May 14, 2021
Have you ever worn a dark T-shirt on a sunny day and felt the fabric warm in the Sun’s rays? Most of us know dark colors absorb sunlight and light colors reflect it – but did you know this doesn’t work the same way in the Sun’s non-visible wavelengths?
The Sun is Earth’s power source, and it emits energy as visible sunlight, ultraviolet radiation (shorter wavelengths), and near-infrared radiation, which we feel as heat (longer wavelengths). Visible light reflects off light-colored surfaces like snow and ice, while darker surfaces like forests or oceans absorb it. This reflectivity, called albedo, is one key way Earth regulates its temperature – if Earth absorbs more energy than it reflects, it gets warmer, and if it reflects more than it absorbs, it gets cooler.
The picture becomes more complicated when scientists bring the other wavelengths into the mix. In the near-infrared part of the spectrum, surfaces like ice and snow are not reflective – in fact, they absorb near-infrared light in much the same way a dark T-shirt absorbs visible light.
“People think snow is reflective. It’s so shiny,” said Gavin Schmidt, director of NASA’s Goddard Institute for Space Studies in New York City and acting NASA senior climate adviser. “But it turns out in the near-infrared part of the spectrum, it’s almost black.”
Clearly, for climate scientists to get the whole picture of how solar energy enters and exits the Earth system, they need to include other wavelengths besides visible light.
Earth’s energy budget is a metaphor for the delicate equilibrium between energy received from the Sun versus energy radiated back out in to space. Research into precise details of Earth’s energy budget is vital for understanding how the planet’s climate may be changing, as well as variabilities in solar energy output.Credits: NASA’s Goddard Space Flight Center
That’s where NASA’s Total and Spectral Solar Irradiance Sensor (TSIS-1) comes in. From its vantage point aboard the International Space Station, TSIS-1 measures not only the total solar irradiance (energy) that reaches Earth’s atmosphere, but also how much energy comes in at each wavelength. This measurement is called spectral solar irradiance, or SSI. TSIS-1’s Spectral Irradiance Monitor (SIM) instrument, developed by the University of Colorado Boulder’s Laboratory for Atmospheric and Space Physics, measures SSI with an accuracy better than 0.2%, or within 99.8% of the true SSI values.
“With TSIS-1, we have more confidence in the measurements of visible and near-infrared light,” said Dr. Xianglei Huang, professor in the department of Climate and Space Sciences and Engineering at the University of Michigan. “How you partition the amount of energy at each wavelength has implications for the mean climate.”
The composition of that light that falls on Earth matters to understanding Earth’s energy budget. NASA’s Total Solar and Spectral Irradiance Sensor (TSIS-1) measures the Sun’s energy in 1,000 different wavelengths, including the visible, ultraviolet, and infrared, known as solar spectral irradiance. Credits: NASA’s Goddard Space Flight CenterDownload this video and other supporting visualizations from NASA Goddard’s Scientific Visualization Studio
Huang and his colleagues at the University of Michigan, NASA’s Goddard Space Flight Center in Greenbelt, Maryland, and University of Colorado Boulder recently used TSIS-1 SSI data in a global climate model for the first time. “Several studies used various SSI inputs to analyze the sensitivity of climate models in the past” – however, this study was the first to investigate how the new data changed the modeled reflection and absorption of solar energy at Earth’s poles, said Dong Wu, project scientist for TSIS-1 at Goddard.
They found that when they used the new data, the model showed statistically significant differences in how much energy ice and water absorbed and reflected, compared to using older solar data. The team ran the model, called the Community Earth System Model, or CESM2, twice: Once with new TSIS-1 data averaged over an 18-month period, and once with an older, reconstructed average based on data from NASA’s decommissioned Solar Radiation and Climate Experiment (SORCE).
The team found that the TSIS-1 data had more energy present in visible light wavelengths and less in the near-infrared wavelengths compared to the older SORCE reconstruction. These differences meant that sea ice absorbed less and reflected more energy in the TSIS-1 run, so polar temperatures were between 0.5 and 1.3 degrees Fahrenheit cooler, and the amount of summer sea ice coverage was about 2.5% greater.
“We wanted to know how the new observations compare to the ones used in previous model studies, and how that affects our view of the climate,” said lead author Dr. Xianwen Jing, who carried out this research as a postdoctoral scholar in the department of Climate and Space Sciences and Engineering at the University of Michigan. “If there’s more energy in the visible band and less in the near-infrared band, that will affect how much energy is absorbed by the surface. This can affect how the sea ice grows or shrinks and how cold it is over high latitudes.”
This tells us that in addition to monitoring total solar irradiance, Huang said, we also need to keep an eye on the spectra. While more accurate SSI information will not alter the big picture of climate change, it may help modelers better simulate how energy at different wavelengths affects climate processes like ice behavior and atmospheric chemistry.
