The Declining Arctic Ice Cap During September 19

The Declining Arctic Ice Cap During September 19

The Declining Arctic Ice Cap during September 19 Survey Ice area in The data table to the left shows the minimum ice Year millions of cap area for the Arctic during the month of September. At square km 1979 7.2 this time, the ice cap volume is at an annual minimum 1980 7.9 during the Arctic Summer. Global warming theory 1981 7.3 predicts that the polar regions will experience the largest 1982 7.5 impacts from continued planetary warming. 1983 7.5 In this exercise, we will use regression techniques 1984 7.2 to examine the trends in this tabular data, and examine 1985 6.9 how reliable forcasts will be for the year 2030 given the 1986 7.5 current data. 1987 7.5 1988 7.5 In the problems below, perform the calculations using 1989 7.0 your choice of technology, or by hand. 1990 6.2 1991 6.6 Problem 1 - Graph the tabular data using convenient 1992 7.6 scaling of the horizontal (Year since 1979) and vertical 1993 6.5 (Area) axes. 1994 7.2 1995 6.1 Problem 2 - Use a linear regression to model the data 1996 7.9 between 1979-2011 and compute the R2 value of the fit. 1997 6.7 1998 6.6 Problem 3 - Use a quadratic regression to model the 1999 6.2 data between 1979-2011 and compute the R2 value of 2000 6.3 2001 6.8 the fit. 2002 5.9 2 2003 6.2 Problem 4 - To the nearest 100,000 km , what would you 2004 6.1 predict as the area of Arctic sea ice in the year 2030 2005 5.6 using each regression model? 2006 5.9 2007 4.3 Problem 5 - Which of the two forecasts would you 2008 4.7 consider more statistically reliable? Which would you 2009 5.4 consider more believable? 2010 4.9 2011 4.6 NASA satellite data reveals how this year's minimum sea ice extent, reached on Sept. 9, 2011 as depicted here, declined to a level far smaller than the 30-year average (in yellow) and opened up Northwest Passage shipping lanes (in red). (Credit: NASA Goddard's Scientific Visualization Studio) Space Math http://spacemath.gsfc.nasa.gov Answer Key 26 The tabular data was obtained from the NOAA, National Snow and Ice Data Center archive at ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/Sep/ The archive of sea ice data can be assessed at http://nsidc.org/data/seaice_index/archives/index.html NASA Press Release: Arctic Sea Ice Continues Decline, Hits 2nd-Lowest Level October 4, 2011 URL = http://www.nasa.gov/topics/earth/features/2011-ice-min.html Problem 1 - Graph the tabular data using convenient scaling of the horizontal (year since 1979) and vertical (Area) axes. 9 9 8 8 7 7 6 6 5 5 4 4 Area (millions of sq-km) Area (millions of sq-km) 3 3 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 Year Year Note: For regression purposes, because the year numbers are so large, convert X axis to X = ‘Years since 1979’. Problem 2 - With Excel Spreadsheet, a linear regression (top left) gives A = 7.9561 -0.0847 (X) with R2 = 0.71. Problem 3 - With Excel Spreadsheet, a quadratic regression (top right) gives A = -0.0033 (X)2 + 0.0264(X) +7.308 with R2 = 0.79 Problem 4 – To the nearest 100,000 km2, what would you predict as the area of Arctic sea ice in the year 2030 using each regression model? X = (2030-1979) = 51, then Linear: A = 7.9561 – 0.0847 (51) so A = 3.6 million km2. Quadratic: A = -0.0033 (X)2 + 0.0264(X) +7.308 so A = 0.1 million km2. Problem 5 - Which of the two forecasts would you consider more statistically reliable? Which would you consider more believable? Answer: The quadratic regression has the better regression coefficient, but if we had removed the last three points (2009, 2010 and 2011) the regression coefficient would be similar to the one for the linear regression, so the quadratic regression is not as ‘believable’. More data beyond 2011 is needed. Space Math http://spacemath.gsfc.nasa.gov .

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