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Scafetta, Nicola, and Richard C. Willson 2014 Addendum: Figure 16

1. Irishmen Michael Connolly, the father, and Ronan Connolly, the son (photo above), hold doctorate degrees, Ronan in Chemistry and Michael in an unknown field of study. Together, they have formed a research organization with the acronym “CERES” {Center for Environmental Research and Earth Sciences} (logo above). The founders, Michael and Ronan, are the only members of CERES. Their research in atmospheric physics and climate change is carried out in this context as CERES researchers. Their research is published in an online journal called {Open Peer Review Journal} of which they are the founders and only authors. These works are also posted on Researchgate.net where full text pdf files are available for download.
2. This post is a review of their claim that their analysis shows that the GHG effect of CO2, the foundation of the catastrophic AGW fear-based activism against fossil fuels, is not the primary driver of climate change as assumed in AGW theory and as required to serve as the rationale for the proposed climate action of changing the energy infrastructure from fossil fuels to renewable energy.
3. They found that in the study period 1881 to 2013, when the Hoyt & Schatten TSI {total solar irradiance} data are used in conjunction with CO2 forcing, TSI can explain the current warming with or without the CO2 effect with almost equal precision. Very high correlations of ρ≥0.7 are found for TSI alone against temperature. The authors of this post tested the validity of the correlation with detrended correlation analysis and found detrended correlations ≥0.45 with strong statistical significance. More importantly, the addition of CO2 forcing did not make a significant improvement in the correlation.
4. The results imply that long term temperature trends in surface temperature data are driven almost entirely by variability in total solar irradiance (TSI) when the Hoyt&Schatten proxy data are used. The dramatic difference between the Kopp&Lean and the Hoyt&Schatten TSI data are depicted in the chart above (Figure 16 in Scafetta and Willson 2014). The  greater variability of Hoyt&Schatten is able to explain the current warming event with greater precision than the Kopp&Lean TSI data and without the use of CO2 GHG forcing. The important contribution of this work to the AGW discussion is that it may encourage a greater attention to solar variability in the understanding of climate change that now relies on the Lacis principle that climate change can and must be understood solely in terms of fossil fuel emissions and CO2 forcing.  Related posts on this site are : [LINK] [LINK] [LINK] [LINK][LINK] [LINK] 
5. However, it is important in this context to pay attention to the issue of uncertainty in proxy paleo data in general and in reconstructions of TSI in particular. The large differences seen in the chart above between the Hoyt&Schatten and Kopp&Lean TSI proxy data are not anomalous but rather what one would normally expect in paleo proxy reconstructions. Therefore, that a single proxy reconstruction exists that supports the Connolly hypothesis requires confirmation with different proxy data sources. This aspect of proxies is a generic problem with paleo data that has been described most clearly by Professor Carl Wunsch [LINK].
6. He writes that “Thousands of papers do document regional changes in proxy concentrations, but almost everything is subject to debate including, particularly, the age models, geographical integrity of regional data, and the meaning of the apparent signals that are often transformed in complicated ways on their way through the atmosphere and the ocean to the sediments. From one point of view, scientific communities without adequate data have a distinct advantage because they can construct interesting and exciting stories and rationalizations with little or no risk of observational refutation. Colorful, sometimes charismatic, characters come to dominate the field, constructing their interpretations of a few intriguing, but indefinite observations that appeal to their followers, and which eventually emerge as “textbook truths.” Therefore, although high correlations between TSI proxies and temperature have been shown with the Hoyt&Schatten proxy data, this relationship will gain greater credibility if it can be shown to exist in other proxies or in direct observations.
7. Yet another consideration is that the study examines five distinct regions with  mean temperature data for China, USA, the Arctic, the Northern Hemisphere, and sea surface temperature. AGW is a theory about global mean temperature and it would seem important that a test of that hypothesis should include a test of global mean temperature. Thus, in the selection of proxies to use and in the selection of regions to study, the methodology leaves open a possibility of data selection bias that would imply a circular reasoning issue in the form of the so called Texas Sharpshooter fallacy in the sense that data selection may have played a role in the success of the empirical test in proving what the authors had apparently set out to prove.
8. Another area of research by the Connolly family is the urban heat island effect. In that work they find that much of the warming being attributed to CO2 driven AGW is actually an “urbanization effect” caused by a rising urban heat island effect in the instrumental temperature series driven by growth in urban areas and thereby a growing heat island effect. The data presented are global average GHCN temperatures that show higher warming rates in urban areas than in rural areas. As a quick check of this result, one can compare the warming rates in Northern Hemisphere land areas in the reconstruction from the instrumental record (as in CRUTEM) with UAH satellite data for the same regional description. Since the Northern Hemisphere land areas have undergone significant urbanization over the period 1979-2018 one would expect to see a rising difference between the warming rates in these two temperature series. However that test showed a difference in warming rates of 0.0145C/yr in the full span of the data, 0.0137C/yr in the first half, 0.0172C/yr in the mid half, and the lowest rate of 0.0105C/yr in the second half of the time series. This result is inconsistent with the proposed urbanization bias that would be expected to create increasing differences between instrumental warming rate (CRUTEM) and the satellite data that is free of the urban heat island effect ((UAH). These results are displayed graphically below.
9. With respect to sea level rise, they write that “The main estimates of long-term sea level changes are based on data from various tidal gauges located across the globe. These estimates apparently suggest a sea level rise of about 1 to 3mm a year since records began. This works out at about 10-30cm (4-12 inch) per century, or about a 1 foot rise every 100-300 years. Importantly, the rate still seems to be about the same as it was at the end of the 19th century, even though carbon dioxide emissions are much higher now than they were during the 19th century. The last sentence is an interesting observation supported by a statistical analysis presented for the relationship between emissions and sea level rise at this site [LINK]  where we show that the proposition by climate science that sea level rise can be moderated by cutting emissions is not supported by the data.
10. In “The Physics of the Earth’s Atmosphere” section, the Connolly family writes that they looked at data from weather balloons to study the phenomenon of temperature change with height and found that it is explained by changes in water content and the existence of a previously unreported phase change. They state that this finding shows that the temperatures at each height are completely independent of the greenhouse gas concentrations. This part of their work is somewhat mysterious. The mystery deepens when they explain the chemistry of these changes in terms of “multimerization” of oxygen and/or nitrogen” and a mechanism called “pervection” explaining that  energy is transmitted throughout the atmosphere faster than the speed of light by pervective power and that this mechanism is not considered in the greenhouse effect theory, or in the current climate models and that explains why the greenhouse effect theory doesn’t work. A detailed bibliography of their work and related works is presented below. 

