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Daniel Geisler (Jun 25 2020 at 00:36):Much improved climate predictions from statistical mechanics
Morgan Rogers (he/him) (Jun 25 2020 at 09:43):Interesting, but vague? I don't understand from this article what they have actually done.
Daniel Geisler (Jun 26 2020 at 01:55):The underlying Coupled Model Intercomparison Project 6 - CMIP6 is a system of systems that validate and then incorporate different sets of climate related data. The current set of integrated data was then responsive to transfer operators based on impulse forces to climate change. This is the first time a large composite climate data model has generated so many climate phenomena.
Predicting Climate Change through Response Operators in a Coupled General Circulation Model
Abstract.
Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Here we show how to use statistical mechanics to construct operators able to flexibly predict climate change. We perform our study using a fully coupled model - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO2 increase on a vast range of temporal scales, from inter-annual to centennial, and for very diverse climatic variables. We investigate within a unified perspective the transient climate response and the equilibrium climate sensitivity, and assess the role of fast and slow processes. The prediction of the ocean heat uptake highlights the very slow relaxation to a newly established steady state. The change in the Atlantic Meridional Overturning Circulation (AMOC) and of the Antarctic Circumpolar Current (ACC ) is accurately predicted. The AMOC strength is initially reduced and then undergoes a slow and partial recovery. The ACC strength initially increases due to changes in the wind stress, then undergoes a slowdown, followed by a recovery leading to a overshoot with respect to the
initial value. Finally, we are able to predict accurately the temperature change in the North Atlantic.
Data
These common dataset forcings are stored and coordinated by input4MIPS (input datasets for Model Intercomparison Projects).
Historical Short-Lived Climate Forcers (SLCF) and GHG (CO2 and CH4) Emissions
Biomass Burning Emissions
Global Gridded Land-use Forcing Datasets
Historical greenhouse gases (GHG) concentrations: a full description is published via the CMIP6 Special Issue publication
Ozone Concentrations and Nitrogen (N)
Aerosol Optical Properties and Relative Change in Cloud Droplet Number Concentration
Solar Forcing
Stratospheric Aerosol Data Set
AMIP Sea Surface Temperature and Sea Ice Datasets
Beyond these historical forcings, CMIP6 also has a common set of future scenarios comprising land use and emissions as required for the future Shared Socio-Economic Pathways (SSPs) and Representative Concentration Pathways (RCPs).
Daniel Geisler (Jun 26 2020 at 05:32):I am concerned that climatology currently has a last mile problem connecting mathematically creative people like those in ACT with the availability of the latest climate models, particularly using CMIP6.
What if there were a Climate Lounge where people could network with others to look at the models with different parameters?
Tying problems together, I read that a linear increase in climate temperature translates to an exponential increase in diseases.