Guest Post by Willis Eschenbach
The CERES dataset is satellite data that is based on radiation measurements made from low earth orbit. The CERES data has two parts. The first part is observational data, measurements of downwelling and upwelling solar radiation and of upwelling longwave radiation. It is usually referred as the CERES “top-of-atmosphere” data. The official name is “CERES EBAF-TOA”, and it is available here.
However, the second part of the CERES is not top-of-atmosphere observations from the satellite. Instead, it is calculated surface data based on the CERES TOA observations along with other satellite observations. It’s called the “CERES EBAF-Surface” dataset, and is available from the same location.
As a result, I’ve always been concerned about the accuracy of the CERES surface data. After all, it’s just calculations, it’s not actual observations. So I got to thinking that I could “ground-truth” the CERES surface observations by using the TAO buoy data. It’s not a comprehensive test by any means, but the TAO buoys cover a region of great interest to me, the tropical Pacific. The TAO buoy data is available here.
I started out by seeing how well the CERES surface longwave radiation data agreed with the TAO sea surface temperature (SST) data. Now, the CERES dataset doesn’t have SST data, but we can convert the CERES surface radiation data into temperature by using the Stefan-Boltzmann relationship. First I looked at a string of TAO buoys that run along the Equator. I used the location of each TAO buoy, and compared it with the CERES surface calculated result for that location. Figure 1 shows that comparison for the eight TAO buoys along the Equator which have SST data.
Figure 1. Sea surface temperatures (SST) from the TAO buoys (red) and from the CERES surface data calculations (blue).
I was pleasantly surprised by this result. The greatest bias is ± two tenths of a degree, and the correlation is very high, 0.97 to 0.99.
Having looked at an east-west line of buoys, I then looked at a north-south line of buoys. These are all at 165°E, in the warmest area in the Pacific.
Figure 2. Sea surface temperatures (SST) from the TAO buoys (red) and from the CERES surface data calculations (blue).
Again the correlations are good, although there is one of the seven down at a correlation of 0.92. And the bias is slightly larger, -0.3 to -0.4°C. In this region all of the CERES data is slightly below the TAO buoy data.
Overall, however, if the bias errors are only on the order of a few tenths of a degree and the correlation is on the order of 0.97 or better, I’m more than happy to say that the sea surface temperature is extremely well represented by the CERES surface calculations.
However, that’s the easiest of the variables. Next I looked at something much harder to estimate—the available solar radiation at the surface after atmospheric reflection, absorption, and scattering. Figure 3 shows the available solar measurements from buoys along the Equator.
Figure 3. Available surface downwelling solar after atmospheric reflection, absorption, and scattering from the TAO buoys (red) and from the CERES surface data calculations (blue).
This one surprised me quite a bit. I wouldn’t have guessed that the satellite calculations would come this close. Not only do they get the annual cycles right, but they also get the occasional departures from the annual cycles. Yes, the correlation of some of them is lower, but they still do a good job. And the bias in all cases is less than 2%, a respectable showing.
I then looked at the same group of north-south buoys I’d used above. Here are those results.
Figure 4. Available surface downwelling solar after atmospheric reflection, absorption, and scattering from the TAO buoys (red) and from the CERES surface data calculations (blue).
Again, a very good showing, with correlations from 0.87 to 0.97, and bias of less than 2%.
There is one more overlapping dataset between CERES and TAO, that of downwelling longwave radiation (DLR). Unfortunately, there are only five TAO buoys with DLR data, and one record is very short … but we use what we have. Here is that group of buoys.
Figure 5. Downwelling longwave radiation (DLR) from the TAO buoys (red) and from the CERES surface data calculations (blue).
Of all of the results, I was most surprised by this one. I would say that this one would be the hardest to calculate from the satellite data. But despite that, if we set aside the very short (5-month) dataset in the first panel of Figure 5, the other four have good correlations (0.82 to 0.97), and the three longer datasets (panels 2, 3, and 4) have a bias of well under 1%.
Conclusions? Well, as I said, this is far from a comprehensive test … but I am greatly encouraged nonetheless. The CERES surface dataset, despite being calculated rather than observed, is a very good match to the TAO buoy data in all available respects. Makes me feel much better about using it.
My regards to you all,
w.
PS-If you disagree with someone please have the courtesy to quote the exact words you disagree with. This lets all of us understand the exact nature of what you think is incorrect.
Looks convincing to a lay-person like me too. Nice work. So now its time (for you) to start using it I guess. I look forward to some useful solar energy balance facts in the (near?) future. Thanks Willis
Not bad.
But their data is for near-equatorial conditions.
I have not found any Sereze-approved calc’s for the far north (or far south areas past 55 north or south) accurate against actual ocean albedo’s, sea ice albedo’s, air masses, attenuation factors, incident angles, or solar elevation angles.
but, neat the equator? Looks like they are right.
Good.
That was my first thought – but surely the additional calculation is just Euclidian geometry, which isn’t hard to do.
The poles themselves aren’t calculated are they?
I’m a bit surprised to find that measured SS W/m^2; solar is not around 1 kW/m^2 which is what all earth bound solar panel designs are based on (measured normal to the sun vector).
So what gives Willis, that you only find 240 W/m^2; and that is supposed to be a measured number; not a calculated number.
I’m puzzled. I assume that the solar flux measurements includes at least the 0.25 to 4.0 micron wavelengths.
g
george e. smith (asking willis e)
Willis is playing the “total radiation over 24 hours”/24 hour (at 3600 second/hr) game. It doesn’t really work that way. For example, during the daylight hours, the world at sea level near the tropics received 1000 watt/sec (as you indicate) for a period of 6 hours. Then the rest of the systems (evaporation, LW radiation loss and gain, convection to the atmosphere, etc) spend the next 18 hours losing that 6 hours of heat, plus the original 6 hours when both heat gain and heat loss are going on at the same time.
george e. smith February 24, 2015 at 3:47 pm
What I’m showing is the average solar over the month, not the instantaneous solar at high noon.
RACookPE1978 February 24, 2015 at 7:03 pm
Oh, piss off. I don’t play games. I give the results as best I understand them. I’ve given a comparison of the monthly averages from CERES and the monthly averages of the TAO data. If you wish to make some other comparison, that’s your business. But it doesn’t give you leave to falsely accuse me of playing games.
In any case, RA, if you don’t like monthly averages, how do you propose that we compare the TAO data and the CERES data?
Regards to all,
w.
Willis Eschenbach (in reply to RACookPE1978 February 24, 2015 at 7:03 pm )
Submitted on 2015/02/25 at 1:19 am | In reply to george e. smith (original)
Ah, but I regret you misunderstand my use of “games” there; the world is but a stage, is it not? And we but simple players upon its fractally infinite beach toying with pretty pebbles – just to mix a few inappropriate quotes there.
More seriously, listen to what Dr Roy Spencer wrote in Climate Confusion (hardback version, pg 65-66) about these satellite measured differences.
RACookPE1978 February 26, 2015 at 8:43 am
RA, you say you weren’t accusing me of “playing games”, you were simply misquoting poetry?
Well, OK … but your intention was far from clear. Let me suggest that in future you purge “playing games” from your list of playful allegorical accusations.
Thanks, RA. I agree completely with Dr. Roy.
w.
PS— I note that in your reply you didn’t answer my scientific question, so let me ask it again …
“The CERES dataset is satellite data that is based on radiation measurements made from low earth orbit.”
The Ceres data is known to suffer from calibration problems.
Some comments appear in Loeb et al. Toward Optimal Closure of the Earth’s Top-of-Atmosphere Radiation Budget. J.of Climate, AMS, V.22, p.748.)
URL: http://www.nsstc.uah.edu/~naeger/references/journals/Sundar_Journal_Papers/2008_JC_Loeb.pdf
In 2012 an update was published in Nature Geoscience on the subject of uncertainties in the observations of solar and terrestrial energy flows (radiative flux). The authors stated:
“The net energy balance is the sum of individual fluxes. The current uncertainty in this net surface energy balance is large, and amounts to approximately 17 Wm–2. This uncertainty is an order of magnitude larger than the changes to the net surface fluxes associated with increasing greenhouse gases in the atmosphere (Fig. 2b). The uncertainty is also approximately an order of magnitude larger than the current estimates of the net surface energy imbalance of 0.6 ±0.4 Wm–2 inferred from the rise in OHC. The uncertainty in the TOA net energy fluxes, although smaller, is also much larger than the imbalance inferred from OHC.”
Regarding the estimate of ocean heat content, they stated,
“For the decade considered, the average imbalance is 0.6 = 340.2 – 239.7 – 99.9 Wm-2 when these TOA fluxes are constrained to the best estimate ocean heat content (OHC) observations since 2005 (refs). This small imbalance is over two orders of magnitude smaller than the individual components that define it and smaller than the error of each individual flux. The combined uncertainty on the net TOA flux determined from CERES is ±4 Wm-2 (95% confidence) due largely to instrument calibration errors (refs). Thus the sum of current satellite-derived fluxes cannot determine the net TOA radiation imbalance with the accuracy needed to track such small imbalances associated with forced climate change.”
Graeme L. Stephens et al, An update on Earth’s energy balance in light of the latest global observations. Nature Geoscience Vol. 5 October 2012
URL: http://www.aos.wisc.edu/~tristan/publications/2012_EBupdate_stephens_ngeo1580.pdf
The estimate of 0.6 Wm-2 was updated by Loeb and others in 2012 to 0.5 Wm-2.
Reference: Norman G. Loeb, John M. Lyman, Gregory C. Johnson, Richard P. Allan, David R. Doelling,Takmeng Wong, Brian J. Soden and Graeme L. Stephens. Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty. (Nature Geoscience Vol 5 February 2012)
URL: http://www.met.reading.ac.uk/~sgs02rpa/PAPERS/Loeb12NG.pdf
My detailed comments here:
https://geoscienceenvironment.wordpress.com/2014/09/04/the-emperors-of-climate-alarmism-wear-no-clothes/
Given the calibration errors are so large, what is the explanation for the close correlation between TAO and CERES? Could CERES have been actively calibrated against TAO, or a closely related data set?
Neither of the two satellite metrics calibrate against surface data. It’s straight MW conversion. A few years back, Dr. Christy was very vehement on that, and I trust him implicitly in this.
That energy varies with the 4th power of temperature,
E = σT^4,
is another way of stating that temperature varies with the fourth root of energy,
T = (E^¼)/σ,
a very small number when compared with the CERES noise, as you have pointed out.
T = (E^¼)/σ, that is.
Oh, no, its
T = (E/σ)^¼
Well, you get the drift, equations have the same degree, off by a constant.
Surely this isn’t the first time that Ceres data has been ‘ground-truthed’ ?
Thanks, Katio. It’s the first time I’ve done it, and I did it to see what’s what vis-a-vis the TAO data.
w.
Two comments, Willis:
First, please can you consider Eric Worrall’s question carefully? It is one that would not have occurred to me.
Second, do you think that CO2 is supposed to increase downwelling LW over time and do you think the CERES graphs refute that?
Thanks – nice article.
Rich.
“Now, the CERES dataset doesn’t have SST data, but we can convert the CERES surface radiation data into temperature by using the Stefan-Boltzmann relationship.”
