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Friday, July 21, 2017

+Myth: The Tropospheric Hot Spot does not Exist

This post is part of a series addressing issues related to the hot spot. The other parts of this series are listed in the "Myths about the Hot Spot" section of the "Quick Scientific Debunking" page.


The outline for this post is as follows:
  1. The Myth and Its Flaw
  2. Context and Analysis
  3. Posts Providing Further Information and Analysis
  4. References

This is the "+References" version of this post, which means that this post contains my full list of references and citations. If you would like an abbreviated and easier to read version, then please go to the "main version" of this post.

References are cited as follows: "[#]", with "#" corresponding to the reference number given in the References section at the end of this post.




1.  The Myth and Its Flaw



Climate models predict that in moist tropical areas, a region of the lower atmosphere will warm more than Earth's surface. This is known as the "hot spot" [8; 16, pages 14 and 42; 31, page 6; 32]. The myth claims that there is little-to-no evidence of a hot spot, or the scientific evidence argues against the hot spot's existence.

Proponents of this myth include David Evans [1 - 7; 109; 148; 149; 171; 172; 189; 193; 203], Stefan Molyneux [7], Judith Curry [8], Richard Lindzen [9, page 942], S. Fred Singer [10; 211; 212], Christopher Monckton [10; 11], Anthony Watts [12; 54], John Christy [8; 13 - 17; 209], Roger Pielke Sr. [8; 15; 209], Jospeh D'Aleo [16; 17], James Wallace III [16; 17], Steve McIntyre [18], Ross McKitrick [108], Matt Ridley [164], The Daily Caller [19], Paul Homewood [20], Tom Nelson [21], Roy Spencer [32; 117; 158], Vladan Ducic [144; 145], A. S. Lavrov [146], and a number of blogs including WattsUpWithThat [22 - 24], Climate Etc. [147], Global Warming Policy Foundation [161], the Heartland Institute [162], Popular Social Science [163], GlobalWarming.org [159], and Friends of Science [160].

Christy, D'Aleo, Wallace III [16; 17], and an organization known as ICECAP [200], use the myth to attack the US Environmental Protection Agency's attempts to regulate CO2 emissions. Interestingly, a Friends of Science representative objects to the method Christy, D'Aleo, and Wallace III use to claim that there was no hot spot [210, comment from Ken Gregory in the comments section]. Myth advocates therefore do not necessarily agree with one another.

Based on the myth proponents listed above, this myth's bandwagon includes some of the most prominent "skeptics" of the mainstream scientific consensus on man-made climate change. This group of "skeptics" includes Curry and Christy, two of the four witnesses who testified in a climate science Congressional hearing held earlier this year [110; 111]. And of all the myth defenders, David Evans may be the most strident and persistent in his defense of the myth. For example, Evans says:


"Memo to believers of global catastrophe: Here’s a strategic tip — run, flee, hide, and avoid the Hot Spot argument at all costs. (You can’t win) [149]."

Though I do not buy into the "global catastrophe" straw man [150, section 3.2.3 on page 41, pages 48 - 50] Evans offers, I also do not want to "run, flee, [and] hide" when told to. So let's examine the hot spot argument / myth.

The myth's flaw: tropical precipitation/convection patterns [45; 97] and paleoclimate data [46; 118] provide evidence of the hot spot, as do the majority of satellite analyses [27; 33; 34; 37; 43; 214], radiosonde analyses [55 - 59; 63; 64], and re-analyses [77; 89 - 92]. So the preponderance of the evidence shows that hot spot exists, contrary to the myth. Scientists have had evidence of the hot spot since at least 2004 [33]. Yet myth proponents typically obscure this point by using cherry-picking to avoid evidence of the hot spot, or by failing to acknowledge their sources show the hot spot.



2. Context and Analysis



Earth's atmosphere contains multiple layers. The layer closest to the Earth's surface air is known as the troposphere. Tropospheric temperature decreases with increasing height; the rate of decrease is known as the tropospheric lapse rate

Climate models and basic physical theory predict that warming at Earth's surface will cause more water to evaporate, especially over tropical oceans. This evaporation increases the amount of water vapor in the air, since warmer air can hold more water vapor. The vapor-rich air then rises into the troposphere by convection. The water vapor subsequently condenses with increasing tropospheric height, since tropospheric temperature and pressure decreases with increasing height.

Condensation of water vapor releases some of the energy that went into evaporating the water; this is known as release of latent heat. So water vapor condensation causes more warming of the lower troposphere and even more warming of the upper troposphere. This latent heat release shrinks the rate at which tropospheric temperature decreases with increasing height; therefore latent heat release reduces the magnitude of the tropospheric lapse rate [10; 25, pages 4 and 22; 26, from 31:01 to 31:48; 27 - 30; 50; 52; 192; 216, pages 7 and 8; 217, pages 101 and 102], as depicted in figure 1:

Photo:

Figure 1: A diagram of tropical tropospheric warming reducing the magnitude of the tropospheric lapse rate (adapted from Crok, Strengers, and Verheggen [31, page 3]). The horizontal dimension represents temperature, with temperature increasing as one goes to further right. The vertical dimension represents altitude in the troposphere, with altitude increasing as one goes further up from Earth's surface at the black line. The blue line represents the tropical temperature profile before warming, while the red line represents the tropical temperature profile after warming. Latent heat release causes more warming with increasing height [10; 25, pages 4 and 22; 26, from 31:01 to 31:48; 27 - 30; 50; 52; 192], leading to the red line being steeper than the blue line. As a result, there is less of a temperature decrease with increasing height after tropical warming. Thus the lapse rate's magnitude is greater for the blue line than for the red line, indicative of a lapse rate reduction in response to tropical warming.


So the tropical troposphere should behave somewhat like a moist adiabat, in which the rate of warming increases with increasing height in response to water vapor condensing from vapor-saturated air [10; 25, pages 4 and 22; 26, from 31:01 to 31:48; 27 - 30; 50; 52; 192].

The aforementioned tropical warming amplification is called the tropical tropospheric hot spot by many myth proponents [8; 16, pages 14 and 42; 31, page 6; 32]. As myth proponent Roy Spencer puts it:

"One of the most vivid predictions of global warming theory is a “hotspot” in the tropical upper troposphere, where increased tropical convection responding to warming sea surface temperatures (SSTs) is supposed to cause enhanced warming in the upper troposphere [32]."

So the hot spot I will discuss relates to amplification of warming as one goes from the tropical surface to higher in the tropical troposphere [8; 16, pages 14 and 42; 31, page 6; 32]. This is different from the question of whether the amount ormagnitude of observed tropospheric warming matches the amount of warming projected by climate models [31, pages 5 - 7; 108]; I address the "magnitude" issue in"Myth: Santer et al. Show That Climate Models are Very Flawed". So, for the sake of argument, I will take the advice of myth proponent John Christy[8; 13 - 17; 209] and not compare observations to models:


"Section III. Research Design

Unlike some research in this area, this research does not attempt to evaluate the existence of the THS [tropical hot spot] in the real world by using the climate models. This would constitute a well-known error in mathematics and econometrics [...] [16, page 14]."

