Wednesday, April 16, 2014

New paper finds sea levels were significantly higher than the present for ~10,000 years during the last interglacial

A paper published today in Quaternary Research reconstructs sea levels in the Arabian/Persian Gulf over the past 200,000 years and finds that during the last interglacial [Eemian, MIS 5.1-5.5 below] around 120,000 years ago, sea levels were as much as 5 meters [16 feet] higher than the present for around 10,000 years. The authors find this sea level rise was almost entirely eustatic [from the melting of glaciers] rather than tectonic movements, which were found to be "negligible."

Other papers have found sea levels during the last interglacial were up to 31 feet higher than the present in other locations. Ice core analysis also shows Greenland was 8C warmer than the present during the last interglacial. These changes obviously occurred naturally and there is no evidence that the current interglacial is any different.

Present day sea level is indicated by the dotted horizontal line at zero meters, shown in upper left. Horizontal axis is thousands of years before the present. During the last interglacial [MIS 5.5 shown above] around 120,000 years ago, sea levels were as much as 5 meters higher than the present for ~10,000 years.


Accurate sea-level reconstruction is critical in understanding the drivers of coastal evolution. Inliers of shallow marine limestone and aeolianite are exposed as zeugen (carbonate-capped erosional remnants) on the southern coast of the Arabian/Persian Gulf. These have generally been accepted as evidence of a eustatically driven, last-interglacial relative sea-level highstand preceded by a penultimate glacial-age lowstand. Instead, recent optically stimulated luminescence (OSL) dating suggests a last glacial age for these deposits, requiring > 100 m of uplift since the last glacial maximum in order to keep pace with eustatic sea-level rise and implying the need for a wholesale revision of tectonic, stratigraphic and sea-level histories of the Gulf. These two hypotheses have radically different implications for regional neotectonics and land–sea distribution histories. Here we test these hypotheses using OSL dating of the zeugen formations. These new ages are remarkably consistent with earlier interpretations of the formations being last interglacial or older in age, showing that tectonic movements are negligible and eustatic sea-level variations are responsible for local sea-level changes in the Gulf. The cause of the large age differences between recent studies is unclear, although it appears related to large differences in the measured accumulated dose in different OSL samples.

Review paper finds effects of ocean "acidification" on corals overblown

A new paper from SPPI and CO2 Science reviews the scientific literature on the response of corals to ocean "acidification" and finds such concerns overblown, and in many cases coral calcification and photosynthetic rates of their symbiotic algae improve with elevated CO2 levels. 

corals_acidification
[Illustrations, footnotes and references available in PDF version]
It has been predicted that rates of coral calcification, as well as the photosynthetic rates of their symbiotic algae, will dramatically decline in response to what is typically referred to as an acidification of the world's oceans, as the atmosphere's CO2 concentration continues to rise in the years, decades, and centuries to come. As ever more pertinent evidence accumulates, however, the true story appears to be just the opposite. This summary examines such evidence obtained from field-based studies conducted in the natural ocean.

Increased CO2 enhances the nutritional quality of food crops

A recently published scaremongering study claims that increasing CO2 levels will decrease the nutritional quality of food crops. However, the vast majority of the scientific literature finds the opposite, that increased CO2 improves the nutritional quality of crops. A new paper by SPPI and CO2 Science reviews the scientific literature on the health-promoting effects of elevated CO2 on common food plants and concludes, "it is becoming ever more evident that the ongoing rise in the air's CO2 content is not only increasing the productivity of earth's common food plants, it is significantly increasing the quantity and potency of the many health-promoting substances found in their tissues, which are the ultimate sources of sustenance for essentially all animals and humans."





For the Full Report in PDF Form, please click here.

[Illustrations, footnotes and references available in PDF version]

Excerpts:


How will the ongoing rise in the air's CO2 content alter the amounts of various health-promoting substances found in the plants that we commonly eat? Studies of the effects of atmospheric CO2 enrichment on the quality of the different plants that comprise our diets have typically lagged far behind studies designed to assess the effects of elevated CO2 on the quantity of plant production. Some noteworthy exceptions were the early studies of Barbale (1970) and Madsen (1971, 1975), who discovered that increasing the air's CO2 content produced a modest increase in the vitamin C concentration of tomatoes, while Kimball and Mitchell (1981) demonstrated that enriching the air with CO2 also stimulated the tomato plant's production of vitamin A. Then, a few years later, Tajiri (1985) found that a mere one-hour-per-day doubling of the air's CO2 concentration actually doubled the vitamin C contents of bean sprouts, and that it did so over a period of only seven days.

The direct effects of atmospheric CO2 enrichment on the health-promoting properties of soybean seeds are likely universally beneficial and a boon to the entire human race, especially in light of the fact that Bernacchi et al. (2005) characterize the soybean as "the world's most important seed legume.”

