Jump to content

ENSO Discussion


snow_wizard

Recommended Posts

What's sobering about it? We've been warming steadily since the end of the LIA, and there's been little (if any) acceleration of sea level rise since that warming started over 400 years ago. This warming has benefitted humanity overall..ideally we'd like to be a few degrees warmer if anything.

 

Sea levels rose just as much from 1880-1950 (natural) as they did from 1950-present (CO^2 comes into play). Over 70% of the sea level rise since the end of the LIA occurred before 1950.

 

http://i724.photobucket.com/albums/ww243/phillywillie/Mobile%20Uploads/45CD1819-F214-46ED-A88D-5F14B3E0C786_zpszq99xz0p.png

 

Also, I'd argue the satellite derived data is more representative of reality than surface data, given vastly more area is measured:

 

http://i724.photobucket.com/albums/ww243/phillywillie/Mobile%20Uploads/FB408DE3-E5A7-4204-A39A-0DE0065C44BA_zpsoe5gomwy.gif

 

 

The temperature uncertainties in satellite data dwarf (by a few orders of magnitude) surface based stations which are geographically fixed in space and time, and provide the most homogenous, confident, and longest available record of temperature in the observational era. Keep in mind that satellites don't actually measure temperature to begin with nor are they actually measuring the same thing as surface data. Temperature data from satellites has to be inferred, in the case of microwave sounding units, they measure emission spectra of oxygen nuclei in various layers of the atmosphere, which are inherently assumed to be directly proportional to temperature changes, (of course this isn't completely true here, a plethora of confounding factors distort this relationship) since satellites have a lifespan that's a few orders of magnitude less than surface based stations, usually lasting at most several years-decade, because they can't measure the same place on the earth at the same time of the day and suffer from orbital drift, and are susceptible to contamination from clouds, surface albedo, etc., computer models must be applied to account for these diurnal, orbital, emission, and observational platform corrections before any temperature data is derived. Thereafter, even more adjustments have to be made to ensure the record is homogeneous and nearly globally complete... 

From Cowtan, note uncertainties in satellite data are about 5x higher than surface data. Surface data is certainly "more representative of reality"

rss_ensemble_box_rg.png

 

A quote from Carl Mears in Sept 2014 highlights my point here...

http://www.remss.com/blog/recent-slowing-rise-global-temperatures

 

"As a data scientist, I am among the first to acknowledge that all climate datasets likely contain some errors.  However, I have a hard time believing that both the satellite and the surface temperature datasets have errors large enough to account for the model/observation differences.  For example, the global trend uncertainty (2-sigma) for the global TLT trend is around 0.03 K/decade (Mears et al. 2011).  Even if 0.03 K/decade were added to the best-estimate trend value of 0.123 K/decade, it would still be at the extreme low end of the model trends.  A similar, but stronger case can be made using surface temperature datasets, which I consider to be more reliable than satellite datasets (they certainly agree with each other better than the various satellite datasets do!).  So I don’t think the problem can be explained fully by measurement errors."

 

This isn't to say that surface data isn't without it's disadvantages and uncertainties especially regarding observational coverage, but per capita the uncertainties are far greater in satellite vs surface based stations. Oth, it's also important to absorb all available sources of information and a move towards a hybrid, ensemble surface-satellite based dataset, similar to Cowtan (2014) & somewhat analogous to what I've been able to do with the Oceanic Nino Index (ONI), but on a much grander scale, is a necessity in order to improve our assessment & monitoring capabilities of historical global temperatures. Although many argue that such a dataset would be inhomogeneous w/ changing observational platforms, coverage, and uncertainties, as measurement and coverage steadily improved throughout the observational record, aren't "singular" data sources/platforms already intrinsically inhomogeneous as is? Why not provide the most reliable record at each specific interval in the record, as opposed to limiting capabilities for fear of inconsistencies when it already exists (and to a significant extent at that)?

Link to comment
Share on other sites

FWIW, CDAS also continues to run much warmer globally than NESDIS and every other dataset. Food for thought.

 

http://www.ospo.noaa.gov/data/sst/anomaly/2017/anomnight.4.20.2017.gif

 

You bring up a very good point, CDAS in fact running above virtually every dataset atm, I'm very curious as to why this is the case...

  • Like 1
Link to comment
Share on other sites

Water is now warmer than normal off our coast and continuing to warm...

 

7-day change...

 

Looks like a lot of cooler water still waiting in the wings to move toward the coast once we dry out, and a ridge develops offshore, like you've been hoping for.

 

The warming directly along the coast is partially a result of the very wet SW flow pattern we have been stuck in.

Link to comment
Share on other sites

I'm honestly baffled why legitimate meteorologists/researchers still try to give the CFSv2 any credence regarding ENSO. This model has a notorious NINO bias (some of which stems from it's +SSTA bias in the southeastern Pacific), and like most climate models a profound "rebound"/sinusoidal bias, in which integrated ENSO behavior is more regular than reality. Unfortunately, it appears this model is being initialized w/ potentially erroneous CDAS1 data and is already ~0.2-0.3C above Reynolds OISSTv2, but in spite of this its newest forecast (blue) is appreciably less enthusiastic about a +ENSO event later this year. While another El Nino is not dynamically impossible, as suggested by the historical 150+ year modern ENSO and ~60 year QBO record, in the 2nd year immediately following the culmination of a strong-super NINO event, and under WQBO regime in the midst of neutral-negative ENSO, another cold La Nada-weak La Nina event is most likely for 2017-18...

C-AsnbIXYAAO_my.jpg

  • Like 2
Link to comment
Share on other sites

The temperature uncertainties in satellite data dwarf (by a few orders of magnitude) surface based stations which are geographically fixed in space and time, and provide the most homogenous, confident, and longest available record of temperature in the observational era. Keep in mind that satellites don't actually measure temperature to begin with nor are they actually measuring the same thing as surface data. Temperature data from satellites has to be inferred, in the case of microwave sounding units, they measure emission spectra of oxygen nuclei in various layers of the atmosphere, which are inherently assumed to be directly proportional to temperature changes, (of course this isn't completely true here, a plethora of confounding factors distort this relationship) since satellites have a lifespan that's a few orders of magnitude less than surface based stations, usually lasting at most several years-decade, and since they can't measure the same place on the earth at the same time of the day and suffer from orbital drift, and are susceptible to contamination from clouds, surface albedo, etc. and computer models must be applied to account for these diurnal, orbital, emission, and observational platform corrections before any temperature data is derived & thereafter even more adjustments have to be made to ensure the record is homogeneous and nearly globally complete...

From Cowtan, note uncertainties in satellite data are about 5x higher than surface data. Surface data is certainly "more representative of reality"

rss_ensemble_box_rg.png

Alarmist blogs like Skeptical Science generally aren't the best sources in terms of scientifically literacy, in my opinion. I've actually spoken personally with Mr. Cowtan, and this wouldn't be the first time John Cook misrepresented his work.

 

The latest available verification analysis for UAHv6 has been published, and the margin of error is demonstrably much lower than is suggested Mears et al and Cowtan/Way et al for the TMT/TLT boundaries. In fact, most of these concerns were addressed years ago.

