|
|
|
|
|
by René Gommes,
Senior Officer, Agrometeorology (FAO/SDRN)
Andy Bakun,
FAO Fisheries Department
Graham Farmer,
FAO Remote Sensing specialist
|
| March 1998 | |
El Niño-Southern Oscillation defined
El Niño is a local warming of surface waters which takes place in the entire
equatorial zone of the central and eastern Pacific Ocean off the Peruvian
coast and which affects the atmospheric circulation world-wide. It usually
peaks around Christmas, hence the name of the phenomenon: El Niño is Spanish
for Christ Child). La Niña refers to the "cold" equivalent of El Niño.
Like most atmospheric phenomena, it occurs at more or less regular intervals
(pseudo-cycles) and, as such, there is nothing "abnormal" in the occurrence
of El Niño. El Niño triggers so much interest for three reasons: it can be
modelled, thus forecast; its influence on climate is global, and there is
a time lag between the phenomenon itself and many of its most important
climatic consequences. Therefore, it can be used for forecasting climate [1].
The Southern Oscillation is an East-West balancing movement of air masses
between the Pacific and the Indo-Australian areas. It is associated (roughly
synchronised) with typical wind patterns and El Niño, and "measured" by the
Southern Oscillation Index (SOI) [2]. El Niño is the oceanic component,
while the Southern Oscillation is the atmospheric one. This combination
gives rise to the term ENSO. Although there is no perfect correlation
between El Niño and the Southern Oscillation for minor variations, large
negative values of the SOI are associated with warm events.
As illustrated in figure 1 below, El Niño occurs on average every 4 to 5
years, sometimes less (2 to 3 years), sometimes more (8 to 11 years). The
phenomenon proper lasts 12 to 18 months, also a recent very unusual event
lasted from mid-1990 to mid-1995 [3]. As indicated, El Niño is a permanent
feature of the Pacific ocean; the wording warm event describes an anomalous,
unusually warm El Niño. Similarly, there are cold events when the Sea Surface
Temperatures (SST) become unusually cold.
Figure 1:
Recent variations of the Southern Oscillation Index
Low (negative) values correspond to the warm phase. The graph was
prepared based on time series taken from the Queensland Department of
Primary Industries web-site (QDPI, Australia) and the Goddard
Distributed Active Archive Center (DAAC, USA). The February 1998
value corresponds to the 30-day period ending on 25 February (given
by QDPI). SOI is normalised, i.e. it is the dimensionless deviation
from the 1951-80 average expressed in standard deviation units.
It is important to realise that the ENSO phenomenon has always happened and
will continue to do so. What has changed recently is a better modelling and
understanding of the physics, hence better forecasting and more focused
monitoring of ENSO, as well as better world-wide forecasting of the climatic
consequences.
| The current
situation and possible consequences |
 |
Global impacts
There are essentially four sources for ENSO forecasts: the US National
Oceanic and Atmospheric Administration
(NOAA; see http://www.pmel.noaa.gov/toga-tao/el-nino/forecasts.html#enso),
the Australian Bureau of Meteorology
(BoM; see http://www.bom.gov.au/bmrc/mrlr/rzk/climfcn3.htm),
the Lamont Doherty group at Columbia University
(see http://rainbow.ldeo.columbia.edu)
and the Centre for Ocean-Land-Atmosphere Studies (COLA/IGES funded by NOAA,
NSF, and NASA; see
http://grads.iges.org/nino/)
A warm event had been forecast for
1997 by one of the climate forecasting Centres in January. However, the
agreement between the forecasts could only be reached when the actual
warming started to be observed. The models still disagree on details like
the intensity, the timing and geographic extension of the SST peak. The
warming has now been amply confirmed by satellite observations, moored and
floating buoys, deep ocean temperature soundings and sea level analysis.
The phenomenon is very visible in figure 2 below, where SOI is compared with
some records (1982, 1972), as well as the average of the 5 years of this
century (1900 to 1996) which recorded the lowest SOI values. The value
indicated for June is among the lowest ever. This behaviour is also very
clear in the SST records and various other ENSO indices (see, for instance,
under http://www.cdc.noaa.gov/ENSO/enso.current.html).
The current El Niño is exceptional in that it started very early in March-April
and because it reached record values during the summer 1997. It actually
culminated in June-August but had adopted a more normal pattern in the late
months of 1997, seasonally increasing again in December-January and remaining
stationary in February 1998. The "previous strongest" El Niño (1982) peaked
in March-April but started slower than the current one. The 1972 event (also
one of the top 6 for this century) collapsed after July [4]. Therefore, it
is very difficult to say exactly how the situation will develop this time.
It is clear by now that some extreme weather occurred, though not necessarily
where it was expected. On the other hand, some predicted disasters did not
occur. Of course, the situation is still developing, and no final conclusions
can yet be drawn.
