From the University of Alabama, Huntsville via email from Dr. John Christy.
Weather Satellite Wanders Through Time, Space, Causing Stray Warming to Contaminate Data
In the late 1990s, the NOAA-14 weather satellite went wandering through time and space, apparently changing the record of Earth’s climate as it went.
Designed for an orbit synchronized with the sun, NOAA-14’s orbit from pole to pole was supposed to cross the equator at 1:30 p.m. on the sunlit side of the globe and at 1:30 a.m. on the dark side, 14 times each day. One of the instruments it carried was a microwave sounding unit (MSU), which looked down at the world and collected data on temperatures in Earth’s atmosphere and how those temperatures changed through time.
By the time NOAA-14 was finishing its useful life in 2005, however, it had strayed eastward from its intended orbit until it was crossing the equator not at 1:30 but at about 8:00. That pushed its early afternoon passage until after dark and its middle of the night measurements until well after dawn.
Diagram showing wander orbit of NOAA-14. Credit: University of Alabama Huntsville
Because local temperatures typically change between 1:30 and 8:00, this introduced spurious temperature changes that had to be calculated and removed from long-term temperature datasets that use data from satellite instruments.
The drift also changed the satellite’s orientation relative to the sun, so that instead of instruments being shielded from sunlight in a consistent way, the sun’s rays peaked into unshielded and open crevices and other places where intense sunlight could influence the sensors. It warmed the MSU, which caused it to look at the atmosphere’s mid-troposphere (from the surface up to about 40,000 feet) as very slightly warmer than it actually was relative to its initial 1:30 crossing time.
Using data from weather satellites that stayed closer to home than NOAA-14, scientists in the Earth System Science Center (ESSC) at The University of Alabama in Huntsville (UAH) have calculated how much false warming NOAA-14 reported so the false warming could be removed from a long-term global atmospheric temperature record collected by MSU’s on satellites since mid-November 1978.
The wandering satellite became an issue when Dr. John Christy, director of UAH’s ESSC and lead author of the study, and Dr. Roy Spencer, an ESSC principal research scientist, were updating and revising UAH’s satellite-based global temperature dataset. (Version 6.0 was completed in 2016.) While they knew NOAA-14 had strayed from its path, a closer look showed the warming reported by the MSU on NOAA-14 was out of kilter with temperature data collected by instruments on other NOAA satellites. This seemed to be especially true in the tropical mid-troposphere.
NOAA-14 was “drifting more than any other spacecraft used in this dataset,” said Christy.
“We were looking at 39 years of a temperature trend, and this stray satellite affected the trend by about 0.05 degrees Celsius (about 0.09° F) per decade,” said Christy said. “Over 39 years, that would be a total warming of about 0.2 C, or more than one-third of a degree Fahrenheit. And this problem occurred, almost all of it, in the 1990s and the early 2000s.
“An important piece of evidence pointing to a problem with the NOAA-14 satellite was its warming relative to the new NOAA-15 satellite that came in at the end of the 1990s,” Christy said.
To measure the scale of the problem after the UAH satellite dataset was finalized, the ESSC team started with a subset of U.S. weather balloons that hadn’t changed either instruments or software during at least a major part of the period NOAA-14 was in orbit. Weather balloons are a useful tool for benchmarking against the satellite data because both collect temperatures from the surface up through deep layers of the atmosphere.
When the U.S. balloons showed less warming than the MSU on NOAA-14, Christy expanded the study to include a group of Australian weather balloons that also hadn’t changed instruments during a major part of the time NOAA-14 was in orbit.
“This gave us two reputable datasets that are widely separated across the Earth’s surface,” Christy said. “Then we also looked at homogenized data from independent groups that correct balloon datasets.”
That data from NOAA, the University of Vienna and the University of New South Wales was added to data from three other groups — the European Center for Medium Range Forecasts, the Japan Climate Research Group and NASA — that “reanalyze” global weather data, correcting for flaws and problems.
UAH even created its own homogenized balloon dataset from raw balloon data archived by NOAA, which came from 564 stations around the world.
