Increasing Rates of Melanoma NOT caused by Sun Exposure

November 21, 2011 2 Comments

Mercola.com
November 21, 2011

Rates of melanoma, the deadliest form of skin cancer, have been rising for at least the last three decades, and this increase has been largely blamed on exposure to ultraviolet (UV) light from the sun.

However, research published in the British Journal of Dermatology shows that the sun is likely nothing more than a scapegoat in the development of melanoma, and the sharp increase may actually be “an artifact caused by diagnostic drift.”

Melanoma Increases Due to Benign Disease, Not Sunlight

Diagnostic drift, according to the study, refers to a hefty increase in disease that is being fueled by non-cancerous lesions.

In fact, during the study period from 1991 to 2004, there were nearly 4,000 cases of melanoma included in the report, with an annual increase of 9.39 to 13.91 cases per 100,000 per year.

The researchers revealed that, rather than being fueled by increasing exposure to sunlight as is commonly suggested, the increased incidence was almost entirely due to minimal, stage 1 disease.

They noted:

“There was no change in the combined incidence of the other stages of the disease, and the overall mortality only increased from 2.16 to 2.54 cases per 100,000 per year … We therefore conclude that the large increase in reported incidence is likely to be due to diagnostic drift, which classifies benign lesions as stage 1 melanoma.”

In other words, people are being diagnosed with melanoma skin cancer even when they have only a minimal, non-cancerous lesion, and these diagnoses appear to be skewing disease rates significantly. Further, adding even more credence to the growing body of evidence showing sun exposure is not the primary cause of melanoma, the researchers noted that the distribution of the lesions reported did not correspond to the sites of lesions caused by sun exposure.

They concluded:

“These findings should lead to a reconsideration of the treatment of ‘early’ lesions, a search for better diagnostic methods to distinguish them from truly malignant melanomas, re-evaluation of the role of ultraviolet radiation and recommendations for protection from it, as well as the need for a new direction in the search for the cause of melanoma.”

Is Lack of Sunlight a More Likely Culprit?

Despite all the bad press linking sun exposure to skin cancer, there’s almost no evidence at all to support it. There is, however, plenty of evidence to the contrary. Over the years, several studies have confirmed that appropriate sun exposure actually helps prevent skin cancer. In fact, melanoma occurrence has been found to decrease with greater sun exposure, and can be increased by sunscreens.

One of the most important facts you should know is that an epidemic of the disease has in fact broken out among indoor workers. These workers get three to nine times LESS solar UV exposure than outdoor workers get, yet only indoor workers have increasing rates of melanoma — and the rates have been increasing since before 1940.

There are two major factors that help explain this, and the first has to do with the type of UV exposure.

There are two primary types of UV rays from sunlight, the vitamin-D-producing UVB rays and the skin-damaging UVA light. Both UVA and UVB can cause tanning and burning, although UVB does so far more rapidly. UVA, however, penetrates your skin more deeply than UVB, and may be a much more important factor in photoaging, wrinkles and skin cancers.

A study in Medical Hypotheses suggested that indoor workers may have increased rates of melanoma because they’re exposed to sunlight through windows, and only UVA light, unlike UVB, can pass through window glass. At the same time, these indoor workers are missing out on exposure to the beneficial UVB rays, and have lower levels of vitamin D.

Researchers wrote:

“We hypothesize that one factor involves indoor exposures to UVA (321–400nm) passing through windows, which can cause mutations and can break down vitamin D3 formed after outdoor UVB (290–320nm) exposure, and the other factor involves low levels of cutaneous vitamin D3.

After vitamin D3 forms, melanoma cells can convert it to the hormone, 1,25-dihydroxyvitamin D3, or calcitriol, which causes growth inhibition and apoptotic cell death in vitro and in vivo. 

… We agree that intense, intermittent outdoor UV overexposures and sunburns initiate CMM [cutaneous malignant melanoma]; we now propose that increased UVA exposures and inadequately maintained cutaneous levels of vitamin D3 promotes CMM.”
To put it simply, UVB appears to be protective against melanoma — or rather, the vitamin D your body produces in response to UVB radiation is protective.

As written in The Lancet:

“Paradoxically, outdoor workers have a decreased risk of melanoma compared with indoor workers, suggesting that chronic sunlight exposure can have a protective effect.”

Vitamin D Helps Protect You Against Cancer

Vitamin D is a steroid hormone that influences virtually every cell in your body, and is easily one of nature’s most potent cancer fighters. So I want to stress again that if you are shunning all sun exposure, you are missing out on this natural cancer protection.

Your organs can convert the vitamin D in your bloodstream into calcitriol, which is the hormonal or activated version of vitamin D. Your organs then use it to repair damage, including damage from cancer cells and tumors. Vitamin D’s protective effect against cancer works in multiple ways, including:

  • Increasing the self-destruction of mutated cells (which, if allowed to replicate, could lead to cancer)
  • Reducing the spread and reproduction of cancer cells
  • Causing cells to become differentiated (cancer cells often lack differentiation)
  • Reducing the growth of new blood vessels from pre-existing ones, which is a step in the transition of dormant tumors turning cancerous

This applies not only to skin cancer but other types of cancer as well. Theories linking vitamin D to certain cancers have been tested and confirmed in more than 200 epidemiological studies, and understanding of its physiological basis stems from more than 2,500 laboratory studies, according to epidemiologist Cedric Garland, DrPH, professor of family and preventive medicine at the UC San Diego School of Medicine.