Even though the polar climate looks different with the new data, there are still more steps to take before scientists can use it to predict future climate change, the authors warned. The team’s next steps include investigating how TSIS data affects the model at lower latitudes, as well as continuing observations into the future to see how SSI varies across the solar cycle.
Learning more about how solar energy interact with Earth’s surface and systems – at all wavelengths – will give scientists more and better information to model the present and future climate. With the help of TSIS-1 and its successor TSIS-2, which will launch aboard its own spacecraft in 2023, NASA is shining a light on Earth’s energy balance and how it is changing.
Banner image: In this photo taken from the International Space Station, the rising Sun casts long shadows across the Philippine Sea. Credit: NASA
Some of the Garbage in has been found.
In the late 19th and early 20th century properties of different colour lights were a bit of enigma even for the great minds such as Planck, Bohr, Einstein etc, but it gave a rise to the quantum mechanics, a mischievous part of physics that turned everything upside down,and “that means we really don’t understand it” said Richard Feynman.
Is this some kind of trick? Dr. Jing seems to be admitting over estimating warming in the past?
Am I to understand that the spectral qualities of sunlight were not thoroughly studied? We really haven’t had much else we can do with the sun for a couple of centuries.
Okaaay…so… if we are now (ONLY NOW?) going to look at the entire electromagnetic spectrum to find global warming, are we also going to discuss the huge percentage of that energy turned into the matter and processes that make up the metabolism of our planet?
Probably not…
Yep,
this has been a pet peeve of mine for a long time as well.
just how much of the incoming (solar) energy is ‘used’ by life on our planet?
for some reason none of the global ‘energy budget’ diagrams i have seen has ‘life’ as one of the listed items. Yet the energy used for producing all of the planet’s biomass must be quite large.
and no not all of it is decomposed/recycled in a short timeframe so there should be a net effect.
Just wondering..
Stay sane,
willem
I have always wondered about the actual conversion and storage of energy (UV and chlorophyll) that take CO2 and H2O to manufacture potential energy hydrocarbons. That is, does the growth of matter reduce the heat measurement on earth. Obviously combusting it released energy. Does growing plant life have a cooling affect?
If you assume that the total volume of plant matter is in equilibrium, the amount of energy consumed to create it is moot since you get that same energy back out as it’s burned, eaten, decays, etc.
If the volume is increasing (and several studies show that it is), then only the quantity of energy that creates that increase matters. But yes, that amount of incremental growth will drive a small net cooling effect. At least until the plant volume reaches equilibrium again.
Make sense. The 15% greening of the globe must have been one of the indirect negative feedbacks from CO2 increase
Sorry, no citation but someone posting on a different article made a comment that intensified corn production has actually cooled the local climate around the farms. Hopefully there’s enough there to find the original article. Makes sense that a carpet of green leaves would reflect sunlight better than typical prairie.
Yes, leaves also transpire water and increased irrigation would lead to evaporative cooling too. So that complicates cause an effect. But the direct calculation of the number of calories stored is a measurable thing.
Precisely, since CO2 emitted energy is so weak it cannot penetrate the surface skin. This leads primarily to enhanced evaporation or immediate reradiation back into the atmosphere. What little is left most likely back fills for the solar energy used by the enhanced biosphere. Nothing of note left to produce warming.
And the total energy radiated back to space at all wavelengths?
Settled, I thought.
Love to see Willis chruncing the TSIS data set!
(As I remember the solar irradiation is quiet low in the near infrared? )
kind regards
SteenR
I do not buy that argument (that solar energy is low in the infrared region). Sensibly, as I go outside in this subtropical morning sunlight where I reside, the IR sensors in my skin report a very high amount of IR from the sun! As high or higher than standing 3 feet from a 1500 deg F campfire with red hot coals.
The amount of solar IR hitting the ground is a very high value. It is not the trivial amount as so many make it out to be. I doubt the proper context of the solar energy spectrum is perceived or reported by so called experts! (I do not doubt that higher wavelengths of solar energy have a lot of energy, but the absolute IR component is NOT small nor trivial)
This “study” opens a pandora’s box in my view – “they” say solar irradiance does not change much on average, but has anyone looked at the distribution of solar spectral frequencies over time? If the sun has any kind of cyclic shift in dominant freqs – that could severely alter the climatic effects here, even though average irradiance may not change much!
It isn’t just IR that warms you. All the light that isn’t reflected from your skin or clothes will be converted to sensible heat.
In the tropics, the insolation reaching you when in direct sunlight will be around 1100W/sq.m normal to the line of the sun. That will be about 4 times the radiant heat at 6ft from a blazing campfire 2ft across.
