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Pielke Sr. and SkS Disagreements and Open Questions

Posted on 1 October 2011 by dana1981

Dr. Roger Pielke Sr. has responded to our last set of questions and answers, and we would like to thank him for a civil discourse to this point. Unfortunately, in the meantime Dr. Pielke has taken offense to some challenging, but relatively benign comments (although we think he got in a few licks himself), and decided that his interaction with SkS was over.

To sum up the discussion, there are some points on which we agree, others on which we disagree, and a few others which require further clarification.  We will summarize the disagreements and open questions in the text below, based on our understanding of Dr. Pielke's comments.  Readers are invited to read Dr. Pielke's comments to verify that we are accurately representing them in this summary.

CO2 Contribution to Global Warming

In response to our question regarding what fraction of the observed global warming is due to CO2 and other anthropogenic effects, Dr. Pielke responded:

"~26% of the positive radiative forcing was from CO2"

This is not a complete answer, but the question is a complex one.  However, we believe Dr. Pielke has underestimated the CO2 contribution.  Figure 1 shows the radiative forcing estimates in the 2007 IPCC report.

ipcc forcings

Figure 1:  Global average radiative forcing in 2005 (best estimates and 5 to 95% uncertainty ranges) with respect to 1750.  Source (IPCC AR4).

The radiative forcing from CO2 is well-known, and estimated at 1.66 Watts per square meter (W/m2).  The remainder of the positive radiative forcings add up to 1.63 W/m2.  Therefore, CO2 accounts for approximately 50% of the positive radiative forcing - twice Dr. Pielke's estimate.  Dr. Pielke references research which has suggested that, for example, methane plays a larger role than the IPCC estimate.  However, the radiative forcing from methane (which is well-known) is based on its atmospheric concentration, which is also well-known.  Dr. Pielke also clarified his opinion that soot (black carbon) might account for a larger positive radiative forcing than CO2.  However, aerosols have both warming and cooling effects, with the cooling effects likely being larger in magnitude (Ramanathan and Carmichael 2008).

Answering the SkS Question

Our view of this question is that if we use the current CO2 forcing and a transient climate response of approximately 2°C for doubled atmospheric CO2 (IPCC AR4 best estimate), the atmospheric CO2 increase over the past century has caused approximately 0.9°C warming of the average global surface temperature (best estimate).  This best estimate is more than 100% of the observed surface warming (0.8°C), meaning that all other non-CO2 anthropogenic plus natural effects have most likely had a small net cooling effect over this period.

NRC Report

Dr. Pielke cites the 2005 National Research Council (NRC) report on radiative forcing of climate change in arguing that climate models underestimate the effects of land-use change on climate.  The report does note (emphasis added):

"Regional variations in radiative forcing may have important regional and global climatic implications that are not resolved by the concept of global mean radiative forcing."

However, the NRC report does not share Dr. Pielke's minimization of the role of CO2, or the continued importance of the top the atmosphere (TOA) energy imbalance:

"The strengths of the traditional radiative forcing concept warrant its continued use in scientific investigations, climate change assessments, and policy applications"

"The largest positive forcing (warming)...is from the increase of well-mixed greenhouse gases (CO2, nitrous oxide [N2O], methane [CH4], and chlorofluorocarbons [CFCs])"

OHC as The Global Warming Diagnostic

Dr. Pielke appears to believe that ocean heat content (OHC) by itself is a sufficient "diagnostic to monitor global warming."  We do agree that most of the global energy imbalance goes into the oceans - we even created a high resolution graphic illustrating this point:

where's GW going

However, as the graphic illustrates, nearly 7% of the energy goes into the rest of the climate system.  Moreover, the degree of accuracy of OHC measurements is still quite uncertain: the ARGO network is relatively new, and doesn't measure the deep oceans, and short-term noise in the data remains a concern (i.e. see Domingues et al. 2008). 

Furthermore, we humans are surface-dwelling creatures, so impacts to the climate on the surface is highly significant to us.  And most fast feedbacks are dominated by surface/atmospheric temperatures; so to rely on OHC as the sole diagnostic would disguise the progression of processes that will affect our experience of climate.

Ultimately we stand behind our answer that we must consider all lines of evidence, and all aspects of the climate.  SkS does not believe there should be a single preferred global warming diagnostic.  However, it's also important to note that a lot of energy has gone into the oceans (more on this below).

lymann

Ocean Heat Content anomaly from 0 to 700 metres calculated by various teams (Lyman 2010).

Colleagues' Contributions

Dr. Pielke has yet to acknowledge the frequent climate myth and misinformation propagation of several of his colleagues (most notably Roy Spencer and John Christy).  We do agree that these individuals have done some good scientific research and made valuable contributions, such as the development of the satellite temperature record.  Dr. Pielke says of Roy Spencer:

"Despite the vigor with which you criticize Roy Spencer, he actually has been instrumental in elevating our awareness that natural variations in cloud cover, as a result of temporal variations in atmospheric circulation features, as causing long term variations in the TOA radiative imbalance."

We question the accuracy of this statement.  Much of Spencer's research related to cloud cover has been fundamentally flawed, due, for example, to his over-reliance on an overly simplistic climate model (i.e. see here and here and here).  And while they have made some valuable contributions, they have also done significant damage by misinforming the public and policymakers on climate issues.

Acting on the Prudent path

Although we were able to find common ground with Dr. Pielke on the 'prudent path' of reducing human CO2 emissions, we remain concerned that he continues to vigorously defend his colleagues who make statements that undermine this goal, for example Roy Spencer:

"Just as the deepening horse manure crisis was alleviated by the introduction of the automobile over a century ago, I suspect that our current worries over global warming will evaporate in the coming decades"

While we are happy that SkS and Dr. Pielke find common cause when it comes to how humans should deal with mitigating climate change, we are concerned and confused that Dr. Pielke continues to defend his colleagues who are very clearly opposed to taking this critical action, who think that man-made warming is a non-issue, and who communicate that belief to the public and policymakers in an effort to delay action.

Climate Model Accuracy

Dr. Pielke does not believe that climate model projections have been accurate, particularly at the regional level, and that linking policy to climate model results does more harm than good.

As the saying goes, all models are wrong, but some are useful.  Climate models are by no means perfect and several weaknesses are recognized by the modelers themselves.  For example, models tend to slightly overestimate the lower troposphere temperature trend, underestimate the Arctic sea ice decline, and decadal and sub-regional projections aren't yet satisfactory. However, despite their imperfections, climate models are valuable tools which have been used in many attribution studies, and have given the broadscale picture of what has happened over the past half century reasonably well.  There are examples of models making accurate projections on important metrics, for example in drought (Sheffield and Wood 2007), precipitation extremes (Min et al. 2011), and floods (Pall et al. 2011).  It is the over-emphasizing of their (real or purported) weaknesses that does more harm than good.

Finally, we must bear in mind the possibility that models may paint too rosy of a picture, based on data from the geologic record:

"In the meantime, we need to be cautious. If anything, the models are underestimating change, compared with the geological record. According to the evidence from the past, the Earth's climate is sensitive to small changes, whereas the climate models seem to require a much bigger disturbance to produce abrupt change. Simulations of the coming century with the current generation of complex models may be giving us a false sense of security." (Valdes 2011)

Ocean Acidification

Regarding ocean acidification, Dr. Pielke commented: "Regardless of whether we reduce the alkalinity of the oceans..."  We would like to note that this is not a debatable question: human CO2 emissions are making the oceans more acidic.  For details, see the OA not OK series or booklet, or various posts on the subject, including by renowned ocean expert Ove Hoegh-Guldberg.

Unanswered Questions

From Pielke

Dr. Pielke was dissatisfied with our answers to his questions regarding preferred climate change diagnostics, and whether global warming is a subset of or dominates climate change.  We accept the NRC definition of "climate change" provided by Dr. Pielke.  Our answer remains that we do not have preferred diagnostics of climate change; we must take all lines of evidence and data into consideration, and there are many (i.e. sea-level rise, ice melt, species endangerment and migration, crop yields, heat wave frequency and intensity, etc.).  Based on the NRC definition, the increase in global temperature is a subset of climate change.

From SkS

SkS was dissatisfied with Dr. Pielke's answer to our question about reconciling his colleagues' arguments for low climate sensitivity and the paleoclimate record.

"I do not find the glacial and interglacial periods as useful comparisons with the current climate since when we study them with models, they have large differences in imposed terrain (e.g. massive continetal glaciers over the northern hemisphere which will alter jet stream features, for example).

In any case, I find the discussion of the so-called “climate sensitivity” by all sides of this issue as an almost meaningless activity."

We acknowledge Dr. Pielke's position on this issue, but disagree, and would appreciate an answer to this question.  Ultimately, while there are certainly differences between glacial and interglacial periods, the global energy imbalance must be able to explain the change in surface temperature.  There are also some good paleoclimate analogues to the current climate, like during the Pliocene and the Paleocene-Eocene Thermal Maximum (PETM).

If the equilibrium climate sensitivity is ~1°C for double CO2, as Spencer and Christy and Lindzen argue, a radiative forcing of nearly 20 W/m2 is required to explain glacial-interglacial transitions.  This is three times larger than the net forcing identified in the paleoclimate record during these periods.  That's a big discrepancy; can it be reconciled?  Based on the evidence, we don't believe so.

Further Questions

Although Dr. Pielke appears to have terminated his interactions with SkS, we would like to give him the opportunity to clarify or retract some questionable statements he has recently made on his blog.

Troposphere Warming

Of Santer et al. (2011), Dr. Pielke said:

"they did not recognize that the global average temperature trend in the lower troposphere has been nearly flat  as shown, for example, in the figure below from the RSS MSU data...There has been NO long-term trend since the large El Niño in 1998.  That’s 13 years."

However, Santer et al. concluded that a minimum of 17 years is necessary to identify human effects in the temperature of the lower troposphere (TLT), so why look at the 13-year trend?  Moreover, as Pielke notes, there was a very strong El Niño in 1998, and TLT data is very sensitive to changes in ENSO.  We wonder, will Dr. Pielke will acknowledge that 1998 was a poorly-chosen start date for this analysis?

Ocean Warming

In another blog post, Dr. Pielke said that the upper 700 meters of ocean have accumulated no heat since 2003.  However, we examined the data from several studies on the subject (provided by NOAA), and found that between 2003 and 2009, the upper 700 meters accumulated between 1.1 x 1021 Joules (Levitus - though this reference may be slightly out of date), and 5.6 x 1022 Joules (Palmer), with Willis et al. falling in between at 5.1 x 1021 Joules. 

And of course there's nothing special about the upper 700 meters; von Shuckmann and Le Traon (2011) estimate an increase of 5.9 x 1022 Joules between 2005 and 2010 for 10 to 1,500 meters, and heat is accumulating in the deep oceans as well (i.e. see here and here and here).

While the trends listed above are not statistically significant due to the short timeframe, they are nevertheless most likely positive, and we certainly can't be confident that they are zero, particularly given the order of magnitude discrepancy between the various estimates.  Given this data we wonder, will Dr. Pielke agree that his previous assessment of zero Joules accumulated during this period was incorrect, and that the timeframe (since 2003) and depth (700 meters) is insufficient for a suitable assessment of the climatological trend?

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Comments 51 to 99 out of 99:

  1. Regarding the graphic #48, do you believe that the change in weather from interglacial to glacial has no forcing effect (i.e. weather is defined as feedback only)? A small (negligible) forcing effect)? Dr Pielke pointed out that the equatorward displacement of the polar jet would be one such weather change (a positive forcing for the interglacial transition as pointed out in the paper I linked in #47). The cloud albedo would be different as well (with likely fewer clouds overall). The static diagram also does not explain the hysteresis (the forcing is not sufficient, feedback is required).
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  2. Skywatcher, you said "Why and how this change [in atmospheric jets and ocean currents] causes a threefold increase in sensitivity (and not a decrease) has not been specified, and is presently speculation."