But in case you are interested in what the models show, figure 2 depicts a modeled hot spot (amplification of warming with increasing height in the tropics) in response to warming caused by increased solar activity or in response to warming caused by increased carbon dioxide (CO2):


Figure 2: ECHAM3/LSG model (European Center/Hamburg Model 3 / Large Scale Geostrophic coupled atmosphere-ocean climate model) simulation of the atmospheric response to (a) increased solar forcing (from increased solar output) and (b) increased CO2 forcing (from increased CO2 levels). Colored areas indicate significant responses, with darker blues indicating cooling and darker reds indicating warming. The horizontal axis represents latitude, with the tropics being between roughly 30°N and 30°SThe vertical axis represents altitude, with decreasing atmospheric pressure as altitude increases [112, page 707]. The tropical troposphere lies below 150hPa, while the tropical stratosphere is above 70hPa [65]. Tropical tropospheric warming increases with height in both panels a and b, indicating that the hot spot forms in response to both solar-induced warming and CO2-induced warming. In contrast, strong tropical stratospheric cooling comes with CO2-induced warming, but not solar-induced warming. This figure is taken from a 2001 report of the United Nations Intergovernmental Panel on Climate Change (IPCC) [112, page 707].

Myth proponents claim that scientific evidence argues against the hot spot's existence, or that there is little-to-no evidence of the hot spot's existence [1 - 24; 32]. Many myth proponents then falsely claim that the absence of the hot spot is evidence against CO2-induced global warming, as I discussed in "Myth: The Tropospheric Hot Spot is a Fingerprint of CO2-induced Warming". But the proponents' argument fails, since multiple lines of evidence show the hot spot exists. Let's go through some of these lines of evidence, which are as follows:

  1. Tropical precipitation and convection patterns [45; 97]
  2. Evidence from climate change in the distant past (paleoclimate evidence) [46; 118]
  3. Satellite-based temperature records [27; 33; 34; 37; 43; 214]
  4. Measurements from weather balloons (radiosondes) [55 - 59; 63; 64]
  5. Temperature re-analyses [77; 89 - 92]
{The last three sources have been cited by many myth proponents [1 - 9; 11; 12; 15 - 24; 54; 76, pages 4 - 7], so I do not seen how they could object to my citing those sources as well. Global positioning system radio occultation (GPS RO) [136; 137; 139 - 142; 156] offers a 6th means of detecting the hot spot. However, the GPS RO record is currently too short [138; 143] to be useful in detecting a multi-decadal hot spot, though GPS RO data reveals a hot spot in response to shorter-term warming [137, figures 1 and 3; 139, figure 4; 156, figure 4]. As the length of the GPS RO record increases with time, scientists may be able to use GPS RO to detect a longer-term hot spot. And despite its temporal limitations, GPS RO shows cooling of the upper atmosphere [136; 137; 139], which is a sign of the CO2-induced warming discussed in "Myth: The Sun Caused Recent Global Warming and the Tropical Stratosphere Warmed". This cooling appears in part b of figure 2 above and in figures 4, 5, 7, and 8 below.}

During the period of post-1970s global warming, tropical precipitation and convection patterns changed in a way indicative of moist-adiabatic lapse rate reduction, as shown in a 2010 paper [45]. A subsequent 2011 paper disputed this finding [121], though a 2017 paper [97] supported the results from the 2010 paper [45]. Furthermore, paleoclimate research indicates that the tropical lapse rate likely decreased during tropical warming in the distant past, while the lapse rate increased in response to tropical cooling [46; 118, figure 3]. So paleoclimate data and recent tropical precipitation/convection patterns provide two independent lines of evidence showing a hot spot during tropical warming (more recent land-based records also suggest that warming increased with increasing height in the recent past [124 - 129; 130 as discussed in 131], though these results are more tentative [124; 128; 129; 132; 133], especially in the tropics [124]).

Satellite-based measurements provide another independent line of evidence for the hot spot, since scientists can infer tropospheric temperature from satellite data. At least six satellite research groups generate satellite-based tropospheric temperature records, using different data analysis methods and different corrections for known artifacts/errors in the data; these corrections are known as homogenization and the artifacts are known as heterogeneities [27; 33 - 44; 152] (I discuss homogenization in more detail in section 3.1 of "John Christy, Climate Models, and Long-term Tropospheric Warming", with examples of scientists validating homogenization techniques [27; 37; 41]). The following six groups generate homogenized, satellite-based tropospheric temperature records:

  • a group at the University of Washington (UW) [27; 37 - 39]
  • a group at the National Oceanic and Atmospheric Administration Center for Satellite Applications and Research (NOAA/STAR or NOAA) [27; 33 - 36]
  • a group at Remote Sensing Systems (RSS) [27; 40; 41]
  • Vinnikov et al. at the University of Maryland (UMD) [43; 96]
  • a group at the University of Alabama in Huntsville (UAH) [32; 42]
  • Weng and Zou at the University of Maryland [44; 107]

Myth proponent John Christy cites the first five analyses [76, pages 4 - 7; 98, page 1694; 116], so it would be worthwhile to see if these analyses support the "no hot spot" myth. Christy has not cited the Weng and Zou analysis, to my knowledge, though Weng and Zou produce a temperature record showing the hot spot [44, figures 12 and 13]. However, other climate scientists do not often cite the Weng and Zou temperature record, and I have some doubts about the veracity of the Weng and Zou analysis. So let's aside their analysis. That leaves us with five satellite-based tropospheric temperature records cited by the myth defender John Christy [76, pages 4 - 7; 98, page 1694; 116].

4 out of 5 satellite analyses show the hot spot, with greater warming in the tropical mid- to upper troposphere than at Earth's surface. Specifically: the UW, NOAA/STAR, RSS, and UMD analyses show the hot spot [37, table 4 on page 2285; 43, figures 8 and 10; 214]. Figure 3 shows four of these five analyses, with two versions of the UW analysis:


Figure 3: HadCRUT4 tropical surface warming trends and tropical mid- to upper tropospheric warming trends (in K per decade) from 20°N to 20°S above the land, oceans, and both land and oceans from 1979 - 2012. Tropospheric warming trends are from UW, NOAA, RSS, and UAH satellite data analyses. UW(GCM) and UW use different methods for processing the satellite data. The value in parentheses is the ratio of the tropospheric warming to the surface warming for a given tropospheric temperature trend [37]. The RSS tropospheric warming trend is spuriously low due to an error in homogenization. The RSS team later corrected this error [40]. This resulted in a RSS tropical mid- to upper tropospheric warming trend that is between the NOAA trend and the UW trend [27, figure 4B on page 379].

Figure 3 shows amplification above the tropical oceans and the sum of land+oceans, but not above tropical land. This result is not surprising [66]. To see why, first note that as warm surface air rises to the troposphere, the warm air mixes by convection. This transfers heat from some of the warmer air that rose from the land to some of the nearby, less warm air that rose from the oceans. Thus convection makes the tropospheric warming rates above the tropical land more similar to the warming rate above the nearby tropical oceans [67, page 1; 75, page 4] (figure 8 below shows this more clearly, with tropospheric warming become more similar above different regions as one gets higher in the troposphere [89, figure 7]). And since land surface warming should be greater than ocean surface warming [26, from 31:47 to 33:33; 67 - 74], the similar tropospheric warming rates above tropical land and oceans would imply a lower amplification ratio above land than above oceans. One would also expect a greater amplification ratio above oceans than above land, since oceans provide a readier source of water that can evaporate, condense in the upper troposphere, and thus produce the tropospheric hot spot [67, page 7]. Thus one can explain why figure 3 shows greater tropospheric warming amplification above the tropical oceans vs. above the tropical land.

