How do you explain climate modelling in just 12 minutes? Gavin Schmidt, global climate modeller at NASA GISS, manages to do so. A beautiful talk, I would have been proud to have given it.
As a variability kind of guy, I especially like the introduction. The fundamental problem of climate science is that we have so many orders of magnitude in scale to cover. Spatially the scales go from microscopic dust particle (aerosols) to the size of the Earth; 14 orders of magnitude. In time a similar range is important from fast chemical reaction times to the millennia during which climate is changing. You could easily claim even more orders of magnitude. The chemical composition of the aerosols is, for example, also important for how quickly clouds develop and rain out. The variability over all these scales and how it changes with scale is one of the fascinating aspects of the climate system.
All the scales and all the processes dependent on each other. The aerosols are needed to build clouds. If there are a lot, you get many cloud droplets, which together have a huge surface and the cloud will be very white. If there are only little aerosols, you get less and bigger cloud droplets. To produce rain, less of these large drops need to collide together and rain can builds easier. These clouds, especially the huge shower systems in the tropics, again drive the circulation of the atmosphere, which determines which kinds of vegetation grows where, which again influences ... As Gavin Schmidt states: "You can't understand climate change in pieces. It's the whole, or it's nothing."
You can understand the processes in pieces up to a limit. People measure the chemical properties and shapes of aerosols in the laboratory. Instrumented aircrafts fly through the clouds and measure the sizes of the aerosols and cloud droplets. Simultaneously, remote sensing instruments on the ground and in space measure these clouds, so that the measurements can be compared with each other. The satellites validated at these small scales can then provide the global overview. In modelling the huge range of scales is bridged by a range of models, from large eddy simulation models that resolve the turbulence in the atmosphere, to cloud resolving models that model all the cloud processes in detail, to regional climate models that take land surface into account, to finally global models with ocean and ice models underneath. These detailed models are validated by measurements and themselves used to validate the larger-scale and global climate models.
Models are simplifications and thus by definition "wrong", but they do have skill. Quite an amazing skill if you realise that all the above mentioned and many further processes are only coded at the smallest scale of the model. The highs and lows and their fronts, the hurricanes and shower systems, El Nino and the North Atlantic Oscillation, they all emerge from the interaction of all these processes. This explains the title of the talk says: "The emergent patterns of climate change".
The models have skill, but they are not perfect. Much is simplified. Effective parameters based on measurements unavoidably represent the current climate. Humanity is taking the climate system into uncharted waters and we will only notice which simplifications were too strong when it is too late. To speak with Judith Curry, there is lots of uncertainty. Contrary to Curry, this uncertainty is what worries me most. Uncertainty goes both ways. The word does not mean that it has be turn out for the best. We are messing with a complex climate system upon which our existence depends and we cannot know with certainty what will happen. Not a conservative thing to do.
Enjoy the great talk. If you are interested in climate change, it will be worth your 12 minutes.
