CAMEL
Module #12 - Agricultural Consequences of ENSO (LAB)
Module Title
Summary
Short Description
Agricultural Consequences of ENSO: El Niño Throws a
Tantrum
In this lab, students learn how El Niño - Southern
Oscillation (ENSO) upsets normal patterns of
atmospheric circulation. ENSO’s warm and cold phase
events influence weather patterns in regions quite remote
from the tropical Pacific Ocean. In these areas, critical
and climate-sensitive industries such as agriculture can
be adversely affected.
El Niño brings more than above average rain and warm
weather. The warm phase of El Niño that impacts the
eastern tropical Pacific Ocean every 2 to 7 years disrupts
normal weather patterns and can damage agriculture.
Developing an understanding of El Niño will allow
scientists and citizens to consider ways to offset or
mitigate the negative effects on agriculture.
Image
Source: http://www.agriculture-ph.com/2010/03/el-nino-negative-growth-effectson.html
Learning Goals
Context for Use
Students will learn the following:
 To understand ENSO temperature and pressure
patterns
 To see why and how the warm phase of ENSO
affects the climate of remotely located regions and
their agricultural systems
The format suggested for this lesson is a data lab. Since
it requires no laboratory equipment, the class size can
range from a small student seminar to a medium sized
lecture hall. The only mitigating factor related to class
size is the necessity for each student (or perhaps pairs if
the instructor elects to make the lab report a paired
activity) to have a computer terminal or bring a laptop to
class. The class does not need to have a SmartBoard or
LCD projector, since the lab work will be conducted at
Description and Teaching
Materials
individual computers, but access to multimedia
equipment is preferred. See “Description and Teaching
Materials” below for link to the source lab.
Description and Teaching Materials:
The structure and primary components of this lab lesson
is sourced from Columbia University’s Earth
Environmental Systems Climate (EESC) course Lab #6
Agricultural Consequences of ENSO (Spring 2011).
I. ENSO: Sea surface temperature behavior
A. Background
Large amounts of heat can be exchanged between the
ocean and atmosphere, providing a link between these
two major components of the climate system. In this lab,
we will look at “sea surface temperature anomalies”
(SST). Anomalies are the difference between the SST
measured that month (e.g. September of 1997) and the
averaged SST for all Septembers for which we have data;
our data spans January 1970-September 1998. The
horizontal (x and y direction) coverage is 124E to 70W
longitude and 29S to 29N latitude, with a resolution of
2C. To learn more about these data, visit the
documentation page.
B. Temperature maps
Use the viewer (if that doesn't work, try the alternate
link) to look at an animation of monthly SST anomalies.
Take note of the latitudinal and longitudinal range of the
map view here. To animate, go to the white box above
the SST anomaly map and type in "Jan 1970 to Sep
1998" and click on the redraw button to the left. You
will see a progression of SST anomaly maps drawn,
starting from January 1970 and continuing to the present.
Find the largest spatial-scale anomaly patterns that you
see, then hit "Stop" on your internet browser to stop the
animation.
Task 1: Describe the pattern of SST anomalies across the
tropical Pacific.
Use these questions to guide descriptions (2-3
sentences):
 Where are the anomalies the largest?
 What is the typical temperature range of the anomalies?
II. The Effect of ENSO on the Tropical Atmosphere
During warm phase of ENSO, the atmosphere in the
tropics is heated via increased SST, so the atmosphere
must redistribute the extra heat. It does so by increasing
convection. One way we can observe changes in
convection is via satellite observations of the outgoing
longwave radiation (OLR). The OLR measurement tells
us the temperature of the surface that the satellite sees. If
the atmosphere between the satellite and the Earth's
surface is clear, then the satellite essentially sees the
OLR from the ocean or land surface. However, if the
atmosphere is full of thick clouds, then the satellite sees
the top of the. Since the cloud tops may be 5-10 km
above the surface, they are much colder than the surface.
Therefore, when we see patches of low OLR, we
interpret this as the locations of thick thunderclouds.
Task 2: Now look at the OLR anomaly for December
1982 -February 1983, which is the middle of a strong
ENSO warm phase event (this is the same period for
which you just examined sea surface temperature data).
 Where are the most negative OLR anomalies found?
 What could you infer from this about cloud behavior
during a warm phase event (El Niño) compared to
normal conditions?
 Where are the most negative OLR anomalies found?
 What could you infer from this about cloud behavior
during a warm phase event (El Niño) compared to
normal conditions?
III. What is the relationship between SST and sealevel pressure in the tropical Pacific?
This question will be investigated by examining the
correlation between sea-surface temperatures and
pressures, using the datasets described below:
NINO3 (TEMPERATURE) is the average SST anomaly
over the region 150W to 90W, 5N to 5S. (From the
map views of SST anomaly, you can see that this region
has the strongest SST anomalies associated with ENSO
warm phase events). The NINO3 data (click for
documentation) were computed by Alexey Kaplan at
LDEO from the Global Ocean Surface Temperature Atlas
SST anomaly dataset.
