Chuck Spinney: How Hot is Hot? Case Study in Government Misrepresentation

Knowledge, Politics
Chuck Spinney

Below is a very important 2 part analysis of the meaning of the recent heat wave in the US and and the nature of reported temperature increases in general, and whether or not they can be attributed to increases in CO2 concentrations.

The author, John Christy, is a highly regarded climatologist, albeit a skeptical one.  At the end of Part II, Christie gently eviscerates the recent analysis by climate activist/scientist James Hansen, et al, by definitively showing how Hansen’s analysis is biased to produce a preordained answer, both in terms of Hansen’s  selection of its data interval and his metric of choice. (See Hansen’s op-ed in Washington Post here and I would urge readers to download his report).  Anyone interested in trying to sort the wheat from the chaff in the climate wars ought to study these two papers. (I have not changed a word, but reformatted them in a few places, breaking paragraphs into “bullets” and highlighted i; I also inserted a few comments in [red] to clarify his points.)
Chuck Spinney
Gaeta, Italia
August 13th, 2012 by Roy W. Spencer, Ph. D.

guest post by John Christy, UAHuntsville, Alabama State Climatologist

Let me say two things up front.

  1. The first 10 weeks of the summer of 2012 were brutally hot in some parts of the US. For these areas it was hotter than seen in many decades.
  2. Extra greenhouse gases should warm the climate. We really don’t know how much, but the magnitude is more than zero, and likely well below the average climate model estimate.

Now to the issue at hand. The recent claims that July 2012 and Jan-Jul 2012 were the hottest ever in the conterminous US (USA48) are based on one specific way to look at the US temperature data. NOAA, who made the announcement, utilized the mean temperature or TMean (i.e. (TMax + TMin)/2) taken from station records after adjustments for a variety of discontinuities were applied. In other words, the average of the [adjusted] daily high and daily low temperatures is the metric of choice for these kinds of announcements.

Unfortunately, TMean is akin to averaging apples and oranges to come up with a rather uninformative fruit.

  • TMax represents the temperature of a well-mixed lower tropospheric layer, especially in summer.
  • TMin, on the other hand, is mostly a measurement in a shallow layer that is easily subjected to deceptive warming as humans develop the surface around the stations. [e.g., UHI]

The problem here is that TMin can warm over time due to an increase in turbulent mixing (related to increasing local human development) which creates a vertical redistribution of atmospheric heat. This warming is not primarily due to the accumulation of heat which is the signature of the enhanced greenhouse effect.

Since TMax represents a deeper layer of the troposphere, it serves as a better proxy (not perfect, but better) for measuring the accumulation of tropospheric heat, and thus the greenhouse effect. This is demonstrated theoretically and observationally in McNider et al. 2012. I think TMax is a much better way to depict the long-term temperature character of the climate.

With that as a introduction, the chart of TMax generated by Roy in this post, using the same USHCNv2 stations as NOAA, indicates July 2012 was very hot, coming in at third place behind the scorching summers of 1936 and 1934. This is an indication that the deeper atmosphere, where the greenhouse effect is more directly detected, was probably warmer in those two years than in 2012 over the US.

Another way to look at the now diminishing heat wave is to analyze stations with long records for the occurrence of daily extremes. For USA48 there are 970 USHCN stations with records at least 80 years long. In Fig. 1.1 is the number of record hot days set in each year by these 970 stations (gray). The 1930s dominate the establishment of daily TMax record highs (click for full-size):

Fig1.1-summer.png

But for climatologists, the more interesting result is the average of the total number of records in ten-year periods to see the longer-term character. The smooth curve shows that 10-year periods in the 1930s generated about twice as many hot-day records as the most recent decades. Note too, that if you want to find a recent, unrepresentative, “quiet” period for extremes, the 1950s to 1970s will do (see Part 2 to be posted later). [it is attached beneath this paper]

Figure 1.2 below compares the ten-year averages between high TMax and high TMin records:

Fig1.2-summer.png

There has been a relatively steady rise in high TMin records (i.e. hot nights) which does not concur with TMax, and is further evidence that TMax and TMin are not measuring the same thing. They really are apples and oranges. As indicated above, TMin is a poor proxy for atmospheric heat content, and it inflicts this problem on the popular TMean temperature record which is then a poor proxy for greenhouse warming too.

Before I leave this plot, someone may ask, “But what about those thousands of daily records that we were told were broken this year?” Unfortunately, there is a lot of confusion about that. Records are announced by NOAA for stations with as little as 30 years of data, i.e. starting as late as 1981. As a result, any moderately hot day now will generate a lot of “record highs.” But, most of those records were produced by stations which were not operating during the heat waves of the teens, twenties, thirties and fifties. That is why the plots I’ve provided here tell a more complete climate story. As you can imagine, the results aren’t nearly so dramatic and no reporter wants to write a story that says the current heat wave was exceeded in the past by a lot. Readers and viewers would rather be told they are enduring a special time in history I think.

Because the central US was the focus of the recent heat, I generated the number of Jan-Jul record high daily TMaxs for eight states, AR, IL, IN, IA, KS, MO, NE and OK that includes 2012 (Fig. 1.3):

Fig1.3-summer.png

(Because a few stations were late, I multiplied the number in 2012 by 1.15 to assure their representation). For these states, there is no doubt that the first seven months of 2012 haven’t seen as many record hot days since the 1930s. In other words, for the vast majority of residents of the Central US, there were more days this year that were the “hottest ever” over their lifetimes. (Notice too, that the ten-year averages of TMax and TMin records mimic the national results – high TMin records are becoming more frequent while TMax records have been flat since the 1930s.)

The same plot for the west coast states of CA, OR and WA (Fig. 1.4) shows that the last three years (Jan-Jul only) have seen a dearth of high temperature records:

Fig1.4-summer.png

However, even with these two very different climates, one feature is consistent – the continuously rising number of record hot nights relative to record hot days. This increase in hot nights is found everywhere we’ve looked. Unfortunately because many scientists and agencies use TMean (i.e. influenced by TMin) as a proxy for greenhouse-gas induced climate change, their results will be misleading in my view.

I keep mentioning that the deep atmospheric temperature is a better proxy for detecting the greenhouse effect than surface temperature. Taking the temperature of such a huge mass of air is a more direct and robust measurement of heat content.

Our UAHuntsville tropospheric data for the USA48 show July 2012 was very hot (+0.90°C above the 1981-2010 average), behind 2006 (+0.98 °C) and 2002 (+1.00 °C) and just ahead of 2011 (+0.89 °C). The differences (i.e. all can be represented by +0.95 ±0.06) really can’t be considered definitive because of inherent error in the dataset. So, in just the last 34 Julys, there are 3 others very close to 2012, and at least one or two likely warmer.

Then, as is often the case, the weather pattern that produces a sweltering central US also causes colder temperatures elsewhere. In Alaska, for example, the last 12 months (-0.82 °C) have been near the coldest departures for any 12-month period of the 34 years of satellite data.

In the satellite data, the NH Land anomaly for July 2012 was +0.59 °C. Other hot Julys were 2010 +0.69, and 1998 at +0.67 °C. Globally (land and ocean), July 2012 was warm at +0.28 °C, being 5th warmest of the past 34 Julys. The warmest was July 1998 at +0.44 °C. (In Part 2, I’ll look at recent claims about Northern Hemisphere temperatures.)

So, what are we to make of all the claims about record US TMean temperatures?

  • First, they do not represent the deep atmosphere where the enhanced greenhouse effect should be detected, so making claims about causes is unwise.
  • Secondly, the number of hot-day extremes we’ve seen in the conterminous US has been exceeded in the past by quite a bit.
  • Thirdly, the first 10 weeks of 2012’s summer was the hottest such period in many parts of the central US for residents born after the 1930’s. So, they are completely justified when they moan, “This is the hottest year I’ve ever seen.”

By the way, for any particular period, the hottest record has to occur sometime.

REFERENCE
McNider, R.T., G.J. Steeneveld, A.A.M. Holtslag, R.A. Pielke Sr., S. Mackaro, A. Pour-Biazar, J. Walters, U. Nair, and J.R. Christy, 2012: Response and sensitivity of the nocturnal boundary layer over land to added longwave radiative forcing. J. Geophys. Res., 117, D14106, doi:10.1029/2012JD017578.

August 15th, 2012 by Roy W. Spencer, Ph. D.

Guest post by John Christy, UAHuntsville, Alabama State Climatologist

(NOTE: Fig. 2.2 has now been extended in time.)