TEST OF THE URBANIZATION BIAS 

BIBLIOGRAPHY

1. Hoyt, Douglas V., and Kenneth H. Schatten. “Group sunspot numbers: A new solar activity reconstruction.” Solar physics 179.1 (1998): 189-219. In this paper, we construct a time series known as the Group Sunspot Number. The Group Sunspot Number is designed to be more internally self-consistent (i.e., less dependent upon seeing the tiniest spots) and less noisy than the Wolf Sunspot Number. It uses the number of sunspot groups observed, rather than groups and individual sunspots. Daily, monthly, and yearly means are derived from 1610 to the present. The Group Sunspot Numbers use 65941 observations from 117 observers active before 1874 that were not used by Wolf in constructing his time series. Hence, we have calculated daily values of solar activity on 111358 days for 1610–1995, compared to 66168 days for the Wolf Sunspot Numbers. The Group Sunspot Numbers also have estimates of their random and systematic errors tabulated. The generation and preliminary analysis of the Group Sunspot Numbers allow us to make several conclusions: (1) Solar activity before 1882 is lower than generally assumed and consequently solar activity in the last few decades is higher than it has been for several centuries. (2) There was a solar activity peak in 1801 and not 1805 so there is no long anomalous cycle of 17 years as reported in the Wolf Sunspot Numbers. The longest cycle now lasts no more than 15 years. (3) The Wolf Sunspot Numbers have many inhomogeneities in them arising from observer noise and this noise affects the daily, monthly, and yearly means. The Group Sunspot Numbers also have observer noise, but it is considerably less than the noise in the Wolf Sunspot Numbers. The Group Sunspot Number is designed to be similar to the Wolf Sunspot Number, but, even if both indices had perfect inputs, some differences are expected, primarily in the daily values.
2. Schatten, Kenneth, and Douglas Hoyt. Solar cycle 23 forecast update Geophysical research letters 25.5 (1998): 599-601.  Solar activity, although virtually impossible to forecast a month in advance, has succumbed to scientific methods on long time scales, much as climate or seasonal weather predictions are simpler than weekly weather forecasting. Moderately accurate solar activity forecasts on decadal time scales now seem possible. The methods that work fall into a class of prediction techniques called “precursor methods.” We utilize solar, interplanetary field, and geomagnetic precursors to update our cycle 23 prediction to provide a mean smoothed sunspot number of 153 ± 30 and mean smoothed Fl0.7 cm Radio flux of 200 ± 30. This is comparable to, but somewhat smaller than, the NOAA SEC panel findings that the next solar cycle would peak at a sunspot number near 160 ± 30. This paper also provides some discussion relating solar and interplanetary field components to serve as a bridge in interplanetary space, helping to forge Sun‐Earth connections.
3. Fröhlich, C., and J. Lean. “Solar irradiance variability and climate.” Astronomische Nachrichten 323.3‐4 (2002): 203-212.  Since November 1978 a complete set of total solar irradiance (TSI) measurements from space is available, yielding a time series of more than 23 years. From measurements made by different space‐based radiometers (HF on NIMBUS 7, ACRIM I on SMM, ACRIM II on UARS and VIRGO on SOHO) a composite record of TSI is compiled with an overall precision of order 0.05 Wm^–2 and a secular trend uncertainty of ±3 ppm/year. This time series is compared with an empirical model of irradiance variability based on sunspot darkening and brightening due to faculae and network. From this comparison the model is calibrated and used to estimate possible changes of TSI in the past, using historical proxies of solar activity. For this purpose, stellar observations provide information about the possible range of solar variability over the last millennium when changes of Earth’s climate are well documented. Together, the paleo solar and climate data enable a discussion of the extent of global climate change that can be explained by a variable Sun.
4. Haigh, Joanna D. “The effects of solar variability on the Earth’s climate.” Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 361.1802 (2002): 95-111.  The absolute value of total solar irradiance is not known to better than ca.0.3% but measurements from satellite instruments over the past two solar cycles have shown that it varies by ca.0.1% on this time-scale. Over longer periods its value has been reconstructed using proxy measures of solar activity, and these suggest that during the Maunder minimum in solar activity of the late 17th century it was 3−4 W m⁻² lower than at present. Observational data suggest that the Sun has influenced temperatures on decadal, centennial and millennial time-scales, but radiative forcing considerations and the results of energy-balance models and general circulation models suggest that the warming during the latter part of the 20th century cannot be ascribed entirely to solar effects. However, chemical and dynamical processes in the middle atmosphere may act to amplify the solar impact. An analysis of zonal mean temperature data shows that solar effects may be differentiated from those associated with other factors such as volcanic eruptions and the El Niño Southern Oscillation.
5. Mendoza, Blanca. “Total solar irradiance and climate.” Advances in Space Research 35.5 (2005): 882-890. The solar radiation is the fundamental source of energy that drives the Earth’s climate and sustains life. The variability of this output certainly affects our planet. In the last two decades an enormous advance in the understanding of the variability of the solar irradiance has been achieved. Space-based measurements indicate that the total solar irradiance changes at various time scales, from minutes to the solar cycle. Climate models show that total solar irradiance variations can account for a considerable part of the temperature variation of the Earth’s atmosphere in the pre-industrial era. During the 20th century its relative influence on the temperature changes has descended considerably. This means that sources other than solar activity as well as internal and man-made causes are contributing to the Earth’s temperature variability, particularly the former in the 20th century. Some very challenging questions concerning total solar irradiance variations and climate have been raised: are total solar irradiance variations from cycle to cycle well represented by sunspot and facular changes? Does total solar irradiance variations always parallel the solar activity cycle? Is there a long-term variation of the total solar irradiance, and closely related to this, is the total solar irradiance output of the quiet sun constant? If there is not a long-term trend of total solar irradiance variations, then we need amplifying mechanisms of total solar irradiance to account for the good correlations found between total solar irradiance and climate. The latter because the observed total solar irradiance changes are inconsequential when introduced in present climate models.
6. de Jager, Cornelis, and Ilya Usoskin. “On possible drivers of Sun-induced climate changes.” Journal of Atmospheric and Solar-Terrestrial Physics 68.18 (2006): 2053-2060.  We tested the validity of two current hypotheses on the dependence of climate change on solar activity. One of them states that variations in the tropospheric temperature are caused directly by changes of the solar radiance (total or spectral). The other suggests that cosmic ray (CR) fluctuations, caused by the solar/heliospheric modulation, affect the climate via cloud formation. Confronting these hypotheses with seven different sets of the global/hemispheric temperature reconstructions for the last 400 years, we found that the former mechanism is in general more prominent than the latter. Therefore, we can conclude that in so far as the Sun–climate connection is concerned tropospheric temperatures are more likely affected by variations in the UV radiation flux rather than by those in the CR flux.
7. Roy, Indrani, and Joanna D. Haigh. “Solar cycle signals in sea level pressure and sea surface temperature.” Atmospheric Chemistry and Physics 10.6 (2010): 3147-3153.  We identify solar cycle signals in 155 years of global sea level pressure (SLP) and sea surface temperature (SST) data using a multiple linear regression approach. In SLP we find in the North Pacific a statistically significant weakening of the Aleutian Low and a northward shift of the Hawaiian High in response to higher solar activity, confirming the results of previous authors using different techniques. We also find a weak but broad reduction in pressure across the equatorial Pacific. In SST we identify a weak El Niño-like pattern in the tropics for the 155 year period, unlike the strong La Niña-like signal found recently by some other authors. We show that the latter have been influenced by the technique of compositing data from peak years of the sunspot cycle because these years have often coincided with the negative phase of the ENSO cycle. Furthermore, the date of peak annual sunspot number (SSN) generally falls a year or more in advance of the broader maximum of the 11-year solar cycle so that analyses which incorporate data from all years represent more coherently the difference between periods of high and low solar activity on these timescales. We also find that studies of the solar signal in SST over the second half of the 20th century may alias as ENSO signal if this is not properly taken into account.
8. Shapiro, A. I., et al. “A new approach to the long-term reconstruction of the solar irradiance leads to large historical solar forcing.” Astronomy & Astrophysics 529 (2011): A67. The variable Sun is the most likely candidate for the natural forcing of past climate changes on time scales of 50 to 1000 years. Evidence for this understanding is that the terrestrial climate correlates positively with the solar activity. During the past 10 000 years, the Sun has experienced the substantial variations in activity and there have been numerous attempts to reconstruct solar irradiance. While there is general agreement on how solar forcing varied during the last several hundred years – all reconstructions are proportional to the solar activity – there is scientific controversy on the magnitude of solar forcing.We present a reconstruction of the total and spectral solar irradiance covering 130 nm–10 μm from 1610 to the present with an annual resolution and for the Holocene with a 22-year resolution. We assume that the minimum state of the quiet Sun in time corresponds to the observed quietest area on the present Sun. Then we use available long-term proxies of the solar activity, which are ¹⁰Be isotope concentrations in ice cores and 22-year smoothed neutron monitor data, to interpolate between the present quiet Sun and the minimum state of the quiet Sun. This determines the long-term trend in the solar variability, which is then superposed with the 11-year activity cycle calculated from the sunspot number. The time-dependent solar spectral irradiance from about 7000 BC to the present is then derived using a state-of-the-art radiation code. We derive a total and spectral solar irradiance that was substantially lower during the Maunder minimum than the one observed today. The difference is remarkably larger than other estimations published in the recent literature. The magnitude of the solar UV variability, which indirectly affects the climate, is also found to exceed previous estimates.We discuss in detail the assumptions that lead us to this conclusion.
9. Scafetta, Nicola, and Richard C. Willson. “ACRIM total solar irradiance satellite composite validation versus TSI proxy models.” Astrophysics and Space Science 350.2 (2014): 421-442.  The satellite total solar irradiance (TSI) database provides a valuable record for investigating models of solar variation used to interpret climate changes. The 35-year ACRIM total solar irradiance (TSI) satellite composite time series has been revised using algorithm updates based on 13 years of accumulated mission experience and corrections to ACRIMSAT/ACRIM3 results for scattering and diffraction derived from recent testing at the Laboratory for Atmospheric and Space Physics/Total solar irradiance Radiometer Facility (LASP/TRF). The net correction lowers the ACRIM3 scale by ∼3000 ppm, in closer agreement with the scale of SORCE/TIM results (average total solar irradiance ≈1361.5 W/m²). Differences between the ACRIM and PMOD TSI composites are investigated, particularly the decadal trending during solar cycles 21–22 and the Nimbus7/ERB and ERBS/ERBE results available to bridge the ACRIM Gap (1989–1992), are tested against a set of solar proxy models. Our findings confirm the following ACRIM TSI composite features: (1) The validity of the TSI peak in the originally published ERB results in early 1979 during solar cycle 21; (2) The correctness of originally published ACRIM1 results during the SMM spin mode (1981–1984); (3) The upward trend of originally published ERB results during the ACRIM Gap; (4) The occurrence of a significant upward TSI trend between the minima of solar cycles 21 and 22 and (5) a decreasing trend during solar cycles 22–23. The same analytical approach does not support some important features of the PMOD TSI composite: (1) The downward corrections applied to the originally published ERB and ACRIM1 results during solar cycle 21; (2) The step function sensitivity change in ERB results at the end-of-September 1989; (3) The downward trend of ERBE results during the ACRIM Gap and (4) the use of ERBE results to bridge the ACRIM Gap. Our analysis provides a first order validation of the ACRIM TSI composite approach and its 0.037 %/decade upward trend during solar cycles 21–22. The implications of increasing TSI during the global warming of the last two decades of the 20th century are that solar forcing of climate change may be a significantly larger factor than represented in the CMIP5 general circulation climate models.