Atmospheric CO2 enrichment can enhance the health-promoting quality of broccoli because of induced glucosinolate content changes

In conclusion, it is becoming ever more evident that the ongoing rise in the air's CO2 content is not only increasing the productivity of earth's common food plants, it is significantly increasing the quantity and potency of the many health-promoting substances found in their tissues, which are the ultimate sources of sustenance for essentially all animals and humans. Thus, as these foods make their way onto our dinner tables, they improve our health and help us better contend with the multitude of diseases and other maladies that regularly afflict us. In fact, it is possible, if not likely, that the lengthening of human life-span that has occurred over the past half-century or more - as described by Horiuchi (2000) and Tuljapurkar et al. (2000)9 - may in some significant part be due to the concomitant CO2-induced increases in the concentrations of the many health-promoting substances found in the various plant-derived foods that we eat.

Tuesday, April 15, 2014

New paper finds storm activity in Alaska is at relatively low levels compared to the past 9,600 years

A paper published today in Quaternary Research reconstructs storm activity in Alaska over the past 9,600 years and finds storm activity at the end of the record [2000 AD] was at relatively low levels in comparison to the rest of the Holocene [past ~10,000 years]. The authors also find storm activity was more variable from 1500 AD - 1850 AD during the Little Ice Age, which contradicts alarmist claims that warming causes increased extreme weather.  

Top graph of BSI % is a proxy for storminess, with lower levels indicating more storminess, as shown at bottom of graph. Horizontal axis is thousands of years before the present. 

The abundance of sedimentary organic material from two lakes was used to infer past Holocene storminess on Adak Island where frequent storms generate abundant rainfall and extensive cloud cover. Andrew and Heart Lakes are located 10 km apart; their contrasting physical characteristics cause the sedimentary organic matter to respond differently to storms. Their records were synchronized using correlated tephra beds. Sedimentation rates increased between 4.0 and 3.5 ka in both lakes. Over the instrumental period, Andrew Lake biogenic-silica content (BSi) is most strongly correlated with winter sunlight availability, which influences photosynthetic production, and river input, which influences the dilution of BSi by mineral matter. Heart Lake BSi is likely affected by wind-driven remobilization of sediment, as suggested by correlations among BSi, the North Pacific Index, and winter storminess. The results indicate relatively stormy conditions from 9.6 to 4.0 ka [thousands of years ago], followed by drying between 4.0 and 2.7 ka, with the driest conditions from 2.7 to 1.5 ka. The stormiest period was between AD 500 and 1200, then drying from 1150 to 1500 and more variable until 1850. This record of Holocene storminess fills a major gap at the center of action for North Pacific wintertime climate.

New paper finds solar activity may influence Arctic sea ice, less ice during Medieval & Roman Warm Periods

A paper published today in Palaeogeography, Palaeoclimatology, Palaeoecology reconstructs Arctic sea ice near West Greenland over the past 5,000 years and finds that solar activity "may be an important contributor to the sea-ice changes." The paper shows Total Solar Irradiance [TSI] at the end of the 20th century was at the highest levels of the past 5,000 years, and a correspondence between solar activity and Arctic sea ice concentration. 

Data from the paper shows Arctic sea ice concentrations were similar [or less than] the present during the Medieval & Roman Warm Periods & the late Holocene Climate Optimum, when solar activity was relatively high. The authors find Arctic sea ice was at the highest concentrations during the Little Ice Age [LIA], corresponding to a period of very low solar activity [the LIA is coincidentally when instrumental observations of global temperatures began]. 

Total Solar Irradiance shown in top graph, LIA = Little Ice Age, MCA = Medieval Climate Anomaly = Medieval Warm Period, DACP = Dark Ages Cold Period, RWP = Roman Warm Period, HTM =  Holocene Thermal Maximum


A diatom-based sea-ice transfer function has been established off West Greenland.
The reconstructed sea ice coincides with the instrumental data for the last 75 years.
Sea-ice condition is influenced by changes in the West Greenland Current components.
The period of the most extensive sea-ice cover occurred during the Little Ice Age.
Solar forcing may be an important contributor to the sea-ice changes.

Abstract

A diatom-based sea-ice concentration (SIC) transfer function was developed by using 72 surface samples from west of Greenland and around Iceland, and validated against associated modern SIC. Canonical correspondence analysis on surface sediment diatoms and monthly average of SIC indicated that April SIC is the most important environmental factor controlling the distribution of diatoms in the area, justifying the development of a diatom-based SIC transfer function. The agreement between reconstructed SIC based on diatoms from West Greenland and the satellite and modelled sea-ice data during the last ~ 75 yr suggests that the diatom-based SIC reconstruction is reliable for studying the palaeoceanography off West Greenland.
Relatively warm conditions with a strong influence of the Irminger Current (IC) were indicated for the early part of the record (~ 5000–3860 cal. yr BP), corresponding in time to the latest part of the Holocene Thermal Maximum. Between 3860 and 1510 cal. yr BP, April SIC oscillated around the mean value (55%) and during the time interval 1510–1120 cal. yr BP and after 650 cal. yr BP was above the mean, indicating more extensive sea-ice cover in Disko Bugt.
Agreement between reconstructed April SIC and changes in the diatom species suggests that the sea-ice condition in Disko Bugt was strongly influenced by variations in the relative strength of two components of the West Greenland Current, i.e. the cold East Greenland Current and the relatively warm IC. Further analysis of the reconstructed SIC record suggests that solar radiation may be an important forcing mechanism behind the historic sea-ice changes.