El Niño affects marine fisheries, particularly in the eastern Pacific Ocean
where it tends to radically lower the ocean primary production. It is thought
to be associated with declines of a number of fish stocks, including the
largest fishery that has ever existed on earth, the Peruvian anchoveta fishery,
which totally collapsed in conjunction with the 1972 El Niño.
El Niño has different impacts in different parts of the world, sometimes
beneficial (for instance, it is believed to suppress hurricanes in the
Atlantic), sometimes negative (drought in Southern Africa and Northern
Latin America). Some of the possible consequences are illustrated in
figure 3 below. Although for many of them the mechanisms are well understood,
it should be noted that they are based on the empirical/statistical observation
that extreme ENSO has been associated in the past with extreme climatic
phenomena. In this context, extreme is taken in a statistical sense, i.e.
rare, occurring with a low frequency and usually associated with unusual
intensities [5].
Figure 2:
A comparison of the current SOI development with historical data
(The data used are the same as for figure 1)
The figure given for February 1998 is the average of the 25 first
days of the month.
From an agricultural perspective, it is important to remember that the
cropping season of the northern tropics falls between April and September,
while it coincides with October-March in the southern hemisphere (this
excludes all-year moist equatorial areas, the "sub-tropical" Mediterranean
areas and winter crops of the temperate climates). It is thus essential to
pay attention to the relative timing of the warm events and the crop
calendar: the top of figure 3 is thus essentially post-ENSO, while figure
3b coincides with the build-up of high SST (pre-ENSO).
Local impacts
Several WWW sites have assessments of El Niño impacts at a regional and
national level. As they have a lot of cross-referencing, it is sometimes
difficult to point to the actual source of the data. Some of them are
listed below, by continents.
Several WMO members have ENSO information, for instance Brazil, Chile,
Colombia, France, UK and the USA. They can be found under
http://www.wmo.ch/web-en/member.html;
more are added regularly. Meteorology, climatology and geography departments
of universities also frequently carry information on ENSO.
Figure 3:
World-wide climatic impacts of warm ENSO events
The upper half (3a) corresponds to the northern hemisphere winter
(October to March) and the lower half (3b) covers impacts during
April to September. D indicates drought, R stands for unusually
high rainfall (not necessarily unusually intense rainfall) and W
indicates abnormally warm periods. The figure is modified from two
illustrations given by Pacific Marine Environmental Laboratory WWW
home page (NOAA, USA).
| More details on
the situation, by continent |
 |
According to the analyses of the Queensland Department of primary industries
(http://www.dpi.qld.gov.au/longpdk),
the following areas may experience unusual rainfall conditions in the period
February-April:
-
drier than normal in parts of Gabon and adjacent areas, parts of the
horn of Africa, parts of SW Mexico and S central Brazil, parts of N Vietnam
and Laos
-
wetter than normal in parts of S India, parts of SE Australia, some
areas in S Brazil, parts of S Colombia and Venezuela, parts of N central
Africa.
Details about the current anomalies can be taken from WWW site of NCEP (National
Center for Environmental Prediction), CPC (Climate Prediction Center) of
National Oceanic and Atmospheric Administration (NOAA), USA
(http://nic.fb4.noaa.gov/products/analysis_monitoring/GLOB_CLIM/).
The situation described is that of the end of September - early October.
It is stressed that the anomalous weather shown is not necessarily a consequence
of El Niño.
Africa
"Normal" El Niño impacts:
-
Southern Africa: dryness coincides with the rainy/growing season, good
positive correlation with maize yield (negative impact) in Zimbabwe and
South Africa
-
East African wetness Oct-Dec coincides with and benefits short season crops
-
Sahel: no clear influence due to influence of the Atlantic Ocean
Up-to-date information from the following web-sites:
Asia
"Normal" El Nino impacts:
-
India: Dryness corresponds with the SW monsoon, usually associated with
reduced rice yields
-
Thailand: Negative impact on maize yields. Weak correlation with rice
-
Philippines: Dryness corresponds with the NE monsoon season (secondary
season), associated with reduced rice yield
-
Indonesia: Dryness corresponds with the dry season (a minor growing
season)
Up-to-date information from the following web-sites:
Australia
"Normal" El Niño impacts
Generally wet in the North west, but dry in most other parts of the country,
particularly the NE (Queensland)
Up-to-date information from the following web-sites:
Latin America
"Normal" El Niño impacts:
- Brazil: Rainy season Jan-Jun. El Niño mainly affects first half
of the season, mainly in the Nordeste.
- Ecuador/N. Peru: Heavy rain potential entire rainy season (Nov-Apr)
- Peru/Bolivia: slight tendency for dryness in Dec-Feb
Up-to-date information from the following web-sites:
Pacific Islands
In general, the timing and strengthening observed for this event in recent
months has been well ahead of that seen in other warm episodes over recent
decades (e.g. since the early 1950s). Although the 1982-83 warm event is
still regarded as the strongest this century, the present event has already
exceeded it by some measures, and may yet develop into a record-breaking
event.