Figure 3 also indicates that UAH is the only analysis lacking a hot spot [32; 37, table 4 on page 2285]. One could predict this in advance since:
  1. UAH has a long history of under-estimating tropospheric warming due to UAH's faulty homogenization [26, from 36:31 to 37:10; 47; 49; 53, pages 5 and 6; 123; 152; 213; 215].
  2. Other scientists have critiqued UAH's homogenization methods [27; 31, pages 17 - 19; 33; 34; 37 - 40; 47 - 49; 123; 213; 215].
  3. UAH's satellite-based temperature analyses often diverge from analyses made by other research groups, in both the mid- to upper troposphere and other atmospheric layers [27; 31, pages 17 - 19; 33; 34; 37 - 40; 47- 49; 51; 123].
UAH is thus the odd analysis in the bunch, and likely the least credible analysis. So UAH's data analysis serves as (at best) a very weak argument for the "no hot spot" myth. As noted by the UW team members who made figure 3:

"Our amplification factor over land is reduced because of enhanced land surface warming relative to sea surface warming [...]. All of the MSU/AMSU [microwave sounding unit for determining atmospheric temperature] datasets demonstrate tropical tropospheric amplification, except UAH [emphasis added] [37, page 2285]."

Rather tellingly, UAH scientists John Christy and Roy Spencer [32; 42] have been some of the most vocal defenders of the "no hot spot" myth [8; 13 - 17; 32; 117; 158; 209]; Spencer and Christy may propagate the myth as a means of defending their flawed UAH analysis. In fact, myth proponents such as Judith Curry [8], Anthony Watts [54; 158], David Evans [148; 171], and The Daily Caller [19] use Christy and Spencer's claims to prop up the "no hot spot" myth [22; 159; 162]. One might wonder why these myth proponents cherry-pick the outlier UAH team, as opposed to the other satellite research groups mentioned...

Anyway, in addition to mid- to upper tropospheric temperature, UAH and RSS also produce satellite-based estimates of lower tropospheric temperature [41; 42; 214]. In contrast, NOAA/STAR and UW do not produce a lower tropospheric temperature analysis [27, page 383]. Consistent with UAH's status as the outlier group, UAH's analysis does not show amplified mid- to upper tropospheric warming relative to lower tropospheric warming, while RSS' analysis does show amplification [27, figure 9B on page 385]. This again illustrates that the flawed UAH analysis is the only up-to-date, satellite-based temperature record supporting the "no hot spot myth", in contrast to four other records debunking the myth [27, figure 9B on page 385; 37, table 4 on page 2285; 43].

Alongside satellites, scientists also use weather balloons (radiosondes) to measure tropospheric temperature. Radiosonde temperature records can be calculated from measurements of wind or from temperature sensor readings; this provides two methods for confirming temperature trends [56 - 59]. There are at least five homogenized radiosonde temperature records, which are as follows:

  • Radiosonde Observation Correction using Reanalysis (RAOBCORE) from a team at the University of Vienna [55 - 57]
  • Radiosonde Innovation Composite Homogenization from a team at the University of Vienna (RICH) [55 - 57]
  • Iterative Universal Kriging (IUKv2) from a team at the University of New South Wales [58; 59; 190]
  • Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) from a team at the NOAA [60]
  • Hadley Center Radiosonde Temperature (HadAT2) from a team at the United Kingdom Met Office [61; 62; 153]

4 out of 5 radiosonde analyses show the hot spot, with greater warming in the tropical upper troposphere than near Earth's surface [56, figure 9; 58, figures 1 and 2; 63, figure 2c; 64, figure 3 and table 1]. Upper tropospheric amplification occurs at an atmospheric pressure level of around 300hPa [58, figures 1 and 2; 63, figure 2c; 64, figure 3 and table 1], as illustrated in figure 4 using the IUKv2 record:


Figure 4: Tropical warming/cooling trend versus height for IUKv2 weather balloon measurements from 30°N to 30°S, unless otherwise noted. Pressure decreases from the Earth's surface (near the bottom of the y-axis) to the troposphere to the stratosphere (near the top of the y-axis) [58]. The tropical troposphere lies below 150hPa, while the tropical stratosphere is above 70hPa [65]. The green line extends to the beginning of satellite era of atmospheric temperature measurements (1979), while the purple line extends to before the satellite era. The inset legend for circles, diamonds, etc. indicates different temperature trends given different data analysis choices. The blue line roughly indicates the warming pattern expected for a moist adiabat [58].

Myth proponent John Christy cites all of the radiosonde analyses [16, page 23; 17, page 21; 76, pages 4 - 7; 98, page 1694; 116], though he recently stopped citing HadAT2 [16, page 23; 17, page 21; 76, pages 4 - 7; 116]. And of the 5 radiosonde analyses, HadAT2 is the outlier; HadAT2 shows the hot spot over some multi-decadal time periods [61, figures 10 and 11; 63, figure 2c; 64, figure 3 and table 1], but not over other multi-decadal periods [61, figures 10 and 11; 63, figure 2c] (see figure 7 below). This may explain why myth proponents such as David Evans [2; 6; 109; 171], the Global Warming Policy Foundation [161], and C3 headlines [23; 161] rely so heavily on HadAT analyses, to the exclusion of other analyses.

One should treat the HadAT2 result with skepticism, however, given some deficiencies in the homogenization for HadAT [153 - 155] and HadAT2 [63; 154]. The HadAT/HadAT2 team acknowledges these deficiencies [63; 153 - 155]. So the HadAT/HadAT2 research group strongly recommends that researchers not rely on just the HadAT2 data-set. Instead, the team recommends that researchers use other radiosonde data-sets, along with the RSS satellite analysis [62], to ensure that their result is robust. Since the hot spot appears in the other radiosonde analyses [56, figure 9; 58, figures 1 and 2; 63, figure 2c; 64, figure 3 and table 1] and the RSS analysis [27, figure 9B on page 385; 37, table 4 on page 2285], HadAT2's lack of a hot spot (over some time periods) is not a robust result. So HadAT2 and HadAT provide little support for the hot spot myth, contrary to the claims of David Evans [2; 6; 109; 171]. 

Evans also usually cherry-picks older analyses which contain more heterogeneities and which include data from just 1979 - 1999 [1; 2; 5 - 7; 109; 149; 171] (see figure 6 below). This allows him to evade the multi-decadal time periods in which HadAT2 shows the hot spot [61, figures 10 and 11; 63, figure 2c; 64, figure 3 and table 1] (ex: compare figures 6 and 7 below). He defends this practice in at least four ways. 

Evans' first defense states that the 1979 - 1999 HadAT2 analysis is "the only image as a function of height and latitude ever publicly released, apparently [171]." He offered this defense in November 2015 [171]. In 2012, Evans used a similar claim to make conspiracy-theory-laden insinuations about the United States Climate Change Science Program (CCSP):

"The weather balloon data showing the atmospheric warming pattern was finally released in 2006, in the US Climate Change Science Program [...] This is the only data there is. [By the way], isn’t this an obscure place to release such important and pivotal data – you don’t suppose they are trying to hide something, do you [203]?"

