In an article about evaluating models, there is an interesting discussion of climate as a modeled entity. Some of the things that cause the Earth to have more stability are discussed, but what caught my attention was how you can close the loop on some open ended things with rules of thumb. (Then the question becomes how those rules of thumb change over time and over changed inputs / conditions…)
So I started here:
then worked my way back up stream into the comments that caused it. Also of particular interest was a graph posted by Willis. one comment above (as I type… but things being nested subject to change over time)
I’m going to talk about the image first, then get back to the first link.
Albedo Corelation With Temperature
Willis points out the strong correlation of albedo with temperature in the tropics as more temperature causes more clouds.
This is because, in the all-important tropics where most of the solar energy enters the system, albedo goes up with the temperature. They are very highly correlated, as you can see below.
But what got my attention was the NEGATIVE correlation at the poles. Being ice, it just doesn’t matter what the temperature is at the poles. They just don’t absorb much no matter what. Yet it isn’t all an ice effect. The corelation is most negative over the LAND of North America, Asia, and Chile / Argentina. One wonders why.
Is it farming and ploughed ground when the weather warms? Is it trees turning from green to brown in fall? Is it ice melting in spring? Is it the freezing out of water vapor and the loss of clouds when it goes to “cold winter nights”?
What are the implications of the equatorial zones being strongly positive corelation and the temperate and polar areas being negative corelation?
My suspicion is that this reflects the water cycle as dominant in our climate and weather patterns. While the equatorial zones demonstrate the “negative feedback” of the thunderstorm thermostat (water as vapor), the temperate and polar zones show the positive feedback that gives us strong seasons (water as ice and snow). Albedo is the reflected sunlight fraction, so a negative albedo corelation would be a positive feedback to heating – as you get hotter you get less albedo and more sunshine absorbed ‘up north’. I note in passing that the American South is about neutral and California is in the positive corelation quasi-tropical mode, despite being dry, but perhaps it is that offshore water and the San Francisco summer fog effect.
In short, is it just showing that summers in the temperate to polar regions have fewer clouds and more nice sunny days, leading to added warming as the winter clouds fade; yet too much heat is not possible as the oceans create lots of cloud and rain as the water approaches the 84 F range and that also causes negative feedback (positive albedo corelation)? Do we have two thermostats at work? One making the tropics stable, the other making the polar regions prone to swings? (Or is it seasonal changes of insolation that drive the swings that cause the albedo shift…)
I can see an endless argument about feedbacks springing from that. When one is positive and the other negative, which wins? Does that change over time?
Back at the first link
CO2IsNotEvil said (bold mine):
“The problem with this analysis is that Psun * (1-a), the amount of solar energy available after albedo reflections, is itself a function of the temperature.”
Not as much as you think. Yes, the albedo in polar regions is larger than equatorial regions owing to ice and snow, but the decreasing albedo from melting ice and snow is quite small. It was larger coming out of the last ice age when there was a lot more of the surface covered in ice, but today, the average fraction of the planet covered by ice is pretty close to the minimum possible. Average polar temps are far below freezing and no amount of GHG action will ever be enough to melt it all and prevent it from returning in the winter. About the only thing that will cause this is when the Sun enters its red giant phase.
Considering that 2/3 of the planet is covered by clouds, which have about the same reflectivity as ice, 2/3 of all future melted ice has no affect on the net albedo. Polar regions receive less insolation to begin with and when you calculate the increase in the incident power from melting all ice and snow on the planet and distribute that power across the entire planet, its only a few W/m^2 and less than what’s required to achieve the global emissions increase (temperature increase) they claim arises by doubling CO2.
The sensitivity expressed as a change in temperature per change in input power, dTs(t)/dPi(t) is already a function of temperature and that function of temperature is independent of the albedo. None the less, since (1-a) is linear to e, whatever effect albedo has can be rolled into an equivalent value of e, both of which can be expressed as functions of the fraction of the planet covered by clouds. Note that the sensitivity expressed as a change in surface emissions per change in input power is constant, where
dPs(t)/dPi(t) = 1/e
Yes, e is a higher order function of temperature, but when we measure it over the last couple of decades, it’s remarkably constant coming in at about 0.6, where dPs(t)/dPi(t) is about 1.6 W/m^2 of Ps per W/m^2 of Pi. It’s even relatively constant from the poles to the equator where e increases only slightly as the average temperature transitions through freezing.
It is an interesting approach. Looking at the way one place loses albedo but it causes a net gain in other places so the planet as a whole has far less change of energy budget.
But what this points out to me is just how critical it is to think in terms of clouds and ice. Those two are the ones driving this albedo show. If we can’t determine what actually changes them over time, we can’t explain the balance of negative and positive feedbacks from them and how those change over time.
Any model that claims to represent the Earth simply MUST start with solar input, how it varies, and how that varies the ice and clouds of the world. Otherwise they have the wrong albedo numbers, the wrong positive vs negative albedo feedbacks, and the wrong results.
I need to revisit the GCM source codes I’ve got to confirm (or deny) but I think they treated the sun as a constant (only variation being at grid cells via tilt changes) and treated albedo as a derived result of temperature changes caused by gas “forcing”. I don’t remember them using different albedo correlations by latitude or grid cell. (Perhaps I just missed it… some of that code is painfully obscure and dense). Basically, I think it was mostly a case of “making snow” and then adjusting albedo if that happened. (But I need to check it…)
It seems to me that there is plenty of room to “close the loop” on some of those processes; like accounting for 2/3 of ice melt as cloud increases) and reduce some of the positive feedback built into the present models.
Then, a muse per Ice Age Glacials:
IFF the negative corelation (positive feedback) is driven by the ice cycle, the implication is that a modest expansion of the area covered by ice, or having more of it persist seasonally, could tip our climate balance from the present negative feedback stable warm phase into a positive feedback cold phase. Enough of that, and if the positive feedback is to the cold direction, and we would have the oscillator that causes Ice Age Glacials to lock up for 100,000 years waiting for enough solar heating at the polar regions to get us back into a stable warm phase.
Basically, if axial tilt change shifts those positive feedback zones further toward the equator, at some point they win the positive / negative feedback balance wars and we tip into unstable positive feedback net. If due to ice, we lock up in ice. That would be bad…
Perhaps we need more monitoring of the temperature / albedo corelation values… especially as the snows are coming earlier to Europe and Australia and extending further south in North America… Ice Age Now has a lot of such reports listed at the moment: