The Climate System
EESC 2100 Spring 2007
Lectures - Monday and Wednesday, 11:00 AM - 12:15 PM
Lab - Tuesday, 4:10 PM -7 PM
Case Studies: ENSO Impacts
This material builds from what we learned on Monday's lecture. Specifically
we use the knowledge of how and why the tropical Pacific ocean-atmosphere
system changes every 3-7 years to understand how these changes impact the
climate of the regional and, in fact, the climate of regions very far away
from the tropical Pacific.
From this session you should have an understanding of why El Niño
and La Niña cause the climatic changes that they do, both from an
intuitive sense based on your present knowledge of basic atmosphere and ocean
dynamics, and a specific understanding of the natural variability of this
system, its role in affecting the climate of near and far-field regions,
and its related societal impacts. This recitation underscores the issue that
regardless of your academic focus, year-to-year changes in the ENSO state
produce very real climatic, social, and economic perturbations at a global
Here are some of the known global climate impacts of El
Niño (warm event) and La
Niña (cold event).
Here we consider the effects of ENSO variability on the climate of SE Australia
as a case study for ENSO impacts elsewhere. Then, we turn the discussion
over to you and ask you to investigate what these ENSO climate linkages really
mean, how reliable they are, and how they might be used in practical management
decisions on the scale of an individual farmer or governmental agencies charged
with allocating irrigation water.
I. Case Study of ENSO Impacts:Australia
- High potential evaporation (E) rates over entire continent (Fig
1). Semiarid setting makes it very sensitive to ENSO-related changes
in regional rainfall.
- Model calculations of wheat yield in Australia, which are quite sensitive
to rainfall amounts and timing during the growing season, agree quite well
for a period of 18 years [1975-93] (Fig
2). This is true for each of the five states in which wheat is grown
- Wheat is grown in a relatively narrow band of Australia where rainfall,
temperature and soil conditions are optimal (Fig
3). Average (1901-99) crop yields in each shire (county) range over
about a factor of eight, from 0.5 to 4.0 T/ha, with a national average
of about 1.7 T/ha.
- National annual yields per unit area (simulated by model calculations)
vary from less 1 T/ha to more than 2.1 T/ha during the twentieth century
(Fig 4), largely
in response fluctuations in rainfall amounts and timing relative to cropping
seasons. A significant fraction of this interannual variability in rainfall
patterns is correlated with variations in ENSO parameters.
- The percentage of variation in simulated annual wheat yields tends to
be relatively small in Western Australia and relatively large in SE Australia
where correlations of rainfall amounts with ENSO tend to be the strongest
II. Response of River Discharge in SE Australia to ENSO
III. Questions for you to consider:
- If the weather forecast says there is a 90%, 50% or 20% chance of rain,
what does this mean? If it doesn't rain was the forecast incorrect? In
yesterday's lab you computed the correlation coefficient (r) between
the SOI and SST indices of ENSO. If you were told that the square of the
correlation coefficient (r*r = r2) is a measure of the degree of shared
variability (relatedness) between two potentially correlated variables,
what value of r would you want to have to say a region had a 90%, 50%,
or 20% chance of being linked to ENSO? (hint: 90% = 90/100 = 0.90).
- What happened in India during last year's El Niño? Drought is
expected in an El Niño year (Fig
11) which 1997 certainly was. And ENSO is certainly correlated with
food production (Fig 12). But
last year was quite normal (Fig 13)
-- though not everywhere of course (Fig
14). What are some reasons why the crop yield was not affected by the
strong El Niño of 1997? Consider the same question for Peru - Since
there is a strong ENSO connection in Peru, what possible reasons are there
for the low correlation with NINO3 of maize in Peru?
- The maize crop in Zimbabwe was planted in October 1997. Suppose you were
advising the government at that time? What would you tell them to expect?
How confident are you? How would you convince them to pay attention to
you? (CF Fig 15 and Fig
16). Using the r-value in Figure 5, what is the degree of shared variability
(relatedness) between Zimbabwe crop yield and ENSO? (Hint: see question
1). How could you use this statistic to convince the authorities?
- Some places have taken action in the past to mitigate ENSO impacts. In
the Nordeste region of Brazil, they adjust planting dates (Fig 17). In Peru coastal farmers plant
rice instead of cotton (Fig 18).
Which other regions might adopt such strategies? How would this affect
the future correlations between ENSO and crop yields for these places?
- Arizona (Fig 19), one of
the most arid states in the U.S.A., has two large urban centers (Phoenix
and Tucson) plus major irrigation zones. Most of the municipal water supply
for Phoenix is derived from climate district #4 in the central highlands.
Precipitation in this district is significantly different during El Nino
years, compared with La Nina years (Fig
20). Which months show the largest differences in precipitation amount
between El Nino and La Nina years? What changes in management practices
for the water storage reservoirs in the central highlands would be reasonable
during El Nino years?
Note: ENSO conditions as of October 1998 are shown in Figure
21 which shows the global SST anomalies as of the end of that month.
How does this SST pattern compare with the 1997 El Niño?
Text by Mark Cane, Peter deMenocal, and Jim Simpson.