Monday, April 14, 2014

Satellite data shows CO2 does not control Earth's radiative balance or climate

Dr. Roy Spencer has an interesting post today analyzing several satellite datasets, which suggest "some portion of recent warming was simply due to a natural decrease in cloud cover."

Dr. Spencer also finds an independent method of determining Earth's radiative fluxes [fig 6 below], since "radiative fluxes are so important (e.g. being the basis for global warming theory) that any independent means of estimating them are worth looking into." "Be careful in interpreting the estimated radiative fluxes in Fig. 6 because they could have an offset. Since the anomalies I compute (by definition) sum to zero over the entire time series, that means the total time-integrated radiative energy flux also sums to zero. So, while the graph in Fig. 6 suggests energy loss by the global oceans over the last 5 years, it could be the whole curve needs to be shifted upward. There is no way to know."

I have overlaid the CO2 forcing from increased CO2 levels since 1987 as the red line in Dr. Spencer's Fig. 6 below, based upon the IPCC/Myhre formula for CO2 forcing due to the change in CO2 levels of 349.16 ppm in 1987 to 400 ppm today,

5.35*ln(400/349.16)=0.73 W/m2




which clearly illustrates a disconnect between CO2 levels and net radiative flux, and demonstrates CO2 radiative forcing is not the so-called climate "control knob."

However, all IPCC models are based upon the IPCC/Myhre formula for CO2 radiative forcing, and despite the complexity of the models, the global warming predictions essentially follow this simple formula 1:1:
You don't even need a climate model to show what climate models predict - projections are based upon a single independent variable - CO2 

Thus explaining why the models have been falsified at confidence levels exceeding 98%.



SSM/I Global Ocean Product Update: Increasing clouds with a chance of cooling

by Roy W. Spencer, Ph. D.

My research field of satellite passive microwave remote sensing took off like a rocket (pun intended) when the first Special Sensor Microwave/Imager (SSM/I, built by Hughes Aircraft) was launched in mid-1987 on the DoD series of weather satellites (DMSP).

We SO anticipated that first instrument…good calibration, and high frequency channels to estimate precipitation over land. The previous NASA instruments (ESMR-5, -6, and SMMR) were a good start, but had limited channel selection and less than optimal calibration strategies.

The SSM/I instrument series was later redesigned to incorporate the temperature sounding channels (SSMIS, built by Aerojet). (By the way, we don’t use these in our UAH global temperature monitoring work, since we receive very little money to produce the UAH datasets and incorporating an entirely new series of instruments would be a major effort).

But the real benefit of the SSM/I series of satellite sensors was the production of the “ocean suite” of products: integrated water vapor, surface wind speed, integrated cloud water, and rain rate. These continue to be produced by several investigators, and I use those produced by Remote Sensing Systems (RSS).

To help interpret the SSM/I measurements, let’s start with the HadSST3 sea surface temperatures (SSTs) measured since July, 1987, which is when SSM/I data first became available. (All of the following time series are monthly global anomalies since July, 1987; some have trailing 6-month averages plotted as well). It shows the well-known warming up until the 1997/98 El Nino, then roughly level temperatures since then.
Fig. 1. Monthly global oceanic HadSST3 anomalies from July 1987 thru Feb. 2014.
The first SSM/I field to address is total vertically-integrated water vapor, which closely follows the SST variations:
Fig. 2. Monthly global oceanic anomalies in SSM/I total integrated water vapor.
The water vapor variations lag the SST variations by an average of one month. A regression relationship reveals an average 10.2% increase in vapor per deg. C increase in SST. This is larger than the theoretically-expected value of 6.5% to 7% increase, a discrepancy which can be interpreted in different ways (more evaporative cooling of the ocean stabilizing the climate, or more water vapor feedback destabilizing the climate — take your pick).