A good start on improving or knowledge on the reflectance/absorption of solar energy. There is another part of the equation, the actual reflectance mechanics. Incoming solar energy, at different wavelengths, does not simply reflect, it enters molecular binding sites, overloads the binding energy, and is discharged or tolerated. Reflectance is not like we imagine a mirror. Different wavelengths produce different reflectance/absorption parameters also based on the molecular makeup of the target of the incoming radiation. This is the basis for Short Wave Infrared Spectrometers, which we geologist utilize to aid in the processing of satellite sensor data (the SWIR machines utilize absorption, which is inverted to show reflectance). It will be interesting to see how the new reflectance/absorption data is utilized, because all data of this type now goes through political filters.
Do they come with the instrument or do they need to be ordered separately? And any information about the band pass (wide or narrow) would be helpful as well. 🙂
The bloody political filters are all over the place.
Yes, they are “free”.
1,000 bands over the visible through at least non-thermal IR. Fairly narrow bands compared to multispectral imagers. Essentially what would be called hyperspectral.
You would think that if they are going through “political filters” that would include Government Employee Filters as well, and as we all know there are an over-abundance of those filters that are always on break, or are standing around looking busy but are not, so they cannot be producing much energy gain. I would say those filters are actually lowering global temperatures.
Nothing new in this. Engineers have known that emissivity and absorptivity vary with temperature for both source and receiver. They do not use albedo which has no specified temperature or wavelength. Scientists basically have no understanding of thermodynamics and heat&mass transfer. Water over the temperature range has an emissivity of around 0.95 but it is lowered by salt content and algae. Oceans with waves and foam bring the emissivity below 0.9. Ice in the temperature range 0 to -50C has an emissivity less than 0.40. It could be higher if there is some dust and melt water on the surface.
Remember that in a gobal heat balance the radiation window is 66 W/m2 and not 40 W/m2 which Dr Trenberth has acknowledged but refuses to withdraw his infamous cartoon of heat balance with the false back radiation from CO2. There is no back radiation. CO2 is not a greenhouse gas as defined by the IPCC. It just delays the radiation heat outflow at the wavelength 14.8 micron. The outward radiation to space still occurs at a temperature of around 200K in the upper atmosphere.
Of course there is.
You are denying a century of proven physics. Even outer space at a temperature of 3 degrees Kelvin “backradiates” some photons to planet Earth. Although those stars at night don’t heat your retinas very much.
The amount of heat being radiated from one surface to another is
q/a= [k/(1/ehot+1/ecold-1] x (Thot^4-Tcold^4).
The ground is at Thot due to being warmed by sunshine, and gets “back-radiated” by photons emitted from the cold sky and clouds.
…..This is Basic physics that was part of the origins of quantum mechanics with the Planck curve that explained away the ultra-violet catastrophe.
No it’s not. It is pseudo-science. Energy cannot flow up gradient. Radiant energy always travels from the high energy source to the lower energy sink. You cannot separate the potential terms in the Stefan-Boltzman equation in the real world. The minus sign simply informs you of the direction of energy flow.
The photon is nothing more than energy quanta. It is not something like the bullets of a Gatling gun being sprayed around. It is E-M energy released downfield from a higher energy object to a lower energy object in discrete quanta. Clouds exist in the same E-M that Earth and all matter exists in and are equilibrated in that field in microseconds or less for clouds responding to Earth, much faster than their formation. LW energy from clouds only flows one way unless there is a temperature inversion.
I am surprised that the flawed radiation image still gets trotted out in the IPCC reports. It just shows how silly climate “science” really is. Real physicists at GISS must be totally embarrassed to be associated with that tripe.
RickWill,
I see this over and over and over. You are confusing the actual Laws of Thermodynamics with an algebraic simplification. The NET effect of energy transfer is that energy moves down hill, from higher potential to lower potential. This is simple mathematical fact (which math is just a model, not reality) that does not tell the story of what is actually going on. ALL BODIES THAT ABSORB thermal radiation ALSO RADIATE thermal radiation. This was discovered by Balfour Stewart in the 19th century. The radiation emitted is dependent upon its absolute temperature. So absortive bodies at some value of absolute temperature also radiate energy, and what ever is in the way of that radiation can absorb it, and that absorption becomes part of its own energy budget. When a body in space emits the same amount of radiation that it absorbs, its temperature is stable. Two bodies in close proximity will emit and absorb some amount of each other’s radiation. If they are at different temperatures then the colder body will emit less thermal radiation than the hotter, but at no time does it stop emitting thermal radiation if its temperature is greater than 0K. There is no “switch” in the Laws of Thermodynamics that can arbitrarily turn them on or off.
-BillR
BillR ‘
Take a lesson or ten in radiative energy transfer and get back to me when you have clue:
https://pubs.giss.nasa.gov/abs/mi06010m.html
If you are not willing to spend the time to learn, then skip to 22 minutes in this video:
https://www.youtube.com/watch?v=hjKJyn_uoIE
And just listen for a few minutes. That might improve your understanding.
To settle the argument about backradiation, let me suggest that you are both right, but radiation back down is going to be a minor part of the equation, drowned out by convection heat transfer. They are fussing and wetting themselves over what co2 could possibly due in a small part of the spectrum and ignoring monsterously huge amount of heat moved around by water in its various forms. So in the end it doesn’t matter if they want to point their spanking new ir guns at a cloud and yell out “look! It’s radiating!”. Just be patient, it will eventually be raining and you can ask him to show just how much that cloud is warming him up with all that rain.
Exactly. It’s complicated, and some effects are more important than others. You will notice that I qualified my discussion to avoid heat transfer by conduction and convection, which in the atmosphere are significant and very important. I also avoided discussing properties of water, which also are very significant and important.
Absolute language rarely has a place in science. And things don’t stop happening just because the effect is small.
-BillR
Yes, a photon is an energy quanta…everything else in your version of reality is in need of considerable substitution with experimental fact.
The question arises : how can the models using the wrong old information have matched the real climate? Surely there must have been a discrepancy betwen the model output and measurements because of the errors in the old data?
Well, that’s certainly a question that should be asked, but I can answer it (as can anyone with any knowledge of how the models actually work). The answer is that the models have vast numbers of parameters that are fiddled until the models’ output does match measurements. Those parameters can – and do – cover up any number of errors in the models. What this means is that the models’ internal workings do not need to bear any relationship to reality at all. If there’s an error in the composition of sunlight and its reflection and absorption in the Arctic, for example, a few parameters can be tweaked here or there to bring the models into line. I explained it a long time ago – https://wattsupwiththat.com/2015/09/17/how-reliable-are-the-climate-models/ – as follows (but there are plenty of better explanations out there):
– – –
The fourth IPCC report [para 9.1.3] says : “Results from forward calculations are used for formal detection and attribution analyses. In such studies, a climate model is used to calculate response patterns (‘fingerprints’) for individual forcings or sets of forcings, which are then combined linearly to provide the best fit to the observations.”.
To a mathematician that is a massive warning bell. You simply cannot do that. [To be more precise, because obviously they did actually do it, you cannot do that and retain any credibility]. Let me explain :
The process was basically as follows
(1) All known (ie. well-understood) factors were built into the climate models, and estimates were included for the unknowns (The IPCC calls them parametrizations – in UK English : parameterisations).
(2) Model results were then compared with actual observations and were found to produce only about a third of the observed warming in the 20th century.
(3) Parameters controlling the unknowns in the models were then fiddled with (as in the above IPCC report quote) until they got a match.
(4) So necessarily, about two-thirds of the models’ predicted future warming comes from factors that are not understood.
– – –
It’s not difficult to work out that no matter how many errors there are in the models they can still get a match with past measurements. What happens next, of course, is that it doesn’t take long for later observations to start diverging from the models’ predictions. But the problem is easily solved, in a cycle that can run for ever: they simply run the models again and tune them to the new measurements. Voila! They match again.
epicycles?
No – this time it’s deferrant!
That was my first thought as well. Glad you expressed it better than I could have done.
There was but now there isn’t. The process of homogenisation is able to correct the past to suit the models.
The modellers do not even blink when they present data like I have attached. As long as all the models show a similar upward trend with temperature they are meeting their objective.
Reality is not a list of interest of climate modellers.
If I was a computer programmer and was awarded a job to work on a climate model with the GOAL of matching the past and creating a warming future what would I do?
Mikw Jones
Mike, I respect you’re asking a legitimate question, but our fabled climate scientists (Mike Mann, Australian psychologist Lewandowsky, the mechanical engineer Bill Nye & other such qualified luminaries) ARE ACTUALLY NOT SCIENTISTS.
In fact they (and money grubbing, power-hungry politicians) could give a crap if “natural data” does not match modeled data. The only thing that counts is “are the sheep responding to our scare tactics?”.
Forty years (2 generations) of this propaganda is still having the desired effect: more and more sheep are ABSOLUTELY CONVINCED (ref: Gretta Thornberg & soon-to-be King Charles) the world is going to end…soon!.
So, it’s clear all the models are wrong and it’s been confirmed yet again.
That’s the mantra. It’s like, “we used this data set upside down but our answer is correct anyway”. The models may be garbage but you’ll never get ‘them’ to admit it.
I found the following graphic interesting. I have been researching the radiation, emissivity/absorbance, and energy balance lately. There are a couple of interesting things. Currently, the energy spectra from the sun is considered 50% visible and 50% near-infrared. But when you examine the power levels between incoming and outgoing there are major differences as this shows. (notice the different y-axis values)
You are comparing spectral power. You have to bring them to a total power flux by integrating over their spectra.
If you want to look at energy balance on Earth then the NASA Earth Observatory database is a great place to collect data.
https://neo.sci.gsfc.nasa.gov/view.php?datasetId=CERES_LWFLUX_M
You can get the top of atmosphere data to do your own energy balance. Easy to download data in Excel format and build your own picture.