10. The importance of the TSI satellite debate for solar physics and climate change, Scafetta, Nicola, and Richard C. Willson. “ACRIM total solar irradiance satellite composite validation versus TSI proxy models 2014.” Unpublished Addendum: The Sun is a variable star (Brekke 2012). However, the multi-decadal trending of solar activity is currently poorly modeled and numerous alternative proxy reconstructions have been proposed. Understanding the correct amplitude and dynamics of solar variability is important both for solar physics and climate change science. The multi-decadal trending difference between the ACRIM (Willson and Mordvinov 2003) and PMOD TSI composites (Fröhlich and Lean 1998; Fröhlich 2006) shown in Fig. 2 is important for understanding the multi-decadal variation of solar dynamics and therefore for discriminating among solar models used also to interpret climate changes. Because the ACRIM TSI composite shows an evident upward pattern from 1980 to 2000 while PMOD shows a slight downward trend during the same period, the former would suggest a larger TSI low-frequency variability than the latter and different TSI multidecadal variation mechanisms. The origin of a slowly varying irradiance component may derive from changes in the solar faculae and/or in the background solar radiation from solar quiet regions. These mechanisms are currently poorly understood and modeled. However, if TSI increased from 1980 to 2000, total solar and heliospheric activity could have increased as well contributing significantly to the global warming observed from 1980 to 2000 (Scafetta and West 2005, 2007; Scafetta 2009, 2011, 2012a, 2013b,c). The Coupled Model Intercomparison Project Phase 5 (CMIP5) used to study climate change (Scafetta 2013c) currently recommends the use of a solar forcing function deduced from the TSI proxy model proposed by Lean and collaborators (Wang et al. 2005; Kopp et al. 2007). Lean’s recent models show a small secular trend (about 1 W/m21 W/m2) from the Maunder minimum (1645–1715) to the present with a peak about 1960 and it is quasi stationary since. However, alternative TSI proxy reconstructions have been proposed and some of them present much larger secular variability and different decadal patterns. Figure 16A compares two alternative multisecular TSI proxy model: Lean’s TSI model and the TSI reconstruction proposed by Hoyt and Schatten (1993) rescaled at the ACRIM TSI scale. Figure 16A also shows in blue the annual mean ACRIM TSI satellite composite since 1981 (Willson and Mordvinov 2003). Total solar irradiance (TSI) reconstruction by Hoyt and Schatten (1993) (red) rescaled on the ACRIM record (Willson and Mordvinov 2003) (since 1981) (blue) vs. the updated Lean model (Wang et al. 2005; Kopp et al. 2007) (green). [B] Comparison between the Central England Temperature (CET) record (black) Parker et al. (1992) and the TSI model by Hoyt and Schatten plus the ACRIM TSI record. The latter is linearly rescaled on the CET record using the formula T=0.1915∗TSI−251.05 that rescales the TSI record into a temperature record. Good correlation is observed at least since 1772. (Note CET is less certain before 1772). The Hoyt and Schatten (1993) reconstruction has been made by rescaling it on the ACRIM record from 1980 to 1992 using the formula HS93∗1361.267/1371.844, where 1371.844 is the 1981–1992 average of Hoyt and Schatten (1993)’s proxy reconstruction and 1361.267 is the 1981–1992 average of the ACRIM TSI composite. The value in 1980 in [B] was estimated as the average between the ACRIM mean and the rescaled Hoyt and Schatten (1993) reconstruction

    Hoyt and Schatten (1993, Fig. 10) showed that their multi-proxy TSI model is highly correlated with an annual mean northern hemisphere temperature variation reconstruction since 1700. This correlation is confirmed (Fig. 16B) by comparing a Hoyt+ACRIM TSI combination model against the Central England Temperature (CET) record since 1700 (Parker et al. 1992). The comparison between the two records is made using a simple linear regression of the Hoyt+ACRIM TSI record against the CET record. The linear regression algorithm simplistically transforms the TSI curve into a temperature signal and only provides an approximate estimate of the climatic effect of the solar variability as described by the Hoyt+ACRIM TSI record. The divergence observed during the last decades is likely due to (1) an additional anthropogenic warming component, which was quite significant during the last decades, and (2) to the necessity of using a more advanced model to obtain the temperature signature of the solar variability. This problem is better addressed in the literature interpreting global climate change (e.g.: Scafetta and West 2005, 2007; Scafetta 2009, 2010, 2011, 2012a, 2013b,c). A good correlation between the same TSI proxy model and numerous climatic records for the 20th century including temperature records of the Arctic and of China, the sunshine duration record of Japan and the Equator-to-Pole (Arctic) temperature gradient record was demonstrated (Soon 2005; Soon et al. 2011; Soon and Legates 2013). Key features are a warming from 1910s to 1940s, a cooling from the 1940s to 1970s, a warming from the 1970s to 2000s and a steady-to-cooling temperature since ∼2000, all of which correlate much better with the Hoyt+ACRIM TSI composite than with Lean’s proxy model. The observed pattern is compatible with a quasi 60-year oscillation commonly observed in climate and solar records throughout the Holocene (e.g.: Chambers et al. 2012, Klyashtorin et al. 2009, Knudsen et al. 2011, Mazzarella and Scafetta 2012, Ogurtsov et al. 2002, Qian and Lu 2010, Scafetta 2010, 2012a,b, 2013a,b,c, Scafetta and Willson 2013a). Recently, Liu et al. (2013, see also the supplementary information) used the ECHO-G model and showed that to reproduce the ∼0.7 ^∘C global cooling observed from the Medieval Warm Period (MWP: 900–1300) to the Little Ice Age (LIA: 1400–1800) according to recent paleoclimatic temperature reconstructions (e.g.: Ljungqvist 2010; Mann et al. 2008; Moberg et al. 2005), a TSI model with a secular variability ∼3.5 times larger than that shown by Lean’s TSI model would be required. The IPCC (2007, Sect. 6.6.3.4 and its Fig. 6.14) reports that to obtain a cooling of about 0.7 ^∘C from the MWP to the LIA Maunder Minimum a corresponding TSI downward trend of −0.25 % is required. Lean’s TSI model shows a trend of only −0.08 % over this period (Wang et al. 2005). The same climate models rescaled using Lean’s TSI model predict a MWP-to-LIA Maunder Minimum cooling of only 0.25 ^∘C that is compatible only with the controversial hockey stick temperature reconstruction of Mann et al. (1999). It should be noted that the updated proxy temperature reconstructions by Mann et al. (2008) show a significantly warmer MWP than the Mann’s 1999 temperature reconstruction used by the IPCC in 2001. See the extended discussion in Scafetta (2013a). Thus, recent paleoclimatic temperature reconstructions imply that the natural climate variability varied significantly more than predicted by the CMIP5 general circulation models, which use Lean’s low-variability TSI model (e.g.: Scafetta 2013a,b,c). The most likely explanation is that solar variations (TSI and other astronomical effects) are a more significant contributor to climate change than currently understood (see also: Liu et al. 2013; Scafetta 2013a). A stronger solar effect on the climate would also imply a significantly larger solar contribution to the 20th century global warming, as demonstrated in some works (Scafetta 2009, 2013a,b,c). Indeed, despite the IPCC (2007) claims the Sun has an almost negligible effect on climate, numerous authors found significant correlations between specific solar models and temperature records suggesting a strong climate sensitivity to solar variations (e.g.: Bond et al. 2001; Hoyt and Schatten 1993; Loehle and Scafetta 2011; Mazzarella and Scafetta 2012; Ogurtsov et al. 2002; Scafetta 2009, 2010, 2012b, 2013b; Schulz and Paul 2002; Soon 2005; Soon and Legates 2013; Steinhilber et al. 2012; Svensmark 2007; Thejll and Lassen 2000). Shapiro et al. (2011) and Judge et al. (2012) proposed TSI models based a comparison between solar irradiance reconstructions and sun-like-stellar data that show a TSI secular variability at least 3-to-6 times greater than Lean’s TSI proxy. These new TSI models look similar to those proposed by Hoyt and Schatten (1993). The Shapiro model also predicts a small TSI increase between the solar minima of 1986 and 1996, that is more consistent with the ACRIM 1980–2000 upward TSI pattern and contradicts PMOD. This pattern derives from the fact that the cosmic ray flux record, which is inversely proportional to solar magnetic activity, presents a slight decrease from about 1970 to 2000 (Scafetta 2013c, Fig. 20). It was recently speculated that long term changes in the solar interior due to planetary gravitational perturbations may produce gradual multi-decadal and secular irradiance changes (e.g.: Abreu et al. 2012; Charbonneau 2013; Scafetta 2012b,c; Scafetta and Willson 2013a,b,c). The planetary models proposed by Scafetta (2012b) and Scafetta and Willson (2013a) shows a quasi 60-year modulation of solar activity since 1850 with peaks in the 1880s, 1940s and 2000s. Thus, it shows good agreement with the ACRIM composite’s upward trending from about 1980 to 2000. Scafetta (2014) addresses the scientific background of the astronomical theory of solar and climate oscillations. In conclusion, despite recent scientific climate change literature (e.g.: IPCC 2007) has favored the PMOD interpretation of the TSI experimental records we have provided experimental and theoretical reasons supporting the claim that the ACRIM TSI composite is a most likely interpretation of the current satellite TSI database. The dynamical pattern revealed by the ACRIM TSI composite appears to better agree with a number of new evidences that are emerging and, therefore, solving the TSI satellite controversies could be quite important for better understanding solar physics and climate change alike.

11. Connolly, Michael, and Ronan Connolly. “The physics of the Earth’s atmosphere I. Phase change associated with tropopause.” Open Peer Rev. J. 19 (2014).  Atmospheric profiles in North America during the period 2010-2011, obtained from archived weather balloon radiosonde measurements, were analysed in terms of changes of molar density (D) with pressure (P). This revealed a pronounced phase change at the tropopause. The air above the troposphere (i.e., in the tropopause/stratosphere) adopted a “heavy phase”, distinct from the conventional “light phase” found in the troposphere. This heavy phase was also found in the lower troposphere for cold, Arctic winter radiosondes. Reasonable fits for the complete barometric temperature profiles of all of the considered radiosondes
    could be obtained by just accounting for these phase changes and for changes in humidity. This suggests that the well-known changes in temperature lapse rates associated with the tropopause/stratosphere regions are related to the phase change, and not “ozone heating”, which had been the previous explanation.
    Possible correlations between solar ultraviolet variability and climate change have previously been explained in terms of changes in ozone heating influencing stratospheric weather. These explanations may have to be revisited, but the correlations might still be valid, e.g., if it transpires that solar variability influences the formation of the heavy phase, or if the changes in incoming ultraviolet radiation are redistributed throughout the atmosphere, after absorption in the stratosphere. The fits for the barometric temperature profiles did not require any consideration of the composition of atmospheric trace gases, such as carbon dioxide, ozone or methane. This contradicts the predictions of current atmospheric models, which assume the temperature profiles are strongly influenced by greenhouse gas concentrations. This suggests that the greenhouse effect plays a much smaller role in barometric temperature profiles than previously assumed. [FULL TEXT PDF]
12. Connolly, Michael, and Ronan Connolly. “The physics of the Earth’s atmosphere II. Multimerization of atmospheric gases above the troposphere.” Open Peer Rev. J. 22 (2014).  In a companion paper, a pronounced phase transition was found to occur between the troposphere and the tropopause/stratosphere regions. In this paper, it is argued that this phase change is due to the formation of multimers of the main atmospheric gases (N2 and O2) in the tropopause/stratosphere. This has several implications for our current understanding of the physics of the Earth’s atmosphere: 1. It offers a more satisfying explanation as to why stratospheric temperatures increase with altitude, than the conventional “ozone heating” explanation. 2. It provides an additional mechanism for the emission of infra-red and microwave radiation from the tropopause/stratosphere. 3. It suggests a faster mechanism for the formation of ozone in the ozone layer than the conventional Chapman mechanism. 4. It provides new insights into a number of weather phenomena, e.g., cyclonic/anti-cyclonic behaviour, tropical cyclones, polar vortices and the jet streams. [FULL TEXT PDF]
13. Connolly, Ronan, and Michael Connolly. “Global temperature changes of the last millennium.” Open Peer Review Journal 16 (2014).  A review of the various global (or hemispheric) millennial temperature reconstructions was carried out.
    Unlike previous reviews, technical analyses presented via internet blogs were considered in addition to the conventional peer-reviewed literature. There was a remarkable consistency between all of the reconstructions in identifying three climatically distinct periods. These consisted of two relatively warm periods – the “Medieval Warm Period” (c. 800-1200 AD) and the “Current Warm Period” (c. 1900 AD on) – and a relatively cool period – the “Little Ice Age” (c. 1500-1850 AD). Disagreement seems to centre over how the two warm periods compare to each other, and exactly how cold, and continuous the cool period was. Unfortunately, many of the assumptions behind the reconstructions have still not been adequately justified. Also, there are substantial inconsistencies between the different proxy data sources, and between proxy-based and thermometer-based estimates. Until these issues have been satisfactorily resolved, all of the current millennial temperature reconstructions should be treated with considerable Caution. [FULL TEXT PDF]
14. Connolly, Ronan, and Michael Connolly. “Urbanization bias I. Is it a negligible problem for global temperature estimates?.” Open Peer Rev. J. 28 (2014).  Several studies have claimed that the warming bias introduced to global temperature estimates by urbanization bias is negligible. On the basis of this claim, none of the groups calculating global temperature estimates (except for NASA Goddard Institute for Space Studies) explicitly correct for urbanization bias. However, in this article, by re-evaluating these studies individually, it was found that there was no justification for this. There is considerable evidence that there has been global warming since the late 1970s. The urbanization bias problem is sometimes incorrectly framed as being a question of whether there has recently been global warming or not. However, the recent warming appears to have followed a period of global cooling from an earlier warm period which ended in the 1940s. So, resolving the urbanization bias problem is necessary to address issues such as how the recent warm period compared to the early 20th century warm period. If the earlier warm period was comparable to the recent warm period, then claims that recent global temperature trends are unprecedented or unusual will need to be re-evaluated. [FULL TEXT PDF]
15. Connolly, Ronan, and Michael Connolly. “Urbanization bias II. An assessment of the NASA GISS urbanization adjustment method.” Open Peer Rev. J. 31 (2014).  NASA GISS are currently the only group calculating global temperature estimates that explicitly adjust their weather station data for urbanization biases. In this study, their urbanization adjustment procedure was considered. A number of serious problems were found with their urbanization adjustments: 1.) The vast majority of their adjustments involved correcting for “urban cooling”, whereas urbanization bias is predominantly a warming bias. 2.) The net effect of their adjustments on their global temperature estimates was unrealistically low, particularly for recent decades, when urbanization bias is expected to have increased. 3.) When a sample of highly urbanized stations was tested, the adjustments successfully removed warming bias for the 1895-1980 period, but left the 1980s-2000s period effectively unadjusted. In an attempt to explain these unexpected problems, a critical assessment of their adjustment procedure
    was carried out. Several serious flaws in their procedure were identified, and recommendations to overcome these flaws were given. Overall, NASA GISS’ urbanization adjustments were found to be seriously flawed, unreliable and inadequate. Until their adjustment approach is substantially improved, their global temperature estimates should be treated with considerable caution. [FULL TEXT PDF]
16. Connolly, Ronan, and Michael Connolly. “Urbanization bias III. Estimating the extent of bias in the Historical Climatology Network datasets.” Open Peer Rev. J. 34 (2014).  The extent to which two widely-used monthly temperature datasets are affected by urbanization bias was considered. These were the Global Historical Climatology Network (GHCN) and the United States Historical Climatology Network (USHCN). These datasets are currently the main data sources used to construct the various weather station-based global temperature trend estimates. Although the global network nominally contains temperature records for a large number of rural stations, most of these records are quite short, or are missing large periods of data. Only eight of the records with data for at least 95 of the last 100 years are for completely rural stations. In contrast, the U.S. network is a relatively rural dataset, and less than 10% of the stations are highly urbanized. However, urbanization bias is still a significant problem, which seems to have introduced an artificial warming trend into current estimates of U.S. temperature trends. The homogenization adjustments developed by the National Climatic Data Center to reduce the extent
    of non-climatic biases in the networks were found to be inadequate, inappropriate and problematic for urbanization bias. As a result, the current estimates of the amount of “global warming” since the Industrial Revolution have probably been substantially overestimated. [FULL TEXT PDF]
17. Soon, Willie, Ronan Connolly, and Michael Connolly. “Re-evaluating the role of solar variability on Northern Hemisphere temperature trends since the 19th century.” Earth-Science Reviews 150 (2015): 409-452. Debate over what influence (if any) solar variability has had on surface air temperature trends since the 19th century has been controversial. In this paper, we consider two factors which may have contributed to this controversy: Factor#1: Several different solar variability datasets exist. While each of these datasets is constructed on plausible grounds, they often imply contradictory estimates for the trends in solar activity since the 19th century. Factor#2: Although attempts have been made to account for non-climatic biases in previous estimates of surface air temperature trends, recent research by two of the authors has shown that current estimates are likely still affected by non-climatic biases, particularly urbanization bias.With these points in mind, we first review the debate over solar variability. We summarise the points of general agreement between most groups and the aspects which still remain controversial. We discuss possible future research which may help resolve the controversy of these aspects. Then, in order to account for the problem of urbanization bias, we compile a new estimate of Northern Hemisphere surface air temperature trends since 1881, using records from predominantly rural stations in the monthly Global Historical Climatology Network dataset. Like previous weather station-based estimates, our new estimate suggests that surface air temperatures warmed during the 1880s–1940s and 1980s–2000s. However, this new estimate suggests these two warming periods were separated by a pronounced cooling period during the 1950s–1970s and that the relative warmth of the mid-20th century warm period was comparable to the recent warm period. We then compare our weather station-based temperature trend estimate to several other independent estimates. This new record is found to be consistent with estimates of Northern Hemisphere Sea Surface Temperature (SST) trends, as well as temperature proxy-based estimates derived from glacier length records and from tree ring widths. However, the multi-model means of the recent Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model hindcasts were unable to adequately reproduce the new estimate — although the modelling of certain volcanic eruptions did seem to be reasonably well reproduced. Finally, we compare our new composite to one of the solar variability datasets not considered by the CMIP5 climate models, i.e., Scafetta and Willson, 2014’s update to the Hoyt and Schatten, 1993 dataset. A strong correlation is found between these two datasets, implying that solar variability has been the dominant influence on Northern Hemisphere temperature trends since at least 1881. We discuss the significance of this apparent correlation, and its implications for previous studies which have instead suggested that increasing atmospheric carbon dioxide has been the dominant influence. [FULL TEXT PDF] .
18. Soon, Willie Wei-Hock, et al. “Comparing the current and early 20th century warm periods in China.” Earth-Science Reviews 185 (2018): 80-101.  Most estimates of Chinese regional Surface Air Temperatures since the late-19th century have identified two relatively warm periods – 1920s–40s and 1990s–present. However, there is considerable debate over how the two periods compare to each other. Some argue the current warm period is much warmer than the earlier warm period. Others argue the earlier warm period was comparable to the present. In this collaborative paper, including authors from both camps, the reasons for this ongoing debate are discussed. Several different estimates of Chinese temperature trends, both new and previously published, are considered. A study of the effects of urbanization bias on Chinese temperature trends was carried out using the new updated version of the Global Historical Climatology Network (GHCN) – version 4 (currently in beta production). It is shown that there are relatively few rural stations with long records, but urbanization bias artificially makes the early warm period seem colder and the recent warm period seem warmer. However, current homogenization approaches (which attempt to reduce non-climatic biases) also tend to have similar effects, making it unclear whether reducing or increasing the relative warmth of each period is most appropriate. A sample of 17 Chinese temperature proxy series (12 regional and 5 national) is compared and contrasted specifically for the period since the 19th century. Most proxy series imply a warm early-20th century period and a warm recent period, but the relative warmth of these two periods differs between proxies. Also, with some proxies, one or other of the warm periods is absent. [FULL TEXT PDF] .

URBAN HEAT ISLAND BIBLIOGRAPHY

1. Parker, David E. “Urban heat island effects on estimates of observed climate change.” Wiley Interdisciplinary Reviews: Climate Change 1.1 (2010): 123-133.  Urban heat islands are a result of the physical properties of buildings and other structures, and the emission of heat by human activities. They are most pronounced on clear, calm nights; their strength depends also on the background geography and climate, and there are often cool islands in parks and less‐developed areas. Some old city centers no longer show warming trends relative to rural neighbourhoods, because urban development has stabilised. This article reviews the effects that urban heat islands may have on estimates of global near‐surface temperature trends. These effects have been reduced by avoiding or adjusting urban temperature measurements. Comparisons of windy weather with calm‐weather air temperature trends for a worldwide set of observing sites suggest that global near‐surface temperature trends have not been greatly affected by urban warming trends; this is supported by comparisons with marine surface temperatures. The use of dynamical‐model‐based reanalyses to estimate urban influences has been hindered by the heterogeneity of the data input to the reanalyses and by biases in the models. However, improvements in reanalyses are increasing their utility for assessing the surface air temperature record. High‐resolution climate models and data on changing land use offer potential for future assessment of worldwide urban warming influences. The latest assessments of the likely magnitude of the residual urban trend in available global near‐surface temperature records are summarized, along with the uncertainties of these residual trends. Copyright © 2010 John Wiley & Sons, Ltd.

EXCERPTS FROM [GLOBALWARMINGSOLVED DOT COM] 

1. 11/13/2013: WHAT DOES THE IPCC SAY?: The UN’s Intergovernmental Panel on Climate Change (or IPCC) have published a series of reports, which are widely assumed to represent the scientific consensus on man-made global warming.Since these reports are quite long and tedious, many of the people who have looked at the reports have mostly just considered the “Summary for Policymakers” (“SPM”) sections of the reports. These sections are assumed to accurately summarise the main findings of the entire reports. In their most recent Summary for Policymakers (September 2013), the IPCC claimed that it is more than 95% likely, i.e., “extremely likely” that “… human influence has been the dominant cause of the observed warming since the mid-20th century”. They also claimed that this global warming will become much greater during the 21st century if nothing is done to slow down CO2 emissions. Because thousands of top climate scientists are involved in the writing of the IPCC reports, these Summary for Policymakers claims are widely assumed to represent the views of all the top climate scientists. However, in this essay, we show that this assumption is a mistake. Those views are certainly expressed by many of the IPCC scientists who are heavily involved in the report writing. But, most IPCC scientists are never even asked for their views on those claims. Indeed, several IPCC scientists are prominent man-made global warming critics who openly disagree with a number of the claims made in the Summary for Policymakers. The problem is that the IPCC adopt a hierarchical system which gives a relatively small number of scientists the power to dismiss the views of other IPCC contributors, if they disagree with them. So, even though thousands of scientists have some involvement in the writing of the IPCC reports, the final views expressed by the reports are dominated by the views of a few dozen scientists. [FULL TEXT PDF]
2. 11/13/2013: IS THE ARCTIC MELTING?: Since satellite records began, there seems to have been a general decline in average Arctic sea ice extent. Interestingly, this hasn’t occured for Antarctic sea ice. The satellite records only began in October 1978, however. This coincided with the start of a recent warming trend in the Arctic. Before that, from the 1950s-1970s, Arctic temperatures were cooling. So, it is quite likely that in the decades immediately before the satellite records began, average Arctic sea ice extent was actually increasing, but we just weren’t monitoring it. It seems that the Arctic sea ice extent naturally goes through periods of expansion, followed by periods of contraction. In case you’re unsure about which is which, the Arctic is the polar region in the north (the one with polar bears, etc.) and the Antarctic is the polar region in the south (the one with penguins, etc.)In this essay, we look at what we know about Arctic sea ice extent.
3. 11/19/2013: THE PHYSICS OF THE EARTH’S ATMOSPHERE: In this essay, we will briefly summarise the analysis in our three “Physics of the Earth’s atmosphere” papers, which we have submitted for peer review at the Open Peer Review Journal.In Paper 1, we developed new analytical techniques for studying weather balloon data. Using these techniques, we found that we were able to accurately describe the changes in temperature with height by just accounting for changes in water content and the existence of a previously unreported phase change. This shows that the temperatures at each height are completely independent of the greenhouse gas concentrations. This disproves the greenhouse effect theory. It also disproves the man-made global warming theory, which is based on the greenhouse effect theory. In Paper 2, we suggest that the phase change we identified in Paper 1 involves the “multimerization” of oxygen and/or nitrogen in the air above the “troposphere” (the lower part of the atmosphere). This has important implications for a number of important phenomena related to the atmosphere, e.g., ozone formation, the locations of the jet streams, and how tropical cyclones form. In Paper 3, we identify a mechanism by which energy is transmitted throughout the atmosphere, which we call “pervection”. This mechanism is not considered in the greenhouse effect theory, or in the current climate models. We carried out laboratory experiments to measure the rates of pervection in air, and find that it is much faster than radiation, convection and conduction. This explains why the greenhouse effect theory doesn’t work. [FULL TEXT PDF] .
4. 11/21/2013: What is happening to sea levels? Hollywood and the media have helped created a popular perception that humans are causing dramatic sea level rises by man-made global warming. This perception comes from an exaggeration of more modest, though still dramatic, computer model predictions of 1-2 metre rises by the end of the 21st century. However, the actual experimental data shows, at most, a slow and modest increase in sea levels, which seems completely unrelated to CO2 concentrations. The main estimates of long-term sea level changes are based on data from various tidal gauges located across the globe. These estimates apparently suggest a sea level rise of about 1 to 3mm a year since records began. This works out at about 10-30cm (4-12 inch) per century, or about a 1 foot rise every 100-300 years, hardly the scary rates implied by science fiction films like The Day After Tomorrow (2004) or Waterworld (1995). Importantly, the rate still seems to be about the same as it was at the end of the 19th century, even though carbon dioxide emissions are much higher now than they were during the 19th century. Moreover, there are a number of problems in using the tidal gauge data which have not been resolved yet. So, despite claims to the contrary, it is still unclear if there has actually been any long term trend! In this essay, we will summarise what is actually known about current sea level trends.  [FULL TEXT PDF]
5.  11/27/2013: Is there a scientific consensus on global warming? By promoting the idea that climate scientists are all in agreement on man-made global warming theory, it might create the impression that there is scientific consensus. But, it hides the wide range of different views that are actually held by the scientific community. Many people (including many scientists) believe that there is a strong scientific consensus that increases in atmospheric CO2 concentrations cause dangerous man-made global warming, and that if we don’t urgently reduce our carbon footprint, it will get much worse. But, while it is true that a substantial fraction of climate scientists hold this view, there is actually a wide range of opinions on man-made global warming in the scientific community. For instance, some scientists believe there has been man-made global warming, but that the media descriptions are seriously exaggerated, and that it isn’t an urgent issue. Other scientists believe that global warming is probably due to natural climate variability. In this essay, we present examples of some of the different views actually held by climate researchers.
