# Climate and Climate Change: Assignment 8

Assignment 8: (100 points)

Access the article named “Why are there so many ENSO indexes, instead of just one?” from Barnston – NOAA (https://www.climate.gov/news-features/blogs/enso/why-are-there-so-many-enso-indexes-instead-just-one) an summary the information about the different indexes of ENSO and why this is necessary so many indexes.

Part 2: ENSO analysis (60 points)

Step 2: In sheet 1, you’ll find three charts for each Logan – Utah, Corvalis – Oregon, and Quincy – California. The black line in these charts represents the Dec-Feb Nino 3.4 SST Anomaly. The lines are the same for each plot, so pick a chart and do the following. Recall, an anomaly is the difference between that specific time, and the long-term average. (6 points)

1. For the Nino 3.4 SST Anomaly, identify the top three extreme El Nino years, and the top three extreme La Nina years.
1. El Nino:
1. La Nina:

Step 3: In sheet 2, you’ll find data organized by year from 1950-2015. The first dataset is the average Dec-

February Nino3.4 sea surface temperatures anomaly and is what you see already plotted. Additionally, you’ll see three sections of columns, one for each of the three cities. Here you’re given the average Dec-Feb precipitation (blue columns) and temperature (red columns). Data that is missing or unreliable has been intentionally left blank for the purpose of this class.

Step 4: For each city, calculate the precipitation anomaly and temperature anomaly values for each year. To

do this, program the equation “=X-AVERAGE(\$X\$3:\$X\$122)”, where “X” is the specific column reference for each of the datasets you’re calculating the anomaly for. The use of the “\$” allows those cells to remain constant when you autofill an equation…these are crucial for correctly calculating the long-term average, so don’t leave them out. For example, the 1950 Logan Utah DJF Precip. Anomaly will look like “=D3-AVERAGE(\$D\$3:\$D\$122)and give a value of 13.71 mm. (20 points)

=p3-AVERAGE(\$p\$3:\$p\$122)

Step 5: Head back to sheet 1, where you’ll see the anomaly data you just calculated is now filled into the

charts (I preprogrammed it for you J). Now that each chart has three lines, do the following:

1. For each city in the table below, note the magnitude & sign of the anomaly for each of the three extreme El Nino and La Nina years you identified above. Use a “+” for a positive anomaly and a “++” if the anomaly is very high relative to the others. Conversely, use a “-“ for a negative anomaly and a   “- -“ if the year is notably anomalous. If the anomaly is around normal, use a “0” to indicate neutral anomaly. (14 points)
• For each city, identify the three years with the greatest anomaly in temperature and precipitation and indicate in the following table what phase of ENSO was occurring.  Use a “+” for an El Nino anomaly, a “-“ for a La Nina anomaly, and a “0“ if the year was neutral. Recall the threshold for ENSO events is ±0.5 °C. Once again, if the ENSO event is large or extreme, use a “++” or “- -“ to indicate as such. (14 points)

Step 6: For each of these locations, describe the expected pattern of temperature and precipitation for

El Nino and La Nina events. Does this expected pattern hold true for the extreme ENSO events from the 5A table? How about for the extreme temperature and precipitation events from the 5B table?     (6 points)

Copy and Paste your Logan, UT graph here

Copy and Paste your Quincy, CA graph here

What to Turn In: