LAB Assignment using Matlab program

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timer Asked: Dec 6th, 2018

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Part I: Linear regression analysis, interpolation, 2-D data displaying

Part II: Integrating spatial data analysis and bivariate analysis

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GEOG 444 Lab Assignment #6: Due @ 5pm on December 6th, 2018 Name: _______________________ LAB Assignment #5: Least-squared best-fit linear regression, 2-D spatial data analysis and mapping. Part I: Linear regression interpolation, 2-D data displaying (20 pts) GEOG 444 Labanalysis, Assignment #2: Download the MATLAB MAT file Katrina.mat (Canvas, Week15) to your working directory. This Partstatistics II: Relational and logical operators data contains of Category 5 Hurricane Katrina in 2005. The statistics include: latitude, longitude, wind speed (mph, miles per hour), and surface air pressure (mb, millibars) from the In recent (08/23/2005) weeks, you’ve heard about the hurricanes (Harvey, Irma, etc.) isa lot. Theinso-called storm’s formation to its disappearance (08/31/2005). Each Jose statistics shown each Saffir-Simpson Hurricane Wind Scale is a 1 to 5 rating based on a hurricane's sustained wind speed. of the four columns of the data file. This scale estimates potential property damage. See the below Hurricane category table, adapted from National Hurricane Center, http://www.nhc.noaa.gov/aboutsshws.php . Use the MATLAB 1) Plot the tracks of Hurricane Katrina and the coast lines in the Atlantic basin (100W-60W, relational and logical operators (hint: if-elseif-else statement) to write a MATLAB code file (.m) to 10N-50N). AND color-code the tracks by its categories, which isthe based on theiswind speeddamage determine for a given wind speed of a hurricane, which category hurricane and what rd (3has. column). You may refer to Lecture 26 for various color schemes. Categories of tropical You need to first name a variable, “WindSpeed” to denote the wind speed, a variable storms are shown here.and Thea coastal data,“Damage” coast.mat to is denote downloadable from(from Week13. (5 and “HurricaneCategory” variableline named the category 1 to 5) pts) denote damage at landfall (listed in the table). Refer to Lecture Note 05. Category 1 2 3 4 5 Wind speed (mph) 74-95 96-110 111-129 130-156 >=157 Damage at landfall Minimal Moderate Extensive Extreme Catastrophic You can copy/paste your codes here. Or print and attach the file you wrote. 2) Calculate the correlation coefficient between wind speed and surface air pressure. (2 pts) 3) Calculate the linear least-squares regression between surface air pressure (as THE predictor) and wind speed (as THE predictand). (3 pts) The slope b1= ____________ mph per mb, the intercept b0= ____________ mph. 4) Using the regression equation to calculate the wind speed when the surface air pressure reaches 950 mb. (2 pts) WindSpeed@950mb = __________ mph. 5) (a) Scatter plot the surface air pressure (x-axis) vs. wind speed (y-axis) and denote the variable and unit in x-label and y-label. (b) Then superimpose the least-squares linear regression line to the scatterplot. (c) Show the error bounds of the linear regression fit. (4 pts) 1 GEOG 444 Lab Assignment #6: 6) Calculate the confidence intervals (95%) for the slope and the intercept of the linear regression equation using Student’s t-distribution. The Student’s t-distribution table can be found in Lecture note 24. On the basis of given relationship between surface air pressure and wind speed from Hurricane Katrina there is a 95% probability that the true population slope lies in the interval of [_______ , _________] mph per mb; And there there is a 95% probability that the true population intercept lies in the interval [_______ , _________] mph. (4 pts) Do include all your MATLAB codes for calculations and plotting. 2 GEOG 444 Lab Assignment #6: Part II: Integrating spatial data analysis and bivariate analysis (30 pts) Download the MATLAB MAT file usatempC.mat from Canvas, Week15 to your working directory. This data contains the annual-mean surface air temperature averaged over the United State continent from 1982 to 2016. Download the OISST_1982_2016.nc and lsmask.nc NetCDF files from Canvas, Week15. 1) Calculate the correlation coefficients between the annual-mean surface air temperature over US and annual-mean global SST from 1982 to 2016. Plot the spatial map with masked land. In the map, please: a. Include the global coast lines (You’ll need the coast.mat and showmap.m files from Week13) b. Set the correlation coefficient limits from -1 to 1 c. Add a colorbar d. Use blue-white-red color scheme (You’ll need the bluewhitered.m file from Week15) (10 pts) 2) Calculate the least-square linear regression slope between the annual-mean surface air temperature over US and annual-mean global SST from 1982 to 2016. Use US temperature as the predictor and global SST as the predictand. Plot the spatial map of the slope. In the map with masked land, please: a. Include the global coast lines b. Set the regression slope limits from -0.4 to 1.2 c. Add a colorbar d. Use jet color scheme. (10 pts) 3) Calculate and plot the year-to-year (1982-2016) standard deviations of global annual-mean sea surface temperature (Hints: try “help std” to find out how to calculate the standard deviation along a desired dimension). In the map with masked land, please: a. Include the global coast lines b. Set the regression slope limits from 0 to 1.6 c. Add a colorbar d. Use the default parula color scheme Question: From the map you plotted, which of the ocean basin presents the largest year-to-year variability (largest standard deviation)? a) US west coast; b) Gulf of Mexico; c) tropical eastern Pacific Ocean; d) tropical Indian Ocean; e) South Atlantic Ocean (10 pts) Do include all your MATLAB codes. 3
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