Yet before Evans made his November 2015 statement, scientists published a number of images showing warming at various atmospheric heights in the tropics [55, figure 11; 56, figure 9; 58, figures 1 and 2; 59, figure 3; 60, figures 4 and 6; 61, figures 10 and 11; 89, figure 7; 90, figure 1; 190, figures 3 and 6]. This includes 2005 RATPAC [60, figures 4 and 6] and HadAT2 [61, figures 10 and 11] images published before Evans' 2006 CCSP image [171]Figure 5 shows a 2005 RATPAC image, figure 6 depicts the 2006 image that Evans habitually presents, figure 7 shows a 2005 HadAT2 image, and figure 8 shows a 2015 IUKv2 image that Evans objects to [172]:

Figure 4

Figure 5: Warming/cooling trend versus height for RATPAC weather balloon measurements from 1979 - 2004 [60, figure 4]. Pressure decreases from the Earth's surface (near the bottom of the y-axis) to the troposphere to the stratosphere (near the top of the y-axis). The tropical troposphere lies below 150hPa, while the tropical stratosphere is above 70hPa [65].


Figure 6: Evans' image [1, page 4] taken from a 2006 report of the US Climate Change Science Program (CCSP). This image displays warming/cooling trend versus height for HadAT2 weather balloon measurements from 1979 - 1999 [191, figure 5.7 on page 116]Pressure decreases from the Earth's surface (near the bottom of the y-axis) to the troposphere to the stratosphere (near the top of the y-axis). The tropical troposphere lies below 150hPa, while the tropical stratosphere is above 70hPa [65]. Temperature trends in °C/decade are equivalent to trends in K/decade.

Figure 11.

Figure 7: Top two panelsWarming/cooling trend (in K/decade) versus height for HadAT2 weather balloon measurements. Crosses indicate trends statistically distinguishable from 0 [61, figure 11]. Pressure decreases from the Earth's surface (near the bottom of the y-axis) to the troposphere to the stratosphere (near the top of the y-axis). The tropical troposphere lies below 150hPa, while the tropical stratosphere is above 70hPa [65]. Bottom two panels: Estimate of some of the uncertainty (in K/decade) at atmospheric pressure levels corresponding to the top panel images [61, figure 11].


Figure 8: Warming/cooling trend (in K/decade) versus height for IUKv2 weather balloon measurements from 1960 - 2012. The temperature trends are not derived from wind measurements, and southern latitudes are marked as negative [58, figure 1]. Pressure decreases from the Earth's surface (near the bottom of the y-axis) to the troposphere to the stratosphere (near the top of the y-axis). The tropical troposphere lies below 150hPa, while the tropical stratosphere is above 70hPa [65].

The differences between the images largely stem from differences in the color-coding used for temperature trends, the homogenization method, and the time-frame selected. HadAT2 figure 7 shows greater upper tropospheric warming from 1958 - 2002 than from 1979 - 2002. This likely stems from 1980s in radiosonde equipment; this heterogeneity artificially increases 1980s radiosonde temperature measurements for the tropical upper troposphere [165; 166; 207]. 

While RATPAC figure 5 partially homogenizes this 1980s warm bias, HadAT2 figures 6 and 7 do not adequately address this 1980s heterogeneity. In contrast, IUKv2 figure 8 addresses the heterogeneity to the point that there is little difference between IUKv2's 1959 - 2012 and 1979 - 2012 trends (see figure 4). In performing this homogenization, the IUK team could learn from over a decade of scientific research validating different homogenization methods [ex: 155; 205; 207]. Much of this research came after figures 5, 6 and 7, and thus this research did not beneficially inform the homogenization used in figures 5, 6 and 7, in contrast to the homogenization for figure 8. These research-based homogenization improvements revealed a post-1979 hot spot in every radiosonde analysis (as of 2017), other than HadAT2 [63, figure 2c]. So there is good reason to trust the 2015 IUKv2 figure 8 more than the 2006 HadAT2 figure 6 that covers 1979 - 1999.

Unfortunately, Evans opts for figure 6, with its shorter time-frame of 1979 - 1999 and its color-coding that mutes the hot spot's increasing tropical tropospheric warming with increasing height. This is rather ironic, since Evans complains that IUK's color-coding [172; 190, figure 6] exaggerates the warming [1, page 11]. And since Evans is aware [1, page 11; 172] of some of the pre-November-2015 IUK images [58, figures 1 and 2; 59, figure 3; 190, figures 3 and 6], he is knowingly misleading his audience when he claims that figure 6 is "the only image as a function of height and latitude ever publicly released, apparently [171]." 

Thus, Evans' first defense collapses because he intentionally under-estimates how much information is available on the hot spot. He should also drop his insinuation that the United States CCSP was "trying to hide [203]" radiosonde information relevant to the hot spot. One could easily examine radiosonde analyses in the scientific literature before the CCSP published their 2006 report [61; 65] (ex: see figures 5 and 7 above); Evans probably missed these analyses because he does not know how to do a competent literature review.

In his second defense, Evans claims that since there has been no surface warming from 1999 (or 2001) to 2014, he does not need to include radiosonde data from after 1999 [1, page 5;171, comment #17.2; 172]. This defense fails for at least five reasons:

  • Earth's surface warmed since 1999 [94; 173 - 188], and radiosonde analyses show the tropics warmed since 1999 [63, figure 3] (for more on this, see my post "Myth: No Global Warming for Two Decades").
  • Evans cites model-based tropospheric projections from 1958 - 1999 [1, pages 3 - 7; 2; 5; 6; 109; 171; 172] (or from 1890 to 1999 [1, page 8; 5; 149]), and then compares those projections to HadAT2 analysis from 1979 - 1999 [1, pages 3 - 7; 2; 5; 6; 109; 149; 171; 172]. But that is a flawed comparison, since he needs to look at 1958 - 1999 radiosonde data in order to do a comparison to 1958 - 1999 projections. Alternatively, Evans could compare 1979 - 1999 observations with 1979 - 1999 projections, as his cited source [1, page 4] (the CCSP) did [191, figure 5.7 on page 116]. But doing that would greatly (and justifiably) reduce [191, figure 5.7 on page 116] Evans' depicted discrepancies between models and observations [1, pages 3 - 7; 2; 5; 6; 109; 149; 171; 172]. So Evans chooses not to perform this more accurate analysis, and instead opts for a flawed comparison [1, pages 3 - 7; 2; 5; 6; 109; 149; 171; 172] in order to misleading exaggerate the model-observations discrepancy.
  • Since scientists have at least 54 years worth of radiosonde data from 1959 to 2012 [58; 63] (ex: see figure 4), Evans' 21 year period uses less than half of the data. His smaller sample size makes his result less statistically robust and more prone to the effects of random noise; analogously, one is more likely to get a 2:1 heads-to-ratio, by chance, for 21 coin flips of a fair coin versus 54 flips of the same fair coin.
  • Evans' defense does not explain why one should exclude all the data from before 1979 and from after 1999. For example, his defense does not show any deep flaws present in the pre-1979 and post-1999 data, but not present in the 1979 - 1999 data. So even if the post-1999 data contains no warming, Evans has not shown that including the post-1999 data would do any harm. And since including the post-1999 would make Evans' analysis more statistically robust and less prone to random noise, Evans should include the post-1999 data.
  • Evans' favored HadAT2 analysis does not adequately address the instrument-change-based heterogeneity that caused 1980s tropical upper tropopsheric temperature measurements to be artificially high [165; 166; 207]. This heterogeneity biases Evans' 1979 - 1999 trend more than it would bias a longer trend such as 1959 - 1999 or 1959 - 2012. So Evans' shorter trend remains particularly susceptible to bias by heterogeneities.