I understand that. However eyeball the amount of near IR power absorbed by H2O as compared to what is radiated by CO2.
It’s good that they more carefully compare the models to reality. However, when looking at absorption/reflection of ice and snow (and presumably other surfaces) what matters is not the wavelengths at the top of the atmosphere but those reaching the surface. That measurement should have been available long ago since it doesn’t require putting a sensor in orbit.
Actually, the surface response has been known a long time — essentially since the first Landsat satellite (EROS 1) was launched in 1972.
That should be ERTS 1
Nice to know these guys are beginning to learn something about radiation physics.
Also if we can get them to learn some meteorology as well then that would be real progress.
All they ever needed to do was listen to Dr. Happer.
Intensity and emissivity are crucial. Hence why CO2 is irrelevant.
How a professional modeler would address Climate Change. A “Stepwise” approach to building a robust, serious, professional Climate Model. If you are building a pregnancy test model, you don’t include men, pre-pubescent children, post-menopause women, sterile, and other populations because they make the results nonsensical. The data sets chosen have to be relevant to the questions being asked. Imagine how idiotic the results would be if we included men in pregnancy tests? That is what an aggregate climate model is. AN idiotic construction of dissimilar data sets all put in a blender. Their results are nonsensical and effectively meaningless.
How then would a professional modeler create a climate model?
1) Start with a data set that has as few exogenous and/or variables as possible.
2) Antarctica and cold and dry deserts are ideal for controlling for the Urban Heat Island Effect and Water Vapor. The only real variables are CO2, Clouds, air currents and Sun.
3) Run a regression of temperatures and CO2 using the data from Antarctica or a composite of desert locations. https://imgur.com/a/mHIjixS#BLncbpV
4) The Error you get is due to Clouds, Sun, and air currents, and the coefficient on CO2 is the relationship and CO2 and Temperature. Most likely, you will get a 0.00 on CO2, even when CO2 increases by 25%.
5) Take the error of the regression, and use that at the data for normal variation or temperature due to exogenous factors.
6) The next model would use the data set right above Antarctica. That data set is close to Antarctica, but has more exposure to the oceans.
7) Run a regression using the Antarctica Error, CO2, and Temperature. The error you get from this model is the variability due to adding the effect of oceans to the data set.
8) The next model uses the data set next higher up on the latitude that would include Land.
9) Run a regression using CO2, the Antarctica Error, the Ocean surrounding Antarctica error against temperature. The error you get is due the impact of adding land. (Yes, I know if isn’t perfect, but it is infinitely better than the nonsense being created today) The current models are a joke.
http://www.drroyspencer.com/wp-content/uploads/68-models-vs-obs-1979-2021-oceans-Fig01.jpg
By using a stepwise approach of using similar data sets, and using the error to explain the exogenous variable, and using that exogenous variable as an indigenous variable in the new model, climate modelers would be able to slowly build more accurate climate models. Because each region of the globe has different indigenous variables, an aggregate model is a 100% complete joke.
Climate models should be done by regions to isolate the impact of the known indigenous variables on temperature.
Publishing trends on data sets that don’t have linear trends is pure nonsense. ANOVA Table statistics should be published. That would give you model R^2, variable coefficients, and the significance of those variables. That is how a professional model is built. Show me any real field of science that doesn’t produce ANOVA Tables? Linear trends are nonsensical when applied to temperatures. They literally tell you nothing about what is causing the warming.
Here is a climate model based on the physics of earths atmosphere and oceans:
Average surface temperature of Earth = {30+(-2)}/2
Works reliably until there is no sea ice at either pole in any year and the tropical Atlantic fails to reach 30C annually.
The first sign of next glaciation will be when the tropical Atlantic does not reach 30C in any year.
There is a 30-year history of solar spectral irradiance measurements taken in low earth orbit, and they claim to have reduced the uncertainty to 0.2%. This seems optimistic given that similar measurements on the ground have uncertainties of a few percent, and these numbers increase outside of the visible.The problems with older LEO measurements has been limited wavelength ranges of different instruments, and regions where the data have been slightly low.
Also, the solar spectral irradiance is extremely stable outside of the UV, where it varies with solar activity. I don’t see how these data will have any effect at all on climate models, except that perhaps they are graduating from a two-wavelength (short and long) representation of the air mass zero SSI to something with more detail, but this could have been done years ago.
Yes, from what I have been told, it is difficult to get very high precision optical measurements even in a laboratory setting.
I don’t know how the orbital instruments are calibrated, but terrestrial spectroradiometers are calibrated against NIST standard lamps, and these are the largest source of uncertainty. The NIST lamps are incandescent, and the output level is falling off rapidly at wavelengths less than 500 nm.
Isn’t this just a long way of saying “We are calculating Bond Albedo”?