I was finishing up my U.S. Senate testimony for 1 Aug when a reporter sent me a PNAS paper by Hansen et al. (2012) embargoed until after the Hearing. Because of the embargo, I couldn’t comment about Hansen et al. at the Hearing. This paper claimed, among other things, that the proportion of the Northern Hemisphere land area (with weather stations) that exceeded extreme summer hot temperatures was now 10 percent or more for the 2006 to 2011 period.

For extremes at that level (three standard deviations or 3-sigma) this was remarkable evidence for “human-made global warming.” Statistically speaking, the area covered by that extreme in any given hotter-than-average year should only be in the lowest single digits … that is, if the Hansen et al. assumptions are true – i.e.,

  • (a) if TMean accurately represents only the effect of extra greenhouse gases,
  • (b) if the climate acts like a bell-shaped curve,
  • (c) if the bell-shaped curve determined by a single 30-year period (1951-1980) represents all of natural climate variability, and
  • (d) if the GISS interpolated and extrapolated dataset preserves accurate anomaly values. (I hope you are raising a suspicious eyebrow by now.)

The conclusion, to which the authors jumped, was that such a relatively large area of recent extremes could only be caused by the enhanced greenhouse effect. But, the authors went further by making an attempt at advocacy, not science, as they say they were motivated by “the need for the public to appreciate the significance of human-made global warming.”

Permit me to digress into an opinionated comment. In 2006, President George W. Bush was wrong when he said we were addicted to oil. The real truth is, oil, and other carbon-based fuels, are merely the affordable means by which we can satisfy our true addictions – long life, good health, prosperity, technological progress, adequate food supplies, internet services, freedom of movement, protection from environmental threats, and so on. As I’ve said numerous times after living in Africa, – without energy, life is brutal and short.

Folks with Hansen’s view are quick to condemn carbon fuels while overlooking the obvious reasons for their use and the astounding benefits they provide (and in which they participate). The lead author referred to coal trains as “death trains – no less gruesome than if they were boxcars headed to the crematoria.” The truth, in my opinion, is the exact opposite – carbon has provided accessible energy that has been indisputably responsible for enhancing security, longevity, and the overall welfare of human life. In other words, carbon-based energy has lifted billions out of an impoverished, brutal existence.

In my view, that is “good,” and I hope Hansen and co-authors would agree. I can’t scientifically demonstrate that improving the human condition is “good” because that is a value judgment about human life. This “good” is simply something I believe to be of inestimable value, and which at this point in history is made possible by carbon.

Back to science.

After reading Part 1 [above], everyone should have some serious concerns about the methodology of the Hansen et al. as published in PNAS. [By the way, I went through the same peer-review process for this post as for a PNAS publication: I selected my colleague Roy Spencer, a highly qualified, award-winning climate scientist, as the reviewer.]

With regard to [Hansen’s assumption] (a) above, I’ve already provided evidence in Part 1 that TMean misrepresents the response of the climate system to extra greenhouse gases. So, I decided to look only at TMax. For this I downloaded the station data from the Berkeley BEST dataset (quality-controlled version). This dataset has more stations than GISS, and can be gridded so as to avoid extrapolated and interpolated values where strange statistical features can arise. This gridding addresses [Hansen’s] assumption (d) above. I binned the data into 1° Lat x 2° Lon grids, and de-biased the individual station time series relative to one another within each grid, merging them into a single time series per grid. The results below are for NH summer only, to match the results that Hansen et al. used to formulate their main assertions.

In Fig. 2.1, I show the percentage of the NH land areas that Hansen et al. calculated to be above the TMean 3-sigma threshold for 2006 to 2011 (black-filled circles). The next curve (gray-filled circles) is the same calculation, using the same base period (1951-1980), but using TMax from my construction from the BEST station data. The correlation between the two is high, so broad spatial and temporal features are the same. However, the areal coverage drops off by over half, from Hansen’s 6-year average of 12 percent to this analysis at 5 percent (click for full-size version):

fig2.1.gif

Now, I believe [Hansen’s] assumption (c), that the particular climate of 1951-1980 can provide the complete and ideal distribution for calculating the impact of greenhouse gas increases, displays a remarkably biased view of the statistics of a non-linear dynamical system. Hansen et al. claim this short period faithfully represents the natural climate variability of not just the present, but the past 10,000 years – and that 1981-2011 is outside of that range. Hansen assuming any 30-year period represents all of Holocene climate is simply astounding to me.