Here are just a few highlights into some of the most noteworthy findings:

  • Some 600,000 cases of breast and colorectal cancers could be prevented each year if vitamin D levels among populations worldwide were increased, according to previous research by Dr. Garland and colleagues.
  • Optimizing your vitamin D levels could help you to prevent at least 16 different types of cancer including pancreatic, lung, ovarian, prostate, and skin cancers.
  • A large-scale, randomized, placebo-controlled study on vitamin D and cancer showed that vitamin D can cut overall cancer risk by as much as 60 percent. This was such groundbreaking news that the Canadian Cancer Society has actually begun endorsing the vitamin as a cancer-prevention therapy.
  • Light-skinned women who had high amounts of long-term sun exposure had half the risk of developing advanced breast cancer (cancer that spreads beyond your breast) as women with lower amounts of regular sun exposure, according to a study in the American Journal of Epidemiology.
  • A study by Dr. William Grant, Ph.D., internationally recognized research scientist and vitamin D expert, found that about 30 percent of cancer deaths — which amounts to 2 million worldwide and 200,000 in the United States — could be prevented each year with higher levels of vitamin D.

When Using the Sun to Fight Cancer, the Dose is What Matters

When I recommend using the sun therapeutically, this means getting the proper dosage to optimize your vitamin D levels. This typically means exposing enough of your unclothed skin surface to get a slight pink color on your skin. Your exact time will vary radically depending on many variables, such as you skin color, time of day, season, clouds, altitude and age.  The key principle is to never get burned, while still spending as much time as you can in the sun during the peak hours, as it is virtually impossible to overdose as long as you don’t get burned.

A common myth is that occasional exposure of your face and hands to sunlight is “sufficient” for vitamin D nutrition. For most of us, this is an absolutely inadequate exposure to move vitamin D levels to the healthy range. Further, if you use sunscreen, you will block your body’s ability to produce vitamin D!

And, contrary to popular belief, the best time to be in the sun for vitamin D production is actually as near to solar noon as possible which is 1 PM in the summer for most (due to Daylight Saving Time).. The more damaging UVA rays are quite constant during ALL hours of daylight, throughout the entire year — unlike UVB, which are low in morning and evening and high at midday.

When using the sun to maximize your vitamin D production and minimize your risk of malignant melanoma, the middle of the day (roughly between 10:00 a.m. and 1:00 p.m.) is the best and safest time. During this time you need the shortest exposure time to produce vitamin D because UVB rays are most intense at this time. Plus, when the sun goes down toward the horizon, the UVB is filtered out much more than the dangerous UVA.

Once you reach this point your body will  peak at about 10,000-40,000 units of vitamin D. Any additional exposure will only cause harm and damage to your skin. Most people with fair skin will max out their vitamin D production in just 10-20 minutes, or, again, when your skin starts turning the lightest shade of pink. Some will need less, others more. The darker your skin, the longer exposure you will need to optimize your vitamin D production.

Why Not Just Take Vitamin D from a Supplement?

You can get vitamin D3 in supplement form, and if sunlight or a safe tanning bed is not an option, this is a better choice than getting no vitamin D at all. If you do use a supplement, it now appears as though most adults need about 8,000 IU’s of vitamin D a day in order to get their serum levels above 40 ng/ml.

However, sunlight is really the superior source for vitamin D, as when you expose your skin to sunshine, your skin synthesizes vitamin D3 sulfate. This form of vitamin D is water soluble, unlike oral vitamin D3 supplements, which is unsulfated. The water-soluble form can travel freely in your bloodstream, whereas the unsulfated form needs LDL (the so-called “bad” cholesterol) as a vehicle of transport.

The oral non-sulfated form of vitamin D may not provide all of the same benefits as the vitamin D created in your skin from sun exposure, because it cannot be converted to vitamin D sulfate.

I believe this is a very compelling reason to really make a concerted effort to get your vitamin D requirements from exposure to sunshine, or by using a safe tanning bed (one with electronic ballasts rather than magnetic ballasts, to avoid unnecessary exposure to EMF fields). Safe tanning beds also have less of the dangerous UVA than sunlight, while unsafe ones have more UVA than sunlight. If neither of these are feasible options, then you should take an oral vitamin D3 supplement.

What Should Your Vitamin D Levels be for Cancer Protection?

In 2007 the recommended level was between 40 to 60 nanograms per milliliter (ng/ml). Since then, the optimal vitamin D level has been raised to 50-70 ng/ml, and when treating cancer or heart disease, as high as 70-100 ng/ml.

Natural Treatment for Non-Melanoma Skin Cancer
Melanoma skin cancer is the deadliest form, but far more common are non-melanoma skin cancers, which impact millions of Americans every year.

If you or someone you love is affected, a cream containing eggplant extract, known as BEC and BEC5, appears to cure and eliminate most non-melanoma skin cancers in several weeks time. Unlike conventional skin-cancer treatment, which is often surgery, the eggplant-extract cream leaves no scarring and no visible sign a tumor or lesion was ever present. The eggplant extract appears to be exceptionally safe and only kills cancerous cells, leaving healthy cells untouched, and causes only minor side effects, such as itching and burning.

The leading researcher in this area today is Dr. Bill E. Cham, who reported as early as 1991 in Cancer Letters that:
“A cream formulation containing high concentrations (10%) of a standard mixture of solasodine glycosides (BEC) has been shown to be effective in the treatment of malignant and benign human skin tumors.

We now report that a preparation … which contains very low concentrations of BEC (0.005%) is effective in the treatment of keratoses, basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) of the skin of humans. In an open study, clinical and histological observations indicated that all lesions (56 keratoses, 39 BCCs and 29 SCCs) treated with [the preparation] had regressed.”
Dr. Cham’s latest study was published in the International Journal of Clinical Medicine this year. The paper includes two impressive case reports of 60-something men who were suffering from large basal cell carcinoma (BCC) or squamous cell carcinoma (SCC), which had plagued them for years.  The results upon treatment with a cream formulation of BEC (eggplant extract) twice a day are astounding, and you can view the pictures here.