Presumably to four decimal places as it is already quoted to three….
Bond albedo is inappropriate for all but diffuse reflectors. Water is highly specular, and almost everything else such as tree leaves have a specular component. Clouds are diffuse reflectors. However, even sand and regolith exhibit specular characteristics at near glancing angles.
https://wattsupwiththat.com/2016/09/12/why-albedo-is-the-wrong-measure-of-reflectivity-for-modeling-climate/
Bond Albedo is NOT inappropriate, Clyde, any more than the often stated “15C is the average temperature of the planet” is inappropriate. Bond Albedo is intended to be a large area average reflectance of incoming solar wavelengths, specular or not. It is useful in many explanatory calculations, and like any wide area approximation, has local irregularities, same as you cover your plants some nights in May because it’s not 15 C outside.
I guess you didn’t bother to read the link I provided. Albedo was originally developed as an assessment of the relative brightness of celestial bodies such as planets and asteroids in visible light. They only have regolith (some have ice); they have no water or other smooth surfaces that can specularly reflect. Thus, the relative brightness only provides information on the retro-reflectance, which is a lower-bound of the total reflectance.
We can now measure the reflectance in all wavelengths. However, only nadir views of the reflecting material are truly characteristic of the material. The larger the angle of incidence, the higher the reflectance (even for diffuse reflectors such as regolith), and at 100% reflectance (glancing illumination) the reflected light has a spectrum identical to the illuminating source. Albedo, Bond or otherwise, does not catch any of those subtleties!
I guess that should answer a lot of the question you bring up in your article.
Btw.. why focus so much on reflectivity when emissivity (or lw-reflectivity respectively) might be so much more important?
The amount of radiant energy that arrives on the surface, and is absorbed, is responsible for the first-order heating. The equations that calculate the absorbed energy use a parameter (inappropriately) called albedo, which apparently is an approximation often given to only 1 significant figure (0.3), while the other parameters are given to several significant figures. I have made the case that the 0.3 value is a lower-bound of the total reflectivity and the specular reflection at angles of incidence greater than about 60 degrees is (like with clouds) largely wavelength independent, whereas, the light reflected off water, vegetation, and rocks ( at smaller angles) is highly dependent on wavelength. It is that first-order estimate of heating that determines where the peak emission will be and what the amplitude will be. From that, we know what wavelength to use for defining the emissivity. While we can measure the wavelength range of the current thermal emission, the models need to be able to calculate the theoretical values, which requires a good estimate of the energy absorbed.
You seem to ignore the merrit of the chart above.
“I have subsequently calculated the area under the curve, and I find it to be about 12.2% for the range of 0 degrees angle-of-incidence to 90 degrees. I also calculated the instantaneous reflectance for the ideal Waterworld hemisphere, and I find it to be about 17.6%. The reason that the numbers are not the same is because a spot near the Equator has a lower reflectance at noon (0°) than a spot at higher latitudes, which only sees a minimum reflectance appropriate for an angle of incidence equal to the latitude.”
The “area under the curve” is not the way to solve the question. You need to use sin^2 as a density function for the geometric weightening. The high reflectance towards the terminator will be offset by a declining share of sun light hitting these regions. If you do all that correctly and even include the wavelength dependent alterations of refractive index and extinction coefficient (though negligible in SW range), you get the results shown above. If then you weight these according to the planck’s curve, total reflectivity of an ideal “Waterworld” is 6.3%.
That is why “Indeed, a value of 6% for open ocean seems to be totally inappropriate” is not a true statement. Rather 6% is surprisingly accurate, although I doubt it is for the right reasons.
I think that you are making the same mistake that Klipstein did. Reflectance is defined as the ratio of the reflected intensity to incident intensity. The intensity of the incident light is reduced with large angles of incidence because a bundle of rays is spread over a larger area than for normal incidence. To calculate the reflected flux in energy per unit area, then both the increased footprint of a bundle of rays, and the longer slant-range, causing more scattering and absorption, have to be taken into account. However, I’m looking at just the one parameter, reflectivity.
This seems like a remarkably basic principle and metric. Understandably a newish sensor can expand our knowledge, but each time one does you’d think it would expand our knowledge of our ignorance. How many other places do we not even know the right questions to ask or what to measure, let alone know what to look for and can build a system to measure it?
And yet they blithely calculate how uncertain, or usually not uncertain, they are about where we’ll be in 80 years, even while you have people like Schmidt saying gee “it turns out” white is actually black.
It’s like embarking on a circumnavigation of the globe with a bunch of kindergarteners at the helm arguing over what their finger-painted map means. Which wouldn’t be so bad if the little brats wouldn’t keep telling everyone else to sit down and shut up every time they run aground.
Why do so few inferior brains lack the humility of Feynman’s superior one?