Next, let’s examine the surface wind speed variations from SSM/I. These have been compared to literally millions of buoy wind measurements, and are quite accurate. In fact, I would wager these are by far the best estimate of changes in global ocean wind speed we have:
Fig. 3. Monthly global oceanic anomalies in surface wind speed from SSM/I.
We see there was a slight (1-2%) increase in ocean wind speed from before the 1997/98 El Nino to after, which at least qualitatively might be supportive of Trenberth’s claim of increase ocean heat storage and surface cooling temporarily cancelling out anthropogenic global warming. I have not looked into whether a 1-2% change in wind speed could have such an effect, so feel free to comment on this. Note also that the last year or so hints at a reversal of this increase back to pre-1998 wind speeds. If wind speeds remain at the lower level, it will be interesting to see if surface warming resumes. I’m making no predictions on this.

The SSM/I rain rate variations are always quite noisy. Warm conditions tend to show more rainfall, but the strong 1997/98 El Nino curiously shows little effect, and there is a hint of increasing ocean rainfall in recent years:
Fig. 4. Monthly global oceanic anomalies in rainfall from SSM/I.
Finally, let’s look at what I think is the most interesting SSM/I variable from a climate change standpoint, total integrated cloud liquid water (CLW):

Fig. 5. Monthly global oceanic anomalies in integrated cloud water from SSM/I.
The variations in cloud water show some interesting low-frequency behavior. I have previously discussed the fact that these cloud water variations are correlated with CERES-measured net radiative flux, and so provide a proxy measurement for the net radiative imbalance over the ocean which suggest some portion of recent warming was simple due to a natural decrease in cloud cover.

The updated regression relationship I get is 0.24 W/m2 loss in Net (solar plus IR) radiative energy for each percent increase in SSM/I cloud water, a scale factor we can then apply to the cloud water graph to get a Net radiative flux graph:
Fig. 6. Monthly global oceanic anomalies in Net radiative flux estimated from SSM/I cloud water variations, using a CERES-based scale factor of 0.24 W/m2 per percent cloud water change.

Why use an SSM/I estimate of CERES Net radiative flux, instead of CERES directly? Mostly because CERES is available only since 2000, whereas SSM/I is available since 1987. But also, the CERES measurements are very difficult, with the reflected solar flux (which dominates the CERES-SSM/I relationship) having a strong angular dependence. The SSM/I measurements are instead thermally-based (microwave emission) and have no such angular dependence. Finally, radiative fluxes are so important (e.g. being the basis for global warming theory) that any independent means of estimating them are worth looking into.

Be careful in interpreting the estimated radiative fluxes in Fig. 6 because they could have an offset. Since the anomalies I compute (by definition) sum to zero over the entire time series, that means the total time-integrated radiative energy flux also sums to zero. So, while the graph in Fig. 6 suggests energy loss by the global oceans over the last 5 years, it could be the whole curve needs to be shifted upward. There is no way to know. The CERES fluxes have already been adjusted to match the increase in oceanic heat content, which was a logical thing for the CERES Team to do since the absolute accuracy of CERES is ~10 W/m2, whereas the increase in ocean heat content in recent years (IF you believe the warming estimates) correspond to only a few tenths of a W/m2 imbalance. The main value in the graph is to identify possible changes over time.

Others might see some relationships in the above plots that I haven’t noticed; I’ve made the Excel spreadsheet available for those who want to play with the data.

Wednesday, April 9, 2014

New Paper Corroborates the Solar-Cosmic Ray Theory of Climate

A paper published today in Environmental Research Letters corroborates the Svensmark cosmic ray theory of climate, whereby tiny 0.1% changes in solar activity are amplified via the effect on cosmic rays and cloud formation, which in turn may control global temperatures. The authors find cosmic ray variations due to changes over solar cycles may have as much as 10 times larger effect than previous studies have estimated. The paper also finds that a tiny 0.2C temperature increase increases the cosmic ray induced cloud condensation nuclei by around 50%, thus acting as a natural homeostatic mechanism. 

According to the authors, "The effect of solar cycle perturbation on [cloud condensation nuclei] based on present study is generally higher than those reported in several previous studies, up to around one order of magnitude [10 times]...Our global simulations indicate that a decrease in ionization rate associated with galactic cosmic ray flux change from solar minimum to solar maximum reduces annual mean nucleation rates, number concentration of cloud condensation nuclei larger than 10 nm... by 6.8%, 1.36%...respectively. The inclusion of 0.2 °C temperature increase enhances the CCN [cloud condensation nuclei] solar cycle signals by around 50%."


"The most obvious way for warming to be caused naturally is for small, natural fluctuations in the circulation patterns of the atmosphere and ocean to result in a 1% or 2% decrease in global cloud cover. Clouds are the Earth’s sunshade, and if cloud cover changes for any reason, you have global warming — or global cooling."

This new paper finds annual mean cloud nucleation rates may vary 6.8% over solar cycles, far more than the 1-2% change in global cloudiness required to change global temperature. 

The solar-cosmic ray theory of climate is only one of many solar amplification mechanisms described in the scientific literature. 






Effect of solar variations on particle formation and cloud condensation nuclei

OPEN ACCESS FOCUS ON HIGH ENERGY PARTICLES AND ATMOSPHERIC PROCESSES
Fangqun Yu and Gan Luo
Show affiliations


Paper
The impact of solar variations on particle formation and cloud condensation nuclei (CCN), a critical step for one of the possible solar indirect climate forcing pathways, is studied here with a global aerosol model optimized for simulating detailed particle formation and growth processes. The effect of temperature change in enhancing the solar cycle CCN signal is investigated for the first time. Our global simulations indicate that a decrease in ionization rate associated with galactic cosmic ray flux change from solar minimum to solar maximum reduces annual mean nucleation rates, number concentration of condensation nuclei larger than 10 nm (CN10), and number concentrations of CCN at water supersaturation ratio of 0.8% (CCN0.8) and 0.2% (CCN0.2) in the lower troposphere by 6.8%, 1.36%, 0.74%, and 0.43%, respectively. The inclusion of 0.2 °C temperature increase enhances the CCN [cloud condensation nuclei] solar cycle signals by around 50%. The annual mean solar cycle CCN signals have large spatial and seasonal variations: (1) stronger in the lower troposphere where warm clouds are formed, (2) about 50% larger in the northern hemisphere than in the southern hemisphere, and (3) about a factor of two larger during the corresponding hemispheric summer seasons. The effect of solar cycle perturbation on CCN0.2 [cloud condensation nuclei] based on present study is generally higher than those reported in several previous studies, up to around one order of magnitude.

Tuesday, April 8, 2014

New paper finds significant decreasing trend of Australian tropical cyclones

A paper published today in Atmospheric Science Letters finds "a significant decreasing trend in [Australian tropical cyclone] numbers at the 93–98% confidence level." The paper adds to many others finding cyclone and storm activity has decreased globally with warming, despite the opposite cries of alarmists.



Long-term changes in Australian tropical cyclone numbers


Andrew J. Dowdy

Tropical cyclone (TC) observations are used to examine changes in the TC climatology of the Australian region. The ability to investigate long-term changes in TC numbers improves when the El Niño-Southern Oscillation (ENSO) is considered. Removing variability in TC numbers associated with ENSO shows a significant decreasing trend in TC numbers at the 93–98% confidence level. Additionally, there is some indication of a temporal change in the relationship between ENSO and TC numbers, with ENSO accounting for about 35–50% of the variance in TC numbers during the first half of the study period, but only 10% during the second half.

Monday, April 7, 2014

WSJ: "'Shut Up' Is No Argument. It reveals a lack of confidence in global-warmist dogma"

'Shut Up' Is No Argument

The illiberal left lacks confidence in its ideas.

By JAMES TARANTO April 7,2014  THE WALL STREET JOURNAL

Excerpt: 
...So Democrats are stuck with ObamaCare. But as long as we have a two-party system, the debate will go on. What's striking is that the quality of the pro-ObamaCare arguments is so abysmally poor. "Blah, blah, blah." "Feel free to ridicule right-wingers." "This thing is going to work."
Does he have confidence in his views? Getty Images
Most of all: "The debate . . . is over." A demand for silence is not a sign of intellectual self-confidence. And this is not the only subject on which the left is demanding that its opponents just shut up. For years we've been hearing that the debate about global warming--or "climate change" or whatever they're calling it this week--is settled. Early in the 2000s some news organizations declared they would banish dissenting points of view from their pages. The debate goes on.
Last month Adam Weinstein wrote a piece for Gawker.com called "Arrest the Climate-Change Deniers." "Man-made climate change kills a lot of people," he claimed, offering no evidence. "It's going to kill a lot more. We have laws on the books to punish anyone whose lies contribute to people's deaths. It's time to punish the climate-change liars."
He stipulates that "I'm not talking about the man on the street," who is a mere "idiot . . . too stupid to do anything other than choke the earth's atmosphere a little more with his Mr. Pibb burps and his F-150's gassy exhaust":
I'm talking about Rush [Limbaugh] and his multi-million-dollar ilk in the disinformation business. I'm talking about Americans for Prosperity and the businesses and billionaires who back its obfuscatory propaganda. I'm talking about public persons and organizations and corporations for whom denying a fundamental scientific fact is profitable, who encourage the acceleration of an anti-environment course of unregulated consumption and production that, frankly, will screw my son and your children and whatever progeny they manage to have.
Those malcontents must be punished and stopped.
Deniers will, of course, fuss and stomp and beat their breasts and claim this is persecution, this is a violation of free speech.
In reality, it is none of those things, because it is not going to happen--at least not in America, with our vigorous First Amendment tradition. It's a fantasy--but a revealing one. What it reveals is a lack of confidence in global-warmist dogma.

The Time-Integral of Solar Activity explains Global Temperatures 1610-2012, not CO2


Guest post by Dan Pangburn

Introduction

This monograph is a clarification and further refinement of Reference 10 (references are listed at the end of this paper) which also considers only average global temperature. It does not discuss weather, which is a complex study of energy moving about the planet. It does not even address local climate, which includes precipitation. It does, however, consider the issue of Global Warming and the mistaken perception that human activity has a significant influence on it.

The word ‘trend’ is used here for temperatures in two different contexts. To differentiate, α-trend applies to averaging-out the uncertainties in reported average global temperature measurements to produce the average global temperature oscillation resulting from the net ocean surface oscillation. The term β-trend applies to the slower average temperature change of the planet which is associated with change to the temperature of the bulk volume of the material (mostly water) involved.

The first paper to suggest the hypothesis that the sunspot number time-integral is a proxy for a substantial driver of average global temperature change was made public 6/1/2009. The discovery started with application of the first law of thermodynamics, conservation of energy, and the hypothesis that the energy acquired, above or below breakeven (appropriately accounting for energy radiated from the planet), is proportional to the time-integral of sunspot numbers. The derived equation revealed a rapid and sustained global energy rise starting in about 1941. The true average global temperature anomaly change β-trend is proportional to global energy change.

Measured temperature anomaly α-trends oscillate above and below the temperature anomaly β-trend calculated using only the sunspot number time-integral. The existence of ocean oscillations, especially the Pacific Decadal Oscillation, led to the perception that there must be an effective net surface temperature oscillation with all named and unnamed ocean oscillations as participants. Plots of measured average global temperatures indicate that the net surface temperature oscillation has a period of 64 years with the most recent maximum in 2005.

Combination of the effects results in the effect of the ocean surface temperature oscillation (α-trend) decline 1941-1973 being slightly stronger than the effect of the rapid rise from sunspots (β-trend) resulting in a slight decline of the trend of reported average global temperatures. The steep rise 1973-2005 occurred because the effects added. A high coefficient of determination, R2, demonstrates that the hypothesis is true.

Over the years, several refinements to this work (often resulting from other's comments which may or may not have been agreeable) slightly improved the accuracy and led to the equations and figures in this paper.

Prior work

The law of conservation of energy is applied effectively the same as described in Reference 2 in the development of a very similar equation that calculates temperature anomalies. The difference is that the variation in energy ‘OUT’ has been found to be adequately accounted for by variation of the sunspot numbers. Thus the influence of the factor [T(i)/Tavg]4 is eliminated.

Change to the level of atmospheric carbon dioxide has no significant effect on average global temperature. This was demonstrated in 2008 at Reference 6 and is corroborated at Reference 2 and again here.

As determined in Reference 3, reported average global temperature anomaly measurements have a random uncertainty with equivalent standard deviation ≈ 0.09 K.

Global Warming ended more than a decade ago as shown here, and in Reference 4 and also Reference 2.

Average global temperature is very sensitive to cloud change as shown in Reference 5.

The parameter for average sunspot number was 43.97 (average 1850-1940) in Ref. 1, 42 (average 1895-1940) in Ref. 9, and 40 (average 1610-2012) in Ref. 10. It is set at 34 (average 1610-1940) in this paper. The procession of values for average sunspot number produces slight but steady improvement in R2 for the period of measured temperatures and progressively greater credibility of average global temperature estimates for the period prior to direct measurements becoming available.

Initial work is presented in several papers at http://climaterealists.com/index.php?tid=145&linkbox=true

The sunspot number time-integral drives the temperature anomaly trend

It is axiomatic that change to the average temperature trend of the planet is due to change to the net energy retained by the planet.

Table 1 in reference 2 shows the influence of atmospheric carbon dioxide (CO2) to be insignificant (tiny change in R2 if considering CO2 or not) so it can be removed from the equation by setting coefficient ‘C’ to zero. With ‘C’ set to zero, Equation 1 in Reference 2 calculates average global temperature anomalies (AGT) since 1895 with 89.82% accuracy (R2= 0.898220).

The current analysis determined that 34, the approximate average of sunspot numbers from 1610-1940, provides a slightly better fit to the measured temperature data than did 43.97 and other values 9,10. The influence, of Stephan-Boltzmann radiation change due to AGT change, on energy change is adequately accounted for by the sunspot number time-integral. With these refinements to Equation (1) in Reference 2 the coefficients become A = 0.3588, B = 0.003461 and D = ‑ 0.4485.  R2 increases slightly to 0.904906 and the calculated anomaly in 2005 is 0.5045 K. Also with these refinements the equation calculates lower early anomalies and projects slightly higher (0.3175 vs. 0.269 in 2020) future anomalies. Measured anomalies are shown in Figure 2 of Reference 3. The excellent match of the up and down trends since before 1900 of calculated and measured anomalies, shown here in Figure 1, demonstrates the usefulness and validity of the calculations.

Projections until 2020 use the expected sunspot number trend for the remainder of solar cycle 24 as provided 11 by NASA. After 2020 the limiting cases are either assuming sunspots like from 1925 to 1941 or for the case of no sunspots which is similar to the Maunder Minimum.

Some noteworthy volcanoes and the year they occurred are also shown on Figure 1. No consistent AGT response is observed to be associated with these. Any global temperature perturbation that might have been caused by volcanoes of this size is lost in the temperature measurement uncertainty. Much larger volcanoes can cause significant temporary global cooling from the added reflectivity of aerosols and airborne particulates. The Tambora eruption, which started on April 10, 1815 and continued to erupt for at least 6 months, was approximately ten times the magnitude of the next largest in recorded history and led to 1816 which has been referred to as ‘the year without a summer’. The cooling effect of that volcano exacerbated the already cool temperatures associated with the Dalton Minimum.
 
 Figure 1: Measured average global temperature anomalies with calculated prior and future trends using 34 as the average daily sunspot number.

As discussed in Reference 2, ocean oscillations produce oscillations of the ocean surface temperature with no significant change to the average temperature of the bulk volume of water involved. The effect on AGT of the full range of surface temperature oscillation is given by the coefficient ‘A’.

The influence of ocean surface temperature oscillations can be removed from the equation by setting ‘A’ to zero. To use all regularly recorded sunspot numbers, the integration starts in 1610. The offset, ‘D’ must be changed to -0.1993 to account for the different integration start point and setting ‘A’ to zero. Setting ‘A’ to zero requires that the anomaly in 2005 be 0.5045 - 0.3588/2 = 0.3251 K. The result, Equation (1) here, then calculates the trend 1610-2012 resulting from just the sunspot number time-integral.

Trend3anom(y) = 0.003461/17 * Σyi = 1610 [s(i)-34] – 0.1993                (1)

Where:
Trend3anom(y) = calculated temperature anomaly β-trend in year y, K degrees.
0.003461 = the proxy factor, B, W yr m-2.
17 = effective thermal capacitance of the planet, W Yr m-2 K-1
s(i) = average daily Brussels International sunspot number in year i
34 ≈ average sunspot number for 1610-1940.
-0.1993 is merely an offset that shifts the calculated trajectory vertically on the graph, without changing its shape, so that the calculated temperature anomaly in 2005 is 0.3251 K which is the calculated anomaly for 2005 if the ocean oscillation is not included.

Sunspot numbers back to 1610 are shown in Figure 2 of Reference 1.

Applying Equation (1) to the sunspot numbers of Figure 2 of Reference 1 produces the trace shown in Figure 2 below.

Figure 2: Anomaly trend from just the sunspot number time-integral using Equation (1).

Average global temperatures were not directly measured in 1610 (thermometers had not been invented yet). Recent estimates, using proxies, are few. The anomaly trend that Equation (1) calculates for that time is roughly consistent with other estimates. The decline in the trace 1610-1700 on Figure 2 results from the low sunspot numbers for that period as shown on Figure 2 of Reference 1. 

How this phenomenon could take place

Although the connection between AGT and the sunspot number time-integral is demonstrated, the mechanism by which this takes place remains somewhat theoretical.

Various papers have been written that indicate how the solar magnetic field associated with sunspots can influence climate on earth. These papers posit that decreased sunspots are associated with decreased solar magnetic field which decreases the deflection of and therefore increases the flow of galactic cosmic rays on earth.

Henrik Svensmark, a Danish physicist, found that decreased galactic cosmic rays caused decreased low level (< 3 km) clouds and planet warming. An abstract of his 2000 paper is at Reference 13. Marsden and Lingenfelter also report this in the summary of their 2003 paper 14 where they make the statement “…solar activity increases…providing more shielding…less low-level cloud cover… increase surface air temperature.”  These findings have been further corroborated by the cloud nucleation experiments 15 at CERN.

These papers associated the increased low-level clouds with increased albedo leading to lower temperatures. Increased low clouds would also result in lower average cloud altitude and therefore higher average cloud temperature. Although clouds are commonly acknowledged to increase albedo, they also radiate energy to space so increasing their temperature increases radiation to space which would cause the planet to cool. Increased albedo reduces the energy received by the planet and increased radiation to space reduces the energy of the planet. Thus the two effects work together to change the AGT of the planet.

Simple analyses 5 indicate that either an increase of approximately 186 meters in average cloud altitude or a decrease of average albedo from 0.3 to the very slightly reduced value of 0.2928 would account for all of the 20th century increase in AGT of 0.74 °C. Because the cloud effects work together and part of the temperature change is due to ocean oscillation substantially less cloud change is needed.

Combined Sunspot Effect and Ocean Oscillation Effect

As a possibility, the period and amplitude of oscillations attributed to ocean cycles demonstrated to be valid after 1895 are assumed to maintain back to 1610. Equation (1) is modified as shown in Equation (2) to account for including the effects of ocean oscillations. Since the expression for the oscillations calculates values from zero to the full range but oscillations must be centered on zero, it must be reduced by half the oscillation range.

