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Of Satellites and Air – A Primer on Tropospheric temperature measurement by Satellite

Posted on 24 March 2011 by Glenn Tamblyn

This post is an overview of the current state of Tropospheric temperature measurement via satellite. It is also the Advanced rebuttal to ‘the Troposphere isn’t warming’ sceptic argument.

The History of Tropospheric Temperature Measurement by Satellite

NASA has been building and launching the Tiros series (Television Infrared Observation Satellite) weather satellites since 1961. The satellites’ design has evolved over time. And after launch they are often operated by other agencies. The ones used for Tropospheric temperature measurement are operated by NOAA (National Oceanographic and Atmospheric Administration) beginning with Tiros N in Oct 1978 then NOAA 6 in June 1979 through to NOAA 19 Feb 2009. These satellites are designed principally as Weather Satellites; their use in Climatology is a secondary role. Also used in temperature measurement is the NASA AQUA satellite launched in May 2002 as a research Satellite, part of the NASA A-Train.


A general overview of the spacecraft and their equipment and roles can be found here.

What the satellites do

These satellites have Microwave Sounding Units (MSU) that read the Brightness Temperature of microwave signals from below in 4 separate frequencies radiated by Oxygen molecules. These frequencies tend to originate at different altitudes in the air column below the satellite and reflect the temperature at that altitude. I say tend because this isn’t exactly true and will matter later in the discussion. Using microwave signals associated with Oxygen has the advantage that microwaves are not substantially blocked by the atmosphere and Oxygen is evenly distributed throughout the atmosphere so its concentration only varies by negligible amounts. So the temperature signal from Oxygen is easy to detect, and isn’t going to be distorted by concentration changes. 

As the satellite orbits the Earth the MSU continually scans a swathe below the spacecraft, at nadir (looking straight down) and to the limits of the instrument on each side. Also on each scan the MSU calibrates its readings by taking readings from 2 other sources – cold deep-space, and an on-board, instrumented, hot reference source.

The satellites are Polar Orbiting & Sun Synchronous. Each makes around 14 orbits a day. Their orbit takes them nearly over the poles and the plane of the orbit lines up with the Sun. This is important because it ensures that each point on the Earth is always measured at the same time of day – Solar noon and Solar midnight.

On satellites up to NOAA-14, MSU’s were used. On later satellites, including AQUA, Advanced Microwave Sounding Units (AMSU) were fitted. These are more advanced designs that scan in more detail and over more frequencies, but the basics of how they work are the same. In this discussion I will refer mainly to MSU’s. The same concepts apply to the AMSU’s. 

Some Science

 This paper Grody 1983 (section 2) contains a discussion of the science of Microwave Sounding, and in particular the existence of Weighting Functions derived from solving the Radiative Transfer Equation. “…the temperature weighting function…defines the contribution of temperature at different altitudes to the brightness temperature.”. These functions are produced by summing the contribution at each frequency of microwave emissions from multiple levels in the atmosphere, taking into account the radiating behaviour of the atmosphere, pressure, temperature, path length etc.  Weighting Functions

Grody 1983 section 2

Here, as is common with atmospheric measurements, altitudes are given as pressures rather than kilometres. The dotted lines are the weighting functions for the extreme side parts of the scans while the solid lines are for the nadir view. The fact that the weighting functions at different frequencies have very different profiles wrt altitude is what allows us to measure temperatures at these different altitudes. Each frequency obtains most of its signal from a band of altitude. This altitude behaviour adds a major complication to measurement however; More on this later… 

The signal received by the MSU in its target frequency is made up of three components: Signals from the atmosphere radiated up to the satellite, signals from the atmosphere radiated down and reflected off the Earth’s surface, and signals emitted by the Earth itself.

The 4 frequencies are designated MSU Channels 1 (50.30 GHz), 2 (53.74 GHz), 3 (54.96 GHz), and 4 (57.95 GHz). Because the peak of the weighting function for Channel 1 is so close to the surface, this has a rather high component being emitted from the surface and is not very useful for Tropospheric temperature measurement because of this surface ‘contamination’. For the other channels, the surface component is much smaller but still needs to be allowed for. And this differs over land and sea. 

