Again to Fundamentals – Watts Up With That?

A few years in the past, I made a easy estimate of the temperature impact of the greater than 10% brightening during the last 4 many years in The Netherlands [1]. The Royal Dutch Metrological Institute (KNMI) attributed solely 0.2^oC to that brightening [2], whereas my methodology resulted in about 1^oC. That would go away only one/3 of the noticed 1.5 ^oC warming to the impact of greenhouse gasses (GHG’s). I coupled “brightening” to much less clouds, and got here to an estimate for the sensitivity to cloud change (cc) of about 0.1 Okay/%cc.
Within the subsequent dialogue with the KNMI, the one argument towards my method boiled right down to: “refined local weather fashions inform us one thing totally different, so your simplistic mannequin have to be mistaken”. A number of different strategies to find out this cloud-sensitivity, all delivered comparable outcomes. Lastly, I concluded that KNMI referred to cloud-feedback outcomes from local weather fashions, whereas I used to be trying to the impact of an unbiased change in cloudiness. Subsequent, I in contrast each views towards present traits in cloudiness, floor temperatures, and so on. from satellite tv for pc information [3]. When matched to traits in cloud-coverage, World Circulation Mannequin (GCM)-derived cloud-feedbacks delivered a local weather situation near a runaway state of affairs. Whereas my very own thought of an unbiased forcing attributable to clouds appearing as shutters (modulating photo voltaic enter) delivered very surprisingly, that the sum of all feedbacks exterior the essential Planck suggestions parameter, turned swiftly (virtually) zero [3].

These outcomes confirmed my notion that prime values for local weather feedbacks will not be actual however artifacts from local weather fashions. If temperature-induced feedbacks happen on account of elevated GHG’s, in itself a believable thought, they should be by definition “small”. Our local weather may be very secure and the Plank suggestions will accommodate any perturbation from a small forcing, even from 2xCO₂, simply. All these feedbacks ought to, and are in my view small, 2^nd order results, or already included in that parameter as confirmed by the result of my suggestions evaluation [3]. For that cause, I additionally used a barely modified Planck suggestions parameter for the basic local weather sensitivity within the recurrent relation of the Local weather Mannequin Checker (CMC) in my WUWT-contribution “Outdoors the Black Field” [4].

However learn how to show that the IPCC/GCM local weather sensitivities are essentially mistaken?

That quest began with a sort of “reverse engineering” of my CMC [4] utilizing the identical information, T_S type HadCrut5 [7], the greenhouse gasoline (GHG) forcing F_GHG from NASA/GISS [6] and calculate the local weather sensitivity as   ̶ 1/λ = ∆T_S/∆F_GHG (see eq.3 additional on) during the last century. With a view to use this sensitivity as a very good proxy to the Equilibrium Local weather Sensitivity ECS, lengthy durations of 15 years had been utilized for figuring out the typical slopes in T_S(t) and F_GHG(t). Outcomes are plotted in fig.1, however given the small ∆F_GHG values earlier than say 1920, one ought to take the values earlier than that point, not too severe.

The nonetheless rocky (black) curve reveals that ∆T_S/∆F_GHG yields “any” worth for the local weather sensitivity, even adverse ones throughout 1950-1975, the years of “World Cooling”

that local weather scientists appear to have forgotten.
Our local weather nevertheless, is fairly secure and accordingly, results from simply incremental quantities of additional GHG’s over a interval of 15 years, is not going to alter the local weather sensitivity dramatically. If there was simply the AGW-effect warming our local weather, a easy steadily rising temperature profile was to be anticipated.
However what we see, appears fairly totally different. If we translate this – 1/λ worth of say the final decade 2010-2020 into a worth for the ECS, the sensitivity that the IPCC is utilizing of their communications, we get ~ 2^oC. That is the supposed temperature improve from doubling the pre-industrial 280 ppm CO₂ in keeping with ΔF_2xCO2 = 3.0 W/m² from Van Wijngaarden and Happer [8]. Round 1980 that ECS would have been solely about 1^oC, however in the direction of 1940 it will have been virtually 8^oC. To be adopted by a particularly speedy decline in the direction of -2^oC across the fifties. World Cooling was “alarming” certainly.

As soon as, I criticized the CMIP6 forcings [4] as being too excessive, however tailored values would solely marginally change fig.1. It could anyhow present this “fingerprint” of pure causes for international warming. Not solely that different forcings are at play, but additionally that they have to be bigger than the forcing by GHG’s. Except in fact, our local weather isn’t the very secure system that I assume. So, when Willis Eschenbach was so form to share his CERES-database on WUWT [5], I noticed instantly alternatives to check that stability assertion and a few hypotheses I developed since these workout routines described above.
That assertion can certainly be simply checked with the CERES information over the interval 2000-2020. All vitality streams, both within the SW- or within the LW-channel are utterly mounted to their prime streams SW_IN and LW_OUT respectively.I haven’t seen ratios for which the annual averages modified greater than about 0.3% over this era. Robust variations had been solely discovered between all sky and clear sky, with surprisingly totally different results of clouds in both channel, and noteworthy variations between Northern- and Southern Hemispheres. These very secure all sky ratios, present how well-controlled our local weather system finally works. And that means, that we don’t should know a lot about what’s occurring inside this “black field” that we name “local weather”, to know the results of perturbations.
This complicated local weather system mirrored in as an illustration the Trenberth kind diagrams, is absolutely ruled by these two, spectrum-wise non-overlapping vitality flows SW_IN and LW_OUT, and their values at TOA. These flows solely “contact” one another on the Earth’ floor the place the primary is being transferred into the latter and all the opposite vitality flows are simply “good to know”.

However what about these giant local weather feedbacks? Thankfully, being caught in an issue, there’s all the time a technique out: “again to fundamentals”. And that climate-basics is fairly easy the relation between floor temperature T_S, incoming shortwave photo voltaic vitality SW_IN and outgoing longwave IR radiation LW_OUT, given by the Earth’ vitality steadiness on the prime of the environment (TOA) by way of:

C dT_S/dt = SW_IN – LW_OUT = F_TOA                                        (1)

In eq.1, C is the efficient thermal capability per floor space of the Earth’ system and T a system-characteristic temperature. In apply, the floor temperature T_S shall be thought to be the attribute climate-temperature for apparent causes. In equilibrium, ∂T_S/∂t = F_TOA = 0.

I’m not going to repeat all of the steps that one can discover in any local weather science textbook, however merely state crucial components derived from eq.1, beginning with the overall assumption that adjustments in radiative flux at TOA are proportional to floor temperature adjustments:

∆F_TOA = λ∆T_S                                                                         (2)

a 1^st order linear relation between the temperature change ∆T_S and adjustments in radiative flux ∆F_TOA. It’s unbiased from any assumption about what’s driving our local weather. The inverse of the fixed λ may be thought to be our fundamental local weather sensitivity. By introducing small perturbations in eq.1, so known as forcings ∆F we derive the well-known relation typically used to find out the local weather sensitivity:

– 1/λ = ∆T_S/∆F                                                                       (3)

During which ∆T_S is the change in floor temperature T_S, and ∆F the “forcing” that induces an imbalance. The time period λ, which ought to in precept be equal to the one in eq.2, is now known as a “suggestions”, in view of the local weather response to compensate that forcing, and is subsequently by conference “adverse”. This eq.3 holds for an entire restoration of equilibrium and that’s solely at “infinity”. For a dynamic evaluation we frequently see this components with a denominator (∆F – ∆N) the place ∆N represents the (relaxation) imbalance at TOA. For a time interval of say 2-3x the thermal leisure time of our planet, estimated at 3-5 years, one can assume ∆N to be small and eq.3 is sufficiently correct. I used eq.3 in fig.1 on this solution to calculate -1/λ as the worth of the local weather sensitivity to GHG-forcings.
The final vital relation for use is the expression for the Planck suggestions parameter:

– λ_PL = 4 SW_IN/T_S                                                                     (4)

The shortwave photo voltaic radiation SW_IN as utilized in eq.1. is in literature typically written as (1  ̶  α)Φ₀ with the albedo α and the typical photo voltaic depth Φ₀ in house. The Planck suggestions parameter λ_PL determines the way in which our local weather reacts to disturbances within the system. It’s the consequence of eq.2 for our current local weather and unbiased from any assumptions apart from that the Stefan-Boltzmann regulation determines the LW vitality circulation from the floor. Consequently, – 1/λ_PL also needs to be by definition our local weather sensitivity to disturbances like the results of GHG’s.

However apparently, local weather scientists produce other concepts. I shall come again on this problem, however first we’re going to apply eq.2 to investigate some CERES information, particularly the radiation measurements at TOA. We’ll take a look at all sky information solely.
In fig.2 the values for SW_IN and LW_OUT at TOA are plotted for the interval 2000-2020. These are transferring annual averages to suppress all short-term variations. Nonetheless, they’re nonetheless fairly “rocky”, however their traits appear secure, and in common, going up. Their absolute values may be questioned for his or her accuracy, however I simply want their rather more dependable slopes.
We rewrite eq.2 for the local weather sensitivity as:

1/λ = (∂T_S/∂t)/(∂F_TOA /∂t)                               (5)

One can now immediately calculate the local weather sensitivity that ruled our local weather throughout that interval. With the slopes that the CERES information present: ∂/∂t (SW_IN-LW_OUT) = 0.41 W/m²/decade (fig.2), and from ∂T_S/∂t = 0.125 Okay/decade, we calculate 1/λ = 0.30/Okay/W/m². I might even have used the UAH LT development of 0.13 Okay/decade, with 1/λ = 0.32/Okay/W/m² however that wouldn’t have modified the conclusion that 1/λ is remarkably near this “fundamental” Planck worth of – 1/λ_PL = 0.30 Okay/W/m² as derived from eq.4.

This can’t be a coincidence and clearly reveals that the CERES information don’t help the outcomes of GCM calculations: there are not any giant local weather sensitivities, nor vital feedbacks. These CERES measurements affirm what fundamental local weather science predicts (if not prescribes), that our local weather is first and for all, managed by the inverse of the Planck suggestions parameter of about 0.3 Okay/W/m².

We will additionally take a look at the “stability” of the Planck suggestions parameter and see how that worth evolves over time. In fig.3, – 1/λ_PL is plotted vs. time, as calculated via eq.4 from the values derived from the CERES information. To suppress noise, annual averages are used to calculate its worth (4SW_IN/T_S)^-1 over the interval 2000-2020. Fig.3 makes instantly clear the excessive stability of this local weather sensitivity (thoughts the size) with lower than 0.2% change over 20 years. However furthermore, it’s declining and that’s opposite to what may be anticipated from an amplified warming impact of a excessive ECS with giant feedbacks.
Since GHG’s don’t act on the SW-channel, the nominator of eq.4 ought to be fixed whereas the denominator ought to improve. That suggests:
– 1/λ_PL ought to improve with warming/time, if the AGW-hypothesis could be right. It doesn’t.
It merely reveals that theSW_IN part is rising as an alternative, as already clear from fig.2, and even quicker than the floor temperature T_S, can observe.

I haven’t put any model-assumptions within the above evaluation, however simply seemed to the info. And people information don’t present any indicators of enormous local weather sensitivities and/or giant feedbacks.
The best way to justify this with that “settled” local weather science? Let’s first look to how and why local weather feedbacks have been launched. The derivation of eq.2-4 is predicated on a linear approximation so, 2^nd order results may very well be the rationale to develop λ with further phrases as these temperature feedbacks. However then, these 2^nd order feedbacks ought to be by definition, small.
On this case nevertheless, I assume these giant feedbacks to be only a postulate to “make up” for the distinction between statement/GCM calculation, and the consequence obtained by making use of eq.3 with λ_PL as proportionality. Fig.1 reveals, that the latter merely delivers by far not sufficient warming since 1980. For the calculated temperature anomalies from GCM’s it’s even worse. Based on eq.3 now we have apparently a big inequality, which can’t be from a 2^nd order impact in our local weather’s response:

ΔT_S = – ΔF_GHG/λ_AGW  >> – ΔF_GHG/λ_PL                                (6)  

Right here the subscript AGW is used to point that this reasoning is coupled to the AGW-hypothesis the place all local weather adjustments are attributable to growing GHG’s solely. Now to get the “right” warming related to this “recognized” forcing, the commonly accepted resolution is to adapt the local weather sensitivity by introducing the idea of additional local weather feedbacks in keeping with:

λ_AGW = λ_PL + λ₁ + λ₂ + λ₃ + ….. = λ_PL + ∑ λ_i = λ_PL + λ_FB                 (7)

The Plank suggestions parameter retains taking part in its function, however it’s apparent from eq.6 that the mixed feedbacks λ_FB must be giant and with an reverse signal to λ_PL to get |λ_AGW| << |λ_PL|. Thoughts, that these mixed feedbacks show a “feedforward” character and thus, improve warming results from GHG-forcings to suit a higher-than-expected ΔT_S. The arguments that this can be a good thought, are all very believable. Take the so-called Water Vapor suggestions λ_WV: growing GHG’s yield warming, which boosts water-evaporation. Hotter air can include extra water vapor. Being a powerful greenhouse gasoline itself, extra water vapor yields the next temperature. Or take the Albedo suggestions λ_AL: increased temperatures soften the polar caps, thus reducing the general reflection. Much less reflection implies extra photo voltaic vitality absorption by the Earth and so, it warms. These are all scientifically “sound” arguments.