    Allow me to clarify one fact: weather can be forcing or feedback because the energy lost or gained at TOA can depend on weather. Ocean currents are not a factor at TOA, but do greatly influence weather. The weather causes the loss or gain of energy which amplifies the cooling or warming from the other long term forcings. Some weather changes can be considered forcings because the glacial weather conditions are different from interglacial with different energy losses (cloud albedo, meridional flow and energy transfer, water cycle, etc)
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  3. Eric (skeptic) @51, the supposition that weather should be considered as a forcing rather than a feedback presumes that the weather does not respond sensitively to changes in global mean surface temperature. This is not true, for example, of the southern Sub Tropical Front (mentioned by you in 47). The Sub Tropical Front is at least partly driven by the presence of strong westerlies in the latitudes south of Australia and Africa. The location of those westerlies are known to be sensitive to global mean temperature, moving south as climate warms, and north as climate cools - behaviour mimicked by the STF. The sensitivity of the STF's location to temperature is also shown by the fact that its location varies with season.

    The same is also true of the location of the Jet Streams, whose position is primarily determined by the location of the boundaries between Hadley Cells, Ferrel cells and Polar Cells (see diagram below). Although there location is influenced by geographical barriers such as the Himalayas, the global circulation is their primary determinant, and that circulation is determined by the GMST. As temperatures rise, Hadley cell becomes large, pushing the jet streams further from the tropics. As it cools, the Hadley cell shrinks bringing the jet streams closer to the tropics.



    In both cases, because the "weather" effect is temperature sensitive, it is properly treated as a feedback.

    Treating these weather effects as feedbacks rather than as semi-permanent geographical features allows the issue to be stated this way:

    "Measuring temperature and forcing differences between glacial and interglacial will not determine current climate sensitivity because climate sensitivity varies greatly with different temperatures and geographical arrangement."

    So, stated, the claim is obviously open to empirical testing. As it happens, climate sensitivity has been tested across the range of phanerozoic distributions of continents and climate conditions and resulted in very similar values:





    While it is true that changes in ice albedo will have far less effect now than during the LGM, Hansen determined the climate sensitivity for green house gases independent of that for albedo, so that determination is not effected by that difference. Further, current conditions are more susceptible to the water vapour feedback than at the LGM.
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    Response:

    [DB] Upgraded the image quality on Royer Figure 1.

  4. Tom, thanks for your explanation. The effects of weather changes are semi-permanent and not negligible. The effects are manifested in two modes: glacial and interglacial; there is a "cooler weather" effect for the former and "warmer weather" for the latter. Our current NH example is the polar jet starting to migrate south for the winter, but that is not due to average temperature but increased temperature contrast in the NH. When the weather changes in the glacial it is similarly not due to GAT or similar metric. Since it is a response to some original change it is technically a feedback, however, it is not a response to a forcing such as CO2, but rather to a geographic (ice sheet and ocean ice) change. The other Pielke thread had a great argument quoted by Albatross: "Because BC forcing results in a vertical redistribution of the solar forcing, a simple scaling of the forcing with the CO2 doubling climate sensitivity parameter may not be appropriate"."

    The point here is that the forcings pointed out in post 48 are much more different from CO2 than BC is from CO2 and cannot be simply scaled with a CO2 doubling forcing.

    Please send a reference for " As it happens, climate sensitivity has been tested across the range of phanerozoic distributions of continents and climate conditions and resulted in very similar values" I am very interested in what kind of model they used.
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  5. Eric#54: "The effects of weather changes are semi-permanent and not negligible. "

    I wonder if you would care to explain this statement in terms more substantive than the example you cite here. To avoid interrupting the flow of dialogue with Dr. Pielke, perhaps the thread 'Weather vs Climate' would be appropriate for this sidebar.
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  6. Eric (Skeptic) @54:

    The first diagram comes from Royer et al, 2007, and the second from Royer 2008.

    I find your explanation of the seasonal migration of the Hadley cell and Ferrel cells, and consequently the of the jet streams dubious. Specifically, it is well known that the inter tropical convergence zone follows the sun, and the Hadley cells and Ferrel cells follow the ITCZ. Additional explanation in terms of "temperature contrast" seems unnecessary.

    It is also well known that the Hadley cells specifically, have expanded in size with increasing global temperature. This is particularly noticable in South West Western Australia. The Westerlies formed by the returning surface winds of the Ferrel Cell are the major source of winter rainfall in southern Western Australia. During winter, the migration of the Ferrel cell brings the westerlies and the rain they bring north to Perth's latitude. During summer they pass south of the continent. Further north the land lies under the dry, returning air of the Hadley cell, and is arid through out the year. Hence West Australia's characteristic rainfall pattern:



    As previously mentioned, increased temperature expands the Hadley cell, pushing the Ferrel cell and the rain bringing westerlies further south. As a result, they do not come sufficiently north in winter, resulting in dry winters for southern Western Australia:



    This can be seen to be an effect of the changing size of the Hadley cell because summer rainfall has not been effected:



    This same trend is probably a significant cause of the repeated droughts in recent years in southern Africa.

    Turning to the ice age weather effects, you have provided no reason to think the effects are not responsive to temperature. Taking the Sub Tropical Front, the relevant effect on climate is its position relative to the Cape of Good Hope. If it is north of that latitude, the STF, it acts as a barrier to warm water flowing from the Indian Ocean into the Atlantic. Below that latitude, and it presents no barrier. There is nothing in this which prevents its position from being determined by temperature, and hence its being a feedback on temperature. The effect provides a distinct "tipping point", but that in no way obviates its status as a feedback. Similar warming "tipping points" have been postulated in the current circumstances, and while they do mean temperature increases may not by even with increasing CO2, they do not change the basic calculations of climate sensitivity.
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    Response:

    [DB] Replaced links to dynamic remote-hosted graphs to static locally-hosted graphs.