How do you convert the radiation data into tempature in detail? Most of the IR thermal radiation of the oceans is absorbed by the atmosphere. It is true that there are some atmospheric windows in the IR, which you can use to reconstruct the Stefan-Boltzmann spectrum emitted by the surface. But you have to assume that the albedo is constant for these windows. It would be nice if satellites could measure the surface temperature directly, for instance by inelastic light scattering (Brillouin, Raman scattering). But unfortunately these techniques can only be used in the lab.
It can be measured directly. They just don’t know how because they are so focused on the details . Can’t see the forest for the trees.
Thanks, Paul. I converted using the standard S-B relationship, which is that
Radiation = S-B_constant * emissivity * temperature^4
For the surface radiation I used the CERES calculated upwelling surface radiation, the EBAF-SURFACE dataset called “surf_lw_up_all”.
w.
Well this of course takes as gospel the assumption that the ocean surfaces are indeed black body radiators, which one might conjecture should be true for the 5.0 – 80 micron wavelengths characteristic of a 288k BB radiator.
Of course Konrad insists that the ocean is anything but a BB emitter.
Well that’s his opinion. I’ve never measured it, but would assume its a fairly good BB at its surface Temperature.
G
I’m always embarrassed to admit my ignorance, which is profound in many areas. Nevertheless, rather than persist in my ignorance, I’ll ask for help.
Google tells me TAO stands for Tropical Atmosphere ocean, so I’m further advanced than I was before. But what does the term ‘bias’ mean when you are using it in these graphs?
The word “bias” has many meanings in the dictionary, most of them related to conveying a judgment. When applied to human judgment it implies the existence of prejudice or subjectivity, usually in a derogatory sense.
But “bias” is also used mathematically, to describe the output of statistical estimators, and simply means that on average the consistently misses the ‘ground truth’ value by a constant offset, i.e. it consistently overestimates or underestimates. In this sense it usually carries no judgmental stigma, as in the human-judgment sense of the word. It is a simply a way to measure the reliability and usefulness of a statistical estimator.
When the measured bias of an estimator equals zero, we say the estimator is “unbiased”.
Be careful not to confuse “bias” with “variance”, which is a random offset observed in virtually all estimators, which is distinct from “bias” because in the long run it averages out to zero. Bias and variance of components of the total squared error: SE=bias^2 + variance
Thanks, Johanus. Your comments from the second paragraph forward are of course what I was looking for.
Yet even with your help, there’s much I don’t understand.
Sure, Willis could fairly say ‘he’s using the term in a perfectly ordinary statistical sense’, and I have no doubt that’s exactly what he’s doing. Still, he is writing for a lay audience. That’s me and people with even less stats education than me, so I don’t think I’m unreasonable to continue to pursue the matter.
Are the graphs simply reporting the difference between the calculated values for the Pacific and the measured values from the TAO buoys, and calling the difference ‘bias’? [Whether that is or isn’t it, what do both systems do about ‘time of measurement’? That would surely create differences much greater than the fractional degree Willis is reporting.]
If my inference above is wrong, then I need lots more explanatory help. In this particular example, what thing is the statistical estimator? If the measurements of the TAO are not the ‘Ground Truth’, then how do we know what the Ground Truth is? Why would there be a bias rather than variance?
I’ve now read the Wikipedia article on Bias (Statistics), and it lists 12 Categories of Bias excluding sub-categories. What type is this and how do we know? And how do we calculate its value?
My ‘take home’ message from Willis’s article is that the temperature figures of TAO and CERES EBAF – Surface are very similar. That’s good to know. The calculated result is biased in some fashion. Which set of figures is biased, or is he simply using the term to refer to the amount of difference between the two sets? When I go to explain his work to others, what exactly do I tell them? Don’t worry about insulting my intelligence, just give clear explanations.
johanus,
Excellent explanation for bias.
This is a good summation of weather model bias’s in the world of meteorology:
http://www.hpc.ncep.noaa.gov/mdlbias/biastext.shtml
Taking a set of model outputs projecting the temperature for the past fifteen years or so, and comparing them to the measurements on the ground, what sort of ‘bias’ number is seen?
Based on the explanation above, it must be a pretty big number. Any model run will have bias and variance too. To me, the models look biased towards heating. When evaluated as ‘worthy or not’ models using ordinary criteria, how do they stand up?
The calculated Ceres numbers are the output of a set of calculations that are a ‘model’ too. With a bias of one or two per cent the Ceres model looks good. It seems to me the bias of the GCMs is, on average, far, far larger.
Is TAO a typo for TOA or another entity entirely?
TAO and TOA were both correctly used in the article. The latter is Top of Atmosphere the former is Tropical Atmosphere Ocean program which posted a series of buoys across the tropical Pacific.
I have yet to see data about the increasing LWIR, being a sign of increased “GH effect”. It is an unquestioned assumption all models work with, but has it ever been really observed? There was a study of LWIR observations at clear sky conditions somewhere from US Midwest, which shown even decrease of LWIR.
Can one distinguish between upward IR coming from within the atmosphere and upward IR emanating from the surface ?
Stephen 4:52am: Yes. Dr. Spencer has explained how at his site. If I recall correctly, they use the atm. O2 signature calibrated to radiosonde. This top post should be useful for you to start to add intuitive radiative energy transfer lacking in your limited intuitive KE+PE transfer to reach better meteorological conclusions especially at the surface.
Dr Spencer’s method is not the be all and end all method for measuring temperature. There are other ways, even using the data from ‘his’ satellites. I’m not taking anything away from his work. It is quite complicated.
His focus is on temperatures up and down the atmosphere. His work is not focused on near to earth stuff.
Just everything from the ground to the satellite. You can probably calculate the reading cone from the NASA website for individual readings.
My reason for asking is that I’m sure that if radiation to space from within an atmosphere changes then radiation from the surface to space varies in an equal but opposite direction.
The regulating mechanism is then variations in the amount of potential energy returning as heat to the surface in adiabatic descent.
The more radiation to space there is from within an atmosphere the less energy as heat that can be returned to the surface in adiabatic descent and the less the surface can radiate to space and vice versa.
It is a neat self adjusting process but unless we can distinguish the two separate sources for outgoing IR we cannot check it out.
Stephen
I know your ‘bag’ is adiabatic stuff. I don’t disagree with it. I just know the principle of spectrometers and that kind of instrumentation. Dr Spencer’s stuff seems to be in regard to upper troposphere and all the various levels of the atmosphere. I suggest you look at the raw data at his work site and kinda do calculations from that.
Dr Spencer deals with multiple levels within the atmosphere but doesn’t seem able to sum up everything from within the atmosphere and then distinguish it from that which comes from the solid surface.
Stephen
That is the problem and I agree with you. There are other ways to look at things but people just do their job and don’t go there. Such is life. Look at his data , the actual satellite stuff raw. Pain in the arse for me too. I have to work out the software and data to do my own thing.
Can that be right, the buoys around the equator are 15 degrees apart? That is 900 miles, and that is a proxy for water temps? Realistically that may be the way its done, it only tells me that satellites should be the gold standard for earth temps.
Well, if the Ceres measurements for the surface are that good, then one can proceed to checking what the entire land surface and ocean SSTs are really doing.
The TOA is not really important since we live at the surface. Ceres is just showing us that not much is really happening at the TOA (a few ups and downs but the imbalance/balance and individual components are not really changing. The Ceres 0.5-0.6 W/m2 energy imbalance is NOT really what the satellite is measuring. It IS what the Argo floats are measuring. They use Argo’s numbers as a proxy since Ceres’ components don’t add up. The imbalance is the OHC numbers from the Argo floats.
It is also very interesting that the Stefan-Boltzmann equation works so well here. I note that it works everywhere in the universe it is tried and if it works so well in this example, I think that gives one the go-ahead to convert Ceres radiation data to temperature and be confident about it.
Why would it be interesting that the Stefan-Boltzman equation works in this case? It would be more interesting if it didn’t.
I hate to pile in Bill Illis but even I (as hard-core a sceptic as you find) didn’t have reason to doubt the Stefan-Boltzmann equation.
What reason would you have for questioning its applicability? Was it the assumptions around what counts as a “black body”?
You seem to be sceptical about something I took as reasonable and that perturbs me.
The S-B “balance” assumptions include superconductivity, matte black emitter, zero specific heat, zero thickness, no changes of form or state (melting, evaporation), and no other sinks. Equilibrium is treated as instantaneous, radioactivity is ignored as an energy source. The planet is treated as an ideal point source. The indicator of heat used, temperature, is intensive and cannot be dealt with arithmetically (adding, averaging).
Treating the whole surface as an undifferentiated black body uses “averaging” to handwave such quibbles away. Enthalpy is just too hard to figger, don’cha know?
Brian H February 27, 2015 at 4:53 pm
And yet, the S-B equation gives an answer that has about a 95%+ correlation with the ground data from the TAO buoys … “too hard to figger”??? I’d say the scientists “figgered” it just about exactly.
I’m sorry, but your sarcasm and your faux folksiness don’t work when the equation does work, and works very well.
I’d advise you save your snark for an equation that doesn’t work …
w.
Willis!
Yet, putting aside the problems in his rejoinder, what is the actual S-B constants (and factors) for long wave heat loss from a horizontal flat “real surface” (a gray body) at sea level radiating “up” into the T_air?
If so, what is the correct correction for air temperature at 2 meters (T_air) at a given relative humidity?
Or is it radiation into a “T_sky at 15,000 meters (40,000 ft) at ???? cloud conditions?
Or is it the “total condition” of T_ground into T_Space? can’t be => Else the FL fruit growers would not spray water onto orange grows and use foggers to protect their trees on clear nights in sub-freezing weather!
I’ve worked outside on clear nights at 22 – 20 deg F. It’s d***ed cold! But “How cold is cold is it?” has never been clear. ANd the more “papers” and “pdf’s” I read, the less I am convinced the “clima-astrologists” know either. Other than, the classic T_ground and T_space = 0.0 K problem that the original S-B equations approximate.
Yes, Willis says the following (in the top post):
“Now, the CERES dataset doesn’t have SST data, but we can convert the CERES surface radiation data into temperature by using the Stefan-Boltzmann relationship.”
Fine, even though we know already that the ‘CERES surface radiation data’ is itself computed using inputs from other sources. These sources provide specific information on clouds, temperature and humidity in the air column above the surface. This information then goes into a radiative heat transfer model.
Pretty complex work in the end. But it all seems to function quite well. At least for the region checked here by Willis …
Here is NASA (by Seiji Kato) on the data and its origin:
“Surface irradiances included in this dataset are from the CERES Energy Balanced and Filled (EBAF)-Surface Ed2.8 data product (Kato et al. 2013). They are computed using MODIS-derived cloud properties (Minnis et al. 2011) and atmospheric properties (temperature and humidity profiles) given by the Goddard Earth Observing System (GEOS-4 and 5) Data Assimilation System reanalysis (Bloom et al. 2005; Rienecker et al. 2008). To account for the diurnal cycle of cloud properties between 60°N and 60°S latitude, cloud fraction and cloud top height derived from five geostationary satellites (Minnis et al. 1995) are also used. Geostationary satellites are calibrated against MODIS (Doelling et al. 2013). Other inputs for irradiance computations include ozone amount (Yang et al. 2000), ocean spectral surface albedo from Jin et al. (2004), and broadband land surface albedos that are inferred from the clear-sky CERES measurements (Rutan et al. 2009). Because computed TOA irradiances do not necessarily agree with CERES-derived TOA irradiances, computed TOA irradiances are adjusted to be consistent with CERES-derived TOA outgoing shortwave radiation (rsut, rsutcs for clear-sky) and outgoing longwave radiation (rlut, rlutcs for clear-sky) from EBAF-TOA Ed2.8 (Loeb et al. 2009; Loeb et al. 2012). TOA irradiance adjustments are made by adjusting inputs (surface, atmospheric, and cloud properties). In the adjustment process, CALIPSO, CloudSat, and AIRS observations are used to constrain cloud and atmospheric properties (Kato et al. 2013).”
http://ceres.larc.nasa.gov/documents/cmip5-data/Tech-Note_CERES-EBAF-Surface_L3B_Ed2-8.pdf
Willis
ALL satellite data is calculated and not observed. Why are you surprised? Because it is accurate and correlates with other readings? Those effing things are up there for a reason.