SOI (PRESSURE) is the difference between the
atmospheric sea level pressure anomaly at Tahiti (in the
southeastern tropical Pacific), and the atmospheric sea
level pressure anomaly at Darwin, Australia (in the
western Pacific). Pressure is usually low in the western
tropical Pacific, and high in the eastern tropical Pacific
(given the pattern of sea surface temperatures across the
tropical Pacific, does this make sense?). The SOI tells us
when this atmospheric pressure pattern departs from
normal conditions, or in other words, when atmospheric
sea level pressure is simultaneously lower in the eastern
tropical Pacific, and higher in the western tropical
Pacific, or vice versa. The SOI data are from the
Australian Bureau of Meteorology. We will use the data
for the period 1961 through 1990.
Save the data (accompanying file) in a place you can
easily access (e.g. the desktop). There are three columns
of data. The first is the calendar year. The second
column is the NINO3 averaged SST anomaly for Sep,
Oct, Nov of the corresponding years, and the third
column gives like averages of the SOI (Jun-Nov). These
intervals of months correspond to the seasons when the
maximums of SST and SOI occur during most El Niño
and La Niña episodes.
Task 3: Make a scatter plot of NINO3 vs. SOI.
Compute the correlation between SOI and NINO3 using
Excel's =correl() function and report it on your plot.
IV. Relationships between SOI, precipitation, river
discharge, and agricultural yields
The atmosphere has to get rid of the extra heating
supplied by the eastern tropical Pacific Ocean during an
ENSO warm phase event. It does this in certain
preferred patterns, which affect temperatures and
precipitation in many places around the world. As a
result, weather-sensitive human activities, such as
agriculture, can be affected. In this part of the lab, we'll
examine how closely ENSO parameters are associated
with remotely located agricultural yields. We'll do so by
examining the correlation between SOI and selected
wheat yields from agricultural model time series in
Australia. View a map of Australia obtained from the
National Mapping Division of Geoscience Australia to
learn more about the various regions you'll be examining
in today's lab.
Most of Australia is semi-arid, and climate conditions are
relatively unfavorable for many agricultural crops. Of
the major grains, wheat requires the least amount of
precipitation to grow, and thus is the most important
grain crop in the country. Australia is one of only about
five or six countries that produce a significant excess of
wheat crop beyond domestic consumption requirements.
These few countries supply most of the grain for
international trade in wheat. Since ENSO is responsible
for a significant portion of the interannual climate
variability in parts of Australia, knowledge of ENSO
conditions is critical in agricultural decisions in many
regions of the country.
Task 4: What is the relationship between SOI and annual
precipitation in Australia?
Using SOI as an indicator of ENSO conditions, make a
scatter plot of annual precipitation amount in the
catchment of the River Murray (southeastern Australia)
vs. SOI (Table 2). The Murray River catchment basin
(map obtained from the Murray-Darling Basin
Commission) precipitation and discharge data were
obtained via personal communications with staff of the
Australian Bureau of Meteorology and the MurrayDarling Basin Commission, respectively. Add a linear
regression slope, with correlation coefficient and slope
equation to the plot.
 Is there higher rainfall during El Niño or La Niña
episodes?
Task 5: What are the connections between SOI and
Wheat Yields?
Make scatter plots of Wheat Yields in NSW,
Queensland (QLD), and Western Australia (WA) each vs.
SOI (Table 3) – i.e., you should get three different series.
 Do the years of higher and lower yield tend to occur
in El Niño or La Niña episodes? Add a linear
regression slope, with correlation coefficient and
slope equation on each plot (or each series, if you put
them all on the same plot).
 Which regions’ wheat yields are positively correlated
with SOI?
DISCUSSION: Based on your observations …


What physical processes link SST and SSP? Explain
the NINO3 and SOI correlation. (paragraph)
Which ENSO state is likely to be more favorable for
growing wheat in Australia? (in other words, do you
think droughts would be more likely during El Niño
or La Niña episodes?). Why? (paragraph)
Below are the links for source material and resources:
 EESC course page, Agricultural Consequences of
ENSO lab: https://courseworks.columbia.edu/cms/
Handouts and Directions:
 Lab instructions
 Data
Background Information for instructors/TAs:
Instructors/TAs may find it useful to refer to lecture
notes from the following two lectures:
 ENSO Impacts; Other Climate
Variations/Oscillations: NAO, NAM, SAM, PDO
(Ting)
Teaching Tips and Notes
Assessment
References and Resources
Equipment/Supplies:
 Computer lab or moveable laptops with Internet
access and Excel.
 LCD projector or SmartBoard
See background information for instructors/TAs.
Students summarize their findings in a lab report.
All resources cited in the description of the course.