looks pretty linear from CO2 going from 400 ppm to 550 ppm.
Linden (2007) objected to the simplistic notion that greenhouse gases “inhibit cooling of the Earth by thermal radiation, and serves as a blanket which causes the Earth to be warmer than it otherwise would be". The lower atmosphere is relatively opaque to IR radiation but as the altitude increases, the density decreases and transmission of IR improves. Lindzen defined an altitude sufficiently high that the optical depth for IR is about 1 so that transmission of IR is attenuated roughly as e^-1. This is a region of the atmosphere that can radiate power from the Earth to space. He described the effect of CO2 as raising the principal altitude where the earth radiates thermal power to space, and when that region is cooler, the earth radiates less power.
Whatever the actual physical mechanism is, the IPCC used some method to convert CO2 increase to temperature increase. Empirically, if you examine the SSP scenarios they are linear in delta-T from delta-CO2 and the linearity is essentially the same as that prior to 2015.
I would like to post a general question I've had for some time regarding urban heating and its effect on temperature estimates. People seem to interpret the urban impact on temperature as being a result of albedo changes due to buildings, asphalt etc. My question is what contribution does the vast energy consumption that occurs within cities play relative to albedo effects. Cities consume energy heating homes, cooling homes, in transportation systems, manufacturing, and lighting etc which I assume eventually turns into heat. A city consumes a known amount of electricity each day. If you know the area of the city one could easily calculate the watts per square meter that gets added to incoming solar energy within the city limits. Of course you would need to add energy consumption from the direct burning of fossil fuels to the total. Is this significant? Is there a flaw in my reasoning that I'm missing?
One of the main reasons for using satellites for temperatures sounding is that you get a uniformity of reading in space and time that you cannot achieve through using individual measurements across the earths surface by different nations. Therefore, to degrade the value of the satellite measurements because they happen to run against the results you are trying to propound sounds a bit sick to me.
I can understand how a large number of temperature measurement sites, however faulty for one reason or another, can come up with an approximate answer. Believing that good temperatures can be extracted from spectral measurements in the troposphere requires an act of faith.
I worked on the selective chopper radiometer which was flown on ERTS Nimbus 4 and 5 satellites around 1975 and the whole point of the exercise was to carry out temperature sensing of the atmosphere at specific levels. You would need to look it up to learn more. I believe that the temperatures derived were accurate and consistent across the whole globe which was covered once per day. Obviously the temperatures were for a specific height above the earth. Whether there was criticism of the method I cannot say because I moved off the project after a few years. This was a joint project between the Clarendon Lab, Oxford, and Heriott Watt university Physics Dept involving John Houghton and S D Smith.
Climate science generally does not have an adequate theory for the tropics. The moist adiabat theory is what suggests the hot spot and that theory is pretty badly wrong. Climate models use very coarse grids and simply cannot resolve tropical convection. This phenomenon is what determines the response to greenhouse gases in the tropics.
What is amazing is that climate scientists and modelers have surely known this for a very long time. Why hasn't it received adequate attention?
People who's career and livelihood depend on pursuing a field of endeavor of dubious veracity continue to do so because they don't have a better option, and besides, they are p]aid to do it. I used to know a fellow who had a black attributed to Ken Kruishank that said:
If a committee is allowed to discuss a bad idea long enough, they will eventually adopt it because of all the work they put in.
The equatorial tropical ocean is where the energy is concentrated and thus a convective source. Need to read my Sub(Surface)Stack articles on how to model ENSO in the Pacific and AMO in the Atlantic to understand how the most significant source of climate variability arises.
https://pukite.substack.com/p/machine-learning-validates-the-enso
https://pukite.substack.com/p/machine-learning-validates-the-amo
Back in the 1990s, I went to talk with Inez Fung and Andrew Weaver about possibly doing a PhD in climate science. Inez mentioned to me that one of the hardest problems they were trying to figure out was the modelling of clouds. Tropical convection as it relates to the creation of thunderheads and storms probably fits into one of the hard to model cloud problems.
1) Climate Science is fascinating
2) Climate Science is really complicated
Anyone proposing any modelling methodology which give definitive answers is wrong?
But we have to try.
And we have to interpret data, and try and fit our models to it.
Gravity is the 'lid' on earth's atmosphere.
The Lapse Rate is as important as CO2 in the current anthripocentric Climate Change modelling.
There are 3 (at least) caused for the Lapse Rate.
i) Loeschmidt
ii) Upward Convection and Expansion
iii) A cold side / hot side heat gradient.
They ALL come into play (is my view).
Are these all included in current algorithms?
I don't know !
So really generic stuff, but throwing it in the ring.
1 is true
2 is false
AGW is beyond easy to model, and natural climate variability is a bit more complex, as the forcing isn't just a trend.
Luca: I think we must distinguish between climate models (CMIPs) and IPCC scenarios (SSPs). For some time, the climate models have been widely thought to overestimate temperature rise. I agree that the satellite temperature data (as well as the ground data) refute the climate models.
The SSP scenarios lay out expectations for future emissions and they convert future cumulative emissions (after 2015) to changes in temperature (since 1800s). I have demonstrated that the IPCC converts cumulative emissions since 2015 (Gt) to temperature rise since 1800s using this simple equation: delta-T = 1.15 + 0.000893 (Gt) where "delta T" is the temperature increase from some base point in the 1800s (I am not sure what they chose). This equation is used for the future, and it is derived from the past: divide the IPCC estimated temperature gain from 1800s to 2015 (about 1.15 C) by estimated cumulative emissions from 1800s to 2015 (about 1,280 Gt) to get the above formula.
The IPCC then uses this same formula to convert cumulative emissions to delta-T in the future. So, when the IPCC uses a SSP scenario for the future and claims any given delta-T per decade, they are really claiming cumulative emissions per decade and using the above equation as a transfer function to convert cumulative emissions to temperature.
If you think that some SSPs overestimate delta-T in the future, that is because you think that they overestimate cumulative emissions.
Finally, is it proper to use the correlation of delta-T vs. Gt from the past to project delta-T vs. Gt to the future? One thought is that the effect of rising CO2 ought to produce gradually diminishing returns as it increases because the main IR absorption bands are saturated, and the effect of increased CO2 is in the wings of the bands. Counter to that is the thought that the global sinks for CO2 might be losing capacity as they absorb more and more CO2.
Thank you! I didn't realize what they did was this straightforward. The assumption is that all of the temperature increase since the 1800's is due to CO2 then. Correct?
Clayton: I am not sure I fully understand the machinations that the IPCC went through. However, if I simply assume that all the net temperature gain since the 1800s to 2015 was due to carbon emissions, and I use IPCC data for the temperature gain (1.15 C) and a reasonable estimate for total cumulative CO2 from 1800s to 2015, and I divide delta-T by cumulative emissions, I get the temperature rise per Gt of CO2. Then when I examine the various IPCC scenarios that go into the future, they show delta-T and Gt CO23 in the future in separate graphs. If I divide one by the other, voila, I find essentially the same ratio as from the 1800s to 2015. So, regardless of what complex analysis the IPCC might have done, at the bottom line it is equivalent to saying 1 Gt of CO2 produces so much warming, and whatever that amount was going from the 1800s to 2015, it is also projected into the future. And YES, the assumption (always by IPCC) is the all net warming is due to greenhouse gases.
Thanks again. I realized after my original reply that you were independently trying to assess how they did their predictions, as opposed to the IPCC admitting to a particular methodology. I thought that there was general agreement that the relationship between CO2 concentration and temperature was logarithmic in that a fixed temperature increase would be achieved by a doubling of CO2 in the atmosphere. If true that would be inconsistent with the approach they seem to be using.
I've been interested the climate change the science and politics for a long time now but I'm firmly on the natural variability side. I've more recently come to the conclusion that there is no one study or groups of studies that will win the scientific argument, although I lean strongly towards the natural variability side. My reasons are as follows;
Here in the UK AGW has been aggressively promoted by all Govts and the media for 30+yrs. All, and I mean all, Govts backed horses have turned into net failures for society. I used to trust the media but Brexit and especially Covid told me I was wrong to do so. The media clearly works on hype - one reason I've moved to Substack!
Every major scare prediction never comes true but AGW proponents simply reset the clock and start again (Hansen said the UK would be a series of islands by the yr 2000, Gore said no arctic ice by c2010, I could go on). The observational predictions never match reality.
Climate change scenarios have huge amounts of complexity it them. Most people I speak to have no idea they are founded on
different economic scenarios. Most economic scenarios are widely out beyond 1yr. The data gaps are massive so huge assumptions are made. It's no wonder they are wrong.
Businesses are in place to provide services and goods for profits - the green agenda is unbelievably profitable for them.
History is littered with failed 'settled issues' - anyone who says science is settled I don't think understands it as the paper cited suggests.
Energy policy, in the pursuit of green tech, has been a disaster - we are now on x3 - x5 costs compared to 3yrs ago
We were promised cheaper energy and lots of green jobs but neither have arrived here in the UK dispite all the tax payer subsidies
Green tech is incredibly polluting and harmful for the environment- leaching pads and mine tailings are very destructive. There appears to be a lot of child labour and forced labour used in its making. Stores or rare earn a will deplete pretty quickly if we transition as the pace AGW believers want (although physics will prohibit that).
The cost of transition is only just beginning and most people have no idea about the ruinous scale (I ask people how long is a billion seconds after telling them a million is c11days - they are gobsmacked). If we are going to transition we need to be certain we are investing wisely given all competing demands for our taxes.
Why has no town, city, state or even small country tried a full transition experiment, say for 1 - 5yrs? We can then assess it's impact more objectively.
Every advocate of AGW I've met is not willing to give up their mobile phone but they have no appreciation of how it's made directly and indirectly by fossil fuels.
Lifting people out of poverty has been done using CO2 producing fossil fuels. Billions of people continue to need this.
Where are all the fossil fuel derivatives going to come from? Plastics, clothing, fertiliser, glass, etc etc etc We should transition only when we have replacements if we want to maintain our lifestyles.
The paleoclimatic proxy data must be averaged sometimes over multiple decades or multiple centuries but we compare them to modern measurements that strike at less than a second interval.
Historic reports of extreme hot weather from old newspapers no longer correlate with the homogenized data presented today.
Every slightly out of the ordinary weather event is now used as a battering ram for AGW, but the cold events are generally ignored. You have written some great stuff on weather extremes that appears very objective (but not to the believers).
It's rare to find debates between the different views but when you do after debate polls generally seem to favour the skeptics.
Most people prefer warmer to colder climates and the UEA arbitrary 2°C 'tipping point' doesn't seem problematic to me given we experience maybe 10 - 20°C variances each day and maybe 30 - 40°C seasonally.
There's clearly lots more to include but like I said, I think there is so much political capital invested and dark money funding AGW that it will be a decade or more before people simply reject it on the basis of cost.
Maybe not quite what you wanted to read but I remain extremely skeptical and whilst I welcome new scientific papers like Zetal I don't think they will change the views of the key opinion formers, but we must keep producing them. Physics and cost will win out.
It's not natural variability because natural variability reverts to a mean of zero. Just as with ocean tides, it ebbs and flows but always reverts back. Need to read my Sub(Surface)Stack articles on how to model ENSO in the Pacific and AMO in the Atlantic using tidal forcing.
https://pukite.substack.com/p/machine-learning-validates-the-enso
https://pukite.substack.com/p/machine-learning-validates-the-amo
The STAR team is to be commended for this extraordinarily careful effort to look at all the satellite data. As they point out, their earlier Star 4.1 model and the RSS models both predicted >50% higher warming than their new STAR 5.0. So for about 20 years, it seemed as if RSS and STAR were agreeing on about a 50% higher rate of warming compared to UAH. Now, however, the STAR 5.0 agrees very closely with UAH across the entire 30+ years of measurement (Figure 13). It requires real devotion to scientific integrity to report a result that for decades was used to argue against the UAH results.
That's the major part of this study. The other major finding is the possible recent acceleration of warming. but that is based on splitting the data in two, and thus we have only 15 or 20 years of observation of a highly noisy time series. Interesting to be sure, but hardly a secure hook to hang our hat on.