 

http://link.springer.com/article/10.1007%2Fs13143-017-0010-y

 

Version 6 of the UAH MSU/AMSU global satellite temperature dataset represents an extensive revision of the procedures employed in previous versions of the UAH datasets. The two most significant results from an end-user perspective are (1) a decrease in the global-average lower tropospheric temperature (LT) trend from +0.14°C decade−1 to +0.11°C decade−1 (Jan. 1979 through Dec. 2015); and (2) the geographic distribution of the LT trends, including higher spatial resolution, owing to a new method for computing LT. We describe the major changes in processing strategy, including a new method for monthly gridpoint averaging which uses all of the footprint data yet eliminates the need for limb correction; a new multi-channel (rather than multi-angle) method for computing the lower tropospheric (LT) temperature product which requires an additional tropopause (TP) channel to be used; and a new empirical method for diurnal drift correction. We show results for LT, the midtroposphere (MT, from MSU2/AMSU5), and lower stratosphere (LS, from MSU4/AMSU9). A 0.03°C decade−1 reduction in the global LT trend from the Version 5.6 product is partly due to lesser sensitivity of the new LT to land surface skin temperature (est. 0.01°C decade−1), with the remainder of the reduction (0.02°C decade−1) due to the new diurnal drift adjustment, the more robust method of LT calculation, and other changes in processing procedures.

1) It also should be noted that over the last 30 years, despite demonstrably untrue claims of "superior accuracy", the trends in the surface station datasets have been adjusted over 400% as much as the satellites'. These claimed margins of error from the surface station folks have never actually been true, either in theory or in practice.

 

2) Surface stations measure a tiny fraction of the globe, almost completely confined to areas where people live. The data is the. extrapolated over millions of square miles across the oceans, deserts, ice sheets, what have you. Any UHI/contamination is therefore extrapolated along with it.

 

A quote from Carl Mears in Sept 2014 highlights my point here...

http://www.remss.com/blog/recent-slowing-rise-global-temperatures

 

"As a data scientist, I am among the first to acknowledge that all climate datasets likely contain some errors. However, I have a hard time believing that both the satellite and the surface temperature datasets have errors large enough to account for the model/observation differences. For example, the global trend uncertainty (2-sigma) for the global TLT trend is around 0.03 K/decade (Mears et al. 2011). Even if 0.03 K/decade were added to the best-estimate trend value of 0.123 K/decade, it would still be at the extreme low end of the model trends. A similar, but stronger case can be made using surface temperature datasets, which I consider to be more reliable than satellite datasets (they certainly agree with each other better than the various satellite datasets do!). So I don’t think the problem can be explained fully by measurement errors."

That quote from Mears in 2014 is no longer viable.

 

As of the UAHv6 update, the satellite datasets are now in better agreement with one another than the surface station networks. The difference in trend between HADCRUT4 and GISS over the last 15 years is more than double the difference in trend between UAH & RSS for TLT.

 

This isn't to say that surface data isn't without it's disadvantages and uncertainties especially regarding observational coverage, but per capita the uncertainties are far greater in satellite vs surface based stations. Oth, it's also important to absorb all available sources of information and a move towards a hybrid, ensemble surface-satellite based dataset, similar to Cowtan (2014) & somewhat analogous to what I've been able to do with the Oceanic Nino Index (ONI), but on a much grander scale, is a necessity in order to improve our assessment & monitoring capabilities of historical global temperatures. Although many argue that such a dataset would be inhomogeneous w/ changing observational platforms, coverage, and uncertainties, as measurement and coverage steadily improved throughout the observational record, aren't "singular" data sources/platforms already intrinsically inhomogeneous as is? Why not provide the most reliable record at each specific interval in the record, as opposed to limiting capabilities for fear of inconsistencies when it already exists (and to a significant extent at that)?

Well, I think the evidence contradicts this line of thinking. The performed adjustments (and internal disagreements) involved with the surface networks are vastly larger than anything present within the satellite data. It doesn't get much more straightforward than that, in my opinion.

Link to comment
Share on other sites

Alarmist blogs generally aren't the best sources. I've actually spoken personally with Carl Mears and Mr. Cowtan, and this wouldn't be the first time John Cook misrepresented his work.

 

For one, the latest available verification analysis for UAHv6 had been published, and the margin of error is demonstrably much lower than is suggested Mears et al 2014 for TMT. In fact, most of these concerns were addressed years ago.

 

http://link.springer.com/article/10.1007%2Fs13143-017-0010-y

 

 

1) It also should be noted that over the last 30 years, despite demonstrably untrue claims of "superior accuracy", the trends in the surface station datasets have been adjusted over 400% as much as the satellite data. These claimed margins of error from the surface station folks are nothing more than defensive crouches.

 

2) Surface stations measure a tiny fraction of the globe, almost completely confined to areas where people live. The data is the. extrapolated over millions of square miles across the oceans, deserts, ice sheets, what have you. Any UHI/contamination is therefore extrapolated along with it.

 

That quote from Mears in 2014 is no longer viable.

 

As of the UAHv6 update, the satellite datasets are now in better agreement with one another than the surface station networks. The difference in trend between HADCRUT4 and GISS over the last 15 years is more than double the difference in trend between UAH & RSS for TLT. Oops. :lol:

 

Well, I think the evidence blatantly contradicts this line of thinking.

 

The performed adjustments (and internal disagreements) involved with the surface networks are vastly larger than anything present within the satellite data. It doesn't get much more straightforward than that.

 

Alarmist? Hardly, in fact if you actually looked under the title of that article, it comes straight from the horses' mouth, it was actually written by Cowtan himself...

 

As of the UAHv6 update, the satellite datasets are now in better agreement with one another than the surface station networks. The difference in trend between HADCRUT4 and GISS over the last 15 years is more than double the difference in trend between UAH & RSS for TLT. Oops.  :lol:

 

Actually, this is no longer valid, RSS was recently adjusted upward and is now more in line w/ the surface based data but again they aren't measuring the same thing so they aren't directly comparable to begin with

 

1) It also should be noted that over the last 30 years, despite demonstrably untrue claims of "superior accuracy", the trends in the surface station datasets have been adjusted over 400% as much as the satellite data. These claimed margins of error from the surface station folks are nothing more than defensive crouches.

2) Surface stations measure a tiny fraction of the globe, almost completely confined to areas where people live. The data is the. extrapolated over millions of square miles across the oceans, deserts, ice sheets, what have you. Any UHI/contamination is therefore extrapolated along with it.

 

These claims are fine as long as you completely and purposely ignore the diurnal and drift corrections which are often on the order of several times larger than any of the surface corrections.

Link to comment
Share on other sites

http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-15-0744.1

 

"The new dataset shows substantially increased global-scale warming relative to the previous version of the dataset, particularly after 1998. The new dataset shows more warming than most other midtropospheric data records constructed from the same set of satellites."