  7. Let's move on to point #2.

    2) Regardless of your reason for choosing 1998 as the starting point for your analysis, our explanation regarding why it was a poor choice remain valid. 1998 was a statistical outlier in the TLT record, and thus is a poor choice for a starting point when estimating a trend, especially since we also know that 13 years is an insufficient timeframe according to the very study you were critiquing (Santer et al. 2011):
    "Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature."
    The starting point makes a big difference in the trend for such short timeframes. The UAH trend is 0.10°C per decade since 1997, 0.06°C per decade since 1998, 0.18°C per decade since 1999, and 0.14°C over the past 17 years. Note that changing the starting date by a single year from 1998 to 1999 triples the UAH TLT trend.
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  8. Regarding point #2, and the weak selection of 1998 as the point at which the TLT became "~flat", Tamino's How Long post is incredibly relevant for those wishing to statistically determine the length of time required before a significant trend emerges from the noise.

    Trends from UAH using woodfortrees - 1980-1992, and 1997,1998,1999-present:

    You can see the 1998 outlier skews trends of 13 years length to be much smaller than the overall trend. A year before or after, as dana shows gives a steeper trend, which happens to be much closer to the long-term trend. 1980-1992 inclusive has a virtually flat trend, that is, 13 years where the noise (and a volcanic eruption outlier) masked the signal.
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  9. All - please see the top and bottom figures in figure 7 in http://www.ssmi.com/msu/msu_data_description.html. Let me know the trends you see starting in different years since 1998.

    My view, is that focusing on a linear trend with respect to a actual nonlinear signal is a substantial oversimplication of how we should expect the climate sytstem to behave both naturally, and in response to the diversity of human climate forcings.
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  10. Prof. Pielke what evidence do you have that the underlying signal (i.e. the forced climate change) is significantly non-linear over such a short timescale?

    Indeed lets look at trends starting in different years around 1998.



    If you start a year earlier, you get a trend of 0.103 degrees C per decade, starting in 1998 it is 0.060 degrees per decade, starting a year later in 1999 it is a whopping 0.183 degrees per decade (which is actually higher than the trend since the start of the UAH dataset, which is 0.138 degrees per decade). In other words, you need to pick 1998 to minimise the trend and the result isn't robust to changing the start date by a year in either direction.

    Please explain to me why we should be looking at the lack of warming since 1998, rather than looking at the trend since 1999, which gives the impression* that warming is accelerating as the post 1999 trend is steeper than the overall trend)?

    I suspect the problem is that the eye is deceived by the El-Nino excursion, computing the statistical trends gives a different picture that is not so heavily biased by that feature.

    *Of course I wouldn't try to make such an argument as a serious point because such short term trends are not robust and hence statistically almost meaningless. This is true whether the trend is large or small.
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  11. Dr. Pielke - "...focusing on a linear trend with respect to a actual nonlinear signal is a substantial oversimplication..."

    Absolutely correct. However, given the inherent noise in the system and measurements, as well presented by Santer et al 2011, a linear trend is is the only marginally justifiable extraction from such a short time period - any more complex fit would simply be statistically unsupportable given the limited evidence.

    And shown the 3x variations in linear trend with just a year variation in start point, 13 years isn't enough for a robust linear fit, either - it's not enough data.
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  12. Dikran @60,

    Dana also calculated the trends using different start dates. Here are some more using the UAH data (which is considered by "skeptics" to be a superior dataset):

    If one starts in 2000: the slope is 0.14 C per decade.
    If one starts in 1996: the slope is 0.13 C per decade.

    Spot the outlier:
    If one starts in 1996: the slope is 0.13 C per decade.
    If one starts in 1997: the slope is 0.10 C per decade.
    If one starts in 1998: the slope is 0.06 C per decade.
    If one starts in 1999: the slope is 0.18 C per decade.
    If one starts in 2000: the slope is 0.14 C per decade.

    As Dana showed above, if one uses at least 17 years of data as the research suggests is required (e.g., Santer et al. 2011) one gets 0.14 C per decade.

    Using the 1998 start date to claim that there has been little or no warming (for 13 years) as Dr. Pielke did is grossly misleading, is a poor choice for obvious reasons, and is simply too short a window to calculate a statistically significant trend, and as such is simply not justifiable or defensible.
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  13. Albatross@62 Indeed, I am somewhat puzzled that Prof. Pielke asks us to "Let [him] know the trends you see starting in different years since 1998.", given that both dana and skywatcher had already done so!

    Along with statistical significance, if you want to suggest there hasn't been any warming, then you also need to estimate the statistical power of the test. If there isn't enough data to reliably reject the null hypothesis when it actually is false, then the lack of statistical significance really isn't saying much!
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  14. Hi Albatross - You said to move the dicussion over here.

    With respect to the global average surface temperature trend, the land portion makes up a significant portion of it. Even more importantly, we need to dissect into regions as that is the spatial scale of major atmospheric circulation features. Land is also where most people live.
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  15. Dikran Marsupial - I look at the figure and see lots of ups and downs. A linear line only explains a small part of the observed pattern.
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  16. I have asked a simple question and you have only partially answered. What is the trend since 2000, 2001, 2002 etc. I realize these are shorter time periods. My point is that if you would to convince people that human's are causing global warming, there are going to ask where the warming has been in the lower troposphere since 2002?

    Dikran Marsupial -

    You can claim it is too short of a time, but you leave yourself vulnerable to the same type of cherrypicking that you accuse others of doing by not including more recent years.

    If you want a convincing analysis for CO2, use the Mauna Loa Observatory plot of CO2 concentrations over time. By bringing in your expected long-term linear trend in lower tropospheric temperature but which is reality is embedded in a nonlinear system, you weaken your argument. In fact, it illustrates that the real climate system is significantly more complicated than presented by the climate models.

    Why not just stay with the risks of the added atmospheric concentration of CO2 as one of the climate concerns?
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  17. Hello Dr. Pielke @64,

    Sorry, there has been a miscommunication. I provided the wrong link. I requested that further discussion of the land use forcing be continued on the following thread.

    This thread is now dedicated to discussing the curious and puzzling choice by you to select 1998 as the start point for your trend.
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  18. Prof. Pielke writes "You can claim it is too short of a time, but you leave yourself vulnerable to the same type of cherrypicking that you accuse others of doing by not including more recent years."

    This is not correct, I explicitly said that I would not base a serious argument on such short term trends, precisely becuase they are not robust and statistically meaningless. The additional trends over even shorter periods are even less robust, and even more statistically meaningless.

    I asked you for evidence that the underlying signal (i.e. the forced climate change) is significantly non-linear over the sort of timescales we are discussing and you have presented none. Of course the climate system has non-linearities, but that does not mean that a linear approximation is not entirely reasonable in this situation.

    I do not wish to divert the discussion onto CO2 or any other cause of the trend. The concern is with your use of trends computed over too short a period to have any statistical robustness.
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  19. Prof. Pielke wrote "I look at the figure and see lots of ups and downs. A linear line only explains a small part of the observed pattern. "

    The "ups and downs" are essentially noise, not signal. They are caused by internal variability, e.g. ENSO and say nothing about the underlying signal (i.e. the forced climate change).

    I am rather concerned that an experienced scientist should draw conclusions by "looking" at data, rather then performing a proper statistical analysis of the data. Human beings are all too good at detecting patterns in data where no pattern exists, which is why scientists use statistics.
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  20. Dikran Marsupial - I recommend you and other readers read Lucia's discussion of this issue on her weblog post; e.g. see

    http://rankexploits.com/musings/category/global-climate-change/gcms/

    and other related posts. She has statistically looked at this issue.

    The short time period does raise the issue as to when you expect the upturn to recommence.
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  21. It seems to me that two graphs by Tamino would help illustrate this discussion.

    The first shows the statistical significance of linear trends in Gistemp from the start year to June, 2011:



    Although Tamino uses a different temperature index (because he is responding to Steve Goddard, not Dr Pielke, the point remains the same. In the case of Gistemp, the trend since 2002 has insufficient data to distinguish between an underlying trend of between +/- 0.24 degrees C per decade. That is, consistent with the data, from 2002 to June, 2011, the temperature data could reflect a long term warming or cooling of 0.24 degrees per decade plus noise. (Please note the confidence interval is estimated by eyeball, so it could be +/-0.02 from indicated value.) It is likely that UAH or RSS will constrain the trend even less over such short intervals in that they react much more strongly to ENSO events than does the surface temperature data.

    For completeness, the Gistemp data from 1998 to June, 2011 is consistent with long term trends between +0.27 degrees per decaded and -0.03 degrees per decade.

    In contrast, the trend since 1994 (17 years ago) could lie between +0.08 and +0.28 degrees per decade. That from 1981 could lie between +0.13 and +0.23 per decade.

    The possible range of the trend increases from 0.1 degrees per decade for 30 years data to 0.2 for 17, 0.3 for 13 (1998) and 0.48 for 9 (2002). As the temperature data itself never varies by more than 0.023 over the period shown, or by more than 0.01 degree in a single year, decadal trends with uncertainties greater than ten times those values are clearly useless.

    Fortunately we are not in a situation in which we do not know the major sources of noise in the global means surface temperature. The three strongest sources of noise are, in order of strength, ENSO, volcanic eruptions and the eleven year solar cycle. Because these sources of noise are well known, and their strength quantified, their influence can be removed from the temperature data:


    (Click on image to read accompanying article.)

    As Dr Pielke believes the "flat" trend from 1998 (and 2002) is significant, perhaps he could point to the flat trend in the data once adjusted for these well known sources of noise?
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  22. Dr Pielke, it is funny you should ask about a return to an 'upturn, when we are presently above the long-term trend in the UAH data, as shown in my post at #58.

    We have been above the 30-year trend for most of the time since 2001. What gives you cause for thinking the trend has stopped? Did you think it had stopped in 1992?
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  23. Dr Pielke @70, with respect, linking to a list of posts, at least one of which has nothing to do with temperatures is not very useful. Which post did you have in mind? And in what way does it support your position?
    0 0
  24. Hello Dr. Pielke,

    The discussion is getting side tracked. Let us recall that the topic at issue here is the choice of 1998 as a start date to support the claim (made on your blog) that there has been little or no warming for 13 years. Do you agree that it was perhaps an inappropriate start date and is without statistical significance? I'm sure that Lucia and Tamino would concur.

    Further, the choice of 1998 (and more recently 2002) is also puzzling given that you said on your blog that "I agree with Santer et al that “[m]inimal warming over a single decade does not disprove the existence of a slowly-evolving anthropogenic warming signal".

    Your arguments against using linear trends are also puzzling, especially given that in a recent paper that you co-authored with Christy et al. (2010), you used linear trends extensively. In fact, Adobe tells me that the word "trend" appears 126 times in your paper. Additionally, why is using a linear trend acceptable to suggest that there has been no warming for 13 years, but using a linear trend to challenge that assertion is not?
    0 0
  25. Tom Curtis - You write

    "As Dr Pielke believes the "flat" trend from 1998 (and 2002) is significant, perhaps he could point to the flat trend in the data once adjusted for these well known sources of noise?"

    First over the period ~2002 to 2011 the trend in the RSS MSU LT data is nearly flat - http://www.ssmi.com/msu/msu_data_description.html; see Fig 7.

    I never said it was statistically significant, but it certainly is distinct from the plots you have above. The surface and lower tropospheric trends are supposed to be in synch and they clearly are not as we reported in

    Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2009: An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., 114, D21102, doi:10.1029/2009JD011841. http://pielkeclimatesci.wordpress.com/files/2009/11/r-345.pdf

    Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2010: Correction to: "An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., 114, D21102, doi:10.1029/2009JD011841", J. Geophys. Res., 115, D1, doi:10.1029/2009JD013655. http://pielkeclimatesci.wordpress.com/files/2010/03/r-345a.pdf

    In terms of the "well known sources of noise" these are not noise but part of the climate system.
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  26. Albatross - Linear trends are used in Christy et al since that is what everyone is using and we were examining the data using that widely applied (but inadequate) metric.

    If you look at the RSS MSU data, the data tells us that there has been little if any warming in the lower troposphere since ~2002. There is no other way to spin the data.

    You can make the claim that this is due to natural variability and I agree with that. However, it does not change that the trend is ~flat over recent years. I am quite puzzled by any disagreement with the obvious. You could also say there was rapid warming in 2009 and 2010 in that data and you would be right.

