Whatever you think to know about clouds within the climate system, this would be about the right time forget it all. Common data products on cloud forcing are nothing but junk science. Here is why.
This is one of those things people just can not imagine and even if you happen to see it with your own eyes, you have a hard time trusting your senses. And once you realize it is true, you sink into your chair and think OMG! It is certainly redefining reality and alienating from society, or at least "science".
On the other side however it is not all dark and negative, but rather blindingly bright and inspiring. The science is not settled, not even close, not everything has been discovered, there is a lot of unexplored space within reach and you can just go out and find it. All the troubles that there are also mean opportunity and that is what life is all about after all - solving problems. And what a contrast this perspective is opposed to the depressingly stupid and blinkered appeals by the Gores and Gretas of this world to simply shut up and give up on life. Yes.
Quite recently we have gone through a lot of these disruptive realities, although there has been insufficient reflection on the subject matter. The WHO has told the world not to bother about the outbreak of SARS-COV-2, it insisted on not interrupting air travel with China, it recommended to not wear masks and until the 20th of January 2020 claimed it was not transmissible human to human. Yes, the WHO was playing an active role in spreading the virus. Take it for what it is.
Equally surreal was the way Europe dealt with the outbreak. Till March 2020 there was the very simple dogma of no human to human transmission within Europe. Any identifiable cases of Covid-19 had to be linked to travel with Asia. If you were not returning from Asia, or at least had contact with someone who did and turned ill, there was no chance you would get tested. With turning a blind eye onto the spread of the pandemic and no testing in this regard, no cases were reported, which again confirmed the dogma. This led to an absurd situation when hospitals were filling up with Covid-19 patients, having all the symptoms, being badly ill, some even dying, infecting health workers and yet they were not getting tested.
Only in late February some brave doctors dared to take a look under the bed by testing patients and there it was, the beast jumped right into their faces. Yet it still took weeks for health authorities and politics to realize the virus was spreading freely and unchecked, while they still kept telling the public there was no reason for concern and they had everything under control. This disinformation definitely helped the virus to spread, unnecessarily claimed a lot of lives and made Europe the main hub of the pandemic.
The bigger the lie, the more people follow it
If you ever happened to "believe" in science, or rather its institutions and you have trust in authorities, this example should be reason enough to finally give it up. There are many more examples, far too many to name them all. The reason why I even name this one is that we need to learn to overcome convenient thinking. "The bigger the lie, the more people follow it". Or as I would put it, the bigger the lie, the more inconvenient to consider the alternative.
As I have pointed out already empiric data on the cloud / temperature relation suggest a positive net cloud radiative effect (NCRE). There is a lot of data yet to be discussed, but since I have gone through a lot of which I can tell it is a very consistent picture. I have checked my results over and over and they look just fine. Consequently this brought up the question why the empiric evidence contradicts the satellite data, with me "believing" the satellite data might be wrong. Of course me "believing" something is per se just as significant as a sack of rice fallen over in China. The only thinkable consequence it had was me searching for answers, a leverage so to say. And searching in this context is not really an activity but rather and event to be triggered, just in case there should be a fitting pattern.
Brace for impact
Guess what, I stumbled over it one day. A key that would fit the lock just perfectly, brace for impact. The LWCRE (long wave cloud radiative effect) is defined as the difference in emissions between average sky conditions (including clouds) and clear skies. As I have told before with clear skies emissions are ~270W/m2, while on average it is only about 240W/m2. That is why the LWCRE amounts to about 30W/m2 according to the IPCC and plenty of papers dealing with the subject. All that may sound perfectly logical, but in fact it is blatantly wrong! And all it needs to figure it all out is a little bit of IQ.
Let me first demonstrate the problem with the help of modtran, which is a decently sophisticated non-dynamic model of the Earth's emission spectrum. It is essentially a database of the spectral lines of various GHGs and as such a climate model on its own. Again, it is not dynamic, but interestingly the RCP scenarios are not either, but that is a different story. There are a couple of interesting things we can do with it, but for now there is just one thing I would like to demonstrate.
If you load this version of modtran1 by default you will get a certain preset with a certain amount of GHGs and the scenario of a "tropical atmosphere". With this preset emissions are 298.52W/m2. Now we can add some clouds to the model, although the choices are very restricted and not all too realistic. If we choose "Altostratus Cloud Base 2.4km Top 3.0km" emissions will sink to 269.004W/m2. The specific LWCRE for this cloud scenario thus is 29.516W/m2.
Next we do the same thing, just that this time we set all (six) parameters for GHGs to zero. The model here seems to retain some assumptions on aerosols and/or surface emissivity < 1, but it gets close to the emissions of a perfect black body at the given temperature. Now emissions are 443.682W/m2. If we add the same cloud scenario as before emissions drop to 350.738W/m2. In the absence of GHGs the LWCRE grows from 29.516 to 92.944W/m2, more than 3times as large! Why is that?