“there are still more steps to take before scientists can use it to predict future climate change”
While happy to learn that both Georges Bush were correct and more research is needed, and that Barack Obama is still wrong about the end of science, how can an accredited scientist of any nationality claim that they can become a seer? Hasn’t modern science been adamant about discrediting the likes of Nostradamus?
I somehow do not take comfort from this announcement from my government, coming as it does quoting Gavin Schmidt and three apparent foreign nationals in U.S. employ. If Trump was also correct, as were both Bushes, I’m expecting a sucker punch.
Correcting models should be a good thing. Admitting the possibility of a past mistake would have been nice. Chewey, I’ve got a bad feeling about this.
I knew it this would happen! Not only does heat cause cold, but black is white.
And Gavin is wrong. See my remark at May 15, 2021 8:51 am.
Gavin is off base. It may not be as reflective in the IR as in the visible region, but it isn’t “black,” according to the USGS Professional Paper 1386-A: Near-IR is about 20% for glacial ice and about 90-95% for snow. There isn’t significant reduction until the SW-IR region is reached.
Radiation that is NOT reflected is absorbed and reradiated according to SB at its radiative temperature. This re-emission is often confused by the uninformed with reflection, even sometimes by those reading instruments for their Ph.D thesis….
Almost, but no cigar! Light that is not reflected is transmitted into the reflector, where it may be partially or completely absorbed, depending on the extinction coefficient, the thickness, and the abundance of included absorbers.
You are correct that if it is absorbed, it will increase the temperature and re-radiate according to SB. However, in the context of what Gavin said, your remarks are a non sequitur.
I think that you are out of your element here.
We are talking about SNOW here, not some hazy gas with an extinction coefficient. And I am agreeing with you that Gavin is off base. So why disparage me…bad day ? Maybe you don’t like anyone pointing out your ocean reflectance article is wrong. (9:18 AM) See my response to E. Schaffer at 4:08 PM…
I’m not talking about gasses. All substances have a refractive index that is a complex number where the imaginary part is commonly called the extinction coefficient. For most materials that are considered to be transparent, the imaginary part is negligible and often ignored. But, even a small extinction coefficient becomes important when dealing with thick materials.
In your response to Shaffer, your points about confounding conditions are basically correct. However, the apparent roughness decreases as the angle of incidence increases, the wavelength impacts decrease with increasing angle of incidence, and the importance of suspended particles decrease as less light is refracted into the water. These effects are all substantiated by the graph you supplied that shows that all the lines of ‘t-sub d’ converge at about 60 deg zenith angle. That means that a simple Bond albedo misses the geometric effects as sunlight approaches the terminator.
You are claiming that my ocean reflectance article is wrong. However, you haven’t provided evidence to support your claim.
“The first step to learning is to admit you’re ignorant.” – unknown
The problem with this is that they are measuring the Top of Atmosphere radiation. That is important for a good estimate of the radiation that is absorbed and scattered in the atmosphere. However, they were modeling the interaction at the poles, meaning that they needed accurate measurements of what was passing through the atmosphere and arriving at the surface. Since the solar radiation has a long slant range through the atmosphere at the poles (indeed, also at the terminator) compared to the Equator, ground measurements are most important for modeling the interaction at the surface.
It seems that the quality of science is declining at the same time that technology is providing better tools.
It is not quite ready yet, but I am going to provide the complete solution to “climate science” here. I guess for most it will be interesting to learn how the GHE is a hoax after all, if I put it simple. I have already put plenty of disruptive insights up..
https://www.greenhousedefect.com/what-is-the-surface-emissivity-of-earth
Your reflectance graph is only applicable to still water surfaces. Add real waves, real light wavelengths, real water clarity and purity, real algae and dust….and then you need to work out transmittance, and you end up with a lot different numbers than just assuming the horizon is a mirror….
Do you know what the chart is meant to show?
Schaffer
Congratulations! You are one of the few that has a good handle on the issue of the reflectivity as it varies with angle of incidence.
A couple of Rules of Thumb: Substances that are considered opaque have non-negligible extinction coefficients, and there is about a 90% correlation between the extinction coefficient and the reflectivity. Therefore, when small, it can be ignored. When greater than about 0.1, it is important.
Excel allows the use of complex arithmetic to solve Fresnel’s equation for reflectivity. Otherwise, you might have to use the sine and cosine transform to do the complex arithmetic calculations. It is no small task to include the extinction coefficient in the calculations.
Here is something to ponder, which I don’t know the answer to off the top of my head. If the extinction coefficient for the complex refractive index is non-negligible, will it require a complex number to express the emissivity of the material as well? If so, what does a complex emissivity mean?
I suspect that the reflectivity peaks in the IR for snow may be a result of a significant extinction coefficient, but I’m not sure.
I attempted to leave the above message at your website, but it was rejected because it supposedly contained a “bad word.”
