World of Climate Change Infographics

Raymond of RiC-Communications studio created infographics on CO2 for improving public awareness.  He produced 13 interesting slides which are presented in the post World of CO2 Infographics  A second project was created on a related theme The World of Climate Change comprising six charts, including one regarding Alpine glacier studies by two prominent geologists.  In addition, Raymond was able to consult the work of  these two experts in their native German language.

This project is The World of Climate Change

Infographics can be helpful, in making things simple to understand. Climate change is a complex topic with a lot of information and statistics. These simple step by step charts are to better understand what is occurring naturally and what could be caused by humans. What is cause for alarm and what isn’t cause for alarmism if at all. Only through learning is it possible to get the big picture so as to make the right decisions for the future.

– N° 1 600 million years of global temperature change
– N° 2 Earth‘s temperature record for the last 400,000 years
– N° 3 Holocene period and average northern hemispheric temperatures
– N° 4 140 years of global mean temperature
– N° 5 120 m of sea level rise over the past 20‘000 years
– N° 6 Eastern European alpine glacier history during the Holocene period.

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Summer Temperatures (May – September) A rise in temperature during a warming period will result in a glacier losing more surface area or completely vanishing. This can happen very rapidly in only a few years or over a longer period of time. If temperatures drop during a cooling period and summer temperatures are too low, glaciers will begin to grow and advance with each season. This can happen very rapidly or over a longer period in time. Special thanks to Prof. em. Christian Schlüchter / (Quartärgeologie, Umweltgeologie) Universität Bern Institut für Geologie His work is on the Western Alps and was so kind to help Raymond make this graphic as correct as possible.

Comment:

This project explored information concerning how aspects of the world climate system have changed in the past up to the present time.  Understanding the range of historical variation and the factors involved is essential for anticipating how future climate parameters might fluctuate.

For example:

The Climate Story (Illustrated) looks at the temperature record.

H20 the Gorilla Climate Molecule looks at precipitation patterns.

Data vs. Models #2: Droughts and Floods looks at precipitation extremes.

Data vs. Models #3: Disasters looks at extreme weather events.

Data vs. Models #4: Climates Changing looks at boundaries of defined climate zones.

And in addition, since Chart #5 features the Statue of Liberty, here are the tidal gauge observations there compared to climate model projections:

NYC past & projected 2020

Beware Energy Balance Cartoons

Figure 1. The global annual mean energy budget of Earth’s climate system (Trenberth and Fasullo, 2012.)

Recently in a discussion thread a warming proponent suggested we read this paper for conclusive evidence. The greenhouse effect and carbon dioxide by Wenyi Zhong and Joanna D. Haigh (2013) Imperial College, London. Indeed as advertised the paper staunchly presents IPCC climate science. Excerpts in italics with my bolds.

IPCC Conception: Earth’s radiation budget and the Greenhouse Effect

The Earth is bathed in radiation from the Sun, which warms the planet and provides all the energy driving the climate system. Some of the solar (shortwave) radiation is reflected back to space by clouds and bright surfaces but much reaches the ground, which warms and emits heat radiation. This infrared (longwave) radiation, however, does not directly escape to space but is largely absorbed by gases and clouds in the atmosphere, which itself warms and emits heat radiation, both out to space and back to the surface. This enhances the solar warming of the Earth producing what has become known as the ‘greenhouse effect’. Global radiative equilibrium is established by the adjustment of atmospheric temperatures such that the flux of heat radiation leaving the planet equals the absorbed solar flux.

The schematic in Figure 1, which is based on available observational data, illustrates the magnitude of these radiation streams. At the Earth’s distance from the Sun the flux of radiant energy is about 1365Wm−2 which, averaged over the globe, amounts to 1365/4 = 341W for each square metre. Of this about 30% is reflected back to space (by bright surfaces such as ice, desert and cloud) leaving 0.7 × 341 = 239Wm−2 available to the climate system. The atmosphere is fairly transparent to short wavelength solar radiation and only 78Wm−2 is absorbed by it, leaving about 161Wm−2 being transmitted to, and absorbed by, the surface. Because of the greenhouse gases and clouds the surface is also warmed by 333Wm−2 of back radiation from the atmosphere. Thus the heat radiation emitted by the surface, about 396Wm−2, is 157Wm−2 greater than the 239Wm−2 leaving the top of the atmosphere (equal to the solar radiation absorbed) – this is a measure of ‘greenhouse trapping’.

Why This Line of Thinking is Wrong and Misleading
Principally, the Earth is not a disk illuminated 24/7 by 1/4 of solar radiant energy. 

That disk in the cartoon denies the physical reality of a rotating sphere, and completely distorts the energy dynamics.  Christos Vournas addresses this issue directly in deriving his planetary temperature equation that corresponds to NASA satellite measurements of planets and moons in our solar system.  Previous posts provide background for this one focusing on the radiant heating of the rotating water planet we call Earth (though Ocean would be more accurate).  See How to Calculate Planetary Temperatures and Earthshine and Moonshine: Big Difference.  

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Φ – is the dimensionless Solar Irradiation accepting factor. It recognizes that a sphere’s surface absorbs the incident solar irradiation not as a disk of the same diameter, but accordingly to its spherical shape. For a smooth spherical surface Φ = 0,47

The classical blackbody surface properties

A blackbody planet surface is meant as a classical blackbody surface approaching.  Here are the blackbody’s properties:

1. Blackbody does not reflect the incident on its surface radiation. Blackbody absorbs the entire radiation incident on its surface.

2. Stefan-Boltzmann blackbody emission law is:   Je = σ*Τe⁴

Notice:

Te is the blackbody’s temperature (surface) at every given moment. When the blackbody is not irradiated, the classical blackbody gradually cools down, gradually emitting away its accumulated energy.  The classical blackbody concept assumes blackbody’s surface being warmed by some other incoming irradiation source of energy – see the Sun’s paradigm.  Sun emits like a blackbody, but it emits its own inner energy source’s energy. Sun is not considered as an irradiation receiver. And sun has a continuous stable temperature.

Therefore we have here two different blackbody theory concepts.

a. The blackbody with the stable surface temperature due to its infinitive inner source (sun, stars).
b. The blackbody with no inner energy source.

This blackbody’s emission temperature relies on the incoming outer irradiation only.

Also in the classical blackbody definition it is said that the irradiation incident on the blackbody is totally absorbed, warms the blackbody and achieves an equilibrium emission temperature Te.  It is an assumption.

This assumption, therefore, led to the next assumption: the planet like a blackbody emitting behavior.  And, consequently, it resulted to the planet’s Te equation, in which it is assumed that planet’s surface is interacting with the incoming irradiation as being in a uniform equilibrium temperature.

Consequently it was assumed that planet’s surface had a constant equilibrium temperature (which was only the incident solar irradiation dependent value) and the only thing the planet’s surface did was to emit in infrared spectrum out to space the entire absorbed solar energy.

3. When irradiated, the blackbody’s surface has emission temperature according to the Stefan-Boltzmann Law:

Te = (Total incident W /Total area m² *σ)¹∕ ⁴ K

σ = 5,67*10⁻⁸ W/m²K⁴, the Stefan-Boltzmann constant.

Notice: This emission temperature is only the incoming irradiation energy depended value. Consequently when the incoming irradiation on the blackbody’s surface stops, at that very moment the blackbody’s emission temperature disappears.  It happens because no blackbody’s surface accumulates energy.

4. Blackbody interacts with the entire incident on the blackbody’s surface radiation.

5. Blackbody’s emission temperature depends only on the quantity of the incident radiative energy per unit area.

6. Blackbody is considered only as blackbody’s surface physical properties. Blackbody is only a surface without “body”.

7. Blackbody does not consist from any kind of a matter. Blackbody has not a mass. Thus blackbody has not a specific heat capacity.  Blackbody’s cp = 0.

8. Blackbody has surface dimensions. So blackbody has the radiated area and blackbody has the emitting area.

9. The entire blackbody’s surface area is the blackbody’s emitting area.

10. The blackbody’s surface has an infinitive conductivity.

11. All the incident on the blackbody’s surface radiative energy is instantly and evenly distributed upon the entire blackbody’s surface.

12. The radiative energy incident on the blackbody’s surface the same very instant the blackbody’s surface emits this energy away.

A Real Planet is Not a Blackbody

But what happens there on the rotating real planet’s surface?

The rotating real planet’s surface, when it turns to the sunlit side, is an already warm at some temperature, from the previous day, planet’s surface.

Thus, when assuming the planet’s surface behaving as a blackbody, we face the combination of two different initial blackbody surfaces.

a. The one with an inner energy source.

And

b. The one warmed by an outer irradiation.

The Real Planet’s Surface Properties:

1. The planet’s surface has not an infinitive conductivity. Actually the opposite takes place. The planet’s surface conductivity is very small, when compared with the solar irradiation intensity and the planet’s surface infrared emissivity intensity.

2. The planet’s surface has thermal behavior properties. The planet’s surface has a specific heat capacity, cp.

3. The incident on the planet solar irradiation is not being distributed instantly and evenly on the entire planet’s surface area.

4. Planet does not accept the entire solar irradiation incident in planet’s direction. Planet accepts only a small fraction of the incoming solar irradiation. This happens because of the planet’s albedo, and because of the planet’s smooth and spherical surface reflecting qualities, which we refer to as “the planet’s solar irradiation accepting factor Φ”.

Planet reflects the (1-Φ + Φ*a) portion of the incident on the planet’s surface solar irradiation.  And  Planet absorbs only the Φ(1 – a) portion of the incident on the planet’s surface solar irradiation.

Here “a” is the planet’s average albedo and “Φ” is the planet’s solar irradiation accepting factor.

For smooth planet without thick atmosphere, Earth included, Φ=0,47

5. Planet’s surface has not a constant intensity solar irradiation effect. Planet’s surface rotates under the solar flux. This phenomenon is decisive for the planet’s surface infrared emittance distribution.

The real planet’s surface infrared radiation emittance distribution intensity is a planet’s rotational speed dependent physical phenomenon.

Vournas fig1

Φ factor explanation

The Φ – solar irradiation accepting factor – how it “works”. It is not a planet specular reflection coefficient itself.

There is a need to focus on the Φ factor explanation. Φ factor emerges from the realization that a sphere reflects differently than a flat surface perpendicular to the Solar rays.

It is very important to understand what is really going on with planets’ solar irradiation reflection.

There is the specular reflection and there is the diffuse reflection.

The planet’s surface Albedo “a” accounts for the planet’s surface diffuse reflection. Albedo is defined as the ratio of the scattered SW to the incident SW radiation, and it is very much precisely measured (the planet Bond Albedo).

So till now we didn’t take in account the planet’s surface specular reflection. A smooth sphere, as some planets are, are invisible in space and have so far not been detected and the specular reflection not measured . The sphere’s specular reflection cannot be seen from the distance, but it can be seen by an observer situated on the sphere’s surface.

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Thus, when we admire the late afternoon sunsets on the sea we are blinded from the brightness of the sea surface glare. It is the surface specular reflection that we see then.

