a As discussed in our first classes global climate is warming, however the temperature change at a given location may be

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A As Discussed In Our First Classes Global Climate Is Warming However The Temperature Change At A Given Location May Be 1 (68.65 KiB) Viewed 72 times

a As discussed in our first classes global climate is warming, however the temperature change at a given location may be quite different than the global average. Furthermore even if the average temperature over many years (climate timescale) at a given location warms that does not mean that a given day of the year becomes consistently warmer. There is variability in warming from year to year, month to month and day to day, and definitely on these timescales we often see cooling. I have a great concern that climate variability, in the case of temperature how much of hot and cold spells we have in how quick succession, may be systematically increasing, a possible serious danger to ecosystems and humanity. The standard deviation of a set of data values. (d), is the square root of the variance, where the variance is given by <td - <d>>>, with the angle brackets, <>, representing the mean. The covariance of two sets of data values. (d) and (d.], is given by <d; - <dd> - <d->)>. The ratio of the covariance of the data sets to the product of their standard deviations, <(d, -<d>Hd; - <ds>)>/(<(d- <d>)>22</ds - <ds>)>**). is the correlation coefficient which measures to what extent the two data sets vary together. It ranges in value from 1 (perfect correlation, they vary the same way through o (no correlation, they vary in independent ways) to-1 (perfect anti-correlation, they vary oppositely). Project: 1. Find data for the temperature in New York City for each day of April in 1972 (when I was a young teenager) and 2022. Use OPTION 1: a data set all of whose values are for the same time of day (and state the time) OR OPTION 2: a data set of highs for the day OR OPTION 3: a data set of lows for the day OR OPTION 4: a data set of means for the day. Make plots vs. day of month for temperature for both years' April's and of the difference between the temperatures on corresponding dates of the two years. 2. Calculate the mean of each year's data set and the difference of the means. 3. Calculate the standard deviations of the data sets for both years. 4. Calculate the correlation coefficient for the two years. 5. Comment on whether your results suggest that New York City may be warming or cooling, or whether the climate variability in New York City may be increasing or decreasing, or whether the patterns of temperature within the month may have changed in New York City.