A Comparison Of The Earth's Climate Sensitivity To Changes In The Nature Of The Initial Forcing

Guest post by Bob Irvine

ABSTRACT

The Earth’s feedback response to warming is independent of the nature of the forcing that caused that warming. The question I intend to examine is whether the nature of the forcing will have a significant impact on the initial warming or the response time of the earth’s system. I looked at changes in three different types of forcing and their effect on the earth’s temperature response.

1. Changes in solar forcing caused by variation in solar output at the sun’s surface that may cause changes in Cosmic Ray flux or other solar multiplier effects.

2. Changes in solar forcing caused by changes in the earth’s milankovitch cycles (Last Glacial Maxima, LGM) and volcanic activity that do not affect cosmic ray flux.

3. Changes in Anthropogenic Green House Gas (AGHG) concentrations.

The IPCC and others assume that climate sensitivity derived from #2 (Last Glacial Maxima, or Milankovitch cycles and volcanic activity) also applies to #1 and #3. This paper attempts to show that this is unlikely to be the case when the best available data is compared.

For #1 we found the climate sensitivity to be between 1.0°C and 1.8°C per Watt per Square meter of forcing. For #2 we found climate sensitivity to be approximately between 0.4°C and 1.2°C per W/M² and for #3 we found climate sensitivity to be between 0.1°C and 0.36°C per W/M².

INTRODUCTION

Climate sensitivity is the temperature increase at equilibrium for each Watt per square meter of forcing or “X” in the following equation. X°C/WM^-2 .

Generally as the planet warms it activates various feedbacks. A negative feedback will decrease the earth’s system response time at the top of the atmosphere and a positive feedback will increase this response time. For example, a decrease in sea ice will slow the return of energy to space and can, therefore, be considered a positive feedback to warming.

Not all feedback’s, however, are a response to warming. For example, if the cosmic ray effect is real then it can be considered a positive feedback to increased solar activity that is not related to warming. Similarly different types of forcing can have different response times at the top of the atmosphere. I intend to show in this paper that changes in long wave GHG forcing have a considerably shorter response time than changes in short wave solar forcing and, therefore, can be expected to have a lower climate sensitivity.

I, therefore, intend to show that the IPCC’s climate sensitivity based on #2 above should not be applied to AGHGs.

I have used the IPCC’s climate sensitivity derived from #2 above to calculate the current equilibrium temperature due to AGHG’s already in the system and compared this with the NOAA actual temperature since 1880 in Fig. 1. The calculations done to produce the graph below are set out in Appendix “1”.

Basically the IPCC’s agreed CO2 concentrations were used to calculate expected equilibrium temperature which was adjusted using the IPCC’s 3^rd and 4^th assessment reports figures to include all AGHG’s (i.e. NO2, CH4, Halogens etc.). All calculations used to produce this graph (fig. 1) are generally agreed and accepted and used by the IPCC.

The inconsistency of the IPCC central prediction and upper limit with the actual data (blue line) is immediately apparent. It is possible that the lower IPCC limit might be compatible but even this becomes untenable when climate sensitivity to changes in Total Solar Irradiance (TSI) which include any solar multiplier effects, #1, is taken into account. This sensitivity, #1, will be estimated in section “A” below. Section “B” will show how the IPCC derived their climate sensitivity for #2 above.

The IPCC’s position is that industrial aerosols have artificially cooled the planet masking the warming effects of the AGHGs and that equilibrium temperature is approximately 1.5 times transient or current temperature. Section “C” will show that even these are not enough to avoid the conclusion that climate sensitivity due to changes in AGHGs, #3, is considerably smaller than both #1 and #2.

Fig. 1 AGHG Forced equilibrium temperature using the IPCC’s sensitivity based on #2 (LGM and volcanic) and compared to actual temperature as measured by the NOAA since 1880. The upper IPCC limit assumes a climate sensitivity of “X” = 1.2, the IPCC central prediction assumes “X” = 0.8, and the lower IPCC limit assumes “X” = 0.4.

#1. SECTION A We used two methods to match TSI (Total Solar Irradiance) changes as Watts/Square meter at the earth’s surface with the best temperature data available. These TSI changes will affect the cosmic ray flux and possibly have other solar multiplier effects as they are caused by changes in solar activity at the sun’s surface.