Evans' third defense involves claiming that the amount of warming for the predicted hot spot is much greater than the radiosonde's limits of temperature detection [1, pages 1, 5, and 10; 5]. But Evans response lacks merit because the heterogeneities in question are not exclusively about the sensitivity of radiosondes in detecting slight temperature differences. Instead, the heterogeneities include changes in radiosonde design overtime, solar radiation directly heating inadequately shielded radiosondes such that the radiosondes are not just measuring air temperature, etc. [155; 165; 166; 167, pages 23 - 25; 169; 170; 204 - 208]. These heterogeneities are often greater than the error value given by Evans [1, pages 1, 5, and 10; 5]. Therefore scientists correct for these heterogeneities, with various degrees of success, resulting in the five homogenized radiosonde temperature records mentioned above [55; 57; 58; 60; 61; 168; 170; 204 - 208]. So Evans' third defense fails since he mischaracterizes the nature of the heterogeneities and he under-estimates the need for homogenization.

In his fourth defense, Evans insinuates that "raw" radiosonde analyses are preferable to homogenized radiosonde analyses [172; 189]. Evans' insinuation is off-base, since raw/un-homogenized analyses would contain large heterogeneities that would obscure climate-related trends in the data [155; 165; 166; 167, pages 23 - 25; 169; 170]. This is why informed climate scientists avoid using un-homogenized records or records with older, inferior homogenization [55; 57; 58; 60; 61; 63; 168; 170]. Scientists embarrass themselves if they do otherwise. For instance: for years, myth proponents Spencer and Christy under-estimated tropospheric warming because their UAH homogenization failed to adequately account for decaying satellite orbits [26, from 36:31 to 37:10; 47; 49; 53, pages 5 and 6; 123; 152]. Evidently Evans did not learn from Spencer and Christy's mistake.

And, ironically, Evans' data sources are homogenized. For example, he cites UAH's homogenized satellite-based analysis [148; 171; 203], he admits to using radiosonde analyses that are adjusted to account for ice sticking to the radiosondes [1, page 5], and he relies on (inadequately) homogenized HadAT or HadAT2 analyses [1; 2; 5 - 7; 109; 149; 171]. So Evans cites (inadequately) homogenized analyses when they suit his purposes [1; 2; 5 - 7; 109; 149; 171]; but he then insinuates that the analyses are "raw", when he needs to cast doubt on homogenized analyses that rebut his position [172; 189].

Thus Evans side-steps most of the homogenized records and instead opts for older analyses known to contain large heterogeneities [1; 2; 5 - 7; 109; 149; 171]. He does this despite the HadAT/HadAT2 team acknowledging the heterogeneities in their analyses [63; 153 - 155]. So not only is Evans cherry-picking by focusing on HadAT analyses, but he also cherry-picks by choosing analyses that are known to be worse and by choosing a time period that includes most of the data that shows the hot spot. Once one sets aside Evans' cherry-picking of particular analyses, the radiosonde analyses, on balance, provide evidence that the hot spot exists [56, figure 9; 58, figures 1 and 2; 63, figure 2c; 64, figure 3 and table 1].
Radiosonde data and satellite data, along with other data sources, are also incorporated into temperature re-analyses [77 - 94; 120]. These re-analyses help generate a broader picture of global temperature using a wealth of data [120]. A number of myth proponents (including Judith Curry [106], John Christy [76, pages 4 - 7; 116], Roger Pielke Sr. [95; 115], and Anthony Watts [12]) cite tropospheric warming trends from re-analyses, while David Evans links the hot spot to upper tropospheric humidity trends from a re-analysis [2; 171; 193]. So it would be worthwhile to see if the re-analyses support the "no hot spot" myth.

There are at least six re-analysis groupings, with each grouping having different re-analysis versions and updates [120; 134]. The homogenized groupings are as follows:

  • European Centre for Medium-Range Weather Forecasts Interim re-analysis (ERA-I) [77; 78]
  • Modern-Era Retrospective analysis for Research and Applications (MERRA) [79; 80]
  • National Centers for Environmental Prediction / Climate Forecast System Re-analysis (CFSR or NCEP/CFSR) [81; 82]
  • Japan Meteorological Agency Re-analysis (JRA) [83 - 85]
  • National Centers for Environmental Prediction / National Center for Atmospheric Research re-analysis (NCEP, NCEP-2, or NCEP/NCAR) [86 - 88]
  • 20th Century Re-analysis (20CR) [135]

(You can access re-analysis data using a free online tool [201; 202]. I do not present such an analysis here and instead rely on published, peer-reviewed analyses that show better familiarity with possible issues with the re-analyses than I would.)

20CR only incorporates surface data [120; 134, page 1423; 135, section 8], and thus may not be very useful for examining mid- to upper tropospheric warming trends [134, page 1423] (though a 20CR analysis is available [125, figure 6; 201]). So let's set aside 20CR. That leaves us with five re-analysis groupings.

4 out of 5 re-analyses show the hot spot, with greater warming in the tropical upper troposphere than near Earth's surface [77, figure 23 on page 348 and section 10.2.2 on page 351; 89, figure 7; 90, figure 1; 91, figure 4; 92, figure 4]. Upper tropospheric amplification occurs at an atmospheric pressure level of around 300hPa, as depicted in figure 9 for three of the re-analyses:

Figure 9: Tropospheric warming trend from 1979 - 2012 for the entire tropics (blue line; from 30°N to 30°S), tropical land (green line; from 30°N to 30°S), and the Sahara desert (red line). The Sahara's red line is not relevant for our purposes, since the Sahara is too arid to behave like a moist adiabat. The horizontal axis represents the warming trend in K per 34 years. The vertical axis represents altitude, with decreasing atmospheric pressure as altitude increases [89].

As illustrated in figure 9, NCEP-2 shows greater warming in the lower tropical troposphere than in the upper troposphere [89, figure 7; 91, figure 4]. This NCEP-2 trend should be taken with a grain of salt, since the NCEP re-analysis has a history of under-estimating tropospheric warming [90; 93; 99]. Other re-analyses, such as MERRA and ERA-I (see figure 9), tend to have more upper tropospheric warming than NCEP [89, figure 7; 91, figure 4] and tend to perform better than NCEP/NCEP-2 when it comes to representing atmospheric phenomena [90; 91; 99 - 105; 113; 122; 151; 194; 196 - 198], with a couple of short-term exceptions [199]. NCEP [90; 103; 105; 113; 122; 134, page 1422] and NCEP-2 [102; 105; 113; 122; 134, page 1422] also perform poorly in comparison to CFSR, with a few exceptions [195; 199]. CFSR shows the hot spot [90, figure 1; 91, figure 4], as do MERRA [89, figure 7; 90, figure 1; 91, figure 4] and ERA-I [77, figure 23 on page 348 and section 10.2.2 on page 351; 89, figure 7; 90, figure 1; 91, figure 4]. So the better-performing re-analyses show the hot spot.

Given the aforementioned deficiencies in NCEP-2, one should consider relying on another re-analysis instead of NCEP-2 [114; 119]. This may explain why myth defender John Christy does not cite NCEP-2, but does cite ERA-I, MERRA-2, and JRA-55 [76, pages 4 - 7; 116]. Yet Anthony Watts mistakenly relies on the NCEP-2 re-analysis as evidence against the hot spot's existence, to the exclusion of other re-analyses and without Watts noting NCEP-2's deficiencies [12]. Thus Watts unjustifiably cherry-picks the NCEP-2 re-analysis. A similar point applies to Evans' use of NCEP trends [2; 171; 193].

In contrast to NCEP-2 [157], ERA-I shows greater warming near the tropical surface than in the lower troposphere [89, figure 7; 91, figure 4], as shown in figure 9. This is because ERA-I under-estimates the rate of lower tropospheric warming, as acknowledged by the ERA-I research team [77; 94]. ERA-I is particularly damaging to the position of myth proponent Judith Curry, since Curry defends the "no hot spot" myth [8] and promotes the myth on her blog Climate Etc. [8; 147], even though Curry lauds [106] the ERA-I analysis that shows the hot spot [77]. Yet Curry does not acknowledge the hot spot in ERA-I, as far as I know. So Curry may not realize that her own source refutes her position.


Myth defender John Christy has an even worse conundrum since he defends the "no hot spot" myth [16; 17; 76, page 10], even though he cites re-analyses, satellites analyses, and radiosonde analyses [16; 17; 76, pages 4 - 7; 98, page 1694; 116] that show the hot spot [27, figure 9B on page 385; 37, table 4 on page 2285; 56, figure 9; 58, figures 1 and 2; 63, figure 2c; 77; 89]. The hot spot even appears in a figure made by Christy [116]. So Christy is aware that the hot spot exists, but he claims that it does not exist (I discuss this more in "Myth: John Christy Thinks There is No Evidence of the Hot Spot"). Thus one of the most cited proponents of the "no hot spot" myth [8; 13 - 17; 19; 22; 54] is well-aware that the myth is nonsense. Amazing.




3. Posts Providing Further Information and Analysis





4. References


  1. David Evans': "The Missing Hotspot"
  2. http://joannenova.com.au/2012/05/models-get-the-core-assumptions-wrong-the-hot-spot-is-missing/
  3. https://chriscolose.wordpress.com/2008/12/20/skepticsdenialists-part-2-hotspots-and-repetition/
  4. https://bravenewclimate.com/2008/08/10/dr-david-evans-born-again-alarmist/
  5. http://naturalclimatechange.us/disproofs-of-agw-hypothesis/the-missing-hotspot-2/
  6. "The missing greenhouse signature"
  7. Stefan Molyneux's video: "Climate Change in 12 Minutes - The Skeptic's Case"
  8. https://judithcurry.com/2015/03/04/differential-temperature-trends-at-the-surface-and-in-the-lower-atmosphere/
  9. "Taking greenhouse warming seriously"
  10. https://www.skepticalscience.com/tropospheric-hot-spot-advanced.htm
  11. "Greenhouse warming? What Greenhouse warming?"
  12. https://wattsupwiththat.com/2014/08/04/what-stratospheric-hotspot/
  13. "McNider and Christy: Why Kerry is flat wrong on climate change"
  14. https://ourchangingclimate.wordpress.com/2014/02/22/john-christy-richard-mcnider-roy-spencer-flat-earth-hot-spot-figure-baseline/
  15. "What do observational datasets say about modeled tropospheric temperature trends since 1979?"
  16. "On the Existence of a “Tropical Hot Spot" & The Validity of EPA’s CO2 Endangerment Finding"
  17. "On the Existence of a “Tropical Hot Spot” & The Validity of EPA’s CO2 Endangerment Finding, Abridged Research Report, Second Edition"
  18. https://climateaudit.org/2008/04/26/tropical-troposphere/
  19. "The ‘fingerprint’ of global warming doesn’t exist in the real world, study finds"
  20. https://notalotofpeopleknowthat.wordpress.com/2015/09/13/another-attempt-to-find-the-tropical-hotspot/
  21. http://hockeyschtick.blogspot.com/2010/07/why-agw-hot-spot-wont-happen.html
  22. https://wattsupwiththat.com/2017/04/02/why-john-christies-missing-hotspot-matters/
  23. http://www.c3headlines.com/2013/02/ipccs-global-warming-hypothesis-fails-ultimate-test-no-tropical-hotspot-after-17-years-of-immense-co.html
  24. http://www.c3headlines.com/2014/01/ipcc-fail-tropical-hotspot-refuted-by-latest-empirical-evidence-those-stubborn-facts.html
  25. "Response of the large-scale structure of the atmosphere to global warming"
  26. Ray Pierrehumbert's 2012 video: "Tyndall Lecture: GC43I. Successful Predictions - 2012 AGU Fall Meeting"
  27. "Comparing tropospheric warming in climate models and satellite data"
  28. "Physical mechanisms of tropical climate feedbacks investigated using temperature and moisture trends"
  29. "Regional variation of the tropical water vapor and lapse rate feedbacks"
  30. "Elevation-dependent warming in mountain regions of the world"
  31. "Extended Summary of the Climate Dialogue on the (missing) tropical hot spot"
  32. http://www.drroyspencer.com/2015/05/new-satellite-upper-troposphere-product-still-no-tropical-hotspot/
  33. "Contribution of stratospheric cooling to satellite-inferred tropospheric temperature trends"
  34. "Satellite-derived vertical dependence of tropical tropospheric temperature trends"
  35. "Error structure and atmospheric temperature trends in observations from the Microwave Sounding Unit"
  36. "Stability of the MSU-derived atmospheric temperature trend"
  37. "Removing diurnal cycle contamination in satellite-derived tropospheric temperatures: understanding tropical tropospheric trend discrepancies"
  38. "A bias in the midtropospheric channel warm target factor on the NOAA-9 Microwave Sounding Unit"
  39. "Reply to “Comments on 'A bias in the midtropospheric channel warm target factor on the NOAA-9 Microwave Sounding Unit'"
  40. "Sensitivity of satellite-derived tropospheric temperature trends to the diurnal cycle adjustment"
  41. "A satellite-derived lower tropospheric atmospheric temperature dataset using an optimized adjustment for diurnal effects"
  42. "UAH version 6 global satellite temperature products: Methodology and results"
  43. "Temperature trends at the surface and in the troposphere"
  44. "30-year atmospheric temperature record derived by one-dimensional variational data assimilation of MSU/AMSU-A observations"
  45. "Changes in the sea surface temperature threshold for tropical convection"
  46. "The tropical lapse rate steepened during the Last Glacial Maximum"
  47. "Tropospheric temperature trends: history of an ongoing controversy"
  48. "A comparative analysis of data derived from orbiting MSU/AMSU instruments"
  49. "The reproducibility of observational estimates of surface and atmospheric temperature change"
  50. "Water vapor and the dynamics of climate changes"
  51. "Stratospheric temperature changes during the satellite era"
  52. "The physical basis for increases in precipitation extremes in simulations of 21st-century climate change"
  53. "Review of the consensus and asymmetric quality of research on human-induced climate change"
  54. https://wattsupwiththat.com/2015/05/14/claim-climate-scientists-find-elusive-tropospheric-hot-spot-over-the-southern-ocean/
  55. "Homogenization of the global radiosonde temperature dataset through combined comparison with reanalysis background series and neighboring stations"
  56. "New estimates of tropical mean temperature trend profiles from zonal mean historical radiosonde and pilot balloon wind shear observations"
  57. "Radiosonde bias adjustments- ERA-CLIM2 project; Bias adjustments for radiosonde temperature, wind and humidity from existing reanalysis feedback; Deliverable 4.1 of EU 7FP project ERA-CLIM2 (Grant No. 607029)"
  58. "Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data (IUKv2)"
  59. "Warming maximum in the tropical upper troposphere deduced from thermal winds"
  60. "Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC): A new data set of large-area anomaly time series"
  61. "Revisiting radiosonde upper-air temperatures from 1958 to 2002"
  62. http://www.metoffice.gov.uk/hadobs/hadat/index.html
  63. "Internal variability in simulated and observed tropical tropospheric temperature trends"
  64. "Reexamining the warming in the tropical upper troposphere: Models versus radiosonde observations"
  65. "Tropical Tropopause Layer" [doi:10.1029/2008RG000267]
  66. http://www.realclimate.org/index.php/archives/2009/11/muddying-the-peer-reviewed-literature/?wpmp_tp=1
  67. "Assessing atmospheric temperature data sets for climate studies"
  68. "Transient responses of a coupled ocean–atmosphere model to gradual changes of atmospheric CO2. Part I. Annual mean response"
  69. "An analogue model to derive additional climate change scenarios from existing GCM simulations"
  70. "Land/sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations"
  71. "Mechanisms for the land/sea warming contrast exhibited by simulations of climate change"
  72. "Communicating global climate change using simple indices: an update"
  73. "Control of land-ocean temperature contrast by ocean heat uptake"
  74. "Land–ocean warming contrast over a wide range of climates: Convective quasi-equilibrium theory and idealized simulations"
  75. "Response of the large-scale structure of the atmosphere to global warming"
  76. "U.S. House Committee on Science, Space & Technology, 29 Mar 2017, Testimony of John R. Christy"
  77. "Estimating low-frequency variability and trends in atmospheric temperature using ERA-Interim"
  78. "The ERA-Interim reanalysis: configuration and performance of the data assimilation system"
  79. "MERRA: NASA's modern-era retrospective analysis for research and applications"
  80. "MERRA-2: Initial evaluation of the climate"
  81. "The NCEP climate forecast system reanalysis"
  82. "The NCEP climate forecast system version 2"
  83. "The JRA-25 reanalysis"
  84. "The JRA-55 reanalysis: Representation of atmospheric circulation and climate variability"
  85. "The JRA-55 reanalysis: General specifications and basic characteristics"
  86. "NCEP–DOE AMIP-II Reanalysis (R-2)"
  87. "The NCEP–NCAR 50-Year Reanalysis: Monthly means CD-ROM and documentation"
  88. "The NCEP/NCAR 40-Year Reanalysis project"
  89. "Detection and analysis of an amplified warming of the Sahara Desert"
  90. "Impacts of atmospheric temperature trends on tropical cyclone activity"
  91. "Influence of tropical tropopause layer cooling on Atlantic hurricane activity"
  92. "Westward shift of western North Pacific tropical cyclogenesis"
  93. "Response to Comment on "Contributions of Anthropogenic and Natural Forcing to Recent Tropopause Height Changes""
  94. "A reassessment of temperature variations and trends from global reanalyses and monthly surface climatological datasets"
  95. https://pielkeclimatesci.files.wordpress.com/2009/10/r-278b.pdf
  96. "Global warming trend of mean tropospheric temperature observed by satellites"
  97. "Observed warming trend in sea surface temperature at tropical cyclone genesis"
  98. "A comparison of tropical temperature trends with model predictions"
  99. "Validating atmospheric reanalysis data using tropical cyclones as thermometers"
  100. "Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite"
  101. "On the factors affecting trends and variability in tropical cyclone potential intensity"
  102. "Evaluation and intercomparison of cloud fraction and radiative fluxes in recent reanalyses over the Arctic using BSRN surface observations"
  103. "Evaluation of multireanalysis products with in situ observations over the Tibetan Plateau"
  104. "TropFlux: Air-Sea Fluxes for the Global Tropical Oceans – Description and evaluation against observations"
  105. "Representation of tropical subseasonal variability of precipitation in global reanalyses"
  106. https://judithcurry.com/2016/08/01/assessing-atmospheric-temperature-data-sets-for-climate-studies/
  107. "Uncertainty of AMSU-A derived temperature trends in relationship with clouds and precipitation over ocean"
  108. https://www.thegwpf.com/new-paper-models-vs-observations-in-the-tropical-troposphere/
  109. https://climatism.wordpress.com/2014/01/28/the-missing-hot-spot/
  110. http://climatefeedback.org/scientists-reactions-us-house-science-committee-hearing-climate-science/
  111. "Full committee hearing- Climate ccience: Assumptions, policy implications, and the scientific method"
  112. "Climate change 2001: The scientific basis; Chapter 12: Detection of climate change and attribution of causes"
  113. "Evaluation of atmospheric precipitable water from reanalysis products using homogenized radiosonde observations over China"
  114. "Overview of current atmospheric reanalyses"
  115. "Comment on "Contributions of Anthropogenic and Natural Forcing to Recent Tropopause Height Changes""
  116. "At what cost? Examining the social cost of carbon"
  117. http://www.drroyspencer.com/2013/06/epic-fail-73-climate-models-vs-observations-for-tropical-tropospheric-temperature/
  118. "Modern and glacial tropical snowlines controlled by sea surface temperature and atmospheric mixing"
  119. https://climatedataguide.ucar.edu/climate-data/ncep-reanalysis-r2 ("Expert guidance" section)
  120. https://climatedataguide.ucar.edu/climate-data/atmospheric-reanalysis-overview-comparison-tables
  121. "The threshold sea surface temperature condition for tropical cyclogenesis"
  122. "A comparison of atmospheric temperature over China between radiosonde observations and multiple reanalysis datasets"
  123. "The effect of diurnal correction on satellite-derived lower tropospheric temperature"
  124. "Elevation-dependent warming in mountain regions of the world"
  125. "Are the central Andes mountains a warming hot spot?"
  126. "Impact of the global warming hiatus on Andean temperature"
  127. "Evidence of high-elevation amplification versus Arctic amplification"
  128. "Regional air pollution brightening reverses the greenhouse gases induced warming-elevation relationship"
  129. "Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols"
  130. "Recent changes in freezing level heights in the Tropics with implications for the deglacierization of high mountain regions"
  131. "Savor the Cryosphere"
  132. "Negative elevation-dependent warming trend in the Eastern Alps"
  133. "Artificial amplification of warming trends across the mountains of the western United States"
  134. "Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems"
  135. "The Twentieth Century Reanalysis Project"
  136. "Atmospheric temperature change detection with GPS radio occultation 1995 to 2008"
  137. "Atmospheric climate change detection by radio occultation data using a fingerprinting method"
  138. EGU 2017 General Assembly 2017 conference abstract: "Vertically resolved trends from GPS Radio Occultation and their uncertainties"
  139. "ENSO-related moisture and temperature anomalies over South America derived from GPS radio occultation profiles"
  140. "Variability of zonal mean tropical temperatures derived from a decade of GPS radio occultation data"
  141. "Evaluating CMIP5 models using GPS radio occultation COSMIC temperature in UTLS region during 2006–2013: twenty-first century projection and trends"
  142. "Application of GPS radio occultation to the assessment of temperature profile retrievals from microwave and infrared sounders"
  143. EGU 2017 General Assembly 2017 conference abstract: "Differences in trends and anomalies of upper-air observations from GPS RO, radiosondes, and AMSU"
  144. "Tropical temperature altitude amplification in the hiatus period (1998-2012)"
  145. "Temperature altitude amplification as a footprint of a possible anthropogenic impact on the climate of Australia"
  146. "Comparison of free atmosphere temperature series from radiosonde and satellite data"
  147. https://judithcurry.com/2011/10/29/tropospheric-and-surface-temperatures/
  148. http://joannenova.com.au/2015/05/new-satellite-analysis-fails-to-find-the-hot-spot-agrees-with-millions-of-weather-balloons/
  149. http://joannenova.com.au/2012/04/so-is-the-hotspot-a-fingerprint-or-signature-is-it-unique/
  150. "Polluted discourse: Communication and myths in a climate of denial"
  151. "Trends in tropospheric humidity from reanalysis systems"
  152. "Correcting temperature data sets"
  153. "Assessing bias and uncertainty in the HadAT-adjusted radiosonde climate record"
  154. "A quantification of uncertainties in historical tropical tropospheric temperature trends from radiosondes"
  155. "Critically reassessing tropospheric temperature trends from radiosondes using realistic validation experiments"
  156. "Tropical temperature variability and Kelvin-wave activity in the UTLS from GPS RO measurements"
  157. "An observational analysis: tropical relative to Arctic in?uence on midlatitude weather in the era of Arc-tic ampli?cation"
  158. https://wattsupwiththat.com/2010/09/14/spencer-on-water-vapor-feedback/
  159. http://www.globalwarming.org/2013/06/10/climate-models-epic-failure-or-spot-on-consistent-with-observed-warming/
  160. https://www.friendsofscience.org/index.php?id=710
  161. https://www.thegwpf.com/ipcc-fail-tropical-hotspot-17-years-immense-co2-emissions/
  162. https://www.heartland.org/news-opinion/news/models-predicted-too-much-warming-new-data-show
  163. http://www.popularsocialscience.com/2012/11/14/climate-change-what-are-the-facts-what-are-the-myths/
  164. https://quadrant.org.au/magazine/2015/06/climate-wars-done-science/
  165. "Biases in stratospheric and tropospheric temperature trends derived from historical radiosonde data"
  166. "Radiosonde daytime biases and late-20th century warming"
  167. "Classic examples of inhomogeneities in climate datasets"
  168. "A "Global Radiosonde and tracked-balloon Archive on Sixteen Pressure levels" (GRASP) going back to 1905 – Part 2: homogeneity adjustments for pilot balloon and radiosonde wind data"
  169. "Observation errors in early historical upper-air observations"
  170. "Comparison of radiosonde and GCM vertical temperature trend profiles: Effects of dataset choice and data homogenization"
  171. http://joannenova.com.au/2015/11/new-science-17-solving-the-mystery-of-the-missing-hotspot/
  172. http://joannenova.com.au/2015/05/desperation-who-needs-thermometers-sherwood-finds-missing-hot-spot-with-homogenized-wind-data/
  173. "Estimating changes in global temperature since the pre-industrial period"
  174. "Global temperature evolution: recent trends and some pitfalls"
  175. "Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends"
  176. Hansen et al.: "Global temperature in 2015"
  177. "Assessing recent warming using instrumentally homogeneous sea surface temperature records"
  178. "Unabated planetary warming and its ocean structure since 2006"
  179. "Tracking ocean heat uptake during the surface warming hiatus"
  180. "Assessing the impact of satellite-based observations in sea surface temperature trends"
  181. "A review of global ocean temperature observations: Implications for ocean heat content estimates and climate change"
  182. "Possible artifacts of data biases in the recent global surface warming hiatus"
  183. "Land surface temperature over global deserts: Means, variability, and trends"
  184. "On the definition and identifiability of the alleged “hiatus” in global warming"
  185. "Global land-surface air temperature change based on the new CMA GLSAT dataset"
  186. "Improved estimates of ocean heat content from 1960 to 2015"
  187. "Industrial-era global ocean heat uptake doubles in recent decades"
  188. "In situ–based reanalysis of the global ocean temperature and salinity with ISAS: Variability of the heat content and steric height"
  189. http://joannenova.com.au/2015/06/sherwoods-devout-unscientific-faith-in-climate-change-and-the-hot-spot/
  190. "Robust tropospheric warming revealed by iteratively homogenized radiosonde data"
  191. "Temperature trends in the lower atmosphere: Steps for understanding and reconciling differences"
  192. "Global warming due to increasing absorbed solar radiation"
  193. http://joannenova.com.au/2010/11/dessler-2010-how-to-call-vast-amounts-of-data-spurious/
  194. "A comparison of tropopause heights over China between radiosonde and three reanalysis datasets for the period 1979–2012"
  195. "Assessment of the quality of NCEP-2 and CFSR reanalysis daily temperature in China based on long-range correlation"
  196. "Trends in the frequency of high relative humidity over China: 1979–2012"
  197. "Consistency of temperature and precipitation extremes across various global gridded in situ and reanalysis datasets"
  198. "Comparison of NCEP-NCAR and ERA-Interim over Australia"
  199. "Evaluation of NCEP–CFSR, NCEP–NCAR, ERA-Interim, and ERA-40 Reanalysis Datasets against Independent Sounding Observations over the Tibetan Plateau"
  200. http://icecap.us/images/uploads/ImportanceoftheHotSpot_093016_.pdf
  201. "Web-based Reanalysis Intercomparison Tool: Monthly/seasonal time series" https://www.esrl.noaa.gov/psd/cgi-bin/data/testdap/timeseries.pl
  202. "Web-Based Reanalysis Intercomparison Tools (WRIT) for analysis and comparison of reanalyses and other datasets"
  203. http://joannenova.com.au/2012/01/dr-david-evans-the-skeptics-case/
  204. "Temporal homogenization of monthly radiosonde temperature data. Part I: Methodology"
  205. "Temporal homogenization of monthly radiosonde temperature data. Part II: Trends, sensitivities, and MSU comparison"
  206. "Homogenization of radiosonde temperature time series using innovation statistics"
  207. "Toward elimination of the warm bias in historic radiosonde temperature records—Some new results from a comprehensive intercomparison of upper-air data"
  208. "Using first differences to reduce inhomogeneity in radiosonde temperature datasets"
  209. "An alternative explanation for differential temperature trends at the surface and in the lower troposphere"
  210. https://wattsupwiththat.com/2016/09/22/study-tropical-hotspot-fingerprint-of-global-warming-doesnt-exist-in-the-real-world-data/
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