    What is the purpose in disagreeing with a plot of the data?

    My recommendation is to focus on the fact that CO2 concentrations are steadily going up. By linking to the temperature trends, if it does not evolve the way the models predict, you are fueling those who conclude that CO2 is not a problem to be concerned with.

    By focusing on the increase in atmospheric concentration, however, which has (very incompletely known) biogeochemical effects, you would be able to build a broader consensus that this an issue to be dealt with. As it is you are exposed to the more complex response of the climate system in terms of temperatures to the wide diversity of climate forcings. This is why, in my view, you are so vigorously defending the model-predicted linear trend of the global average surface temperature when anyone presents data that conflicts, even if on a short time period.

    My question to you, is what is your expectation of the RSS MSU LT temperature anomalies over the next 5 and next 10 years?
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  27. It is not a disagreement with the data. It is a disagreement with the usage of the data.

    You agree that the timespan is too small to smooth out natural variability. Why push an irrelevant point then?

    It would not be valid to say that there was rapid warming in 2009 and 2010.
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  28. pielkesr#76: "What is the purpose in disagreeing with a plot of the data?"

    So if we do not disagree with a plot such as this:



    we must conclude there a number of short periods with 'little if any warming.' If these short flat spots are real and if they can be taken as signals of 'natural variation,' why would that matter over the long term? The long term warming trend swamps these supposed natural variations.
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  29. Dr. Pielke, you suggest TLT is not evolving the way models predict, and ask
    "what is your expectation of the RSS MSU LT temperature anomalies over the next 5 and next 10 years?"
    However, as Santer et al. (2011) showed,
    "Because of the pronounced effect of interannual noise on decadal trends, a multi-model ensemble of anthropogenically-forced simulations displays many 10-year periods with little warming."
    In short, you're asking the wrong question. The long-term trend is often masked by short-term noise over periods on the order of a decade.

    However, we're going to explore this issue in greater depth in an upcoming blog post, so unless you have anything more to add to this particular discussion, we should move on to point #3.
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  30. WoodForTrees: RSS MSU TLT plotted with 17 year mean

    The 17 year timespan determined by Santer, et al. is not flat.

    Based on this dataset, my expectation of the 17 year mean is 0.32 for 2016 and 0.42 for 2021. The raw temperature anomaly has wide divergence from that mean, so I am not going to hazard a guess.
    0 0
  31. muoncounter - The linear regression is certainly correct. However, it appears a two-piece linear regression split about 2002 fits the data better. Also, why have you not extended to to September 2011?
    0 0
  32. dana1981 -

    Regarding

    "However, as Santer et al. (2011) showed,
    "Because of the pronounced effect of interannual noise on decadal trends, a multi-model ensemble of anthropogenically-forced simulations displays many 10-year periods with little warming."

    In short, you're asking the wrong question. The long-term trend is often masked by short-term noise over periods on the order of a decade."

    I assume you are convinced the linear trend will then pick up soon. I am not as convinced as you are as I have less confidence in the models. However, time will tell which of us is correct.

    I agree; its time to move on.
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  33. Dr Pielke @75,

    1) The comments on your blog where made in a critique of Santer et al, 2011. They discuss detecting the signal of human effects on tropospheric temperature, and conclude (from their abstract):

    "A single decade of observational TLT data is therefore inadequate for identifying a slowly evolving anthropogenic warming signal. Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature."


    Therefore, for their purposes, and by extension for the purposes of this discussion, the change in tropospheric temperatures due to human influences are the signal, while changes due to natural variability are noise. If we where studying the effect of ENSO on global temperatures, then the anthropogenic warming and solar and volcanic influences would be noise, and ENSO related variability would be signal. But we are not.

    2) Nobody that I know of says the linear trend of the data between 1998 and 2011 exlcusive, or 2004 and 2011 exclusive is not flat. What is disputed is whether that flatness is because the anthropogenic warming (signal) has ceased or significantly reduced; or because those intervals coincide with particularly strong natural variations which obscure the anthropogenic signal. Given that is the core issue, IMO at least, would you be so kind as to clearly state whether you think the flatness in the temperature trend between those intervals is due to a reduction of the anthropogenic warming (signal) or due to coincidence with strong natural variations (noise)? If the former, would you also state what relevance the flatness has to Santer et al, 2011 beyond the fact that they show that intervals at least 17 years are needed to reliably distinguish a weak warming signal (as predicted for climate models in the early 21st century) against background natural variablity? Frankly, I can see none!

    3) Given that we know that El Nino's introduce a strong warming effect, and La Nina's a strong cooling effect to global temperatures, and given that Santer et al, 2011 where discussing detection of an anthropogenic warming signal, can you explain the appropriateness of choosing as a start date the year with one of the three strongest El Nino's in 136 years of records (1998) (SOI) and ending with one of the strongest La Nina's over the same period and the second weakest solar minimum in over a hundred years.



    Does not such a choice of start and end date maximize the influence of natural variability on the data, and thereby minimize the ability to detect the anthropogenic trend in the signal?

    Given that a very large number of people, including politicians in control of our policy response to climate change, believe that the flat temperatures between 1998 and 2011 are a result of a cessation of anthropogenic warming, do you not wish to correct the record and firmly indicate that that flatness is only the consequence of natural variability and in no way indicates that we can afford to not respond to climate change?
    0 0
  34. pielkesr#81:

    I cited the source of the graph in #78, which was the same source as used here.

    Wouldn't splitting the linear regression at 2002 require some physical justification for so doing? Or is it just to get 'a better fit'?
    0 0
  35. Moving on to point #3:

    3) We appreciate your acknowledgment that your blog post claiming that OHC has not increased since 2003 was incorrect. We agree that increase in OHC for the upper 700 meters has slowed in recent years. However, as we discussed in the post above, and Rob P's recent post, and John's post today, heat is also accumulating in the oceans at depths below 700 meters.



    Hansen et al. (2011) note that
    "The inferred planetary energy imbalance, 0.59 ± 0.15 W/m2 during the 6-year period 2005-2010, confirms the dominant role of the human-made greenhouse effect in driving global climate change."
    See their Figure 10, which uses ARGO data to 1500 meters:



    We do not agree with recommending OHC as the primary metric to monitor global warming. Firstly, the OHC data is sparser and younger than surface temperature measurements, and deep ocean data is lacking. Hansen et al. estimate that only ~55% of the global energy imbalance between 2005 and 2010 went into the upper 700 meters, and ~70% into the upper 1500 meters of ocean. Thus relying exclusively on ARGO data would result in neglecting 30 to 45% of the global energy imbalance over this period.

    Additionally, as we have repeatedly noted, we do not endorse or understand the need or the logic behind adoption of any single metric as 'the primary assessment tool' to monitor global warming. Arguably, the climate system of the Earth is as complex as the human body, yet we don't expect any single metric to indicate the health status of the body. It's critical to take all metrics and lines of evidence into account.
    0 0
  36. Dr. Pielke wrote in #76: "This is why, in my view, you are so vigorously defending the model-predicted linear trend of the global average surface temperature when anyone presents data that conflicts, even if on a short time period."

    I'm sorry, but what model(s) are we talking about here? I'm not aware of any which are stated to predict a linear trend on short time scales. Obviously, that wouldn't make any sense given that there will inevitably be deviations due to major volcanic eruptions, solar output variation, internal heat transfer, and other such factors.

    Thus, if we accept that linear trend projections are meant to refer only to the long term outcome then rejecting the idea that short term deviations invalidate the projection is not indicative of an 'agenda', but rather simply awareness of the (long term) intent and adherence to basic statistical analysis.
    0 0
  37. Tom Curtis - You write

    "....they show that intervals at least 17 years are needed to reliably distinguish a weak warming signal (as predicted for climate models in the early 21st century) against background natural variablity?"

    This "weak" signal is why we need to broaden the metrics we use to assess the role of humans on the climate system.

    Such a hiatus in global warming was not anticipated by anyone that I am aware of prior to the last few years. Indeed, Jim Hansen specifically said [http://pielkeclimatesci.files.wordpress.com/2009/09/1116592hansen.pdf]

    "Contrary to the claim of Pielke and Christy, our simulated ocean heat storage (Hansen et al., 2005) agrees closely with the observational analysis of Willis et al. (2004). All matters raised by Pielke and Christy were considered in our analysis and none of them alters our
    conclusions.

    The Willis et al. measured heat storage of 0.62 W/m2 refers to the decadal mean for the upper 750 m of the ocean. Our simulated 1993-2003 heat storage rate was 0.6 W/m2 in the upper 750 m of the ocean. The decadal mean planetary energy imbalance, 0.75 W/m2, includes heat
    storage in the deeper ocean and energy used to melt ice and warm the air and land. 0.85 W/m2 is the imbalance at the end of the decade.

    Certainly the energy imbalance is less in earlier years, even negative, especially in years following large volcanic eruptions. Our analysis focused on the past decade because: (1) this is the period when it was predicted that, in the absence of a large volcanic eruption, the increasing greenhouse effect would cause the planetary energy imbalance and ocean heat storage to rise
    above the level of natural variability (Hansen et al., 1997), and (2) improved ocean temperature measurements and precise satellite altimetry yield an uncertainty in the ocean heat storage, ~15% of the observed value, smaller than that of earlier times when unsampled regions of the ocean created larger uncertainty."

    Also, the issue of El Nino causing a warming signal. This is why in the 1990s, with the 1998 one being an example, it was claimed we would be having more of them. This has not, however, occurred as anticipated.

    The bottom line, in my view, is that we do not understand the climate system as well as claimed on SkS (and by the IPCC). It does not mean the human role is less important, but that it is more diverse in its forcings, and the natural climate forcings and feedbacks are larger than previously assumed. Judy Curry has very well spoken to this later issue, and if you have not already done so, I recommend you read her view on this on her weblog.

    Focusing on a "weak long term warming" signal, as the primary focus is not an effective way to present the climate issues to the public and policy communities.
    0 0
  38. muoncounter - You split data when you see an obvious breakpoint but do not have a preconceived test of what you are expecting. You would not split the data if you are examining an hypothesis (i.e. a "weak long term" global warming).

    Both approaches are appropriate.
    0 0
  39. dana1981 - Regarding

    "We appreciate your acknowledgment that your blog post claiming that OHC has not increased since 2003 was incorrect. We agree that increase in OHC for the upper 700 meters has slowed in recent years. However, as we discussed in the post above, and Rob P's recent post, and John's post today, heat is also accumulating in the oceans at depths below 700 meters."

    The OHC accumulation for the upper 700m since 2003 is positive but small [see http://oceans.pmel.noaa.gov/]. We seem to agree on tha (as does others such as Kevin Trenberth). If there is heat accumulating at depth (and I have been discussing this issue at Real Climate, the question is whether we see this transfer of heat downward in the Argo data).

    Regardless, if the heat is actually there, it has important consequences:

    1. The use of the global annual average surface temperature to monitor global warming misses a component of this heating. This means the current trends using this metric underestimate global warming, but also make the difference between its trend and that of the lower tropospher even greater.

    2. The reduction of surface ocean heating means that the evaporation of water vapor into the atmosphere would be less. Indeed, in recent years, the water vapor content in the tropsphere does not seem to have been increasing.

    3. If there is heat at depth, it is hard to see how it quickly remerge back into the atmosphere in order to affect weather.

    Thus, the identification of greater heating at depth introduces yet another complexity into the real climate system.
    0 0
  40. Prof. Pielke wrote: "You split data when you see an obvious breakpoint but do not have a preconceived test of what you are expecting."

    This is simply incorrect. There are statistical tests for determining whether there is significant evidence for the existence of a breakpoint (e.g. segmented regression, although I personally would probably use a Bayes factor based approach). Seeing an "obvious breakpoint" would be a good reason to perform the test, but it would not be good scientific practice to assert the existence of a breakpoint without first demonstrating that there were statistically significant evidence for that hypothesis (or a physical reason as muoncounter suggests).

    "You would not split the data if you are examining an hypothesis (i.e. a "weak long term" global warming)."