If these changes in TSI lead to greater temperature changes per unit forcing than solar changes that do not result in changes in the cosmic ray flux, such as Milankovitch cycles or volcanic activity, then this would lend some credence to theories suggesting that cosmic rays have a significant effect on the earth’s surface temperature.

The two methods we will use are a) compare solar irradiance changes over the last millennium with temperature records, and b) compare temperature and forcing for the 11 year sun cycle.

a) The TSI variations are taken from Swingedouw et al (2011) who used the Bard et al (2000) reconstruction and are the same as those used by Crowley (2000). The scaling used is from Lean et al (1995). Lean et al (2002) and Foukal et al (2004) suggest that long term irradiance changes could be considerably less which would imply a higher temperature sensitivity to a given forcing.

Fig. 2, W/M² at the earth’s surface due to changes in Solar activity for the last millennium.

Fig. 3, Solar activity for the last 1100 years.

I have used the temperature reconstructions of Mann 2008 EIV, Moberg 2005, Loehle 2008 and Ljungqvist 2010 to represent temperature change over the last millennium. They are, I believe, the best available series at the time of writing. These temperature reconstructions are reproduced in Appendix “2”. An approximation of the range of temperature over this period is then compared with the range in solar forcing at the earth’s surface.

With considerable uncertainties, this comparison will give us an approximation of the climate’s sensitivity to changes in solar forcing at the earth’s surface that include any cosmic ray effect and/or other solar multiplier effects .

Fig. 4, Maximum and minimum temperatures for 4 different temperature reconstructions over the last 1500 years. The warmest three decades and the coolest three decades from each reconstruction are shown.

From fig 2 and fig 3 the range in solar forcing at the earth’s surface over the last 1000 years excluding the 20^th century is approximately 0.6 w/m².

From fig 4 the range in temperature in each of the four reconstructions can be seen. It is then possible to calculate “X” where X is the change in the earth’s surface temperature in degrees Celsius that results from a one w/m² change in forcing.

From Fig 4 the range in temperature for Mann 2008 EIV is approximately 0.75°C, for Moberg 2005 is approximately 0.9°C, for Loehle 2008 is approximately 1.1°C and for Ljungqvist 2010 is approximately 0.9°C.

Climate sensitivity is described by the equation X°Celcius / wm^-2. .

The value of “X” will change, with time from equilibrium, and with any other changes in the earth’s feedback systems etc. For the purposes of this paper, however, “X” will be considered to be linear for a given forcing. This paper is considering the possibility that “X” will change considerably depending on the nature of the forcing that drives any change.

The value of “X” is then derived for each of the four different temperature reconstructions.

For Mann 2008 “X” equals 1.25 (0.75/0.6)

For Moberg 2005 “X” equals 1.5 (0.9/0.6)

For Loehle 2008 “X” equals 1.8 (1.1/0.6)

For Ljungqvist 2010 “X” equals 1.5 (0.9/0.6)

These values of “X” should approximate the equilibrium response since the data is taken over a millennium or more. There are considerable uncertainties in these estimates of climate sensitivity that derive from the max/min method used and the error margins of the various temperature reconstructions used.

It is worth noting that if the max/min method used overstates the temperature response then it is also likely that max/min method also overstates the solar forcing at the earth’s surface causing some of the possible error to be cancelled.

It is beyond the scope of this paper to estimate these uncertainties other than to say that the climate sensitivity, as calculated from current knowledge by this method, probably lies in the range 1.25°C/wm^-2 and 1.8°C/wm^-2.

b) The 11 year solar cycle will also include changes in cosmic ray flux as it too results from changes in solar output at the sun’s surface.

Camp and Tung (2008) use the 11 year sun cycle to derive transient sensitivity of between 0.69 and 0.97°C/wm^-2. They also estimate equilibrium temperature as being 1.5 times higher than this which is consistent with the IPCC’s position in their 4AR.

This gives an “X” value for climate sensitivity calculated by this method of between 1.04°C/wm^-2 and 1.46°C/wm^-2

Combining a) and b) we get the likelihood that climate sensitivity for TSI changes that include changes in cosmic ray flux and/or any other solar multiplier effect will probably lie between 1.0°C/wm^-2 and 1.8°C/wm^-2.

#2. SECTION B The second type of forcing is one that causes changes in solar energy reaching the earth without effecting cosmic ray flux. These include the Milankovitch cycles and volcanic activity that occur at the earth’s surface and, therefore, are not due to changes in TSI at the sun’s surface.

Annan and Hargreaves (2006) looks at climate sensitivity derived from observation of volcanic activity and the Last Glacial Maxima (LGM).

They studied the literature and concluded that volcanic activity indicates that climate sensitivity would be between 1.5°C and 6°C for a forcing of 3.7w/m² at equilibrium with the upper limit constrained to 4.5°C after the 20^th century temperature record and evidence from the Maunder minimum are considered.

Volcanic activity, therefore, gives a climate sensitivity of between 0.4(1.5/3.7)°C/wm^-2 and 1.2(4.5/3.7)°C/wm^-2 to 95% confidence.

A & H (2006), after studying the literature, concluded that LGM measurements support a climate sensitivity between 1.3°C and 4.5°C for a 3.7w/m² forcing to 95% confidence. The upper limit was constrained for the reasons outlined above.

This gives a value for “X” between 0.4 and 1.2 derived from evidence taken from both volcanic activity and the LGM. This agrees closely with the IPCC’s position outlined in all of their assessment reports.

Fig. 5, IPCCs Forcing’s bar graph from their 2007 4AR. Note the large aerosol cooling effect they expect for 2005. Minimum -0.4w/m², Likely -1.2w/m², Maximum -2.4w/m². Note also the large AGHG Forcing of approximately 2.7 w/m² which at their central sensitivity of “X” = 0.8 should give an equilibrium temperature increase in 2005 of 2.16°C. This is not consistent with actual temperature rise as seen in Fig. 1.

That Milankovich Cycles are overwhelmingly the main drivers of the ice ages, and more particularly the LGM used by A & H (2006) to estimate their climate sensitivity, is shown convincingly by Roe (2006) “In Defence of Milankovich”.

#3. SECTION C Since 1880 an extremely active sun has added directly, approximately 0.5w/m² at the earth’s surface (Fig. 2). According to our best historical temperature series as seen in section A and after an adjustment to give transient temperature, this active sun should have increased the earth’s temperature by a minimum of approximately 0.33°C to a maximum of 0.6°C since 1880.

According to the NOAA in Fig. 1 the earth’s temperature has risen by about 0.7°C since 1880.

This leaves between 0.1 and 0.37°C plus any industrial aerosol cooling effect to be explained by increasing AGHGs.

This can be summarised by the following equation;

Equation 1; “Y” plus (0.1 to 0.37) = “Z” Where “Y” is the net aerosol cooling in 2010 and “Z” is the total transient warming due to AGHGs in 2010.

At this point we introduce another check on aerosols to get a second simultaneous equation. According to Stern (2006) industrial aerosol production has fallen by over 30% since 1990, Fig. 6. Mishchenko confirms this with satellite measurements showing a drop in sun blocking aerosols since 1990, Fig. 7. Basically, If an increase in industrial aerosols gives a significant cooling as postulated by the IPCC then a drop in aerosols, as has happened since 1990, should cause a significant warming. Here is a supporting quote from the IPCC’s 4AR. “Global sulphur emissions (and thus sulphate aerosol forcing) appear to have decreased after 1980 (Stern 2005)…”

This drop in industrial aerosols can be explained by cleaner combustion techniques forced on people by acid rain and other undesirable environmental effects.

There are other contributors to the earth’s temperature other than Industrial aerosols, AGHGs, and solar, but they are negligible in the context of this paper.

To form a second simultaneous equation we need an estimate of AGHG forcing and an estimate of temperature change since 1990.

Fig. 6 Estimated global SO2 production. Stern 2006

Fig. 7.

The temperature series, Fig. 8, below gives a temperature rise between 1990 and 2010 of approximately 0.2°C. It is uncertain whether natural forcing’s would have increased or decreased this figure so we have approximated this figure to a rise of between 0.1°C and 0.3°C which is an estimate of the anthropogenic temperature change since 1990. The effect of the Mt. Pinatubo eruption in 1991 has also been removed.

Fig. 8 Earth’s temperature 1990 to 2010 according four main temperature series.

AGHGs added 0.82 w/m² from 1990 to 2010, based on their increase in concentration, which is 28% of the total forcing, attributed to AGHGs in 2010 by the IPCC.

