Reposted from Dr. Judith Curry’s Climate Etc.
Posted on January 10, 2020 by curryja |
by Frank Bosse
Equilibrium climate sensitivity computed from the latest energy imbalance data.
The Earth Energy Imbalance (EEI) is a key issue for estimating climate sensitivity.
If EEI is positive then the Earth’s climate system gains energy; if it’s negative the system loses energy, largely due to the energy flow into or out of the oceans.
A recent paper, Dewitte et al (2019), henceforth D19, derives changes in the EEI during the period 2000-2018, using data from the satellite CERES mission.
They shift the CERES values so that their average matches an EEI estimate from another study that is based on in-situ ocean heat content (OHC) data from ARGO buoys, and drift-correct them.
D19 concludes:
“At first sight it seems surprising that the EEI is decreasing during a period of continued greenhouse gas emission.”
Fig.1: The slightly decreasing EEI trend (green) during 2000…2018. (Source: Fig. 14 from D19)
It is indeed surprising that the EEI not climbed during the last 19 years when taking into account the ongoing increase of forcing, arising mainly from rising greenhouse gas levels.
In D19 the authors considered the plausibility of this outcome. They bolster the result with inspection of OHC data, calculating the time derivative dOHC/dt (which represent ~93% of the EEI) and the trend in it.
It’s not the only paper which estimates a near zero EEI trend in the 21st century. Also a review paper ( Meyssignac et al (2019)) comes to this outcome, see their Fig. 12 for 2006…2016. For a further check I calculated the derivative dOHC/dt for two year intervals, which are a measure of the EEI ( not the absolute OHC, see this report, section 2b) from three observational OHC products ( Domingues/Levitus; Ishii; Cheng) from this source.
The fourth cited dataset, Resplandy et al (2018), I skipped due to the retraction of the related paper, the mindful reader will remember.
The development of the EEI deduced from Cheng, this dataset was also used in L/C 18:
Fig.2: The dOHC/dt development with a 15 years Loess smooth
The result gives a very similar picture, indicating a near zero (or even a slightly falling) trend during 1999….2018 for the EEI.
What does this mean for the climate sensitivity?
Equilibrium/effective climate sensitivity (ECS) can be estimated as the (scaled) slope of the relationship between observed Global Mean Surface Temperature (GMST) and the excess of effective radiative forcing (ERF) over EEI, provided that the influence of natural climate system internal variability is small enough over the analysis period.
When there is an EEI standstill over a given period, then during this time the slope of the relationship between the observed GMST and the ERF reflects the climate sensitivity in equilibrium.
Sensitivity estimate for 1999…2018
The observed time span is very short for this purpose, only 20 years. This limits the toolbox available for doing calculations. In Lewis/Curry (2018) (LC18) the authors take changes between base and -final periods for both ERF and GMST data, see their section 4.
This avoids some pitfalls from the dilution problem of regression approaches which biases the slope estimations low. However, that method is only suitable with long enough time windows. Therefore I apply the regression method, including all annual data, in this case not using OLS (for Ordinary Least Square) regression but Deming regression. This method takes into account the uncertainties in variables from both datasets used, ERF and GMST, and should avoid the regression dilution problem.
The short time window will make optimizing the S/N ratio very crucial due to the fluctuating non-anthropogenic influences. Therefore I tried to reduce the “climate noise” in the GMST dataset- HadSST4 based Cowtan and Way (C&W) in this case.
I adjusted it for ENSO, solar and volcano influences, very similarly as was shown here. The “filter” was developed by Grant Foster aka “tamino”, released here.
The ERF data used are the same as used in L/C18, updated by the lead author to 2018.
Results
Fig.3: Deming Regression of the ERF on filtered GMST for 1999…2018 when the EEI was in a temporary standstill. All estimated natural forcing and ENSO variability was filtered out in the GMST, therefore the total anthropogenic ERF is used.
The trend slope reflects the observed climate feedback parameter λ (in W/m²/K).
The R² of the calculated trend is 0.88, which is a remarkably high value, when one takes the short time span involved into account.
The derived ECS best estimate (based on an ERF of 3.8 W/m² when doubling the CO2 content of the atmosphere) is:
3.8 W/m² / 2.21 W/m²/K =1.72 K
Conclusion
I calculated the climate sensitivity in a temporary standstill period (or slightly decreasing) as it was detected in the observations of the EEI during 1999 to 2018. The ECS value of 1.72K as the best estimate is in excellent agreement with the value found in LC18, 1.66K using the then current C&W GMST dataset (see Tab.3 of this paper).
The published ECS-values of the CMIP6 models have a mean above 4 K (see this recent paper) that is higher by a factor of 2.4 than observed here. This growing discrepancy between observed values of ECS reduces the credibility of the high model estimates.
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NH vs SH warming? Well look up videos of the work of Allan Savory and John D. Liu not to mention Anthony Watts and what he discovered with our Stevenson Screens. Where is most of the desertification and unnatural ground cover and I’ll even give Al Gore a mention in that regard-
https://www.theguardian.com/environment/2009/apr/28/black-carbon-emissions
Is that more relevant than their CO2 with any detectable anthropogenic warming? One thing I know with the really big picture is they have no correlation between the one true proxy for temperature in sea level movement and CO2 so they should be looking elsewhere for any possible dooming but they’re not. The Groupthink and hysteria is rather perplexing in that regard but science and the scientific method will prevail.
Speaking of deserts there’s one in the Pacific Ocean but then you all knew that because science is settled-
https://www.msn.com/en-au/news/techandscience/theres-a-desert-in-the-middle-of-the-pacific-and-we-now-know-what-lives-there/ar-BBYVh80
What! No nutrients from all that nasty human runoff on land and no warmening? Green Utopia.
@Julian Flood
Thanks for your comment!! I am finding your theory [that the warming of the oceans occurs due to contamination with oil/organics and general pollution] very interesting.
I have noticed that our ionic waste (especially phosphates, nitrates & sulfates) often stimulates algae growth and other primitive forms of live. I am sure this could also be a factor trapping heat in the oceans.
Is there perhaps a way we can prove the theory by actual testing?
J Flood..
Looked at your W.F.Trees link in more detail.
Cannot post links in here, but set the input parameters to 1850 instead of 1970.
You may be surprised to find that the situation you described with NH higher than SH also occurred in the period before 1900. It really does look like it is a cyclic behaviour as in the 1920 – 39 period it went into reverse..
I am sure (If we can trust the data), that something can be gleaned from the results.
I will leave it to other more specialised people to try and decode and produce any theories..
@Dave UK
Interesting. I am going it have a look at it. I wonder if it has to do with the GB cycle?
Click on my name.
It seems Dave UK is right. The rise between 1850 and 1880 was also much higher in the NH.
It must be the sun? Vuk?
Three things:
1. Estimates of ECS and TCR assume that all temperature changes are related to CO2 concentration. This allows hard-line skeptics to say “ECS is zero, recent warming is natural”. It also allows alarmists to say “there has to be (unspecified as to source) natural cooling of x, so ECS is really 1.7 + x”
2. Incoming is about 1349 w/m² and outgoing is about 1348 w/m². This makes measurement of EEI a classic case of “small difference between two large numbers”. Are they really measuring radiative fluxes with an accuracy of a small fraction of 1 w/m²? Authors citing the data don’t seem to be raising this question.
3. I keep speculating that the sw IR sensor must be detecting over a directional range of less than a half-space, otherwise it would pick up incoming solar when it crosses from night to day. Depending on the actual aperture angle, it is going to be more or less downward-looking. As such, interpreting the data must include theassumption that reflected sw comes from diffuse surfaces like clouds and snow, and that will make it omnidirectional.
But there will be a small amount of low-angle reflection that will come at the satellites sideways, and not be detected by downward-looking sensors. Low-angle reflection can come from calm seas and lakes and bare ice in Arctic regions when there is surface melting). Could the amount of this low-angle reflection be about 1 w/m²?
@Julian/ DaveUK
http://www.woodfortrees.org/plot/hadsst3gl/from:1850/plot/hadsst3nh/from:1850/plot/hadsst3sh/from:1850/plot/hadsst3gl/from:1850/trend
looking at SST from 1850,
actually shows less much less warming as well…
Is that really only 0.5K from 1850 till now?