In advance of my September 2018 global surface and lower troposphere temperature anomaly update, this is a very quick introduction to the new (over a year old) lower troposphere temperature anomaly data from RSS (Remote Sensing Systems)…just three graphs.
As you likely know, I haven’t published a monthly global temperature update in almost 2 years. Since then, in July 2017, RSS released their version 4.0 lower troposphere temperature (TLT) anomaly data. See the RSS webpage FAQ about the V4.0 TLT Update for more insights.
While preparing this month’s global temperature update, I downloaded the new global RSS TLT version 4.0 data for the first time and compared it to the UAH TLT data and to the three surface temperature datasets from NASA GISS, NOAA NCEI and the UKMO Hadley Centre—with all datasets starting in January 1979 and all referenced to the base years of 1981-2010. The new RSS TLT data shocked me, to say the least. (Expletives deleted.) See Figure 1.
Figure 1
Note that, from January 1979 to October 2018, the new RSS TLT warming rate is even higher than all three surface temperature datasets. Un-flip-flopping-believable!
That prompted me to compare the global (70S-85N) RSS TLT data version 3.3 data (still available here) to the new version 4.0 data (available here). See Figure 2. As illustrated, the new data has a noticeably higher warming rate. I actually said, “Wow!” aloud when EXCEL produced the graph.
Figure 2
And for anyone interested, Figure 3 presents the difference between the two RSS TLT datasets with the version 3.3 data subtracted from the version 4.0 data.
Figure 3
WHAT DR. ROY SPENCER HAD TO SAY!
Dr. Roy Spencer, co-author of the lower troposphere temperature anomaly dataset from UAH, published a couple of posts about the new RSS TLT data.
- Comments on the New RSS Lower Tropospheric Temperature Dataset, which was cross posted at WattsUpWithThat here.
- Warming in the Tropics? Even the New RSS Satellite Dataset Says the Models are Wrong
COMMENTS ABOUT THE NEW RSS TLT DATA, ANYONE?
I have a funny feeling this post will generate a couple of comments…hmmmm probably lots of comments at WUWT. Have fun!!!
That’s it for now. I’ll publish the full monthly update very soon. It’s almost ready. I just have to rewrite the text for the RSS data. Oy! I’ll try to remain civil.
STANDARD CLOSING REQUEST
Please purchase my recently published ebooks. As many of you know, this year I published 2 ebooks that are available through Amazon in Kindle format:
- Dad, Why Are You A Global Warming Denier? (For an overview, the blog post that introduced it is here.)
- Dad, Is Climate Getting Worse in the United States? (See the blog post here for an overview.)
Be back soon.
Bob
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The RSS team are decent scientists and have done a good work with version 4. The major change, an improved diurnal drift correction of AMSU-satellites, has been validated against the experimental reference series REF_SAT and MIN_DRIFT, which only use satellites with little or no drift.
UAH v5.6 had a similar approach, using non-drifting AMSU satellites mainly, and it also corroborates RSSv4.
As a comparison, UAH v6 is flawed in the AMSU-era, it has not been properly validated, and has a much lower trend than the old v5.6 non-drifting “reference” data .
Here is a comparison of UAH and RSS with state of the art (third generation) reanalysis data (TLT-weighted)
http://postmyimage.com/img2/249_RSS_UAHvsReanalyses.png
RSSv4 has almost the same trend as the reanalysis average, whereas UAHv6 lose around 0.06 C per decade.
UAH is particularly poor in the AMSU-era (starting in late 1998).
The graph also show the effect of UAH’s cherrypick of satellites.
The last MSU satellite NOAA-14, and the first AMSU-satellite disagree largely in the overlap 1999-2005. The UAH-team believes (without supporting evidence) that NOAA-15 is right and NOAA-14 is wrong, so they discard NOAA-14 data between 2001 and 2005, and arbitrarily adjust down earlier NOAA-14 data.
RSS on the other hand, acts in a scientifically correct way. They can’t find any error in either of the satellites, so the keep both and split the error. RSS wants their satellite product to be independent of other data, so they don’t use radiosonde, reanalyses, etc to choose the right satellite.
The above chart shows whether the choice of UAH and the non-choice of RSS makes sense in weather models (reanalyses are weather models that ingest all kinds of weather data and reconstruct
the likely state of the atmosphere)
Conclusions:
UAH drops like a rock between 1999 and 2005
RSS drops a little less here
Hence, NOAA-14 seems to be right and NOAA-15 wrong
UAH made the wrong pick of satellite, resulting in a too low AMSU-era trend
RSS is only half wrong since they didn’t choose and split the error.
I think you partially answered my question below. RSS acts unscientifically by averaging 2 satellites (the average of wrong data is wrong), and not using other sources to insure their data is correct. It is UAH that uses the radiosonde data to insure their numbers are correct. I incorrectly thought it was RSS.
Jeff:
“RSS acts unscientifically by averaging 2 satellites (the average of wrong data is wrong), and not using other sources to insure their data is correct. It is UAH that uses the radiosonde data to insure their numbers are correct. I incorrectly thought it was RSS.”
Except that UAH V6 does not agree with radiosonde data in the AMSU era aboard NOAA15 as well as does RSS v4 …..
So how can that be?
(h/t to Olof for graphs)
UAH is the cold outlier – here is a comparison of trends for various tropospheric temp series.
If UAH validate against radiosonde (as you say) then why is it so far away from RATPAC?
Much further than anything else…..
Because RatPac converges from other radiosonde data.
Its a “selected and adjusted” compilation.
And like all fabrications that are agenda driven, it shows more warming.
“Its a “selected and adjusted” compilation.”
The classic naysayers “and with one bound” response.
If you say so fred.
AB, so tell everyone how the average of radiosondes shows very little warming just like UAH6 and agrees better to RSS3.3 while RATPAC (which is supposedly based on those very same measurements) shows much more warming.
I’ve been waiting ever since RATPAC came out for someone to explain is little inconvenient truth.
RATPAC, pronounced Rat pack!
Jeff in Calgary,
UAH does NOT use “the radiosonde data to insure their numbers are correct”.
Their v6 AMSU data and significant “choices” have not been validated (and can’t be validated by any kind of relevant independent data). If I’m wrong, please show me the evidence.
What UAH did was a brief check of the overall trend (1979-2015) versus Ratpac B and Raobcore. Not surprisingly (from a cherry-picking perspective) these happens to be the two radiosonde datasets with the lowest trends, and not suitable for the purpose. Ratpac B is unadjusted after 1996 and has inhomogeneities. Raobcore is too circular since it is adjusted by reanalysis which are partly based on satellite data.
Anyway, with a proper difference chart it would be quite easy to see that UAH’s AMSU data and choices are not supported by Ratpac B: (a comparison to Raobcore would be similar)
http://postmyimage.com/img2/193_image.png
The picture is even worse compared to Ratpac A:
http://postmyimage.com/img2/732_image.png
If anyone believes that something is wrong with just Ratpac, here’s a comparison with the average of four independent radiosonde datasets:
http://postmyimage.com/img2/334_image.png
These charts were made after 2016, and to be honest, UAH has improved slightly since then. They introduced a new non-drifting satellite, Metop-B with data beginning in 2013, and all of a sudden the trend increased. This was simply because their lousy diurnal drift correction became diluted with good data.
UAH has also, for unclear reasons, avoided the non-drifting satellite Metop-A. This gold standard reference satellite (not needing drift adjustments) formed the backbone of UAH v5.6 AMSU data, and of course also the RSS datasets.
“…The RSS team are decent scientists and have done a good work with version 4…”
So these “decent scientists” must have done a piss poor job with versions 3.3 and earlier to be so far off.
“So these “decent scientists” must have done a piss poor job with versions 3.3 and earlier to be so far off.”
You could say exactly the same of UAH and V5.6. But in fact, they are both just dealing with a very difficult measurement problem. The proper response is to be sceptical of measures that can vary so much, even with best efforts.
I trust land based temps .
Just wondering Nick if your bank used the same method with your bank account would you be happy ?
“So these “decent scientists” must have done a piss poor job with versions 3.3 and earlier to be so far off.”
I seem to remember Roy Spencer saying much the same thing at the time.
Here’s the quote I had in mind. Dr Roy Spencer on the spurious cooling in RSS 3.3.
http://www.drroyspencer.com/2011/07/on-the-divergence-between-the-uah-and-rss-global-temperature-records/
Another classic:
Science expert via dint of reading a Blog.
Go look here to see how easy it is to be “piss-poor” ……
http://www.remss.com/measurements/upper-air-temperature/
that’s the problem with climate science olof ,people don’t seem to understand if something isn’t quite right,it is wrong. it would appear you don’t agree with that.
It is my understanding that RSS used balloon measurements to calibrate their sensors. So if this is the case, it is hard for me to believe that this big of a change would ever be needed. Is the new data better calibrated to the balloon measurements? I need answers.
Jeff:
“At RSS, we do not use radiosonde data to guide our choices when constructing long-term satellite datasets. This is done in order to try and keep the two types of data independent of each other. That being said, these results do suggest that our changes to the AMSU data are supported by the radiosondes (RSS V3.3 also shows a large cooling signal relative to the radiosondes over the 1998-2007 period). Note that all satellite data warm relative to radiosondes before about 2000, and then cool after about 2000. We don’t know if this overall pattern is due to problems with the radiosonde data, with the satellite data or (most likely) both.”
http://www.remss.com/blog/faq-about-v40-tlt-update/
This Roy Spencer’s take and his response to Olof R….
http://www.drroyspencer.com/2016/03/comments-on-new-rss-v4-pause-busting-global-temperature-dataset/
Olof R says:
March 5, 2016 at 4:10 AM
The difference between Ratpac A and B Global is that B is weighted by latitude only, whereas A is weighted by both latitude and longitude.
Thus, in A the oceans get a more fair representation. A has a slightly higher trend than B during the alleged pause years, because the troposphere over oceans (maybe a little contraintuitive) has warmed faster than over land during this period..
Roy W. Spencer, Ph. D. says:
March 5, 2016 at 5:55 AM
I’ve asked John Christy about the discrepancy…he’s the one who did the raob comparisons.
Roy W. Spencer says:
March 5, 2016 at 11:34 AM
OK, according to John Christy, it’s because you are using the 850-300mb layer to estimate MT, which is a little apples and oranges. You need to do appropriate weighting of all pressure levels up into the lower stratosphere for MT. If you use only 850-300, you won’t sample the statospheric cooling that MT includes, the warming trend will increase, and so you will get better agreement with RSS because it has a warmer trend.
Olof R says:
March 4, 2016 at 11:21 AM
Sorry, I posted this comment in the wrong place. I’ll better move i here were it was intended:
Well, this discussion is about the trend during the alleged pause years or AMSU years, ie from 1997-2000 til now.
The trends of UAH v6 TLT and RSS v3 TLT cant exactly be validated/verified by satellites or radiosondes:
http://postmyimage.com/img2/995_Tropospheretrends.png
All other reanalysis and radiosonde datasets agree with those above. The new RSS TTT v4 have a trend roughly the same as UAH 5.6.
Why should AMSU-5 on NOAA-15 be OK? Is it normal that the trend is 0.15 C/ decade lower than that of AMSU-4 (Mo 2009)?
Is it normal that AMSU-5 on NOAA-15 drifts versus the other AMSU-5s and makes the joint Channel 5 trend much lower than that of a weighted average of nearby Channel 4 and 6?
http://satelliteconferences.noaa.gov/2013/docs/Tuesday%20Poster%20Session%20Final%20Posters/T38_WenhuiWang.AMSUA%20Only%20Atmospheric%20Temperature%20Climate%20Data%20Records.NOAASatelliteMeeting2013.pdf
(free poster, there is a paywalled paper with the same title)
Roy W. Spencer, Ph. D. says:
March 4, 2016 at 11:46 AM
we have examined the NOAA-15 trends (unadjusted) as a function of height…channels 3,4,5,6,7,8,9….and ch. 4 is an outlier. Ch. 5 does not significantly depart from the vertical profile of trends produced by the other channels. The AMSU channel 4 has a history of problems on most of the AMSUs for some reason, including channel failures.
Olof R says:
March 4, 2016 at 12:43 PM
Yes, but in the AMSU-only dataset by NOAA STAR, state of the art intercalibrated and adjusted, AMSU 5 is the obvious outlier in trend vs the other channels.
AMSU 4, a TLT in itself, has a slightly lower trend than UAH 5.6 TLT over the 1998-2011 period, which is in the lower end of those trends suggested by radiosondes and reanalyses.
Even lower and true outliers are those datasets that make full use of AMSU-5 onboard NOAA-15. UAH 5.6 TLT is relatively immune against this spurious cooling contamination, since it relies relatively more on other satellites than NOAA-15, IMO…
In the NOAA STAR poster, it is quite obvious that there is a drift in NOAA-15 AMSU 5 versus the other AMSU-satellites, also after intercalibration, etc..
Data fiddling, sorry, data recalibration, to get at the desired result is the hallmark of a pseudo science. The data fiddlers are also known as quacks.
Yes, data fiddling is the right word. There is a lot of “divine interference” , unsupported by evidence, in the UAH v6 AMSU data. UAH v5.6 was much better, using nondrifing AMSU satellites only, that didn’ t need adjustment.
Ah shucks…..going to get harder to make those numbers look better with the cold wave that’s coming
Figure 3 patently displays an all-too-familiar pattern of trend exaggeration via a whole panoply of dubiously rationalized data adjustments. We’ve already seen similar increases of trend by GISS, HADCRUT and BEST in the successive versions of their respective GAST series. And then they have the temerity of pretending that such blatant trend manipulations produce scientifically improved data accuracy.
Direct (or indirect) cause of natural variability of the global temperature may not be currently well understood, thus a high correlation to the other natural variables should not be dismissed as irrelevant.
The old graph updated with the most recent data is here
I’m continually amazed by the amount of analysis, reanalysis, weighting, re-weighting, etc. that temperature data is subjected to.
“.. state of the art (third generation) reanalysis data (TLT-weighted)”
The “art” part seems more obvious, where temperature data is concerned.
I honestly don’t know the answer to the question that I am about to ask, and so someone fill in my ignorance:
“In what other field of science is data so artfully improved?”
Hi Bob T,
Just a tip to enhance readability of your figure 1 especially.
In Excel go to menu ‘Format’, click ‘Shape outline’ then ‘Weight’ then select most suitable line thickness.
Cheers, Bob Fernley-Jones
I did up this pair of graphs last night for a blog argument.
The top graph is snow cover extent anomaly data from Rutgers Snow Lab. The bottom graph is UAH NH LT land temperature anomaly from the data Roy Spencer puts up on his blog each month. So they are an apples to apples comparison, albeit lower troposphere for the temperature. I inverted the UAH y axis so that it would be easier to match peaks in the two graphs. They do match well: as you might expect low temperature equates to more snow cover.
I’ve included linear trends from mid 1994.
What these graphs show is that even UAH v6.0 is running too hot. The snow cover extent anomaly is a measure of the geographical area at or below 0 C. If the trend is flat it means the area isn’t changing, and therefore real world temperature isn’t rising. Since UAH and RSS are both rising it suggests the corrections being made for orbital decay and whatnot are introducing a warming bias.
But it’s pretty clear that snow is saying that not much is happening. You can’t fool snow, it’s easy to measure directly by satellite, it melts at 0 C and ignores adjustments.
How about plot 4 with the difference between RSS and one of the reconstructions from thermometer readings. How can the differences between versions be so noisy while measurements of two different things, although closely related, by a completely different method not be much noisier? (There obviously months with huge differences such as during the 1998 El Nino).
Please consult this paper published earlier this year. The information is in regard to the mid-troposphere, but is applicable to TLT since the same channels are used to generate TLT. In particular, note the reasoning behind all of our decisions, including the strong case for shutting off NOAA-14 early as it had drifted will past its time frame for diurnal corrections to be meaningful while NOAA-15 was the new AMSU with highly calibrated sensors which maintained a stable orbit for several years (and was in excellent agreement with NASA’s AQUA satellite). As noted in the paper, UAH and RSS (as compared with satellite datasets of NOAA and UW) had the lowest error rates relative to ALL of the radiosondes, with UAH a bit better. Note also the tropical plots and trend differences – demonstrating RSS tends to warm up more rapidly than the other various datasets (balloons and reanalyses). Both datasets are pretty good and I’ve advocated using the average of the two for a way to decrease the random error contained in both datasets and to reduce the effect of any unforeseen biases we each may have inflicted upon our datasets (I often do this in formal presentations, especially for comparison with models.)
https://www.tandfonline.com/doi/abs/10.1080/01431161.2018.1444293
Thank you
Doesn’t reanalysis use MSU/AMSU data for their model based re-constructions?
Also, as I recall UAH used to remove those scan positions which are impacted by precipitable ice (aka: hydrometeors). In your newest version 6 data analysis, do you still delete those and do you do so for both the MSU and AMSU data?
yes, reanalyses use satellites, but I don’t know the details of how they adjust for various drift effects.
Out current v6 does not do any precipitation screening… previous tests showed it has not effect on global trends, but certainly can affect interannual variability in certain regions, such as the regional shifting of deep convection during El Nino and La Nina in the tropical Pacific. Out new LT is less sensitive to precipitation effects than the old LT (RSS still uses the old way of computing LT).
Dr Spencer,
I would have thought otherwise, as there have been projections for increased storm intensity from AGW. Also, if one were to expand the definition of “tropical” to +/- 30 degrees, that might catch more of the intense tropical cyclones as they exit the +/-20 band and move into the mid-latitudes. Figure 1 from your 2018 paper shows the projected warming extending to that range. The cloud top temperatures from Michael were as low as -93 C (180 K). Panama City, FL is located at 30N.
Have/will you document those tests you mention? I’m sure lots of folks would like to see the reasoning and analysis behind your decision to exclude screening.
Thanks.
Dr Christy,
I understand that NOAA-14 has drifted outside the time frame for diurnal correction.
But the time frame for diurnal correction has increased since 2015, because NOAA-18 and NOAA-19 continue to drift apart. The problem is that you use the difference between two drifters to calculate the drift. An obvious limitation with your empirical drift correction. RSS’ hybrid model/empirical diurnal drift correction can handle NOAA-14.
I’m not astonished that NOAA-15 and Aqua agrees, because the drift (diurnal + other) in NOAA-15 is corrected with the difference to Aqua.
However, I don’t consider it wise to trust NOAA-15 (the first satellite of its kind, never tested in the field before) enough to let it run alone in space, before it is accompanied by Aqua (June 2002?).
The complete confidence in NOAA-15 and interference with NOAA-14 data needs a sanity check, ie it has to be supported by other/independent data.
Like this:
https://drive.google.com/open?id=181P3P7qKKGRLGJWENmEMgji4ulPEKEgp
As far as I can see, there is not a single dataset supporting UAH v6 during the NOAA 14/15 overlap period. NOAA 15 is likely rogue, having other drifts than the diurnal. Half of your diurnal drift corrections rely on NOAA-15. What are the consequences of an unknown drift on the TMT/TLT datasets?
Literally everyone I have talked to about temperature data adjustments by our record keepers looks at me with a confused look and says “Adjustments? Its just measurements right?”.
They have the whole world fooled. Thats why I say eventually, after enough adjustments, by say 2030, the ten plus years of the “Pause” in the early 2000s will be changed into the largest temperature rise in a ten year period in our planet’s history. Thats what happened to the 90s. When the century ended even Hanson’s summary on the decade (and the whole 20th century) said there was no meaningful trend in temperature one way or another. Then after 10 or 15 years of slowly making the data before 1950 cooler and the 80’s and 90’s data warmer, we now have this massive temperature rise in the 80s and 90s that wasn’t there in the data when the century ended.
I laughed – literally – at Figure 3. 0.25°C warming between 1980 and 2015, purely of adjustments between one version and another. Pathetically hilarious, were it not used as justification by the UN globalists for shutting down the developed world’s power generation and personal mobility.
My daughter’s going to have the same reaction when she sees it 🙂
Consider the many, many authors who did the research and wrote the papers – but used a temperature data set that has been discontinued because it was shown to be wrong.
Where are all of the science papers saying “Please disregard the finding from our paper on (such-and-such) because we now have to go back and do it all again because the temperatures were wrong”.
Don’t know about others here, but I have not been seeing the expected number of retractions and corrigenda, let alone the press releases announcing : “We were wrong … because temperature” – or “We were right more than we imagined … because temperature.”
Maybe we need to launch a new Journal of Temperature Adjustment Consequences.
Or just carry on as at present with the lackadasical “Don’t worry about it, we know it’s mainly guesswork so a bit more erroneous work won’t make any difference to our preconceptions. It is climate work, after all ….”
This is actually expected because RSS has taken on the warming error that UAH had before it. This was removed by UAH, but RSS implemented it with that recent data adjustment. UAH showed a warming bias back in the 2000’s that neither surface or RSS showed. RSS was cooling a little more than HADCRUT and especially GISS, but UAH was warming more than any of them. this was corrected now RSS resembles the error that UAH had and has not been corrected since.
Read the hrading as RSS TILT Data. Would be appropriate…