A quick look at the time series of the US record of high TMax’s (Fig.1.1 in Part 1 [above]) indicates that the period 1951-1980 was one of especially low variability in the relatively brief 110-year climate record. Thus, it is an unrepresentative sample of the climate’s natural variability. So, for a major portion of the observed NH land area, the selection of 1951-80 as the reference-base immediately convicts the anomalies for those decades outside of that period as criminal outliers.

This brings up an important question. How many decades of accurate climate observations are required to establish a climatology from which departures from that climatology may be declared as outside the realm of natural variability? Since the climate is a non-linear, dynamical system, the answer is unknown, but certainly the ideal base-period would be much longer than 30 years thanks to the natural variability of the background climate on all time scales.

We can test the choice of 1951-1980 as capable of defining an accurate pre-greenhouse warming climatology. I shall simply add 20 years to the beginning of the reference period. Certainly Hansen et al. would consider 1931-1950 as “pre-greenhouse” since they considered their own later reference period of 1951-1980 as such. Will this change the outcome?

The result is the third curve from the top (open circles) in Fig. 2.1 above, showing values mostly in the low single digits (6-year average of 2.9 percent) being generally a quarter of Hansen et al.’s results. In other words, the results change quite a bit simply by widening the window back into a period with even less greenhouse forcing for an acceptable base-climate. (Please note that the only grids used to calculate the percentage of area were those with at least 90 percent of the data during the reference period – I couldn’t tell from Hansen et al. whether they had applied such a consistency test.)

The lowest curve in Fig. 2.1 (squares) uses a base reference period of 80 years (1931-2010) in which a lot of variability occurred. The recent decade doesn’t show much at all with a 1.3 percent average. Now, one may legitimately complain that since I included the most recent 30 years of greenhouse warming in the statistics, that the reference period is not pure enough for testing the effect. I understand fully. My response is, can anyone prove that decades with even higher temperatures and variations have not occurred in the last 1,000 or even 10,000 pre-greenhouse, post-glacial years?

That question takes us back to our nemesis.

  • What is an accurate expression of the statistics of the interglacial, non-greenhouse-enhanced climate?
  • Or, what is the extent of anomalies that Mother Nature can achieve on her own for the “natural” climate system from one 30-year period to the next?

I’ll bet the variations are much greater than depicted by 1951-1980 alone, so this choice by Hansen as the base climate is not broad enough. In the least, there should be no objection to using 1931-1980 as a reference-base for a non-enhanced-greenhouse climate.

In press reports for this paper (e.g., here), Hansen indicated that “he had underestimated how bad things could get” regarding his 1988 predictions of future climate.

According to the global temperature chart below (Fig. 2.2), one could make the case that his comment apparently means he hadn’t anticipated how bad his 1988 predictions would be when compared with satellite observations from UAH and RSS:

Fig2.2-summer-fixed.gif

By the way, a climate model simulation is a hypothesis and Fig. 2.2 is called ”testing a hypothesis.” The simulations fail the test. (Note that though allowing for growing emissions in scenario A, the real world emitted even more greenhouse gases, so the results here are an underestimate of the actual model errors.)

The bottom line of this little exercise is that I believe the analysis of Hansen et al. is based on assumptions designed to confirm a specific bias about climate change and then, like a legal brief, advocates for public acceptance of that bias to motivate the adoption of certain policies (see Hansen’s Washington Post Op-Ed 3 Aug 2012).

Using the different assumptions above, which I believe are more scientifically defensible, I don’t see alarming changes. Further, the discussion in and around Hansen et al. of the danger of carbon-based energy is simply an advocacy-based opinion of an immensely complex issue and which ignores the ubiquitous and undeniable benefits that carbon-based energy provides for human life.

Finally, I thought I just saw the proverbial “horse” I presumed was dead twitch a little (see Part 1). So, I want to beat it one more time. In Fig. 2.3 is the 1900-2011 analysis of areal coverage of positive anomalies (2.05-sigma or 2.5 percent significance level) over USA48 from the BEST TMax and TMin gridded data. The reference period is 1951-1980:

fig2.3.gif

Does anyone still think TMax and TMin (and thus TMean) have consistently measured the same physical property of the climate through the years?

It’s August and the dewpoint just dipped below 70°F here in Alabama, so I’m headed out for a run.

REFERENCE:
Hansen, J., M. Sato and R. Ruedy, 2012: Perception of climate change. Proc. Nat. Ac. Sci., doi/10.1073/pnas.1205276109.