Surface Temperature Response to Solar EMR at Top of the Atmosphere

By Richard Willoughby

Summary

This technical note examines the linkage between measured surface temperature and calculated solar electromagnetic radiation (EMR) available to the top of the atmosphere (ToA) that changes due to variation in Earth’s orbit.

Four regions are examined and analyzed using monthly averages for temperature and solar EMR available at ToA.  Figure 1 shows the regions examined.

The regions are:

  • Central USA using GHCN temperature measurements
  • Mediterranean Sea using NCEP/Reynolds Sea Surface (excludes land in the region)
  • Nino34 region of the Equatorial Pacific using NCEP/Reynolds
  • Southern Ocean 55S to 65S using NCEP/Reynolds (NCEP assumes water below ice is -1.8C)

For each region, the monthly measured time based data for temperature and calculated Solar EMR is displayed as well as correlations between the two.  There are also time shifted correlations that indicate the thermal response of each region.  The responses to solar forcing vary significantly but the correlations outside the tropics are high:

  • Central USA requires 13.5W/m^2 for each degree Centigrade; regression coefficient 97%
  • The Mediterranean requires 28.5W/m^2 for each degree Centigrade; regression coefficient 96%
  • The Nino34 region requires minus 40W/m^2 for each degree Centigrade; regression coefficient 14%
  • The Southern Ocean requires 192W/m^2 for each degree Centigrade; regression coefficient 93%.

Both the solar EMR and surface temperature in the Nino34 region are subjected to frequency analysis to give insight into other factors that influence the surface temperature in addition to solar EMR.

Southern Ocean

The December Solar EMR at 60S peaked 3,800 years ago.  It has been in decline since then.  Figure 2 shows the monthly average temperature for both solar EMR and surface temperature for 55S to 65S for all longitudes.

Figure 3 examines the correlation between temperature and EMR.

There is a relatively weak positive correlation but there is indication of a phase shift.

Figure 4 shows how the correlation is dramatically improved by lagging the EMR two months relative to the measured surface temperature.  It takes 192W/m^2 change in EMR to move the surface temperature 1C.

Mediterranean Sea

Average April solar EMR at 37N was at a minimum of 374W/m^2 5,000 years ago.  It is now 387W/m^2.  The April EMR will reach its next April peak of 399W/m^2 in 3,500 years from present.  The following Figures 5, 6 and 7 show the EMR and temperature analysis for the Mediterranean Sea.

The linear correlation has a regression coefficient of 96%.  A change of 28.5W/m^2 is required to shift the surface temperature 1C.

Central USA

Given the good correlations over ocean surfaces, it was considered educational to look at a region of land surface that has good coverage of reliable temperature records.  Figures 8, 9 and 10 show the result.

The month-to-month correlation for the land surface is much better than for the ocean but there is an obvious loop.  The best correlation is achieved with just 1 month lag.

The correlation of 97% for land is better than for ocean despite the much wider annual range in temperature for the same range in solar EMR; requiring only 13.5W/m^2 to move the surface temperature 1C.

Nino34 Region

The temperature response to EMR in the Nino34 region shown in Figure 11 is quite different to the higher latitudes so far considered.

It is clear that there is some annual cycling, but it is obviously poorly correlated with the EMR variation as shown in Figure 12.

It is notable that the correlation is negative.  In fact the correlation is improved by advancing the EMR.

The regression coefficient of 14% indicates high confidence the correlation is negative.  The fact that temperature leads EMR is consistent with negative feedback based on the surface temperature rather than the temperature actually controlling the sun.

The temperature trend in the region displays a definite longer-term beat, which shows up in the frequency analysis in Figure 14.

The annual peak is dominant but there are other broad peaks around 10.7 years and 22.3 years using just the temperature from the satellite era.

Figure 15 shows the frequency analysis for the calculated solar EMR based solely on the orbital geometry.

It is clear that there is no matching peak at a period around 11 years so it is concluded that the beat in the temperature record is not related to orbital changes.

Figure 16 shows the time variation of the temperature with monthly sunspot number.

There may be some correlation, but it is not clear in this graph. And the frequency analysis of the sunspot number shows peaks at periods similar to the temperature measurement.

The month-to-month correlation between temperature and sunspot numbers is insignificant per Figure 18 but becomes significant when the Sunspot number is lagged 31 months per Figure 19.

Conclusions

It has been demonstrated that land and ocean surface temperature are highly correlated to solar EMR in mid and higher latitudes; making due allowance for different thermal inertia of land and ocean.

It is further noted the observed trends in reliable surface temperature records can be forecast by the changing regional monthly solar EMR.  Figure 20 shows how solar EMR has changed over the past 520 years and will change in the next 80 years at 30N.

Over the past 520 years, the April EMR has undergone the highest monthly increase at 30N and will continue to do so, increasing by almost 3W/m^2 over the 600 year time frame.  In contrast, September EMR is in decline and will reduce by about 2.6W/m^2 over the 600 year period.  Overall there is a slight upward trend in annual average EMR at 30N that will continue.

It has also been observed that land surface temperature responds in half the time and twice the range of latitudinal constrained deep water bodies such as the Mediterranean Sea for the same EMR variation.  So it should be expected, as the solar EMR increases in the Northern Hemisphere, while reducing in the Southern hemisphere, the global average surface temperature will increase due to the higher proportion of land to water in the NH compared with the SH.

The average solar intensity over the Southern Ocean is in steady decline but the decline is most evident in November, which reduces the peak summer surface temperature.  Figure 21 shows how the solar EMR has changed during the satellite era from 1980 to 2022 and will continue to change to 2040.

The Nino34 region is in a temperature limited region where temperature is negatively correlated with solar EMR.  There is high probability that there are other solar factors in addition to orbital changes influencing the temperature in the region.    

Data Sources

The data used to determine top of atmosphere reflected EMR were downloaded from NASA’s Earth Observation web site.

https://neo.gsfc.nasa.gov/

The data for GHCN land air temperature and NCEP measured SST were downloaded from the Climate Explorer website.

http://climexp.knmi.nl/start.cgi

The orbital parameters for determining the changes in ToA solar EMR came from the Astropicxels site:

Planetary Ephemeris Data (astropixels.com)

The data on sunspot number were sourced from the Royal Observatory of Belgium Sunspot Index and Long-term Solar Observations (SILSO) web site:

https://sidc.be/silso/datafiles

Although solar EMR was calculated from the orbital data, there is a useful reference source for determining insolation at nominated latitudes and months using the IMCCE insola web based model:

http://vo.imcce.fr/insola/earth/online/earth/online/index.php

The Author

Richard Willoughby is a retired electrical engineer having worked in the Australian mining and mineral processing industry for 30 years with roles in large scale operations, corporate R&D and mine development.  A further ten years was spent in the global insurance industry as an engineering risk consultant where he developed an enduring interest in natural catastrophes and changing climate.

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PCman999
October 4, 2022 10:15 pm

Thank you for your hard work and insight!

Wim Röst
October 4, 2022 10:47 pm

A very interesting post.
 
A question about figures 20 and 21.
comment image?w=947&ssl=1
Am I right that in figure 20 the black line “Present to 2100” must be read as “Situation 2100 compared to 2022” or “Change in solar EMR from 2022 to 2100”? The actual wording “Present to 2100” suggests the black line is showing the average change from 2022 to 2100.
(The same for the other lines in both figures)

Last edited 1 month ago by Wim Rost
RickWill
Reply to  Wim Röst
October 4, 2022 11:19 pm

Wim
The overall change over the full 600 years is the difference between the two curves. Spring time increasing and autumn reducing but overall upward. I did this around the present situation as the reference to make the point that the change is accelerating; spring has taken 520 years to gain 1.7W/m^2 while only taking 80 years to increase another 1.1W/m^2.

There are year-to-year swings due to orbital variation as well. If I had taken 2104 as the final year then the upswing would be even higher. 2020 was the highest solar input in total this century so far. There will only be a couple of other years in the next 80 years that exceed 2020.

Wim Röst
Reply to  RickWill
October 4, 2022 11:54 pm

RickWill: “spring has taken 520 years to gain 1.7W/m^2 while only taking 80 years to increase another 1.1W/m^2.”

WR: Thank you Richard (or Rick if preferred), this is clear. But someone who only sees the graphic will not exactly know what the lines represent, I think. For me, the meaning of the black line would have been more clear when would be stated: “Change in solar EMR from 2022 to 2100″.

What do you exactly mean by “There are year-to-year swings due to orbital variation as well.” Isn’t all orbital variation represented in the graphic? Is the graphic only about the effect of changes in precession, for example?

RickWill
Reply to  Wim Röst
October 5, 2022 12:11 am

My point with the year-to-year comment is that the changes are not necessarily gradual. They bounce around. If you only looked at two years say 10 years apart, you might see a different story to looking at two years 100 years apart. The yearly change can be very different to the average of 100 year change.

Wim Röst
October 5, 2022 12:04 am

Richard Willoughby: “It has also been observed that land surface temperature responds in half the time and twice the range of latitudinal constrained deep water bodies such as the Mediterranean Sea for the same EMR variation.
 
WR: A very interesting change will occur when there will be a (relative) shift in the presence of high- (or low-) pressure areas from ocean to land or inversely. As shown in the post, the temperature effect for respectively Land and Ocean is considerable, even for unchanged solar EMR. High-pressure areas are known as less cloudy areas and will permit more solar energy to reach the surface. A shift in pressure from Land to Ocean must have a considerable effect on (average) temperatures. Shifting solar EMR over latitudes (and seasons) must result in differences in pressure.

RickWill
Reply to  Wim Röst
October 5, 2022 12:34 am

Shifting solar EMR over latitudes (and seasons) must result in differences in pressure.

The important factor with this observation for most humans is the degree of moist air divergence from oceans to land. Rainfall and snowfall are both important factors for humans.

So the pressure difference need to be translated into the airflow and the moisture it carries.

Convective instability is the engine of the atmospheric circulation. It requires a minimum of 15C surface temperature and 35mm of water vapour to operate. It requires at least 22C and 48mm of water vapour to achieve deep convection that is associated with cloudburst.

So it is not only the surface pressure but also the moisture in the air column because that makes a huge difference in how one column interacts with another.

Javier
October 5, 2022 1:55 am

The main factor that determines surface temperature is insolation. This has always been known.

A problem with precession is that its changes are too slow to account for the kind of centennial temperature changes that occupy us and preoccupy some.

Another problem is that precession does not change the amount of energy the planet gets over a year, it just changes its seasonal distribution.

A third problem is that the effect of precession is opposite in both hemispheres. When it increases summer insolation and decreases winter insolation in one, it increases winter insolation and decreases summer insolation in the other. It is not good at inducing global changes.

A fourth problem is that global temperature responds very poorly to precession changes. In fact, the same precession situation as we have now took place about 21,000 years ago when the planet was in the last glacial maximum.

This figure shows the three-month curves for precession at the northern and southern hemispheres for the past 40 kyr as a percent of modern precession. The background color displays changes due to obliquity by latitude in W/m2. The black curve is Greenland GISP2. The figure is from my book Climate of the Past, Present and Future.

comment image

I consider it shows very clearly that global temperature responds primarily to obliquity changes.

Due to all the above, precession involvement in modern global warming is likely to be negligible.

RickWill
Reply to  Javier
October 5, 2022 3:24 am

Another problem is that precession does not change the amount of energy the planet gets over a year, it just changes its seasonal distribution.

But the solar intensity changes dramatically. The sun puts as much energy into the SH in 180 days that it puts into the NH in 186 days. And the surface temperature is highly correlated to the solar intensity in the mid latitudes as I have clearly demonstrated.

A third problem is that the effect of precession is opposite in both hemispheres. When it increases summer insolation and decreases winter insolation in one, it increases winter insolation and decreases summer insolation in the other. It is not good at inducing global changes.

Exactly. Land responds at least twice as fast over twice the range for the same change in solar intensity as ocean surface. Now all you need to know is that the NH comprises 50% land while the SH 10% land. The Southern Ocean takes 14X more solar intensity to shift 1C as central USA. So what do you think is going to happen as the intensity in the SH reduces while increasing in the NH. Very slow cooling in the SH but much faster warming in the NH.

A problem with precession is that its changes are too slow to account for the kind of centennial temperature changes that occupy us and preoccupy some.

It is a slow change over an enormous range. The intensity change from perihelion to aphelion is currently 7% of the total solar input. So centennial changes are significant as I have shown. Even decadal changes are apparent in good records like the NOAA/Reynolds.

Javier – You have these ill-informed misconceptions about solar intensity. Take the time to do the calculations so you are better informed. The orbit is tightly linked to the changes in sea level, temperature and CO2 over the past 800kyr. CO2 does zip.

Javier
Reply to  RickWill
October 5, 2022 5:10 am

And the surface temperature is highly correlated to the solar intensity in the mid latitudes as I have clearly demonstrated.

You didn’t need to demonstrate it. It has been known since antiquity that the more insolation received the higher the temperature. It is the basis for adoring the Sun as a god.

Land responds at least twice as fast over twice the range for the same change in solar intensity as ocean surface.

Land does not store solar energy. Only the oceans do. The land returns the energy to the atmosphere over the same day. This makes the NH vary its temperature over the year a lot more, but it is not the basis of the higher warming experimented by the NH.

The intensity change from perihelion to aphelion is currently 7% of the total solar input.

And it has a very small effect on climate, as demonstrated by the fact that the Earth is 3.8ºC warmer when it is farther from the Sun than when it is closer.

comment image

Precession is important for climate but at a different timescale. You are just following precession down a rabbit hole.

RickWill
Reply to  Javier
October 5, 2022 5:51 am

And it has a very small effect on climate, as demonstrated by the fact that the Earth is 3.8ºC warmer when it is farther from the Sun than when it is closer.

Do you see that you make my point perfectly with this statement?. The fact that the planet is warmer when it has the least solar intensity but directed at the NH proves exactly what I am saying. The high proportion of land in the NH means it responds to solar intensity to a much higher degree than the ocean dominated SH. Now imagine if the solar intensity in the NH has a long term upward trend and the SH a long term downward trend. What is the average temperature going to do?

The NH is 3.8C warmer when it has the least solar intensity. Can you have a stab at how much warmer it will be when it has the highest solar intensity?

Oceans are not storing energy through the surface other than at the high latitudes where high saline water carriers heat below 500m. They are retaining more heat when the water cycle slows down. Globally ocean are coolest in December and January when they are taking in the most energy. Temperature and heat input globally are 180 degrees out of phase. A large proportion of the oceans in the NH go into temperature limit mode in April through to August because there is less heat transfer to the land via latent heat. The net ocean evaporation reaches its annual minimum in July. Globally the runoff to oceans is declining. Net evaporation is at is maximum in December when the oceans are taking in most heat but the ocean temperature is at its coolest. Deep oceans cool when evaporation is high and retain more heat when the surface is at the 30C limit because all warm pools are mid level convergence zones with net precipitation.

RickWill
Reply to  RickWill
October 5, 2022 6:10 am

One of the other factors in the rapid warming of the NH due to changes in solar intensity is that the land is drying out because precipitation over the NH land is declining. Less water means lower thermal inertia so even faster and greater response to solar forcing.

Javier
Reply to  RickWill
October 5, 2022 6:54 am

The fact that the planet is warmer when it has the least solar intensity but directed at the NH proves exactly what I am saying.

It does not. It proves that land warming does not result in an albedo increase due to an increase in cloud cover. Your analysis ignores albedo (cloud cover) changes.

The high proportion of land in the NH means it responds to solar intensity to a much higher degree than the ocean dominated SH.

It does not mean that. Solar energy is stored by the climate system in the oceans. Land warming has only a daily and seasonal effect. Everybody has personal experience with that.

Now imagine if the solar intensity in the NH has a long term upward trend

So long-term that it cannot explain any significant part of modern solar warming. I don’t have to imagine it. From 42 Kyr BP to 32 Kyr BP NH insolation had a very long-term increase in insolation and Greenland (in the NH) shows a temperature decrease. Your hypothesis doesn’t fly.

Oceans are not storing energy through the surface other than at the high latitudes where high saline water carriers heat below 500m. They are retaining more heat when the water cycle slows down.

You have an insufficient understanding of the planet’s energetics. Please study ocean boundary energy flux. You can start with Jim Steele’s excellent articles. In this one, you have a figure halfway through that shows net surface heat flux:

https://perhapsallnatural.blogspot.com/2022/06/big-5-natural-causes-of-climate-change.html

Ocean heat content has been increasing, demonstrating that the ocean is accumulating heat.

Deep oceans cool when evaporation is high and retain more heat when the surface is at the 30C limit

This makes no sense. Deep ocean temperature changes respond very little to short-term surface processes. The global ocean has been accumulating heat since 2004 at depths all the way down to 1900 m deep.

http://climate4you.com/images/VerticalTempChangeArgoWorldOceanSince200401%2065N-65S.gif

RickWill
Reply to  Javier
October 5, 2022 2:53 pm

This makes no sense. Deep ocean temperature changes respond very little to short-term surface processes. The global ocean has been accumulating heat since 2004 at depths all the way down to 1900 m deep.

It does make sense but you have not thought it through or ever tried to heat water from the surface against convection. There are two means of causing temperature rise in the deep oceans. The bottom water is coolest so if the net water cycle slows down, there is less cool water being drawn upward so the column gets hotter. This process is the only way deep ocean can get warmer over decades. Heating below 500m through conduction takes thousands of years so any current heating in the deep ocean is not being caused by surface heat flux.

You have an insufficient understanding of the planet’s energetics. Please study ocean boundary energy flux.

To be precise, the diagram in Jim Steele’s image is accurately described as net radiation flux. The actual heat flux is close to zero because the temperature hardly changes in the tropical Pacific, in fact, I have shown that the temperature is negatively correlated with sunlight in the tropics. So all that net radiation drives evaporation. The total surface heat flux is close to zero. The Eastern tropical Pacific is a high evaporation zone so it has high net radiation input at the surface that comes back out as evaporation.
\
I have a far better understanding of the ocean energetics than you have if you present this stuff as the basis of your understanding.

It does not. It proves that land warming does not result in an albedo increase due to an increase in cloud cover. Your analysis ignores albedo (cloud cover) changes.