We can now create a second simultaneous equation;

Equation 2; 0.3 x “Y” Plus 0.28 X “Z” = 0.1 to 0.3

Solving for the simultaneous equations 1 and 2 gives total aerosol cooling of between 0.12°C and 0.34°C in 2010 (“Y”). This implies total AGHG forced transient warming in 2010 (“Z”) of between 0.22°C and 0.69°C.

If we assume equilibrium temperature is approximately 1.5 times transient temperature and use the IPCC’s total forcing of 2.9 w/m² we arrive at an AGHG climate sensitivity of;

“X” = 0.11°C/wm^-2 to “X” = 0.36°C/wm^-2.

CONCLUSION

To my mind the IPCC’s upper limit and central prediction are not consistent with the NOAA actual temperatures in Fig. 1. If our best temperature series over the last 1000 years are to be believed then the IPCC lower limit in Fig. 1 can also not be reconciled with the actual measured temperatures as has been demonstrated in section A, B and C above.

The IPCC would put 4 possible arguments to explain the discrepancies apparent in Fig. 1.

1. That equilibrium temperature is considerably more than 1.5 times transient temperature which would overturn nearly all the literature on the subject and be inconsistent with all the IPCC’s model assumptions.

2. That industrial aerosols have a massive cooling affect which would be inconsistent with evidence since 1990 (see section C above). They would also need to explain the fact that industrial aerosols generally remain local and are overwhelmingly produced in the northern hemisphere. The northern hemisphere has experienced more warming over the last century than the southern hemisphere.

3. That AGHG sensitivity is not linear. It is initially lower and increases to their published sensitivity at doubling. It is therefore unlikely but possible that the IPCC’s lower limit of “X” = 0.4 could be consistent with the upper limit for AGHGs of “X” = 0.36. This would imply a much larger cosmic ray or other solar multiplier effect (minimum “X” = 1.0, see section A above) than is generally accepted.

4. That temperature measurements over the last millennium are so uncertain that no conclusions can be drawn from them. These are the best series (see appendix 2) that we have. The existence of the medieval warm period and the little ice age have been confirmed by many studies around the world and are not seriously challenged anymore. It can be safely stated that the IPCC’s estimated climate sensitivity range can be falsified by the best evidence that we have at the time of writing.

The IPCC’s position is that climate sensitivity measurements deduced from the LGM and volcanic activity that do not include any solar multiplier effect and are based on short wave solar radiation can be assumed to apply to Long Wave Radiation from AGHGs and changes in TSI at the sun’s surface that include possible solar multiplier effects.

This paper proposes that the IPCC’s position is not consistent with our best millennial temperature records nor is it consistent with Green House Gas Forcing and temperature rise in the 20^th century (Fig. 1) without unrealistically large aerosol cooling. The IPCC’s position is particularly inconsistent when it is noted that aerosol levels have fallen over the last 20 years at a time when temperature rise has abated.

All the available data is neatly reconciled and consistent if we are prepared to accept that the earth’s climate sensitivity is different for long wave greenhouse gas forcing than it is for short wave solar forcing. It is, in fact, unlikely that these two would have the same sensitivity and there are good physical reasons why they wouldn’t.

PHYSICAL EVIDENCE

1. The existence of a cosmic ray effect on temperature has been debated for some time now and would explain the different sensitivities described in section “A” and section “B”. This is discussed in Shaviv 2005, “On Climate Response to Change in Cosmic Ray Flux and Radiative Budget.” Certainly the existence of some form of solar multiplier is supported by the evidence of the last millennium (section “A”) when it is compared with the IPCC’s sensitivity (section “B”). The IPCC’s climate sensitivity is derived from LGM and volcanic measurements that don’t include any solar multiplier effects as they are caused by changes at the earth’s surface as opposed to changes at the sun’s surface.

2. The climate response time is the time it takes for the atmosphere to respond to a change in forcing and is dependent on sensitivity and the amount of ocean mixing. Hansen, Sato and Kharecha, “Earth’s Energy Imbalance and Implications”, say “On a planet with no ocean or only a mixed layer ocean, the climate response time is proportional to climate sensitivity. ………..Hansen et al (1985) show analytically, with ocean mixing approximated as a diffusive process, that the response time increases as the square of climate sensitivity.”

If it can be shown that a change in the Long Wave Radiation from AGHGs has a shorter response time than a change in Short Wave Solar Radiation, then this would imply a lower climate sensitivity for changes in AGHGs than you would expect from changes in solar forcing.