However at what temperature will that feedforward mechanism lastly cease? Furthermore, we definitely had local weather adjustments prior to now with warming results comparable to those who GHG’s induce as we speak. So, these feedbacks ought to already be “half and parcel” of the Planck suggestions. What makes GHG-forcings then so particular? The evaluation of λ_PL and the local weather sensitivity derived from the CERES radiation imbalance information, are giving a transparent reply: nothing particular! The actual problem is: local weather sensitivity is a (close to) mounted parameter, and never a freely adaptable one relying on to the sort of forcing at hand. Massive feedbacks are simply because of the false impression that GHG’s are “the one present on the town”.

The inequality in eq.6 can be restored by altering ΔF whereas maintaining λ_AGW = λ_PL. Simply settle for one other forcing ΔF_SW subsequent to the GHG-forcing ΔF_GHG, as I did intuitively in analyzing cloud-effects [3]:

ΔT_S = – (ΔF_GHG + ΔF_SW)/λ_PL                           (8)

The subscript SW signifies a forcing that primarily acts on the SW_IN-channel in eq.1. That isn’t by hypothesis, however the one choice to clarify the constructive change in SW_IN in addition to LW_OUT, as in fig.2.
The AGW-hypothesis can merely by no means clarify an growing LW_OUT by rising GHG-forcings solely!
The reasoning behind that assertion is straightforward: though ΔF_SW and ΔF_GHG are each forcings that improve the floor temperature, they show fairly totally different “fingerprints” at TOA. A GHG-forcing ΔF_GHG will decrease LW_OUT and the local weather response to extend T_S is fed by a relentless SW_IN. That improve in T_S will finally restore the lowered LW_OUT to its previous worth (see additionally fig.4). In case of a shortwave forcing ΔF_SW, ΔT_S comes immediately from this extra SW_IN and thus, will improve LW_OUT completely. In a dynamic scenario with an growing forcing, a GHG-forcing with e.g., ∂F_GHG/∂t = fixed, will yield ∂LW_OUT/∂t ≈ ∂SW_IN/∂t = 0. However a ∂F_SW/∂t = fixed i.e., ∂SW_IN/∂t > 0, will yield ∂LW_OUT/∂t > 0. Each constructive slopes within the SW-case are the “fingerprint” at TOA as presently noticed (see fig.2).

Adherents to the AGW-hypothesis will instantly declare that enormous feedbacks affecting the SW_IN part equivalent to Albedo- and Cloud suggestions will produce an analogous sample to that ΔF_SW > 0 case. True, however simply in precept as there are a variety of arguments towards that declare. Initially, the strongest suggestions i.e., from Water Vapor acts on the LW-channel suppressing LW_OUT even additional. Secondly, Albedo- and Cloud suggestions ship collectively not rather more than 1 W/m²/Okay [13], which may by no means clarify the 1.38 W/m² improve within the SW_IN as measured by CERES. It could require an accompanying temperature improve of 1 – 1.5 ^oC between 2000 and 2020, which is way past any statement. Nonetheless, most significantly, it will solely be doable when the slopes of the 2 traits are a lot nearer, in step with a a lot bigger local weather sensitivity. The evaluation making use of eq.5 on the CERES information in fig.2 has proven already that (∂SW_IN/∂t – ∂LW_OUT/∂t) is set by the Planck suggestions solely. Different feedbacks simply don’t play a lot of a job in fig.2.

There are a number of choices for such SW_IN-forcings. Clouds, and particularly the low hanging clouds, are for me choice #1 as they affect each SW- and LW channels, be it fairly in a different way. From the Cloud Radiative Impact (CRE) out of CERES information, we all know that the net-effect favors a ΔF_SW contribution in eq.8, as additionally concluded in my earlier work [1][3]. Since clouds do act on SW_IN differently than on LW_OUT, we don’t even want a change in common cloudiness. A re-distribution over the assorted latitudes is adequate as (SW_IN – LW_OUT) varies from extremely constructive to extremely adverse, going from the equator to the poles [12].  Modifications within the stratospheric Ozone, and/or in UV-radiation associated adjustments because of the cyclic conduct of the Solar, present potentialities for solar-related forcings as nicely. However different explanations are definitely to not be excluded.

