Arrays
1. Read this article: https://www.spur.org/publications/urbanist-article/2009-11-01/strategies-managing-sea-level-rise (Links to an external site.)Links to an external site.
2. Watch this video: Miami Beach Prepares For Rising Seas | shift | msnbc (Links to an external site.)Links to an external site
3. Download the sea level data from http://climate.nasa.gov/vital-signs/sea-level (Links to an external site.)Links to an external site.Create a program that does the following:
a. Tell the user that the program uses data from NASA to predict sea level from the years 2020 to 2050.
b. Store the sea level data in an array. You only need to use one data point for each year from 1993 to the present year. Use the 10th column for each row (the Global Mean Sea Level GMSL with annual and semi-annual signal removed).
c. Find the average annual change in sea level over all the years specified in the data. (Hint – use a loop to store the annual change in an array over the years, and then use a loop to compute the average annual change).
d. Assume a linear increase and compute the predicted sea level rise for the years 2020, 2025, 2030, 2035, 2040, 2045, and 2050. Store these results in their own array. (Hint – just use the average you computed in part c as the annual change for the future years).
e. Display the results for the user and be sure to reference the data set as specified in the data file so the user knows where the data came from.
Sample output:
The predicted Global Mean Sea Level is
2020    64.32
2025    68.98
2030    73.51
2035    78.12
2040    83.43
2045    88.12
2050    93.04
These predictions were made using data provided by XXXXXXXXXX
Deliverables in a single Word document:
1. The code that solves the problem (no design tool needed). (80 points)
2. Screenshot of the output (10 points)
3. Reflection of what you learned about using arrays as well as what you learned about sea level rise. (10 points).
 
 
 

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