Up-to-date information from the following web-sites:
USA/North America
Up-to-date information from the following web-site:
| What agrometeorology
can do: elements for a strategy |
 |
FAO does not have any mandate in the geo-physical aspects of the El Niño
phenomenon. Our interests are only in the impacts on agriculture -and consequently
food security - of the extreme negative/positive climatic events that can
be triggered by El Niño. This involves essentially the monitoring
of the ENSO situation, which is now easily done through a number of excellent
WWW sites, for instance the International Research Institute for Climate
prediction
(http://iri.ucsd.edu), the Climate Diagnostic Centre
(http://www.cdc.noaa.gov),
the American Geophysical Union
(http://earth.agu.org), the Institut Français
de Recherche Scientifique pour le Développement en Coopération
(http://www.orstom.fr), as well as the other WWW sites mentioned above.
Given the diversity of ENSO situations, and the resulting diversity of climate
scenarios, the seasonal forecasts of the extreme climate that may result
from El Niño (locally: at the level of countries and below) are the
competence of the sole national meteorological services. Needless to say,
regional/sub-continental centres can play an important role whenever the
national meteorological services either lack the capacity or the information
required to issue adequate warnings for the farming community. In southern
Africa, it is the SADC Regional Early Warning Unit and the WMO Drought Monitoring
Center which have introduced the ENSO problématique and operational
warnings in the region (Matarira and Unganai, 1994)
There are obvious benefits in knowing in advance what a cropping season
is going to be like, as this will allow farmers and governments alike to
take preventive action mainly in the areas of crop management (see
http://www.pmel.noaa.gov/toga-tao/el-nino/impacts-brazil.html
for an excellent example) and marketing (as commodity prices can be better
predicted).
The methodology of whether to take management decisions taking into account
ENSO information must be based as much on economic data as on potential
agronomic impacts. But it is essential that the seasonal forecasts be accompanied
by reliable probabilities of occurrence which will allow the calculation
of quantitative agricultural scenarios.
It would be too narrow an approach to develop a strategy that would deal
only with "reacting against El Niño". The proper strategy
is to develop response mechanisms that can be used at different levels (from
Government to farmers) to react to short and medium-term weather forecasts
(24 hours up to one week) and to more or less long-term climatic forecasts.
Whether the extreme factor is due to El Niño or any other cause is
not really relevant. (The only typical feature of El Niño impacts
being better than average predictability).
The proper reaction to extreme ENSO events must be seen in a broader context,
i.e. the development of a strategy covering extreme atmospheric factors
in general and involving several institutional partners. Current discussions
about how to react to El Niño are useful only if they lead to long-term
solutions. It is suggested that the proper strategy would incorporate the
following :
-
National Meteorological Services should improve their capability to
issue sub-national seasonal forecasts for their main agricultural areas,
including realistic and reliable probabilities of occurrence. The historic
ENSO data now allow improved predictions in many areas. It is important
that experimental forecasts be issued in order to allow users to develop
confidence in the forecasts;
-
Agricultural services should develop decision/simulation tools incorporating,
next to "future climate", economic considerations as well. This
also assumes good working relations between Meteorological and Agricultural
Services.
-
National Agricultural Research Institutes should look into the mechanisms
linking ENSO and agricultural impacts. Such mechanisms are not always very
direct. For instance, in a paper by Cane et al. (1994), it appears that
better links can sometimes be found between ENSO variables and agricultural
production that are statistically stronger than the relation between say,
rainfall and maize production [6]. Other examples of direct agricultural
applications are given by Simard et al. (1985), Instituto de Fomento Pesquero
(1985), etc.
-
Climate/weather impact on agriculture should be seen as much in terms
of opportunities (taking advantage of unusually "good conditions",
commodity market opportunities and planning...) and more efficient use of
climate resources by farmers rather than only in terms of loss mitigation.
As El Niño develops, some of the expected consequences actually materialize,
while others are not verified. It is clear that the current event is exceptional
also in terms of the attention it received from the media, governments and
the man in the street alike. Some countries were able to realistically manage
the situation while others over-reacted or found themselves completely unprepared.
Much can be learnt from the current situation in terms of adaptation and
mitigation strategies.
| Notes |
 |
1. Climate forecasts, also know as seasonal forecasts differ in many respects
from weather forecasts especially as regards the input data, the methods
used and the time horizon. Weather forecasts cover up to 10 days, while
climate forecasts extend up to one year ahead. Another difference is that
climate is defined as average weather, thus a climatic forecast is much
less detailed than a weather forecast: only general situations are outlined
(i.e. "dry conditions" , "abnormally warm", etc.) in
comparison with a reference period.
2. The Southern Oscillation is not unlike the swinging movement of water
in a bath tub. It is popular because it is easy to measure as the difference
between sea level atmospheric pressures at Darwin (N Australia) and Tahiti
(South- Central Pacific), for which there is a long historic record which
has greatly facilitated research.
3. This can be considered as one long, chronic, multiple-peaked El Niño
or rather as several small ones coming in rapid sequence. What is important
is that it lacked the general periodicity of the earlier historical period.
4. There are some marked differences between the current El Niño
and the July 1972 event: the SSTs stayed warm throughout 1972 (NINO3 was
+2.64 in December, then cooled rapidly in 1973). From an SST viewpoint the
collapse was not as rapid as with the SOI, and it is the SST anomalies that
provide surplus energy for some climate impacts. NINO3 is currently at +3C
and NINO1.2, along the coast is at +4.2C, hence the "feeling"
of many experts that the event is not going to disappear rapidly. Note that
NINO3 and NINO1.2 correspond to different "sectors" of the central
Pacific ocean.
5. One of the consequences is a relative difficulty to achieve good statistical
significance. It should further be noted that the frequency is referred
to a time period which may differ. For instance, figures 1 and 2 adopt the
1951 to 1980 period as reference. Since warm events have been relatively
more frequent after 1980, a more recent reference period would have ranked
1997 as less "extreme". Also, El Niño is only one of the
factors that affect global atmospheric circulation and climate. As far as
is known, it does not depend on other external forcing. Therefore, there
cannot possibly be a "perfect" association between El Niño
and climatic impacts. For instance, 1957/58 or 1977/78 had virtually no
effect in Southern Africa. Finally, warm events differ in many ways, such
as their "position" in the sequence of warm/cold/average SSTs,
their absolute magnitude, duration, location, etc.
6. This can be explained, for instance, by the fact that ENSO results in
a "climatic complex" characterized by rainfall, solar radiation
(linked to cloudiness), temperatures, etc. All the factors contribute to
the final production figure. In other words, ENSO variables may be more
synthetic than a single climatic factor.
| References |
 |
There is a very large volume of fundamental and applied research on El
Niño. Most quoted WWW sites will provide an easy entry
point, maybe starting from
http://earth.agu.org/revgeophys. For general
overviews, also refer to the web site of WMO
(http://www.wmo.ch).
Not all references are quoted in the text above. Some have been added because
of their focus on agriculture or because they present a good overview (e.g.
Glantz, 1996).
Bryceson, K.P. and D.H. White, Editors, 1994. "Proceedings of a Workshop
on Drought and Decision Support". Department of Primary Industries
and Energies, Bureau of Resources Sciences Canberra, Australia. vii + 63
pp. By the people who run one of the most operational ENSO WWW sites.
Cane,M.A., G. Eshel and R.W. Buckland,1994. 'Forecasting Zimbabwean maize
yield using eastern equatorial Pacific sea surface temperature'. "Nature",
370: 204-205.
Costa Amaral, O., 1993. 'A variabilidade pluviométrica no leste do
nordeste do Brasil e o evento enos de 1992'. "Boletim de geografia
teorética", 23(45-46): 61-70.
Glantz, M.H., 1996. "Currents of change: El Niño's impact on
climate and society". Cambridge University Press UK, xiii + 194 pp.
Instituto de fomento pesquero, 1985. "Taller nacional fenomeno El Niño
1982-83. Investigacion pesquera" (Numero especial), Santiago,Chile.
254 pp. This is a collection of papers focusing on ENSO applications in
fisheries in Latin America.
la Cock, G.D., 1986. 'The southern oscillation, environmental anomalies,
and mortality of two southern African seabirds'. "Climate change",
8: 173-184
Lagos,P. and J. Buizer, 1992. 'El Niño and Peru: a nation's response
to interannual climate variability'. In "Natural and technologies disasters:
causes, effects and preventive measures", Chapter 17, 224-239.
Matarira, C.H., and L.S. Unganai, 1994. "A rainfall prediction model
for Southern Africa based on the Southern Oscillation Phenomena". SADC/FAO
Early Warning System, GCPS/RAF/270/DEN, Harare, Zimbabwe. 42 pages.
Pearce,F., 1994. 'Fire and flood greet El Niño's third year.' "New
Scientist", 1908:9
Seleshi,Y., and G.R. Demarée, 1995. 'Rainfall variability in the
Ethiopian and Eritrean highlands and its links with the Southern Oscillation'
Index. J. Biogeogr., 22: 945-952.
Simard, A.J., D.A.Haines and W.A. Main, 1985. 'Relations between El Niño/Southern
oscillation Anomalies and wildland fire activity in the United States'.
"Agric. Forest Meteorol.", 36(2): 93-104.
|