Some Nomenclature

A range of terms are used in the following discussion so I will summarise their meaning here:




T1, MSU Channel 1 Real channel peaking near ground level. Seldom used

T2, MSU Channel 2, TMT

Real channel peaking in mid to lower Troposphere. Stratospheric bias not removed
T3 MSU Channel 3, TTS, TUT Real channel peaking in mid to upper Troposphere. Stratospheric bias not removed

T4, MSU Channel 4, TLS

Real channel peaking in lower Stratosphere.
TLT Synthetic channel derived from T2, peaking in lower Troposphere, Stratospheric bias is removed


 Who Analyses the data


Data from the various instruments onboard the NOAA satellites are distributed to a wide range of organisations for various purposes. For Climatological temperature measurement the two main groups performing this regular analysis of the data from the MSU’s and providing temperature products are at the University of Alabama, Huntsville (UAH) & at Remote Sensing Systems in California (RSS). A number of other research groups have also done analyses of the data, but to investigate the methodology, not to produce regular temperature series products. To produce a long term temperature series from the satellite data these groups need to address a number of issues: 

Satellite Problems

NOAA-B, 1980 failed to achieve orbit. NOAA-13 had a catastrophic power failure 2 weeks after launch. NOAA-9 only had a relatively short overlap (3 months) with its follow-on satellite NOAA-10. Questions have been raised about the calibration of NOAA-16.

Overlap between satellites

Each satellite has slightly different calibrations, orbits etc. To get a long term temperature series, you need to ‘splice’ together the data from various satellites, launched and de-activated at different times. You need enough overlap between the operating lives of each satellite to compare their results to establish a common baseline. Many of the satellites have had quite long lives so another factor is degradation of the equipment and ‘drift’ in their calibrations. There is then the question of whether to use a new satellite’s data with its overlap issues or continue using an older satellite with its ageing issues. Some commentators have suggested that a major part of the discrepancy between the UAH & RSS products is due to the different methods they have used to handle the limited overlap of NOAA-9 & NOAA-10, perhaps as high as 65% of the difference. The following graph shows the difference between UAH & RSS temperature series for channel T2. The divergence is noticeable from around 1987 when NOAA-9 & NOAA-10 had their limited overlap period. The upper line on each graph is the difference between RSS & UAH. These graphs only go to 2004.


Switching from MSU to AMSU

Since the AMSU has a different number of channels at slightly different frequencies, this makes ‘splicing’ their data to that of the older MSU’s more complex.  

Orbital Decay:

The NOAA satellites do not have propulsion systems to correct for decay in their orbit due to friction from the very top of the atmosphere. So their altitude slowly drops over time. This has an effect on the readings; in much the same way as changing the scan angle alters the weighting function. This must be compensated for. Orbital decay is not always even. Changes in solar activity cause the Earths atmosphere to bulge & contract, changing the decay rates. However, the AQUA satellite does have propulsion so does not suffer as much from these problems. 

Instrument Body Effect

This is the problem of the satellite experiencing varying heating and cooling as it travels around its orbit. The hot target is meant to be fixed to a single temperature but actually they experience some change over the life of the satellite. Also the body of the MSU warms and cools and this can affect the readings it takes. Some of this IBE can be adjusted for after launch by analyses that compare between satellites. Also, over long periods these variations will tend to average out. But not all errors can be removed. 

Diurnal Drift

Earlier I mentioned that the satellites are in Sun Synchronous orbits and are meant to stay aligned with the Sun so that they always cross the equator at the same time – the Local Equator Crossing Time (LECT). If they don’t then the normal daily temperature cycles below (the Diurnal cycle) will start to add a false bias to the data. To stay Sun Synchronous the satellite’s orbit has a small precession, just less than one degree per day. However, this precession isn’t perfectly accurate and small drifts in this can introduce a ‘diurnal drift’ for each satellite, slowly changing it’s LECT. Drifts of up to 0.5 hr/year have been observed. So a Diurnal Drift correction is needed for each satellite. The two groups – UAH & RSS have used different methods to achieve this.  

UAH use data from view angles to left & right of nadir at fixed times in the orbit to look at different times of day below. This data allows a calculation that can remove the effect of the drift rate. The approach is simple but the calculations can magnify the effects of other uncertainties. 

RSS take the approach of using a high resolution climate model to simulate the expected daily variations beneath the satellite and use this to remove the diurnal drift. The modelled simulation is validated against the actual daily temperature ranges observed by the satellite. This method uses a simulation but has much less sampling noise compared to the UAH method. 

And as the following graph shows, the net effect is that the UAH method has added a cooling bias over time while RSS’s adds a warming bias to the raw temperature data.

 RSS vs UAH DD Correction

Figure 2: Diurnal drift corrections by UAH and RSS. UAH corrections add an overall cooling effect. RSS corrections added an overall warming effect. Both teams show strongest corrections in the tropics but in opposite directions.