Trend4anom(y) = (0.3588,y) – 0.1794 + 0.003461/17 * Σyi = 1610 [s(i)-34] – 0.1993   (2)

The ocean oscillation factor, (0.3588,y) – 0.1794, is applied prior to the start of temperature measurements as a possibility. The effective sea surface temperature anomaly, (A,y), is defined in Reference 2.

Applying Equation (2) to the sunspot numbers from Figure 2 of Reference 1 produces the trend shown in Figure 3 next below. Available measured average global temperatures from Figure 2 in Reference 3 are superimposed on the calculated values.
 
 Figure 3: Calculated anomalies from the sunspot number time-integral plus ocean oscillation using Equation (2) with superimposed available measured data from Reference 3 and range estimates determined by Loehle.

Figure 3 shows that temperature anomalies calculated using Equation (2) estimate possible trends since 1610 and actual trends of reported temperatures since they have been accurately measured world wide. The match from 1895 on has R2 = 0.9049 which means that 90.49% of average global temperature anomaly measurements are explained. All factors not explicitly considered must find room in that unexplained 9.51%. Note that a coefficient of determination, R2 = 0.9049 means a correlation coefficient of 0.95.

A survey 12 of non-tree-ring global temperature estimates was conducted by Loehle including some for a period after 1610. A simplification of the 95% limits found by Loehle are also shown on Figure 3. The spread between the upper and lower 95% limits are fixed, but, since the anomaly reference temperatures might be different, the limits are adjusted vertically to approximately bracket the values calculated using the equations. The fit appears reasonable considering the uncertainty in all values.

Calculated anomalies look reasonable back to 1700 but indicate higher temps prior to that than most proxy estimates. They are, however, consistent with the low  sunspot numbers in that period. They qualitatively agree with Vostok, Antarctica ice core data but decidedly differ from Sargasso Sea estimates during that time (see the graph for the last 1000 years in Reference 6). Credible worldwide assessments of average global temperature that far back are sparse. Ocean oscillations might also have been different from assumed.

Possible lower values for average sunspot number
Possible lower assumed values for average sunspot number, with coefficients adjusted to maximize R2, result in noticeably lower estimates of early (prior to direct measurement) temperatures with only a tiny decrease in R2. Calculated anomalies resulting from using an average sunspot number value of 26 are shown in Figure 4. The projected anomaly trend decline is slightly less steep (0.018 K warmer in 2020) than was shown in Figure 1.

Figure 4: Calculated anomalies from the sunspot number time-integral plus ocean oscillation using 26 as the average sunspot number with superimposed available measured data from Reference 3 and range estimates determined by Loehle.

Carbon dioxide change has no significant influence

The influence that CO2 has on AGT can be calculated by including ‘C’ in Equation (1) of Reference 2 as a coefficient to be determined. The tiny increase in R2 demonstrates that consideration of change to the CO2 level has no significant influence on AGT [average global temperature]. The coefficients and resulting R2 are given in Table 



1.Conclusions

Others that have looked at only amplitude or only duration factors for solar cycles got poor correlations with average global temperature. The good correlation comes by combining the two, which is what the time-integral of sunspot numbers does. As shown in Figure 2, the anomaly trend determined using the sunspot number time-integral has experienced substantial change over the recorded period. Prediction of future sunspot numbers more than a decade or so into the future has not yet been confidently done although assessments using planetary synodic periods appear to be relevant 7,8.

As displayed in Figure 2, the time-integral of sunspot numbers alone appears to show the estimated true average global temperature trend (the net average global energy trend) during the planet warm up from the depths of the Little Ice Age.

The net effect of ocean oscillations is to cause the surface temperature trend to oscillate above and below the trend calculated using only the sunspot number time-integral. Equation (2) accounts for both and also, because it matches measurements so well, shows that rational change to the level of atmospheric carbon dioxide can have no significant influence.
Long term prediction of average global temperatures depends primarily on long term prediction of sunspot numbers.


References:
11. Graphical sunspot number prediction for the remainder of solar cycle 24http://solarscience.msfc.nasa.gov/predict.shtml
12. http://www.econ.ohio-state.edu/jhm/AGW/Loehle/Loehle_McC_E&E_2008.pdf
13.   Svensmark paper, Phys. Rev. Lett. 85, 5004–5007 (2000)  http://prl.aps.org/abstract/PRL/v85/i23/p5004_1
14.  Marsden & Lingenfelter 2003, Journal of the Atmospheric Sciences 60: 626-636  http://www.co2science.org/articles/V6/N16/C1.php
15. CLOUD experiment at CERNhttp://indico.cern.ch/event/197799/session/9/contribution/42/material/slides/0.pdf