Climate Change Banter

[AvantHiatus]

Wow.... are you finally seeing the reality of what's happening?

I've always felt/thought this way, it's just an issue of the lesser of two evils for me and after Sandy I believe AGW is a greater evil than economic downturn. Without strong action this place is doomed way sooner than otherwise due to SLR. Kind of hopefully explains why i've been so fanatical lately. I didn't even know SLR would be a serious decadal issue locally until 2012/2013.

 

At risk of sounding selfish. I can understand why climate denial has grown so big (albeit leveled out somewhat in recent years).

[StudentOfClimatology]

The heat/forcing is there, the satellites are simply not picking it up on the same scale as the surface datasets. You can verify this by reviewing and comparing global and northern hemisphere SST anomalies, which are warmer than 2014 by a significant margin.

At this point, we have way better alternatives to measuring the global energy budget rather than relying on MTT data. More effective metrics on decadal scales include SLR and Ocean Heat Content. As a result, we already know the 2020's will be warmer than the 2010's due to the temporal lag between ocean and land temperatures.

Troposphere temperatures are unreliable/noise-prone and variable (subject to hadley cell dynamics, global wind speeds, etc), particularly in the way UAH assimilates the data.

This is a load of crap. The lower troposphere won't respond until sometime between October and January, as usual.

The 1997-98 Niño didn't spike the TLT until mid-late November. The 2009-10 Niño took until January to do it. The 1982-83 Niño took until mid December.

[StudentOfClimatology]

RATPAC has an average gridded spatial resolution 850km. That's horrible, and even getting there requires homogenizing for the lack of radiosonde coverage in remote areas.

There's a reason there are over 900 peer reviewed papers using the AMSU/MSU data for depth-based analyses, and under 50 that use the RATPAC sonde aggregation for the same purpose.

[nflwxman]

RATPAC has an average gridded spatial resolution 850km. That's horrible, and even getting there requires homogenizing for the lack of radiosonde coverage in remote areas.

There's a reason there are over 900 peer reviewed papers using the AMSU/MSU data for depth-based analyses, and under 50 that use the RATPAC sonde aggregation for the same purpose.

Source of that statistic, please?

[donsutherland1]

RATPAC has an average gridded spatial resolution 850km. That's horrible, and even getting there requires homogenizing for the lack of radiosonde coverage in remote areas.

There's a reason there are over 900 peer reviewed papers using the AMSU/MSU data for depth-based analyses, and under 50 that use the RATPAC sonde aggregation for the same purpose.

Its resolution notwithstanding, it has provided surface trends that are representative of those on the major surface data sets.

[nflwxman]

RATPAC has an average gridded spatial resolution 850km. That's horrible, and even getting there requires homogenizing for the lack of radiosonde coverage in remote areas.

There's a reason there are over 900 peer reviewed papers using the AMSU/MSU data for depth-based analyses, and under 50 that use the RATPAC sonde aggregation for the same purpose.

The resolution wouldn't matter as much over a 60 year period. In shorter timescales, it's impact becomes more evident.

[The_Global_Warmer]

The resolution wouldn't matter as much over a 60 year period. In shorter timescales, it's impact becomes more evident.

This.

[skierinvermont]

RATPAC has an average gridded spatial resolution 850km. That's horrible, and even getting there requires homogenizing for the lack of radiosonde coverage in remote areas.

There's a reason there are over 900 peer reviewed papers using the AMSU/MSU data for depth-based analyses, and under 50 that use the RATPAC sonde aggregation for the same purpose.

 

So? It's possible to form quality surface datasets with resolutions 10X that size. Quality over quantity. 

 

Your post strikes me more as a biased cheap-shot at a reliable peer-reviewed data source.

[frontranger8]

The resolution wouldn't matter as much over a 60 year period. In shorter timescales, it's impact becomes more evident.

Why don't people apply this same logic to the satellite data sets? Instead they get all wrapped up in short term stuff.

[donsutherland1]

The resolution wouldn't matter as much over a 60 year period. In shorter timescales, it's impact becomes more evident.

This is a key point. On a year-to-year basis, there might be some differences (though at least this year, the data closely fits the surface data sets). Over timeframes of 10 years or longer, RATPAC has closely matched the surface data sets.

 

IMO, the issue of possible spurious cooling on the satellite data sets, all of which require very complex calculations to try to account for factors such as diurnal drift, among others, is something that likely requires a closer examination, especially as satellites do not directly measure temperatures. That the satellite data has diverged from actual measurements (surface + RATPAC) suggests at least an examination of that issue is warranted. 

 

In fact, the accuracy of the present approach to satellite temperature estimates has already been raised in at least one academic paper with at least one major fix suggested:

 

http://www.theguardian.com/environment/climate-consensus-97-per-cent/2014/nov/07/new-study-disputes-satellite-temperature-estimates

 

http://link.springer.com/article/10.1007%2Fs00382-013-1958-7

[StudentOfClimatology]

Anyone putting faith in the RATPAC aggregation over the MSU/AMSU satellite networks is horribly misguided re: required homogenization and cross-verification. The former requires sunstantially more quality control despite utilizing only a fraction of the datapoints.

[donsutherland1]

Anyone putting faith in the RATPAC aggregation over the MSU/AMSU satellite networks is horribly misguided re: required homogenization and cross-verification. The former requires sunstantially more quality control and contains despite utilizing only a fraction of the datapoints.

Just because a data set requires more work to complete the product doesn't mean that it isn't reliable. The measure of reliability is whether it fits other measured data sets. RATPAC does. In stark contrast, the satellite estimates have been diverging from the measured data. That raises several questions:

 

1. How can the possible spurious cooling be explained?

2. What fixes will be applied to address that problem?

3. With regard to UAH v.6.0, which has a linear cooling trend relative to v.5.6 (in addition to the surface data sets) with a very high coefficient of correlation, where is the peer-reviewed paper to address that possible issue and lay out the adjustments?

 

The paper to which I provided a link addresses one of the problems related to such cooling (and the difference in temperatures is large). The proposed fix in the paper has not been applied to the satellite data sets (or at least no papers or web searches indicated such a fix was being made). It's been 3 1/2 months since v.6.0 has been released and no paper has been submitted for peer review. Why? Usually papers precede methodology changes, not the other way around, so that the proposed changes are reviewed in a robust fashion before being implemented.

 

In sum, the data divergence and unaddressed issues (including the brightness issue found in the paper) argue that perhaps there is greater reason to question the satellite-derived estimates than RATPAC.

 

Given the above, IMO, the satellites are part of the mix. Issues exist and improvements are almost certainly necessary given those issues. At this point in time, I don't believe one can say that the satellites are qualitatively superior to RATPAC, much less the surface data sets.

[nflwxman]

Anyone putting faith in the RATPAC aggregation over the MSU/AMSU satellite networks is horribly misguided re: required homogenization and cross-verification. The former requires sunstantially more quality control and contains despite utilizing only a fraction of the datapoints.

You are not so secretly a climate change skeptic, by the way. Your game is fairly obvious. Stop trashing your own integrity for the end game.

RATPAC uses several sensors. MSU products use ONE. Yes, color me skeptical when one sensor that requires several post processing techniques is being used to define the future of our planet.

[nflwxman]

Why don't people apply this same logic to the satellite data sets? Instead they get all wrapped up in short term stuff.

Not sure. Clearly it can affect a 10-15 year trend, but the datasets tend to converge at the end.

[StudentOfClimatology]

You are not so secretly a climate change skeptic, by the way. Your game is fairly obvious. Stop trashing your own integrity for the end game.

I'm not a skeptic at all (anymore). This board is just uninformed/out of the scientific mainstream on a lot of topics. It doesn't surprise me that you'd try and pull that one, though.

RATPAC uses several sensors. MSU products use ONE. Yes, color me skeptical when one sensor that requires several post processing techniques is being used to define the future of our planet.

At least now I know you're lying about your remote sensing education. There are 7 different MSU/AMSU satellites used in the UAH/RSS interpretations. Meanwhile, RATPAC uses no "sensors"..it is an aggregated sonde network.

[nflwxman]

I'm not a skeptic at all (anymore). This board is just uninformed/out of the scientific mainstream on a lot of topics. It doesn't surprise me that you'd try and pull that one, though.

At least now I know you're lying about your remote sensing education. There are 7 different MSU/AMSU satellites used in the UAH/RSS interpretations. Meanwhile, RATPAC uses no "sensors"..it is an aggregated sonde network.

Sondes are sensors....

Okay, so let's assume for a hot second you are not a skeptic. What dataset do you trust the most for empirical TCR and ECS calculations?

[StudentOfClimatology]

Just because a data set requires more work to complete the product doesn't mean that it isn't reliable. The measure of reliability is whether it fits other measured data sets. RATPAC does.

It's RATPAC that's diverging from UAH/RSS.

Again, the surface datasets and satellites do not measure within the same domain(s), so you can't compare them on the scale you are. Different physical processes govern temperature trend(s) between these two boundaries on both interdecadal and decadal timescales. So when it comes to the lower troposphere, you have three viable datasets, and it so happens that the two most spatially adequate ones agree with one another.

[nflwxman]

It's RATPAC that's diverging from UAH/RSS.

Again, the surface datasets and satellites do not measure within the same domain(s), so you can't compare them on the scale you are. Different physical processes govern temperature trend(s) between these two boundaries on both interdecadal and decadal timescales. So when it comes to the lower troposphere, you have three viable datasets, and it so happens that the two most spatially adequate ones agree with one another.

Where are your statistics about how UAH/RSS is used 900 times in peer review versus RATPAC less than 50? Just curious.

[StudentOfClimatology]

Sondes are sensors....

Okay, so let's assume for a hot second you are not a skeptic. What dataset do you trust the most for empirical TCR and ECS calculations?

The satellite datasets are not sufficiently long enough to be used for ECS/TCR calculations at this time. I'd use an aggregation of all surface station datasets to determine ESC/TCR at the surface. Sensitivity in the TLT/TMT cannot be determined using the surface networks.

[StudentOfClimatology]

Where are your statistics about how UAH/RSS is used 900 times in peer review versus RATPAC less than 50? Just curious.

Google scholar. Need me do this for you, too?

[donsutherland1]

I'm not a skeptic at all (anymore). This board is just uninformed/out of the scientific mainstream on a lot of topics. It doesn't surprise me that you'd try and pull that one, though.

At least now I know you're lying about your remote sensing education. There are 7 different MSU/AMSU satellites used in the UAH/RSS interpretations. Meanwhile, RATPAC uses no "sensors"..it is an aggregated sonde network.

Although there are 7 satellites, don't each of the satellites depend on a microwave radiometer?

[StudentOfClimatology]

Although there are 7 satellites, don't each of the satellites depend on a microwave radiometer?

Of course. Each radiometer is calibrated seperately based on it's orbital parameters and observed bias(es), if any.

[donsutherland1]

It's RATPAC that's diverging from UAH/RSS.

But would UAH (especially 6.0) and RSS look different if the problem related to cloud-affected radiances were fixed, especially as the lower and middle tropospheric warming trend would be increased by an estimated 20%-30%?

[nflwxman]

Google scholar. Need me do this for you, too?

Yes, could you please?

[StudentOfClimatology]

Yes. Exactly.

Yeah, seven radiometers, individually calibrated based on unique physical specifications. How does that jive with what you said earlier?

[skierinvermont]

Why don't people apply this same logic to the satellite data sets? Instead they get all wrapped up in short term stuff.

 

Because the satellites have long-term biases. Resolution is not a bias, it is simply a lack of precision which over time averages out to zero.

[skierinvermont]

Sondes are sensors....

 

 

Funny you had to explain that one to him. So much bias he will say just about anything to 'win.' 

[StudentOfClimatology]

Funny you had to explain that one to him. So much bias he will say just about anything to 'win.'

Sondes aren't sensors, sondes contain sensors.

He said RATPAC uses "several sensors" and the AMSU/MSU networks use "one sensor". That's laughably false. We're debating stuff than needn't be debated.

[skierinvermont]

Sondes aren't sensors, sondes contain sensors.

 

Is this post for real?

[StudentOfClimatology]

Is this post for real?

I've built radiosondes, so yes.