That is simple, you only have to estimate the total volume of the ice. We then talk about 60-70 m of sea level rise. But this is very unlikely to happen. There was no ice-free earth for at least the last 43 million years. Even if it gets much warmer, a rise of a few meters would take a few 1,000 years.
You talked about the micro-climate of glaciers. From analyzing this microclimate, can you also obtain information how to model the climate of the entire earth? Are there similar model used?
Well, it is the same equations, the Navier-Stokes equations of hydrodynamics, that govern what happens on the glacier. But on glaciers, there are very huge gradients, e.g. on a warm summer day, the temperature 3 m above the glacier is 15°C but at the surface 0°C. This is a huge stratification that usually is not encountered. The micro-climate of glaciers is persistent but small scale. That makes it special.
You already mentioned the sea level. Let me first ask a basic question: the sea level e.g. in the Netherlands is rising while in other places it is falling (for example in east Scandinavia or the Maledives). What exactly is the "Global sea level'', this one number you always hear about?
The global sea level is very difficult to define. There are so many factors that play a role and you have very few absolute references. But normally, the sea level is defined as follows: if you would have no motion in the oceans, the sea level would follow an equipotential level (a geoid) of the gravitational field of the earth. But of course, then you have the dynamics which cause a gradient in the slope of the ocean surface. Furthermore, there are differences in atmospheric pressure, the wind set-up in the shallow coastal regions etc. And then there are tectonic movements and isostatic adjustments. That is what dominates in Scandinavia. But also the salinity and the temperature of the ocean play a role, since they can change the water density. So its very complicated. But what we now normally define as the global sea level is an average of many satellite measurements. This is still a relative number, but that is not a real problem because you are interested in changes. When you use the same source and do the data handling always in the same way, you get reliable information about the changes.
Let me ask a more general question about climate science. About 20 years ago, Chaos theory was very popular when talking about complex, non-linear systems such as the climate. One essential result of Chaos theory is the "Butterfly effect'', which means that the time evolution of a complex, nonlinear system can change drastically for very small changes of the initial or boundary conditions. This strongly limits the predictability of systems like the climate.
On the other hand, if you follow today's discussion in the media, you sometimes get the impression that the climate evolves in a rather simple way: You often her about monotonous, even linear dependencies. Are these two incompatible vies of how climate science works?
I was trained as a physicist and meteorologist when these theories were popular. The work of Edward Lorenz, where he looked at how non-linearites limit the predictability of non-linear systems, was a standard work for any meteorologist. I think this has been a bit forgotten nowadays—wrongly I think. This is also a bit part of my personal struggle. In many lectures, I say that we have to study the climate but we must realize that predictability is limited, especially when you go to more regional scales, where atmospheric dynamics play a more important role.
In general, people do not like this—especially politicians. People, not specialized in climate processes do not like the message that things are not that predictable. Take the people making impact studies: non-predictability limits the relevance of their work. But I am convinced that there is quite some limit to the predictability.
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