Of course the cloud cover is included. I take the solar EMR at the top of the atmosphere and look at how the surface responds. Everything between the sun and the surface is accounted for. The reason the temperature leads the sunlight in the tropics is precisely due to the time it takes for the atmospheric water to increase and form the clouds that increase reflection to provide the negative feedback.

The response of the Southern Ocean to sunlight is 1/14th of the response of central USA to sunlight. Surely you can see if the sunlight tis reducing in the SH while increasing in the NH with its dominance of land there will be an increase in temperature for small variation sunlight.

I will have a close look at Greenland to see if I can solve your puzzle.

RickWill
Reply to  Javier
October 5, 2022 4:01 pm

The main factor that determines surface temperature is insolation. This has always been known.

Yes, obvious to most but not many have plotted the relationship.

But who knew that the response to solar forcing was negative in the tropics? If this was well known then all climate models would show the tropics cooling in response to CO2 forcing.

Who knew that the response to solar forcing over land could be more than an order of magnitude higher to the response over ocean?

Meisha
October 5, 2022 5:35 am

While not a scientist, I do have an engineering background and I must say your approach to understanding solar/ temperature relationships is eye-opening. Your analysis (finally) shows how enthalpy works in driving temperature — i.e., temperature response difference over land versus water. Javier seems to believe these different land/ water responses don’t matter because they “average out.” When will people come to realize you CANNOT average temperatures to make sense of energy flows?

What is really striking is the N34 analysis. It clearly demostrates the Eschenbach/ Lindzen hypotheses (I know they are not exactly the same…but they are related) that tropical ocean regions work to modulate solar input. It’s intriguing that there *may* be a sunspot signal there, although that aspect would require more investigation to clarify. The reality is that when multiple overlapping cyclical (and chaotic) phenomena overlap, the causal connections become difficult to tease apart.

I would be interested to know to what extent climate models implement these orbital/ EMR effects. If they do, how does that implementation relate to this analysis? If not, why not; and what effect would including them have on model output?

While rising oceans may be the best “fear factor” CAGW cultists have in rousing public opinion against fossil fuels (and modern political/ economic systems), it is temperatures over crop-growing land that REALLY matter to the future of mankind’s prosperity. A little warming (2C-3C) is likely to be net beneficial (irrespective of cause), a little cooling of 2C-3C could be a serious calamity in food production.

RickWill
Reply to  Meisha
October 5, 2022 6:07 am

The comment is appreciated.

Also, I have previous posts on the ocean surface limit of 30C that give very detailed description of the temperature limiting process:
https://wattsupwiththat.com/2022/07/23/ocean-atmosphere-response-to-solar-emr-at-top-of-the-atmosphere/
This one goes into much more detail on measurements at the moored buoys as well as the global response to atmospheric water:
http://www.bomwatch.com.au/wp-content/uploads/2021/08/Bomwatch-Willoughby-Main-article-FINAL.pdf

As far as ocean warming goes, there is a widely held misconception that deep oceans can be warmed by surface heat flux in a matter of decades. That is not how they work. The only way deep oceans can warm in decades is through slowing down net evaporation – transfer of water to land. That means the transport of cold water from high latitudes to the tropics slows down and the oceans retain more heat; heat retention rather than heat input.

There is clear evidence that net ocean evaporation has reduced in the past 50 years or so due to reducing measured runoff from land.

Javier
Reply to  Meisha
October 5, 2022 6:59 am

Javier seems to believe these different land/ water responses don’t matter because they “average out.”

If you want to know what I believe, you don’t have to invent it. You can get my book. If $2.99 is too much for you, you can get it free at my researchgate page.

Meisha
Reply to  Javier
October 5, 2022 7:48 am

Javier, apologies if I misrepresented your beliefs. And, no, $2.99 is very reasonable for access to all the work you’ve done.

My comment was in reaction to yours above; for example,

Another problem is that precession does not change the amount of energy the planet gets over a year, it just changes its seasonal distribution.”

and

“When it increases summer insolation and decreases winter insolation in one, it increases winter insolation and decreases summer insolation in the other. It is not good at inducing global changes.”

These comments seem to suggest that average global temperature, per se, is the metric of interest and importance. I think Rick’s point, and mine, is that regional temperatures, e.g., over land versus water and on a seasonal basis, is what matters to mankind. Global temperature is a strange metric for at least two reasons: (1) it’s an intensive measurement and so, technically, cannot be average over the globe and make “sense,” and (2) it does not directly affect anybody except insofar as it affects other weather or hydrological processes that directly impact people.

As a result, talking about average temperature — except in relatively local areas — has two problems:
(1) Global temperature may or may not be relevant to impacts on mankind and how we live our lives — for example: Arctic ice melting is of little concern to sea level; grounded Antarctic ice melting is a different story.
(2) Global temperature is affected by very different albedos and heat capacities of land and water (and their respective cloud covers…and more) such that averaging temperatures in the Arctic with temperatures in the Tropics and everything inbetween tells us little about what’s going on to drive that weird (IMHO) metric of “global temperature.”

Rick is focused on temperature impacts in different parts of the globe and what affects those temperature variations. You are focused on “average” global temperatures. Chalk and cheese.

Javier
Reply to  Meisha
October 5, 2022 9:18 am

No problem, Meisha.

The climate change theory I have developed, the Winter Gatekeeper hypothesis, is based precisely on the importance of winter atmospheric circulation and meridional transport changes. The winter in the name refers to the importance of seasonal changes.

My disregard for precession changes as a first-order factor in climate change comes from a profound analysis of how climate changes naturally. Precession is very important to set the position of the ITCZ, the climatic equator, and therefore responsible for important Holocene changes, like the drying of the green Sahara.

But it is a second-order factor to obliquity in the glacial cycle and the overall Holocene interglacial temperature evolution. I cannot detect any effect from precession in modern global warming, as it is a too short period to cause significant changes.

Another question is that 65ºN insolation is still dropping. If the climatic precession factor was so important, how the hell did the Northern Hemisphere get out of the LIA? You can check Bertrand et al. 2002. High frequency variations of the Earth’s orbital parameters and climate change. It essentially contradicts everything Rick Will here is telling us. For example they say:

Another point which is clearly highlighted on these panels is that the amplitude in the model response to the 11-year solar cycle is much larger than to the high frequency orbital forcing, which appears to be of the same amplitude as the model noise.

And that is only considering the response to solar cycle TSI changes, when I have demonstrated that most of the response is dynamical to UV changes transmitted to the polar vortex.

If one wants to be serious about climate change and not only contribute to the noise, one has to do a lot of reading about climate change.

RickWill
Reply to  Javier
October 5, 2022 3:48 pm

If one wants to be serious about climate change and not only contribute to the noise, one has to do a lot of reading about climate change.

And if one is apt to believe everything they read without testing it then they will arrive at the same misconceptions as the authors.

Look at how widely the unphysical claptrap of back radiation is accepted in climate phiisics. The fact that this nonsense prevails shows that the field is bereft of any understanding of EMR heat transfer.

Thomas
Reply to  Meisha
October 5, 2022 1:35 pm

Preevyet Meisha, I agree with your global temperature comments. There are more reasons, such as the fact that global average atmospheric temperature is not a measure of the system’s (earth, ocean, ice, air) average heat content, so it tells us nothing about whether the system is gaining or loosing heat. Also, in an El Niño or similar event, global atmospheric temperature goes up, but the system is actually cooling—heat from an ocean warm pool is release to the atmosphere, where it then vents to space. The atmosphere warms as the heat moves through it but the overall system is cooling.

Bob Weber
October 5, 2022 6:45 am

Rick, your Figure 14 frequency analysis of Nino34 was very telling wrt sunspot cycles.

However, I am unclear as to how you achieved such smooth monthly insolation curves from the Astropixels planetary empheris tables, which just have aphelion and perihelion distance values.

About your Figure 20, I attempted to replicate it with NASA’s monthly latitude insolation webform, which uses Berger’s orbital parameters, and arrived at different values for both the 1500-2020 and especially the 2020-2100 30N insolation changes. Spreadsheet. Can you find out why your results differ from NASA’s?

comment image

Javier
Reply to  Bob Weber
October 5, 2022 7:11 am

Rick, your Figure 14 frequency analysis of Nino34 was very telling wrt sunspot cycles.

Nothing that wasn’t already known. White et al. 2003 show in figure 4 the coupling between global ocean temperature and solar surface radiative heating.

White, W.B., Dettinger, M.D. and Cayan, D.R., 2003. Sources of global warming of the upper ocean on decadal period scalesJournal of Geophysical Research: Oceans108(C8).

RickWill
Reply to  Javier
October 5, 2022 3:16 pm

Nothing that wasn’t already known. 

I do not place much store in anything I read unless I can verify it. So it appears White 2003 arrived at a similar result and can claim priority.

As a further note I looked at the response to cosmic rays and the correlation improved slightly to 8% with a 24 month lag.

The timing of ENSO is unrelated to the solar cycle but its intensity responds to the cycle. The strong El Nino of 2015/16 occurred at the last peak of the solar up cycle so temperature was sustained higher than the 2011 event that occurred during a minimum in the solar cycle.

