The prediction of how much manmade global warming we will see in the future (as well as how much past warming was manmade) depends upon something called “climate sensitivity”.
For many years, climate researchers have struggled to diagnose the Earth’s climate sensitivity from measurements of the real climate system. It’s almost a “holy grail” kind of search, because if we could discover the true value of the climate sensitivity, then we would basically know whether future global warming will be benign, catastrophic, or somewhere in between.
Here I present a new method of satellite data analysis which I believe reveals the climate sensitivity, and I also show why it has been so hard to diagnose from observations.
When the Earth warms, it emits more infrared radiation to outer space. This natural cooling mechanism is the same effect you feel at a distance from a hot stove. The hotter anything gets the more infrared energy it loses to its surroundings.
For the Earth, this natural cooling effect amounts to an average of 3.3 Watts per square meter for every 1 deg C that the Earth warms. There is no scientific disagreement on this value.
Climate sensitivity is how clouds and water vapor will change with warming to make that 3.3 Watts a bigger number (stronger natural cooling, called “negative feedback”), or smaller (weaker natural cooling, called “positive feedback”).
While there are other sources of change in the climate system, cloud and water vapor changes are likely to dominate climate sensitivity. The greater the sensitivity, the more the Earth will warm from increasing atmospheric greenhouse gas concentrations being produced by humans through the burning of fossil fuels.
There are three possibilities for climate sensitivity:
1. If clouds and water vapor don’t change as we add CO2 to the atmosphere, then the expected warming by 2100 would only be about 1 deg. C, which would not be a very big concern for most people. This is called the “zero-feedback” case.
2. If low clouds decrease, high (cirrus) clouds increase, or water vapor increases, then warming will be magnified. Most, if not all, climate models predict that clouds and water vapor will change like this, resulting in an amplification of the CO2-only warming of 1 deg C to as much as 4.5 deg. C or more. This is called the “positive-feedback” case, and the greater the positive feedback, the greater the warming. (NOTE: If the sum of all positive feedbacks more than cancel out the 3.3 Watt natural cooling, then the climate system is inherently unstable…this is why you sometimes hear of climate change “tipping points”.)
3. If the climate modelers are wrong — and low clouds increase, high clouds decrease or water vapor decreases with warming — then the effect will be to reduce the warming to less than 1 deg. C. For instance, if that 3.3 Watts of natural cooling mentioned earlier increased to as much as 8 Watts from cloud changes, the warming would be reduced to about 0.5 deg C by 2100. This is called the “negative feedback” case.
Read more from Roy Spencer here: http://www.weatherquestions.com/Climate-Sensitivity-Holy-Grail.htm
In this simplied version of a paper entitled ‘Chaotic Radiative Forcing, Feedback Stripes, and the Overestimation of Climate Sensitiviy’ submitted on June 25, 2008 to the Bulletin of the American Meteorological Society Dr Spencer goes on to conclude that:
1. Current satellite estimates of climate sensitivity have a spurious bias in the direction of high sensitivity.
2. This bias is probably due to small, natural fluctuations in cloud cover.
3. The true climate sensitivity only shows up during those shorter periods of time when non-radiative forcing (e.g. evaporation) is causing a relatively large source of temperature variability compared to that from cloud variability.
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Read Global Warming for Dummies Part 1 here: https://jennifermarohasy.com.dev.internet-thinking.com.au/blog/archives/000959.html
And Global Warming for Dummies Part 2 here: https://jennifermarohasy.com.dev.internet-thinking.com.au/blog/archives/002844.html


Jennifer Marohasy BSc PhD has worked in industry and government. She is currently researching a novel technique for long-range weather forecasting funded by the B. Macfie Family Foundation.