Jsw.absorbed = Φ*(1-a) *Jsw.incoming

For a planet with albedo a = 0 (completely black surface planet) we would have

Jsw.reflected = [1 – Φ*(1-a)]*S *π r² =

Jsw.reflected = (1 – Φ) *S *π r²

For a planet which captures the entire incident solar flux (a planet without any outgoing specular reflection) we would have Φ = 1

Jsw.absorbed = Φ*(1-a) *Jsw.incoming

Jsw.reflected = a *Jsw.incoming

And

For a planet with Albedo a = 1 , a perfectly reflecting planet

Jsw.absorbed = 0 (no matter what is the value of Φ)

In general:  The fraction left for hemisphere to absorb is  Jabs = Φ (1 – a ) S π r²

We have Φ for different planets’ surfaces varying  0,47 ≤ Φ ≤ 1

And we have surface average Albedo “a” for different planets’ varying  0 ≤ a ≤ 1

Notice:

Φ is never less than 0,47 for planets (spherical shape).

Also, the coefficient Φ is “bounded” in a product with (1 – a) term, forming the Φ(1 – a) product cooperating term. Thus Φ and Albedo are always bounded together.

The Φ(1 – a) term is a coupled physical term.

The Φ(1 – a) term “translates” the absorption of a disk into the absorption of a smooth hemisphere with the same radius.

When covering a disk with a hemisphere of the same radius the hemisphere’s surface area is 2π r². The incident Solar energy on the hemisphere’s area is the same as on the disk:  Jdirect = π r² S

But the absorbed Solar energy by the hemisphere’s area of 2π r² is:  Jabs = Φ*( 1 – a) π r² S

It happens because a smooth hemisphere of the same radius “r” absorbs only the Φ*(1 – a)S portion of the directly incident on the disk of the same radius Solar irradiation.

In spite of hemisphere having twice the area of the disk, it absorbs only the Φ*(1 – a)S portion of the directly incident on the disk Solar irradiation.

Gaseous Planets

Φ = 1 for gaseous planets, as Jupiter, Saturn, Neptune, Uranus, Venus, Titan.

Gaseous planets do not have a surface to reflect radiation. The solar irradiation is captured in the thousands of kilometers gaseous abyss. The gaseous planets have only the albedo “a”.

Heavy Cratered Planets

Φ = 1 for heavy cratered planets, as Calisto and Rhea ( not smooth surface planets, without atmosphere ).

The heavy cratered planets have the ability to capture the incoming light in their multiple craters and canyons. The heavy cratered planets have only the albedo “a”.

That is why the albedo “a” and the factor “Φ” we consider as different values. Both of them, the albedo “a” and the factor “Φ” cooperate in the

Energy in = Φ(1 – a) left side of the Planet Radiative Energy Budget.

Conclusively, the Φ -Factor is not the planet specular reflection portion itself.

The Φ -Factor is the Solar Irradiation Accepting Factor (in other words, Φ is the planet surface shape and roughness coefficient).

Bottom Line

What is going on here is that instead of Jabs.earth = 0,694* 1.361 π r² ( W ) we should consider Jabs.earth = 0,326* 1.361 π r² ( W ).

Averaged on the entire Earth’s surface we obtain:

Jsw.absorbed.average = [ 0,47*(1-a)*1.361 W/m² ] /4 =

= [ 0,47*0,694*1.361W/m² ] /4 = 444,26 W/m2 /4 = 111,07 W/m²

Jsw.absorbed.average = 111,07 W/m² or 111 W/m²

Example:  Comparing Earth and Europa

Earth / Europa satellite measured mean temperatures 288 K and 102 K comparison
All the data below are satellites measurements. All the data below are observations.

Planet Earth Europa
Tsatmean  288 K 102 K
R 1 AU 5.2044 AU
1/R² 1 0,0369
N 1 1/3.5512 rot/day
a 0.3 0.63
(1-a) 0.7 0.37
coeff 0.91469 0.3158

We could successfully compare Earth /Europa ( 288 K /102 K ) satellite measured mean temperatures because both Earth and Europa (moon of Jupiter) have two identical major features.

Φearth = 0,47 because Earth has a smooth surface and Φeuropa = 0,47 because Europa also has a smooth surface.

cp.earth = 1 cal/gr*°C, it is because Earth has a vast ocean. Generally speaking almost the whole Earth’s surface is wet. We can call Earth a Planet Ocean.  Europa is an ice-crust planet without atmosphere, Europa’s surface consists of water ice crust, cp.europa = 1cal/gr*°C.

The table below shows how well the universal equation estimates temperatures of planets and moons measured by NASA.

Planet Φ Te.correct  [(β*N*cp)¹∕ ⁴]¹∕ ⁴ Tmean  Tsat
Mercury  0.47 364 0.8953 325.83 340
Earth  0.47 211 1.3680 287.74 288
Moon  0.47 224 0.9978 223.35 220
Mars  0.47 174 1.2270 213.11 210
Io  1 95.16 1.1690 111.55 110
Europa  0.47 78.83 1.2636 99.56 102
Ganymede 0.47 88.59 1.2090 107.14 110
Calisto  1 114.66 1.1471 131.52 134 ±11
Enceladus  1 55.97 1.3411 75.06 75
Tethys  1 66.55 1.3145 87.48 86 ± 1
Titan  1 84.52 1.1015 96.03 93.7
Pluto  1 37 1.1164 41.60 44
Charon  1 41.9 1.2181 51.04 53
My Comment:

This post explains why it is an error to treat Earth (or any planetary body) as a classic blackbody in either the absorption of incident energy or in the emission of radiation.  Thus the typical energy balance cartoons are not funny, they are false and misleading.  A further error arises in claiming that greenhouse gases like CO2 in the atmosphere cause surface warming by trapping Earth radiation and slowing the natural cooling.  This fallacy is addressed directly in a previous post Why CO2 Can’t Warm the Planet.

The table above and graph below show that Earth’s warming factor is correctly calculated despite ignoring any effect from its thin atmosphere.

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Earthshine and Moonshine: Big Difference

earth moon highres

A previous post elaborated a rigorous equation from Christos Vournas for calculating surface temperatures of planets or moons, for comparison with NASA satellite measurements of such bodies in our solar system.  That post is How to Calculate Planetary Temperatures.

The image above presents the huge disparity in day and night temperatures between Earth and its Moon, and notes the role of ocean heat transport.  But as I have learned from Christos, there is much more to the story, and this post discusses these deeper implications.  He adds the rotational factor and its impact upon the radiation emitted by both bodies, ie. Earthshine and Moonshine (though obviously it is not simply visible light).  Excerpts from Vournas are in italics with my bolds.

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Moon and Earth – so close to each other – and so much different…

Moon is in our immediate neighborhood

Moon rotates around its axis at a slow rate of 29.5 days.  The day on the Moon is 14.75 earth days long, and the night on the Moon is also 14.75 Earth days long. 

Moon is in our immediate neighborhood. So Moon is at the same distance from the sun, as Earth, R=1 AU (astronomical unit).  The year average solar irradiation intensity on the top of atmosphere for Moon and Earth is the same

So = 1361 W/m².

We say “on the top of the atmosphere”, it means the solar intensity which reaches a celestial body and then falls on it. For certain then, during these 14.75 earth days long lunar day the Moon’s surface gets warmed at much higher temperatures than the Earth.

There is the Planet Surface Rotational Warming Phenomenon

I’ll try here in few simple sentences explain the very essence of how the planet rotational warming Phenomenon occurs.

Lets consider two identical planets F and S at the same distance from the sun.  Let’s assume the planet F spins on its axis Faster, and the planet S spins on its axis Slower.  Both planets F and S get the same intensity solar flux on their sunlit hemispheres. Consequently both planets receive the same exact amount of solar radiative energy.

The slower rotating planet’s S sunlit hemisphere surface gets warmed at higher temperatures than the faster rotating planet’s F sunlit hemisphere. The surfaces emit at σT⁴ intensity – it is the Stefan-Boltzmann emission law.

Thus the planet S emits more intensively from the sunlit side than the planet F.  There is more energy left for the planet F to accumulate then.  That is what makes the faster rotating planet F on the average a warmer planet.

That is how the Planet Surface Rotational Warming Phenomenon occurs.

And it becomes very cold on the Moon at night

Moon gets baked hard during its 14,75 earth days long lunar day.  And Moon also emits hard from its very hot daytime surface.  What else can the very hot surface do but to emit hard, according to the Stefan-Boltzmann emission Law.  The very hot surface emits in fourth power of its very high absolute temperature.

Jemit ~ T⁴

A warm object in space loses heat via emission. The hotter is the object, the faster it loses heat.  So there is not much energy left to emit during the 14.75 earth days long lunar night.

The Table below shows the implications:

Planet Tsat mean Rotations Tmin Tmax
Mercury 340 K 1/176 100K 700K
Earth 288 K 1
Moon 220 Κ 1/29.5 100K 390K
Mars 210 K 0.9747 130K 308K
Comparing Mars and Mercury

The closest to the sun planet Mercury receives 15.47 times stronger solar irradiation intensity than the planet Mars does.  However on the Mercury’s dark side Tmin.mercury = 100 K, when on the Mars’ dark side Tmin.mars = 130 K.

These are observations, these are from satellites the planets’ temperatures measurements.  And they cannot be explained otherwise but by the planet Mars’ 171.5 times faster rotation than planet Mercury’s spin.

Earth-Moon temperatures comparison -why the differences

The faster (than Moon) Earth’s rotation smooths the average heat. The higher (than Moon) Earth’s surface specific heat capacity(oceanic waters vs dry regolith), also smooths the average heat. Consequently the daytime Earth’s surface temperature (compared to Moon) lessens, and the nighttime Earth’s surface temperature (compared to Moon) rises. Earth receives the same amount of solar heat (per unit area) from sun as Moon – for the same albedo. And Earth emits the same amount of solar heat, as the Moon does.

But something else very interesting happens.

It is the difference between Earth’s and Moon’s emitting temperatures. At the daytime Earth’s surface is warmed at a much lower temperatures and therefore at the daytime Earth’s surface emits IR radiation at a much lower intensities. So the intensity of Earth’s daytime IR radiation is much lower (than Moon’s).

As a result, there is a great amount of energy – compared to Moon – “saved” on Earth during the daytime emission..  This “saved” energy should be emitted by Earth’s surface during the nighttime then. At the night-time Earth’s surface is warmer than Moon’s and therefore Earth’s surface at night-time is at a higher temperatures.  So the intensity of Earth’s night-time IR radiation is higher.

There is always a balance.  The energy in = the energy out

But again something else very interesting happens.

In order to achieve that balance Earth’s night-time IR emitting intensity should be much higher than the night-time IR emitting intensity of the Moon.  Now we should take notice of the nonlinearity of the Stefan-Boltzmann emission law. Consequently the night-time temperatures on Earth rise higher (compared to Moon) than the daytime temperatures on Earth lessens.

So the average Earth’s surface temperature is warmer (compared to the Moon). Thus Earth’s Tmean.earth = 288 K and Moon’s Tmean.moon = 220 K

The faster rotation and the higher specific heat capacity does not make sun to put more energy in the Earth’s surface. What the faster rotation and the higher specific heat capacity do is to modify the way Earth’s surface emits, the same amount as Moon, of energy (per unit area).

Earth emits IR radiation at lower temperatures during the daytime and at higher temperatures at night-time. Because of the nonlinearity of this process according to the Stefan-Boltzmann emission law, Earth ends up to have on average warmer surface than Moon.

The night-time temperatures on Earth rise higher (compared to Moon) than the day-time temperatures on Earth lessens. Earth receives (for the same albedo and per unit area) the same amount of solar energy as the Moon . This energy is “welcomed” on each planet and processed in a unique way for each planet.

To illustrate the above conclusions I’ll try to demonstrate on the Earth-Moon temperatures comparison rough example:

Surface temperatures

.min……mean……max

Tmin↑↑→T↑mean ←T↓max

Moon…100 K…220 K …390 K

Δ………..+84 K +68 K….- 60 Κ

Earth…184K↑↑.288 K↑.330 K↓

So we shall have for the faster rotating Earth, compared to the Moon:

Tmin↑↑→ T↑mean ← T↓max

+84↑↑→ +68↑mean ← -60↓

The faster a planet rotates (n2>n1) the higher is the planet’s average (mean) temperature T↑mean.

Note:  To emphasize we should mention that Moon’s max and min temperatures are measured on Moon’s equator, and Earth’s max and min temperatures are not.  Earth’s max and min temperatures are measured on continents, and not on oceanic waters. Otherwise the Δmin would have been even bigger and the Δmax would have been much smaller.

This rough example nevertheless illustrates that for the faster rotating and covered with water (higher cp) Earth compared with Moon the average temperature should be higher.

The planet’s faster rotation and the planet’s higher specific heat capacity “cp” not only smooths, but also processes ( Δmin > Δmax ), the same incoming solar heat, but in a different emission pattern.

Earth is warmer because Earth rotates faster and because Earth’s surface is covered with water

We had to answer these two questions:

1. Why Earth’s atmosphere doesn’t affect the Global Warming?

It is proven now by the Planet’s Mean Surface Temperature Equation calculations. There aren’t any atmospheric factors in the Equation. Nevertheless the Equation produces very reasonable results:

Tmean.earth = 287,74 K,  calculated by the Equation, which is the same as the Tsat.mean.earth = 288 K, measured by satellites.

Tmean.moon = 223,35 K, calculated by the Equation, which is almost identical with the Tsat.mean.moon = 220 K, measured by satellites.

2. What causes the Global Warming then?

The Global Warming is happening due to the orbital forcing.

And… what keeps Earth warm at Tmean.earth = 288 K, when Moon is at Tmean.moon = 220 K? Why Moon is on average 68 oC colder? It is very cold at night there and it is very hot during the day…

Earth is warmer because Earth rotates faster and because Earth’s surface is covered with water.

Does the Earth’s atmosphere act as a blanket that warms Earth’s surface?

No, it does not.

.

How to Calculate Planetary Temperatures

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In the second graph we have the Ratio of Planet Measured Temperature to the Corrected Blackbody Temperature (Tsat /Te.correct). Link [30] In this graph we use in (Tsat /Te.correct) the planet corrected blackbody temperatures – which are the planet effective temperatures Te.correct corrected by the use of the Φ -factor. The Φ = 0,47 for smooth surface planets and moons, and the Φ = 1 for the rough surface planets and moons. As we can see, in the second graph, the red dot planets and the green dot planets have stretched in a linear functional relation according to their Warming Factor = (β*N*cp)^1/16 values. The bigger is the planet’s or moon’s Warming Factor, the higher is the (Tsat /Te.correct) ratio. It is obviously a linearly related function.

On a recent comment thread at Climate Etc. Christos Vournas provided a link to his blog. After spending time reading his articles I made this post to introduce aspects of his studies and thinking that I find persuasive. His home page sets the theme The Planet Surface Rotational Warming Phenomenon. Below are just a few excerpts from Vournas’ blog in italics with my bolds.

Introduction

My name is Christos J. Vournas, M.Sc. mechanical engineer, living in Athens Greece. I launched this site to have an opportunity to publish my scientific discoveries on the Climate Change.  I have been studying the Planet Earth’s Climate Change since November 2015;

First I discovered the Reversed Milankovitch Cycle.

Then I found the faster a planet rotates (n2>n1) the higher is the planet’s average (mean) temperature T↑mean.

Φ – the next discovery – is the dimensionless Solar Irradiation accepting factor – very important

The further studies led me to discover the Rotating Planet Spherical Surface Solar Irradiation Absorbing-Emitting Universal Law and the Planet’s Without-Atmosphere Mean Surface Temperature Equation.

The Planet Surface Rotational Warming Phenomenon

It is well known that when a planet rotates faster its daytime maximum temperature lessens and the night time minimum temperature rises.

But there is something else very interesting happens. When a planet rotates faster it is a warmer planet. (It happens because Tmin↑↑ grows higher than T↓max goes down)

The faster a planet rotates (n2>n1) the higher is the planet’s average (mean) temperature T↑mean:

Tmin↑↑→ T↑mean ← T↓max

The understanding of this phenomenon comes from a deeper knowledge of the Stefan-Boltzmann Law. It happens so because when rotating faster a planet’s surface has a new radiative equilibrium temperatures to achieve.

which20moons20have20atmospheres

A Planet Without-Atmosphere Mean Surface Temperature Equation

A Planet Without-Atmosphere Mean Surface Temperature Equation derives from the incomplete Te equation which is based on the radiative equilibrium and on the Stefan-Boltzmann Law.

Using the new equation, the new estimate Tmean closely matches the estimate surface temperatures from satellite observations:

Planet Te.incomp Tmean Tsat.mean
Mercury 437,30K 323,11K 340K
Earth 255K 287,74K 288K
Moon 271K 221,74K 220K
Mars 209,91K 213,59K 210K

We have moved further from the incomplete effective temperature equation

Te = [ (1-a) S / 4 σ ]¹∕ ⁴

(which is in common use right now, but actually it is an incomplete planet Te equation and that is why it gives us very confusing results)

a – is the planet’s surface average albedo

S – is the solar flux, W/m²

σ = 5,67*10⁻⁸ W/m²K⁴, the Stefan-Boltzmann constant

We have discovered the Planet Without-Atmosphere Mean Surface Temperature Equation

Tmean = [ Φ (1-a) S (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴ (1)

The Planet Without-Atmosphere Mean Surface Temperature Equation is also based on the radiative equilibrium and on the Stefan-Boltzmann Law.

The Equation is being completed by adding to the incomplete Te equation the new parameters Φ, N, cp and the constant β.

Φ – is the dimensionless Solar Irradiation accepting factor

Φ – is the dimensionless Solar Irradiation accepting factor.  It is a realizing that a sphere’s surface absorbs the incident solar irradiation not as a disk of the same diameter, but accordingly to its spherical shape.  For a smooth spherical surface Φ = 0,47

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N – rotations /day, is the planet’s axial spin

cp – cal /gr*oC, is the planet’s surface specific heat capacity

β = 150 days*gr*oC/rotation*cal – is the Rotating Planet Surface Solar Irradiation Absorbing-Emitting Universal Law constant.

The Planet Without-Atmosphere Mean Surface Temperature Equation is also based on the radiative equilibrium and on the Stefan-Boltzmann Law.

But the New Equation doesn’t consider planet behaving as a blackbody, and the New Equation doesn’t state planet having a uniform surface temperature.

Interesting, very interesting what we see here:

Planet Tsat mean Rotations Tmin Tmax
Mercury 340 K 1/176 100K 700K
Earth 288 K 1
Moon 220 Κ 1/29,5 100K 390K
Mars 210 K 0,9747 130K 308K

Earth and Moon are at the same distance from the Sun R = 1 AU.

Earth and Mars have almost the same axial spin N = 1rotation /day.

Moon and Mars have almost the same satellite measured average temperatures 220 K and 210 K.

Mercury and Moon have the same minimum temperature 100 K.

Mars’ minimum temperature is 130 K, which is much higher than for the closer to the Sun Mercury’s and Moon’s minimum temperature 100 K.

The planet’s effective temperature old Te = [ (1-a) S /4σ ]¹∕ ⁴ incomplete equation gives very confusing results.

And the faster rotating Earth and Mars appear to be relatively warmer planets.

We ended up to the following remarkable results

To be honest with you, at the beginning, I was surprised myself with these results.

You see, I was searching for a mathematical approach…

We use more major parameters for the planet’s surface temperature equation.

Planet is a celestial body with more major features when calculating planet effective temperature to consider. The planet without-atmosphere effective temperature calculating formula has to include all the planet’s basic properties and all the characteristic parameters.

3. The planet’s axial spin N rotations/day.

4. The thermal property of the surface (the specific heat capacity cp).

5. The planet’s surface solar irradiation accepting factor Φ ( the spherical surface’s primer solar irradiation absorbing property ).

Altogether these parameters are combined in the Planet’s Without-Atmosphere Surface Mean Temperature Equation:

Tmean.planet = [ Φ (1-a) So (1/R²) (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴ (1)

Earth’s Without-Atmosphere Mean Surface Temperature Equation
Tmean.earth

So = 1.361 W/m² (So is the Solar constant)

Earth’s albedo: aearth = 0,306

Earth is a rocky planet, Earth’s surface solar irradiation accepting factor Φearth = 0,47 (Accepted by a Smooth Hemisphere with radius r sunlight is S*Φ*π*r²(1-a), where Φ = 0,47)

β = 150 days*gr*oC/rotation*cal – is a Rotating Planet Surface Solar Irradiation Absorbing-Emitting Universal Law constant

N = 1 rotation /per day, is Earth’s sidereal rotation spin

cp.earth = 1 cal/gr*oC, it is because Earth has a vast ocean.

Generally speaking almost the whole Earth’s surface is wet. We can call Earth a Planet Ocean.

σ = 5,67*10⁻⁸ W/m²K⁴, the Stefan-Boltzmann constant

Earth’s Without-Atmosphere Mean Surface Temperature Equation Tmean.earth is:

Tmean.earth = [ Φ (1-a) So (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴

Τmean.earth = [ 0,47(1-0,306)1.361 W/m²(150 days*gr*oC/rotation*cal *1rotations/day*1 cal/gr*oC)¹∕ ⁴ /4*5,67*10⁻⁸ W/m²K⁴ ]¹∕ ⁴ =

Τmean.earth = [ 0,47(1-0,306)1.361 W/m²(150*1*1)¹∕ ⁴ /4*5,67*10⁻⁸ W/m²K⁴ ]¹∕ ⁴ =

Τmean.earth = ( 6.854.897.370,96 )¹∕ ⁴ = 287,74 K

Tmean.earth = 287,74 Κ

And we compare it with the

Tsat.mean.earth = 288 K, measured by satellites.

These two temperatures, the calculated one, and the measured by satellites are almost identical.

Conclusions:

The equation produces remarkable results.

A Planet Without-Atmosphere Surface Mean Temperature Equation gives us a planet surface mean temperature values very close to the satellite measured planet mean temperatures.

It is a Stefan-Boltzmann Law Triumph! And it is a Milankovitch Cycle coming back! And as for NASA, all these new discoveries were possible only due to NASA satellites planet temperatures precise measurements!

The calculated planets’ temperatures are almost identical with the measured by satellites.

The 288 K – 255 K = 33 oC difference does not exist in the real world.

The air density is some 1,23 kg/m³, and it is a very thin atmosphere of 1 bar at sea level.… In Earth’s very thin atmosphere  there are on average 1% H₂O and 0,04% CO₂.  Those two are trace gases in Earth’s very thin atmosphere. H₂O and CO₂ very tiny contents in earth’s atmosphere are not capable to absorb the alleged huge “absorbed by atmosphere 70%-85% outgoing IR radiation” portion.

The Earth’s atmosphere is very thin. There is not any measurable Greenhouse Gasses Warming effect on the Earth’s surface.

Postscript:  Reversed Milankovitch Cycle

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i285978589391487304._szw1280h1280_

Of course climate changes.  And of course the planet’s rotational spin is almost constant.  Also Earth has a very thin atmosphere; Earth has a very small greenhouse phenomenon in its atmosphere and it doesn’t warm the planet.

The cause of climate change is not the Earth’s atmosphere. The cause of climate change is orbital.  Milutin Milankovitch has explained everything 100 years ago.

The ( Ṃ ↓ ) represents the Original Milankovitch Cycle grapheme.  And the ( Ẇ ↑ ) represents the Reversed Milankovitch Cycle grapheme.

( Ṃ ↓ ) – supposedly this is the Original Milankovitch Cycle. Please take notice of the dot under ( Ṃ ↓ ).  The dot’s position represents the present time, when Planet Earth is in Original Milankovitch Cycle Minima:  The Original Milankovitch Cycle shows a cooling trend.

( Ẇ ↑ ) The Reversed Milankovitch Cycle shows a warming trend.

Milankovitch had to reverse his cycle to match the instrumental data. But he didn’t have time.  It was a critical mistake in Milankovitch’s assumptions.  Now it is time for us to make the necessary correction. 100 years have passed, Milankovitch agrees, if it is necessary, for us to make a correction.

When comparing with the Perihelion point, which is at January 2, the solar irradiance Earth receives now is 7% less. As a result we have at the North Hemisphere much cooler summers and much warmer winters.  In 10.000 (ten thousand) years from now, Earth’s axis will be pointing at star Vega, instead of Polaris at which it points now. So in 10.000 years the Winter Solstice will occur when Earth is in Aphelion (it happens now with Earth in Perihelion).

As a result in 10.000 years we would have at the North Hemisphere much warmer summers and much cooler winters. A shift of 7% in the Hemispheres’ insolation intensity will happen.  Instead of the Southern Hemisphere (as it happens now) with its vast oceans accumulative capacity… there would be a +7% stronger insolation on the North Hemisphere’s plethora of continental areas.

We know continents do not accumulate heat so much effectively as oceans do, thus Earth will gradually cool down, until a New Ice Age commences!

As for the current warming phase – we still receive the +7% solar energy onto Southern Hemisphere’s oceans… and oceans willingly accumulate the excess solar energy…It happens so during the current Winter Solstices, when Earth is still tilted towards sun with its Southern Hemisphere’s vast oceanic waters.

The warming trend we observe now started some 6.500 years ago. It is a very slow process. The MWP ( the Medieval Warm Period ) is a confirmation of the existence of a long warming trend.  The LIA ( the Little Ice Age ) was observed as a colder atmosphere and more snowy winters. Also the glaciers were increasing.

On the other hand oceans continued accumulating heat.  It is a very long cycle. We are observing the Reversed Milankovitch Cycle culmination period. It will last about a millennia and a half and then there will be a cooling trend.

Right now Planet Earth is in an orbital forced warming trend. And these are culmination times.  The very slow warming trend will continue for about a 1,5 millennia on. Then slowly and gradually the Global Temperatures will become cooler.

US Heat and Drought Advisory June

Climatists are raising alarms about the rising temperatures and water shortages as evidence of impending doom (it’s summer and that time of year again).  So some contextual information is suitable.

First, a comparison of recent US June forecasts for temperatures.

NOAA US temp 2019 2021

And then for the same years, precipitation forecasts.

NOAA US rain 2019 2021

Finally, a reminder of how unrelated CO2 is to all of this.

us-wet-dry-co2rev-1

giss-gmt-to-2018-w-co2

Solar Cycles Chaotic

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A recent study published at Science Daily The sun’s clock by Helmholtz-Zentrum Dresden-Rossendor Excerpts in italics with my bolds

Not only the 11-year cycle, but also all other periodic solar activity fluctuations can be clocked by planetary attractive forces. With new model calculations, they are proposing a comprehensive explanation of known sun cycles for the first time. They also reveal the longest fluctuations in activity over thousands of years as a chaotic process.

Not only the very concise 11-year cycle, but also all other periodic solar activity fluctuations can be clocked by planetary attractive forces. This is the conclusion drawn by Dr. Frank Stefani and his colleagues from the Institute of Fluid Dynamics at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and from the Institute of Continuous Media Mechanics in Perm, Russia. With new model calculations, they are proposing a comprehensive explanation of all important known sun cycles for the first time. They also reveal the longest fluctuations in activity over thousands of years as a chaotic process. Despite the planetary timing of short and medium cycles, long-term forecasts of solar activity thus become impossible, as the researchers in the scientific journal Solar Physics assert.

Solar physicists around the world have long been searching for satisfactory explanations for the sun’s many cyclical, overlapping activity fluctuations. In addition to the most famous, approximately 11-year “Schwabe cycle,” the sun also exhibits longer fluctuations, ranging from hundreds to thousands of years. It follows, for example, the “Gleissberg cycle” (about 85 years), the “Suess-de Vries cycle” (about 200 years) and the quasi-cycle of “Bond events” (about 1500 years), each named after their discoverers. It is undisputed that the solar magnetic field controls these activity fluctuations.

Explanations and models in expert circles partly diverge widely as to why the magnetic field changes at all. Is the sun controlled externally or does the reason for the many cycles lie in special peculiarities of the solar dynamo itself? HZDR researcher Frank Stefani and his colleagues have been searching for answers for years — mainly to the very controversial question as to whether the planets play a role in solar activity.

Rosette-shaped movement of the sun can produce a 193-year cycle

The researchers have most recently taken a closer look at the sun’s orbital movement. The sun does not remain fixed at the center of the solar system: It performs a kind of dance in the common gravitational field with the massive planets Jupiter and Saturn — at a rate of 19.86 years. We know from the Earth that spinning around in its orbit triggers small motions in the Earth’s liquid core. Something similar also occurs within the sun, but this has so far been neglected with regard to its magnetic field.

The researchers came up with the idea that part of the sun’s angular orbital momentum could be transferred to its rotation and thus affect the internal dynamo process that produces the solar magnetic field. Such coupling would be sufficient to change the extremely sensitive magnetic storage capacity of the tachocline, a transition region between different types of energy transport in the sun’s interior. “The coiled magnetic fields could then more easily snap to the sun’s surface,” says Stefani.

The researchers integrated one such rhythmic perturbation of the tachocline into their previous model calculations of a typical solar dynamo, and they were thus able to reproduce several cyclical phenomena that were known from observations. What was most remarkable was that, in addition to the 11.07-year Schwabe cycle they had already modeled in previous work, the strength of the magnetic field now also changed at a rate of 193 years — this could be the sun’s Suess-de Vries cycle, which from observations has been reported to be 180 to 230 years. Mathematically, the 193 years arise as what is known as a beat period between the 19.86-year cycle and the twofold Schwabe cycle, also called the Hale cycle. The Suess-de Vries cycle would thus be the result of a combination of two external “clocks”: the planets’ tidal forces and the sun’s own movement in the solar system’s gravitational field.

Planets as a metronome

For the 11.07-year cycle, Stefani and his researchers had previously found strong statistical evidence that it must follow an external clock. They linked this “clock” to the tidal forces of the planets Venus, Earth and Jupiter. Their effect is greatest when the planets are aligned: a constellation that occurs every 11.07 years. As for the 193-year cycle, a sensitive physical effect was also decisive here in order to trigger a sufficient effect of the weak tidal forces of the planets on the solar dynamo.

After initial skepticism toward the planetary hypothesis, Stefani now assumes that these connections are not coincidental. “If the sun was playing a trick on us here, then it would be with incredible perfection. Or, in fact, we have a first inkling of a complete picture of the short and long solar activity cycles.” In fact, the current results also retroactively reaffirm that the 11-year cycle must be a timed process. Otherwise, the occurrence of a beat period would be mathematically impossible.

Tipping into chaos: 1000-2000-year collapses are not more accurately predictable

In addition to the rather shorter activity cycles, the sun also exhibits long-term trends in the thousand-year range. These are characterized by prolonged drops in activity, known as “minima,” such as the most recent “Maunder Minimum,” which occurred between 1645 and 1715 during the “Little Ice Age.” By statistically analyzing the observed minima, the researchers could show that these are not cyclical processes, but that their occurrence at intervals of approximately one to two thousand years follows a mathematical random process.

solar-cycle-25-nasa-full

To verify this in a model, the researchers expanded their solar dynamo simulations to a longer period of 30,000 years. In fact, in addition to the shorter cycles, there were irregular, sudden drops in magnetic activity every 1000 to 2000 years. “We see in our simulations how a north-south asymmetry forms, which eventually becomes too strong and goes out of sync until everything collapses. The system tips into chaos and then takes a while to get back into sync again,” says Stefani. But this result also means that very long-term solar activity forecasts — for example, to determine influence on climate developments — are almost impossible.

Background from previous post Climate Chaos

Foucault’s pendulum in the Panthéon, Paris

h/t tom0mason for inspiring this post, including his comment below

The Pendulum is Settled Science

I attended North Phoenix High School (Go Mustangs!) where students took their required physics class from a wild and crazy guy. Decades later alumni who don’t remember his name still reminisce about “the crazy science teacher with the bowling ball.”

To demonstrate the law of conservation of energy, he required each and every student to stand on a ladder in one corner of the classroom. Attached to a hook in the center of the rather high ceiling was a rope with a bowling ball on the other end. The student held the ball to his/her nose and then released it, being careful to hold still afterwards.

The 16 pound ball traveled majestically diagonally across the room and equally impressively returned along the same path. The proof of concept was established when the ball stopped before hitting your nose (though not by much).  In those days we learned to trust science and didn’t need to go out marching to signal some abstract virtue.

The equations for pendulums are centuries old and can predict the position of the ball at any point in time based on the mass of the object, length of the rope and starting position.

Pictured above is the currently operating Foucault pendulum that exactly follows these equations. While it had long been known that the Earth rotates, the introduction of the Foucault pendulum in 1851 was the first simple proof of the rotation in an easy-to-see experiment. Today, Foucault pendulums are popular displays in science museums and universities.

What About the Double Pendulum?

Trajectories of a double pendulum

Just today a comment by tom0mason at alerted me to the science demonstrated by the double compound pendulum, that is, a second pendulum attached to the ball of the first one. It consists entirely of two simple objects functioning as pendulums, only now each is influenced by the behavior of the other.

Lo and behold, you observe that a double pendulum in motion produces chaotic behavior. In a remarkable achievement, complex equations have been developed that can and do predict the positions of the two balls over time, so in fact the movements are not truly chaotic, but with considerable effort can be determined. The equations and descriptions are at Wikipedia Double Pendulum

Long exposure of double pendulum exhibiting chaotic motion (tracked with an LED)

But here is the kicker, as described in tomomason’s comment:

If you arrive to observe the double pendulum at an arbitrary time after the motion has started from an unknown condition (unknown height, initial force, etc) you will be very taxed mathematically to predict where in space the pendulum will move to next, on a second to second basis. Indeed it would take considerable time and many iterative calculations (preferably on a super-computer) to be able to perform this feat. And all this on a very basic system of known elementary mechanics.

And What about the Climate?

This is a simple example of chaotic motion and its unpredictability. How predictable is our climate with so many variables and feedbacks, some known some unknown? Consider that this planet’s weather/climate system is chaotic in nature with many thousands (millions?) of loosely coupled variables and dependencies, and many of these variables have very complex feedback features within them.

Hurricane Gladys, photographed from orbit by Apollo 7 in 1968 (Photo: NASA)

Summary

To quote the IPCC:

The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible. Rather the focus must be upon the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions.

A recent National Review article draws the implications:
The range of predicted future warming is enormous — apocalyptism is unwarranted.

But as the IPCC emphasizes, the range for future projections remains enormous. The central question is “climate sensitivity” — the amount of warming that accompanies a doubling of carbon dioxide in the atmosphere. As of its Fifth Assessment Report in 2013, the IPCC could estimate only that this sensitivity is somewhere between 1.5 and 4.5°C. Nor is science narrowing that range. The 2013 assessment actually widened it on the low end, from a 2.0–4.5°C range in the prior assessment. And remember, for any specific level of warming, forecasts vary widely on the subsequent environmental and economic implications.

For now, though, navigating the climate debate will require translating the phrase “climate denier” to mean “anyone unsympathetic to the most aggressive activists’ claims.” This apparently includes anyone who acknowledges meaningful uncertainty in climate models, adopts a less-than-catastrophic outlook about the consequences of future warming, or opposes any facet of the activist policy agenda. The activists will be identifiable as the small group continuing to shout “Denier!” The “deniers” will be identifiable as everyone else.

Update May 2

Esteemed climate scientist Richard Lindzen ends a very fine recent presentation (here) with this description of the climate system:

I haven’t spent much time on the details of the science, but there is one thing that should spark skepticism in any intelligent reader. The system we are looking at consists in two turbulent fluids interacting with each other. They are on a rotating planet that is differentially heated by the sun. A vital constituent of the atmospheric component is water in the liquid, solid and vapor phases, and the changes in phase have vast energetic ramifications. The energy budget of this system involves the absorption and reemission of about 200 watts per square meter. Doubling CO2 involves a 2% perturbation to this budget. So do minor changes in clouds and other features, and such changes are common. In this complex multifactor system, what is the likelihood of the climate (which, itself, consists in many variables and not just globally averaged temperature anomaly) is controlled by this 2% perturbation in a single variable? Believing this is pretty close to believing in magic. Instead, you are told that it is believing in ‘science.’ Such a claim should be a tip-off that something is amiss. After all, science is a mode of inquiry rather than a belief structure.

Flow Diagram for Climate Modeling, Showing Feedback Loops

Why Climate Models Fail to Replicate the North Atlantic

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A recent paper employed expert statistical analysis to prove that currently climate models fail to reproduce fluctuations of sea surface temperatures in the North Atlantic, a key region affecting global weather and climate.  H/T to David Whitehouse at GWPF for posting a revew of the paper.  I agree with him that the analysis looks solid and the findings robust.  However, as I will show below, neither Whitehouse nor the paper explicitly drew the most important implication.

At GWPF, Whitehouse writes Climate models fail in key test region (in italics with my bolds):

A new paper by Timothy DelSole of George Mason University and Michael Tippett of Columbia University looks into this by attempting to quantify the consistency between climate models and observations using a novel statistical approach. It involves using a multivariate statistical framework whose usefulness has been demonstrated in other fields such as economics and statistics. Technically, they are asking if two time series such as observations and climate model output come from the same statistical source.

To do this they looked at the surface temperature of the North Atlantic which is variable over decadal timescales. The reason for this variability is disputed, it could be related to human-induced climate change or natural variability. If it is internal variability but falsely accredited to human influences then it could lead over estimates of climate sensitivity. There is also the view that the variability is due to anthropogenic aerosols with internal variability playing a weak role but it has been found that models that use external forcing produce inconsistencies in such things as the pattern of temperature and ocean salinity. These things considered it’s important to investigate if climate models are doing well in accounting for variability in the region as the North Atlantic is often used as a test of a climate model’s capability.

The researchers found that when compared to observations, almost every CMIP5 model fails, no matter whether the multidecadal variability is assumed to be forced or internal. They also found institutional bias in that output from the same model, or from models from the same institution, tended to be clustered together, and in many cases differ significantly from other clusters produced by other institutions. Overall only a few climate models out of three dozen considered were found to be consistent with the observations.

The paper is Comparing Climate Time Series. Part II: A Multivariate Test by DelSole and Tippett.  Excerpts in italics with my bolds.

We now apply our test to compare North Atlantic sea surface temperature (NASST) variability between models and observations. In particular, we focus on comparing multi-year internal variability. The question arises as to how to extract internal variability from observations. There is considerable debate about the magnitude of forced variability in this region, particularly the contribution due to anthropogenic aerosols (Booth et al., 2012; Zhang et al., 2013). Accordingly, we consider two possibilities: that the forced response is well represented by (1) a second-order polynomial or (2) a ninth-order polynomial over 1854-2018. These two assumptions will be justified shortly.

If NASST were represented on a typical 1◦ × 1◦ grid, then the number of grid cells would far exceed the available sample size. Accordingly, some form of dimension reduction is necessary. Given our focus on multi-year predictability, we consider only large-scale patterns. Accordingly, we project annual-mean NASST onto the leading eigenvectors of the Laplacian over the Atlantic between 0 0 60◦N. These eigenvectors form an orthogonal set of patterns that can be ordered by a measure of length  scale from largest to smallest.

DelSole Tippett fig1

Figure 1. Laplacian eigenvectors 1,2,3,4,5,6 over the North Atlantic between the equator and 60◦N,  where dark red and dark blue indicate extreme positive and negative values, respectively

The first six Laplacian eigenvectors are shown in fig. 1 (these were computed by the method of DelSole and Tippett, 2015). The first eigenvector is spatially uniform. Projecting data onto the first Laplacian eigenvector is equivalent to taking the area-weighted average in the basin. In the case of SST, the time series for the first Laplacian eigenvector is merely an AMV index (AMV stands for “Atlantic Multidecadal Variability”). The second and third eigenvectors are dipoles that measure the large-scale gradient across the basin. Subsequent eigenvectors capture smaller scale patterns.  For model data, we use pre-industrial control simulations of SST from phase 5 of the Coupled Model Intercomparison Project (CMIP5 Taylor et al., 2012). Control simulations use forcings that repeat year after year. As a result, interannual variability in control simulations come from internal dynamical mechanisms, not from external forcing.

DelSole Tippett fig2Figure 2. AMV index from ERSSTv5 (thin grey), and polynomial fits to a second-order (thick black) and ninth-order (red) polynomial.

For observational data, we use version 5 of the Extended Reconstructed SST dataset (ERSSTv5 Huang et al., 2017). We consider only the 165-year period 1854-2018. We first focus on time series for the first Laplacian eigenvector, which we call the AMV index. The corresponding least squares fit to second- and ninth-order polynomials in time are shown in fig. 2. The second-order polynomial captures the secular trend toward warmer temperatures but otherwise has weak multidecadal variability. In contrast, the ninth-order polynomial captures both the secular trend and multidecadal variability. There is no consensus as to whether this multidecadal variability is internal or forced. 

DelSole Tippett fig4

Figure 4. Deviance between ERSSTv5 1854-1935 and 82-year segments from 36 CMIP5 pre-industrial control simulations. Also shown is the deviance between ERSSTv5 1854-1935 and ERSSTv5 1937-2018 (first item on x-axis). The black and red curves show, respectively, results after removing a second- and ninth-order polynomial in time over 1854-2018 before evaluating the deviance. The models have been ordered on the x-axis from smallest to largest deviance after removing a second-order polynomial in time.

Conclusion:

The test was illustrated by using it to compare annual mean North Atlantic SST variability in models and observations. When compared to observations, almost every CMIP5 model differs significantly from ERSST. This conclusion holds regardless of whether a second- or ninth-order polynomial in time is regressed out. Thus, our conclusion does not depend on whether multidecadal NASST variability is assumed to be forced or internal. By applying a hierarchical clustering technique, we showed that time series from the same model, or from models from the same institution, tend to be clustered together, and in many cases differ significantly from other clusters. Our results are consistent with previous claims (Pennell and Reichler, 2011; Knutti et al., 2013) that the effective number of independent models is smaller than the actual number of models in a multi-model ensemble.

The Elephant in the Room

Now let’s consider the interpretation reached by model builders after failing to match observations of Atlantic Multidecadal Variability.  As an example consider INMCM4, whose results deviated greatly from the ERSST5 dataset.  In 2018, Evgeny Volodin and Andrey Gritsun published Simulation of observed climate changes in 1850–2014 with climate model INM-CM5.   Included in those simulations is a report of their attempts to replicate North Atlantic SSTs.  Excerpts in italics with my bolds.

esd-9-1235-2018-f04

Figure 4 The 5-year mean AMO index (K) for ERSSTv4 data (thick solid black); model mean (thick solid red). Dashed thin lines represent data from individual model runs. Colors correspond to individual runs as in Fig. 1.

Keeping in mind the argument that the GMST slowdown in the beginning of the 21st century could be due to the internal variability of the climate system, let us look at the behavior of the AMO and PDO climate indices. Here we calculated the AMO index in the usual way, as the SST anomaly in the Atlantic at latitudinal band 0–60∘ N minus the anomaly of the GMST. The model and observed 5-year mean AMO index time series are presented in Fig. 4. The well-known oscillation with a period of 60–70 years can be clearly seen in the observations. Among the model runs, only one (dashed purple line) shows oscillation with a period of about 70 years, but without significant maximum near year 2000. In other model runs there is no distinct oscillation with a period of 60–70 years but a period of 20–40 years prevails. As a result none of the seven model trajectories reproduces the behavior of the observed AMO index after year 1950 (including its warm phase at the turn of the 20th and 21st centuries).

One can conclude that anthropogenic forcing is unable to produce any significant impact on the AMO dynamics as its index averaged over seven realization stays around zero within one sigma interval (0.08). Consequently, the AMO dynamics are controlled by the internal variability of the climate system and cannot be predicted in historic experiments. On the other hand, the model can correctly predict GMST changes in 1980–2014 having the wrong phase of the AMO (blue, yellow, orange lines in Figs. 1 and 4).

esd-9-1235-2018-f01

Figure 1 The 5-year mean GMST (K) anomaly with respect to 1850–1899 for HadCRUTv4 (thick solid black); model mean (thick solid red). Dashed thin lines represent data from individual model runs: 1 – purple, 2 – dark blue, 3 – blue, 4 – green, 5 – yellow, 6 – orange, 7 – magenta. In this and the next figures numbers on the time axis indicate the first year of the 5-year mean.

The Bottom Line

Since the models incorporate AGW in the form of CO2 sensitivity, they are unable to replicate Atlantic Multidecadal Variability.  Thus, the logical conclusion is that variability of North Atlantic SSTs is an internal, natural climate factor.

The-Elephant-in-the-RoomOMC

The Greatest Untold Environmental Success Story

2-beams-of-sunlight-rays-shining-through-dramatic-clouds-onto-the-gill-copeland

H/T to Daily Mail for reporting on this study in their article–Warming effect of greenhouse gases ‘has been overestimated’: Ice samples suggest pre-industrial air pollution was WORSE than we thought, and future temperatures will rise more slowly. Excerpts further on, but first I want to comment that Daily Mail missed out on a broader environmental story, where humans are the heroes rather than villains.

My title is based on the researchers’ conclusions confirming that humans deserve more credit than the blame usually dished out for the Modern Warm Period and ending of the Little Ice Age. The money quote from the study itself:

We show that BC (Black Carbon) deposition fluxes in most Antarctic ice cores were roughly constant from 1750 CE to the PD, despite the fact that other anthropogenic emissions—i.e., fossil fuel and biofuel emissions—increased markedly in the SH over the past century (21). This unexpected result can be explained by a large human-induced reduction in wildfire over the same period, as suggested by the fire modeling that we developed independently of the ice core records. The reduced biomass burning emissions largely compensated for the increase in BC emissions from fossil fuel and biofuels.

Thus, by focusing on soot (Black Carbon), researchers were able to compare historical periods when natural, uncontrolled biomass burning dominated, with periods when humans brought biomass burning under control and increasingly sourced their energy instead from underground: first coal, then petroleum and later gas. By cleaning the air of soot, humans removed a major climate coolant which allowed the sun to rewarm the planet. And technological improvements made the burning of coal, oil and gas much cleaner than biomass burning.

Daily Mail Article:

‘Soot deposited in glacier ice directly reflects past atmospheric concentrations so well-dated ice cores provide the most reliable long-term records,’ explained hydrologist Joseph McConnell of the Desert Research Institute in Nevada.

The researchers were surprised to find that the pre-industrial (here defined as 1750–1780) soot levels were considerably higher than was long thought.

‘While most studies have assumed less fire took place in the preindustrial era, the ice cores suggested a much fierier past, at least in the Southern Hemisphere,’ said atmospheric chemist Loretta Mickley, also of Harvard University.

Both the ice core data and the models conclude that soot levels were abundant before the industrial era and remained relatively constant across the 20th century.

As land use changed — and fire activity decreased — emissions from industry increased instead, the models suggest.

The study itself is  Liu et al,  Improved estimates of preindustrial biomass burning reduce the magnitude of aerosol climate forcing in the Southern Hemisphere.  Excerpts in italics wth my bolds.

Abstract

Fire plays a pivotal role in shaping terrestrial ecosystems and the chemical composition of the atmosphere and thus influences Earth’s climate. The trend and magnitude of fire activity over the past few centuries are controversial, which hinders understanding of preindustrial to present-day aerosol radiative forcing.

Here, we present evidence from records of 14 Antarctic ice cores and 1 central Andean ice core, suggesting that historical fire activity in the Southern Hemisphere (SH) exceeded present-day levels. To understand this observation, we use a global fire model to show that overall SH fire emissions could have declined by 30% over the 20th century, possibly because of the rapid expansion of land use for agriculture and animal production in middle to high latitudes.

Radiative forcing calculations suggest that the decreasing trend in SH fire emissions over the past century largely compensates for the cooling effect of increasing aerosols from fossil fuel and biofuel sources.

Introduction

Both climate variability and human activity drive changes in wildfire frequency and magnitude. During the past millennium, the human imprint on wildfire has become increasingly important because of landscape fragmentation through land use and, more recently, through large-scale active fire suppression

For the time scale relevant to climate change in the industrial era, a key uncertainty is where and to what extent human activity has altered fire activity

 As a major source of fire ignition, humans use fire for land clearance, thus introducing fire to areas that are unlikely to burn naturally, such as tropical rainforests or peatlands.  In contrast, recent analyses have suggested that anthropogenic land cover change and landscape fragmentation significantly reduce fire in savannas by affecting fuel load and fire spread, and the fire activity over human-managed land is lower than that under natural conditions.  For example, the global burned area observed by satellite decreased 24% over the past two decades, mainly driven by agricultural expansion and intensification

Before the satellite era, regional and global fire trends have been reconstructed using several types of proxy records, such as charcoal from lake sediments, fire-scarred tree rings, and chemical impurities or trace gases preserved in ice cores. However, large discrepancies remain among different records, and there is an especially large uncertainty in the trend of fire emissions over the past two centuries. On the global scale, the use of fossil fuel and biofuels has increased and become the major source of carbonaceous aerosols, methane, ethane, and carbon monoxide (CO) in the present day (PD), which may confound interpretation of fire activity from these proxies in ice cores. Chemical transport models considering these different sources are therefore needed for the interpretation of ice core records.

Dynamic global vegetation models have been used to simulate historical fire emissions. However, different models demonstrate quite different trends of fire activity from the late preindustrial (PI) Holocene to the PD, mainly because of divergent assumptions regarding the response of fire to human demographic growth and to changes in land use and land cover.

Discussion

Large uncertainty in the PI aerosol loading thus results from uncertainty in PI fire emissions. Knowledge of PI aerosol loading is, however, a key for global climate assessments that consider aerosol forcing. This forcing typically quantifies the PD aerosol effect on radiative fluxes at the top of the atmosphere (TOA), relative to the aerosol effect in the PI (1750 or 1850 CE). Biomass burning emits both light-absorbing black carbon (BC) and light-scattering organic carbon (OC) aerosols, thus directly influencing the radiative balance via aerosol-radiation interactions. Physically and chemically aged smoke particles also serve as cloud condensation nuclei (CCN), consequently altering cloud albedo and indirectly affecting the radiative balance via aerosol-cloud interactions. In addition, the cloud albedo forcing of other emissions, such as fossil fuel and biofuel emissions, is highly nonlinear and largely depends on the CCN concentration of the PI baseline, which is, in turn, determined by biomass burning in the PI. A recent work by Hamilton et al. suggests that a revised PI biomass burning emission scenario that is consistent with Northern Hemisphere ice core records can reduce the calculated mean global cloud albedo forcing magnitude by 35%, compared to the estimate using emissions prescribed in the Sixth Coupled Model Intercomparison (CMIP6).

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Figure 5A shows the time series of the cloud albedo forcing since 1750 owing to changes in both anthropogenic and biomass burning emissions. The shaded area represents the estimated uncertainty considering the error propagation from the variabilities in the input of emissions and meteorology. Simulation with the LPJ-LMfire emissions yields a less negative cloud albedo forcing than that with the BB4CMIP emissions. For the year 2000, the simulation with LPJ-LMfire predicts a mean cloud albedo forcing of −0.33 W m−2 for the SH, compared with a value of −0.52 W m−2 using the BB4CMIP emissions. These results indicate that cloud albedo forcing in the SH is very sensitive to the change in biomass burning emissions. The difference between BB4CMIP and LPJ-LMfire biomass burning emissions can also influence estimates of the PI CCN number concentration in the SH (fig. S7), thus changing the baseline of climate assessments. Under the relatively clean conditions of the PI SH, changes in the CCN number concentration have a greater impact on cloud albedo forcing than they would under the more polluted conditions of the Northern Hemisphere (fig. S8).

Figure 5B depicts the values of direct radiative forcing due to aerosol-radiation interactions calculated for total aerosol (i.e., including biomass burning, fossil fuel, and biofuel emissions) using different biomass burning emission inventories. To separate the contributions of fossil fuel and biofuel versus biomass burning aerosols, we also show the direct radiative forcing of anthropogenic emissions only (Fig. 5B). The increase of anthropogenic emissions alone from 1750 to 2000 has a direct radiative forcing of −0.05 W m−2. Over the same period, the increase in biomass burning emissions suggested by BB4CMIP has an additional negative forcing of −0.03 W m−2, and the total aerosol direct forcing is −0.08 W m−2. In contrast, the total aerosol direct radiative forcing calculated when using LPJ-LMfire emissions is just −0.02 W m−2, indicating that the positive forcing of decreasing biomass burning largely compensates the negative forcing of the increasing anthropogenic emissions. These results suggest that the difference in biomass burning emissions can dominate the magnitude of aerosol direct radiative forcing in the SH. Even so, the values of direct radiative forcing are generally one order of magnitude smaller than those of cloud albedo forcing, suggesting that the climate impact of biomass burning emissions is primarily caused by the cloud albedo effect.

In this study, we perform a comprehensive analysis of fire activity and its associated aerosol radiative forcing for the Southern Hemisphere (SH) over the past 250 years. We achieve this by combining an array of Antarctic ice core records of BC deposition, dynamic global vegetation and fire modeling, and atmospheric chemistry transport modeling. We show that BC deposition fluxes in most Antarctic ice cores were roughly constant from 1750 CE to the PD, despite the fact that other anthropogenic emissions—i.e., fossil fuel and biofuel emissions—increased markedly in the SH over the past century (21). This unexpected result can be explained by a large human-induced reduction in wildfire over the same period, as suggested by the fire modeling that we developed independently of the ice core records. The reduced biomass burning emissions largely compensated for the increase in BC emissions from fossil fuel and biofuels.

These records indicate that the CMIP6 biomass burning emissions widely applied to climate models may underestimate SH fire emissions in the late PI era and further affect estimates of contemporary aerosol radiative forcing. With the improved biomass burning emissions presented here, PI-to-PD aerosol forcing (direct radiative forcing + cloud albedo forcing) in the SH changes from −0.61 to −0.35 W m−2, indicating that large uncertainties in aerosol radiative forcing may stem from uncertainties in the historical trend in biomass burning. Similarly, on the basis of ice core records from Greenland, Europe, and North America, Hamilton et al. (18) suggest that the reduction in biomass burning emissions may also occur in the Northern Hemisphere.

Accurate estimates of aerosol radiative forcing are also crucial for better understanding the transient climate response (TCR) and equilibrium climate sensitivity (ECS) to increasing CO2 and more accurate projection of future climate change (40). The negative aerosol radiative forcing can, in part, cancel out the positive forcing of increasing greenhouse gases and contribute to the uncertainty of total radiative forcing. An overly large aerosol cooling implies that models might overestimate TCR and ECS to reproduce historical temperature response. A recent study using one of the latest-generation CMIP6 climate models (E3SM) suggested that reducing both the magnitudes of negative aerosol radiative forcing and climate sensitivity yields a better agreement with the observed historical record of the surface temperature. Ten in 27 of the CMIP6 climate models have an ECS higher than the upper end of the range (1.5° to 4.5°C) estimated by previous generation models. These high ECS values, however, are not supported by paleoclimate constraints. Modest aerosol forcing and climate sensitivity values have also been suggested by other observationally based studies (44, 45). Our improved fire emissions may help to bridge the gap between aerosol forcing estimates from current climate model simulations and the constraints from observations.

 

 

Climate Change Thinking for Open or Locked-Down Minds

William Happer provides a framework for thinking about climate, based on his expertise regarding atmospheric radiation (the “greenhouse” mechanism).  But he uses plain language accessible to all.  The Independent Institute published the transcript for those like myself who prefer reading for full comprehension.  Source: How to Think about Climate Change  Some excerpted highlights in italics with my bolds,

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This presentation by Dr. William Happer was delivered at the Hillsdale College National Leadership Seminar in Phoenix, Arizona, that was held on February 19, 2021. The Cyrus Fogg Brackett Professor Emeritus of Physics at Princeton University, Dr. Happer is the author of the foreword to the Revised and Expanded Third Edition of the Independent Institute book, Hot Talk, Cold Science: Global Warming’s Unfinished Debate, by S. Fred Singer, David R. Legates and Anthony R. Lupo.

