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The Effects of the Melting Arctic Ice Cap on Florida's Coast Tony Atkinson, Nick Joseph, Louw Scheepers The Effects of the Melting Arctic Ice Cap on Florida's.

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Presentation on theme: "The Effects of the Melting Arctic Ice Cap on Florida's Coast Tony Atkinson, Nick Joseph, Louw Scheepers The Effects of the Melting Arctic Ice Cap on Florida's."— Presentation transcript:

1 The Effects of the Melting Arctic Ice Cap on Florida's Coast Tony Atkinson, Nick Joseph, Louw Scheepers The Effects of the Melting Arctic Ice Cap on Florida's Coast Tony Atkinson, Nick Joseph, Louw Scheepers Abstract Variable and Assumptions We’ve set out to determine the effect of arctic ice melt on the coastline of Florida, more specifically it’s major cities and tourist attractions. Since, this is a daunting task with many aspects, we were forced to narrow our examination to a similar but simpler system. We took into effect arctic land based ice, arctic sea based ice, and the Greenland Glacier. We ignored all other sources of arctic ice melt for the sake of simplicity. In order to have a system of self-check, we created multiple models on different bases. This way we could compare and contrast our results and know that our models are functioning correctly. Our data and analysis showed firm indications of extreme effects on the coastline of Florida and some of it’s major tourist attractions by as early as 2050. The Florida Keys and Miami Beach seem to be among the most affected areas of Florida. Our models present best and worst case predictions, showing that there is ample data to support a non-affected Florida in the next 50 years. However, our worst case scenario predictions describe a Florida coast heavily affected by a raised sea level. This would create irreparable environmental damage as well as negatively affecting the Florida economy. Models MODEL 1: Our first model was a simple statistical model. We started with sea level rise data from two buoys off the coast of Florida. These buoys measure the sea level in increments of time and then send the data via satellite to be recorded. Our first step was simply to graph the data in excel and visually analyze the data in order to see what we should expect our model to do. From these graphs, it is easy to see that the general trend is in fact linear. From this we determined that we could create a simple linear y=mx+b form model in order to predict the future sea level rise. In order to do this more accurately we decided it would be best to run a regression on both sets of data, average these values in order to get values for one model that we could use to predict the rise in the sea level. When we ran a regression on the data from buoy 1, we got a slope of 3.565 and a y-intercept of 5925.14. From running the regression on the second buoy, we got a slope of 2.555 and a y intercept of 6958.929. When we average these values, we get a slope of 3.0603 and a y-intercept of 6443.0348. We used these values to create our first model; you can see it below. S = 3.5649t + 6021Where S is the sea level, and t is the time in years MODEL 2: For this model we envisioned a scenario where three fourths, or 75%, of the arctic ice had melted. This is an accurate estimation of the total arctic ice that will be remaining by the year 2050. Therefore, this model required data of the current status of the size and thickness of the Arctic Ice. We assumed that this ice melt came strictly from 2 areas. The first source of the ice melt is the main arctic ice sheet, and the second source is the Greenland glacier. These are reasonable assumptions since Arctic sea ice has minimal effects to the total global ice melt, since the sea ice is mostly submerged in water anyway. Conclusion Based off of our first model, we found that Florida is not in any immediate danger in the next 50 years. The sea level will continue to rise, and at what seems to be an accelerating rate, but even a century from now major cities like Miami and the Florida Keys, should still be above water. Our model does predict low-balled data due to the nature of regression not being able to properly take into account exponentiation, as well as our model being linear. Our second model showed us that if 75 percent of the ice melted by 2050, much of the Florida coast would be in danger. This extreme model shows that if ice keeps melting, and our first model is shown to be a significant underestimation, there would be negative effects on the wildlife and human inhabitance of the far edges of the Florida Coast. The Keys themselves would recede significantly, displacing many tourists and depreciating the Florida economy. Results Our first model indicates a drastic increase in the sea level rise over the next 50 years. Below you will see a table that shows the sea level rise in increments of ten years for the next fifty years. By subtracting the sea level in the year 2070 from the sea level in the year 2014, you can see the sea level rise over the next 56 years. We obtained a value of 199.63 mm. For our second model, assuming that 75 percent of the arctic circle and Greenland would melt, the sea would rise about 80 +- 5 centimeters. This model is an extreme, however it shows a worst case scenario for climate change. This uncertainty stems from the error extracted from the measurements of the total ice mass. MODEL 1: Since this model is based on the total sea level rise, and not individual components, there are not many assumptions or generalizations. Our data is specific to our region and therefore gives us a very accurate model for the near future. However, this model will not be accurate in predicting sea level rise hundreds of years from now. There are many factors that go into sea level rise that cannot be accounted for in a linear model such as the one we made. MODEL 2: We assumed that this ice melt came strictly from 2 areas. The first source of the ice melt is the main arctic ice sheet, and the second source is the Greenland glacier. These are reasonable assumptions since Arctic sea ice has minimal effects to the total global ice melt, since the sea ice is mostly submerged in water anyway. Model 1 Year2014202020302040205020602070 Sea Level (mm) 6021 6042 60786113624961856220 Model 2 Glacial Areas area (m^(2)) Thickness (m) Volume (m^(3)) Greenland 76200000000 3000 22860000000 0000 Arctic Ice 15143300000 0 2100 31800930000 0000 SUM 54660930000 0000 75 Percent MAX 40995697500 0000


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