    This is also incorrect, whether you split the data or not would depend on the nature of the hypothesis. If the hypothesis were "the climate has warmed more slowly since 1998", for example, it would be difficult to formulate an appropriate statistical test without splitting the data.

    "Both approaches are appropriate."

    I certainly agree with that, however regarldless of which approach is taken, it would not be good scientific practice to base an argument on a trend in the absence of statistically signifiant evidence. It is a very bad idea to analyse the data using your eyes only, as I said human beings are very good at seeing patterns in data where they don't actually exist, which is why we have statistics so we can test objectively if our intuitions are reasonable. It is a safety valve that science has found very useful over the years.
    0 0
  41. Prof. Peilke @88, Would it be possible to do a statistical test to determine whether there is a change point in the data. My girlfriend does this with rainfall data, I don't pretend to understand the methodology but it basically detects if there is a change in the data to a new trend or phase. With rainfall these changes can often be partially attributed to teleconnections such as the NAO. I believe it can also be applied to discharge data but I'm not sure whether it would be applicable to temperature data.
    0 0
  42. Maybe I should have read Dikran Marsupial post @ 90. I think my girlfriend uses a different method, I will have to ask her.
    0 0
  43. Hyperactive Hydrologist Breakpoint detection methods are indeed applicable to temperature data, they are used for example in homogenising raw surface statation data to account for issues such as a change of measuring device or moving the site of the station etc. There are a variety of methods for performing a statistical test for the existence of a breakpoint, segmented regression just had a fairly clear Wikipedia page. The important thing is to actually perform some appropriate statistical test rather than relying on judging by eye, which is notoriously unreliable.
    0 0
    Moderator Response:

    [DB] Dikran, if I'm not mistaken, Tamino explores a method of breakpoint detection here:

    http://tamino.wordpress.com/2010/08/13/changes/

    [Dikran Marsupial] Yes, Taminos article is well worth reading, although the test he uses is a little basic, ideally the test ought to account for the increase in the degrees of freedom of the model, but that is a more subtle issue not needed to make the basic point of letting the data choose the model, rather than unintentionally cherry picking by eye (and performing a significance test).
  44. Hyperactive Hydrologist - This test is certainly worth doing.
    0 0
  45. dana1981 - With respect to the reported deeper ocean heating, why would this heating recently have become larger? I recognize that the data has become better in recent years, however, the mechanism of heat transfer to depth likely would not have changed that much of time.

    If this heat was going to depths for all of the previous years, it increases the magnitude of global warming during those years.

    What is your perspective on this?
    0 0
  46. Prof. Pielke wrote "This test is certainly worth doing."

    I would go further such a test ought to be a necessary pre-condition; it ought to be incumbent on the scientist to be able to state whether the hypothesis has statistically significant support from the data prior to publically putting forward the hypothesis. This is especially true in a contentious issue of public interest, such as climate change.
    0 0
  47. Dikran Marsupial - Hypothesis testing involves seeking to refute it. In my post

    http://pielkeclimatesci.wordpress.com/2010/11/15/hypothesis-testing-a-failure-in-the-2007-ipcc-reports/

    I wrote

    "There has been a development over the last 10-15 years or so in the scientific peer reviewed literature that is short circuiting the scientific method.

    The scientific method involves developing a hypothesis and then seeking to refute it. If all attempts to discredit the hypothesis fails, we start to accept the proposed theory as being an accurate description of how the real world works.

    A useful summary of the scientific method is given on the website sciencebuddies.org where they list six steps

    1. Ask a Question
    2. Do Background Research
    3. Construct a Hypothesis
    4. Test Your Hypothesis by Doing an Experiment
    5. Analyze Your Data and Draw a Conclusion
    6. Communicate Your Results"
    0 0
  48. Prof. Pielke The set of six steps suggested by sciencebuddies.org seems like very good guidance to me. I don't know how to say this less bluntly, but as far as I can see, you have skipped step four/five in that you are making arguments here based on short term trends without properly testing the statistical significance those trends, or examining the statistical power of the test, before communicating your results.

    In addition as far as I can see the hypothesis has not been clearly and unambiguously stated in a way in which it can be properly tested, so step three has also recieved less attention than perhaps it should. What exactly is the hypothesis that you seek to support using the post-1998 trends?
    0 0
  49. Dr. Pielke:
    "The OHC accumulation for the upper 700m since 2003 is positive but small [see http://oceans.pmel.noaa.gov/]. We seem to agree on tha (as does others such as Kevin Trenberth)."
    Yes, I think we're all in agreement that the accumulation in the upper 700 meters has been relatively small, as compared to previous decades. However, there's nothing special about the 700 meter mark, either. And the warming of the upper 1500 doesn't appear to have slowed appreciably.
    "If there is heat accumulating at depth (and I have been discussing this issue at Real Climate, the question is whether we see this transfer of heat downward in the Argo data)."
    I'm not sure that is the question. It's an interesting question whether or not the ARGO network could detect this transfer, but regardless of the answer to this question, the heat at greater depths has been measured. I view your question more in the "interesting" category than "important", necessarily.
    "Regardless, if the heat is actually there, it has important consequences:

    1. The use of the global annual average surface temperature to monitor global warming misses a component of this heating. This means the current trends using this metric underestimate global warming, but also make the difference between its trend and that of the lower tropospher even greater."
    I don't follow you here. I agree with the first sentence about the heat in the deeper oceans not being reflected in surface temperatures. But heat going into the deep oceans doesn't impact surface temperatures or the ratio of TLT to surface temperatures.
    "With respect to the reported deeper ocean heating, why would this heating recently have become larger?...If this heat was going to depths for all of the previous years, it increases the magnitude of global warming during those years."
    I don't know - I'm no oceans expert, and I'm sure there will be a lot of research on this subject in the near future, just as there has been more research on OHC in deeper layers. It's an important question.
    0 0
  50. I'd like to echo Tom's sentiment:

    Dr Pielke, [many policy makers] believe that the flat temperatures between 1998 and 2011 are a result of a cessation of anthropogenic warming, [will you acknowledge] that that flatness is [a temporary result] of natural variability[...]?
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