Alex, 97% correlation with any independent thing surprises me.
That’s seems to provide evidence that the two methods are referring to something independent of their own workings.
In short – it provides evidence that they reflect an independent reality.
In the land of complex climate science that is unusual.
MCourtney
You could be right. Perhaps there was ‘calibration’ that we aren ‘t aware of. I know from my experience in the engineering/scientific world that the correlation would not be unusual. Dealing with climate science? God knows. Maybe I’m just a dreamer with rose coloured glasses. Stop being horrible and leave me with my hallucinogenic dream.
Alex, I’d love to leave you in your hallucinogenic dream. But you said those satellites were up there for a reason… and then that some effective calibration may have happened without any acknowledgment.
Yet satellites are expensive. It wouldn’t be an accident that they are up there. That would mean forethought in dishonesty.
Nah.
These satellites were put in space to seek reality.
And I think they found it.
Alex February 22, 2015 at 6:16 am
Thanks, Alex. While you are correct, you are overlooking an important distinction. The CERES TOA radiation datasets are based on CERES satellite observations. The CERES Surface product is not. The surface product is a “constrained” product, meaning that it is the best estimate of a physical system given that the estimate has to satisfy a variety of constraints. These constraints are based mostly on the CERES TOA radiation datasets, along with other datasets.
This makes the CERES Surface radiation datasets a different kind of creature than the TOA datasets. Among other significant differences, the errors of the surface dataset come from a much wider variety of sources. This means that the errors in the surface dataset are going to be larger than those of the TOA dataset.
That’s why I was so interested in looking at how well the surface datasets match the TAO buoy data, so I could know how much trust to place in the surface results.
Regards,
w.
Looking particularly at 2010, equatorial 165e/170w. There is an inverse correlation between down welling (440 spike ) and available solar at the surface (150 valley).
What would cause this and why such a major extreme during that time period?
Mr. Eschenbach,
What albedo did you use for your S-B calculation? You really need a full spectral measurement of radiation from the surface to get a good measure of temperature. An albedo of 1 would give you the lowest possible temperature. Lower albedos would give higher surface temperatures.
Albedo is irrelevant if you know the peak wavelength of emission. Peak wavelength determiunes temperature and not intensity. I actually have no idea as to how Willis applied Sand B in this case.
Albedo can be a strong function of wavelength so the peak of the emission spectrum may not be at the peak of a Planckian (it usually is however). Regardless, the Stephan-Boltzmann relation is a power balance equation using a mean albedo while the Planckian spectrum has wavelength info. Which one is being used? The article said S-B. No wavelength info there.
rbspielman
I was only referring to albedo. Blackbody, greybody peak (wavelength) emission is the same, just a different intensity. If you are referring to ‘non gray bodies’ then I am out of here
So far as I know “albedo” is exclusively reserved for the reflectance of the incoming solar spectrum energy. If the spectrum is not solar it is NOT a component of albedo.
Useful solar spectrum is 0.25 to 4.0 microns containing 98% of the total solar energy.
At ocean surface Temperatures, the operational BB (Planckian) spectrum is 5.0 to 80 microns which is mutually exclusive with the albedo spectrum.
So surface emitted LWIR has no association with earth’s albedo.
g
Funded by a grant of the Government of New Zealand.
Ice in Antarctica already growing.
http://arctic.atmos.uiuc.edu/cryosphere/antarctic.sea.ice.interactive.html
But there is a sharp downturn this last week in the Arctic sea ice , according to the reference Sea-Ice page .
Almost looks as if maximum ice has been reached a month or 3 weeks ahead of “schedule”.
Could be. Note that short term changes in sea ice are driven more by winds and currents than by temperature, so not much can be inferred from them (except re winds and currents).
No, not really. The Arctic sea ice is just bouncing along right at the -2 std deviation curve like it has the past two years.
http://nsidc.org/data/seaice_index/images/daily_images/N_stddev_timeseries.png
The Arctic sea ice area, and sea ice extents will peak near the end of March, first week in April. Now, we are near the top of the total area curve – and, like all cyclical curves, the top represents a long “flattish” period of almost no net growth, but almost no net loss either. So we will not see any large increase in Arctic sea ice extents either.
But, do you see that the entire Arctic sea ice area (less the extreme south tip of Bering Sea and Hudson Bay is still in the “dark” right now? There is no sunlight energy up there yet!
But the frozen Great Lakes. It be added to the surface of the ice in the north. Over the Arctic we have dipole. But there is a lot of old ice and the volume grows.
http://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/data/
Making all that ice dumps lots of sensible heat into the atmosphere as the water changes state. Does it also spike OLR?
Ren:
The Great Lakes “sea ice” behaves much more like Antarctic sea ice (because the Great Lakes at 42, 43, 44, 45, 46 degrees) are at latitudes much more comparable in reflecting solar energy than the Arctic sea ice up between 81 north to 71 north latitudes. BUT! The Great Lakes are NOT included in the “Arctic sea ice” totals by any of the many different national labs that track sea ice. (Neither is the permanent Antarctic shelf ice grounded near the Antarctic continent. )
So, any increased ice on the Great Lakes or around Antarctica from normal levels DOES reflect significant amounts of solar energy from the planet, thus cooling the planet immediately. (The energy is reflected away in seconds, never available to be absorbed into the dark lake waters to slowly heat the region later.)
Decreased sea ice in the Arctic any months of the year from mid-August through mid-April COOLS the planet because the “missing” sea ice increases heat losses to space from increased conduction, LW radiation, evaporation, and convection. May-June-July? Different story obviously. Decreased Arctic sea ice in those three months does heat the Arctic Ocean because more solar energy is absorbed into the sea than is lost from the exposed ocean surface. But only during those three months.
Willis,
Are the DLR figures that the TAO buoys provide based on measuring incoming thermal infrared in the spectrum of (4 – 100 µm) or is it “calculated” using temperature and humidity?
After all, “DLR or back radiation from the atmosphere to earth is a fundamental pillar of CO2 alarmism.”
http://claesjohnson.blogspot.com/2011/08/who-invented-downwelling-longwave.html
From Poster:
The DLR is derived from several sensors (METEOSAT, MSG) using various approaches, in the framework of the projects.
From Geoland:
However Radiative Transfer Models (RTM) may be used to estimate DLR from atmospheric profiles (temperature and humidity).
Then there is this:
http://claesjohnson.blogspot.com/search/label/myth%20of%20backradiation
Most all ground-based measurements of that so-called “sky radiance” presumably welling down to the surface are done either by pyrgeometers or by spectroradiometers. The former don’t measure (as in ‘detect’) such radiation at all. They are so-called ‘thermal detectors’. They register only the ‘net’ radiative flux (that is, the radiative HEAT flux) at the sensor, expressed as a certain voltage signal (positive or negative, depending on what way the heat goes). Knowing, then, the sensor temperature as well, the instrument computes a hypothetical “sky radiance” flux for you, and you are free to believe that this calculated output constitutes a real, thermodynamically working flux (transfer) of energy down to the warm surface from the cold sky.
The latter instrument needs for its detector to be colder than the air layers above it for it to “experience” any incoming radiation from the sky at all. As in all such cases, you need a heat transfer to detect. It is ALWAYS the heat transfer that is actually detected. The cold detector of a passive spectroradiometer (like the AERI, for instance) is not the warm surface of the Earth. The surface of the Earth can never “experience” any incoming radiation from the sky like this detector does. Not until it becomes colder than the sky. Like the detector. These so-called ‘photonic’ (or ‘quantum’) detectors are held at cryogenic temperatures, normally around 77 K. At this temperature their ‘self-radiation’ would be so weak that they could safely be neglected facing any incoming EM wavetrain from even a pretty cold point or region in the sky. This point/region could therefore be regarded as a ‘pure emitter’ to the detector, meaning, there would be a practically pure radiative heat transfer from the sky to the detector. In the available spectral bands.
This can easily be shown through the Stefan-Boltzmann equation.
Let’s say a certain atmospheric layer whose thermal radiation is able to reach our instrument detector, holds a temperature of 250 K. That’s pretty cold. -23°C. If this layer faced a perfect vacuum at 0 K and could be approximated as a blackbody, it would emit a clean radiative heat flux to the vacuum at absolute zero like this:
q = σ * 250^4 = 221.5 W/m^2
If it were rather faced with our detector at 77 K, how much would this radiative heat flux (q) be reduced?
q = σ (250^4 – 77^4) = 219.5 W/m^2
By 0.9%. That’s not a lot.
In reality, each single layer of atmosphere could not function as a full blackbody radiator to the detector. Only certain wavelengths of radiation would be able to pass through the intervening layers, wavelengths that weren’t already ‘covered’ by those closer layers. The detector receives the total, cumulative radiance from all the layers above it, as far as it can see (normally a few kilometers up, or to some impenetrable cloud layer).
A quiet thread, a good thread to ask about actual longwave radiation losses from (real) surfaces into (real) atmospheres.
Yes. An isolated perfect gray body of emissivity “e” at a perfectly uniform temperature of T degrees K sitting in a perfect vacuum inside a black body of space at 0.0 deg K will emit from all surfaces
LW = S-B * e * (T^4)
But.
That is not where we are. There is a LOT of disagreement about “real” LW radiation losses – once you get away from a perfect gray body sitting in space. But I have not seen the actual calculations presented thoroughly, when they are presented at all. And none have used “measured” data of humidity, winds, and air temperatures – as if nothing existed between ground (or ice, or water) and the cold nothing of interstellar space.
Space is essentially “black”, at 3 deg K. That doesn’t change with weather.
The stratosphere? Not too much of a change: T_sky = -40 deg C almost all of the time at 15,000 meters (40,000 + feet ASL).
Mid-level and low-level air? Well, that IS weather. And it controls radiation loss, right? I’ve worked outside overnight in calm, clear cold nights: It’s bitter. Worked outside in foggy, humid nights with low cloud cover. But I don’t see the climate community organizers actually calculate the respective radiation losses. They “talk” about the two cases frequently, if not all the time. They just don’t calculate them. (They don’t calculate daylight LW radiation losses either.)
So, what is the actual LW radiation loss from a flat surface at sea level of T_surf, E_surf, into a real atmosphere of:
1. Hot weather, cloudy. Air temp = 35 deg C dry bulb, 30 deg C dew point (or wet bulb if you prefer), 1000 pressure, cloudy sky, winds = 3 m/sec?
2. Very cold weather, absolutely “clear”, low humidity. Air temp = -10 deg C dry bulb, 15% relative humidity. No clouds, 1020 pressure, winds = 0.25 meter/sec.