It is well known and accepted physics that Long wave radiation from GHGs only penetrates the oceans to a depth of a fraction of a millimetre. Water is almost totally opaque to these wavelengths. Short wave solar radiation, on the other hand, penetrates water to a depth of 10 meters or more and is, therefore, readily involved in ocean heating.

There is clearly a significant difference in response times between Long wave radiation from AGHGs and the Short wave solar radiation used by the IPCC to calculate their sensitivity. Long wave radiation is returned almost immediately to the atmosphere while Short wave solar radiation is largely absorbed by the ocean and takes much longer to find its way back to the atmosphere on average.

It is entirely logical that shorter response times would equate to lower temperature sensitivities at equilibrium. There would quite obviously be less energy in the pipeline as the oceans are not warmed significantly by AGHG’s.

The IPCC and others argue that the warming of the top fraction of a millimetre by AGHGs prevents energy from escaping from the deeper ocean and, therefore, effectively has the same response time as solar radiation. This position is shown to be not correct by the simple experiment outlined in Appendix 3.

3. As you would expect the IPCC’s models and predictions are already starting to fail as a result of them using the wrong wavelength to estimate AGHG forced climate sensitivity. James Hansen’s catastrophic predictions to the USA congress in 1988 are compared with actual temperature in Fig. 9. They clearly don’t correlate.

Fig. 9 James Hansen’s 1988 predictions to the USA congress compared with actual temperature.

Here is a quote from the IPCC’s 2001 TAR, “..anthropogenic warming is likely to lie in the range of 0.1°C to 0.2°C per decade over the next few decades”, and another from the IPCC’s 2007 4AR “For the next 2 decades, a warming of about 0.2°C per decade is projected”. The earth’s temperature has remained level or fallen since both of these predictions were made.

 

APPENDIX 1

Fig. 1 AGHG Forced equilibrium temperature using the IPCC’s sensitivity based on #2 (LGM and volcanic) and compared to actual temperature as measured by the NOAA since 1880. The upper IPCC limit assumes a climate sensitivity of “X” = 1.2, the IPCC central prediction assumes “X” = 0.8, and the lower IPCC limit assumes “X” = 0.4.

The method used to plot this graph;

1. A preindustrial CO2 concentration of 280 ppm was assumed. CO2 concentrations since 1880 were taken from the IPCC pre 1960 and from Mauna Loa after 1960.

2. CO2 Forcing was calculated using the widely accepted formula ;

rF = 5.35 x ln(C/C₀) wm^-2

Where “C” is the current CO2 concentration and “C_o” is the initial CO₂ concentration. This formula is the basis for the IPCC’s position that a doubling of CO₂ concentration will produce a Forcing of 3.71 wm^-2. i.e. rF = 5.35 x ln (2) = 3.71 wm^-2.

3. Based on the IPCC’s TAR and 4AR reports, the CO₂ forcing was then multiplied by 1.66 to give the total forcing of all the AGHGs (NO₂, CH₄, Halogens etc.) See Fig. 5.

4. The IPCC’s equilibrium temperatures were then calculated using the IPCC’s sensitivity factors, 0.4 (lower), 0.8 (central), and 1.2 (upper). i.e. The IPCC’s central predicted equilibrium temperature for a doubling of CO₂ is, therefore, 0.8 x 3.71 wm^-2 or approximately 3.0°C.

5. All graphs were then zeroed at 1880, the time when relatively accurate thermometer temperature measurements commenced.

 

APPENDIX 2

The four main millennial temperature series summarised in Fig. 4.

Fig.10 Temperature series for the last 1000 years. Ljungqvist 2010 (Black Line), Loehle 2008 (Blue Line)

Fig 11. Moberg 2005 1000 year temperature record including more recent instrumental records.

Fig. 12 Mann 2008 EIV 1000 year temperature series.

 

APPENDIX 3

The simple experiment, attributed to Tallbloke, that proves that GHG increases do not significantly warm the oceans.

Konrad: Empirical test of ocean cooling and back radiation theory

Posted: August 25, 2011 by Tallbloke in atmosphere, climate, Energy, Ocean dynamics 68

Some background –

Willis Eschenbach had a guest posting over at WUWT in which he claimed that LWIR could heat Earth’s oceans. Myself and several others on the thread contended that this LWIR was likely to be stopped by the evaporative skin layer and would not slow the exit of heat from the oceans. Numerous requests for empirical evidence to support Willis’s claim only resulted in one inapplicable study used by the “Hockey Team” to support such claims. After several hundred comments without empirical evidence being offered, I gave up reading and designed and conducted an empirical experiment that shows that any effect of backscattered LWIR on the cooling rate of water would be negligible.