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The Climate Crusade for a False Alarm

The best way to think about the frenzy over climate is to consider it a modern version of the medieval Crusades. You may remember that the motto of the crusaders was “Deus vult!”, “God wills it!” It is hard to pick a better virtue-signaling slogan than that. Most climate enthusiasts have not gone so far, but some actually claim that they are doing God’s work. After decades of propaganda, many Americans, perhaps including some of you here today, think there really is a climate emergency. Those who think that way, in many cases, mean very well. But they have been misled. As a scientist who actually knows a lot about climate (and I set up many of our climate research centers when I was at the Department of Energy in the early 1990s) I can assure you that there is no climate emergency. There will not be a climate emergency. Crusades have always ended badly. They have brought discredit to the supposed righteous cause. They have brought hardship and death to multitudes. Policies to address this phony climate emergency will cause great damage to American citizens and to their environment.

Part of the medieval crusades was against the supposed threat to the holy sites in Jerusalem. But a lot of it was against local enemies. The medieval Inquisition really did a job on the poor Cathars, on the Waldensians of southern France, and on the Bogomils in the Balkans. Climate fanatics don’t know or care any more about the science of climate than those medieval Inquisitors knew or cared about the teachings of Christ.

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Don’t Confuse CO2 with Air Pollution

Just about everyone wants to live in a clean environment. I do, and I am sure everyone here does. This is a photograph of Shanghai, and that’s real air pollution. You can just barely see the Bottle Opener Building in the back through all the haze. Some of this is due to burning coal. But a bigger fraction is due to dust from the Gobi Desert. They have had this type of pollution in Shanghai since the days of Marco Polo and long before. Part of it is burning stubble of the rice fields, which is traditionally done before planting next year’s crop. This is real pollution. I would not want to live in a city like that. If there is anything to do that would make it better, I would certainly support that.

But, none of this has anything to do with CO2. CO2 is a gas you cannot see, smell or taste. So, hare-brained schemes to limit emissions of CO2, which is actually beneficial, as I will explain a little bit later, will only make it harder to get rid of real pollutants like what I just showed you in Shanghai.

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Like all wind farms it is now falling to pieces we can’t dispose of.

Renewable energy is what I would call the inverse Robin Hood strategy—you rob from the poor to give to the rich. Utilities are permitted to raise rates because of their capital investments in inefficient, unreliable renewables. They junk fully depreciated coal, gas and nuclear plants, all of which are working beautifully, and producing inexpensive, reliable energy. But regulated profits are much less. Taxpayers subsidize the rich, who can afford to lease land for wind and solar farms. Tax incentives pander to the upper class who live in gated communities and can afford to buy Tesla electric cars. They get subsidies from the state and federal government. They even get subsidized electrical power to charge up their toys. The common people have little spare income for virtue signaling. They pay more and more for the necessities of life in order to subsidize their betters.

Climate Facts to Replace Hysteria

You cannot spend a lifetime as a professor and not relapse from time to time into giving a classroom lecture. So, you will have to expect to be lectured for a few minutes. The good news is that there will be no quiz. But for those of you who share my view that this climate hysteria is serious nonsense, it helps to know what the facts are. I hope I can arm some of you with the real scientific facts.

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Climate involves a complicated interplay of the sunlight that warms us, and thermal infra-radiation that escapes to space. Heat is transported from the tropics to the poles by the motion of warm air and ocean water. We all know about the Gulf Stream that carries huge amounts of heat to northern Europe, even to Russia. Movements of air in the atmosphere also carry a lot of heat, as we know from regular cold spells and hot spells.

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Here is a picture of Earth’s energy budget. I mentioned we are warmed by the Sun. About half of the sunlight eventually gets to the surface. What prevents it all from reaching the surface are clouds and a small amount of scattering and absorption by the atmosphere. Other parts of America, like New Jersey, now are covered with clouds. Those areas do not get any sunlight directly. But the half of sunlight that does reach the ground heats it. You can notice that in the afternoon, if you go outside. If you are a gardener like me, you can put your hands in the soil and it is nice and warm. It makes the corn grow. But that heat has to be released. If you keep adding heat to the ground, it gets hotter and hotter. So, the heat is eventually released by radiation into space which is that red arrow going up on the viewgraph. But for the first few kilometers of altitude, a good fraction of that heat is not carried by radiation, but by convection of warm, moist air. CO2 has no direct effect on convection near the surface. But once you get up to 10 kilometers or so, most of the heat is transported by radiation.

By the way, I have the meter running now. Remember that the outside air is 400 parts per million CO2. I am not sure you can see the meter but I will read it for you. It is 580 in here. It is not a whole lot higher than the 400 outside. It was at 1,000 parts per million where we were having lunch. CO2 levels are never stable near Earth’s surface. People are panicking about one or two parts per million of CO2. Now, the meter reads 608 parts per million—that is probably because I breathed on it. Hot air sets it off. I sometimes take the meter out onto my back porch. At the end of a summer day the CO2 levels on my back porch drop to maybe 300 parts per million, way below the average for outside air. That is because the trees and grass in my backyard have sucked most of the CO2 out of the local air during the day. If I get up early the next morning and I look at the meter, it is up to 600 parts per million. So just from morning to night CO2 doubles in the air of my back yard. Doubles and halves, doubles and halves. At least during the growing season that is quite common. And we have these hysterics about CO2 increasing by 30 or 40 percent. It is amazing.

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So, why the frenzy over CO2? It is because it is a greenhouse gas. That is true. This is a somewhat deceptive picture. What it shows in red is sunlight, and the horizontal scale on the top panel is the wavelength of the sunlight. Radiation wavelengths for sunlight are typically about a half a micron (half a millionth of a meter). That is green light, the color of green leaves. The thermal radiation that cools the Earth is that blue curve to the right of the upper panel, and that is a much longer wavelength, typically around 10 microns. So, the wavelength of thermal radiation is 10 to 20 times longer than the wavelengths of sunlight. It turns out that the sun’s energy can get through the Earth’s atmosphere very easily. So essentially all sunlight or at least 90 percent, if there are no clouds, gets to the surface and warms it. But radiation cooling of the surface is less efficient because various greenhouse gases (most importantly water vapor, which is shown as the third panel down, and CO2, which is the fourth panel down) intercept a lot of that radiation and keep it from freely escaping to space. This keeps Earth’s surface temperature warmer than it would be (by about 20 or 30 degrees). The Earth would be an ice cube if it were not for water vapor and CO2; and when I say water vapor, you should understand that I really mean water vapor and clouds, the condensed form of water. Clouds are at least as important as greenhouse gases and they are very poorly understood to this day.

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This is an important slide. There is a lot of history here and so there are two historical pictures. The top picture is Max Planck, the great German physicist who discovered quantum mechanics. Amazingly, quantum mechanics got its start from greenhouse gas-physics and thermal radiation, just what we are talking about today. Most climate fanatics do not understand the basic physics. But Planck understood it very well and he was the first to show why the spectrum of radiation from warm bodies has the shape shown on this picture, to the left of Planck. Below is a smooth blue curve. The horizontal scale, left to right is the “spatial frequency” (wave peaks per cm) of thermal radiation. The vertical scale is the thermal power that is going out to space. If there were no greenhouse gases, the radiation going to space would be the area under the blue Planck curve. This would be the thermal radiation that balances the heating of Earth by sunlight.

In fact, you never observe the Planck curve if you look down from a satellite. We have lots of satellite measurements now. What you see is something that looks a lot like the black curve, with lots of jags and wiggles in it. That curve was first calculated by Karl Schwarzschild, whose picture is below Planck’s picture. Schwarzschild was an officer in the German army in World War I, and he did some of his most creative work in the trenches on the eastern front facing Russia. He found one of the first analytic solutions to Einstein’s general theory of relativity while he was there on the front lines. Alas, he died before he got home. The cause of death was not Russian bullets but an autoimmune disease. This was a real tragedy for science. Schwarzschild was the theorist who first figured out how the real Earth, including the greenhouse gases in its atmosphere, radiates to space. That is described by the jagged black line. The important point here is the red line. This is what Earth would radiate to space if you were to double the CO2 concentration from today’s value. Right in the middle of these curves, you can see a gap in spectrum. The gap is caused by CO2 absorbing radiation that would otherwise cool the Earth. If you double the amount of CO2, you don’t double the size of that gap. You just go from the black curve to the red curve, and you can barely see the difference. The gap hardly changes.

The message I want you to understand, which practically no one really understands, is that doubling CO2 makes almost no difference.

Doubling would replace the black curve by the red curve. On the basis of this, we are supposed to give up our liberties. We are supposed to give up the gasoline engines of our automobiles. We are supposed to accept dictatorial power by Bernie Sanders and Ocasio-Cortez, because of the difference between the red and the black curve. Do not let anyone convince you that that is a good bargain. It is a terrible bargain. The doubling actually does make a little difference. It decreases the radiation to space by about three watts per square meters. In comparison, the total radiation to space is about 300 watts per square meter.

So, it is a one percent effect—it is actually a little less than that, because that is with no clouds. Clouds make everything even less threatening.

Finally, let me point out that there is a green curve. That is what happens if you take all the CO2 out of the atmosphere. No one knows how to do that, thanks goodness, because plants would all die if you took all the CO2 out of the atmosphere. But what this curve is telling you is that the greenhouse effect of CO2 is already saturated. Saturation is a jargon term that means CO2 has done all the greenhouse warming it can easily do. Doubling CO2 does not make much difference. You could triple or quadruple CO2 concentrations, and it also would make little difference. The CO2 effects are strongly saturated.

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You can take that tiny difference between those curves that I showed you, the red and the black curves, and calculate the warming that should happen. I was one of the first to do this: in 1982 I was a co-author of one of the first books on radiative effects of CO2. On the right panel is my calculation and lots of other people’s calculations since. It is a bar graph of the warming per decade that people have calculated. The red bar is what has actually been observed. On the right is warming per decade over 10 years, and on the left, over 20 years. In both cases the takeaway message is that predicted warmings, which so many people are frantic about, are all grossly larger than the observed warming, which is shown by the red bars. So, the observed warmings have been extremely small compared to computer calculations over any interval that you consider. Our policies are based on the models that you see here, models that do not work.

I believe we know why they do not work, but no one is willing to admit it.

Nobody knows how much of the warming observed over the past 50 years is due to CO2. There is good reason to that think much of it, perhaps most of it, would be there even without an increase in CO2 because we are coming out of the Little Ice Age. We have been coming out of that since the early 1800s, before which the weather was much colder than now. The green curve is measurements from satellites, very much like the measurements of a temporal scanning thermometer. You can look down from a satellite and measure the temperature of the atmosphere. The satellites and balloons agree with each other, and they do not agree with the computer models. This is very nice work by John Christie at the University of Alabama-Huntsville.

The alleged harm from CO2 is from warming, and the warming observed is much, much less than predictions. In fact, warming as small as we are observing is almost certainly beneficial. It gives slightly longer growing seasons. You can ripen crops a little bit further north than you could before. So, there is completely good news in terms of the temperature directly. But there is even better news. By standards of geological history, plants have been living in a CO2 famine during our current geological period.