Link to comment
Share on other sites

Actually, this is no longer valid, RSS was recently adjusted upward and is now more in line w/ the surface based data but again they aren't measuring the same thing so they aren't directly comparable to begin with, and assuming ...

Actually, that was only for the TMT domain, not TLT. Huge difference there in both practice and theory. Their TLT trends are very much homogenous.

 

1) It also should be noted that over the last 30 years, despite demonstrably untrue claims of "superior accuracy", the trends in the surface station datasets have been adjusted over 400% as much as the satellite data. These claimed margins of error from the surface station folks are nothing more than defensive crouches.

2) Surface stations measure a tiny fraction of the globe, almost completely confined to areas where people live. The data is the. extrapolated over millions of square miles across the oceans, deserts, ice sheets, what have you. Any UHI/contamination is therefore extrapolated along with it.

 

These claims are fine as long as you completely and purposely ignore the diurnal and drift corrections which are often on the order of several times larger than any of the surface corrections.

Well, did you read the latest available verification analysis on this issue? It's very thorough and greatly reduces error potential relative to version 5.6.

 

Alarmist? Hardly, in fact if you actually looked under the title of that article, it comes straight from the horses' mouth, it was actually written by Cowtan himself...

I'm taking about the image you linked. It has a skepticalscience image code.

Link to comment
Share on other sites

http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-15-0744.1

 

"The new dataset shows substantially increased global-scale warming relative to the previous version of the dataset, particularly after 1998. The new dataset shows more warming than most other midtropospheric data records constructed from the same set of satellites."

Again, this is in reference to the TMT, not the TLT (which was virtually unchanged in this analysis).

Link to comment
Share on other sites

Actually, that was only for the TMT domain, not TLT. Huge difference there in both practice and theory. Their TLT trends are very much homogenous.

 

 

Well, did you read the latest available verification analysis on this issue? It's very thorough and greatly reduces error potential relative to version 5.6.

 

 

I'm taking about the image you linked. It has a skepticalscience image code.

 

I actually have, and as noted in Mears & Wentz (2016) the diurnal corrections are the largest sources of uncertainty and are provided for by climate/reanalysis models, which are fraught with their own uncertainties that aren't discussed or accounted for in this paper. Although, the diurnal corrections average towards zero over time, the individual corrections and variance are higher than any of the surface datasets

 

Yes, it is from Skeptical Science, but the article I pulled it from was written by Cowtan himself in January 2016.

 

https://skepticalscience.com/surface_temperature_or_satellite_brightness.html

Link to comment
Share on other sites

While Dr. Spencer's criticism here shouldn't be taken as gospel until his paper clears peer review, this is his take on Mears' new TMT dataset. I happen to agree that the NOAA14 satellite is compromised by drift, and it was obviously left unaccounted for.

 

http://www.drroyspencer.com/2016/03/comments-on-new-rss-v4-pause-busting-global-temperature-dataset/

 

While the title of their article implies that their new diurnal drift adjustment to the satellite data has caused the large increase in the global warming trend, it is actually their inclusion of what the evidence will suggest is a spurious warming (calibration drift) in the NOAA-14 MSU instrument that leads to most (maybe 2/3) of the change. I will provide more details of why we believe that satellite is to blame, below.

 

Also, we provide new radiosonde validation results, supporting the UAH v6 data over the new RSS v4 data.

Link to comment
Share on other sites

I actually have, and as noted in Mears & Wentz (2016) the diurnal corrections are the largest sources of uncertainty and are provided for by climate/reanalysis models, which are fraught with their own uncertainties that aren't discussed or accounted for in this paper. Although, the diurnal corrections average towards zero over time, the individual corrections and variance are higher than any of the surface datasets

 

Yes, it is from Skeptical Science, but the article I pulled it from was written by Cowtan himself in January 2016.

 

https://skepticalscience.com/surface_temperature_or_satellite_brightness.html

Well yeah, RSS does indeed use a "model" to correct for drift and calibration for such, but I don't believe UAH employs the same approach.

 

The TMT issue is a headache, I'll give you that, but fortunately the TLT domain is now clearer under stronger inter-dataset homogeneity (at the moment).

Link to comment
Share on other sites

Well yeah, RSS does indeed use a "model" to correct for drift and calibration for such, but I don't believe UAH employs the same approach.

 

The TMT issue is a headache, I'll give you that, but fortunately the TLT domain is now clearer under stronger inter-dataset homogeneity (at the moment).

 

My point is errors in raw data due to orbit drift alone can be on the order of 10-20 C (or more) in some individual instances where the diurnal cycle is variant, while errors of this magnitude are rarely, if ever observed w/ raw surface based data in any of their corrections... Of course, reanalysis models used to adjust for orbital drift are largely reliant on surface observations to derive & reconstruct their various fields, thus ultimately, the satellite data is not really independent and is inadvertently being adjusted towards surface data, while the inverse isn't true.

 

Again, here's another graphic from Kevin Cowtan showing satellite and surface temperature ensemble realizations, note the appreciably larger uncertainty/spread in satellite data. Also, worth mentioning that the article was written in collaboration w/ Carl Mears of RSS...

 

rss_ensemble_series.png

Link to comment
Share on other sites

I'm honestly baffled why legitimate meteorologists/researchers still try to give the CFSv2 any credence regarding ENSO. This model has a notorious NINO bias (some of which stems from it's +SSTA bias in the southeastern Pacific), and like most climate models a profound "rebound"/sinusoidal bias, in which integrated ENSO behavior is more regular than reality. Unfortunately, it appears this model is being initialized w/ potentially erroneous CDAS1 data and is already ~0.2-0.3C above Reynolds OISSTv2, but in spite of this its newest forecast (blue) is appreciably less enthusiastic about a +ENSO event later this year. While another El Nino is not dynamically impossible, as suggested by the historical 150+ year modern ENSO and ~60 year QBO record, in the 2nd year immediately following the culmination of a strong-super NINO event, and under WQBO regime in the midst of neutral-negative ENSO, another cold La Nada-weak La Nina event is most likely for 2017-18...

C-AsnbIXYAAO_my.jpg

I'm shocked that nobody has drawn attention to the CDAS problems lately (which seem to worsen near the equinoxes).

  • Like 1
Link to comment
Share on other sites

I'm shocked that nobody has drawn attention to the CDAS problems lately (which seem to worsen near the equinoxes).

 

Do you agree with his take that a cold la Nada/weak La Nina event is most likely next winter? You have seemed pretty sold on a some sort of +ENSO event for a little while now.

Link to comment
Share on other sites

My point is errors in raw data due to orbit drift alone can be on the order of 10-20 C (or more) in some individual instances where the diurnal cycle is variant, while errors of this magnitude are rarely, if ever observed w/ raw surface based data in any of their corrections... Of course, reanalysis models used to adjust for orbital drift are largely reliant on surface observations to derive & reconstruct their various fields, thus ultimately, the satellite data is not really independent and is inadvertently being adjusted towards surface data, while the inverse isn't true.

Isn't this only an issue for RSS? I'll have to go back and check but I think UAH employs cross-satellite calibration scheme rather than modeling for calibration, even in the post-AQUA era.