“We tried to understand the situation by inter-comparing against as many individual, independent datasets as possible,” Christy said. “We know no dataset is perfect, so comparing against various sources is a key part of dataset analysis. This allows us to zero in on places with the greatest discrepancy. We found the largest difference between the UAH dataset versus other satellite datasets — and even some with balloons — was found in the 1990s and early 2000s, the period of NOAA-14.”
And NOAA-14 was showing more warming than any of the balloon datasets, as well as more warming than NOAA-12 or NOAA-15, each of which overlapped NOAA-14 at some point during its time in service. They also compared temperature data from NOAA-15 to data from NASA’s orbit-stabilized AQUA satellite.
When the UAH team, led by Spencer, Christy and W. Daniel Braswell, built the Version 6.0 UAH dataset in 2016, they serendipitously did two things that limited the drift’s influence.
“First, we stopped using NOAA-14 in 2001, when it had drifted to 5 p.m.,” Christy said. “In our view, that was just too much drift to have confidence an accurate correction could be found.”
They also applied an algorithm that minimized the differences between the satellites, largely removing the NOAA-14 drift relative to the other satellites.
This resulted in a long-term mid-troposphere warming trend in the tropics of about 0.082 C (about 0.15° F) from late 1978 to 2016. This compares well with the +0.10 C (±0.03 C) per decade trend found by other sources that weren’t exclusively satellite based.
The way UAH built its dataset and accounted for these issues is unique among the four major satellite temperature datasets. The other three datasets still include all of the NOAA-14 data and show warming trends greater than the trend shown in the UAH dataset.
Other satellite-only temperature datasets report tropical mid-troposphere warming trends ranging from +0.13 to +0.17 C per decade.
“Not realizing it at the time, the methods we used to build the newest dataset appear to have dealt with a discrepancy that came to light through this inter-comparison study,” Christy said.
Note: This is not the lower tropospheric data or long-term warming trend reported each month for more than 27 years in UAH’s Global Temperature Report. The lower troposphere extends from the Earth’s surface to an altitude of about eight kilometers (more than 26,000 feet).
Because most low Earth orbiting satellites tend to stray somewhat from their intended orbits, new NOAA polar-orbiting weather satellites scheduled for launch in coming years will carry the extra fuel needed to keep them closer to home throughout their time in space.
The Intergovernmental Panel on Climate Change Assessment Report 5 (IPCC AR5, 2013) discussed bulk atmospheric temperatures as indicators of climate variability and change. We examine four satellite datasets producing bulk tropospheric temperatures, based on microwave sounding units (MSUs), all updated since IPCC AR5. All datasets produce high correlations of anomalies versus independent observations from radiosondes (balloons), but differ somewhat in the metric of most interest, the linear trend beginning in 1979. The trend is an indicator of the response of the climate system to rising greenhouse gas concentrations and other forcings, and so is critical to understanding the climate. The satellite results indicate a range of near-global (+0.07 to +0.13°C decade−1) and tropical (+0.08 to +0.17°C decade−1) trends (1979–2016), and suggestions are presented to account for these differences. We show evidence that MSUs on National Oceanic and Atmospheric Administration’s satellites (NOAA-12 and −14, 1990–2001+) contain spurious warming, especially noticeable in three of the four satellite datasets.
Comparisons with radiosonde datasets independently adjusted for inhomogeneities and Reanalyses suggest the actual tropical (20°S-20°N) trend is +0.10 ± 0.03°C decade−1. This tropical result is over a factor of two less than the trend projected from the average of the IPCC climate model simulations for this same period (+0.27°C decade−1).
From the paper, here is the main conclusion:
One key result here is that substantial evidence exists to show that the processed data from NOAA-12 and −14 (operating in the 1990s) were affected by spurious warming that impacted the four datasets, with UAH the least affected due to its unique merging process.
RSS, NOAA and UW show considerably more warming in this period than UAH and more than the US VIZ and Australian radiosondes for the period in which the radiosonde instrumentation did not change. Additionally the same discrepancy was found relative to the composite of all of the radiosondes in the IGRA database, both global and low-latitude. While not definitive, the evidence does support the hypothesis that the processed satellite data of NOAA-12 and −14 are characterized by spurious warming, thus introducing spuriously positive trends in the satellite records. Comparisons with other, independently constructed datasets (radiosonde and reanalyses) support this hypothesis (Figure 10).
Figure 10. Magnitude of the relative difference between two periods for the respective satellite datasets (colored bars) and the respective radiosonde-based datasets (i.e. positive value indicates satellite warmed more than the radiosonde-based data between defined periods.).
Given this result, we estimate the global TMT trend is +0.10 ± 0.03°C decade−1. The rate of observed warming since 1979 for the tropical atmospheric TMT layer, which we calculate also as +0.10 ± 0.03°C decade−1, is significantly less than the average of that generated by the IPCC AR5 climate model simulations. Because the model trends are on average highly significantly more positive and with a pattern in which their warmest feature appears in the latent-heat release region of the atmosphere, we would hypothesize that a misrepresentation of the basic model physics of the tropical hydrologic cycle (i.e. water vapour, precipitation physics and cloud feedbacks) is a likely candidate.
Note that this addresses the “Tropical hotspot” of models, and is a much lower trend than they show in figure 1 from the paper, shown below, which has values 0f 0.4 to 0.6 °C per decade compared to Christy’s result of 0.10 °C per decade.
Figure 1. Latitude – Altitude cross-section of 38-year temperature trends (°C decade−1) from the Canadian Climate Model Run 3. The tropical tropospheric section is in the outlined box.
NOTE: the first version of this post had an error in the title, and was missing the figure 1 graphic above. This happened due to a versioning error on my part. It has been corrected as well as the original Tweet removed and resent.
This new paper by Christy et al is not looking good for GHE warming hypothesis. Not only the tropical mid-troposphere hotspot is only one-sixth the warming predicted by IPCC models (0.1 C/decade vs. 0.6 C/decade) but more importantly the low troposphere is warming faster than mid-troposphere (0.08-0.17 C/decade vs. 0.1 C/decade) This contradicts the models which show mid should be warming twice faster than low. This is not the sign of GHE warming.
GHE warming is due to radiative heat transfer by SB law:
j = e o T^4
The derivative of flux:
dj/dT = 4 e o T^3
The higher the temperature, the more energy needed for differential increase in temperature. Conversely, the lower the temperature, the less energy needed. Mid-troposphere is cooler than low troposphere. It should warm faster but that’s not what satellite data show.
Dodgy Geezer
April 7, 2018 1:47 am
Seems fairly obvious to me.
If a scientist discovers a real natural phenomenon, people will soon start to study it and will develop instruments and techniques capable of easily isolating the data they want
If a scientist claims to have discovered a natural phenomenon which actually doesn’t exist, people who depend on studying it for their jobs will still develop techniques for isolating the data they need – in this case playing with the variability of sensors at the limits of their accuracy, and producing spurious ‘adjustments’….
Dodgy Geezer
April 7, 2018 2:07 am
If the facts are on your side, argue the facts.
If the facts aren’t on your side, argue the adjustments….
If the adjustments aren’t on your side, just argue. Ad-homs will do quite nicely…
Alan Tomalty
April 7, 2018 2:10 am
Another logical light bulb went off in my head. Since the Masters golf tournamnet 83 year (same time frame as almost all of greenhouse gas emissions by man) temperature history shows no warming; what are the odds of only one place on earth being like that? I will venture to guess that the odds would go to 9 sigma. For those uninitiated; 5 sigma is 99.00004 % against which is the standard for physics. Medicinal studies are unfortunately only 2 sigma. I would guess that climate science is no better than 1 sigma in the end.
Soooo if those odds were astronomical against , then the odds must be 9 sigma for the possibility of there being 1000’s of sites around the world that are like Augusta which is being played this weekend. So since there are 1000’s of such sites there must be temperature records of some of them. Each one is a nail in the coffin of global warming. The odds would be 9 sigma against that all those sites exist and global warming is real at the same time. Because Mr CO2 doesnt discriminate. He is evenly mixed in the atmosphere everywhere , then how can there be global warming in only parts of the world. Since it rains moderately
in Georgia, then CO2 doesnt have any effect in Georgia or else what makes Augusta Georgia so special that it has defied Mr. CO2? If Augusta Georgia isnt special (except for the golf course there and the Masters held there every year for 4 days) then Mr CO2 has an achilles heel. Since we have shown above that there must be thousands of other sites including 10 of the 13 stations in Antarctica that have stood up to Mr CO2s bullying by showing no warming, then I say that MR CO2 has no clothes. .
…..plus what are the odds that two thermometers….less than 20 miles apart….and one shows warming…the other shows cooling….there’s no such thing as Urban Cold Island
Yes, agree w/others, this seems obvious and should be acknowledged in the “science”, such as it is. CO2 has little effect on tropical areas as Willis & others have shown — cloud-feedbacks keep temps from rising (just more day-time clouds). The “CO2 tropical warming” that pops up in the models is garbage.
Ian H
April 7, 2018 8:05 am
I am not sure the issue has been described correctly. It has been presented as an issue of solar precession whereby the time of crossing shifts gradually from midday/midnight to dawn/dusk. But all polar orbits must precess like this since the plane of the orbit is fixed in space as the earth rotates about the sun.
Ian H
April 7, 2018 at 8:05 am
Ian, I am not very sure if I correctly get your point, but if it could help.
The “solar precession’ issue, in this particular subject, is not in regard of satellite’s navigator, or the navigating system.
it is or it could be a serious issue when considering the synchronization between it and the the time kipping as per recording of the data.
Some thing like the condition of the “Captains Cook daily record”.
The hourly timing on that record will be as per Captains belt watch or a mechanical time kipping clock , which over the time of see fairing adventure had to be synchronized to/by the navigator’s every day sundial time measurement (probably at midday 12:00 as per navigator’s sundial).
No synchronization in between, or a poor one will result in a considerable error over time, as per actual timing of the record taken and recorded.
For example, also, in a multi year record to be accomplished with a correct timing, in such cases, even the odd 366 day year could subject the process to a considerable degree of error, when such synchronization required, even when both, the navigation and record kipping in their own respective right do not have much problem with it……but still when a synchronization in between required, the odd year can be a pain that has to be dealt with, if the propagated error in such a case could end up messing the integrity of the record due to wrong time kipping.
Am not sure if this clearly enough put, or even that it may have any much sense.
Only trying to show that it could be a little more complicated than it may seem at first look at it.
cheers
Pamela Gray
April 7, 2018 10:53 am
At the peak of an interglacial period (in the past some have been sharp, some have been plateau-like), there may be decadal ups and downs. So all this .0001 accuracy nonsense is just that; nonsense. We are in a warm period. In general, we should be warmer compared to being on either an up-slope or a down-slope from/to a glacial period.
So someone discovers that some of our warm period sensors are a bit off. Fix it and move on. And if Nick gets nickers in a twist over what he believes to be data that is more accurate than something that was a bit off, well at least it keeps him busy and out of trouble.
As for me, I am glad it is warm. I don’t need to use as much wood heat and it is more fun fishing when it is warm than when it is cold. Except today I can’t go fishing because I did too much heavy lifting last week. All this is to say that it is WAAAAAYYYYY more important that I can’t go fishing today!!!!
Must say: I told you so.
How many times did I mention that we cannot unilaterally trust the sats because of the destruction of anything in space that you want to use to measure> Especially now, lately, for the past few years, the sun’s rays are terrible.
Better to look at Tmax and Tmin at the stations. But you have to use the correct sampling procedure. Data sets (like Best) that are completely biased to the NH are useless, since there has been little or no warming at the SH.
there is an explanation here: https://wattsupwiththat.com/2018/04/05/a-look-at-the-ghcn-daily-minimums-debunks-a-basic-assumption-of-global-warming/comment-page-1/#comment-2784761
I wonder if the contract between UAB and NASA stipulates periodic reporting when the Satellites go out-of-spec.
jasg
April 9, 2018 2:26 am
There is a big difference between sensible calibrated adjustments to correct wonky sensor data and adjustments based on just making data up (as in the NASA extrapolation and C&W infilling over the Arctic), guessed TOBS adjustments (based on an implausible error graph implausibly applied and uncalibrated) or the replacement of good data with poor data in the NOAA pause-buster adjustments. As for the newly warmed-up RSS graph, the fact that their reviewers did not include anyone actually qualified to review it says everything.