Unfortunately, simply eating eggplant, tomatoes, peppers or similar veggies, while beneficial for many reasons, will not induce this same effect because the active components are not able to effectively penetrate your cells. This requires the addition of glycosides, molecules with various simple sugars attached to them that can latch on to receptors found on skin cancer cells.

Simple Skin Cancer Prevention Strategies

What’s even better than an inexpensive, safe and natural cure for skin cancer is, of course, preventing it in the first place. Your body is made to be in the sun, and, when done properly, sun exposure will be one of the best ways you can help reduce your risk of skin, and many other forms of, cancer. Along with optimizing your vitamin D levels, the carotenoid astaxanthin has also piqued the interest of researchers due to its ability to reduce signs of aging by helping protect your skin from sun damage. I personally take 8 mg every day to help limit any potential damage from sun exposure as most of the year I am able to spend one to two hours a day in the sun.

Consuming a healthy diet full of natural antioxidants is another useful strategy to avoid sun damage to your skin, as fresh, raw, unprocessed foods deliver the nutrients that your body needs to maintain a healthy balance of omega-6 and omega-3 oils in your skin, which is your first line of defense against sunburn.

Fresh, raw vegetables also provide your body with an abundance of powerful antioxidants that will help you fight the free radicals caused by sun damage that can lead to burns and cancer.

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Climate Sensitivity Reconsidered Part 1

January 20, 2011

A special report from Christopher Monckton of Brenchley for all Climate Alarmists, Consensus Theorists and Anthropogenic Global Warming Supporters

January 20, 2011

Abstract

The Intergovernmental Panel on Climate Change (IPCC, 2007) concluded that anthropogenic CO2 emissions probably
caused more than half of the “global warming” of the past 50 years and would cause further rapid warming. However,
global mean surface temperature TS has not risen since 1998 and may have fallen since late 2001. The present analysis
suggests that the failure of the IPCC’s models to predict this and many other climatic phenomena arises from defects in its
evaluation of the three factors whose product is climate sensitivity:

1) Radiative forcing ΔF;
2) The no-feedbacks climate sensitivity parameter κ; and
3) The feedback multiplier f.
Some reasons why the IPCC’s estimates may be excessive and unsafe are explained. More importantly, the conclusion is
that, perhaps, there is no “climate crisis”, and that currently-fashionable efforts by governments to reduce anthropogenic
CO2 emissions are pointless, may be ill-conceived, and could even be harmful.

The context

LOBALLY-AVERAGED land and sea surface absolute temperature TS has not risen since 1998 (Hadley Center; US National Climatic Data Center; University of Alabama at Huntsville; etc.). For almost seven years, TS may even have fallen (Figure 1). There may be no new peak until 2015 (Keenlyside et al., 2008).

The models heavily relied upon by the Intergovernmental Panel on Climate Change (IPCC) had not projected this multidecadal stasis in “global warming”; nor (until trained ex post facto) the fall in TS from 1940-1975; nor 50 years’ cooling in Antarctica (Doran et al., 2002) and the Arctic (Soon, 2005); nor the absence of ocean warming since 2003 (Lyman et al., 2006; Gouretski & Koltermann, 2007); nor the onset, duration, or intensity of the Madden-Julian intraseasonal oscillation, the Quasi-Biennial Oscillation in the tropical stratosphere, El Nino/La Nina oscillations, the Atlantic Multidecadal Oscillation, or the Pacific Decadal Oscillation that has recently transited from its warming to its cooling phase (oceanic oscillations which, on their own, may account for all of the observed warmings and coolings over the past half-century: Tsonis et al., 2007); nor the magnitude nor duration of multicentury events such as the Medieval Warm Period or the Little Ice Age; nor the cessation since 2000 of the previously-observed growth in atmospheric methane concentration (IPCC, 2007); nor the active 2004 hurricane season; nor the inactive subsequent seasons; nor the UK flooding of 2007 (the Met Office had forecast a summer of prolonged droughts only six weeks previously); nor the solar Grand Maximum of the past 70 years, during which the Sun was more active, for longer, than at almost any
similar period in the past 11,400 years (Hathaway, 2004; Solanki et al., 2005); nor the consequent surface “global warming” on Mars, Jupiter, Neptune’s largest moon, and even distant Pluto; nor the eerily- continuing 2006 solar minimum; nor the consequent, precipitate decline of ~0.8 °C in TS from January 2007 to May 2008 that has canceled out almost all of the observed warming of the 20th century.

Figure 1
Mean global surface temperature anomalies (°C), 2001-2008


An early projection of the trend in TS in response to “global warming” was that of Hansen (1988), amplifying Hansen (1984) on quantification of climate sensitivity. In 1988, Hansen showed Congress a graph projecting rapid increases in TS to 2020 through “global warming” (Fig. 2):

Figure 2
Global temperature projections and outturns, 1988-2020


To what extent, then, has humankind warmed the world, and how much warmer will the world become if the current rate of increase in anthropogenic CO2 emissions continues? Estimating “climate sensitivity” – the magnitude of the change in TS after doubling CO2 concentration from the pre-industrial 278 parts per million to ~550 ppm – is the central question in the scientific debate about the climate. The official answer is given in IPCC (2007):

“It is very likely that anthropogenic greenhouse gas increases caused most of the observed increase in [TS] since the mid-20th century. … The equilibrium global average warming expected if carbon dioxide concentrations were to be sustained at 550 ppm is likely to be in the range 2-4.5 °C above pre-industrial values, with a best estimate of about 3 °C.”

Here as elsewhere the IPCC assigns a 90% confidence interval to “very likely”, rather than the customary 95% (two standard deviations). There is no good statistical basis for any such quantification, for the object to which it is applied is, in the formal sense, chaotic. The climate is “a complex, nonlinear, chaotic object” that defies long-run prediction of its future states (IPCC, 2001), unless the initial state of its millions of variables is known to a precision that is in practice unattainable, as Lorenz (1963; and see Giorgi, 2005) concluded in the celebrated paper that founded chaos theory –
“Prediction of the sufficiently distant future is impossible by any method, unless the present conditions are known exactly. In view of the inevitable inaccuracy and incompleteness of weather observations, precise, very-long-range weather forecasting would seem to be nonexistent.”  The Summary for Policymakers in IPCC (2007) says –“The CO2 radiative forcing increased by 20% in the last 10 years (1995-2005).”

Natural or anthropogenic CO2 in the atmosphere induces a “radiative forcing” ΔF, defined by IPCC (2001: ch.6.1) as a change in net (down minus up) radiant-energy flux at the tropopause in response to a perturbation. Aggregate forcing is natural (pre-1750) plus anthropogenic-era (post-1750) forcing. At 1990, aggregate forcing from CO2 concentration was ~27 W m–2 (Kiehl & Trenberth, 1997). From 1995-2005, CO2 concentration rose 5%, from 360 to 378 W m–2, with a consequent increase in aggregate forcing (from Eqn. 3 below) of ~0.26 W m–2, or <1%. That is one-twentieth of the value
stated by the IPCC. The absence of any definition of “radiative forcing” in the 2007 Summary led many to believe that the aggregate (as opposed to anthropogenic) effect of CO2 on TS had increased by 20% in 10 years. The IPCC – despite requests for correction – retained this confusing statement in its report.  Such solecisms throughout the IPCC’s assessment reports (including the insertion, after the scientists had completed their final draft, of a table in which four decimal points had been right-shifted so as to multiply tenfold the observed contribution of ice-sheets and glaciers to sea-level rise), combined with a heavy reliance upon computer models unskilled even in short-term projection, with initial values of key
variables unmeasurable and unknown, with advancement of multiple, untestable, non-Popperfalsifiable theories, with a quantitative assignment of unduly high statistical confidence levels to nonquantitative statements that are ineluctably subject to very large uncertainties, and, above all, with the now-prolonged failure of TS to rise as predicted (Figures 1, 2), raise questions about the reliability and hence policy-relevance of the IPCC’s central projections.

Dr. Rajendra Pachauri, chairman of the UN Intergovernmental Panel on Climate Change (IPCC), has recently said that the IPCC’s evaluation of climate sensitivity must now be revisited. This paper is a respectful contribution to that re-examination.

The IPCC’s method of evaluating climate sensitivity

We begin with an outline of the IPCC’s method of evaluating climate sensitivity. For clarity we will concentrate on central estimates. The IPCC defines climate sensitivity as equilibrium temperature change ΔTλ in response to all anthropogenic-era radiative forcings and consequent “temperature feedbacks” – further changes in TS that occur because TS has already changed in response to a forcing – arising in response to the doubling of pre-industrial CO2 concentration (expected later this century).  ΔTλ is, at its simplest, the product of three factors: the sum ΔF2x of all anthropogenic-era radiative forcings at CO2 doubling; the base or “no-feedbacks” climate sensitivity parameter κ; and the feedback
multiplier f, such that the final or “with-feedbacks” climate sensitivity parameter λ = κ f. Thus –

ΔTλ = ΔF2x κ f = ΔF2x λ, (1)
where f = (1 – bκ)–1, (2)

such that b is the sum of all climate-relevant temperature feedbacks. The definition of f in Eqn. (2) will be explained later. We now describe seriatim each of the three factors in ΔTλ: namely, ΔF2x, κ, and f.

1. Radiative forcing ΔFCO2, where (C/C0) is a proportionate increase in CO2 concentration, is given by several formulae in IPCC (2001, 2007). The simplest, following Myrhe (1998), is Eqn. (3) –

ΔFCO2 ≈ 5.35 ln(C/C0) ==> ΔF2xCO2 ≈ 5.35 ln 2 ≈ 3.708 W m–2. (3)

To ΔF2xCO2 is added the slightly net-negative sum of all other anthropogenic-era radiative forcings, calculated from IPCC values (Table 1), to obtain total anthropogenic-era radiative forcing ΔF2x at CO2 doubling (Eqn. 3). Note that forcings occurring in the anthropogenic era may not be anthropogenic.

Table 1
Evaluation of ΔF2x from the IPCC’s anthropogenic-era forcings


From the anthropogenic-era forcings summarized in Table 1, we obtain the first of the three factors –
ΔF2x ≈ 3.405 Wm–2. (4)

Continue to Part 2

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Climate Sensitivity Reconsidered Part 2

January 20, 2011

A special report from Christopher Monckton of Brenchley to all Climate Alarmists, Consensus Theorists and Anthropogenic Global Warming Supporters

Continues from Part 1

2. The base or “no-feedbacks” climate sensitivity parameter κ, where ΔTκ is the response of TS to radiative forcings ignoring temperature feedbacks, ΔTλ is the response of TS to feedbacks as well as forcings, and b is the sum in W m–2 °K–1 of all individual temperature feedbacks, is –

κ = ΔTκ / ΔF2x °K W–1 m2, by definition; (5)
= ΔTλ / (ΔF2x + bΔTλ) °K W–1 m2. (6)

In Eqn. (5), ΔTκ, estimated by Hansen (1984) and IPCC (2007) as 1.2-1.3 °K at CO2 doubling, is the change in surface temperature in response to a tropopausal forcing ΔF2x, ignoring any feedbacks.  ΔTκ is not directly mensurable in the atmosphere because feedbacks as well as forcings are present.  Instruments cannot distinguish between them. However, from Eqn. (2) we may substitute 1 / (1 – bκ) for f in Eqn. (1), rearranging terms to yield a useful second identity, Eqn. (6), expressing κ in terms of ΔTλ, which is mensurable, albeit with difficulty and subject to great uncertainty (McKitrick, 2007).  IPCC (2007) does not mention κ and, therefore, provides neither error-bars nor a “Level of Scientific
Understanding” (the IPCC’s subjective measure of the extent to which enough is known about a variable to render it useful in quantifying climate sensitivity). However, its implicit value κ ≈ 0.313 °K W–1 m2, shown in Eqn. 7, may be derived using Eqns. 9-10 below, showing it to be the reciprocal of the estimated “uniform-temperature” radiative cooling response–