Hopefully not going too Off Topic here: we know ice ages happen. We know they are likely to happen again. Would an ice age kill more or melting the ice caps? my belief is the ice age would - cold weather kills far more than warm, has far less growing capacity and far less water for the same energy.
Have the ice caps ever been completely melted?
Would it be possible to prevent the next ice age?
How much CO2 would it take, assuming that is indeed the cause of global warming.
From my albeit naive holistic view of the planet, I know these things to be true:
* the population is increasing
* increased populations require increased food
* increased populations require increased water
* growing food requires warmth, water and CO2
* increased CO2 reduces the amount of water for food growth + increases food production efficiency / crop yield
It seems to me that the ideal scenario would be an increase in warmth, water and CO2 - naturally - as a population on a planet increased. Without even trying, that is exactly the scenario we see happening now. As if nature itself understands what is required for humans to thrive and provides it. Humans and their processes being part of that nature.
Not only do fossil fuels help this CO2 increase but they improve a host of other elements of living across the board and across the globe.
People already live in floating villages eg Bajau, Venice is on water, and the Chinese simply created / stabilised islands in the South Pacific sea, the Dutch have had dykes for centuries.
The more well funded a people are, the more likely they can come up with solutions to problems that may be elicited by a global temperature change, as opposed to barely being able to afford to heat their homes or being restricted to a 15 minute city.
Where am I going wrong in this?
Three nuances regarding the last point in this list:
1. If this paper is at least mostly correct, some plants which grow faster, with increased atmospheric CO2 concentrations, in turn have lower protein concentrations:
https://ehp.niehs.nih.gov/doi/10.1289/ehp41
"Crops particularly affected include rice and wheat, which are primary sources of dietary protein for many countries."
2. While C3 plants (about 90% of those on Earth) experience increased photosynthesis with higher atmospheric concentrations of CO2, that effect is lessened for C4 plants, which "include most tropical and sub-tropical grasses and several important crops, including maize (corn), sugar cane, sorghum, and the millets."
https://www.nature.com/scitable/knowledge/library/effects-of-rising-atmospheric-concentrations-of-carbon-13254108/
There's limited data on these plants, but from what we know to date, increased CO2 concentrations (above current ambient) don't increase either plant growth or crop yield.
3. As well, per the second paper linked above, legumes (which are C3 plants), in particular, benefit from higher CO2 concentrations. However, that may only affect growth and not crop yield.
These are three examples of how initial impressions can take on greater form, when diving down from an intuitive, holistic view into some of the relevant details.
There are some points I would like to make on the nature paper above which was very detailed and nicely written but was shall we say information dense which required almost forensic reading skill and I have to admit I reread some parts several times.
1) I was aware that enhanced CO2 reduced the proportion of protein in many crops as the amount of CO2 was raised hence they are able if they want to produce much more carbohydrates and other none nitrogenous materials.
However its interesting to note the the paper quotes in paras 5 to 7 that plant growth and productivity are almost exactly balanced by the decrease in nitrogenous material mainly proteins I would assume.
The fall in concentration does not mean a reduction in the absolute amount of protein produced. For most people with a balanced mixed diet this is not a problem as they will not be deficient in protein. Similarly for phosphorous and calcium.
Obviously for people who are malnourished this argument may not hold but the greater productivity will reduce there number.
2)As C4 plant corn and sugarcane are already extremely productive crops because they use the CO2 more efficiently than C3. It would be really helpful to boost the C3 levels up to the C4 level and 90% of plants are C3.
3) Para group heading "Differences among Plant Functional Types in Response to Rlevated CO2" Last para in the group. On the legumes the paper seems a little convoluted but my reading is that soya experience a more photosynthetic activity and plant growth in response to increased CO2 say wheat or rice but this is not reflected in an increase in final productive yield over and above that of wheat and rice.
"this analysis is also consistent with the other part of the paper and quoting here:
this increased growth is also reflected in the harvestable yield of crops, with wheat, rice and soybean all showing increases in yield of 12–14% under elevated CO2 in FACE experiments (Ainsworth 2008; Long et al. 2006)."
