ASSIGNMENT #3: The El Niño Southern Oscillation
r语言代做 Download the following files onto your computer which you will find on canvas on the “Assignment #3” page:exercise3_P1.R exercise3_P2.R SOI_···
r语言代做
Download the following files onto your computer which you will find on canvas on the “Assignment #3” page:
exercise3_P1.R exercise3_P2.R SOI_1952-2012.dat
nino3.4_sst_anom_3mrm_1952-2012.dat
Next, start up “R” and at the prompt (>>) enter your name in the following way: name<-“Jane Doe”
This step is very important since it will identify you on the results of your work. If your name does not appear appropriately on the graphical output that you hand-in with your completed assignments, you will receive no credit for this assignment. In addition, if you omit this step, the R-programs for this exercise will not work correctly and you will get an error message.
PLEASE HAND IN ALL OF THE FIGURES GENERATED BY THE PROGRAMS THAT YOU RUN FOR THIS ASSIGNMENT.
El Niño, La Niña and the Southern Oscillation r语言代做
As we discussed in class, El Niño and La Niña can be monitored using several indicators that are derived from observations of the atmosphere. And ocean in the tropical Pacific. As we have seen, El Niño and La Niña episodes give rise to substantial anomalies in the surface pressure along the equator between the central. And western Pacific Ocean.
The amplitude of these pressure changes can be quantified using the Southern Oscillation Index (SOI). Which is the normalized difference between the standardized pressure anomalies measured at Tahiti and Darwin. Another way to monitor El Niño and La Niña is to observe the sea surface temperature (SST). Temperature anomalies averaged over the region 170°W-120°W, 5°S-5°N yield the so-called “Nino3.4 index.” This is a region characterized by significant variations in SST during El Niño and La Niña episodes.
Question 1: r语言代做
- Brieflyexplain in your own words (1 paragraph) why there is a surface pressure difference in the atmosphere between Tahiti and
- Brieflyexplain in your own words (1 paragraph) what controls the sea surface temperature in Nino3.4 region of the central Pacific
Question 2:
- Run the program “exercise3_P1.R” in R. As you were instructed to do in class and in This will load the data for the monthly SOI. And monthly Nino3.4 index for the period 1952-2012. And will generate a time series plot of each data set (exercise3_plot1.jpg). The SOI time series is called “soi_data”. And the Nino3.4 index time series is called “nino34_data”. Compute the correlation between the two time series using the “cor” function in R (i.e. cor(soi_data,nino34_data)). Record the value that you find, and explain what it means.
- Using the R function “cor.test” (e. cor.test(soi_data,nino34_data)), record the p-value.(In R, a number such as 1×103 will appear as “1e3”, while 1×10-3 will appear as “1e-3.”) Briefly explain what the p-value means.
Question 3: r语言代做
- Now run the program “exercise3_P2.R” in R. This program will reload the SOI. And4 index data and plot for each the probability density function (exercise3_plot2.jpg). Also plotted is the probability density function for a normal distribution (red curve) with the same mean. And standard deviation as the parent time series. Using the “mean” and “sd” functions in R. Record the mean and standard deviation of the SOI (soi_data) and Nino3.4 index (nino34_data). Relate these numbers to the red curves.
- Brieflydiscuss how well a normal distribution fits the data in each
- Table 1 below shows the frequency distribution of the Nino 3.4 index, ri. Sorted into binsof width Dr = 2 . Recall from class Module 1 that the probability density function (PDF)
AND r语言代做
estimate the cumulative probability of occurrence of an El Niño episode with a Nino3.4 index greater than or equal to 1°C (i.e. a “moderate” amplitude El Niño). Explain your reasoning and show your calculations. (ii) Now estimate the cumulative probability of occurrence of El Niño episodes with a Nino3.4 index greater than or equal to 2°C (i.e. a “large” amplitude El Niño).
(iii) Given that the Nino3.4 time series is 61 years long, express both of these cumulative probabilities in the following language: “Moderate/Large amplitude El Niño episodes are a 1 in xx-year event.” Where “xx” is a number that you need to compute based on your answers to (i) and (ii). (iv) Indicate the “moderate”. And “large” amplitude El Niño episodes based on these criteria on the Nino3.4 time series from question (2) (i.e. on the figure exercise3_plot1.jpg) and comment of whether the statements in (iii) are consistent with the figure.
Question 4: r语言代做
Go online and download the most recent ensemble forecasts for the Nino3.4 index from NOAA Climate Prediction Center (CPC) and the European Centre for Medium Range Weather Forecasts (ECMWF). The forecasts can be found here:
NOAA CPC:
http://www.cpc.ncep.noaa.gov/products/people/wwang/cfsv2fcst/CFSv2SST8210.html Choose any of the Nino3.4 forecasts (i.e. E1, E2 or E3).
ECMWF:
https://www.ecmwf.int/en/forecasts/charts/seasonal/seasonal_nino_plumes_public_eurosip?time
=2018010100,0,2018010100&nino_area=3.4
- Interpretthe ensemble of forecasts in each case and include a plot of
- Comment on the degree of consensus between the CPC and ECMWF ensemble
- Brieflyexplain why it is necessary to run an ensemble of forecasts in order to predict
AND r语言代做
Table 1: A table of the frequency distribution of the observed Nino 3.4 index (ri) in the tropical Pacific Ocean (1952-2012). The bin size Δ ri=0.2, and the number of counts per bin, ni, is indicated. The blank columns labeled pi and c(ri) are for you to enter your computed values of the probability density function pi and the cumulative probability density function c(ri). It is recommended that you compute values of pi to 2 decimal places, and values of c(ri) to 3 decimal places. As a guide for you, the first few entries in columns 3 and 4 are shown.
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