LOL,
Hey Nick Stokes and Moshpit, why don’t you guys explain to Tony he’s just imagining things, and Carl Mears is stand up guy…..he’d never do anything unethical. ROTFLMAO https://realclimatescience.com/2018/04/climate-mafia-at-work/
One would expect that Dr. Carl Mears would know how to spell satellite, and that he would also notice that even after he changed the data there is still a very large discrepancy between the models and observations, with observations falling at the very lower end of the model range. But let’s look how he changed the data. He simply got rid of his error range (light blue) and moved the temperature (black line) up to the very top of his error range.
This new paper by Christy et al is not looking good for GHE warming hypothesis. Not only the tropical mid-troposphere hotspot is only one-sixth the warming predicted by IPCC models (0.1 C/decade vs. 0.6 C/decade) but more importantly the low troposphere is warming faster than mid-troposphere (0.08-0.17 C/decade vs. 0.1 C/decade) This contradicts the models which show mid should be warming twice faster than low. This is not the sign of GHE warming.
GHE warming is due to radiative heat transfer by SB law:
j = e o T^4
The derivative of flux:
dj/dT = 4 e o T^3
The higher the temperature, the more energy needed for differential increase in temperature. Conversely, the lower the temperature, the less energy needed. Mid-troposphere is cooler than low troposphere. It should warm faster but that’s not what satellite data show.
Seems fairly obvious to me.
If a scientist discovers a real natural phenomenon, people will soon start to study it and will develop instruments and techniques capable of easily isolating the data they want
If a scientist claims to have discovered a natural phenomenon which actually doesn’t exist, people who depend on studying it for their jobs will still develop techniques for isolating the data they need – in this case playing with the variability of sensors at the limits of their accuracy, and producing spurious ‘adjustments’….
If the facts are on your side, argue the facts.
If the facts aren’t on your side, argue the adjustments….
If the adjustments aren’t on your side, just argue. Ad-homs will do quite nicely…
Another logical light bulb went off in my head. Since the Masters golf tournamnet 83 year (same time frame as almost all of greenhouse gas emissions by man) temperature history shows no warming; what are the odds of only one place on earth being like that? I will venture to guess that the odds would go to 9 sigma. For those uninitiated; 5 sigma is 99.00004 % against which is the standard for physics. Medicinal studies are unfortunately only 2 sigma. I would guess that climate science is no better than 1 sigma in the end.
Soooo if those odds were astronomical against , then the odds must be 9 sigma for the possibility of there being 1000’s of sites around the world that are like Augusta which is being played this weekend. So since there are 1000’s of such sites there must be temperature records of some of them. Each one is a nail in the coffin of global warming. The odds would be 9 sigma against that all those sites exist and global warming is real at the same time. Because Mr CO2 doesnt discriminate. He is evenly mixed in the atmosphere everywhere , then how can there be global warming in only parts of the world. Since it rains moderately
in Georgia, then CO2 doesnt have any effect in Georgia or else what makes Augusta Georgia so special that it has defied Mr. CO2? If Augusta Georgia isnt special (except for the golf course there and the Masters held there every year for 4 days) then Mr CO2 has an achilles heel. Since we have shown above that there must be thousands of other sites including 10 of the 13 stations in Antarctica that have stood up to Mr CO2s bullying by showing no warming, then I say that MR CO2 has no clothes. .
…..plus what are the odds that two thermometers….less than 20 miles apart….and one shows warming…the other shows cooling….there’s no such thing as Urban Cold Island
Google are 100% manipulating searches on climate science.
Yep, you’re right about that.
Yes, agree w/others, this seems obvious and should be acknowledged in the “science”, such as it is. CO2 has little effect on tropical areas as Willis & others have shown — cloud-feedbacks keep temps from rising (just more day-time clouds). The “CO2 tropical warming” that pops up in the models is garbage.
I am not sure the issue has been described correctly. It has been presented as an issue of solar precession whereby the time of crossing shifts gradually from midday/midnight to dawn/dusk. But all polar orbits must precess like this since the plane of the orbit is fixed in space as the earth rotates about the sun.
Ian H
April 7, 2018 at 8:05 am
Ian, I am not very sure if I correctly get your point, but if it could help.
The “solar precession’ issue, in this particular subject, is not in regard of satellite’s navigator, or the navigating system.
it is or it could be a serious issue when considering the synchronization between it and the the time kipping as per recording of the data.
Some thing like the condition of the “Captains Cook daily record”.
The hourly timing on that record will be as per Captains belt watch or a mechanical time kipping clock , which over the time of see fairing adventure had to be synchronized to/by the navigator’s every day sundial time measurement (probably at midday 12:00 as per navigator’s sundial).
No synchronization in between, or a poor one will result in a considerable error over time, as per actual timing of the record taken and recorded.
For example, also, in a multi year record to be accomplished with a correct timing, in such cases, even the odd 366 day year could subject the process to a considerable degree of error, when such synchronization required, even when both, the navigation and record kipping in their own respective right do not have much problem with it……but still when a synchronization in between required, the odd year can be a pain that has to be dealt with, if the propagated error in such a case could end up messing the integrity of the record due to wrong time kipping.
Am not sure if this clearly enough put, or even that it may have any much sense.
Only trying to show that it could be a little more complicated than it may seem at first look at it.
cheers
At the peak of an interglacial period (in the past some have been sharp, some have been plateau-like), there may be decadal ups and downs. So all this .0001 accuracy nonsense is just that; nonsense. We are in a warm period. In general, we should be warmer compared to being on either an up-slope or a down-slope from/to a glacial period.
So someone discovers that some of our warm period sensors are a bit off. Fix it and move on. And if Nick gets nickers in a twist over what he believes to be data that is more accurate than something that was a bit off, well at least it keeps him busy and out of trouble.
As for me, I am glad it is warm. I don’t need to use as much wood heat and it is more fun fishing when it is warm than when it is cold. Except today I can’t go fishing because I did too much heavy lifting last week. All this is to say that it is WAAAAAYYYYY more important that I can’t go fishing today!!!!
LOL….amen
Must say: I told you so.
How many times did I mention that we cannot unilaterally trust the sats because of the destruction of anything in space that you want to use to measure> Especially now, lately, for the past few years, the sun’s rays are terrible.
Better to look at Tmax and Tmin at the stations. But you have to use the correct sampling procedure. Data sets (like Best) that are completely biased to the NH are useless, since there has been little or no warming at the SH.
there is an explanation here:
https://wattsupwiththat.com/2018/04/05/a-look-at-the-ghcn-daily-minimums-debunks-a-basic-assumption-of-global-warming/comment-page-1/#comment-2784761
I wonder if the contract between UAB and NASA stipulates periodic reporting when the Satellites go out-of-spec.
There is a big difference between sensible calibrated adjustments to correct wonky sensor data and adjustments based on just making data up (as in the NASA extrapolation and C&W infilling over the Arctic), guessed TOBS adjustments (based on an implausible error graph implausibly applied and uncalibrated) or the replacement of good data with poor data in the NOAA pause-buster adjustments. As for the newly warmed-up RSS graph, the fact that their reviewers did not include anyone actually qualified to review it says everything.
LOL,
Hey Nick Stokes and Moshpit, why don’t you guys explain to Tony he’s just imagining things, and Carl Mears is stand up guy…..he’d never do anything unethical. ROTFLMAO
https://realclimatescience.com/2018/04/climate-mafia-at-work/
One would expect that Dr. Carl Mears would know how to spell satellite, and that he would also notice that even after he changed the data there is still a very large discrepancy between the models and observations, with observations falling at the very lower end of the model range. But let’s look how he changed the data. He simply got rid of his error range (light blue) and moved the temperature (black line) up to the very top of his error range.