NASA scientist, Josh Willis, was so concerned that his data, showing ocean cooling, did not fit the official consensus on climate change that he searched for a solution. Eventually he “applied a correction” so the historical ocean temperature record showed a relatively steady increase in line with the climate models.
Perhaps Dr Willis really did get it wrong between 2003 and 2005 when his data showed a large decrease in the heat content of the ocean. But after reading his justification for the correction, I am not convinced. Indeed and I am left wondering how to ever trust the official temperature record again.
This is Dr Willis’ story:
On a Thursday evening in February 2007, Josh Willis stood in front of his laptop, his wife cajoling him to get ready to go out to dinner. He looked with a sinking feeling at the map he had just made. Willis, a scientist at NASA’s Jet Propulsion Laboratory, specializes in making estimates of how much heat the ocean stores from year to year.
“The oceans are absorbing more than 80 percent of the heat from global warming,” he says. “If you aren’t measuring heat content in the upper ocean, you aren’t measuring global warming.”
In 2004, Willis published a time series of ocean heat content showing that the temperature of the upper layers of ocean increased between 1993-2003. In 2006, he co-piloted a follow-up study led by John Lyman at Pacific Marine Environmental Laboratory in Seattle that updated the time series for 2003-2005.
Surprisingly, the ocean seemed to have cooled.
Not surprisingly, says Willis wryly, that paper got a lot of attention, not all of it the kind a scientist would appreciate. In speaking to reporters and the public, Willis described the results as a “speed bump” on the way to global warming, evidence that even as the climate warmed due to greenhouse gases, it would still have variation. The message didn’t get through to everyone, though. On blogs and radio talk shows, global warming deniers cited the results as proof that global warming wasn’t real and that climate scientists didn’t know what they were doing.
That February evening, Willis says, he was updating maps and graphs with the data that had become available since the 2006 ocean cooling paper was published. He was preparing for a talk he had been invited to give at the National Center for Atmospheric Research in Boulder, Colorado. The topic was “Ocean cooling and its implications for understanding recent sea level trends.”
He was looking at a map of global ocean temperatures measured by a flotilla of autonomous, underwater robots that patrol the world’s oceans. The devices—Argo floats—sink to depths of up to 2,000 meters, drift with the currents, and then bob up to the surface, taking the temperature of the water as they ascend. When they reach the surface, they transmit observations to a satellite. According to the float data on his computer screen, almost the entire Atlantic Ocean had gone cold. Unless you believe The Day After Tomorrow, Willis jokes, impossibly cold.
“Oh, no,” he remembers saying.
“What’s wrong?” his wife asked.
“I think ocean cooling isn’t real.”
On the opposite side of the country, Takmeng Wong and his colleagues at NASA’s Langley Research Center in Virginia had come to the same conclusion. Since the 1980s, Wong has studied the most fundamental climate variable of all: the net flux of energy at the top of the Earth’s atmosphere—how much solar energy is coming in minus how much the Earth reflects and radiates as heat.
“Our team has been involved for many years in constructing time series of net flux from satellite data, going back to the 1980s,” says Wong. The observations started with a satellite mission called the Earth Radiation Budget Experiment and today are being made with Clouds and the Earth’s Radiant Energy System (CERES) sensors on NASA’s Terra and Aqua satellites.
Wong and his teammates’ record of net flux measured by NASA satellites shows that between the mid-1980s and the end of 1990s, the amount of incoming and outgoing energy at the top of the atmosphere crept out of balance. By the end of the period, about 1.4 watts per square meter more energy was entering the Earth system than leaving it.
Stitching the observations from multiple sensors into a coherent long-term record is complicated. Scientists are always looking for ways to check the accuracy of these pieced-together climate records. Since the ocean is the planet’s single biggest reservoir for surplus energy, the energy imbalance Wong and his colleagues detected in net flux observations ought to be detectable in ocean heat content, too. The connection between these two related, but independently measured vital signs of Earth’s climate brought Wong and Willis into collaboration in 2006.
“When Josh Willis published his first global estimates of ocean heat storage, we saw it as a chance to verify the accuracy of our energy balance time series against a completely independent set of measurements. Josh gave us data on ocean heat storage through 2002, and we compared it to our net flux estimates. There was good agreement, and so we published a paper on that together.”
“We continued to update our net flux time series each year, and we concluded that the positive energy imbalance that we detected previously remained the same,” says Wong. So he was surprised, even a little alarmed, when Lyman and Willis’ reached the opposite conclusion in 2006, saying that the ocean had cooled.
Willis admits the results were puzzling, but the apparent contradiction didn’t automatically convince him the ocean heat data were wrong. A large pulse of melt water from glaciers and ice sheets might account for a rise in sea level even as the ocean cooled and contracted.
The possibility that melting during the period had been large enough to offset a sea level drop became more remote later in 2006, with the release of several studies based on data from NASA’s Gravity Recovery and Climate Experiment, or GRACE, mission. Launched in 2002, the GRACE mission measures changes in Earth’s gravitational field over space and time. Changes in the gravity field are a sign that mass has shifted from one location on Earth to another, like the transfer of water to the ocean when ice sheets and glaciers melt.
When scientists began analyzing the first few years of GRACE data, they concluded that Greenland and West Antarctica were definitely melting and contributing to a rise in sea level. But, says Wong, “The amount did not seem to be enough to offset a cooling as large as they had reported.”
“We let Josh know, diplomatically of course, that all signs were pointing toward his data,” says Wong.
“I was aware that they were not seeing this huge cooling that we were seeing in the ocean,” says Willis. “In fact, every body was telling me I was wrong. And there were always doubts,” says Willis. “After all, it was a very surprising result. As a scientist, its part of my job to turn over every leaf. So I was constantly going back over the data and looking for problems.”
For nearly a year after the 2006 ocean cooling paper was published, nothing obvious turned up. It wasn’t until that next year of data came in that the cooling in the Atlantic became so large and so widespread that Willis accepted the cooling trend for what is was: an unambiguous sign that something in the observations was “clearly not right.”
When scientists mistrust their data, they do they same thing you do when you think your watch is off: they check another clock. To diagnose the problem in the Atlantic, Willis needed to compare ocean temperature measurements from multiple sources. The first source he turned to was sea level data from satellite altimeters.
Because water expands when it absorbs heat, and contracts when it cools, sea level is physically connected to heat content in the upper ocean. Satellite altimeters measure sea surface height with radar. The radar sends a pulse of energy toward the Earth’s surface and listens for the echo. The time delay and intensity of the echo reveal the altitude of the sea surface.
Willis also had ocean-based data sets, including temperature profiles from the Argo robot fleet as well as from expendable bathythermographs, called “XBTs” for short. XBTs are the equivalent of a disposable razor. A temperature sensor is spooled out behind a ship by thin copper wire. It sinks, making measurements at increasing depths, transmitting them back to the ship via the wire until the line snaps and the sensor sinks to the bottom of the ocean, discarded.
The devices are manufactured to free-fall through the water at a known rate; scientists infer the depth of the temperature measurements by the time lapsed after the sensor hits the water. They have been used by the U.S. Navy and oceanographers since the 1960s.
“Basically, I used the sea level data as a bridge to the in situ [ocean-based] data,” explains Willis, comparing them to one another figuring out where they didn’t agree. “First, I identified some new Argo floats that were giving bad data; they were too cool compared to other sources of data during the time period. It wasn’t a large number of floats, but the data were bad enough, so that when I tossed them, most of the cooling went away. But there was still a little bit, so I kept digging and digging.”
The digging led him to the data from the expendable temperature sensors, the XBTs. A month before, Willis had seen a paper by Viktor Gouretski and Peter Koltermann that showed a comparison of XBT data collected over the past few decades to temperatures obtained in the same ocean areas by more accurate techniques, such as bottled water samples collected during research cruises. Compared to more accurate observations, the XBTs were too warm. The problem was more pronounced at some points in time than others.
The Gouretski paper hadn’t rung any alarm bells right away, explains Willis, “because I knew from the earlier analysis that there was a big cooling signal in Argo all by itself. It was there even if I didn’t use the XBT data. That’s part of the reason that we thought it was real in the first place,” explains Willis.
But when he factored the too-warm XBT measurements into his ocean warming time series, the last of the ocean cooling went away. Later, Willis teamed up with Susan Wijffels of Australia’s Commonwealth Scientific and Industrial Organization (CSIRO) and other ocean scientists to diagnose the XBT problems in detail and come up with a way to correct them.
So the new Argo data were too cold, and the older XBT data were too warm, and together, they made it seem like the ocean had cooled,” says Willis. The February evening he discovered the mistake, he says, is “burned into my memory.” He was supposed to fly to Colorado that weekend to give a talk on “ocean cooling” to prominent climate researchers. Instead, he’d be talking about how it was all a mistake.
A scientist could hardly be expected to be happy about finding a mistake in his work after he published it. But if you have to watch your research go down in flames, it may help to regard it as an offering on the sacrificial fire of scientific progress. In the case of “ocean cooling,” Willis has plenty of reasons to consider the sacrifice worth it.
The first payoff for finding and fixing the XBT errors was that it allowed scientists to reconcile a stubborn and puzzling mismatch between climate model simulations of ocean warming for the past half century and observations. The second was that it helped explain why sea level rise between 1961-2003 was larger than scientists had previously been able to account for.
Much of what scientists know about how ocean heat content has changed over the past half century comes from the work of Sydney Levitus, the director of NOAA’s Ocean Climate Laboratory in Silver Spring, Maryland, and his colleagues. In the early 1990s, the United Nations Education and Scientific Organization (UNESCO) asked Levitus to undertake a scientific rescue mission.
The group wanted Levitus to locate historical ocean data sitting around in dusty library stacks, moldy basements, and forgotten filing cabinets around the world before they were lost to natural disaster or neglect. The project became known as the Global Oceanographic Data Archeology and Rescue Project (GODAR).
“Since 1993 or so, we have added several million historical temperature profiles. This collection allowed us for the first time to estimate the change in ocean heat content from 1955 on. When we first published these results in 2000, they received a great deal of media, congressional, and scientific attention, because the warming that we saw was consistent with what would have been expected due to the increased greenhouse gases in the atmosphere,” recalls Levitus.
What wasn’t consistent was several large bumps in the graph of heat content over time. “We saw an overall linear [warming] trend that was consistent, “ says Levitus, “but we also saw some very large interdecadal variability. In particular, toward the late 1970s, heat content increased substantially and then around 1980, it decreased substantially.”
“Those bumps gave everyone heartburn,” says Willis. There was no established physical explanation for them, and climate models didn’t reproduce them. The science community wasn’t sure whether the discrepancy cast doubt on the models or the observations, but fingers got pointed in both directions.
In mid-2008, however Levitus agrees that the interdecadal variability is substantially decreased, but it isn’t totally gone. He argues that before anyone assumes that the observations must be wrong, they should remember that the amount of variability they are talking about is probably less than the amount of heat gained and lost during the intense El Niño in 1997-98. “Climate models don’t reproduce El Niño events very well either,” he says, but no one doubts they are real.
Although he has “caused a stir” among his colleagues in the past by criticizing models’ inability to simulate how ocean heat storage varies on short-term time scales, he stresses, “I have said from the beginning that the fact that the long-term trends in models and observations do agree so well is what is most important.”
“My point is just that we need to remain open-minded because it may be that it is possible for the ocean to gain heat and lose it more rapidly than we think. There may be other phenomena [similar to El Niño] operating on different time scales that can explain interdecadal increases and decreases,” says Levitus. Even if these ups and downs don’t change the long-term destination of global warming, they could reveal more detail about what kind of ride we can expect.
For CSIRO scientist Catia Domingues and her colleagues, being able to show that climate simulations and observations were in better agreement than they previously seemed was only the first payoff of the corrections to the XBT data. The second was that they used the revised data to balance the sea level budget for 1961-2003.
The two main causes of sea level rise are melting of Earth’s frozen landscapes—ice sheets, ice caps, and glaciers—and thermal expansion. Water expands when it absorbs heat. If you add the amount of thermal expansion to the amount of melting, it should equal the observed sea level rise, but somehow, it never did.
“When scientists added these terms, the sum was always less than the observed sea level rise measured by tide gauges and satellite altimeters. It’s like one plus one did not equal two,” says Domingues.
Rising sea level is one of the most serious consequences of global warming. In the past 50 years, sea level rose about 1.8 (plus or minus 0.3) millimeters a year. Satellite observations since 1993 indicate the pace has accelerated to about 3 millimeters per year. What’s driving the acceleration? How much and how fast will sea level rise in the future? In trying to answer these questions, scientists repeatedly tried to balance the sea level budget, and they repeatedly came up short.
“Susan Wijffels and her colleagues from here at CSIRO, along with Josh Willis, provided a way to correct the XBT data, and so we took those corrections and made the first revised estimates of sea level rise due to ocean warming for the period 1961 to 2003. What we found was that ocean heating was larger than scientists previously thought, and so the contribution of thermal expansion to sea level rise was actually 50 percent larger than previous estimates.”
It seems that the main reason the sea level budget between 1961 and 2003 would not add up before is that scientists were underestimating just how much warming and expanding the ocean was experiencing. But what about more recent changes in sea level?
“In this analysis, we focused on 1961-2003 because it is the time period highlighted as being an important, unresolved issue in the last IPCC report [Intergovernmental Panel on Climate Change Fourth Assessment Report],” said Domingues, “but also because the problems with the newest Argo data—the problems that Josh Willis found as well as other problems we have identified—haven’t been totally solved. For the most recent years [2003-2007], the sea level budget once again does not close. Our team is still working on that problem.”
They are also exploring how volcanic eruptions influence ocean heating, and whether a better understanding of how volcanoes influence the energy balance of the ocean will help explain short-term variability in ocean warming and cooling.
“One thing we found was that climate models that do not include volcanic forcing tend to overestimate the long-term change, and their simulated decadal variability is not in agreement with the observations. On the other hand, the models that include volcanic forcing are more realistic in terms of decadal variability, but they tend to slightly underestimate the long-term warming,” she says. “This kind of result tells us volcanic forcing is important, but that we don’t totally understand it yet.”
If there is a moral to this story, it’s that when it comes to understanding the climate system, it’s hard to imagine too much redundancy. Every scientist involved in these studies says the same thing: to understand and predict our climate and how it is going to change, we need it all.
We need multiple, independent, overlapping sets of observations of climate processes from space and from the Earth’s surface so that we can create long-term climate records—and have confidence that they are accurate. We need theories about how the parts of the Earth system are related to each other so that we can make sense of observations. And we need models to help us see into the future.
“Models are not perfect,” says Syd Levitus. “Data are not perfect. Theory isn’t perfect. We shouldn’t expect them to be. It’s the combination of models, data, and theory that lead to improvements in our science, in our understanding of phenomena.”
References
2. Cazenave, A. (2006). How fast are the ice sheets melting? Science, 314(5803), 1250-1252.
3. Domingues, C.M., Church, J.A., White, N.J., Gleckler, P.J., Wijffels, S.E., Barker, P.M., and Dunn, J.R. (2008). Improved estimates of upper-ocean warming and multi-decadal sea level rise. Nature, 453, 1090-1094.
4. Gouretski, V., and Koltermann, K. P. (2007). How much is the ocean really warming? Geophysical Research Letters, 34, L01610.
5. Levitus, S., Antonov, J., Boyer, T., and Stephens, C. (2000). Warming of the world ocean. Science, 287(5461), 2225-2229.
6. Lyman, J. M., Willis, J. K., and Johnson, G. C. (2006). Recent cooling of the upper ocean. Geophysical Research Letters, 33, L18604.
7. Wijffels, S.E., Willis, J., Domingues, C.M., Barker, P., White, N.J., Gronell, A., Ridgway, K., and Church, J.A. (in press). Changing eXpendable bathythermograph fall-rates and their impact on estimates of thermosteric sea level rise. Journal of Climate.
8. Willis, J. K., Lyman, J. M., Johnson, G. C, and Gilson, J. (2007). Correction to “Recent cooling of the upper ocean,” Geophysical Research Letters, 34, L16601.
9. Willis, J. K., Roemmich, D., and Cornuelle, B. (2004). Interannual variability in upper ocean heat content, temperature, and thermosteric expansion on global scales. Journal of Geophysical Research, 109, C12036.
10. Wong, T., and Wielicki, B. (2008). Unscrambling the cause of recent ocean cooling with net radiation observations from the CERES instrument on the Terra satellite. (pdf). The Earth Observer, 20(1), 16-19.
11. Wong, T., Wielicki, B.A., Lee, R.B., Smith, G.L., Bush, K.A., and Willis, J.K. (2006). Reexamination of the observed decadal variability of the Earth radiation budget using altitude-corrected ERBE/ERBS nonscanner WFOV data. Journal of Climate, 19 (16), 4028–
Republished from NASA’s Earth Observatory with thanks.
Jennifer Marohasy BSc PhD is a critical thinker with expertise in the scientific method.
I really don’t see your problem. Bleeding edge science is always working with what we are discovering, what we don’t understand as well as we would like to. That’s how it has always been, and how it always will be.
Yes, we know that data and models are not perfect. Those of us who live in the real world run up against that knowledge every single day. It is academic fools–mostly tax supported–who are able to float about on disconnected theories, models, and data.
Willis being just one among many, who feel tremendous political, economic, and professional pressure to conform to the “consensus”. What a bloody mess! It will take decades to clean up this dishonest tangle of self-promoting lies and half-truths.
I would also disagree with your premise that data was changed. No data was changed. The errors in the data were found and adjusted. If you read the latest paper by Spencer and Douglass, they use data from weather balloons that has been changed because of errors in collecting the raw data that were not recognised at the time. Are Spencer and Douglass frauds?
Christy and Spencer claimed their satellite readings were correct, the models were wrong. No, the models were right, Spencer and Christy were wrong.
They don’t float around on it, that is the hand they have been dealt. The global climate is a massive, and complex, area of study. You can’t blame them for that.
Again this blog highlights a lack of scientific expertise in climate. Models are a statement of our understanding of physics. They are run on computers in difference equation form because partial differential equations cannot be solved analytically. They are a statements of what we know based on peer reviewed published science.
If the data do not agree with physics as we know it then you look at the data first and then if that fails you look at the physics. Yeah sounds strange, but when the physics dates back to the time of Isaac Newton and is based on the laws of conservation of energy, momentum and mass the chances are the data are a problem.
Once again physics has been proved right. The models spotted a problem with a new data type.
The same happened repeatedly with the MSU data, and indeed is likely to happen again soon as a very odd annual cycle in evident in the data of Spencer and Christy.
BTW latest surface data for October is trickling in. According to NASA-GIS October was the hottest on record for the globe. Will be interesting to see the NCDC-NOAA and CRU data.
“Eventually he ‘applied a correction’ “.
Sounds like David Jones and the BoM crew and their ‘data corrections’.. But to be fair to them, they are not alone, all public entities committed to ‘the industry’, are pressured to ‘conform’.
However, as a tax payer, I am affronted by such actions by publically funded agencies.
The initial substantial ocean cooling didn’t really ring true, the corrected 4 years or so of non-warming makes more sense, and does fit at least some models showing a step-wise warming. However, if the non-warming continues for a total of 5 years or more, then it will have departed from the models.
SJT doesn’t know what he is talking about, as usual – Douglas/Christy or Christy/Spencer haven’t been proven ‘wrong.’ There is more to come on this, with the obvious flaws in the Santer et al paper, and a response to come from Douglas/Christy/Singer.
Hmm. I believe the spam filter just ate my comment, so I’ll try it again without the http and backslashes on the links.
In “Reevaluation of Historical Ocean Heat Content Variations With An XBT Depth Bias Correction” (2008), Ishii and Kimoto proposed a bias correction methodology that resulted in the following Ocean Heat Content graph, which is Figure 6 from the paper.
Graph (Figure 6):
i38.tinypic.com/mlvno.jpg
Paper:
atm-phys.nies.go.jp/~ism/pub/ProjD/doc/Ishii-Kimoto-2008.pdf
We’ll just have to wait to see where the Willis corrections fall.
“We need multiple, independent, overlapping sets of observations of climate processes from space and from the Earth’s surface so that we can create long-term climate records…”
Um, dude, the instant you use a model to correct your data, it fails to be “independent”.
RSS and UAH are seeing October as nothing special. Must be the Arctic contributing to this GISS result. Another “independent” data source that interpolates based on climate models. Yeehah!
Not good enough Jen – if you’re going to imply their correction to the data is wrong or “another IPCC conspiracy” you need to state why.
Without such an explanation the whole title is utter bunk and is seen for what it is. Yet another excuse to have a go without any substance.
Willis has been remarkably honest. A real behind the scenes view.
And why are you selectively cynical on “corrections” – the greatest correction of all was with the UAH data that someone else eventually had to fix.
SJT and fellow Travelers,
How is that Ocean Rise from thermal expansion going y’all??
After a year and a half of DECREASING readings I guess the MSU people are down to CORRECT THEIR ERRORS!!!
Y’all are SOOOOOO gullible that you believe the errors are ALWAYS in favor of cooling and MUST BE CORRECTED TO WARMING!!!
Realistically and statistically ludicrous. Just like the AGW theory Fingerprint that must be supported with a statement like:
You can’t EXCLUDE the possibility that there is a hot spot!!
HAHAHAHAHAHAHAHAHAHAHA
Some of the passages such as this one:
““Basically, I used the sea level data as a bridge to the in situ [ocean-based] data,” explains Willis, comparing them to one another figuring out where they didn’t agree. “First, I identified some new Argo floats that were giving bad data; they were too cool compared to other sources of data during the time period. It wasn’t a large number of floats, but the data were bad enough, so that when I tossed them, most of the cooling went away. But there was still a little bit, so I kept digging and digging.””
are outrageous. Did he look for any floats that were giving erroneously warm data? Hell no. He had to rein in his dataset, and if that required “tossing” then so be it.
Dr david from BoM refers to “statements of what we know based on peer reviewed published science,” yet again. It seems to me that your “peer review” will be determined by which peers you decide will review something. So doesn’t that leave everything in the hands of the peer review reviewer? Some science!
He said “compared to other sources of data during the time period”, and it was only a small number of floats. He didn’t just pull figures out of a hat, he compared the new technology to existing technology.
So why not just use the old technology? This is selective cherry-picking and you know it.
I’ve got an idea, I’ll combine the GISS and RSS datasets, but wherever GISS shows “anomalous” warming compared to RSS, I’ll just throw the data out. This is the kind of bullshit adjustment you’re endorsing.
I agree Luke, that Willis has been quite open in his findings and the adjustments he has made.
However is this not yet further proof of “rosenthals rats/ expecations” influencing science.
Our own bias , in Willis case that sea temps should be climbing, led him to look for reasons why the data may be wrong, and he duly found “reasons” to change teh data to fit his expectations.
Do you think he would have done this if the data had shown a greater warming than he expected?
Please note I am not questioning Willis’ integrity or scientific abilities, rather how the basis of our expectaions can so easily lead us to reach the conclusion we are expecting.
T
…so the contribution of thermal expansion to sea level rise was actually 50 percent larger than previous estimates…..
…..the sea level budget once again does not close. Our team is still working on that problem…..”
….This kind of result tells us volcanic forcing is important, but that we don’t totally understand it yet…..
Just confirms that all this climate science is highly uncertain and highly speculative. Anyone who says the science of climate change is settled is either ignorant or a liar.
Yes Toby I do think he would have looked. He’s already discussed some XBT data being “too high”. Scientists aren’t sitting around working out how to cook the books. And data cannot be “adjusted” for any reason. Must be justified. i.e. sensor drift, calibration issues, noise, with satellite imagery – bi-directional reflectance, different platforms. All this is no real news to practitioners.
When trying to evaluate the accuracy of attempting to calculate the heat content of the oceans I would suggest taking a look at climate4you.com – global temperature- recent sea surface temperature. This is a satellite scan updated every few days and shows the sea surface anomaly around the globe. Considering the oceans cover 71% of the earth’s surface and the above map indicates a very mottled surface anomaly of between +3.5 deg to –3.5 deg C I really do not see how 3500 Argo floats could even come close to an accurate average. The paper by Carl Wunsch et al. Decadal trends in sea level patterns 1993 – 2004. Will introduce you to a number of some of the factors affecting the variability of the actual sea level itself, for example air pressure, salinity, tides and of course temperature. On top of this you have the precision of the actual measurement, the sea surface is not exactly a mill pond. In addition the paper presents some of the errors inherent in land based measurement systems so an accurate history of sea levels cannot exist and even modern methods are still subject to variabilities which are an order of magnitude greater than the measurement they are trying to determine.
While I will agree this was one of the more honest insights into the complexities that the IPCC supporters are still struggling with it does highlight the fact that all the bluff and bluster of 10 years ago and ever since is a massive hoax and to declare the science is settled and there is no longer any need to debate the issues, is utterly ridiculous. The only thing more ridiculous is the credibility our moronic political leaders around the world give these people.
Reading that it seemed that a big question was if the ocean is cooling then why do the satellites indicate the sea level is rising? For me there was not enough detail about the whole ocean, was he talking about more than the Alantic? I think so but not clear. The 4AR says again and again that Antartica is getting cooler. This year the sea ice reached the highest level since being recorded (about) 30 years. If the oceans are warming in some parts and cooling in others then surely this means a flow to reach equilibrium. El Nino, La Nina have an effect on rainfall I thought because of evaporation. Warmer seas for Australias northern areas means more rain. Can we measure the evaporation to find another indicator of ocean temperature.
david – “BTW latest surface data for October is trickling in. According to NASA-GIS October was the hottest on record for the globe. Will be interesting to see the NCDC-NOAA and CRU data.”
GISS has got some erroneous data. The September values for many of the Russian sites were carried over into October:
wattsupwiththat.com/2008/11/10/giss-releases-october-2008-data/#comments
Expect a correction.
It is unforgiveable of GISS to try to slip September temperature figures into the October anomaly and claim “unprecedented” “tipping point” anomalies. Absurd Hansen, he has slipped the leash for good.
Climate science has been taken over by Hansen-style paranoiacs and Gore-style politicos. People like Willis never really had a chance to do an honest job of it. It will take decades to clean the taint of political corruption from the science of climate.
In GISS’s defence, it was NOAA’s data that was the problem. However, look at this graphic:
rankexploits.com/musings/wp-content/uploads/2008/11/octobermap.jpg
+16C anomalies! If they were -16C anomalies you can bet that GISS would have caught the error.
Selective bias is pervasive in climate science, for alarmists and sceptics. The difference is that there are a helluva lot more alarmists.
The GISS October debacle is typical and makes it impossible to distinguish between honest mistakes and deliberate obfuscations, lies; as a rule smart people who make dumb mistakes are either under the influence or lying; Gavin Schmidt has been shot down by lucia so many times he must look like swiss cheese. On topic, the above report has Levitus and Domingues; all it needs is Barnett and his anthropogenic warming signal penetrating the ocean over the last 40 years to complete the distorted picture. In respect of Willis, his correcting paper, written with Lyman, Johnson and Gilson, notes in the abstract that “With biased profiles discarded, no significant warming or cooling is observed in upper-ocean heat content between 2003 and 2006.” However, in a later paper with Chambers and Nerem, Willis notes, “Despite excellent agreement of seasonal and interannual sea level variability, the 4-year trends do not agree, suggesting that systemic long-period errors remain in one or more of these observing systems.” Willis does confirm multiyear periods of little warming (or even cooling) without such events being contradictory to general warming, as per the Domingues study just prior. The miracle of this conclusion is that not only are the ARGO measurements and satellite information continually being fiddled but that prior sea level and sea-temperature measurements were very dubious (ie the Bucket case); in their study Cabanes et al (2001) examined sea level trends between 1950-1998 and concluded that sea temperature trends were entirely regional and, to the extent that gauge measurements were acceptable, that sea level trends were also regional. A subsequent study by Volkov and van Aken (2005) concluded that global sea level movements may be part of “interdecadal fluctuations.” Finally, in another serve at Schmidt and a back-hander to Domingues, lucia has shown that sea temperature movements, as modelled, have drastically underestimated lingering volcanic effects;
http://rankexploits.com/musings/2008/sea-level-rise-are-differences-in-trends-due-to-weather/
For the Pro AGW people who form the main cheer squad of Hanson and GISS….. GISS has made a huge error for Octobers anomaly…. They used SEPTEMBERS average…. D’oh!!!
So the October anomaly ain’t 0.78 as is now in the Graph… It is much, much less…. But Napoleon already knew that back in 1812. October is not a very nice month to be in Russia in summer clothing! 😉 LoL
It astounds me that such important data and its subsequent post collection processing is ostensibly in the hands of one person, and the Govt entity that owns the data and systems, and pays these tossers their salaries, has not itself signed off on the results.
Its no wonder the dopey yanks have about bankrupted themselves and the rest of the free world with their subprime mortgage fiasco.
Couldnt run a piss up in a brewery.
Malcolm Hill…. Don’t go knocking all dopey Yanks…. Just the Socialist ones that dominate the Democrat party and retired into comfy jobs on Fanny Mae’s board of directors, etc…..
As for Climate science… Ever since Scientists sold their souls for funding, in order to justify political policies…. Scientific Method has been lost to Society. The concept no longer exits.
Didn’t you read the post? The Russian data had errors in it. No-one slipped anything in anywhere. Now, if they fix up those errors, does that mean they are corrupting the raw data?
How about we actually have a real observations data base somewhere where we can all look back at the original unaltered uncorrected data…all these alterations and corrections just leave a “bad taste in the mouth”. Anyone can seemly come up with an excuse to alter data anytime to prive their point. Real observations and evidence don’t seem to even exist anymore, “it’s all smoke and mirrors” I’m afraid. Science has gone crazy and God help us all to have any meaningful unpoliticized research anymore!
The much respected (here) UAH satellite record is very much an artificial set of data. The satellites cannot directly measure the temperature of the lower troposphere, so it must be interpolated from other data. For some reason, all of a sudden that doesn’t matter.
Ian,
Your suggestion is spot on. It does leave a nasty taste in ones mouth to think that it is all so secret.
Only an elitist few can have access, and the same few decide how it is to be post processed and interpreted before it gets “published”, and in an equally elitist and just as shonky peer review system. What ever happened to academic neutrality, and integrity, open to public scrutiny.
Sorry, Jim Hansford, I will have a go at the dopey yanks, because these are the same people who bred and cultivated that arch shonk Al Gore, so that he could rip them off for about $200m,( at last count) and the natives are too stupid to realise it– or they condone it.
The scientific fraternity rave on about only the suitably qualified can comment on climate science but Gore is a Failed Divinity student, who has published nothing, but who is fawned upon by the Govt funded scientists in USA and elsewhere, who most notaby DONT correct any of the many and varied errors in his AIT, ie they are, and have been, conspicuosly silent, and therefore complicit.
—and for this the leftist Norwegian Parliamentarians gave him a share of Nobel Peace prize.
Mind you they also gave one to Arafat and Carter, so the standards are not that high.
I was happy there for Luke for a while – given all the sh#t you guys dump on him – he seemed gleeful that the October anomaly was up and that the planet, for a few days at least, seemed more likely to be doomed.
WTF does October’s anomaly even matter. Just fodder for denialist wiggle watchers.
Luke,
“WTF does October’s anomaly even matter. Just fodder for denialist wiggle watchers.”
if it doesn’t matter why was it published by Hanson?
You seemed very happy at the time…
“Models are not perfect,” says Syd Levitus. “Data are not perfect. Theory isn’t perfect. We shouldn’t expect them to be. It’s the combination of models, data, and theory that lead to improvements in our science, in our understanding of phenomena.”
There is one problem with this statement – Data cannot be perfect because there is no such things as perfect data, only data. You deal with what you measured and if you discover that your previous measurements produced unreliable data that caused you to form erroneous conclusions, then that’s science, and you re do the experiment.
Reading the various pomposities written here by the useful idiots, quoting their favorite climate guru, one thing stands out – a disconcerting ignorance of sampling theory in which no documentation is supplied showing what the sample support of some measurements are based on.
But to opine that data are imperfect is to assign a particular status to data that the data can never have.
There is no such thing as imperfect data, only data.
Luke: “if it doesn’t matter why was it published by Hanson?”
Pauline?
I thought it might have been Hansen? And don’t blame it on a typo qwerty-face, “e” and “o” are at the opposite ends of the keyboard.
Perhaps your lapse might be attributed to “AGW induced post Obama stress syndrome”.
Jen, There’s some weird thing happening with the left margin of these comments (on Explorer). I only mention it because its making me feel like I’ve had a bottle and a half of Pinot Noir, and yet I’m sure I’ve only consumed a bottle and a quarter.
Luke: ” Scientists aren’t sitting around working out how to cook the books.”
Google ‘begging the question’ or the ‘petitio principle’.
Sub-marxist climate alarmists Luke and SJT are still perpetuating the myths about the UAH data, without showing any concern for the unresolved isssues and warm bias in the statistic known as the ‘global average near surface temperature.’
7 August 2005:
An artifact of the diurnal correction applied to LT
has been discovered by Carl Mears and Frank Wentz
(Remote Sensing Systems). This artifact contributed an
error term in certain types of diurnal cycles, most
noteably in the tropics. We have applied a new diurnal
correction based on 3 AMSU instruments and call the dataset
v5.2. This artifact does not appear in MT or LS. The new
global trend from Dec 1978 to July 2005 is +0.123 C/decade,
or +0.035 C/decade warmer than v5.1. This particular
error is within the published margin of error for LT of
+/- 0.05 C/decade (Christy et al. 2003). We thank Carl and
Frank for digging into our procedure and discovering this
error. All radiosonde comparisons have been rerun and the
agreement is still exceptionally good. There was virtually
no impact of this error outside of the tropics.
The UAH LT data tells us that:
When one takes into consideration that the cooling from the Mt. Pinatubo eruption and the warming from the 1997-98 El Nino event were not part of any underlying long-term trend, we can imagine that globally-averaged temperatures were flat from 1990 until 2000, then there was a brief warming until about 2002, after which temperatures have once again remained flat. Note that the longer temperatures remain flat the greater the warming that will be required to put us back ‘on track’ to match the climate model projections used by the U.N.’s Intergovernmental Panel on Climate Change.
Thanks for the radiosonde reference. Another area of measurements that have needed to be adjusted.
http://www.climateaudit.org/?p=3062
Which leaves with UAH and Christy and Spencer in the same boat as Willis. Did they check their radiosondes against the satellites, since the radiosondes need adjusting, as Spencer himself knows,since he uses RAOBCORE himself, or did they calibrate the satellites against the radiosondes?
SJT:
Satellites are always calibrated in terms of radiosonde data, and as radiosonde data are primary forms of data, why correct them?
You do know what you are writing about, don’t you.
Will, you are particularly left field tonight; Spencer and Christy have addressed both the differences between UAH and RSS and the issue of radiosondes many times; here is one;
http://ams.confex.com/ams/pdfpapers/68728.pdf
RSS did diverge from UAH in the 90’s in respect of having a slight warming trend; this was due, as much as anything, to the fact that RSS has a different latitudinal spread than UAH which takes in slightly cooler latitudes; now both RSS and UAH are converging and showing general cooling.
On another note, Plimer was interviewed on ABC business tonight by a typically smug, stupid ABC interviewer and was excellent; lucid and logical compared with the outrageous gobbledegook served up by AGW leading lights like Flannery and Kaoraly.
September ’08 was the hottest October on record. See flaws in GISS’s October figures at Watts Up With That and climateaudit.org
Also, any more news on the Jason data? What is sea level doing?
=================================================
Sub-marxists ! LOL …. only subs – jeez …
Words like from a supposedly objective scientist this do tend to ring alarm bells
So the sea is cooling and he can’t bring himself to face it.
We than have The Huckster brook putting foeard the proposition that the Amazon could burn down. Yep, all of it.
Back in 2000 my friend and colleague Mark Lynas asked a simple but highly relevant question at a public meeting addressed by Professor Mike Hulme, the head of the Tyndall Centre for Climate Research. “If, as you have argued, the Amazon may burn down adding a further 3 degrees to global climate, that’s curtains for all of us, isn’t it?” This is exactly the kind of question one is never supposed to ask, and Hulme responded energetically to deflate it. “I do not think it is appropriate or useful for us to bang our drum about this- we need to use this information to generate a dialogue about our future options”. He didn’t answer the question because, dialogue or no dialogue, Mark was right. It is curtains, and scientists are remarkably unwilling to ever say this even when the conclusion could be solidly supported by their own data.
These people are seriously nuts.
It is good practice to always worry about your results, which means comparing them where obvious and possible to other results and thinking about non-obvious possibilities. NO SINGLE SET OF MEASUREMENTS STANDS BY ITSELF. The intercomparison drives needed corrections, a lesson you would think everyone had learned from the MSU measurements.
However, it is certainly clear that consistency is the playground of denial and that a bunch which does not worry their pretty little heads about spouting six impossible things at a go is very unimpressed by what Willis did. Eli will simply note that when RPSr was ecstatic about the original Argo paper, Eli pointed out that caution was needed and that when people jumped all over UAH for their many mistakes, he noted that they had the vision to attempt a difficult thing and mistakes were to be expected and corrections hoped for.
These are lessons you learn writing up results.
some one posted this on Steve’s site
The following web site is run by Professor Ole Humlum of Oslo University. It provides nuch historical information, news reports etc. It takes no position on climate change.
http://www.climate4you.com/
It’s an amazing site with excellent charts and graphics.
Spencer and Christy repaid Mears et al from RSS for pointing out that the UAH ‘error’ fell well within the quoted margin for error:
January 16, 2008
We discovered an error in our processing of AMSU data from NOAA-15 for TLT. A new version,
version 3.1 is now available and should be used for all applications. This new version is in much better agreement with other sources of tropospheric temperature. We apologize for any inconvenience.
What was the error?
Last January, I made a small change in the way TLT is calculated that reduced the absolute
Temperatures by 0.1K. But I only used the new method for 2007 (the error).
When the data are merged with MSU, MSU and AMSU are forced to be as close as possible to each other over the 1999-2004 period of overlap. This caused the error to show up as a downward jump in January 2007. To fix the problem, I reprocessed the 1998-2006 AMSU data using the newcode (like I should have done in the first place), and merged it with the MSU data.
We would like to thank John Christy and Roy Spencer, who were very helpful during the diagnosis process.
Carl Mears, RSS, January 16 2008
if willis was remarkably honest he would quit hiding his recent data… like i’m supposed to believe that the missing heat is hiding at the bottom of the ocean… if anyone is a fraud it’s willis
“It is good practice to always worry about your results, which means comparing them where obvious and possible to other results and thinking about non-obvious possibilities. NO SINGLE SET OF MEASUREMENTS STANDS BY ITSELF. The intercomparison drives needed corrections, a lesson you would think everyone had learned from the MSU measurements. ”
Excellent comment Eli now in reference to the ice core data what independent data is used to validate the IPCC’s CO2 history. Note that if the fundamental method is flawed then all results using that method are flawed. The same with computer programs if the program has errors and is based on false assumptions it does not matter how many times you run the program you will always get the wrong answer.
I think Paul Biggs made my point.
I just saw David’s comment about October being the hottest on record – LOL
Another NASA GISS cock-up using the data from September rather than October:
http://wattsupwiththat.com/2008/11/10/giss-releases-october-2008-data/
eli; you keep linking to my 10 best list and harping about the contradictions between Chilingar and Miskolczi, as far as I can see on 2 basis; firstly Chilingar doesn’t believe in atmospheric radiative transfer; which isn’t true; like M he says it just happens at the surface and is dominated by convective movement, as does M; M deals with the greenhouse effect, the LDR as allegedly confirmed by Philipona and others, Chilingar just doesn’t deal with this but accepts there is a greenhouse effect on the first 2 pages of his paper; Chilingar notes the wet lapse rate as accounting for 25% of the heat transfer from the surface and uses a temperature gradient of 6.5K/km for the dry adiabatic lapse rate, which is what his paper is about, which is more than “a few percent of the difference in temperature with altitude to convection” as you said elsewhere. As for M and lapse rates his theory disagrees with AGW which theorises that the wet lapse rate is increasing due to an increase in SH and a constancy of RH; Minschwaner, a co-author of the Dessler paper, has previously found a decline in RH, while evidence for an increase in SH is problematic with Dessler and Soden saying it is and NOAA saying it isn’t with Pan Evaporation decline posing the question of where the SH is coming from. The point of this is where the hell is the contradiction between Chilingar and M?
Excellent comment from RC on the anomaly business – http://www.realclimate.org/index.php?p=620 – really what a hard wank denialists are having over such things. But what is really fun is Santer putting McIntyre in his place as auditing god over at Climateaudit. Maccer might do something useful one day I guess. An innovative publication perhaps?
You are kidding again Luke –
1. Schmitt has been trounced in the SHM letters,
2. Prof Pilmer has told lateline biz AGW is bullshit
3. GISS have screwed up
4. Santer is behaving like a spoiled brat and being totally unscientific.
5. and Dr Karl is NOT DR Karl
that’s all wheels fallen off the AGW bandwagon including the spare.
try to reply without attacking someone.
luke; of all the mule-headed dumb things you have said your comment about Santer takes the cake; here is the primary author of a deeply flawed paper (they used a data period from 1979-1998!) who used esoteric data sorting algorithms who will not advise a legitimate person (ie a member of the public!) what those algorithms are; it is impossible, or nearly so, to work backwards because the algorithm may be variable or stage exclusive or god’s knows what; Santer has published a public paper on a crucial aspect of the AGW debate which effects all of us; the fact that he takes a high and mighty and dismissive tone exemplifies the rotten attitude of the pro-AGW crew and their dismal supporters which has been present from day one; the msm should be all over this issue of recalcitrance (Mann 1&2, Wahl & Ammann, Santer etc) by AGW authors to be fully transparent but they are content to publish egregious misrepresentations from Schmidt. This is not a debate about science, it is about pettiness and arrogance, all qualities of the AGW side. Despicable,
Compelling guys. Compelling ….. zzzzz
Why did Willis stop adjusting when the data fitted the models? If he’d kept going he could have claimed – “it’s much worse than we thought, global warming is happening much faster than in climate models.”
I don’t know why you people bother responding to Luke, he’s either as thick as a strainer post or the troll persona has taken over completely.
What a pain in the backside.
Excellent comment at RC? I don’t think so, and I think this response is on point:
http://rankexploits.com/musings/2008/what-is-gavins-point-about-the-role-of-models-a-response-from-the-excitable-part-of-the-blogosphere/
BTW, I think we should cut Josh Willis some slack. His conversations with Roger Pielke Snr suggest to me claims of dishonesty, etc. are intemperate at best.
Santer’s reaction to a request from McIntyre was petulant and embarressing. Not surprising however; the light thats been generated by McIntyre’s numerous posts have eviscerated Santer et al 2008. Dead man plus 17 walking methinks. And yes, Luke, I agree,I really think that analysis deserves at the very least the publication of a Comment in International Journal of Climatology.
BTW, sorry Neville.
Computer models were used to predict economic movement, look where that got us. Statistics were used to validate the clinical trials that got every recalled drug approved in the first place. Folks fantasy football is absolutely 100% interpreting statistics, yet the average participant is doing pretty well if he is 70% right interpreting data for 15 players over 16 weeks (240 data points). Its laughable that anyone believes these clowns when they claim to be able to measure the temperature of the entire earth over the course of a year within 1/100th of a degree (if they are even remotely scientific, assurances of temperature changes on the order of tenths of a degree, require accuracy of a hundredth of a degree. Sig figs. Crazy right?! I don’t buy it either). And this is using data from weather stations accounting for only about 10-15% of the earths surface, not the reams of data fantasy footballers have available to them.
Statistics are a joke. Computer models are a joke. The next time I hear someone refer to the use of models and statistics as “science” I’m going to go postal.
While this is a heartwarming tale of one man seeing the error of his ways, and taking the necessary steps to redeem himself, it is completely and utterly useless. In every field I’ve ever worked, you validate the model or the experiment BEFORE you perform it, not after, and certainly not after you publish it. If you don’t validate it, and get an unexpected result, you certainly don’t go back in, manipulate the data further, much less attempt to publish it again. Who are these people? Not scientists, that is for sure. The FDA requires validation, at every step of drug study and drug manufacture. Yet they still regularly approve dangerous drug after dangerous drug. So NEWSFLASH: Statistics are meaningless manipulations, and there is nobody WORSE at interpreting them than US Government employees. This is a fact, and there are reams of evidence to prove it.
People love to smell their own farts. And there’s no better way to do so than by talking in big grandiose terms about something you really don’t understand. Or to pretend to understand someone else’s big grandiose terms. Well I don’t buy it. These so called scientists are a joke, as is the whole Global Warming debate considering that there is not a single accurate, authenticated and unbiased data point that supports this alarmist political swindle.
I just don’t understand how the US can spend millions and millions on these scientific instruments and not have put them through some Quality Control before using them. I don’t reading that everything matches the predictions after corrections have been made, it leaves doubts in my mind. For all I know maybe the satellite needs retuning and has drifted giving higher ASL than they really are.
It’s all Smoke and Mirrors with the IPCC, NOAA, GISS etc.
“Models are a statement of our understanding of physics.”
No they are not, and if you knew anything you’d know that studying physics in a computer is a “closed” system and goes against the laws of thermodynamics. So all the proxies and manipulations is not credible. I can not believe how climate scientists are using computers to show physics of the real world as in a “closed” system and the absence of the biggest “open” system driver of climate change THE SUN. So stop with the computer games and go study real data.
“BTW latest surface data for October is trickling in. According to NASA-GIS October was the hottest on record for the globe. Will be interesting to see the NCDC-NOAA and CRU data.”
Riiiight, I guess the 150 cold records broken in Oct must be a mistakes or is it another bad data set?
Here’s why,
http://www.dailytech.com/Deja+Vu+All+Over+Again+Blogger+Again+Finds+Error+in+NASA+Climate+Data/article13410.htm
http://www.climateaudit.org/?p=4325
“In the last few days, NASA has been forced to withdraw erroneous October temperature data. The NASA GISS site is down, but NASA spokesman Gavin Schmidt said at their blog outlet that “The processing algorithm worked fine.”
“Schmidt blamed the failure on defects in a product from a NASA supplier and expressed irritation that NASA should bear any responsibility for defects attributable to a supplier:”
“Correcting Ocean Cooling: NASAChanges Data to Fit the Models Adjusts Data from Buoys”
What a horrible story. There is this Willis character basically being browbeaten to the point of brainwashing. And he does not seem to understand that he’s rigged the data.