Characteristics of ice-melt ponds
Characteristics of ice-melt ponds. Refer to the National Snow and Ice Data Center (NSIDC) collection of data on 504 ice-melt ponds in the Canadian Arctic, presented in Exercise 12.182 (p. 720). The data are saved in the PONDICE file. One variable of interest to environmental engineers studying the ponds is the type of ice observed in each. Ice type is classified as first-year ice, multiyear ice, or land fast ice. The SAS summary table for the types of ice of the 504 ice-melt ponds is reproduced below.
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a. Use a 90% confidence interval to estimate the proportion of ice-melt ponds in the Canadian Arctic that have first-year ice.
b. Suppose environmental engineers hypothesize that 15% of Canadian Arctic ice-melt ponds have first-year ice, 40% have land fast ice, and 45% have multiyear ice. Test the engineers’ theory, using a = .01.
Exercise 12.182
Characteristics of sea-ice melt ponds. Surface albedo is defined as the ratio of solar energy directed upward from a surface over energy incident upon the surface. Surface albedo is a critical climatological parameter of sea ice. The National Snow and Ice Data Center (NSIDC) collects data on the albedo, depth, and physical characteristics of ice-melt ponds in the Canadian Arctic. Data on 504 ice-melt ponds located in the Barrow Strait in the Canadian Arctic are saved in the PONDICE file. Environmental engineers want to examine the relationship between the broadband surface albedo level y of the ice and the pond depth x (in meters).
a. Construct a scatterplot of the PONDICE data. On the basis of the scatterplot, hypothesize a model for E ( y ) as a function of x .
b. Fit the model you hypothesized in part a to the data in the PONDICE file. Give the least squares prediction equation.
c. Conduct a test of the overall adequacy of the model. Use a = .01.
d. Conduct tests (at a = .01) on any important b parameters in the model.
e. Find and interpret the values of adjusted R2Â and s.
f. Do you detect any outliers in the data? Explain.
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