Link to comment
Share on other sites

Do you agree with his take that a cold la Nada/weak La Nina event is most likely next winter? You have seemed pretty sold on a some sort of +ENSO event for a little while now.

I'm leaning warm neutral or weak niño, personally, but I could see a cool neutral if a stronger Walker Cell/weaker +IOD can be sustained into JJA.

 

That said, I'm fairly confident that the ENSO in 17/18 will run warmer vs last winter, through QBO influence alone.

Link to comment
Share on other sites

Isn't this only an issue for RSS? I'll have to go back and check but I think UAH employs cross-satellite calibration scheme rather than modeling for calibration, even in the post-AQUA era.

 

Technically it is, but a glaring concern I have is that cross-calibration with other satellites may not be an effective approach to handling diurnal drift given the already profound discrepancies in instrumentation, platforms, outages, etc, and inconsistencies in bias adjustment given other satellites will still ultimately suffer from diurnal drift... 

Link to comment
Share on other sites

Technically it is, but a glaring concern I have is that cross-calibration with other satellites may not be an effective approach to handling diurnal drift given the already profound discrepancies in instrumentation, platforms, outages, etc, and inconsistencies in bias adjustment given other satellites will still ultimately suffer from diurnal drift...

That's one way to look at it, though (if I remember correctly) there are at least 8 satellites and 24 total radiometers to interpolate from with numerous demonstrable reference points.

 

Obviously the sign(s) of the various cases of sensor/orbital drift won't be the same. Some will oppose, etc.

 

And to be frank, I simply don't trust the surface data, given the frequent adjustments in the historical record which occur on a monthly basis, all of which appear to be aimed at aligning observations with climate model hindcasts. It just doesn't smell right to me. Over the last 20 years, entire years have been "adjusted" by up to 0.5 degrees centigrade. That's much larger than any satellite adjustment, by many orders of magnitude. It's ridiculous.

Link to comment
Share on other sites

That's one way to look at it, though (if I remember correctly) there are at least 8 satellites and 24 total radiometers to interpolate from with numerous demonstrable reference points.

 

Obviously the sign(s) of the various cases of sensor/orbital drift won't be the same. Some will oppose, etc.

 

And to be frank, I simply don't trust the surface data, given the frequent adjustments in the historical record which occur on a monthly basis, all of which appear to be aimed at aligning observations with climate model hindcasts. It just doesn't smell right to me. Over the last 20 years, entire years have been "adjusted" by up to 0.5 degrees centigrade. That's much larger than any satellite adjustment, by many orders of magnitude. It's ridiculous.

 

I really don't understand the hostility towards surface data, other than pure, unfounded speculation, no one has really discovered and confirmed any deliberate, purposeful "mishandling" of the data. Also note that NOAA was already investigated by congress, and their data was independently verified against ARGO floats, buoys, and other platforms, and published over & over again... It was discovered that the older NOAA record and Hadley data suffer from a cold bias, particularly after the early-mid 1990s when the implementation of buoys became more prevalent across the globe, and because the engine room intake measurements are warmer than the measurements by buoys, an upward adjustment to the data was entirely necessary. The adjustments don't occur on a monthly basis, but they do with each update of the surface record that often takes place once every few years or so, which is comparable to the satellite record.

Link to comment
Share on other sites

I really don't understand the hostility towards surface data, other than pure, unfounded speculation, no one has really discovered and confirmed any deliberate, purposeful "mishandling" of the data.

Being a student of paleoclimate myself, and having seen so many blatant, deliberate attempts at tweaking statistical procedure to paint a false narrative for political reasons (Michael Mann being a microcosm of this phenomenon), I keep a very watchful eye on these dataset adjustments.

 

Whether it's deliberate, or via innate confirmation bias, there are coincidences, and then there are "coincidences". Sometimes the pieces to the puzzle are already put together in front of you.

 

Also note that NOAA was already investigated by congress, and their data was independently verified against ARGO floats, buoys, and other platforms, and published over & over again...

1) Congress are not scientists, and that investigation was politicized into oblivion by pro-CAGW politicians. It was never sent to a special prosecutor. Congress frankly would have no way of knowing whether those in question were being transparent about what was said in those emails because they don't understand the scientific procedures involved.

 

2) The ARGO-era began in 2003, and even the data from the ARGO floats were/are systematically adjusted upwards relative to the initially extracted (raw) data. It fits a fimiliar theme.

 

3) The buoy data has also undergone all sorts of various adjustments, many of which happen to be in amazing structural homogeneity with the modern ship-intake valve data and surface station data. Again..coincidence?

 

It was discovered that the older NOAA record and Hadley data suffer from a cold bias, particularly after the early-mid 1990s when the implementation of buoys became more prevalent across the globe, and because the engine room intake measurements are warmer than the measurements by buoys, an upward adjustment to the data was entirely necessary.

The ship intake temperatures should never have been employed in the first place. They're so easily contaminated it's not even funny. The bouy data was adjusted to boost synchronicity with the ship intake data after the late 1980s, and yet this ship data was adjusted downwards significantly from 1920 to 1945, which "coincidently" happens to coincide with the previous global warming period. Again, consistent theme.

 

The adjustments don't occur on a monthly basis, but they do with each update of the surface record that often takes place once every few years or so, which is comparable to the satellite record.

I see tweaks to the GISS data on a month to month basis. It's been frequent since 2011. When I get back home I'll link you to the thousands of monthly adjustments I've documented since 2013.

Link to comment
Share on other sites

Pardon if I come across as harsh here, I really enjoy this discussion as always Phil...

Haha, you know I love you, brother. :wub:

 

I enjoy this debate, too.

  • Like 1
Link to comment
Share on other sites

Being a student of paleoclimate myself, and having seen so many blatant, deliberate attempts at tweaking statistical procedure to paint a false narrative for political reasons (Michael Mann being a microcosm of this phenomenon), I keep a very watchful eye on these dataset adjustments.

 

Whether it's deliberate, or via innate confirmation bias, there are coincidences, and then there are "coincidences". Sometimes the pieces to the puzzle are already put together in front of you.

 

 

1) Congress are not scientists, and that investigation was politicized into oblivion by pro-CAGW politicians. It was never sent to a special prosecutor. Congress frankly would have no way of knowing whether those in question were being transparent about what was said in those emails because they don't understand the scientific procedures involved.

 

2) The ARGO-era began in 2003, and even the data from the ARGO floats were/are systematically adjusted upwards relative to the initially extracted (raw) data. It fits a fimiliar theme.

 

3) The buoy data has also undergone all sorts of various adjustments, many of which happen to be in amazing structural homogeneity with the modern ship-intake valve data and surface station data. Again..coincidence?

 

 

The ship intake temperatures should never have been employed in the first place. They're so easily contaminated it's not even funny. The bouy data was adjusted to boost synchronicity with the ship intake data after the late 1980s, and yet this ship data was adjusted downwards significantly from 1920 to 1945, which "coincidently" happens to coincide with the previous global warming period. Again, consistent theme.