3. Cold weather, higher humidity, overcast with low clouds at 1500 meters. Air temp = 5 deg C, relative humidity = 60%, 980 barr pressure, winds = 2 m/sec?
RACookPE1978
All of your questions may be answered in an upcoming episode of WUWT. Stay tuned
If those questions are to be dealt with, the article should also deal with the fundamental point made by Kristian at February 22, 2015 at 10:29 am.
It could be a very interesting article.
Since detectors cannot routinely be chilled to a cryogenic low point, de facto the ambient temperature is the set point. If the pyro gains no heat, the sources around it and its target are at ambient. If it loses heat, it is emitting more than receiving, and the target is cooler, etc. Calculating that temperature would be a non-linear transform and conversion depending on ambient. “It’s all relative.” But AFAIK no such compensation is attempted.
I understand that you are inherently skeptical of a TOA calculation that produces an effect that you disagree with. However, claiming that you are attempting to find a new TOA calculation result that uses a significantly smaller monitoring area (Equatorial region) than the CERES-EBAF (global series) is hardly a convincing argument!
I’m sorry, but I don’t understand your post at all. Willis is doing a comparison of the CERES-EBAF-Surface data (which is acknowledged as calculated, not measured) against the TAO bouy set of data. Where does that mean he’s attempting to find a new TOA calculation result? I would say he’s doing a verification of the accuracy of that calculation, not trying to find a new calculation.
I would personally think that, assuming the two data sets are completely independent, it’s a useful confirmation that both sets of data agree with each other and therefore can be (subject to evidence that they aren’t independent) trusted to be reasonable reflections of the ‘truth’. At least with respect to equatorial ocean data.
“you” in your comment is presumably Willis. But I cannot relate your comment to Willis’ article. If I understand him correctly, Willis is not disagreeing with anything, he is using an opportunity to test the surface calculations from CERES against surface data from TAO. Since TAO operates in the tropics, that’s where the test takes place – and Willis acknowledges the incompleteness of the test. The really interesting thing about the test is that it shows remarkably good agreement between CERES and TAO. Assuming that there isn’t some factor that Willis has missed that makes this an artificial result (eg, if CERES had been calibrated against those same TAO measurements) then Willis has IMHO come up with a very valuable finding, namely that the CERES surface calculations are remarkably accurate over the tropical ocean.
For my part, and subject to the above assumption, I would like to congratulate Willis for conducting the test and publishing its result regardless of whether it was what he was expecting. I would also like to congratulate the CERES team for a job well done. I also note that all of the satellite teams appear to produce work very high quality – a quality which is unfortunately not always matched in some other areas of climate science.
Hello Willis.
Congratulation for your amassing approach in this matter and issue.
Before I go any further I have to say that I am in a Mosher like attitude, having one too many drinks, but never the less I will try to drive my point through.
From where I stand, you seem to have the ability and the .skill to bring up very interesting points.
So Cutting it short, as far as this posting of yours goes, from my point of view is in the same great approach as the previous one.
Believe me, I say this because I have learned a great deal, because of your expertise and the intellectual approach you show.
Now as far as this matter goes per relevance to the point you try to brink up, one thing or few do seem to raise a confusion.
Simply put, whether your approach simply showing a very weird and odd coincidence or not, it means for as far as I can tell that, if by some chance that is not an weird and odd coincidence than some how you have nailed further into AGW by showing that the tropics and global are at the same pattern.
If the expected measurable impact of AGW not seem to be happening in tropics, your very close and exact calculation when compared to the CERES, MEANS THAT THE SAME HOLDS TRUE.for the globe.
But never the less if this not a figment of imagination, due to some weird coincidence, then it also means that the hypothesis that CO2 in not increasing RF is a bollocks too.
You see, these both require that in the short term data you relied up on,, is shown much more deference.
Only in a CO2 causing increment of RF you get the result you have got at the end, regardless how accurate the CERES or you are in your calculation of the surface radiation.
Only when Co2 emission cause an increment of RF you get such a close match between the CERES and your calculation, otherwise that very close match means that is only an odd coincidence or if not than your believe of CO2 emission not increasing the RF is bollocks.
Is up to you to choose what the case is.
cheers
Willis,
13 months ago you made a post about how the CERES data had been adjusted to correlate to ocean heat content http://wattsupwiththat.com/2014/01/05/new-ceres-data-and-ocean-heat-content/. Is the observed correlation in this analysis being swayed by the post measurement data adjustment that you described in the previous post?
I deeply appreciate your sharing the product of your work.
Denis, the CERES instruments are quite precise but not extremely accurate. So while they can accurately measure a small CHANGE in a value like say upwelling longwave (good precision), the absolute size of the longwave radiation might be off (bad accuracy)
Now the basic equation at the top of the atmosphere is that at the mythical equilibrium, or say averaged over the course of the year, energy gains will be very close to energy losses. Otherwise the planet would be radically warming or cooling. The gains are the total incoming solar. The losses are the outgoing reflected solar and the upwelling longwave infrared radiation (ULR) which is the thermal radiation emitted by a combination of the earth and the atmosphere. They should equal each other.
The problem is … in the CERES dataset the gains don’t equal the losses. Instead, they’re off by about 5 W/m2 or so. And if that were actually the case, we’d see it as a change in temperature.
So … they adjusted the TOA average imbalance. Which makes sense to me. Unfortunately, they adjusted it to James Hansen’s best guess at the imbalance, which as a warming imbalance of +0.85 W/m2.
In any case, whether it’s adjusted to zero or to 0.85, the absolute values can’t be trusted. To deal with this I simply avoid depending on absolute values, and I stick to examining things like geographic or annual and decadal trends and variations.
w.
Willis said:
“The gains are the total incoming solar. The losses are the outgoing reflected solar and the upwelling longwave infrared radiation (ULR) which is the thermal radiation emitted by a combination of the earth and the atmosphere. They should equal each other.”
Good point. They MUST equal one another if an atmosphere is to be retained at all.
Incoming solar must stay the same and be matched by outgoing longwave plus reflected solar over time so the only variables are the thermal radiation emitted from each of earth and atmosphere and reflection.
It must follow that if one variable rises then the others must fall and vice versa.
What enables that equal and opposite adjustment in the thermal radiation from earth and atmosphere?
I have told you that the adjustment mechanism is variations in the amount of kinetic energy returning back to the surface from the potential energy in the atmosphere during adiabatic descent.
With water vapour in the atmosphere the albedo can also vary which provides another adjustment mechanism but in the absence of water vapour it would still work via changes in adiabatic descent.
The key physics to getting the answer correct is radiative transfer models.
the physics that skeptics deny or question.
the validation was done against CEPEX
How its done ( assuming this was the data set you used for example )
http://ceres.larc.nasa.gov/documents/ATBD/pdf/r2_2/ceres-atbd2.2-s4.6.2.pdf
other docs here
http://ceres.larc.nasa.gov/atbd.php
Steven Mosher: the physics that skeptics deny or question.
My “or question” is that too little is known about changes in non-radiative transfer of energy from surface to troposphere; and a few other ways that the “physics” of radiative transfer models are incomplete. Good efforts to fill the gap include the studies surveyed in:
“Energetic Constraints on Precipitation Under Climate Change” by O’Gorman, Allan, Byrne, and Previdi: Surveys in Geophysics, DOI 10/1007/s10712-011-9159-6.
They report estimates of 2% – 7% increase in rainfall in response to a 1C increase in temperature. With surface evapotranspirrative cooling estimated at 80 W/m^2 (Trenberth et al), those estimates indicate a non-ignorable amount of increased surface cooling to be caused by a 1C increase in surface temp. The lower estimates are produced by GCM-based analyses, the upper estimates based on regressions of rainfall vs temp in diverse parts of the Earth.
My “or question” is that too little is known about changes in non-radiative transfer of energy from surface to troposphere; and a few other ways that the “physics” of radiative transfer models are incomplete.
I wait for your publications.
Steven Mosher: I wait for your publications.
Me too.
Meanwhile, assume for the sake of argument that the rate of heat loss due to evaporation will increase 5% per 1C increase in surface temp. Assume Stefan-Boltzmann law is reasonably accurate. Assume that DWLWIR increases 4 W/m^2 and that the temperature warms up. When it has warmed 0.5C, evapotranspiration heat loss will have increased by 2W/m^2, and radiative heat loss by about 2.8W/m^2 — implying that the DWLWIR increase of 4 W/m^2 can not raise the Earth surface temp by 0.5C. Obviously these are approximations (based on flow rates by Trenberth), but there is no justification for ignoring the change in the evapotranspirative heat loss rate.
Anybody can easily repeat these calculations with different published values of the estimated constants and estimated changes. Do you need the imprimatur of a journal reviewer to think about them for a while?
Steven Mosher February 22, 2015 at 10:39 am
The key physics to getting the answer correct is radiative transfer models.
This presumes that:
a) the radiative transfer models are themselves correct, and;
b) there are no other significant processes outside radiative transfer that are significant
Given that the IPCC in AR5 chose to substitute “expert opinion” over output model in regard to sensitivity, it seems that your complaint that:
the physics that skeptics deny or question.
should not be constrained to skeptics alone.
There are correct.
davidmhoffer, at the risk of repeating myself, let me support your point.
Meanwhile, assume for the sake of argument that the rate of heat loss due to evaporation will increase 5% per 1C increase in surface temp. Assume Stefan-Boltzmann law is reasonably accurate. Assume that DWLWIR increases 4 W/m^2 and that the temperature warms up. When it has warmed 0.5C, evapotranspiration heat loss will have increased by 2W/m^2, and radiative heat loss by about 2.8W/m^2 — implying that the DWLWIR increase of 4 W/m^2 can not raise the Earth surface temp by 0.5C. Obviously these are approximations (based on flow rates by Trenberth), but there is no justification for ignoring the change in the evapotranspirative heat loss rate.
Anybody can easily repeat these calculations with different published values of the estimated constants and estimated changes. Does anyone need the imprimatur of a journal reviewer to think about them for a while?
If the models have if right they would do a better job of predicting the temperature of the globe. As per my question above, what is the bias and variance of these ‘correct’ calculations?
I am thinking circular reasoning. The satellite does not measure LW radiation.. it measures voltage or current, not photons directly. To figure out what the ‘reading’ really means, one can calibrate in a lab, but that assumes that one has a perfect test chamber to mimic the world OLR frequencies and thus the CERES input. No way.
I would suggest one would use the very TAO buoy data set that Willis used. Some other data set would be used for say an area of ice. Thus the instrument ‘readings’ can be translated back to worldwide temperatures.
Of course one would get a 99% correlation with the buoy data set if it was used to calibrate CERES. Circular, yes or no?
ECB,
Only if the argument is: the buoy data are accurate because CERES agrees with them.
Brandon
The CERES data comes from the top of the atmosphere. Read:
” It is usually referred as the CERES “top-of-atmosphere” data. The official name is “CERES EBAF-TOA”, and it is available here.
However, the second part of the CERES is not top-of-atmosphere observations from the satellite. Instead, it is calculated surface data based on the CERES TOA observations along with other satellite observations. It’s called the “CERES EBAF-Surface” dataset, and is available from the same location.”
Cool. Thanks again.
I have put up a comment on
http://claesjohnson.blogspot.se/2015/02/ceres-satellite-vs-surface-buoy.html