What follows is an edited version of the experiment design and results as posted on the WUWT thread. I would encourage others to conduct similar experiments to check my results. The equipment required is not overly expensive and the results can be observed in minutes. The results appear to show the measurable difference between reflecting LWIR back to warm water when it is free to evaporatively cool and when it can only cool through conduction and radiation.

What is required –

– Two identical probe type digital thermometers with 0.1 degree resolution

– Two identical insulated water containers. I used rectangular 200ml Tupperware style containers, insulated on their base and sides with foil and Styrofoam. I cut away the clip on rim from each lid to create a frame to clip down cling film for Test B of the experiment.

– One IR reflector. I used an A4 sheet of 10mm Styrofoam with aluminum foil attached with spray adhesive.

– One IR window. I built an A4 size “picture frame” of 10mm square balsa wood strips and stretched cling film over it.

– One 1 litre measuring jug

– Two small identical computer fans. I used Suron 50mm centrifugal blowers powered by a 6v gel cell battery

– Extra cling film

– Optional extras – kitchen timer, an A4 ”dark cool sky” panel of matt black aluminum with peltier cooling, glamorous lab assistant of choice.

What to do –

– Position probe thermometers in identical positions in both water containers. I placed the tips 10mm below the water line by drilling force fit holes in the sides of the containers.

– Position IR reflector and IR window 50mm above either water container. You may need to build two Styrofoam side walls, but air must be free to move over the surface of the water. (The use of the IR window is to ensure that air flow is similar over each water container.)

– Position the computer fans to blow across the water surface of each container, but do not turn on.

– Fill jug with warm water, stir, then fill each water container from the bucket. I used water around 40C as the ceiling was around 18C not a 3k sky.

– When and equal amount of water is in each container, turn on the computer fans.

– Observe the temperature change over time for each tank. Less than half an hour is required for such a small amount of water. You should observe that both tanks cool at the same rate (TEST A).

– Now the important bit – Repeat the experiment, but this time lay a small sheet of cling wrap on the surface of the water in each water tank. This allows cooling through radiation and conduction but prevents evaporation. You do not need the computer fans on in this test. You should be able to observe that while both containers cool slower than before, water under the IR reflector cools slowest (TEST B).

Interpretation –

In TEST A the water cools more quickly, however the two water containers temperatures remain very close to each other over time. This indicates that backscattered LWIR has a very limited effect on the rate of cooling for water when it is free to evaporatively cool.

In TEST B both water containers cool more slowly than Test A, but a divergence in temperature between the two water containers is readily detectable. The container under the foil sky cools more slowly than that under the cling wrap sky. This indicates that backscattered LWIR from a warm material can slow the rate at which that material cools, if radiation and conduction are the only methods for cooling.

Test A represents the evaporative cooling conditions in the real oceans. Test B represents how the climate scientists have modeled the oceans with regard to backscattered LWIR. From what I have observed, backscattered LWIR can slow the rate at which substances cool. However in the case of liquid water that is free to cool evaporatively this effect is dramatically reduced. It would appear that including the oceans in the percentage of Earth’s surface that could be affected by backscattered LWIR may be a serious error. Earth’s oceans cover 71% of the planet’s surface. If backscattered LWIR cannot measurably affect liquid water, then CO2 cannot cause dangerous or catastrophic global warming.

I have conducted further tests using a “cold sky” panel cooled with ice water over the top of the cling film IR window. While the temperature divergence in the evaporation restricted test B does not appear faster, it does appear to diverge for longer.

I would encourage others to conduct similar empirical experiments and share their observations. I would be interested in comments in further experimental design, or empirical evidence related to the LWIR question.

Typical TEST A

Time	Cling Wrap Screen	Foil screen
0	37.1	37.1
5	33.2	33.2
10	29.4	29.4
15	27	26.9
20	25.5	25.5
25	24.5	24.5

Typical TEST B

Time	Cling Wrap Screen	Foil screen
0	38.2	38.2
5	36.3	36.6
10	34.8	35.3
15	33.5	34.2
20	32.6	33.4
25	31.5	32.6