“Under these simplifying assumptions the amplification [f] of the global warming from a feedback parameter [b] (in W m–2 °C–1) with no other feedbacks operating is 1 / (1 –[bκ –1]), where [–κ –1] is the ‘uniform temperature’ radiative cooling response (of value approximately –3.2 W m–2 °C–1; Bony et al., 2006). If n independent feedbacks operate, [b] is replaced by (λ1 + λ 2+ … λ n).” (IPCC, 2007: ch.8, footnote).

Thus, κ ≈ 3.2–1 ≈ 0.313 °K W–1 m2. (7)

3. The feedback multiplier f is a unitless variable by which the base forcing is multiplied to take account of mutually-amplified temperature feedbacks. A “temperature feedback” is a change in TS that occurs precisely because TS has already changed in response to a forcing or combination of forcings.  An instance: as the atmosphere warms in response to a forcing, the carrying capacity of the space occupied by the atmosphere for water vapor increases near-exponentially in accordance with the Clausius-Clapeyron relation. Since water vapor is the most important greenhouse gas, the growth in its
concentration caused by atmospheric warming exerts an additional forcing, causing temperature to rise further. This is the “water-vapor feedback”. Some 20 temperature feedbacks have been described, though none can be directly measured. Most have little impact on temperature. The value of each feedback, the interactions between feedbacks and forcings, and the interactions between feedbacks and other feedbacks, are subject to very large uncertainties.

Each feedback, having been triggered by a change in atmospheric temperature, itself causes a temperature change. Consequently, temperature feedbacks amplify one another. IPCC (2007: ch.8) defines f in terms of a form of the feedback-amplification function for electronic circuits given in Bode (1945), where b is the sum of all individual feedbacks before they are mutually amplified:

f = (1 – bκ)–1 (8)
= ΔTλ / ΔTκ

Note the dependence of f not only upon the feedback-sum b but also upon κ –

ΔTλ = (ΔF + bΔTλ)κ
==> ΔTλ (1 – bκ) = ΔFκ
==> ΔTλ = ΔFκ(1 – bκ)–1
==> ΔTλ / ΔF = λ = κ(1 – bκ)–1 = κf
==> f = (1 – bκ)–1 ≈ (1 – b / 3.2)–1
==> κ ≈ 3.2–1 ≈ 0.313 °K W–1 m2. (9)

Equivalently, expressing the feedback loop as the sum of an infinite series,

ΔTλ = ΔFκ + ΔFκ 2b + ΔFκ 2b2 + …
= ΔFκ(1 + κb + κb2 + …)
= ΔFκ(1 – κb)–1
= ΔFκf
==> λ = ΔTλ /ΔF = κf (10)

Figure 3
Bode (1945) feedback amplification schematic


For the first time, IPCC (2007) quantifies the key individual temperature feedbacks summing to b:
“In AOGCMs, the water vapor feedback constitutes by far the strongest feedback, with a multi-model mean and standard deviation … of 1.80 ± 0.18 W m–2 K–1, followed by the negative lapse rate feedback (–0.84 ± 0.26 W m–2 K–1) and the surface albedo feedback (0.26 ± 0.08 W m–2 K–1). The cloud feedback mean is 0.69 W m–2 K–1 with a very large inter-model spread of ±0.38 W m–2K–1.” (Soden & Held, 2006).

To these we add the CO2 feedback, which IPCC (2007, ch.7) separately expresses not as W m–2 °K–1 but as concentration increase per CO2 doubling: [25, 225] ppmv, central estimate q = 87 ppmv. Where p is concentration at first doubling, the proportionate increase in atmospheric CO2 concentration from the CO2 feedback is o = (p + q) / p = (556 + 87) / 556 ≈ 1.16. Then the CO2 feedback is –λCO2 = z ln(o) / dTλ ≈ 5.35 ln(1.16) / 3.2 ≈ 0.25 Wm–2 K–1. (11) The CO2 feedback is added to the previously-itemized feedbacks to complete the feedback-sum b:

b = 1.8 – 0.84 + 0.26 + 0.69 + 0.25 ≈ 2.16 Wm–2 ºK–1, (12)

so that, where κ = 0.313, the IPCC’s unstated central estimate of the value of the feedback factor f is at the lower end of the range f = 3-4 suggested in Hansen et al. (1984) –

f = (1 – bκ)–1 ≈ (1 – 2.16 x 0.313)–1 ≈ 3.077. (13)

Final climate sensitivity ΔTλ, after taking account of temperature feedbacks as well as the forcings that triggered them, is simply the product of the three factors described in Eqn. (1), each of which we have briefly described above. Thus, at CO2 doubling, –

ΔTλ = ΔF2x κ f ≈ 3.405 x 0.313 x 3.077 ≈ 3.28 °K (14)

IPCC (2007) gives dTλ on [2.0, 4.5] ºK at CO2 doubling, central estimate dTλ ≈ 3.26 °K, demonstrating that the IPCC’s method has been faithfully replicated. There is a further checksum, –

ΔTκ = ΔTλ / f = κ ΔF2x = 0.313 x 3.405 ≈ 1.1 °K, (15)

sufficiently close to the IPCC’s estimate ΔTκ ≈ 1.2 °K, based on Hansen (1984), who had estimated a range 1.2-1.3 °K based on his then estimate that the radiative forcing ΔF2xCO2 arising from a CO2 doubling would amount to 4.8 W m–2, whereas the IPCC’s current estimate is ΔF2xCO2 = 3.71 W m–2 (see Eqn. 2), requiring a commensurate reduction in ΔTκ that the IPCC has not made.  A final checksum is provided by Eqn. (5), giving a value identical to that of the IPCC at Eqn (7):