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This is the greening of the Earth measured from satellites. This picture shows areas of the Earth that are getting greener over the 20-year period. What you notice is that everywhere, especially in arid areas of Sahel (you can see that just south of the Sahara) it is greening dramatically. The western United States is greening, western Australia is greening, western India is greening. This is almost certainly due to CO2, and the reason this happens is that CO2 allows plants to grow where 50 years ago it was too dry. Plants are now needing less water to grow than they did 50 or 100 years before.

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When you raise all these hard, scientific issues with the climate alarmists, the response is “how can you say that? 97 percent of scientists agree that there’s a terrible emergency here that we have to cope with.”

Here there are several things you should say. First of all, in science truth is not voted on. It is not like voting on a law. It is determined by how well your theory agrees with the observations and experiments. I just showed you that the theories of warming are grossly wrong. They are not even close and yet we are making our policy decisions based on computer models that do not work. It does not matter how many people say there is an emergency. If it does not agree with experiments and observations, the supposed scientific basis for the emergency is wrong. The claim of a climate emergency is definitely wrong.

Secondly, even when scientists agree, what they agree on can be wrong. People think of scientists as incorruptible, priestly people. They are not that at all. They have the same faults as everybody else, and they are frequently wrong.

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The clincher actually came when the USA finally declassified the World War II North Atlantic Magnetic Anomaly data which we had been sitting on for 10 years. The data showed mirror-image conveyor belts of newly-formed oceanic crust, starting at the mid-Atlantic ridge and going out left and right toward America, and toward Europe. So, there was absolutely no question that the seafloor was spreading. That is the one bit of evidence that Wegner did not have, but he had lots of other evidence that should have persuaded people.

This is just one example. I could tell you about many other scientific consensuses that made no sense. This one is interesting because it had no political background. It was pure science, but it does illustrate the fallibility of scientists, and the group-think that goes on in science. If you wanted to advance as a young geologist you could write a paper scorning Wegner in 1950 and get promoted right away, even though your paper was completely wrong. And, once you get tenure, you are there for good.

So, the takeaway message is that policies that slow CO2 emissions are based on flawed computer models which exaggerate warming by factors of two or three, probably more. That is message number one. So, why do we give up our freedoms, why do we give up our automobiles, why do we give up a beefsteak because of this model that does not work?

Takeaway message number two is that if you really look into it, more CO2 actually benefits the world. So, why are we demonizing this beneficial molecule that is making plants grow better, that is giving us slightly less harsh winters, a slightly longer growing season? Why is that a pollutant? It is not a pollutant at all, and we should have the courage to do nothing about CO2 emissions. Nothing needs to be done.

 

Worst Threat: Greenhouse Gas or Quiet Sun?

Elite Consensus Opinion

Minority Contrary Opinion

Expect 1+C Warmer from now to 2050 Expect 1C Colder from now to 2050
Mitigate Warming by Stopping Fossil Fuels Adapt to Cooling from Quiet Sun
Goal is Net Zero CO2 Emissions by 2050 Goal Robust Energy supply and Infrastructure Now

At the American Thinker, Anony mee writes The Coming Modern Grand Solar Minimum.  Excerpts in italics with my bolds.

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I wrote last week about the coming Grand Solar Minimum, something that will have much more impact on the environment than anything we puny humans can do. It generated a lot of interest from all sides, so it’s time to delve deeper into what we can expect.

Starting with the hype: During the last grand solar minimum (GSM), the Maunder Minimum of 1645 to 1715, glaciers advanced, rivers froze, sea ice expanded — in short, the Little Ice Age. Is another one is almost upon us?

Probably not. Maunder occurred at the tail end of a bi-millennial cycle. These cycles range between 2,000 and 2,600 years in length and see the Earth first warm, then cool. Gradual cooling had been going on for hundreds of years. Maunder just capped it off. Today we are a few hundred years into the warming phase of the subsequent bi-millennial cycle. Different starting conditions yield different paths.

The progressives say that we’re so deep into anthropogenically accelerated climate change (AACC) that there’s almost no time left to turn things around. If we don’t act now, it will be too late.

Nope, sorry squad members. What we can predict, instead, is an overall temperature reduction of 1 degree Centigrade by the end of the GSM. Afterward, natural warming at the rate of around 0.5 C. every hundred years will continue for the next 600 years or so.

That gives us a good 35 to 50 years to hone the science and come up with the best ways to mitigate the impact of unstoppable global warming on humankind; until, that is, it naturally reverses. See suggestions below for better uses of funding currently earmarked to address the “climate crisis.”

Reasonably speaking: We’ve been warming, so the cooling of the GSM will just even us out for a while. Therefore, nothing to worry about, right?

Well, not quite. There are a few worries. Plants grow in response to warmth, moisture, nutrients, and most importantly sunlight. Even if the temperature does not plunge to glacial depths, some cooling will take place and clouds are expected to grow denser and cover much of the earth’s surface as this GSM bottoms out. If normally-correlating volcanism takes place, the additional material in the atmosphere will further darken the globe and provide even more opportunity for condensation and cloud formation.

Last year, Dr. Valentina Zharkova wrote “This global cooling during the upcoming grand solar minimum…would require inter-government efforts to tackle problems with heat and food supplies for the whole population of the Earth” (not to mention their livestock).

The pessimists ask, what else can go wrong? Well, cooling will increase the demand for heat, darker days will increase the demand for light, and unfavorable outside conditions will increase the demand for power for enclosed food production. With more power needed, the amount we currently rely on from solar installations will decrease as cloud cover limits their efficacy.

A decrease in solar ultraviolet radiation can be expected to slow the formation of ozone in the atmosphere, a lack of which tends to destabilize the jet stream, causing wilder weather. Wind generators turn off when the wind is excessively strong. As we now know, they are not immune from freezing in place. In the face of a greater demand for power, we will generate less.

Even worse is this: Historically, GSMs have been associated with extreme weather events. Floods, droughts, heavy snowfall, late springs, and early autumns have all resulted in famine. Famine during GSMs has led to starvation and societal upheaval. No one wants the former, and I think we’ve seen enough of the latter this past year or so to do for our lifetimes.

We’re about 16 months into this GSM, with 32 more years to go. Already 2019 and 2020 saw record low numbers of sunspots. We’ve had lower than expected crop harvests due to unseasonable rains both years. The April 2021 USDA World Agricultural Product report has articles detailing Taiwan’s expected 20% decrease in rice production this year over last, Cuba’s rice production 15% below its five-year average, Argentina’s corn, Australia’s cotton, Malaysia’s palm oil — all down, all due primarily to the weather. There are some expected bumper crops, all based on expanded acreage.

We’ve got seven years until we hit the trough. There’s no time to lose. Fortunately, We the People are amazing. We’re strong, courageous, resilient, smart, well-educated, and clever. We are capable of coming together for a common cause and working well together regardless of politics and other differences. We must pull together to make sure we all survive the coming tumult. Here’s what we do.

On the federal level, take the brakes off energy production. No more talk of closing power plants, especially coal-fired ones, or of removing hydroelectric dams. Reinstate the Keystone XL pipeline; we’re going to need that fuel available to us when the predictable contraction of the global fuel market occurs. Extend the tax credits for those who install solar power. Production may not be optimal during the GSM, but as much as can occur will take a load off commercial energy.

At the United Nations, Ambassador Thomas-Greenfield should prioritize preparations for the coming dark, cold years. It is in the world’s best interest that all nations cease aggressions, even if just for a decade or so, so that we all may turn our resources to securing the lives of our peoples.

The USDA should not just take the brakes off agricultural production; it should encourage all producers to ramp it up. We need to have enough on hand to address the expected shortfall between production and requirement for at least five years. All loans to all farmers should be forgiven if they will agree to get on board with maximizing production. Garden seed producers, along with all other producers and processors, should be given significant tax credits for ramping up their production too.

Commerce should support vastly expanded food processing for long-term storage. Congress should fund the acquisition and storage of surplus staples and other food commodities so that sufficient amounts are on hand to keep our markets, feeding programs, and food banks operating when crop after crop begins to fail. Stockpiling for our future should take precedence over exports.

The NSC should demand a reconstitution of our strategic grain reserve, and that we prepare not just for ourselves, but to be able to share with needy neighbors and allies to keep America secure.

State, local, and tribal governments should clear away barriers to gardening and small animal production, including not limiting water catchment for gardening. Everything folks can do for themselves will take pressure off public services and limited markets. Local Emergency Services operations should also look at acquiring stocks of staples to help support their residents, as was done in many places last year.

Individuals, as well as schools and other institutions, should begin to garden, even if it’s just pots in a window. It’s a skill that takes time to learn and practice. Everyone should begin to preserve food for the hard times coming – freezing, canning, drying, smoking, pickling. As much as we can do for ourselves, we won’t be looking for someone else to have done for us.

This is really most important. We need to act now while food production is still relatively normal. Later on, if there’s nothing to buy, it won’t matter how much money we have on hand, as individuals or as a nation.

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Valentina Zharkova presents her analysis and findings in paper Modern Grand Solar Minimum will lead to terrestrial cooling.  Excerpts in italics with my bolds.

In this editorial I will demonstrate with newly discovered solar activity proxy-magnetic field that the Sun has entered into the modern Grand Solar Minimum (2020–2053) that will lead to a significant reduction of solar magnetic field and activity like during Maunder minimum leading to noticeable reduction of terrestrial temperature.

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Figure 3 presents the summary curve calculated with the derived mathematical formulae forwards for 1200 years and backwards 800 years. This curve reveals appearance of Grand Solar Cycles of 350–400 years caused by the interference of two magnetic waves. These grand cycles are separated by the grand solar minima, or the periods of very low solar activity.

Currently, the Sun has completed solar cycle 24 – the weakest cycle of the past 100+ years – and in 2020, has started cycle 25. During the periods of low solar activity, such as the modern grand solar minimum, the Sun will often be devoid of sunspots. This is what is observed now at the start of this minimum, because in 2020 the Sun has seen, in total, 115 spotless days (or 78%), meaning 2020 is on track to surpass the space-age record of 281 spotless days (or 77%) observed in 2019. However, the cycle 25 start is still slow in firing active regions and flares, so with every extra day/week/month that passes, the null in solar activity is extended marking a start of grand solar minimum.

Similarly to the Maunder Minimum … the reduction of solar magnetic field will cause a decrease of solar irradiance by about 0.22% for a duration of three solar cycles (25-27).” Zharkova determines that this drop in TSI (in conjunction with the “often overlooked” role solar background magnetic field plays, as well as with cloud nucleating cosmic rays) will lead to “a drop of the terrestrial temperature by up to 1.0°C from the current temperature during the next three cycles (25-27) … to only 0.4°C higher than the temperature measured in 1710,” with the largest temperature drops arriving “during the local minima between cycles 25−26 and cycles 26-27.

The reduction of a terrestrial temperature during the next 30 years can have important implications for different parts of the planet on growing vegetation, agriculture, food supplies, and heating needs in both Northern and Southern hemispheres. This global cooling during the upcoming grand solar minimum (2020-2053) can offset for three decades any signs of global warming and would require inter-government efforts to tackle problems with heat and food supplies for the whole population of the Earth.