Arctic Sea Ice Decline
Arctic Sea Ice Decline
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This rather hectic looking chart, called a stock-and-flow diagram, was created as a final project for GEOG 184: Environmental Modeling. It attempts to model the gradual decline in Arctic sea ice as a result of anthropogenic climate change, using two blue "stocks" (labeled freezable water in ocean and seaice) and "flows" between them, melting and freezing. These two stocks are presumed to hold all of the water in the top three meters of the Arctic Ocean, and the rates of the flows are calculated by a large quantity of variables that you can see floating around in orange and green. Feel free to simulate the interactive model yourself and observe the results.
The first and foremost priority of this analysis should be validity, so the data was fitted to PIOMAS sea ice volume data from the University of Washington. Use the above slider to compare the time-fitted data. While the seasonal variation doesn't quite match range-wise (because my model uses only random inputs as seasonal data, rather than historical data), the trendlines of the two charts clearly follow each other. Your simulation results may vary slightly from that which is shown above as a result of the randomized seasonal input.
Another important part of environmental modeling is the ability to separate the influences of different variables. We often hear politicians deny climate change by claiming that "the climate is always changing," a phrase which is almost as asinine as it is unscientific. Using models like this, we can run the simulation again having removed the green variable "CO2 warming of oceans," giving us the graph to the left. This kind of analysis allows us to say clearly and definitively that the sort of environmental changes we are observing must be the result of an outside variable influencing the climatic system.
You may have noticed that some of the variables in the stock-and-flow diagram reference each other, and connect in circular shapes. These are called feedback loops, and it's the function of these kinds of self-enforcing rules that environmental modeling really focuses on. There are two of these loops included in my model, albedo and wave breakup. Albedo is another word for reflectivity; when sea ice melts, the dark ocean reflects less radiation than the white ice, and therefore absorbs more heat, intensifying melting. Wave breakup has a similar effect; less sea ice means larger wave patterns can build up, which can break up more ice and intensify melting. To the right you can observe the effects of these feedback loops; surprisingly, wave breakup alone has little effect, but in concert with albedo it creates drastically steeper decline than either wave breakup or albedo alone.
It also sometimes surprises people that these terrific declines can come from seemingly small changes. Scientists urge the world to limit warning to 1.5ºC, which sounds like not much warming at all. The graph to the left shows that the climate-change affected ocean temperature is only minutely higher than what would naturally be occurring, but as we saw above, this tiny rise in temperatures could deplete the Arctic Ocean of its entire stock of sea ice by the year 2030, in what scientists term a "Blue Ocean Event."
This was one of my favorite pieces of independent research that I undertook at UCLA. My interest in the topic drove me to consider researching it directly, but before I could consult with my professor, UCLA went virtual due to the 2022 COVID-19 spike, and this class in particular was essentially cancelled, relegating it to my own personal, rather than professional, interest.
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