 

 

I see tweaks to the GISS data on a month to month basis. It's been frequent since 2011. When I get back home I'll link you to the thousands of monthly adjustments I've documented since 2013.

 

"...and yet this ship data was adjusted downwards significantly from 1920 to 1945, which "coincidently" happens to coincide with the previous global warming period. Again, consistent theme."

Again, the buoy data (including ARGO) was adjusted upward to match the ERI measurements from the 1940s-1990s, but this claim is also false, because the data actually shows more warming during World War II, at the height of the previous warming precipice. Pro-AGW politicians? What are you talking about? You do realize that the House Committee Chairman, Oversight Subcommittee Chairman, and Environmental Committee Chairmen were all republicans who publicly expressed their disdain for the new NOAA data, only to later discover no actual wrongdoing. If anything, the prosecutors were actually heavily biased, in favor of anti-AGWers....

 

Oversight Subcommittee Chairman Darin LaHood (R-Ill.): “I applaud Dr. Bates’s efforts in uncovering the truth of this data manipulation, and I commend Chairman Smith and the Science Committee for conducting rigorous oversight on behalf of the American people.  Transparent and faithful execution of the scientific process, especially where taxpayer dollars are involved, is crucial to ensure that our policies are based on sound science and not on politically predetermined outcomes.”

 

Environment Subcommittee Chairman Andy Biggs (R-Ariz.): “I commend Dr. Bates for bringing to light the corrupt practices used by his former colleagues and hope this serves as a deterrence to anyone thinking of manipulating science to serve their own political agenda.  I applaud Chairman Smith and the Science Committee's efforts to provide the necessary oversight to ensure the American people have the best information possible.”

 

Their work has been rigorously evaluated and re-evaluated by the scientific community, and most literature only further supports ERSSTv4's findings, if they actually performed any wrongdoing, tampering, it likely would have been discovered already either by congress or the scientific community, but neither has been able to come forward with any substantial evidence that depicts deliberate tampering. Most of the claims regarding data tampering/manipulation rest on heavily biased, unfounded, and unsubstantiated speculation from the blogosphere. Contaminated? You don't think the satellite radiance isn't (very) significantly  contaminated by clouds, vegetation, orography etc? (Aside from the fact that it again doesn't measure temperature to begin w/) Most of the criticisms to ERSST originate from unqualified pseudo-scientists, biased think tanks, and/or the blogosphere. The double standard here is pretty comical, if the ERSST adjustments reduced the amount of global warming in the modern era, no one would bat an eyelash.

Link to comment
Share on other sites

"...and yet this ship data was adjusted downwards significantly from 1920 to 1945, which "coincidently" happens to coincide with the previous global warming period. Again, consistent theme."

Again, the buoy data (including ARGO) was adjusted upward to match the ERI measurements from the 1940s-1990s, but this claim is also false, because the data actually shows more warming during World War II, at the height of the previous warming precipice.

You wake up so d**n early. :lol:

 

The buoy data was bumped upwards in the 40s/50s? I've never seen any evidence of this. I know the ship data depicted significant warming in the early/mid 20th century, and was subsequently homogenized to the buoy data in large part until the 1970s. I'll grab the ERSSTv4 paper again just to make sure I'm not forgetting anything.

 

Pro-AGW politicians? What are you talking about? You do realize that the House Committee Chairman, Oversight Subcommittee Chairman, and Environmental Committee Chairmen were all republicans who publicly expressed their disdain for the new NOAA data, only to later discover no actual wrongdoing. If anything, the prosecutors were actually heavily biased, in favor of anti-AGWers....

These committees are a (bi)partisan food fight, and in this case they were wholly unprepared to take on the investigation because they held zero understanding of the procedures involved. It should have been sent to a special prosecutor..it's bad politics to grill American scientists, generally speaking.

 

 

Their work has been rigorously evaluated and re-evaluated by the scientific community, and most literature only further supports ERSSTv4's findings, if they actually performed any wrongdoing, tampering, it likely would have been discovered already either by congress or the scientific community, but neither has been able to come forward with any substantial evidence that depicts deliberate tampering.

Are you kidding? There are well-qualified scientists all over the world questioning these adjustments. Some have filed lawsuits, and in many cases the original data is lost due to a convenient computer crash, hardware failure, or something along those lines.

 

It sounds conspiracy-ish, but sometimes you just have to call a spade a spade.

 

Most of the claims regarding data tampering/manipulation rest on heavily biased, unfounded, and unsubstantiated speculation from the blogosphere.

I generally don't read the blogosphere, save Dr. Spencer's for the UAH releases. He also happens to agree with the negative sentiment many scientists hold on these upward adjustments of the temperature data. This isn't just a few bloggers, there's a widespread criticism of this.

 

Contaminated? You don't think the satellite radiance isn't (very) significantly contaminated by clouds, vegetation, orography etc? (Aside from the fact that it again doesn't measure temperature to begin w/)

How would vegetation & orography "contaminate" the O^2 microwave emissions used to interpolate temperature? That doesn't quite compute..the aforementioned factors are part of the climate system and have always influenced temperature.

 

Most of the criticisms to ERSST originate from unqualified pseudo-scientists, biased think tanks, and/or the blogosphere. The double standard here is pretty comical, if the ERSST adjustments reduced the amount of global warming in the modern era, no one would bat an eyelash.

I don't pay attention to any of that stuff, however, I would honestly be just as critical if the tables were turned and the adjustments were of perpetual cooling.

 

In this case, however, you have both political and economic pressure tailwinding AGW, and every single adjustment to the data since 1988 has increased the warming trend, both in structure and magnitude. It's pretty straightforward, dude.

 

Scientists are human, too. We're just as prone to confirmation bias, ulterior political motivations, monetary pressures, and corruption as anyone.

Link to comment
Share on other sites

Phil Jones had to waltz through flaming hoops to even come close to explaining this one. "Removing the 1940s blip":

 

http://di2.nu/foia/1254108338.txt

 

At the very least, this goes to demonstrate the degree of guesswork involved within the older datasets. Superior accuracy my arse.

Link to comment
Share on other sites

The buoy data was bumped upwards in the 40s/50s? I've never seen any evidence of this. I know the ship data depicted significant warming in the early/mid 20th century, and was subsequently homogenized to the buoy data in large part until the 1970s.

 

Wait what, when did I say there was buoy data in the 1940-1950s? I was clearly referring to this earlier statement from you... Again, re-iterating myself here, this statement is wrong, the ERSSTv4 data was actually adjusted upwards in the 1940s, at the peak of the last warming period. While the upward adjustment didn't last nearly as long as the downward adjustment in the 1920s and 1930s, the amplitude was 2x as high as the preceding era's decrease, therefore it roughly offsets the change to ERSSTv4 vs ERSStv3b in the 1920s & 30s.

"The bouy data was adjusted to boost synchronicity with the ship intake data after the late 1980s, and yet this ship data was adjusted downwards significantly from 1920 to 1945, which "coincidently" happens to coincide with the previous global warming period."

