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.


  1. In all the charts that are shown I never see any mention of the affect of Water Vapor as a Greenhouse Gas. Water vapor as a GG makes CO2 insignificant.

  2. Everybody is so desperate to hold on to the greenhouse theory they all miss that it is faulted at first principles. Flattening the Earth and dividing the incoming energy by 4 in the energy balance calculations misrepresent the true condition of Earth as a rotating sphere. If you were to just take incoming solar radiation on an airless planet then close to the sun being in Zenith you'd be looking at more like 90C, and across the sunlit hemisphere as a whole an average of 49C - just due to incoming solar radiation. Not the -18C you get from the divide by 4 fudge.
    It is the presence of an atmosphere, and most importantly the latent heat store of water in it's three states of matter, that acts both as an air conditioner on the sunlit side to cool down the planet, and transports heat away from the zenith zone to the poles and around the night side to keep them much warmer than they would otherwise be.
    The entire premise of the greenhouse theory that we would be at an average temperature of -18C without greenhouse gases is false, and therefore the greenhouse theory has no basis in basic science. Once you start at the right temperature you don't have to devise a complex method of absorption and reradiating heat from gases, and in any case it is so easy to fall foul of the 2nd law of thermodynamics doing this.
    The final test is observations of Venus. This has 96.5% CO2 in it's atmosphere, but observations of spacecraft descending through the atmosphere found a temperature of 63C at a pressure of around 1000mb. This is exactly what you would expect for the position of Venus relative to the Sun and Earth with its increased incoming solar radiation, therefore the almost saturation of CO2 in the Venusian atmosphere has no effect, and therefore the greenhouse theory is fatally wounded. The 485C surface temperature that alarmists say is due to a 'runaway' greenhouse effect is purely due to the crushing 90 Earth atmospheres pressure at the surface, not the reradiated heat from the CO2 in its atmosphere.
    The article above is so much easier to understand if you have a more realistic starting temperature, and use water latent heat as the modifying action that both heats and cools the Earth to achieve equilibrium, which is also why a runaway greenhouse effect is just junk science.

    1. Pressure is not causing the temperature. Gravity is causing the pressure here. The equation you are thinking of PV = nRT is only for a contained system which is forced into a volume. That is not true of planetary atmospheres (they can puff up). So, the temperature is caused by energy here, namely energy in versus out. Since the CO2 absorbs the planets heat and then sends it back it gets more heat and therefore higher temps.

      HOWEVER, it seems the models are greatly overestimating the temperature rises. By my math it should be 1 C per 150 years, and that assumes we keep increasing the CO2 content by 0.5% per year (which is adding 2 ppm per year now). As solar becomes cheaper this will probably chance so I really only expect a 0.3-0.5C increase.

    2. No, sorry you are incorrect about "Pressure is not causing the temperature"

      The great physicist Maxwell explains:

      et al:

  3. CO2 Forcing? ... BS ... no such thing ... And to answer the question above about "Water Vapor", H2O in the atmosphere acts to cool, not warm. There is no such thing as a "green house gas"