κ = ΔTλ / (ΔF2x + bΔTλ)
≈ 3.28 / (3.405 + 2.16 x 3.28)
≈ 0.313 °K W–1 m2. (16)

Having outlined the IPCC’s methodology, we proceed to re-evaluate each of the three factors in dTλ.  None of these three factors is directly mensurable. For this and other reasons, it is not possible to obtain climate sensitivity numerically using general-circulation models: for, as Akasofu (2008) has pointed out, climate sensitivity must be an input to any such model, not an output from it.  In attempting a re-evaluation of climate sensitivity, we shall face the large uncertainties inherent in the climate object, whose complexity, non-linearity, and chaoticity present formidable initial-value and boundary-value problems. We cannot measure total radiative forcing, with or without temperature feedbacks, because radiative and non-radiative atmospheric transfer processes combined with seasonal, latitudinal, and altitudinal variabilities defeat all attempts at reliable measurement. We cannot even measure changes in TS to within a factor of two (McKitrick, 2007).

Even satellite-based efforts at assessing total energy-flux imbalance for the whole Earth-troposphere system are uncertain. Worse, not one of the individual forcings or feedbacks whose magnitude is essential to an accurate evaluation of climate sensitivity is mensurable directly, because we cannot distinguish individual forcings or feedbacks one from another in the real atmosphere, we can only guess at the interactions between them, and we cannot even measure the relative contributions of all forcings and of all feedbacks to total radiative forcing. Therefore we shall adopt two approaches:
theoretical demonstration (where possible); and empirical comparison of certain outputs from the models with observation to identify any significant inconsistencies.

Radiative forcing ΔF2x reconsidered

We take the second approach with ΔF2x. Since we cannot measure any individual forcing directly in the atmosphere, the models draw upon results of laboratory experiments in passing sunlight through chambers in which atmospheric constituents are artificially varied; such experiments are, however, of limited value when translated into the real atmosphere, where radiative transfers and non-radiative transports (convection and evaporation up, advection along, subsidence and precipitation down), as well as altitudinal and latitudinal asymmetries, greatly complicate the picture. Using these laboratory values, the models attempt to produce latitude-versus-altitude plots to display the characteristic
signature of each type of forcing. The signature or fingerprint of anthropogenic greenhouse-gas forcing, as predicted by the models on which the IPCC relies, is distinct from that of any other forcing, in that the models project that the rate of change in temperature in the tropical mid-troposphere – the region some 6-10 km above the surface – will be twice or thrice the rate of change at the surface (Figure 4):

Figure 4
Temperature fingerprints of five forcings Modeled zonal


The fingerprint of anthropogenic greenhouse-gas forcing is a distinctive “hot-spot” in the tropical midtroposphere.
Figure 4 shows altitude-vs.-latitude plots from four of the IPCC’s models:

Figure 5
Fingerprints of anthropogenic warming projected by four models


However, as Douglass et al. (2004) and Douglass et al. (2007) have demonstrated, the projected
fingerprint of anthropogenic greenhouse-gas warming in the tropical mid-troposphere is not observed
in reality. Figure 6 is a plot of observed tropospheric rates of temperature change from the Hadley
Center for Forecasting. In the tropical mid-troposphere, at approximately 300 hPa pressure, the model projected
fingerprint of anthropogenic greenhouse warming is absent from this and all other observed
records of temperature changes in the satellite and radiosonde eras:

Continue to Part 3

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Climate Sensitivity Reconsidered Part 3

January 20, 2011

A special report from Christopher Monckton of Brenchley to all Climate Alarmists, Consensus Theorists and Anthropogenic Global Warming Supporters

Continues from Part 2

Figure 6
The absent fingerprint of anthropogenic greenhouse warming


None of the temperature datasets for the tropical surface and mid-troposphere shows the strong differential warming rate predicted by the IPCC’s models. Thorne et al. (2007) suggested that the absence of the mid-tropospheric warming might be attributable to uncertainties in the observed record: however, Douglass et al. (2007) responded with a detailed statistical analysis demonstrating that the absence of the projected degree of warming is significant in all observational datasets.  Allen et al. (2008) used upper-atmosphere wind speeds as a proxy for temperature and concluded that
the projected greater rate of warming at altitude in the tropics is occurring in reality. However, satellite records, such as the RSS temperature trends at varying altitudes, agree with the radiosondes that the warming differential is not occurring: they show that not only absolute temperatures but also warming rates decline with altitude.  There are two principal reasons why the models appear to be misrepresenting the tropical atmosphere so starkly. First, the concentration of water vapor in the tropical lower troposphere is already so great that there is little scope for additional greenhouse-gas forcing. Secondly, though the models assume that the concentration of water vapor will increase in the tropical mid-troposphere as the space occupied by the atmosphere warms, advection transports much of the additional water vapor poleward
from the tropics at that altitude.

Since the great majority of the incoming solar radiation incident upon the Earth strikes the tropics, any reduction in tropical radiative forcing has a disproportionate effect on mean global forcings. On the basis of Lindzen (2007), the anthropogenic-ear radiative forcing as established in Eqn. (3) are divided by 3 to take account of the observed failure of the tropical mid-troposphere to warm as projected by the models –

ΔF2x ≈ 3.405 / 3 ≈ 1.135 Wm–2. (17)

The “no-feedbacks” climate sensitivity parameter κ reconsidered The base climate sensitivity parameter κ is the most influential of the three factors of ΔTλ: for the final or “with-feedbacks” climate sensitivity parameter λ is the product of κ and the feedback factor f, which is itself dependent not only on the sum b of all climate-relevant temperature feedbacks but also on κ.  Yet κ has received limited attention in the literature. In IPCC (2001, 2007) it is not mentioned.
However, its value may be deduced from hints in the IPCC’s reports. IPCC (2001, ch. 6.1) says:

“The climate sensitivity parameter (global mean surface temperature response ΔTS to the radiative forcing
ΔF) is defined as ΔTS / ΔF = λ {6.1} (Dickinson, 1982; WMO, 1986; Cess et al., 1993). Equation {6.1} is defined for the transition of the surface-troposphere system from one equilibrium state to another in response to an externally imposed radiative perturbation. In the one-dimensional radiative-convective models, wherein the concept was first initiated, λ is a nearly invariant parameter (typically, about 0.5 °K W−1 m2; Ramanathan et al., 1985) for a variety of radiative forcings, thus introducing the notion of a possible universality of the relationship between forcing and response.”

Since λ = κf = κ(1 – bκ)–1 (Eqns. 1, 2), where λ = 0.5 °K W–1 m2 and b ≈ 2.16 W m–2 °K–1 (Eqn. 12), it is simple to calculate that, in 2001, one of the IPCC’s values for f was 2.08. Thus the value f = 3.077 in IPCC (2007) represents a near-50% increase in the value of f in only five years. Where f = 2.08, κ = λ / f ≈ 0.5 / 2.08 ≈ 0.24 °K W–1 m2, again substantially lower than the value implicit in IPCC (2007).

Some theory will, therefore, be needed.

The fundamental equation of radiative transfer at the emitting surface of an astronomical body, relating changes in radiant-energy flux to changes in temperature, is the Stefan-Boltzmann equation – F = ε σ T4 W m–2, (18)
where F is radiant-energy flux at the emitting surface; ε is emissivity, set at 1 for a blackbody that absorbs and emits all irradiance reaching its emitting surface (by Kirchhoff’s law of radiative transfer, absorption and emission are equal and simultaneous), 0 for a white body that reflects all irradiance, and (0, 1) for a graybody that partly absorbs/emits and partly reflects; and σ ≈ 5.67 x 10–8 is the Stefan-Boltzmann constant.  Differentiating Eqn. (18) gives –

κ = dT / dF = (dF / dT)–1 = (4 ε σ T3)–1 °K W–1 m2. (19) Outgoing radiation from the Earth’s surface is chiefly in the near-infrared. Its peak wavelength λmax is determined solely by the temperature of the emitting surface in accordance with Wien’s Displacement Law, shown in its simplest form in Eqn. (20):

λmax = 2897 / TS = 2897 / 288 ≈ 10 μm. (20)

Since the Earth/troposphere system is a blackbody with respect to the infrared radiation that Eqn. (20) shows we are chiefly concerned with, we will not introduce any significant error if ε = 1, giving the blackbody form of Eqn. (19) –

κ = dT / dF = (4 σ T3)–1 °K W–1 m2. (21)

At the Earth’s surface, TS ≈ 288 °K, so that κS ≈ 0.185 °K W–1 m2. At the characteristic-emission level, ZC, the variable altitude at which incoming and outgoing radiative fluxes balance, TC ≈ 254 °K, so that κC ≈ 0.269 °K W–1 m2. The value κC ≈ 0.24, derived from the typical final-sensitivity value λ = 0.5 given in IPCC (2001), falls between the surface and characteristic-emission values for κ.

However, the IPCC, in its evaluation of κ, does not follow the rule that in the Stefan-Boltzmann equation the temperature and radiant-energy flux must be taken at the same level of the atmosphere.  The IPCC’s value for κ is dependent upon temperature at the surface and radiant-energy flux at the tropopause, so that its implicit value κ ≈ 0.313 °K W–1 m2 is considerably higher than either κS or κC.  IPCC (2007) cites Hansen et al. (1984), who say –

“Our three-dimensional global climate model yields a warming of ~4 ºC for … doubled CO2. This indicates a net feedback factor f = 3-4, because [the forcing at CO2 doubling] would cause the earth’s surface temperature to warm 1.2-1.3 ºC to restore radiative balance with space, if other factors remained unchanged.”

Hansen says dF2x is equivalent to a 2% increase in incoming total solar irradiance (TSI). Top-ofatmosphere
TSI S ≈ 1368 W m2, albedo α = 0.31, and Earth’s radius is r. Then, at the characteristic
emission level ZC,

FC = S(1 – α)(πr2 / 4πr2) ≈ 1368 x 0.69 x (1/4) ≈ 236 Wm–2. (22)

Thus a 2% increase in FC is equivalent to 4.72 W m–2, rounded up by Hansen to 4.8 W m–2, implying that κ ≈ 1.25 / 4.8 ≈ 0.260 °K W–1 m2. However, Hansen, in his Eqn. {14}, prefers 0.29 Wm–2.  Bony et al. (2006), also cited by IPCC (2007), do not state a value for κ. However, they say – “The Planck feedback parameter [equivalent to κ –1] is negative (an increase in temperature enhances the long-wave emission to space and thus reduces R [the Earth’s radiation budget]), and its typical value for the earth’s atmosphere, estimated from GCM calculations (Colman 2003; Soden and Held 2006), is ~3.2 W m2 ºK–1 (a value of ~3.8 W m2 ºK–1 is obtained by defining [κ –1] simply as 4σT3, by equating the global
mean outgoing long-wave radiation to σT4 and by assuming an emission temperature of 255 ºK).” Bony takes TC ≈ 255 °K and FC ≈ 235 W m–2 at ZC as the theoretical basis for the stated prima facie value κ –1 ≈ TC / 4FC ≈ 3.8 W m2 ºK–1, so that κ ≈ 0.263 ºK W–1 m2, in very close agreement with Hansen. However, Bony cites two further papers, Colman (2003) and Soden & Held (2006), as justification for the value κ –1 ≈ 3.2 W m2 ºK–1, so that κ ≈ 0.313 ºK W–1 m2.  Colman (2003) does not state a value for κ, but cites Hansen et al. (1984), rounding up the value κ ≈ 0.260 °K W–1 m2 to 0.3 °K W–1 m2 – “The method used assumes a surface temperature increase of 1.2 °K with only the CO2 forcing and the
‘surface temperature’ feedback operating (value originally taken from Hansen et al. 1984).”

Soden & Held (2006) likewise do not declare a value for κ. However, we may deduce their implicit central estimate κ ≈ 1 / 4 ≈ 0.250 °K W–1 m2 from the following passage – “The increase in opacity due to a doubling of CO2 causes [the characteristic emission level ZC] to rise by ~150 meters. This results in a reduction in the effective temperature of the emission across the tropopause by ~(6.5K/km)(150 m) ≈ 1 K, which converts to 4 W m–2 using the Stefan-Boltzmann law.”  Thus the IPCC cites only two papers that cite two others in turn. None of these papers provides any theoretical or empirical justification for a value as high as the κ ≈ 0.313 °K W–1 m2 chosen by the IPCC.

Kiehl (1992) gives the following method, where FC is total flux at ZC:

κS = TS / (4FC) ≈ 288 / (4 x 236) ≈ 0.305 °K W–1 m2. (23)

Hartmann (1994) echoes Kiehl’s method, generalizing it to any level J of an n-level troposphere thus:

κJ = TJ / (4FC)
= TJ / [S(1 – α)]
≈ TJ / [1368(1 – 0.31)] ≈ TJ / 944 °K W–1 m2. (24)

Table 2 summarizes the values of κ evident in the cited literature, with their derivations, minores priores. The greatest value, chosen in IPCC (2007), is 30% above the least, chosen in IPCC (2001).  However, because the feedback factor f depends not only upon the feedback-sum b ≈ 2.16 W m–2 °K–1  but also upon κ, the 30% increase in κ nearly doubles final climate sensitivity:

Table 2
Values of the “no-feedbacks” climate sensitivity parameter κ


The value of κ cannot be deduced by observation, because temperature feedbacks are present and cannot be separately measured. However, it is possible to calculate κ using Eqn. (6), provided that the temperature change ΔTλ, radiative forcings ΔF2x, and feedback-sum b over a given period are known.  The years 1980 and 2005 will be compared, giving a spread of a quarter of a century. We take the feedback-sum b = 2.16 W m–2 °K–1 and begin by establishing values for ΔF and ΔT:  CO2 concentration: 338.67 ppmv 378.77 ppmv ΔF = 5.35 ln (378.77/338.67) = 0.560 W m–2 Anomaly in TS: 0.144 °K 0.557 °K ΔT = 0.412 °K (NCDC) Anomaly halved: ΔT = 0.206 °K (McKitrick) (25) CO2 concentrations are the annual means from 100 stations (Keeling & Whorf, 2004, updated). TS values are NCDC annual anomalies, as five-year means centered on 1980 and 2005 respectively. Now, depending on whether the NCDC or implicit McKitrick value is correct, κ may be directly evaluated:

NCDC: κ = ΔT / (ΔF + bΔT) = 0.412 / (0.560 + 2.16 x 0.412) = 0.284 °KW–1 m2
McKitrick: κ = ΔT / (ΔF + bΔT) = 0.206 / (0.599 + 2.16 x 0.206) = 0.197 °KW–1 m2
Mean: κ = (0.284 + 0.197) / 2 = 0.241 °KW–1 m2 (26)

We assume that Chylek (2008) is right to find transient and equilibrium climate sensitivity near identical; that all of the warming from 1980-2005 was anthropogenic; that the IPCC’s values for forcings and feedbacks are correct; and, in line 2, that McKitrick is right that the insufficiently corrected heat-island effect of rapid urbanization since 1980 has artificially doubled the true rate of temperature increase in the major global datasets.

With these assumptions, κ is shown to be less, and perhaps considerably less, than the value implicit in IPCC (2007). The method of finding κ shown in Eqn. (24), which yields a value very close to that of IPCC (2007), is such that progressively smaller forcing increments would deliver progressively larger temperature increases at all levels of the atmosphere, contrary to the laws of thermodynamics and to the Stefan-Boltzmann radiative-transfer equation (Eqn. 18), which mandate the opposite. It is accordingly necessary to select a value for κ that falls well below the IPCC’s value. Dr. David Evans (personal communication, 2007) has calculated that the characteristic-emission-level value of κ should be diminished by ~10% to allow for the non-uniform latitudinal distribution of incoming solar radiation, giving a value near-identical to that in Eqn. (26), and to that implicit in IPCC (2001), thus –

κ = 0.9TC / [S(1 – α)]
≈ 0.9 x 254 / [1368(1 – 0.31)] ≈ 0.242 °K W–1 m2 (27)

The feedback factor f reconsidered

The feedback factor f accounts for two-thirds of all radiative forcing in IPCC (2007); yet it is not expressly quantified, and no “Level Of Scientific Understanding” is assigned either to f or to the two variables b and κ upon which it is dependent.
Several further difficulties are apparent. Not the least is that, if the upper estimates of each of the climate-relevant feedbacks listed in IPCC (2007) are summed, an instability arises. The maxima are –

Water vapor feedback 1.98 W m–2 K–1
Lapse rate feedback –0.58 W m–2 K–1
Surface albedo feedback 0.34 W m–2 K–1
Cloud albedo feedback 1.07 W m–2 K–1
CO2 feedback 0.57 W m–2 K–1
Total feedbacks b 3.38 Wm–2 K–1 (28)

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