Homework answers / question archive / Matlab project, the project description is in course project pdf, my ID is 40187632 This project resembles standard climate data analyses that will be used for variety of civil, building and environmental engineering applications

Matlab project, the project description is in course project pdf, my ID is 40187632 This project resembles standard climate data analyses that will be used for variety of civil, building and environmental engineering applications

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Matlab project, the project description is in course project pdf, my ID is 40187632
This project resembles standard climate data analyses that will be used for variety of civil, building and environmental engineering applications. The procedure from step 4 onward is replicated below for the city of Montreal. • To plot monthly timeseries of minimum, mean and maximum monthly temperature values, use the similar application of the subplot function as shown below for Montreal. • Ideally your table should look like this. The following table is related to Montreal. Variable Month min mean median mode max std Mean T Jan -11.60 -5.38 -5.20 -6.10 0.80 2.83 Feb -10.40 -3.93 -3.60 -3.20 2.70 2.44 Mar -1.70 2.17 1.70 0.80 8.80 2.33 Apr 6.20 10.93 11.00 10.40 15.00 1.89 May 14.30 18.81 18.80 16.70 23.40 2.10 Jun 20.90 23.75 23.80 23.80 26.80 1.31 Jul 23.40 26.33 26.35 26.10 29.80 1.18 Aug 22.20 25.18 25.20 23.50 28.50 1.44 Sep 17.70 20.48 20.25 19.70 25.10 1.75 Oct 10.20 13.36 13.10 10.80 18.30 1.73 Nov 2.60 5.64 5.50 5.20 9.80 1.73 Dec -10.90 -2.18 -2.10 -2.80 4.60 2.82 ExtMax T Jan -2.30 6.55 6.70 6.70 13.90 3.21 Feb -3.60 6.06 6.10 5.00 15.00 2.96 Mar 4.80 13.08 12.40 10.00 25.80 4.84 Apr 15.60 22.79 22.80 20.00 30.00 3.50 May 22.90 28.42 28.30 29.40 34.70 2.47 Jun 27.10 31.16 31.20 30.00 35.00 1.77 Jul 28.30 32.16 32.25 31.70 35.60 1.62 Aug 27.80 31.28 31.20 31.70 37.60 2.10 Sep 24.40 28.64 28.30 27.80 33.50 2.38 Oct 15.80 23.14 23.30 23.30 28.30 2.40 Nov 7.80 16.37 17.10 14.40 21.70 2.79 Dec 2.20 8.81 8.90 3.90 18.00 3.77 ExtMin T Jan -37.80 -26.38 -26.70 -28.30 -16.80 3.44 Feb -33.90 -24.85 -25.00 -26.10 -15.70 4.10 Mar -29.40 -18.10 -17.80 -20.60 -7.80 4.69 Apr -15.00 -6.67 -6.30 -8.30 0.10 3.07 May -4.40 0.49 0.60 2.20 4.70 1.98 Jun 0.00 5.81 5.85 5.00 9.80 2.23 Jul 6.10 9.84 10.00 10.00 13.30 1.62 Aug 3.30 7.74 7.75 7.20 12.00 1.85 Sep -2.20 2.05 1.70 3.90 9.70 2.42 Oct -7.20 -3.55 -3.70 -5.60 1.50 1.78 Nov -19.40 -10.77 -10.30 -8.90 -3.30 3.25 Dec -32.40 -22.38 -22.10 -28.30 -12.10 4.26 3 • Following descriptions briefly outlines how part 5 should be handled. 1) To fit a linear fit to the data using polyfit function in MATLAB 2) You need to plot the data and fitted lines related to each variable in a separate figures and plot different months as subplots. The following figures show how the plots should look like for variables in Montreal. Mean T: ExtMax T: 4 ExtMin T: 3) The following table shows the slope of the fitted line for each variable and in each month. The fitted lines are obtained by polyfit and shown in above figures. To analyze the climate change in your city you can create a similar table for your variables of interest. If the slope is below 0, it means decreasing with time. If it is above 0 means that it is increasing with time. If it is 0, it means that the variable is not changing with time. Do not underestimate discussing your results. Month Mean T ExtMax T ExtMin T Jan 0.01 0.01 0.02 Feb 0.01 0.01 0.07 Mar 0.01 0.03 -0.01 Apr 0.02 0.03 0.01 May 0.02 0.03 0.03 Jun 0.00 -0.01 0.02 Jul 0.00 0.00 0.02 Aug 0.01 0.00 0.03 Sep 0.02 0.01 0.05 Oct -0.01 -0.01 0.00 Nov 0.01 0.03 0.01 Dec 0.04 0.03 0.07 • Flowcharts need to be complete, comprehensive and detailed; yet they must be concise and can be shown in ONE single page at most.