6. 11/29/2013: Has poor station quality biased U.S. temperature trend estimates?In this essay, we will briefly summarize the analysis in our “Has poor station quality biased U.S. temperature trend estimates?” paper, which we have submitted for peer review at the Open Peer Review Journal. A recent voluntary project, called the Surface Stations project, led by the meteorologist and blogger, Anthony Watts, has found that about 70% of the weather stations in the U.S. Historical Climatology Network are currently sited in locations with artificial heating sources less than 10 metres from the thermometer, e.g., buildings, concrete surfaces, air conditioning units. We found that this poor station quality bias increased the mean U.S. temperature trends of the raw records by about 32%. Some researchers have argued that these biases have been removed by a series of artificial “homogenization” adjustments which had been applied to one version of the U.S. Historical Climatology Network. However, we found that these adjustments were inappropriate and led to “blending” of the biases amongst the stations. While this blending reduced the biases in the most biased stations, it introduced biases into the least biased stations, i.e., the adjustments just spread the biases uniformly between the stations, rather than actually removing the biases. It seems likely that similar siting biases also exist for the rest of the world. So, poor station quality has probably led to an exaggeration of the amount of “global warming” since the 19th century. [FULL TEXT PDF]
7. 12/5/2013: “Urbanization bias” Papers 1-3: Many areas around the world have become highly urbanized over the last century or so. Records of weather stations which are located in urbanized areas may show artifical warming trends due to urbanization bias. In this essay, we summarise the main points of our three “Urbanization bias” papers, which we have submitted for peer review at the Open Peer Review Journal.It has been known since at least the 19th century that urban areas are warmer than rural areas. This is known as the “urban heat island” effect. This is a serious problem for estimating global temperature trends because many weather stations are now showing warming from an urban heat island, which wouldn’t have been there 100 years ago. That is, gradual urbanization has introduced an artificial warming bias into their weather records. This bias is called “urbanization bias”. Since the 19th century, and particularly in the last few decades, the world has become increasingly urbanized. Urban areas still only comprise about 1%. So, this doesn’t really have much impact on actual global temperature trends. But, about half of the weather stations used for analysing global temperatures are in urban areas. As a result, the estimated global temperature trends are seriously affected by this bias. These estimated global temperature trends are the main basis for the claims that there has been “unusual global warming” since the Industrial Revolution. This means that much of the “global warming” that people are worried about is probably just urbanization bias! Despite that, several studies have claimed that urbanization bias isn’t a problem. So, in Paper 1, we carefully analysed these studies to see if their claims were justified. In all cases, we found that they weren’t! It turns out that the authors of those studies had each made basic errors and/or hadn’t looked at their data carefully enough. One of the groups using weather records to calculate global temperature trends has developed a computer program which they believe has removed the urbanization biases from their data. However, in Paper 2, we analysed this program in detail and found that it didn’t work. It actually introduced as many biases as it removed! In Paper 3, we studied the main weather station archives used for calculating global temperature trends, i.e., the Historical Climatology Network datasets. The U.S. component of the datasets was the most reliable component and most of the U.S. stations were fairly rural. However, we found that urbanization bias had introduced an artificial warming trend of about 0.7°C/century into the urban stations. To put this in context, the “unusual global warming” that has allegedly occurred since the Industrial Revolution is supposedly about 0.8°C/century. For the rest of the world, the Historical Climatology Network datasets didn’t actually have enough rural stations with sufficiently long records to estimate global temperature trends. Only EIGHT of the rural stations had data for at least 95 of the last 100 years! This means that the claims that there has been “unusual global warming since the Industrial Revolution” are mostly based on data from urban stations, and much of it is probably an artefact of urbanization bias. [FULL TEXT PDF]
8. 12/11/2013: Is man-made global warming causing more hurricanes? [Wikipedia Graphic: Flood damage in New Orleans, Louisiana (USA) after Hurricane Betsy 1965]. In the mid-2000s, a number of researchers claimed that man-made global warming was leading to an increase in the frequency and intensity of hurricanes, typhoons and other tropical storms. These claims seemed to agree with observations that the cost of damages from tropical storms had been dramatically increasing over the years. In 2005, when Hurricane Katrina devastated the city of New Orleans (USA), this was conclusive proof for many people. As a result, it is now widely believed that global warming is causing an unusual increase in tropical cyclone activity. Now, it seems that whenever a heavy tropical storm makes landfall (e.g., 2012’s Hurricane Sandy or 2013’s Typhoon Haiyan), it is routinely assumed to be somehow related to our fossil fuel usage. However, in this essay, we will show how this belief is seriously flawed for several reasons: It is true that the devastation caused by hurricanes, typhoons and other tropical storms has been dramatically increasing. However, this is because the number of people living in at-risk coastal areas has substantially increased, as has the value of property and infrastructure in those regions. There has indeed been a general increase in the number of recorded tropical cyclones, but much of this increase is due to improvements in our ability to detect cyclones through the use of satellites, aircraft surveillance and better computer analysis Coincidentally, the 1970s seem to have been a relatively quiet era for tropical cyclones, while the 1995-2005 period was relatively active. So, in the mid-2000s, it seemed that there had been a continuous trend from the 1970s. However, 2005 seems to have marked the peak in that active era, and tropical cyclone activity seems to have gone relatively quiet since then. More recent studies have suggested that the proposed link between global warming and cyclone activity is not as straightforward as had been originally thought. The tragedies of recent tropical cyclones such as Hurricane Katrina (2005), Cyclone Nargis (2008), Hurricane Sandy (2012) and Typhoon Haiyan (2013) are bitter reminders of how we should be actively working to improve our ability to adapt and respond to tropical storms. We should also continue researching into better hurricane monitoring and prediction. But, this should be done regardless of global warming. [FULL TEXT PDF] 
9. 5/31/2017: Progress report from the Global Warming Solved team: We haven’t been updating this blog much since early 2014 when we first published our climate science findings. However, while the blog hasn’t been very active, we have been very busy continuing our climate research, discussing our findings with climate scientists around the world and collaborating with other researchers. So, we thought we should write a short post to let you all know how we’ve been getting on since 2014. While the public are still being inundated with claims that “the science is settled”, and that “climate change is man-made and dangerous”, our own experience since we’ve started discussing our findings has mostly been one of encouragement and appreciation from the scientists we’ve met. Most of the scientists we’ve met are usually very interested in our findings, and happy to discuss our work. In this post, we will provide some brief observations on what we’ve found from our discussions. We also include a brief summary of two new papers we’ve published since 2014: W. Soon, R. Connolly & M. Connolly, 2015. Re-evaluating the role of solar variability on Northern Hemisphere temperature trends since the 19th century. Earth-Science Reviews. Vol. 150, 409-452. R. Connolly, M. Connolly & W. Soon, 2017. Re-calibration of Arctic sea ice extent datasets using Arctic surface air temperature records. Hydrological Sciences Journal. In press. [FULL TEXT PDF]