 

nclvaRFaXJADG.tmpqq.gif

 

 

"Are you kidding? There are well-qualified scientists all over the world questioning these adjustments. Some have filed lawsuits, and in many cases the original data is lost due to a convenient computer crash, hardware failure, or something along those lines."

 

Any actual, publishable proof of this or are we just making things up yet again to fit our own preconceived notions? What about those published papers which tackle and dismantle the ERSSTv4 adjustments?... yeah I don't see any of those either... I'm also still waiting on all this "proof" of GISS temperature adjustments. If you feel their adjustments are unsubstantiated,  you should consider publishing on it, you have enough credentials, knowledge, & apparently more than enough time to rant about it here, so why not?

 

I also find it funny how the new RSS data actually shows a little more warming than GISS in the satellite era, yet relative silence from anti-AGW crowd. The datasets are actually very close to one another, again the point here really isn't to claim RSS is warmer than GISS, but that they're consistent w/ one another. 

C8GDnEPUwAA8xP2.jpg

 

 

"Assessing Recent warming using instrumentally homogeneous sea surface temperature records"

 

http://advances.sciencemag.org/content/3/1/e1601207

 

This is posted in both Judith Curry and Skeptical Science's blogs

https://judithcurry.com/2015/11/22/a-buoy-only-sea-surface-temperature-record/

 

"He also happens to agree with the negative sentiment many scientists hold on these upward adjustments of the temperature data. This isn't just a few bloggers, there's a widespread criticism of this."

 

"Widespread criticism"... Again is these scientists were really upset about the ERSSTv4 adjustments (esp those of the likes of Spencer and Cristy, wherein the new data doesn't fit their preconceived notions wrt AGW), then they should take it to literature and publish on it...

 

Worth noting here yet again NOAA's ERSSTv4 actually agrees even more w/ unadjusted buoy data...

 

C5M2GWrVUAAxQ9X.jpg

 

 

How would vegetation & orography "contaminate" the O^2 microwave emissions used to interpolate temperature? That doesn't quite compute..the aforementioned factors are part of the climate system and have always influenced temperature.

 

The fact that these sources of microwave emission have been around for an extended period of time doesn't change the fact that these are significant sources of natural interference wrt microwave radiance emissions which will provide even more uncertainty (than there already is) w/ satellite data. Voltage is measured on the satellite, and from voltage microwave emissions from oxygen (radiance) can be somewhat inferred throughout large depths of the atmosphere, however, microwaves are also emitted from the land and ocean surfaces (including vegetation), clouds, and this also is somewhat dependent on elevation, therefore they actually do contaminate the O^2 microwave emissions. And of course from radiance temperature may be interpreted.

Link to comment
Share on other sites

Are you kidding me? I literally spent 45 minutes on a reply, and I just lost the entire thing when I tried to post it. Screw this phone.

 

I'll be home later tonight, so I'll get back to you then. I'm not doing this from my phone anymore. Sorry dude.

Link to comment
Share on other sites

The buoy data was bumped upwards in the 40s/50s? I've never seen any evidence of this. I know the ship data depicted significant warming in the early/mid 20th century, and was subsequently homogenized to the buoy data in large part until the 1970s.

 

Wait what, when did I say there was buoy data in the 1940-1950s? I was clearly referring to this earlier statement from you... Again, re-iterating myself here, this statement is wrong, the ERSSTv4 data was actually adjusted upwards in the 1940s, at the peak of the last warming period. While the upward adjustment didn't last nearly as long as the downward adjustment in the 1920s and 1930s, the amplitude was 2x as high as the preceding era's decrease, therefore it roughly offsets the change to ERSSTv4 vs ERSStv3b in the 1920s & 30s.

"The bouy data was adjusted to boost synchronicity with the ship intake data after the late 1980s, and yet this ship data was adjusted downwards significantly from 1920 to 1945, which "coincidently" happens to coincide with the previous global warming period."

 

nclvaRFaXJADG.tmpqq.gif

Somehow I misread your first post and thought you were referring to buoy data that existed before the late 1970s (which I was unable to locate).

 

That said, this still doesn't make any sense to me, because the buoy fraction spiked from ~ 10% in the mid 1980s to ~ 50% by the early 2000's, yet those temperatures were adjusted downwards, while almost the entirety the recent upward adjustments (due to the growing buoy proportions) occur after 2003. So, what could have been so cold-biased as to require an adjustment large enough to outweigh the upward adjustments for the increase in the buoy proportion during that time? And, why is this out of phase with the ERI/Hull data adjustments in the early/mid 20th century?

 

As a result of this, the ERSSTv4 trend from 1998-present is literally twice as large as the OISSTv2 and HADSST3 datasets. More than anything, this looks like an attempt to linearize the post-1950 temperature trend.

 

 

Any actual, publishable proof of this or are we just making things up yet again to fit our own preconceived notions? What about those published papers which tackle and dismantle the ERSSTv4 adjustments?... yeah I don't see any of those either... I'm also still waiting on all this "proof" of GISS temperature adjustments. If you feel their adjustments are unsubstantiated, you should consider publishing on it, you have enough credentials, knowledge, & apparently more than enough time to rant about it here, so why not?

John Bates happens to an award-winning NOAA scientist, as does Roy Spencer. When the Karl et al paper was published, dozens of well respected scientists took issue with the methodology employed, including at least two here at my university.

 

I don't know if you converse with climate scientists as frequently as I do, but if so, then I'm sure you've observed the growing suspicion through which these homogenization processes are analyzed through by the scientific community. Try not to isolate yourself in a bubble of like-minded thinkers.

 

I also find it funny how the new RSS data actually shows a little more warming than GISS in the satellite era, yet relative silence from anti-AGW crowd.

What? :huh:

 

No it doesn't. It depicts almost twice as much warming, with the biggest divergence over the oceans (shocked..not).

 

In fact, GISS is an extreme warm outlier even relative to NCDC & HADCRUT4:

 

RSS TLT:

 

http://www.climate4you.com/images/MSU%20RSS%20GlobalMonthlyTempSince1979%20With37monthRunningAverage%20With201505Reference.gif

 

GISS:

 

http://www.climate4you.com/images/GISS%20GlobalMonthlyTempSince1979%20With37monthRunningAverage%20With201505reference.gif

 

Also note the recent GISS update featured an adjustment twice as large as its previously published margin of error. How can anyone with a working brain believe these claims of "superior accuracy" when every d**n adjustment is larger than the published margin of error? Absurd.

 

The fact that these sources of microwave emission have been around for an extended period of time doesn't change the fact that these are significant sources of natural interference wrt microwave radiance emissions which will provide even more uncertainty (than there already is) w/ satellite data. Voltage is measured on the satellite, and from voltage microwave emissions from oxygen (radiance) can be somewhat inferred throughout large depths of the atmosphere, however, microwaves are also emitted from the land and ocean surfaces (including vegetation), clouds, and this also is somewhat dependent on elevation, therefore they actually do contaminate the O^2 microwave emissions. And of course from radiance temperature may be interpreted.

