2015 Global Temperatures

[StudentOfClimatology]

There is a very clear difference - everybody else here gets it except you. ORH gets it - he was agreeing with me.

One is a change in methodology.

The other is not.

End of story.

I don't think ORH is agreeing with you..certainly none of my professors would. In fact, I'm going to show this to my radiative physics/RS professor tomorrow..I'm sure he'll get a good laugh out of it.

Correcting for orbital drift would not be considered a change in the measurement methodology, it'd be considered a quality control adjustment applied after the O^2 microwave emissions have already been gathered and interpolated..a homogenization technique. The same thing GISS does when accounting for UHI influence.

If I took UAH data for the period 1979-1997 published in 1997 it would look nothing liked data for the same period that is published today. If I took GISS data for 1979-1997 published in 1997, it would look almost identical to GISS data for the same period that is published today.

I just linked them to you..the trend differential between 1979-1999 GISS (1999) and GISS (2014) for 1979-1999 is 0.083C/decade. The UAH adjustment was 0.096C/decade. So..0.013C larger than the change in the GISS data.

If you want to split hairs over 0.013C, which is within the margin of error of both datasets, knock yourself out.

This should adequately illustrate the difference to anybody that doesn't have their head up their arse. Again their have been changes to the GISS, HadCRUT, NOAA methods (the switch to HadCRUT4, the switch in ocean data for NOAA - although I think that was a forward looking change not a change to historical data) but the changes are not nearly as large.

Lol, GISS changed it's entire ocean surface interface just over a year ago to ERSST3..this was discussed here. It led to a statistically notable change in the trend since 1999, over 0.041C/decade. The last revision to UAH was in 2012, and it altered the trend by 0.062C/decade during the same period.

The former means that all past, present, and future results are changed because an inadequacy in the old method is discoverd - exhibit A is the revisions to satellite data in 1997 that were forced upon UAH by the critiques from RSS.

You're inventing these definitions, dude. Revisions to data are adjustments. Adjustments to data are revisions. Why did GISS switch to ERSST3 if the old ocean surface interface wasn't "inadequate"? Was it an adjustment to their data incorporation method? Or was it a revision to their data incorporation method?

The recent paper is yet another significant change in methodology.

What recent paper? The paper that tries to apply TMT diurnal noise correction to UAH using the decommissioned NOAA9 satellite? That paper?

What version of UAH are we on now? Version 5Cz14? When is version 6 coming again?

Version 5.6. Hopefully sometime soon.

In one case the methodology and associated results have been significantly revised multiple times (satellite sources) and in the other the methodology and associated results have remained fairly constant (GISS, HadCRUT).

Why you say stuff like this? The surface network results are "revised" constantly..monthly even. All this before they're even gridded and spatially interpolated. GISS and NCDC have both changed their ocean surface interfaces since 2010. This has led to a notable change in the observed trends in both datasets.

[skierinvermont]

I don't think ORH is agreeing with you..certainly no professional I know does. Correcting for orbital drift would not be considered a change in the measurement methodology, it'd be considered a quality control adjustment..a homogenization technique

 

Go ahead and ask him.

 

 

 

I'm going to show this to my radiative physics/RS professor tomorrow..I'm sure he'll get a good laugh out of it.

 

I highly doubt your professor gives 2c about you or some debate you had on a weather forum, but if you happened to be telling the truth, I'd ask your professor where are his papers in the AR5 rebutting Mears 2011?

 

 

I just linked them to you..the trend differential between 1979-1999 GISS (1999) and GISS (2014) for 1979-1999 is 0.083C/decade. The UAH adjustment was 0.096C/decade. So..0.013C larger than the change in the GISS data.

If you want to split hairs over 0.013C, which is within the margin of error of both datasets, knock yourself out.

 

As already pointed out you are comparing GISS meteorological stations only to GISS LOTI (land ocean temperature index). They're both global, but the former does not include the oceans. Yet again, you are making major errors and comparing apples to oranges to try and fit the data into your biases. 