RickWill
Reply to  Bob Weber
October 5, 2022 1:56 pm

I will check the NASA data. The 1500 to 2020 and the 1850 to 2020 appear close to my result. I simply draw a smooth curve through the monthly data points. The difference of 7W/m^2 for the 1500-2020 is somewhat more than I get.

The shift in orbit is significant between 2020 and 2100. The change in perihelion is 15,000 kilometres and there is two days difference between the timing of perihelion so a straight line is unlikely. There is a clear trend from the other two curves and it is unlikely that trend will not be similar for the following 80 years.

RickWill
Reply to  RickWill
October 5, 2022 9:19 pm

Bob
I have checked the NASA site and I wonder about the Berger approximation. It is a useful source for quick look up.

I got the same result as you for 2100 so I looked at 2080 to see if it was just a yearly swing or hidden by rounding. The Present to 2080 change is larger change than I have for Presnt to 2100 as follows:
2080:249 304 373 430 465 476 467 437 386 320 260 231  
 2020:248 303 371 429 464 476 468 438 387 322 261 231

So March is 2W/m^2 higher in 2080 than 2020 and October 2W/M^2 lower. Both similar trends to what I have but probably overstated by lack of decimals.

Bob Weber
Reply to  RickWill
October 6, 2022 6:22 am

Thanx for your effort. That is interesting about 2080. Soon I’ll have time after filling our woodshed to implement the NASA’s webform Fortran code and do more exploration. If it was me, any difference between my results and theirs would be enough to make me wonder whether my method is accurate.

I thank you again for bringing the insolation subject out into the light with your many comments and posts.

RickWill
Reply to  Bob Weber
October 6, 2022 2:25 pm

If it was me, any difference between my results and theirs would be enough to make me wonder whether my method is accurate.

The orbital calculations by others are complex approximations and my calculations based on those have some simplifying assumptions so there could be small discrepancies. I am more interested in the absolute range over monthly and yearly time scale and trends over centuries and I get those close.

I use the IMCCE site for quick reference for checking long run changes:
http://vo.imcce.fr/insola/earth/online/earth/online/index.php

Gary Pearse
October 5, 2022 8:15 am

Thanks Richard, a most interesting study.

“There is high probability that there are other solar factors in addition to orbital changes influencing the temperature in the region (ENSO region).”

Certainly the negative correlation must be due to the response of equatorial heating driving the strong redistribution of heat poleward by atmospheric (Hadley cells) and ocean currents. The ‘heat’ reaching ToA above the Pacific in high latitudes largely originated in the equatorial zone. Looked at another way, it is a quantitative measure of this redistribution. Strong evaporative cooling in the equatorial zone is a large part of this redistribution.

Your mention of water temperatures beneath ice at -1.8C (60S) seems inappropriate for your analysis. The the satellite temperatures above the ice should be used if possible. The -1.8C for water below ice is true for the whole region. Your correlation is high because it is definitely cold there. If ice is forming or at least not melting, it is likely colder. See if the correlation improves with using a temperature of, say, -2.5 or -3C.

RickWill
Reply to  Gary Pearse
October 5, 2022 3:36 pm

The negative correlation in the context of including everything from the ToA solar EMR to the surface was a new result. The fact that the temperature leads the sunlight was something I expected because I have already determined that it takes about a month for the atmospheric water to build up enough to form the reflective cloud that increases solar EMR reflected short wave.

I go into detail on this aspect here:
https://wattsupwiththat.com/2022/07/23/ocean-atmosphere-response-to-solar-emr-at-top-of-the-atmosphere/
I was using much higher time resolution data from moored buoys and arrived at a 25 day lag between the surface temperature and the reduction in surface sunlight due to increased reflection and column absorption in the tropical Pacific.

Your mention of water temperatures beneath ice at -1.8C (60S) seems inappropriate for your analysis.

The NOAA/Reynolds data set is very reliable for ocean surface temperature hence my preferred reference. It is an ocean surface data set that follows the convention of ice covered water being at -1.8C. In this regard, view the sea ice as dense cloud. If I was to use the actual solid surface as the reference then the result would only be slightly different because there is not much sea ice in the band of the Southern Ocean sampled.

Last edited 1 month ago by RickWill
Gary Pearse
Reply to  RickWill
October 6, 2022 8:43 pm

Thanks Rick. A little bit of over-thinking on my part re the Southern Ocean!

DMacKenzie
October 5, 2022 9:14 am

Fig . 13 is missing, replaced by Fig. 12 twice.

RickWill
Reply to  DMacKenzie
October 5, 2022 8:36 pm

Thank you for picking that up. It is an important chart although it only supports the numbers provided in the text.

The reason for its importance is that surface temperature in this region is negatively correlated with solar forcing. So if CO2 was providing forcing in the same way as sunlight then CO2 would be causing the tropics to cool. There is no cooling in the tropics.

Nino34_EMR_Temp.png
Clyde Spencer
October 5, 2022 11:26 am

… regression coefficient 14%

That means that less than 2% of the variance of the dependent variable can be predicted or explained by the independent variable. In other words, it is very likely to not be statistically significant; however, even if it is statistically significant, it is of little practical value.

RickWill
Reply to  Clyde Spencer
October 5, 2022 1:34 pm

The negative correlation is statistically significant.

RickWill
Reply to  RickWill
October 5, 2022 2:00 pm

 even if it is statistically significant, it is of little practical value.

The fact that the response is negative is a REALLY important observation. It means that if CO2 was able to cause forcing similar to sunlight, then it would be cooling the tropics, which is not being observed.

Reply to  RickWill
October 8, 2022 4:30 pm

wrong again.

Reply to  RickWill
October 8, 2022 4:30 pm

nope its not

Frank from NoVA
October 5, 2022 2:42 pm

Rick,

You clearly have invested a lot of time and effort into your analyses of SST vs EMR. However, given the periodicity of the data, I think it’s really difficult to ascertain any relationship between the two. For example, looking at your Fig. 3, I see 12 data clusters, each of which indicates a wide range of SST versus a much narrower, if non-existent, EMR range. While I’m no data expert, I would suggest fitting a periodic wave to each data series and then plot the residuals on xy-plots (w/ or w/o lags) to see what’s really going on besides seasonality. As one of my former professors once said, if you have the wrong functional form of the data, the results can be misleading. Please feel free to tell me I’m all wet.

RickWill
Reply to  Frank from NoVA
October 5, 2022 4:33 pm

Frank
Each data cluster is a month. The widest temperature band for any given month is just over 1C occurring in the month when EMR is around 380W/m^2. There are 40 years so 60 points clustered into that narrow range.

The elliptical nature of the clusters indicate a phase shift. If you are familiar with Lassijous-Bowditch curves then you will appreciate the significance of this. For example two sine waves that are 90 degrees out of phase will produce a circle when plotted on axes scaled for the range. Lagging the sunlight by two months almost corrects for the phase shift apparent in the data. That allows me to make a straight line correlation. If I had higher time resolution data, I may improve the correlation but 93% confirms they are highly correlated.

I could correlate the unshifted data to a single ellipse that would give the same regression coefficient.

Frank from NoVA
Reply to  RickWill
October 5, 2022 6:43 pm

Thanks Rick,

I was indeed aware that each cluster represented a specific month. As I said, I’m no expert, so I am not familiar with Lassijous-Bowditch curves. However, if I was inclined to make out a relationship between EWR and SST, I’d deseasonalize the data.

RickWill
Reply to  Frank from NoVA
October 5, 2022 8:01 pm

However, if I was inclined to make out a relationship between EWR and SST, I’d deseasonalize the data.

By doing that you lose the actual seasonal response, which was the key point to the post. That means you are no longer looking at the range of response to the range in solar EMR or the thermal lags. I have looked at the annual trends in temperature and sunlight and found the temperature follows sunlight outside the tropics. It is the reason the Northern Hemisphere is warming and the Southern Ocean, as well as Antarctica, are cooling.

Those decadal trends in both temperature and sunlight are discussed here:
https://wattsupwiththat.com/2022/07/23/ocean-atmosphere-response-to-solar-emr-at-top-of-the-atmosphere/

There is no decadal trend in the Nino34 region in either temperature or sunlight so if the data was seasonally detrended it would not show the negative correlation or leading response. That is the problem with anomalies, they hide a lot of insight but are good for highlighting minutia.

Reply to  Frank from NoVA
October 8, 2022 4:32 pm

simple plot shos you his linear model is not even wrong and the correlation is meaningless

October 7, 2022 8:08 pm
  • Central USA using GHCN temperature measurements
  • Mediterranean Sea using NCEP/Reynolds Sea Surface (excludes land in the region)
  • Nino34 region of the Equatorial Pacific using NCEP/Reynolds
  • Southern Ocean 55S to 65S using NCEP/Reynolds (NCEP assumes water below ice is -1.8C)

4 regions 4 heterogeneous methods for calculating temps

a. just use gridded temps from
uah
giss
hadcrut
best

October 7, 2022 8:51 pm

The regression coefficient of 14% indicates high confidence the correlation is negative. The fact that temperature leads EMR is consistent with negative feedback based on the surface temperature rather than the temperature actually controlling the sun.

look at the data never never never try to fit a straight line to data like that.

your r^2 is pathetic mannian like.

you need to go back to data analysis 101

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