Eq.8 additionally clarifies a serious attribute of the AGW-hypothesis, particularly ΔF_SW = 0. Given the choices for ΔF_SW, one might additionally state that the AGW-hypothesis “denies” pure causes for international warming. That is precisely IPCC’s place [9] and implicitly, additionally utilized in GCM calculations. 

The distinction between these two choices, both introduce further feedbacks (the AGW-hypothesis), or settle for different forcings (this work), may be simply demonstrated. Take into account a local weather with the choice for a step-wise change at t = 0 within the GHG forcing ΔF_GHG by +/- ΔR, and for a forcing within the SW channel ΔF_SW (∆SW in fig.4) variable in the identical means: +/- ΔR. In fig.4 the evolution over time of the parts that govern these two totally different views on their warming impact, is graphically displayed for the 6 most blatant mixtures. The ultimate adjustments in λΔT_S from these two views, are additionally given and in comparison with the anticipated worth in that specific state of affairs.
State of affairs #6 reveals what occurs as we speak in actuality: a rising temperature mixed with a rising LW but additionally a rising SW. State of affairs #2 displays todays IPCC-view. Attention-grabbing are state of affairs #3 and #5 with an an identical “zero net-warming” response. What to suggest right here? Cease emitting CO₂ in case of #3? For these eventualities with canceling forces for which no warming happens, eq. 6 produces giant, non-zero outcomes. As anticipated, eq.6 yields no warming from a photo voltaic forcing solely. The eventualities with GHG-forcings solely, are in fact appropriately represented by eq.6. All others are merely mistaken.
As eq. 8 “delivers” in all eventualities as anticipated, it merely reveals its validity and correctness. And thus:  
the commonly in local weather science utilized eq.6, is predicated on the mistaken assumption of ΔF_SW = 0.
No marvel, that the IPCC nonetheless retains this big selection of ECS values. It simply depends upon the time and circumstances i.e., the worth of ΔF_SW, what ECS worth eq.6 yields; simply look to the info in fig.1.

It’s attention-grabbing now to calculate the ratio of the derived local weather sensitivities out of each views, by eliminating ΔT_S in combining eq.6 and eq.8 (with AGW and PL as the standard subscripts additionally for ECS):

ECS_AGW/ECS_PL = λ_PL/λ_AGW = (ΔF_GHG + ΔF_SW)/(ΔF_GHG) = 1 + ΔF_SW/ΔF_GHG         (8)

For the interval 2000-2020 we discover from the CERES information (fig.2) ΔF_SW = ΔSW_IN = 1.38 W/m². From the CMIP6 forcings [6] we derive ΔF_GHG = 0.64 W/m², making the ratio ΔF_SW/ΔF_GHG = 2.2.
The local weather sensitivity that the IPCC is selling is thus 3.2x the “actual” sensitivity of our local weather system i.e., the inverse of the Planck suggestions parameter! This issue of three or extra sounds fairly acquainted, doesn’t it? To legitimize it, the idea of local weather feedbacks to bridge that hole between faux and actuality needed to be launched. They appear to be scientifically “sound” results however will not be primarily based on falsifiable physics. They’re constructs with just one function: to compensate for the denial of pure results that may trigger international warming.

From the ratio between ΔF_SW and ΔF_GHG, it’s also clear that the Solar is answerable for about 2/3 of the noticed warming since 2000, and even earlier. Whereas GHG’s may be answerable for the remaining. Certainly “may be”, as I’ve simply taken ΔF_GHG from an estimated/modelled forcing by NASA [6]. In “Outdoors the Black Field” on WUWT, I strongly questioned these information as being too excessive [4]. Nonetheless, this 2:1 ratio helps the evaluation of the impact of brightening in The Netherlands [1] in addition to my suggestions evaluation [3]. Globally, growing SW_IN (fig.2), will need to have created a lot of the noticed warming. The expansion within the atmospheric focus of CO₂ can solely have performed a minor function, because the rising LW_OUT radiation in fig.2 confirms this a lot bigger SW-channel impact.

