b.Do a hand example: Mark up the above data to show in detail how you would generate these results by hand. (i.e. identify the base month and the computation made for each data point read).

c.Write the algorithm: Write the algorithm for this program

d.Translate the algorithm into C: Write the code for this program.

El Nino The past year has seen a particularly strong El Nino event affecting weather around the world. We would like to be able to predict the frequency, duration and severity of future El Nino events. One very crude method for detecting the onset of an El Nino event is to measure the average ocean surface temperature in the eastern Pacific each month. If the measured temperature rises by 10% or more from one month (the base month) to the next, we can consider that to be a possible El Nino event. If the average surface temperature remains 10% above the base month for a second month, we consider that to be a likely event. If that temperature remains 10% above the base month for a third month or more, we can confirm an El Nino in progr subsequent month, the El Nino is over We would like to write a program to process monthly surface temperature data to detect El ess. If the temperature returns to within 10% of the base month in any Nino Events. A typical data file would look like 62.3 61.7 68.3 68.1 65.2 63.8 60.1 67.1 68.8 69.7 67.5 62.3 65.9 7 8 10 12 (a) Understand the problem The output for the above data set would look like: Month 1Normal at 61.70 Month 2 - Possible at 68.30 Month 3 - Likely at 68.10 Month 4Normal at 65.20 Month 5 Normal at 63.80 Month 6Normal a 60.10 Month 7 - Possible at 67.10 Month 8 - Likely at 68.80 Month 9 -El Nino at 69.70 Month 10-El Nino at 67.50 Month 11 - Normal at 62.30 Month 12 - Normal at 65.90