They're more than just "somewhat" inferred. It's actually a fairly straightforward process, utilizing the most basic pre-einsteinian equations, most having been known since the inception of classical mechanics. The challenges are almost all anthropogenic in nature (orbital drift, sensor degradation, etc).

 

Also, natural influences like vegetation and orographics aren't contaminants because they actually alter the global temperature trend. So I'm not sure what you're getting at here. This isn't like UHI which actually contaminates the data because it's extrapolated thousands of miles between stations.

Link to comment
Share on other sites

"You wake up so d**n early. :lol:"

 

Lol, yea I was putting some of the finishing touches on a presentation I have later today regarding Orbital, Geographical and Background Climate Influences on ENSO since the Paleocene. Fun stuff!

Sounds interesting! Shoot me a link sometime if you're able.

 

Right now my area of research is LGM-to-Holocene variation(s) in the annular modes/ENSO, and their influence(s) on the global energy budget (climate).

 

Preliminary results suggest the annular modes have a very large impact on the global heat budget. When the annular modes are negative, particularly over the winter hemisphere, there's more radiative loss at the pole via reduced cloud cover there (and weakened poleward heat advection), more vigorous tropical convection due to decreased tropical static stability, stronger global wind speeds, and stronger/more contracted Hadley Cells. The enhanced wind speed and stronger tropical convection promote increased evaporative cooling of the sea surface and increased latent heat release in the upper troposphere (where it can then be radiated out). So the negative annular mode state naturally promotes global cooling over time. The opposite is true with regards to the positive state of the annular modes.

 

This also may explain the recovery from the LIA and much of the warming over the last 100+ years as well. The southern annular mode has trended strongly positive over the last few centuries, and the northern annular mode has also been in a much more positive state since the early 1980s versus the 1950s-70s, which was preceded by another positive stretch from the 1920s into the 1940s, which was also a period of global warming.

Link to comment
Share on other sites

Both annular modes have generally trended positively since the 1970s. This could (theoretically) explain the weakened tropical convection and reduced upper tropospheric latent heat release observed since the 1970s. It could also explain the observed decrease in stratospheric water vapor.

 

Trends in the annular modes:

 

http://i724.photobucket.com/albums/ww243/phillywillie/Mobile%20Uploads/94F900D8-D6ED-49EE-9A44-E02410D14785_zps2iiqmvlk.png

 

http://i724.photobucket.com/albums/ww243/phillywillie/Mobile%20Uploads/1A9B77A4-E90F-4299-841C-B4DFAED67861_zpsjv0zsjfl.png

Link to comment
Share on other sites

Somehow I misread your first post and thought you were referring to buoy data that existed before the late 1970s (which I was unable to locate).

 

That said, this still doesn't make any sense to me, because the buoy fraction spiked from ~ 10% in the mid 1980s to ~ 50% by the early 2000's, yet those temperatures were adjusted downwards, while almost the entirety the recent upward adjustments (due to the growing buoy proportions) occur after 2003. So, what could have been so cold-biased as to require an adjustment large enough to outweigh the upward adjustments for the increase in the buoy proportion during that time? And, why is this out of phase with the ERI/Hull data adjustments in the early/mid 20th century?

 

As a result of this, the ERSSTv4 trend from 1998-present is literally twice as large as the OISSTv2 and HADSST3 datasets. More than anything, this looks like an attempt to linearize the post-1950 temperature trend.

 

 

 

John Bates happens to an award-winning NOAA scientist, as does Roy Spencer. When the Karl et al paper was published, dozens of well respected scientists took issue with the methodology employed, including at least two here at my university.

 

I don't know if you converse with climate scientists as frequently as I do, but if so, then I'm sure you've observed the growing suspicion through which these homogenization processes are analyzed through by the scientific community. Try not to isolate yourself in a bubble of like-minded thinkers.

 

 

What? :huh:

 

No it doesn't. It depicts almost twice as much warming, with the biggest divergence over the oceans (shocked..not).

 

In fact, GISS is an extreme warm outlier even relative to NCDC & HADCRUT4:

 

RSS TLT:

 

http://www.climate4you.com/images/MSU%20RSS%20GlobalMonthlyTempSince1979%20With37monthRunningAverage%20With201505Reference.gif

 

GISS:

 

http://www.climate4you.com/images/GISS%20GlobalMonthlyTempSince1979%20With37monthRunningAverage%20With201505reference.gif

 

Also note the recent GISS update featured an adjustment twice as large as its previously published margin of error. How can anyone with a working brain believe these claims of "superior accuracy" when every d**n adjustment is larger than the published margin of error? Absurd.

 

 

They're more than just "somewhat" inferred. It's actually a fairly straightforward process, utilizing the most basic pre-einsteinian equations, most having been known since the inception of classical mechanics. The challenges are almost all anthropogenic in nature (orbital drift, sensor degradation, etc).

 

Also, natural influences like vegetation and orographics aren't contaminants because they actually alter the global temperature trend. So I'm not sure what you're getting at here. This isn't like UHI which actually contaminates the data because it's extrapolated thousands of miles between stations.

 

 

Ok I'm willing to accept the first point regarding when the buoy adjustments were made, but it essentially comes down to adjusting the ship data to buoys or vis versa, the former involves altering virtually the entire record, whereas the latter only is applicable for the last 20 years or so. I think w/ ERSSTv5 they're planning to change some of these adjustments along w/ updating the dataset w/ ICOADS release 3.0 that added tens of millions of surface observations, with a dramatic increase in global coverage in the 1860s, and they're (thankfully) getting rid of the extra optimal smoothing which severely degrades the quality of the modern data. Although think for the earlier portion of the record (pre-1950), this is a valid approach, & as I've noticed in the quality control calibrations for my ENS ONI, the pre-1950 ENSO event amplitudes are very reasonable, but, ERSSTv4's quality degrades circa late 20th century/satellite era (which isn't surprising given their omission of satellite data), that's particularly important for the southern hemisphere EOT structures.

 

I showed you a plot w/ a 12-month running average of the 2 datasets with linear regression since 1979, the overall trends are virtually identical, even if you move the base period around some, the difference in results isn't statistically significant. You showed the exact same data, and tried to say they're somehow significantly different. I really don't understand what you're trying to do here. Oth, I definitely won't argue that GISS is warmer than the HADCRUT & NCDC datasets near the end of the record, and amongst the three long term datasets, it's the one I trust the least esp given that Hansen has worked on this dataset I really don't understand their reasoning behind switching ocean dataset interfaces twice (HADISST-OISSTv2 then ERSSTv3b then ERSSTv4) all of which progressively showed more warming w/ each new dataset change.

 

 

It's been well established that earth's surface, clouds, and other media have thermal emission spectra that are similar to oxygen, which is assumed to be a homogeneous tracer in the earth's middle atmosphere for studying middle troposphere temperatures. While it may superficially seem like a straightforward process, there's also inherent error in actually obtaining any temperature to begin with wrt satellites. As aforementioned & noted by Spencer & Christy (1990), there actually is some interference from these other sources, and then of course the canonical nuances due to instrument calibration, orbital drift, etc., and even long term trends in layers above/immediately surrounding the troposphere, including the obvious long-term stratospheric cooling, only add to the uncertainty that's already there before any temperature data is actually attained. The point being here yet again the satellite, remote sensing instruments very likely have higher structural and observational uncertainties than surface stations as I pointed out earlier via Kevin Cowtan's work w/ a collection of 100 ensemble members from both HADCRUT4 & RSS.

  • Like 1
Link to comment
Share on other sites

Sounds interesting! Shoot me a link sometime if you're able.

 

Right now my area of research is LGM-to-Holocene variation(s) in the annular modes/ENSO, and their influence(s) on the global energy budget (climate).

 

Preliminary results suggest the annular modes have a very large impact on the global heat budget. When the annular modes are negative, particularly over the winter hemisphere, there's more radiative loss at the pole via reduced cloud cover there (and weakened poleward heat advection), more vigorous tropical convection due to decreased tropical static stability, stronger global wind speeds, and stronger/more contracted Hadley Cells. The enhanced wind speed and stronger tropical convection promote increased evaporative cooling of the sea surface and increased latent heat release in the upper troposphere (where it can then be radiated out). So the negative annular mode state naturally promotes global cooling over time. The opposite is true with regards to the positive state of the annular modes.

 

This also may explain the recovery from the LIA and much of the warming over the last 100+ years as well. The southern annular mode has trended strongly positive over the last few centuries, and the northern annular mode has also been in a much more positive state since the early 1980s versus the 1950s-70s, which was preceded by another positive stretch from the 1920s into the 1940s, which was also a period of global warming.

 

 

Here's a link to my presentation, I could have gone into more detail but was somewhat limited by the audience I was presenting this to and how much time I had to complete it.

 

 

https://docs.google.com/presentation/d/1yTyFAgZAYKkITiHTrPyZPCVBV-9v71G0y4GlGEaM-i8/edit#slide=id.g1d8ec1cb53_0_25

  • Like 1
Link to comment
Share on other sites

Ok I'm willing to accept the first point regarding when the buoy adjustments were made, but it essentially comes down to adjusting the ship data to buoys or vis versa, the former involves altering virtually the entire record, whereas the latter only is applicable for the last 20 years or so. I think w/ ERSSTv5 they're planning to change some of these adjustments along w/ updating the dataset w/ ICOADS release 3.0 that added tens of millions of surface observations, with a dramatic increase in global coverage in the 1860s, and they're (thankfully) getting rid of the extra optimal smoothing which severely degrades the quality of the modern data. Although think for the earlier portion of the record (pre-1950), this is a valid approach, & as I've noticed in the quality control calibrations for my ENS ONI, the pre-1950 ENSO event amplitudes are very reasonable, but, ERSSTv4's quality degrades circa late 20th century/satellite era (which isn't surprising given their omission of satellite data), that's particularly important for the southern hemisphere EOT structures.

That would be an improvement, but if the "selective" homogenization procedure applied to the buoy data before/after 1998 remains in a player on the trend-line, I'm not going to bite.

 

My gut usually doesn't lead me wrong, and my gut tells me they're going to find a way to steepen the 1998-present trendline once again. Let's see if I'm right.

 

I showed you a plot w/ a 12-month running average of the 2 datasets with linear regression since 1979, the overall trends are virtually identical, even if you move the base period around some, the difference in results isn't statistically significant. You showed the exact same data, and tried to say they're somehow significantly different. I really don't understand what you're trying to do here.

I think you used the RSS TMT data, not the TLT data, because I'm getting a completely different result, both w/ a linear fit and a running mean.

 

Oth, I definitely won't argue that GISS is warmer than the HADCRUT & NCDC datasets near the end of the record, and amongst the three long term datasets, it's the one I trust the least esp given that Hansen has worked on this dataset I really don't understand their reasoning behind switching ocean dataset interfaces twice (HADISST-OISSTv2 then ERSSTv3b then ERSSTv4) all of which progressively showed more warming w/ each new dataset change.

I agree with this. It's also structurally dissimilar from year to year.

 

It's been well established that earth's surface, clouds, and other media have thermal emission spectra that are similar to oxygen, which is assumed to be a homogeneous tracer in the earth's middle atmosphere for studying middle troposphere temperatures.

Within the M/W frequencies they're (broadly) similar, but they're each decipherable through differences in localized spectral intensities and distribution, and they don't change enough on a multidecadal scale to alter the trendline much even if they weren't accounted for, relative to the (potential) effects of orbital drift.

 

The latest verification analysis on UAHv6 also suggests a much reduced margin of error, on par with the (supposed) uncertainty estimates of the surface data. Though given the monstrous adjustments to the latter, I have absolutely zero faith in those analyses.

  • Like 1
Link to comment
Share on other sites

Here's a link to my presentation, I could have gone into more detail but was somewhat limited by the audience I was presenting this to and how much time I had to complete it.

 

 

https://docs.google.com/presentation/d/1yTyFAgZAYKkITiHTrPyZPCVBV-9v71G0y4GlGEaM-i8/edit#slide=id.g1d8ec1cb53_0_25

Awesome, I look forward to watching it (once you give me access to it). :)

Link to comment
Share on other sites

Oh haha, it was just a presentation we had in class for geological oceanography class, no one actually recorded it unfortunately

Ah, gotcha. Reading, watching, whatever...same information, different neurological conduit. :P

  • Like 1
Link to comment
Share on other sites

That would be an improvement, but if the "selective" homogenization procedure applied to the buoy data before/after 1998 remains in a player on the trend-line, I'm not going to bite.

 

My gut usually doesn't lead me wrong, and my gut tells me they're going to find a way to steepen the 1998-present trendline once again. Let's see if I'm right.

 

 

I think you used the RSS TMT data, not the TLT data, because I'm getting a completely different result, both w/ a linear fit and a running mean.

 

 

I agree with this. It's also structurally dissimilar from year to year.

 

 

Within the M/W frequencies they're (broadly) similar, but they're each decipherable through differences in localized spectral intensities and distribution, and they don't change enough on a multidecadal scale to alter the trendline much even if they weren't accounted for, relative to the (potential) effects of orbital drift.

 

The latest verification analysis on UAHv6 also suggests a much reduced margin of error, on par with the (supposed) uncertainty estimates of the surface data. Though given the monstrous adjustments to the latter, I have absolutely zero faith in those analyses.

 

While the UAH adjustments are generally less frequent than the surface data, when they're adjusted, the changes are pretty substantial... The latest UAH adjustment was on the order of 0.2-0.3C globally, which blows the surface adjustments out of the water 

Link to comment
Share on other sites

Join the conversation

You can post now and register later. If you have an account, sign in now to post with your account.

Guest
Unfortunately, your content contains terms that we do not allow. Please edit your content to remove the highlighted words below.
Reply to this topic...

×   Pasted as rich text.   Paste as plain text instead

  Only 75 emoji are allowed.

×   Your link has been automatically embedded.   Display as a link instead

×   Your previous content has been restored.   Clear editor

×   You cannot paste images directly. Upload or insert images from URL.

Loading...

×
×
  • Create New...