Dear All,
I'm working on the projections of Global mean temperature change (observed data obtained from NOAA, 1959-2018) based on green house gas emissions.
For this, I have tested several regression equations but not exactly able to compare these forecasts with IPCC report (TAR and or SR15).
I want to know is there any equation which mathematically or statistically explains these changes in global mean temperature based on CO2 concentrations or CO2 equivalent concentrations in PPM.
In the Radiative Forcing terms, one known reationship is,
delta(t) = Lamdba*delta(F).
where, delta(F) = Radiative forcing = 5.35*log(C(t)/C(0)), where C(0) = 278 PPM (CO2 concentrations in yr 1750).
But issues is that when we plot the calculated temperature change using this equation with observed NOAA data of temperature change, they aren't same. The observed curve is more steep than calculated one.
One more challenge could be the value of Lambda, some are saying that this value is 0.5 or 0.4, but even both values aren't leading to correct curve of temperature change.
What are your thoughts??
Best Regards,
Abhay
This can be consulted "Climate Models, Scenarios, and Projections - Climate Science ...https://science2017.globalchange.gov › downloads › CSSR_Ch4_Climate_M...by K Hayhoe "
Dear Abhay,
your equation for the radiative forcing, which is based on Myhre et al., 1998, Geophysical Research Letters (and, by the way, is measured in W/m^2) results from a fit of radiative forcing to GHG concentrations based on a line-by-line radiative code. It is a simplification, but likely a reasonable one.
Your factor Lambda, which is known as "climate sensitivity parameter", needs a bit more specification. It is not an explanation (neither statistical nor mathematical), but rather an empirical fit to how much the average global temperature changes with one Watt per square metre change in radiative forcing. It can be calculated form past timeseries of climate data, but also from models. I find the explanation on wikipedia quite helpful:
https://en.wikipedia.org/wiki/Climate_sensitivity
Its value depends on a number of things, of which the first is whether you look at the equilibrium change in temperature or a transient reaction to a changing CO2 concentration (such as when you fit the time-series against each other). It is thus not terribly surprising that you run into difficulties fitting timeseries for just the last decades to this equation. The whole concept holds best at equilibrium. Other dependencies are the size of internal feedbacks in the earth system (such as changes in water vapour when the average temperature changes). All this makes the exact value of lambda dependent on the timescale at which you look at it, and also on the background climate state (i.e. there were different values of Lambda when the climate state was very different from today).
So briefly my answer would be: Be aware that this simplifying relation is not an explanation, but rather a simplifying fit for the temperature changes with changing greenhouse gas concentrations; the real explanation needs full climate models.
Best regards, Christoph
Thank you so much for your input Christoph Voelker .
So, i need to study the climate models in order to understand the projected temperature change based on GHG concentrations?
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