Sea Ice & Summer Melt Pools

A complicating factor in the Polar Regions is surface emissions from ice. These make up the normal surface emissions that have to be allowed for in calculating temperature but with the large seasonal variations in sea ice extent, no single surface factor for these regions can be used. Similarly the appearance of melt pools on the ice in summer confuses the picture since these emit like water not ice. For this reason the temperature products don’t go all the way to the poles.

Stratospheric Biasing: Why T2 isn’t what it seems

Twice I have mentioned that the way the microwave signal is generated at different altitudes in the atmosphere is important. Go back and look at the first figure, of weighting functions. The horizontal line at 200 mbar marks the approximate starting height of the Stratosphere. (this actually varies from 1l km near the pole to 17 km at the equator). Look at how much of each curve is above this line. And recall that one of the major effects of AGW is a cooling of the Stratosphere. So Stratospheric cooling adds a cooling bias to the microwave signals. The signal the satellite measures underestimates the Tropospheric temperature. This is most an issue with channels T2 & T3. For T2, around 15% of the signal originates in the Stratosphere and since the Stratosphere has cooled much more than the Troposphere has warmed the effect of this is more than15% of the reading. T3 is split almost 50/50 between the 2 layers. T4 on the other hand gets most of its signal from the Stratosphere with very little from the Troposphere. As a result T2 & T3 significantly underestimate the warming that has occurred in their nominal altitude band. Without some form of correction, they are almost useless.  

T2 vs. TLT

The problems with Stratospheric cool biasing were recognised early and in 1992, Spencer & Christy at UAH introduced a new temperature product to remove the Stratospheric bias and focus more on the lower Troposphere. This removed most of the bias by mathematically combining readings from multiple view angles on the same scan to produce a reading weighted more strongly to the lower Troposphere. This was originally called MSU2LT and later with the addition of AMSU readings MSUTLT. This method produces the lower Troposphere weighting expected but is vulnerable to significantly increased sampling errors – essentially taking the difference between two samples will magnify the sample errors. Also, by looking at an East/West swathe, they are sensitive to temperature variations across the swathe. They are also more sensitive to direct surface emissions since they are magnifying the lower level signal.  

However, this approach was a significant advance in reading lower Tropospheric temperatures. In 2005 RSS also introduced a TLT product using the same nadir/side scan approach and in this work they introduced the different Diurnal Drift compensation described above. 

Fu et al 2004, 2005

In 2004/2005 Qiang Fu, Celeste Johanson et al published an alternative method for removing the Stratospheric bias from the T2 signal. Since the T4 channel is predominantly Stratospheric in origin they removed a proportion of the T4 signal from the T2 signal to remove the Stratospheric bias. In order to determine how much to remove, they used radiosonde data to establish a vertical temperature profile for the atmosphere. Then they determine by a least squares regression technique the appropriate weight to give to T2 & T4. They performed this on global, hemispheric and tropical zones on both the UAH & RSS data, to calculate a temperature series for each between 850 & 300 hPa, producing the following trend values:    Fu et al 2004 Trends

Note that these values were produced in 2004, before RSS had added their Diurnal Drift compensation. And the following shows the modified weighting function from Fu et al: Fu et al Weighting Function

Their weighting function has a broader weighting over the entire Troposphere than the TLT products so is likely to be more representative of the overall Troposphere. NOAA maintains a comparison temperature record for UAH, RSS & the Fu et al adjustments to them here.

The technique of Fu et al has limitations. It depends on an independent source for the vertical temperature profile it uses – the Radiosonde record. This record suffers from limited geographic coverage and has its own issues with data quality. Also the profile may alter over time. And since it uses profiles averaged over large regions, it is not useful for estimating regional trends other than very approximately. However it provides an important validation of the broad results from the TLT products.

In further work here Fu et al used a similar technique to their 2004 study but instead of using radiosonde data they performed a correlation directly between T2 and T4 directly to produce a mid Troposphere result TTT and between T2 and the less frequently used T3 channel to produce a lower Troposphere series TTLT, removing the Stratospheric bias from both and showing results for the tropics. The resulting trends are: Fu et al 2005

The data for this only covers 1987 to 2003 since the T3 Channels on earlier satellites were unreliable prior to 1987. They also critique the UAH data, suggesting that their results are un-physical. However, since their data only goes to 2003, it does not include more recent corrections by UAH. 

Vinnikov & Grody 

In 2005 Vinnikov & Grody et al (V&G) published another analysis of MSU data trends. Based on their previous work, it used a quite different, frequency & statistically based method to determine the underlying trends for the MSU measurements. They also consider additional issues related to calibration errors. Instead of assuming that there is a linear calibration error associated with the hot target calibration, they allow for this calibration varying over the satellites orbit due to external factors. They show that they can calculate this effect based just on latitude/longitude variation of the reading without needing to look at any time dependency.  

In their earlier work they had put a figure on trends of 0.22 to 0.26°C/decade. In this work they are estimating 0.20°C/decade. The following graphs show measured Surface, and their calculated TMT trends vs. latitude, and the same values calculated by climate models. The key discrepancies are at the poles with the modelled Northern Surface temps being much higher than measured Northern Surface temps, but modelled and measured Northern Troposphere values agreeing well. Surface temperature products don’t cover the Northern polar region or extrapolate from lower latitude measurements. Southern polar values also disagree but this is commonly ascribed to the effects of the Ozone hole which climate models do not include yet. There is significant agreement at mid and tropical latitudes.

 V&G Measured trends

  V&G Modelled Trends

Zou et al

In 2010 Zou et al published a new analysis method to produce low level MSU data for T2. This deals with removing many of the other calibration and inter-satellite correlation issues. Their method uses Synchronous Nadir Overpasses – points in time where two satellites are able to observe the same point below. This happens more commonly at high latitudes. Using this they are able to evaluate most of the onboard inter-satellite calibration issues since the satellites are receiving the same signal from below. The main outstanding areas that their analysis does not address are Diurnal Drift and Stratospheric cooling bias. They are not really trying to do this, instead producing a lower level data set to which others could apply further work. Their results are shown below. The data from their analysis can be obtained here.

 Trends from Zou et al

Monthly anomaly time series and trends for the global mean TMT, TUT and TLS, where TMT,TUT, and TLS represent deep-layer temperatures at mid-Troposphere, upper-Troposphere, and lower-Stratosphere.

So who is right?

So which teams analysis method is correct? Throughout the history of Tropospheric temperature measurement, the UAH analysis has always been lower than RSS for all temperature products. However, as time has gone by they have been drawing closer together. Currently their TLT trends are RSS 0.147 and UAH 0.138 which are down from earlier trends due to the slow down in warming in recent years. The convergence of their results may be due to the diminishing impact of the overlap problems between NOAA-9/NOAA-10. By comparison, the Fu et al method applied to RSS TMT & UAH TMT give RSS/FU 0.153°C/decade, UAH/FU 0.112°C/decade. Vinnikov & Grody have given around 0.20°C/decade while Zou et al give 0.137°C/decade; both without Stratospheric bias adjustment. 

Which of the techniques of UAH or RSS are correct? Both have weaknesses – UAH use comparisons between different view angles from one scan in two different parts of their analysis, magnifying the sensitivity to errors. RSS use a short term climate model rather than just data. Commentators seem to prefer the RSS analysis. Neither applies the lat/long dependent analysis of hot source calibration used by V&G so this could well increase their trends somewhat. And applying the Fu et al technique to V&G or Zou may give more divergent results again.  

Perhaps what can be said is that the UAH/RSS approach probably straddles the result their methods would find. Other methods suggest higher values. So a reasonable estimate at this point is that warming lies somewhere between the mid estimate of UAH/RSS and the figures that would be produced by V&G & Zou if Stratospheric cool biasing were removed. This suggests a long term trend of around 0.15 to 0.18°C/decade for the lower Troposphere, much in line with the surface trends. And similar or higher for the mid-Troposphere based on the fact that Fu et al is looking at the entire Troposphere and V&G are showing higher Tropospheric than surface warming through the mid and tropical latitudes. 

So these various analyses clearly show that the Troposphere IS warming, as determined from multiple sources. And if anyone quotes satellite temperature data to make a point with you, make sure you ask them which series they are referring to. If they simply say ‘the satellite data from UAH’, they may not know what they are talking about.

Further Reading

The IPCC had this to say about the satellite record (section

And Scott Church tells you even more than that up to 2005.


This post also has relevance to the ‘There's no Tropospheric hot spot’ argument. Look at some of the graphs above. Fu et al 2004 and 2005 showed greater warming in the Troposphere than the surface for the Tropics & Southern Hemisphere for their adjustments to the RSS data. And Vinnikov & Grody also show greater warming in the Troposphere compared to surface records and also in agreement with models in the Tropics & Southern Hemisphere. Whereas the analyses by UAH, RSS & Zou are not able to show reliably what has happened in the mid & upper Troposphere

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Comments 1 to 36:

  1. That's an interesting review, thanks. It's also exactly what I want from an advanced article - a review of the literature and development of the field giving me a clear picture of what is known, what uncertainties still remain, and what are the major contributions to the field. Well done!
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  2. It would be nice if the other analysis, such as V&G, provided up-to-date monthly data, such that sites like woodfortrees could easily include it. All we seem to get in the blogosphere are Spencer's blog updates, where trend analysis changes to frame any recent data as a cooling trend.
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  3. Where is the cross-correlation with real measurements? Any remote sensing professional in Petroleum knows that such remote measurements aren't worth anything with real measurements to compare it to.
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  4. cloa: "Any remote sensing professional in Petroleum knows that such remote measurements aren't worth anything ... " What are you talking about? The petroleum exploration industry is fully dependent on 'remote sensing;' millions are spent based on measurement at a distance - its called seismic profiling. But, here is correlation between surface and satellite temperature measures, all showing very similar trends.
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  5. I think he means that remote sensing must be calibrated or at least be validated against other measurement techniques. However, TLT isnt a measurement of surface temperature but, (like all MSU measurements), an average for a broad layer in the atmosphere. Validation then has to be done by comparison with radiosonde data. You might like to try here for starters.
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  6. Hasn't such calibration/validation been done, notably by Tamino?
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  7. NewYorkJ @2 The Fu and Zou analyses are available through the links above although I am not sure they are updated every single month. I suspect that they are available because they are produced by sections of NOAA - NCDC & NESDIS - and providing data is part of NOAA's remit. V&G are University based and probably don't have funding for an on-going program.
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  8. cloa513 The satellite measurements have been correlated against Radiosonde data as scaddenp linked to. In addition the technology is based on extremely well understood radiative physics and is based on a very simple signal from a single molecule. Taking muoncounter's point about seismic testing, that is based on validation against known rock profiles when it was first developed and laboratory studies of the vibrational properties of different rocks. A situation very similar to this although, to extend the analogy, here we are only dealing with 1 'rock' type - Oxygen molecules.
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  9. Oddly enough, I just finished reading "An alternative explanation for differential temperature trends at the surface and in the lower troposphere" [Pielke Jr. et al, 2009]. This particular article in combination with this one couldn't have come at a better time. [OT] As for the Pielke Jr. article, I don't think it means what Mr. Poptech thinks it means.
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  10. WSteven Interesting that The Pielke's et al consider the possibility of a warm bias in the surface record but don't consider the possibility of a cool bias in the satellite record. Also this statment "We generally have more confidence in the UAH satellite data set compared with the RSS data set", That John Christy, on of the authorts of this paper is one of the principles behind the UAH data set doesn't enter into this? And recent revisions to the data UAH & RSS data sets have significantly narrowed the margin. And how well can you compare global trends for Surface & Troposphere without considering latitudinal changes. Antarctic temps have been held down by the effects of the Ozone hole. Models, as V&G showed above predict more surface than tropospheric warming in the high North. Without breaking your analysis latitudinally, what are you really looking at
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  11. Glenn "Interesting that The Pielke's et al consider the possibility of a warm bias in the surface record but don't consider the possibility of a cool bias in the satellite record...'have more confidence in the UAH satellite data set compared with the RSS data set.'" Which is a couple of reasons I found your article useful while reading the the Pielke's study.. "And how well can you compare...?" The points that you raised were very good and I admit to not having thought of them all at the time. There's a lot I'm trying to absorb at the moment. :-) Excellent article BTW, Glenn. I find I'm learning a lot.
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  12. 10 Glenn Tamblyn "That John Christy, on of the authorts of this paper is one of the principles behind the UAH data set doesn't enter into this?" Show me a scientist who doesn't think his work is a cut above the rest?
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  13. Glenn Tamblyn BTW thanks for the article, very informative.
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  14. Glenn, to expand on what scaddenp has mentioned, Cloa and other readers may be interested in comparing the satellite MSU data with various global radiosonde (weather balloon) datasets for corresponding atmospheric pressure levels/altitudes, as the radiosonde data are generated from direct temperature measurements. The Remote Sensing Systems (RSS) team have generously done the work of creating and updating charts comparing RSS and UAH MSU data with radiosonde datasets such as HadAT (the UK Meteorological Office Hadley Centre Radiosonde data set) as in this chart covering most of the globe except the polar regions. There are many more plots available for the various radiosonde data sets and for comparisons at different latitude bands, including the tropics from +30 degrees to -30 degrees. It’s a great resource. There page scaddenp links to is excellent and worth repeating here as it covers data validation well.
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  15. Any thoughts on the spencer et al critique of the Fu work?
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  16. 14 Peter Hogarth You could have included this image from the HadAT website to show the global nature of the radiosonde dataset. 450 If you're validating the satellite data against the radiosonde data what do you validate the radiosonde global dataset against?
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  17. Glenn, a minor update for this great article, the Zou paper in your link is actually 2006, the 2009 paper is here. The T2 product in STAR V1.2 is actually corrected for diurnal drift using the diurnal anomalies from RSS. V2.0 (shown in the image) was available as of late 2010.
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  18. HumanityRules at 21:31 PM on 26 March, 2011 Radiosonde thermometers are just highly accurate electronic thermometers, and will be calibrated/validated as any other precision thermometer is. The various models used will have different (but usually very high, and very repeatable) accuracy specifications, such as the one used here which claims “The deviations between the various sensors lie within a few thousandths of a degree, therefore eliminating the need for extensive calibration”. Of course small known biases between different models need correcting, and in the past some types of radiosonde thermometers have suffered from direct radiative heating from the sun. There were many papers on this as far back as the 1950s, and a great deal of effort has gone into minimising these diurnal biases and other effects in the sensor design, or more recently back-correcting the various datasets. If you Google Jean Piccard (after whom the Star Trek captain was named, apparently) you’ll get some fascinating background.
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  19. Peter @14, Thanks for that great link-- super resource.
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  20. Thanks Glenn Tamblyn. I often wondered why those sattellite series showed a lower warming rate than the surface, when the smaller lapse rate should cause the opposite. I think now I understand: they encompass some of the cooling stratosphere too.
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  21. #20 Alexandre at 01:37 AM on 29 March, 2011 I often wondered why those sattellite series showed a lower warming rate than the surface, when the smaller lapse rate should cause the opposite. I think now I understand: they encompass some of the cooling stratosphere too. Nice theory. Except the stratosphere is not cooling.
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    Moderator Response:

    [DB] Nice cherry-pick & ignoring the rest of the picture for the TLS:

  22. BP.... This is the chart presented on the RSS site: TLT = Lower Trop TMT = Mid Trop TTS = Strat/Trop TLS = Lower Strat Source here.
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    Moderator Response: [DB] Sorry, Rob. We submitted at the same time, apparently.
  23. Re: Moderator Response:

    [DB] Nice cherry-pick & ignoring the rest of the picture for the TLS

    Nice omission, ignoring the effect of two major volcanic eruptions. If lower stratospheric temperature anomaly is put against atmospheric CO2 concentration, regime changes due to eruptions can even more clearly be seen. And of course, that carbon dioxide itself has no effect on it at all. There is apparently a strong short time warming effect in the stratosphere from volcanic eruptions followed by a mild cooling with a much longer relaxation time, possibly due to nanoparticles, which have extended stratospheric lifetime (because there's no rain there to wash them out).
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    Moderator Response:

    [DB] Perhaps you missed reading the entire unadulterated graphic straight from RSS, so here's the unvarnished piece in question, again:

    FYI: The spiky bits were the eruptions in question. For those not in full possession of the straight information, volcanoes exert their transient cooling effects in the lower troposphere in opposite fashion in the stratosphere: temporarily warming it.

    Due to the paucity (love that word) of water vapor in the stratosphere, the radiative imbalance of the Earth allows CO2 to freely exert it's GHG effects by cooling the stratosphere. As the clear RSS graphic I have shown twice now starkly delineates, the long-term stratospheric temperature trend is down, while the level of CO2 in our atmosphere is up, driving up the temperature of the lower troposphere and our oceans with it. A change in conditions for which mankind is responsible. No matter the dissembling of some.

  24. BP Although the lower Stratosphere hasn't colled much lately, the fact remains that it has cooled since start of the satellite record. ince each reading from a satellite is based on the current temperature profile through the air column. Since the temps are all anomalies relative to a baseline period, the stratosphere doesn't have to keep cooling to impact what the tropospheric reading from T2 appears to be. Earlier in the history it will have had a growing bias. If its cooling has stabilised, the bias it contributes isn't growing, but there is still a fixed bias from the amount of cooling that has occurred. The important point about how the various compensation schemes for Stratospheric cool bias compensation work is that they are applied at the individual sample level, not at the high order trend level. Each reading has the compensation applied then trends are calculated from it. If the bias isn't changing at present then new samples will still have the same bias removed. Interesting from the records - Eruptions don't show up much at all in the lower trop' series but hugely in the strat'. El Nino is the opposite, largely lower trop' based.
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  25. Re: Moderator Response:

    Due to the paucity (love that word) of water vapor in the stratosphere, the radiative imbalance of the Earth allows CO2 to freely exert it's GHG effects by cooling the stratosphere. As the clear RSS graphic I have shown twice now starkly delineates, the long-term stratospheric temperature trend is down, while the level of CO2 in our atmosphere is up, driving up the temperature of the lower troposphere and our oceans with it.

    I don't know anything about the long-term global stratospheric temperature trend, it is not even measured properly I guess. At the same time trend for the last 32 years (the "satellite era") is down indeed, as measured by brightness temperature in channel TLS of MSU/AMSU devices. However, science is never about the big picture, in fact not about any picture at all. It is about propositions and truth-values (True/False) attached to them. Sweeping generalizations like "stratospheric temperature trend is down, while the level of CO2 in our atmosphere is up therefore temperature changes are driven by CO2" as suggested in your comment are only good for misleading the general public by showing them a gross picture, but unsuitable for actually understanding what's going on and deriving true and meaningful propositions about the system. ( -Off-topic dissembling snipped- ) We have reliable data for the last 32 years, that is, since the beginning of 1979 till February 2011. And yes, temperatures up there have decreased. However, they've done it in a curious manner. All the decrease happened in two distinct steps, one in 1982-85 the other in 1991-94. Otherwise the temperature curve of lower stratosphere is pretty flat with no trend at all, especially so during the second half of the entire 32 year record. These events are clearly identifiable as major volcanic eruptions (El Chichón, April, 1982 & Pinatubo, July, 1991). What happens is actually a huge initial transient increase in stratospheric temperatures that lasts for about two years followed by a decrease that is larger than the increase was. That is, the stratosphere, after a two years long transient ends up in a state with lower temperatures than the one it was assuming prior to the eruption. Of course the stratosphere can't get ever colder with each major eruption, so there must be some recovery on a multi-decadal scale, but three decades are just too short to give a good estimate of the relaxation time involved (other than a lower bound). To see this process more clearly let's have a closer look at the El Chichón event. The image below shows the CO2/TLS phase diagram around this event with monthly resolution. The eruption itself is marked by a red dot on the trajectory, the transient is in yellow while (meta)stable states before and after the event are in different shades of blue. As you can see the before and after states occupy two markedly disjoint regions of the phase space. The projection of these regions to the CO2 axis do overlap (between 340 and 345 ppmv), but even there, they're separated by temperature (0.4°C on average). During the 8 years following the initial transient excursion (but before Pinatubo) TLS is not decreasing further. The trajectory meanders to ever higher CO2 concentrations, but the temperature remains stable or if anything, slowly (and hesitantly) climbs back toward the level from where it started before the eruption. It just did not have the time to accomplish this task before another eruption hit. It is an interesting scientific question what physical process mediates the multi-decadal stratospheric cooling effect of major eruptions. Unfortunately it is a question that mainstream climate science, trapped by the old CO2 paradigm, failed to address so far.
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    Moderator Response: [DB] You identify a number of different topics which are best discussed elsewhere (like volcanoes, for example). If you wish to pursue them, do them elsewhere. If you believe the satellite record is unreliable, then there's threads delving into that topic that perhaps you've missed. Otherwise, you can't use the satellite data to disprove the trend of the satellite data and expect anyone to take you seriously.
  26. Re: Moderator Response: [DB] You identify a number of different topics which are best discussed elsewhere (like volcanoes, for example). If you wish to pursue them, do them elsewhere.
    I'd happily do that as soon as statements cloaked as an imperative from the article above like "And recall(!) that one of the major effects of AGW is a cooling of the Stratosphere" are also moved elsewhere. Until it's done, it remains perfectly appropriate to discuss the issue under this heading. What I have accomplished above was to show the truth-value attached to the proposition "one of the major effects of AGW is a cooling of the Stratosphere" is False. If the overall downward trend in the 32 year record of MSU/AMSU ch. 4 (TLS) is due to two step-like drops associated with well known volcanic events, as it is the case, and these eruptions were not anthropogenic ones, then one can not say the trend demonstrates "one of the major effects of AGW (Anthropogenic Global Warming)". Or can, but in that case you can't expect anyone to take it seriously.
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  27. BP> Unfortunately it is a question that mainstream climate science, trapped by the old CO2 paradigm, failed to address so far. False. Your claim is 5 years too late. The step-wise nature of the cooling was discussed in Ramaswamy 2006 et al. among others. From the abstract: "Observations reveal that the substantial cooling of the global lower stratosphere over 1979–2003 occurred in two pronounced steplike transitions. These arose in the aftermath of two major volcanic eruptions, with each cooling transition being followed by a period of relatively steady temperatures. Climate model simulations indicate that the space-time structure of the observed cooling is largely attributable to the combined effect of changes in both anthropogenic factors (ozone depletion and increases in well-mixed greenhouse gases) and natural factors (solar irradiance variation and volcanic aerosols). The anthropogenic factors drove the overall cooling during the period, and the natural ones modulated the evolution of the cooling."
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  28. "What I have accomplished above was to show the truth-value attached to the proposition "one of the major effects of AGW is a cooling of the Stratosphere" is False." No that is not what you have accomplished. What you have accomplished was to, once again, show that you are so eager to find fault that you will find it even where it does not exist and that you are so happy to find it that you can not even bother to verify whether or not the fault is real. You have shown that pattern consistently since the broad accusation of fraud on the coral and acidification thread. By the way, you never revisited that thread in the way you said you would. Same old pseudo-skeptic attitude.
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  29. BP I hadn't seen the Ramaswamy paper cited by e but have to agree with e's assessment. The signatures of El Chichon and Pinatubo show up clearly in the latitudinal plots and only indicate an impact over the mid latitudes. This can't be determined from looking at the behaviour of just the global average temp anomaly, which calls into question the validity of the approach you are using correlating the global signal to volcanic events. It seems to me far more likely that the volcanoes had a residual effect in subsequent years and what we are seeing is a trend with volcanic spikes superimposed. Perhaps if you repeat this analysis looking at TLS data from different latitude bands and see how consistent the graphs are across the bands. That said there is the possibility - this is speculation on my part here - that the volcanoes may have had a longer term impact. Solomon et al 2010 discuss an apparent decline in stratospheric water vapour levels over the 2000's following an apparent rise in the 90's. Speculatively, could the BIG eruptions inject H2O into the atmosphere that persists for years. Solomon et al is discussed here: Irrespective of that, this post is about the impact of stratospheric cooling, from whatever source, on the accuracy of our tropospheric temp measurements.
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  30. Glenn, e, Phillipe, and BP, The graphic shown here really blows the following nonsensical comment right out of the water: "one of the major effects of AGW is a cooling of the Stratosphere" is False." It shows the global stratospheric temperatures have cooled by about 1.5 K since the late fifties. If anyone can figure out a way of posting the image contained in the link on this thread, please do so. Thanks!
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    Moderator Response:

    [DB] Ask & ye shall receive:

  31. And just a quick comment to people lurking on this thread. The title of the thread is "Of Satellites and Air – A Primer on Tropospheric temperature measurement by Satellite". Interesting the how the contrarians and deniers of AGW then, in the face of overwhelming evidence that the troposphere is warming because of AGW, try and spin things to detract from that inconvenient fact by fabricating false statements about trends in global stratospheric temperatures. A good try, but yet another epic fail for the anti-science crowd.
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  32. Daniel, Thanks-- you rock!
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    Moderator Response: [DB] Thanks, but you did the hard part (finding scientific evidence to trump speculation).
  33. BP #25: "All the decrease happened in two distinct steps, one in 1982-85 the other in 1991-94." This statement is simply false. Using the UAH data we get; 1981 was 0.3603 C cooler than 1978 (0.090 C/year) 1985 was 0.4431 C cooler than 1981 (0.089 C/year) 1994 was 0.1550 C cooler than 1985 (0.016 C/year) 2008 was 0.1763 C cooler than 1994 (0.012 C/year) Those numbers would indicate that roughly 55% of the total cooling took place during the years you identified... rather than the 100% ("All the decrease") you claimed. This shows fairly clearly that greenhouse cooling was ongoing before, during, and after the spikes caused by the volcanic eruptions. Of course, the longer term data supplied by Albatross makes that point even more clearly, but I thought it was noteworthy that the original argument was demonstrably false even using the data it was supposedly based upon.
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  34. Nice graph Daniel. Even shows up the lesser peak from the Agung eruption of 1963/64 Another speculation using that precise scientific instrument, a Mark I eyeball. All three eruptions spike back up to a similar level then drop back down to the old trend. Is that coincidence, a function of the size of the eruptions? Or an underlying property of the impact of any major eruption on the stratosphere?
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    Moderator Response: [DB] Based on my understanding, the graph highlights the transient impact that volcanic eruptions typically have on climate. All bets are off on supervolcanic eruptions, tho.
  35. Daniel. If we have a supervolcano, then we can take AGW of the table as an agenda item for a while. And I will probably stop saving for my retirement. How can I spend my (very limited) wealth in a way that gives me the most fun before I croak?
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    Moderator Response: [DB] Given the effects, if that supervolcano is Yellowstone here in the US, I might only have a few months. But the likelihood is far less than the temperature forcing from CO2. :)
  36. Can someone point me to link explaining the cause of the leveling off of TLS cooling in past decade?


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