Really.. I do not know. My basic knowledge on complex numbers tells me calculations will give you results for the real AND the imaginary part. But obviously there is just ONE result for the fresnel functions including complex numbers. Then these calculations are all done with according software. It is like using a hand calculator and trusting the outcome.
So really I just take the results from refractiveindex.info (to save some hard work), check them against other sources and find they are obiously consistent.
Despite some content, my site is still work in progress. That is also true for the content. Big things coming 😉
In thinking more about this, the calculation of the reflectance provides a real number representing the intensity of the reflected light. Kirchoff’s Law then can be used as usual by subtracting a real number from a real number to obtain the emissivity.
The only time a devil tells the truth…
Either it’s when you won’t believe the devil or when the devil purposely misphrase what appears to be truth to cause misunderstanding and misdirection.
Though, it is nice that NOAA finally recognizes that water is interactive across the light spectrum. Unlike the infinitesimal infrared interactivity of CO₂.
Except, NOAA apparently refuses to believe light reflects off smooth angled surfaces.
Glass is transparent across much of the light spectrum, yet that light can still be reflected if it hits a polished glass surface at the right angles.
Now, if Schmidt admits that water vapor’s evaporation, condensation and solid states drive what they call the Greenhouse effects and moves heat through the atmosphere to eventually radiate into space.
Nah. Schmidt is just trying to establish a small bit of credibility for their ‘new’ climate model algorithms.
”Glass is transparent across much of the light spectrum, yet that light can still be reflected if it hits a polished glass surface at the right angles.’‘
Absolutely correct. When I designed the slope of my glasshouse roof to as close as possible to 90 degrees to the winter sun, I did it for a good reason.
”Nah. Schmidt is just trying to establish a small bit of credibility for their ‘new’ climate model algorithms.”
I would not be at all surprised!
An interesting fact is for infrared detectors, if a pain of glass is very close to the camera, it can be seen through, but it turns opaque if it is viewed about 4 feet away. Of course this probably does not bear on the conversation at hand.
Why does any of this matter! There is a global emergency. Glasgow 2021 is the absolute last chance to resolve the climate emergency. Nothing that happens in Glasgow will change China and India’s trajectory on CO2 emissions. So why bother with the ever-nuanced nonsense on the “delicate” energy balance.
The easy way to fix weather models so they become useful climate models is to use the physics of cloud formation and dissipation rather than parametrising clouds.
Here is another glaring failure of the CSIRO ACCESS climate mode:
https://1drv.ms/u/s!Aq1iAj8Yo7jNhD5U4NzaR6juhSXu
Just a 3K error. Well it highlights the inability of models to predict or even get the present right. Persian Gulf is a unique body of water that does not regulate to 30C maximum like the rest of the oceans. If clouds were based on physics rather than parameters, the model would have a better chance of getting the Persian Gulf right.
So..SSI is measured from the ISS using the SIM on the ISS’s TSIS-1. Got it… 🙂
And there nothing new about any of these measurements.
“there are still more steps to take before scientists can use it to predict future climate change, the authors warned.”
But future climate change has already been predicted. The science is settled. We’re doomed.
”But future climate change has already been predicted.”
Yeah but they predicted that using different input parameters. Oh yes they were also right, but now they can be even righter. There are no mistakes in climate modeling apparently.
What I can’t understand is, how can Schmidt start nitpicking over small and less important climate variables, as he seemingly ignores the huge variables? Everything that happens at the poles is tiny relative to the tropics wrt sunlight and energy received, because even when the light is shining, the angle of incidence is low, and even more so when averaged over a full year, BECAUSE much of the area is completely dark for a huge chunk of the year.
Who cares (really, who cares?) about how much near infrared light is absorbed by polar ice? What about tropical thunderstorms? What about their albedo effects in the visible spectrum? Won’t these dwarf anything measured at the poles, when averaged year-round? Of course, I’m a fed-up taxpayer on a rant. I say the GISS should be shut down and it’s remote sensing data gathering should be turned over to NOAA and NCAR, and their climate models retired, and GISS database binned, and Schmidt given his walking papers. Oh how I wish Trump and the Republicans would have shrunk the size of the federal bureaucracy in that one small way. But the cowards wouldn’t do it.
So Gavin still operates like a true bureaucrat, pretending the CO2 cycle dominates over the water cycle in the Earth’s climate, and that the poles might be dominating over the tropics. After all, if he can make a hockey stick there, he can make a hockey stick anywhere, (sung to the tune of New York, New York).
Here is something that I have not seen. Do a model of the earth with both poles having a thin layer of carbon soot placed on them like the “Climate Scientists” wanted to do in the 1970’s to reduce the chance that we would go into global cooling. Then try to convince idiots that what they are planning by putting light reflecting particles in our atmosphere will cause the opposite crises.
Zianglei Huang, Dong Wu, Xianwen Jing
China -> University of Michigan-> NASA