As a last point I would note that we have already genetically engineered rice to have vitamin A, so potentially relieving millions of people of eye conditions due to its deficiency. With enhanced CO2 levels we could add nitrogen fixing abilities to plants that currently lack it and improve the nutritional value of many plants. Currently we use huge amounts of fossil fuels for nitrogen fixation and this would reduce the amounts used and free poorer people of the need to buy fertilisers.
So the yield does go up by the same amount as wheat and rice
Thank you for the response. This protein impact on faster plant growth is very important and something of which I was unaware.
That said, I do prefer chicken, fish or steak for my protein requirements as it's more delicious, fewer calories need to be consumed and the proteins are complete.
The links are appreciated also, thanks again.
I think that several people seem to misunderstand the import of the graph. This graph does not mean that the IPCC estimate of past warming is way off. You have to compare apples to apples. The increase in temperature since 1979 is estimated to be 0.7 C from satellite measurements. When the IPCC says that the temperature increase from the 1800s (although not specifically when) is 1.15 C, that is the sum of warming after 1979 plus warming prior to 1979. Warming prior to 1979 depends upon the year chosen for comparison and the method to estimate the temperature change. NASA and NOAA attribute about 0.4 C prior to 1979. So, when you add about 0.4 C to 0.7 C you get 1.1 C. I don't see much overall conflict between the end points of satellite measurements and the IPCC claim. However, the satellite measurements do seem to have much greater ups and downs along the way that seem to be related to El Niño/La Niña fluctuations. Since the Pacific covers 1/3 of the earth, maybe that makes sense?
So, we have numerous comments below saying this requires a revolutionary reduction in temperature. I think they are wrong.
I think you misunderstood. The problem is not the increase in temperature since 1800s, but the TTT trends used in climate models. Santer et al. (2021) reported that the multi-model averages for the TTT trends from CMIP5 and CMIP6 were 0.28–0.29 K/decade during 1979–2019. The total TTT trend found in this study was only one-half of the climate model simulations during the same period. The climate models assume faster (way faster) rates. And remember that climate models are both key piece of evidence used by IPCC to support the AGW theory and a tool for future predictions.
With this new adjusted approach, what would we expect the Climate to be in 2050 & 2100? How much less than the 1.5 degree increase that Paris Accord wants to achieve?
As a critical thinker, what this say to me is that the foundation upon which the climate alarmists built their movement continues to crumble. It is clearer with each passing day that we do not have an equation that has the right inputs and relationships to model climate; it's just too complicated for our level of understanding. Moreover, the last thing we should do is spend trillions to "transition" away from inexpensive fossil fuels to intermittent, unreliable and expensive renewables. The bogyman man of impending climate catastrophe is not what was once feared and should not drive national or global energy policy. Inexpensive, reliable clean energy, like natural gas, low sulfur coal, petroleum and nuclear should be what policy makers look to as it's what the free market would suggest. Let's have a pro human and pro plant and animal life perspective.
LOL, it's not that hard. Perhaps natural climate variability is a bit more challenging but then machine learning will eventually figure this out given the right contextual info. These 2 articles show how that will work.
https://pukite.substack.com/p/machine-learning-validates-the-enso
https://pukite.substack.com/p/machine-learning-validates-the-amo
I get a bad feeling when I see a big red trend lines drawn over stochastic data. Even if there is apparent good news, that slope of the line is lower than previously thought.
I was struck by the range of variability visible in the chart. Look at the spike from the 1997-98 El Niño event.
In the paper, I found the quasi-decadal time periods produced by the LOESS analysis interesting. We may be in such a decade now, and mistaking its upslope for a long-term secular trend.
Sorry to be pedantic, but in time series analysis, a time series can be decomposed into: a) a cyclical component; b) a trend component; c) a seasonal component; d) an irregular component. [The Oxford Dictionary of Statistical Terms].
"over stochastic data"
It's not stochastic. Like tides, every cycle is likely a deterministic response to external forces:
https://pukite.substack.com/p/machine-learning-validates-the-enso
https://pukite.substack.com/p/machine-learning-validates-the-amo