 

 

Lol, GISS changed it's entire ocean surface interface just over a year ago to ERSST3..this was discussed here. It led to a statistically notable change in the trend since 1999, over 0.041C/decade. The last revision to UAH was in 2012, and it altered the trend by 0.062C/decade during the same period.

 

 

As I already said there have been a few modest (I would characterize a .04C/decade change for a 10 year period as modest) changes to GISS and HadCRUT4, but there have been many modest and large changes to UAH, RSS, STAR etc. (.1C/decade for a 20 year trend).

 

 

Why you say stuff like this? The surface network results are "revised" constantly..monthly even. All this before they're even gridded and spatially interpolated. GISS and NCDC have both changed their ocean surface interfaces since 2010. This has led to a notable change in the observed trends in both datasets.

 

 

Yes, the raw data is 'revised/corrected/adjusted' ... the methodolgy is not. The raw data is 'revised/adjusted/corrected' according to a consistent methodology that has seen few significant changes. 

[ORH_wxman]

SOC,

The big adjustment wasn't GISS from 1999 to 2014, it was GHCN. GISS interprets the GHCN

data almost the same as 1999 with a few minor changes.The data has to be homogenized before it goes into GISS or Hadcrut4 or NCDC and GHCN is that homogenized data.

Hadcrut4 actually uses some additional non-GHCN data as well for land temps and they do their own method to homogenize that data. But it's pretty similar to the way GHCN does it.

If you want to focus on adjustments that actually matter, I'd read up more on GHCN and not GISS or hadcrut4.

[AvantHiatus]

Not to go OT, but do they really have separate professors for remote sensing and radiative forcing? This whole argument is thoroughly full of BS that nobody can be 'right' anymore. Just be done with it instead of clogging the thread.

 

 

 

If you want to focus on adjustments that actually matter, I'd read up more on GHCN and not GISS or hadcrut4. 

Reoccurring trend with SOC. The next 10 years of data should hopefully be more completely calibrated and will put to rest all this garbage about hockey sticks and warming rate/decade.

[skierinvermont]

This whole argument is thoroughly full of BS that nobody can be 'right' anymore. Just be done with it instead of clogging the thread.

 

 

There is a right answer and it is found in the IPCC report. The AR5 concludes that surface temperature trend data is less uncertain than MSU or radiosonde trend data for TLT. 

 

Any statements to the contrary are false.

 

This has major implications for climate science because if UAH data were perfectly accurate (or really even remotely accurate) it would have serious implications for the water vapor feedback and it would mean that the water vapor feedback is much less than supported by theory or climate models. It would probably mean that climate sensitivity is about 1.5C less than it would be otherwise. 

 

But since UAH data is not considered at all reliable, climate sensitivity is still generally predicted to be around 3C. If UAH were perfectly accurate, it would automatically mean climate sensitivity is around 1.5C. You don't see many climate scientists (other than Spencer who isn't really a scientist at this point) claiming 1.5C is the most probable climate sensitivity do you?

[AvantHiatus]

There is a right answer and it is found in the IPCC report. The AR5 concludes that surface temperature trend data is less uncertain than MSU or radiosonde trend data for TLT. 

 

Any statements to the contrary are false.

Understandable. There is such a large divide in here over an issue that is according to you, has been resolved with great confidence by the mainstream science. Either there is not great certainty or someone was spouting some major BS.

 

After this, I might not be able to take SOCs posts seriously anymore.

 

 

We developed an observationally based diurnal cycle correction to remove the influence of satellite diurnal sampling drifts on long-term tropospheric temperature trends. This is important because other analyses (RSS and NOAA) used a model-derived diurnal cycle correction and questions have been raised about the validity of this bias correction. Trends from our work are in accord with trends from global circulation models and basic theory. 

We also found that the model-derived diurnal cycle correction used by RSS and NOAA is similar to our bias correction. The tropical tropospheric trend from the present study is 2.5 times that from another group, UAH. While this work shows that it is possible to understand discrepancies between MSU/AMSU datasets

there are still important differences between the datasets that need further scrutiny.

In short, the Earth is warming, the warming is amplified in the troposphere, and those who claim otherwise are unlikely to be correct.

[skierinvermont]

Understandable. There is such a large divide in here over an issue that is according to you, has been resolved with great confidence by the mainstream science. Either there is not great certainty or someone was spouting some major BS.

 

 

There is still uncertainty in surface data absolutely - but it is not as great as with MSU based products. Most people familiar with the data and revisions that have taken place over the years get this. It's a plainly stated conclusion that I quoted from the AR5. Even among people on this forum I think most people get that, although some might be loathe to admit it. 

[StudentOfClimatology]

You thinking using big words will make you sound smart? Structural uncertainty simply means all uncertainty inherent in the methodology (IE it includes the uncertainty of the method itself, but also uncertainty that comes from choosing one method over another method).

Correct, AR5 is referring to all *statistical* uncertainty that arises from the measurement process. This includes year to year statistical variability, which is in fact a much larger source of error potential in the satellite data due to changes in tropical convection that contaminates the IR in the relevant 50-60 GHz spectrum.

Orbital drift is the other big "uncertainty" referred to by AR5, but it is much easier to correct for than the shorter term phenomenon.

The AR5 is very clear that they are talking about the uncertainty of the long-term trend. It uses the words 'trend' specifically. They're not talking about regional or short-term stuff that you claim they are.

They talk about both, actually..I never said they don't mention multi-decadal uncertainty. I had to read this portion of AR5 as a condition of the completion my of AS105 course. I don't think you've read the entirety of AR5. Have you?

Do you want me to link the portion of AR5 that discusses interdecadal error potential? Because that's where the literature agrees the majority of the uncertainty lies.

Again, here are the quotes:

"For large scale trends... uncertainties were concluded to be on the order of .1C/decade."

Yes, Mears et al 2011. I've read that paper..have you?

It's probably worth noting that it uses the very radiosonde data that AR4 struggled utilize due to inconsistencies, was rebutted more than once, and also found the highest degree of error potential of any study in over 8 years.

Whereas a comparison between GISS and NOAA published in 2005 would still be valid today because the data has not changed.

This is false. GISS just changed it's entire ocean surface interface.

"Despite unanimous agreement on the sign of the trends, substantial disagreement exists among available estimates as to the rate of temperature changes."

Yes? They're referring to the differences between the MSU/AMSU sounding units.

[StudentOfClimatology]

SOC,

The big adjustment wasn't GISS from 1999 to 2014, it was GHCN. GISS interprets the GHCN data almost the same as 1999 with a few minor changes.The data has to be homogenized before it goes into GISS or Hadcrut4 or NCDC and GHCN is that homogenized data.

I said this two days ago, though, and skier disagreed. See below:

It's not "GISS's methodology", it's the ever changing homogenization techniques in UHCN et al and independent aggregated interfaces that are largely responsible for the significant changes to the observed surface temperature trend(s).

Not only did the cumulative "adjustments" to the global surface station network since 1979 lead to a larger overall change in the temperature trend, but they were also much more frequent.

Whether you call them "revisions" or "adjustments" is irrelevant.

This might be the most pointless debate I've participated in, considering the trend of each respective dataset is within 0.05C/decade of the other..all within the margin of error.

[StudentOfClimatology]

Of all things statistical, I assumed the "structure" of a trend would be easy to understand. "Structure" refers to the sign, shape, and the internal variability of a given trend.

The UAH/RSS trends diverge significantly after 1997, particularly in shape. These *structural* differences lead to a difference in their respective aggregated trend lines.

[skierinvermont]

Correct, AR5 is referring to all *statistical* uncertainty that arises from the measurement process. This includes year to year statistical variability, which is in fact a much larger source of error potential in the satellite data due to changes in tropical convection that contaminates the IR in the relevant 50-60 GHz spectrum.

Orbital drift is the other big "uncertainty" referred to by AR5, but it is much easier to correct for than the shorter term phenomenon.

They talk about both, actually..I never said they don't mention multi-decadal uncertainty. I had to read this portion of AR5 as a condition of the completion my of AS105 course. I don't think you've read the entirety of AR5. Have you?

Do you want me to link the portion of AR5 that discusses interdecadal error potential? Because that's where the literature agrees the majority of the uncertainty lies.

Yes, Mears et al 2011. I've read that paper..have you?

It's probably worth noting that it uses the very radiosonde data that AR4 struggled utilize due to inconsistencies, was rebutted more than once, and also found the highest degree of error potential of any study in over 8 years.

This is false. GISS just changed it's entire ocean surface interface.

Yes? They're referring to the differences between the MSU/AMSU sounding units.

 

All of the quotes yesterday were from sections discussing long-term trend uncertainty.. I simply didn't include the portions of the quote stating that they were talking about long-term trends... you then tried to claim that they were talking about month to month uncertainty.. which they weren't. Yet again, you're wrong and trying to squeeze things into your preconceived little box... with embarassing consequences like falsely claiming that the AR5 was talking about large month to month uncertainty when they're actually talking about long-term trend uncertainty... or mixing up GISS LOTI and GISS met station. 

 

 

And yes.. there is even more uncertainty on shorter timescales -- the short term uncertainty with MSU data is huge because of the calibration between old and new satellites. 

 

Nevertheless, the AR5 clearly states long-term trend uncertainty of MSU data is larger than surface data, as I have claimed throughout. 

 

 

The change in GISS ocean data did not yield a particularly large change in results - it changed a relatively short period of data a relatively modest amount. 

[skierinvermont]

Of all things statistical, I assumed the "structure" of a trend would be easy to understand. "Structure" refers to the sign, shape, an the internal variability of a given trend.

The UAH/RSS trends diverge significantly after 1997..these *structural* differences lead to a difference in their respective aggregated trend lines

 

Wait so first you say structural means height based, then multi-domainal, now you say it means temporal. Any more big words you'd like to try and impress us with?

 

In reality, it is really referring to errors in the structure of the method itself which may be difficult to calculate. 

 

For example, I could create a methodology to sample global temperature and calculate a sampling error of just .02C, however this would not necessarily include structural errors such as the uneven distribution of thermometers. 

 

 

This definition of structural uncertainty from the University of Sheffield Centre for Bayesian Statistics in Health Economics has nothing to do with temporal uncertainty:

 

"Structural uncertainty is present when we are uncertain about the model output because we are uncertain about the functional form of the model"

 

 

Structural uncertainty attempts to account for potential problems with the methodology itself. 

 

 

Yet again, you are caught red-handed talking out of your ass because you think you are smarter than you really are.

 

 

Wikipedia also defines structural uncertainty similarly:

 

Structural uncertainty, aka model inadequacy, model bias, or model discrepancy,

 

 

This again confirms what I have said throughout - it is simply uncertainty that may be left unaccounted for by the methodology because of a problem with the methodology itself. It has nothing to do with the literal temporal 'structure' of a trend. 

[StudentOfClimatology]

All of the quotes yesterday were from sections discussing long-term trend uncertainty.. I simply didn't include the portions of the quote stating that they were talking about long-term trends... you then tried to claim that they were talking about month to month uncertainty..

This is where you misinterpreted me..you need to slow down and read. I never said they were *only* discussing shorter term trends:

"Structural uncertainty" applies to all time resolutions..

Of all things statistical, I assumed the "structure" of a trend would be easy to understand. "Structure" refers to the sign, shape, and the internal variability of a given trend.

The UAH/RSS trends diverge significantly after 1997, particularly in shape. These *structural* differences lead to a difference in their respective aggregated trend lines.

AR5 referring to the fact that structural differences between the MSU/AMSU sounding units are greater than the structural differences between the surface station data..UAH/RSS diverge significantly after 1998 due to their different homogenization techniques.

They're not physically comparing the trends between surface station data and the TLT data as if they were analogous to one another..those are two completely different domains. This seems to be what you're implying, and it's wrong.

[skierinvermont]

They're not comparing the trends between surface station data and the TLT data..those are two completely different domains

 

That is exactly what they are doing. They first agree with Mears that the trend uncertainty with MSU data is .1C/decade, and then they say that this uncertainty is greater than the trend uncertainty for surface data which is clearly much smaller (more like .04C/decade - less than half the uncertainty). 

 

Unless you're telling me that .04C/decade is actually BIGGER than .1C/decade? Is that what you're telling me BethesdaBoy?

[StudentOfClimatology]

That is exactly what they are doing. They first agree with Mears that the trend uncertainty with MSU data is .1C/decade, and then they say that this uncertainty is greater than the trend uncertainty for surface data.

Huh? They're pointing out that the *structural uncertainty* between the respective trends of the UAH/RSS networks is greater than the respective differences between surface station networks, due to differences between the formers' respective homogenization techniques.

They're not physically relating the trend in the surface station networks to the trends in the low/mid troposphere, as if they were analogous. That would be buffoonery.

[skierinvermont]

An analogy for weather models might help.

 

Structural uncertainty is when the underlying physics in the model are wrong. Nothing to do with literal temporal structure of a trend as you claimed. 

 

Parametric uncertainty is when the parameters of the model are wrong. 

[StudentOfClimatology]

Unless you're telling me that .04C/decade is actually BIGGER than .1C/decade? Is that what you're telling me BethesdaBoy?

No, Andrew, that's not what I'm saying.

[skierinvermont]

Huh? They're pointing out that the *structural uncertainty* between the respective trends of the UAH/RSS networks is greater than that of the surface station networks, due to differences between their respective homogenization techniques.

They're not relating the trend in the surface station networks to the trends in the low/mid troposphere. That would be buffoonery.

 

They're not relating the trends themselves. They're relating the uncertainty in the trends.

 

They are saying there is greater uncertainty in the TLT trend than the surface trend. They say that the uncertainty in the TLT trend is .1C/decade, and they say the uncertainty in the surface trend is .04C/decade. And then they drive home the obvious.. .1C/decade is bigger than .04C/decade... and uncertainty in TLT trends is greater than uncertainty in surface trends.

 

I teach reading comprehension for a living.. and you clearly lack it. 

[StudentOfClimatology]

They're not relating the trends themselves. They're relating the uncertainty in the trends.

Seriously? That's what I just said..so you've finally come around?

Huh? They're pointing out that the *structural uncertainty* between the respective trends of the UAH/RSS networks is greater than that of the surface station networks, due to differences between their respective homogenization techniques.

They're not physically relating the trend in the surface station networks to the trends in the low/mid troposphere as if they were analogous. That would be buffoonery.

[StudentOfClimatology]

Also, what you're saying has morphed into something totally different. Originally you were rambling about the "difference" between surface network adjustments vs those of the satellite networks, none of which made any physical sense.

Now you're discussing the section of the AR5 report that discusses the fact that the structural uncertainty between the respective MSU/AMSU sounding analysis and subsequent trend lines is greater than between surface networks, which are in tighter agreement with one another.

No one can debate the latter..it's ground truth.

[ORH_wxman]

This argument has turned into a numbing rhetoric of semantics.

 

None of it really matters that much since the satellite TLT and sfc trends are pretty close to eachother since 1979. The difference is well within the error bars of the sfc data, nevermind the larger error bars of the satellite data trend.

 

There is valid criticism of both datsets, but in the end, it doesn't really amount to a heck of a lot that is actually substantial. The sfc has definitely warmed a bit more in the past couple years vs satellites, but these divergences are not uncommon at all on short timescales. There will probably be a period when the sfc is flatter and satellites are steeper at some point in the near future.

[skierinvermont]

My points have been clear throughout.

 

1) MSU/radiosonde long term trends are more uncertain than surface temperature long term trends (this is stated plainly in AR5 and is related to #2)

 

2) The methodologies for MSU products have changed more significantly and differ between products more so than for surface datasets. 

 

You have incorrectly disagreed with both points. If you've changed your mind, that's great.

[skierinvermont]

This argument has turned into a numbing rhetoric of semantics.

 

None of it really matters that much since the satellite TLT and sfc trends are pretty close to eachother since 1979. The difference is well within the error bars of the sfc data, nevermind the larger error bars of the satellite data trend.

 

There is valid criticism of both datsets, but in the end, it doesn't really amount to a heck of a lot that is actually substantial. The sfc has definitely warmed a bit more in the past couple years vs satellites, but these divergences are not uncommon at all on short timescales. There will probably be a period when the sfc is flatter and satellites are steeper at some point in the near future.

 

It's not semantics. See the above post. And it is significant to climate science.

 

If MSU/radiosonde data for TLT and TMT were considered as reliable as surface temperature data, then it would necessitate a much lower climate sensitivity than is currently theorized because tropospheric amplification would be non-existent which is key to the water vapor feedback. Obviously the scientific community doesn't put a whole lot of stock into MSU/radiosonde data which is why they're sticking with a most likely climate sensitivity range centered on 3C, not 1.5C. The assumption is still that tropospheric amplification and the water vapor feedback do exist, as predicted by theory, and MSU products (particularly UAH tropical TMT data) are just significantly underestimating it.

[AvantHiatus]

Good call Skier. The hidden agenda of SOC reveals itself yet again.

[StudentOfClimatology]

My points have been clear throughout.

1) MSU/radiosonde long term trends are more uncertain than surface temperature long term trends (this is stated plainly in AR5 and is related to #2)

Even if that's what AR5 was arguing, why do you trust Mears et al 2011, which relies on the forementioned radiosonde analysis in part to calculate uncertainty in the MSU/AMSU sounding analysis?

http://onlinelibrary.wiley.com/doi/10.1029/2010JD014954/full

Furthermore, Mears et al 2011 is a relative outlier with its uncertainty estimate, which is much larger than the 0.05C/decade estimate given by Spencer et al.

Sounds to me like preferential bias on your part.

2) The methodologies for MSU products have changed more significantly and differ between products more so than for surface datasets.

What methodologies have changed, and how? Be specific, please. I'm certain that you have no idea what these "methodologies" are in the first place.

You've been peddling this talking point for two days but refuse to elaborate on it. Just do it already.

[StudentOfClimatology]

Mears et al 2011 solely focused on RSS (and conflicts with the post-merging analysis used by Chedley et al 2014, which was posted here a few days ago). Recently published Penckwitt et al 2014 also contradicts allocating method of Mears et al 2011..treating one paper like gospel to buffer a theoretical talking point is just flat out silly.

Mears et al 2011:

http://onlinelibrary.wiley.com/doi/10.1029/2010JD014954/full

[1] Measurements made by the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit (AMSU) provide a multidecadal record of global atmospheric temperature change, which have been used by several groups to produce long-term temperature records of thick layers of the atmosphere from the lower troposphere to the lower stratosphere. Here we present an internal uncertainty estimate for the Remote Sensing Systems data sets made using a Monte Carlo approach that includes contributions to the total uncertainty from sampling error, premerge adjustments to each individual satellite, and the merging procedure. The results can be used to estimate uncertainties in this product at all space and time scales of interest to any specific application.

Penckwitt et al 2014 uses a completely different merging process:

http://www.atmos-meas-tech-discuss.net/8/235/2015/amtd-8-235-2015.pdf

As a major application, the VRT temperature record was used to verify the quality of the merging process of the MSU4 and AMSU9 channels of both the RSS and UAH groups. After removing systematic biases, the residuals relative to our iVRT data set 10 were examined for statistically significant break-points. No statistically significant steps were found in the residuals around the switch from MSU4 to AMSU9, confirming that both groups made appropriate adjustments in the merging process to assure a continuous temperature time series that is not affected by calibration errors between the two types of instruments or other systematic biases due to satellite drifts. Only in the two 15 polar 5◦latitude zones did our iVRT temperature record show an increase in variability in 2005 relative to the UAH temperature series.

[ORH_wxman]

It's not semantics. See the above post. And it is significant to climate science.

 

If MSU/radiosonde data for TLT and TMT were considered as reliable as surface temperature data, then it would necessitate a much lower climate sensitivity than is currently theorized because tropospheric amplification would be non-existent which is key to the water vapor feedback. Obviously the scientific community doesn't put a whole lot of stock into MSU/radiosonde data which is why they're sticking with a most likely climate sensitivity range centered on 3C, not 1.5C. The assumption is still that tropospheric amplification and the water vapor feedback do exist, as predicted by theory, and MSU products (particularly UAH tropical TMT data) are just significantly underestimating it.

 

 

Well if you are focusing on TMT data...sure...maybe. I was talking about the TLT data vs the surface.

 

I'll disagree with the climate sensitivity claim as it's been coming down some recently...esp using empirical data plus the IPCC's own best estimates on energy budget. Then there is whole debate of TCR vs ECS and which is more practical. But all of that is probably a topic for a different thread.

[AvantHiatus]

The overall current understanding of ECS is only valid if aerosols remain at their current concentration, which is unlikely in the the future. Aerosols impart a cooling of about 0.6C.

 

 

 

Independent of a possible aerosol effect on the carbon cycle, it is known that aerosols are an
important climate forcing. IPCC17 concludes that aerosols are a negative (cooling) forcing, probably between -0.5 and -2.5 W/m2. Hansen et al., based mainly on analysis of Earth's energy imbalance, derive an aerosol forcing -1.6 ± 0.3 W/m2, consistent with an analysis of Murphy et al. that suggests an aerosol forcing about -1.5 W/m2. This large negative aerosol forcing reduces the net climate forcing of 
the past century by about half.

[ORH_wxman]

The overall current understanding of ECS is only valid if aerosols remain at their current concentration, which is unlikely in the the future. Aerosols impart a cooling of about 0.6C.

 

This figure is pretty heavily disputed...newest paper on it:

 

http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-14-00656.1

 

 

But not surprising there is a lot of debate on it, because there is a lot of debate on sensitivity in the literature.

[The_Global_Warmer]

Not to go OT, but do they really have separate professors for remote sensing and radiative forcing? This whole argument is thoroughly full of BS that nobody can be 'right' anymore. Just be done with it instead of clogging the thread.

Reoccurring trend with SOC. The next 10 years of data should hopefully be more completely calibrated and will put to rest all this garbage about hockey sticks and warming rate/decade.

professors?

I'm guessing SoC said something about that. that does sound ridiculous.

anyways.

People need to get over this idea that if 6 months where a super nino causes a massive dump of heat into the LT Instead of being stored or spread into the ocean (see OHC).

It doesn't mean the Earth hasn't warmed since 1998.

What makes 1 year, 1 month, 1 day the benchmark?

Smooth that out to 3 years or 5 years and 1998 is blended completely in with how the atmosphere was then.

And its a lot cooler than today.

UAH is averaging a 0.33C for the year.

With tropics literally just at normal.

What do you think will happen if a major nino breaks out?

uah record is like 0.41c.

A major nino would certainly cause a 6 month period of 0.50 to 0.70c easy.

The earth has been collecting heat in the oceans the entire period.

I simply ask why have temps over Ice and land risen so much if radiative forcing isn't strengthening?