Anyhow, the ultimate query stays: “what about these mistaken outcomes of GCM calculations?”
Personally, I do imagine that almost all scientists behind local weather fashions do, and have all the time performed, their utmost to simulate Earth’ local weather to one of the best of their data. Nonetheless, making them extraordinarily detailed with complicated surfaces, coupled oceans, melting ice-caps or no matter interactions “contained in the field”, will most likely not make an enormous distinction in calculated local weather sensitivities.
Then again, these excessive sensitivities, nor these accompanying giant feedbacks are explicitly entered into GCM’s algorithms; they’re simply the results of analyzing their outputs. So, now we have to search for the purpose within the course of the place the AGW-assumption of “no pure forcings” i.e., ΔSW_IN= 0, has its affect and thus, “sneaks” into these GCM-simulations. To my understanding, that may solely occur throughout the tuning course of to generate a local weather that runs over an extended interval with a relentless conduct. As soon as such stability is created, that AGW-characteristic of ΔF_SW = 0, is an integral a part of this specific local weather as inner dependencies are tuned to it. Then, including further GHG’s to that tuned environment to calculate its local weather reactions, might very nicely ship these exaggerated warmings.
However such a secure and fixed local weather has by no means existed. Historical past has proven sturdy pure fluctuations time and again. Even throughout my very own, human time scale, the unexplained World Cooling of the 1950-1975 interval has proven that nothing is fixed in our local weather. GCM-algorithms primarily based on correct physics are in all probability not dangerous in any respect, besides could also be for the modelling of clouds. Their preliminary situations to run them nevertheless, may be essentially mistaken and distorting their output.

I can’t provide you with some other rationalization, and if legitimate, this will simply be solved by tuning to e.g., these CERES information or different “recognized” local weather (re-analysis) information from the current previous.
Nonetheless, the true downside created with this evaluation is, that forecasting with GCM’s has turn into a ineffective and meaningless train so long as we can’t reliably forecast pure adjustments in SW_IN. For the anthropogenic half it’s fairly clear: with a development to a most CO₂-level of 560 ppm, even beneath a sensible ‘enterprise as traditional’ state of affairs [11], there’s definitely not more than about 0.4^oC to go.

Advert Huijser, October 2022

Added after completion: In a sequence of posts https://wattsupwiththat.com/2022/10/21/scatterplot-sensitivity/ , Willis Eschenbach lately printed plenty of scatterplots from 1×1 diploma gridded CERES information. From these information, common local weather sensitivities are calculated for photo voltaic radiation of 1/λ_SW = 0.16 Okay/W/m², and for the greenhouse impact 1/λ_GHG = 0.58 Okay/W/m², respectively (adverse suggestions indicators are ignored for simplicity). These values are derived by assigning floor temperatures to both pure photo voltaic (∆F_GHG = 0), or the pure GHG trigger (∆F_SW = 0). By taking nevertheless, the relative contribution of the forcings by photo voltaic ∆F_SW and GHG’s ∆F_GHG with a ratio of two.2 as derived from eq.8 on this work under consideration, the typical local weather sensitivity for all forcings may be calculated as:

1/λ = (2.2 x 1/λ_SW + 1 x 1/λ_GHG)/3.2 = 0.29 Okay/W/m²,

shut sufficient to the 0.3 Okay/W/m² of the inverse Planck suggestions parameter, to conclude that additionally in Eschenbach’s analyses this Planck suggestions parameter is the climate-change figuring out issue.

References:

1. See for a abstract, https://klimaatgek.nl/wordpress/2020/12/01/de-zon-en-de-opwarming-van-nederland/#more-6953  (In Dutch however on-site translation by Google-translate obtainable)
2. https://www.knmi.nl/kennis-en-datacentrum/achtergrond/knmi-14-klimaatscenario-s
3. A. Huijser (2021), https://www.clepair.web/clouds-AdHuijser.pdf
4. A. Huijser (2022), https://wattsupwiththat.com/2022/02/21/outside-the-black-box/
5. W. Eschenbach (2022), https://wattsupwiththat.com/2022/09/08/the-ceres-data/
6. https://information.giss.nasa.gov/modelforce/
7. https://www.metoffice.gov.uk/hadobs/hadcrut5/
8. W.A. van Wijngaarden and W. Happer (2021), Relative Efficiency of Greenhouse Molecules, https://arxiv.org/abs/2103.16465v1
9. IPCC_AR6_WGI_Full_Report, A.4.4.
10. https://earthobservatory.nasa.gov/options/OceanCooling
11. https://www.climategate.nl/2022/09/pfff-gelukkig-nog-maar-ongeveer-06-graden-c-te-gaan/
12. https://andymaypetrophysicist.com/2022/09/22/the-winter-gatekeeper-hypothesis-vii-a-summary-and-some-questions/
13. S. C. Sherwood, et al. (2020). An evaluation of Earth’s local weather sensitivity utilizing a number of strains of proof, Opinions of Geophysics, 58, https://doi.org/10.1029/2019RG000678

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