Data on cloud forcing are based on an illicit logic
An iceberg might be an accurate analogy. Is an iceberg only the part that reaches out of the water, or is it something significantly larger? If the former was true the Titanic would have shipped around it and safely reached New York only 2 days later. Just because you can not see it, will not mean it does not exist. GHGs and clouds are overlapped in the way they impair emissions. The approach of comparing average to clear sky emissions is necessarily insensitive or "blind" to this overlapped component.
In the named modtran example GHGs alone reduce emissions by 145.2W/m2, the cloud scenario alone by 92.9W/m2, and both together have an effect of 174.7W/m2. Obviously the sum of the single effects is 238.1W/m2 (145.2 + 92.9), and that is 63.4W/m2 larger than the combined effect. So there are some 63.4W/m2 overlapped, over determined, or redundant, whatever you want to call it. To quote an arbitrary source dealing with the subject..
In sum, redundancy constitutes a challenge for theories of causality. While various amendments have been proposed, both from within and with-out the difference-making framework, an uncontroversial solution is yet to be offered. Finding an appropriate distinction between preempting and pre-empted causes remains an open problem in the philosophy of causation2
We have no working algorithm to allocate causation within redundant systems
If Earth was flat we had just fallen off the disc. In this case, thank god, we have only reached the end of epistemology. We have no working algorithm to allocate causation within redundant systems. If two or more factors (A, B..) cause an outcome X, we simply have to accept this overdetermined causality and any attempt to split causation among those factors will necessarily fail. In the above case 63.4W/m2 of "GHE" are caused by GHGs AND clouds simultaneously. Do not try to break up this number any further.
So how has "climate science" solved the problem? The answer is predictably simple, not at all. I mean not just they have not solved it, which is impossible, but rather they made the most idiotic possible mistake. When A causes X and B causes X, then what difference does B make after all? Right, none, and so "climate science" concluded the causation would entirely rest with A, with B being irrelevant. Of course A in this instance would represent GHGs and B clouds. That logic already fails in the respect, that you could arbitrarily turn it around and reason the opposite. That is a bit of a problem to the "GHE", since all our "sophisticated" satellite data (ERBE, CERES..) on the CRE are based on a first grader mistake. It is junk science, sailing close to the waters of science fraud.
With the above example it is easy to show what happens if we invert the erroneous logic. Without clouds GHGs alone reduce emissions by 145.2W/m2. But once we add the chosen cloud scenario and then switch GHGs on and off, the delta shrinks to 81.7W/m2, since now the redundant component is implicitly excluded. The total "GHE" of 174.7W/m2 in this instance consists of three components: 29.5W/m2 due to clouds, 81.7W/m2 due to GHGs and 63.4W/m2 due to clouds AND GHGs.
This beast has been lurking under the bed for decades now
Really I do not know how and when the LWCRE has been defined as difference between average and clear sky emissions, but I do know it was featured in Ramanthan et al (1989)3, so it was no later than that. I have no idea how this could ever have passed a peer review. I mean there had to be some reflection on the question when it was originally "invented". If anyone knows more about it, please post it in the comments.
Sure, once such non sense slipped through and made it into "science" literature it is off the hook and turns into an established fact. That is one of the problems with the dreadful state of peer reviewing, as it provides a bogus claim of certainty. I recently had a chat with one the authors of this paper4 on LW CF (cloud forcing = CRE), where it is measured as difference in "back radiation" between average and clear skies. It is a different approach but the same logic is causing the same mistake. When asked about the inconsistent results of the paper, he replied "that is just how it is defined".
I should probably explain this. "Back radiation" from clouds will necessarily decrease with altitude as fewer and most of all colder clouds remain above you. Despite "back radiation" being the wrong indicator anyhow, the real LWCRE (let us call it LWCREr) will decrease with altitude. However vapor will diminish even faster and so the overlapped part that obscures the LWCREr will overcompensate. The result is, that with increasing altitude you will "see" increasingly more of an actually diminishing LWCREr and that is exactly what the paper shows. The highest site has the largest LWCREf (LWCRE false), which is no incidence. Would that ring any alarm bells with the scientists? No, because "that is just how it is defined". The computer says no, you know. It might be funny, if it was not so sad.
Now it is understandable that the followers of the orthodoxy have no interest in looking under the bed. Even if they had the idea there might be something, it is certainly nothing they would even like to find. For the "critical thinkers" however it seems it just goes beyond their imagination. Or they might be not all too critical after all, or not so honest respectively and rather paid actors. Who knows? And who would dare to ask? It is quite a drama.
At this point, if not any earlier, it should become clear it is not just about criticising the "GHE" concept, but something way more profound. The GHE as foundation to the global warming narrative is so packed with blunders, that we are starting to see signs of soil liquefaction.