One of the big problems of climate science is uncertainty. Some things that always seem to be in flux are historical datasets, partly because, well, they have so much inherent uncertainty built in. Such is the case of the Historical TSI plot presented on the University of Colorado SORCE web page. All of the sudden, with little fanfare, it changed, and not just a little. What is interesting are the drops during the Maunder Minimum as well as our current Solar Cycle 24
Readers may know that a controversy persists as to the actual TSI behavior in the late 80s/early 90s. The so called “ACRIM gap” was created when the Challenger shuttle was destroyed in a famous accident due to mismanagement combined with launch pressure. It caused by the delay of the shuttle-launched ACRIM2, a satellite that was to maintain continuity of TSI measurements. The debate over how to bridge the gap is relevant to the explanation of the warming that persisted into the 90s. The debate has been quite heated, with those invested in the IPCC forcing story claiming that the TSI decreased in the 90s and those (Willson and Scafetta) who argued that the TSI continued to increase in the 90s.
Some previous TSI reconstructions:
Now there’s even more tinkering from SORCE:
http://lasp.colorado.edu/home/sorce/data/tsi-data/#plots
The SORCE TSI reconstruction looked like this a month ago (word BEFORE added):
Here is what it looks like as of today (word AFTER added):
They say this about it today:
This historical reconstruction of TSI is based on that used in the IPCC AR5 Working Group’s Assessment Report and based on TSI reconstructions by Krivova et al. (JGR 2010) and Ball et al. (A&A, 2012). The values from their SATIRE model have been offset -0.30 W/m2 to match the SORCE/TIM measurements during years of overlap and then extended using SORCE/TIM annual averages from 2003 onward. The historical reconstruction provided here was computed by G. Kopp using TIM V.15 data in February 2014, and is updated annually as new TIM data are available.
Download the ASCII data file
Explore the data interactively with LISIRD
Since the previous dataset wasn’t available to me to plot to show differences and comparisons, here is an overlay of the 2013 and 2014 image versions of the plot, scaled to fit properly since the Y axis changed in 2014 to accommodate the greater range:
They have changed the last three solar maxima and now show a clear roll-off since about 1975. Those are enormous changes since last year’s dataset.
Of note is the drop of about 0.3 w/sqm during the last minimum. You’d think they have a measurement handle on that with our current satellite platform, so you have to wonder why that would need adjustment.
Also of note is a drop of about 0.2w/sqm during the Maunder Minimum.
Not only is global temperature adjusted and is a constantly moving target, now so it is with solar irradiance. With so much input data in flux, the “uncertainty monster” of climate modeling output keeps growing.
h/t to Gordon Fulks and Aaron Smith
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Stephen Rasey says:
February 13, 2014 at 12:54 am
Change between the 2013 to 2014 versions makes a surprising wholesale displacement to the curve from about 1998 to 2013 of about 0.25 W/m2.
You are still not paying attention. It is not a surprise. Simply the result of improving measurement of the degradation of SORCE since 2003 and the adjustment necessary to correct for that.
Anthony noted it: You’d think they have a measurement handle on that with our current satellite platform, so you have to wonder why that would need adjustment.
Again, the current platform started in 2003 not in 1996. Adjustment since 2003 is needed because of improved calibration. This is what the data says. Should we ignore the data?
But Isn’t it fortunate they are changes in the right direction to nudge the GCM’s closer to historical temperatures in future runs? Lucky coincidence.
Not fortunate, just the way it is. And anyway, the change in temperature resulting from the adjustment is much too tiny to make any difference re the ‘pause’. You can forget about your conspiracy theories. They are juvenile.
here is my best guess of TSI back to 1700: http://www.leif.org/research/TSI-Reconstruction-2014.png. The assumptions are that variations of TSI are due to variations of the magnetic field. Two proxies for the magnetic field are the sunspots and the field in interplanetary space drawn out from the Sun by the solar wind. Below my guess you can see Schrijver et al.’s reconstruction of the ‘open flux’ [another measure of the Sun’s magnetic field]. Also plotted is the reconstruction by Kopp of LASP which is the topic of this posting [the curve is pink in my plot and [dashed] green in Schrijver’s.
“lsvalgaard says:
February 13, 2014 at 9:15 am
here is my best guess of TSI back to 1700: http://www.leif.org/research/TSI-Reconstruction-2014.png. The assumptions are that variations of TSI are due to variations of the magnetic field. Two proxies for the magnetic field are the sunspots and the field in interplanetary space drawn out from the Sun by the solar wind. Below my guess you can see Schrijver et al.’s reconstruction of the ‘open flux’ [another measure of the Sun’s magnetic field]. Also plotted is the reconstruction by Kopp of LASP which is the topic of this posting [the curve is pink in my plot and [dashed] green in Schrijver’s.”
Thanks leif
@lsvalgaard-I don’t mean to be a pain, but perhaps I should have specified that I wanted either a text file or a spreadsheet, not a picture. I can’t do anything with a picture.
timetochooseagain says:
February 13, 2014 at 11:57 am
I can’t do anything with a picture.
Be patient, I have to extract what you want from a much larger dataset…
@lsvalgaard-Sorry, I didn’t meant o be rude.
timetochooseagain says:
February 13, 2014 at 12:50 pm
Sorry, I didn’t meant to be rude.
You were not, I understand your eagerness 🙂
A suitable file can be found under http://www.leif.org/research/download-data.htm
Some of the other files referred to there are dead or obsolete links. Don’t go there. If you file frustrated go here http://www.leif.org/research/Frustration.gif
@lsvalgaard-Thanks, you’ve been very helpful. 🙂
Hypothesis: Some of the CMIP5 GCM in this plot from Spencer’s Feb. 10 post were run using the 2013 version of TSI reconstruction. If this is not true, then the rest of this post is void.
Prediction: at least some of the CMIP5 GCM will be rerun using the 2014 version of TSI reconstruction If the only inputs that change are the TSI profile, (lower pre 1880, higher 1880-1950, lower post 1996) then the GCM Anomalies output for 2000-2013 will decrease by 0.01 to 0.03 deg C (as per Leif 2/12 9:00am)
In the CMIP5 plot, the Mean of the 90 GCMs is about 0.25-0.30 deg C above the Observed data. So a -0.01 to -0.03 deg C change looks quite insignificant compared to the mean difference. There appear to be about 14 of the GCMs that are within 0.10 deg C of the past couple years. Maybe 30 that are within 0.15 deg. C.
More significant will be a change to the confidence interval.
For as set of 3 two-tail confidence intervals: (90%, 95%, 98%)
The probabilities of observations falling with in the low tail are:
(0.05, 0.025, 0.01).
Given a difference between mean and tail of 0.15 deg C
The implied Standard Deviations are: (0.0912, 0.0766, 0.0645)
Move the mean by an “insignificant” -0.02 without changing the std. dev.
Now the probabilities of observations falling within the low tail are
(0.078, 0.048, 0.022)
Under the old data what were
1 in (20, 40, 100) events are now viewed as
1 in (13, 22, 46)
We have effectively doubled the likelihood of the improbable result. Thus, the results and the models become harder to reject. with the 2014 Version of the TSI than with the 2013 version.
If the spread between mean and tail is 0.3 deg C, and we lower the mean 0.02, then the
1 in (20, 40, 100) becomes
1 in (16, 30, 66)
To use Janice’s terminology, a change in the TSI profile cannot not be the “resurrection of AGW”, but it can be used for the resuscitation of the GCMs. I predict the version change in TSI Profiles will be used to give the GCMs another couple of years of life.