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Page 1
Summary
The climate of 1997-1998 attracted the attention of people and
governments worldwide not only because of a large number of extreme
weather events, but also because the climate anomalies that caused
many of them were accurately predicted months in advance. In early
1997, ocean monitors detected that sea surface temperatures in the
equatorial Pacific Ocean were rising sharply over an expanding
area. Coupled models of ocean-atmosphere interactions transformed
the data, which indicated a severe El Niño-Southern
Oscillation (ENSO) episode, into predictions of anomalous weather
extremes in several parts of the globe, many of which were
confirmed by subsequent events. Many catastrophic events were
linked to the ENSO episode, including water shortages, fires, and
crop failure in Central and South America; fires in Southeast Asia;
major storms in South America and California; tornadoes that killed
more than 120 in the United States; and increased rainfall in the
U.S. Southwest that fostered vegetation growth and increased the
potential for serious wildfires and the threat of a hantavirus
outbreak.
The improved ability to model ocean-atmosphere interactions and
thereby to predict seasonal-to-interannual climatic variations
across broad reaches of the planet has been a hallmark achievement
of the first 10 years of the U.S. Global Change Research Program.
Predictive skill has now increased to the point that the U.S.
National Oceanic and Atmospheric Administration (NOAA) and weather
services in other countries release forecasts of ENSO-related
weather phenomena to the public in the expectation that these
forecasts will allow individuals and organizations to
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Page 1
Summary
The climate of 1997-1998 attracted the attention of people and
governments worldwide not only because of a large number of extreme
weather events, but also because the climate anomalies that caused
many of them were accurately predicted months in advance. In early
1997, ocean monitors detected that sea surface temperatures in the
equatorial Pacific Ocean were rising sharply over an expanding
area. Coupled models of ocean-atmosphere interactions transformed
the data, which indicated a severe El Niño-Southern
Oscillation (ENSO) episode, into predictions of anomalous weather
extremes in several parts of the globe, many of which were
confirmed by subsequent events. Many catastrophic events were
linked to the ENSO episode, including water shortages, fires, and
crop failure in Central and South America; fires in Southeast Asia;
major storms in South America and California; tornadoes that killed
more than 120 in the United States; and increased rainfall in the
U.S. Southwest that fostered vegetation growth and increased the
potential for serious wildfires and the threat of a hantavirus
outbreak.
The improved ability to model ocean-atmosphere interactions and
thereby to predict seasonal-to-interannual climatic variations
across broad reaches of the planet has been a hallmark achievement
of the first 10 years of the U.S. Global Change Research Program.
Predictive skill has now increased to the point that the U.S.
National Oceanic and Atmospheric Administration (NOAA) and weather
services in other countries release forecasts of ENSO-related
weather phenomena to the public in the expectation that these
forecasts will allow individuals and organizations to
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Page 2
prepare for climatic events and be better off as a result. It is
clear that public awareness of El Eiño has increased
dramatically since early 1997. However, there is as yet no full
accounting of how beneficial forecasts have been in reducing
climate-related damage or in allowing people to benefit from
climate-related opportunities. Even though the scientific
capability to forecast seasonal-to-interannual climate variability
remains imperfect, there is good reason to believe that much
benefit can be gained by appropriately linking this capability to
the practical needs of society.
To do this requires scientific understanding of social processes
as well as climatic ones. How does society cope with
seasonal-to-interannual climatic variations? How is the
vulnerability to such variations distributed within and among
societies? How have individuals and organizations used climate
forecasts in the recent past? What kinds of forecast information
are most useful to people whose well-being is sensitive to climatic
variations? Who is likely to benefit from the newly acquired
forecast skill? How do the benefits depend on characteristics of
the users, the information in the forecast, and the ways in which
it is delivered? What is the nature of the potential benefits, and
how can they be measured?
This volume responds to a request from NOAA to review the state
of knowledge and to identify needed research on such questions. It
identifies a set of scientific questions the pursuit of which is
likely to yield knowledge that can make seasonal-to-interannual
climate forecasts more useful. The scientific questions flow from
our findings. Here, we summarize the major findings and the
scientific questions under three thematic categories: (1) the
potential benefits of climate forecast information; (2) improved
dissemination of forecast information; and (3) the consequences of
climatic variations and climate forecasts.
Potential Benefits of Climate Forecast
Information
Climate forecasts are inherently uncertain due to chaos in the
atmospheric system; moreover, forecasting skill varies
geographically, temporally, and by climate parameter. We expect
forecasting skill to improve in regions and for climatic parameters
for which limited skill now exists, thus increasing the potential
usefulness of forecasts over time. However, research addressed to
questions framed by climate science is not necessarily useful to
those whom climate affects. A climate forecast is useful to a
recipient only if the outcome variables it skillfully predicts are
relevant and the forecast is timely in relation to actions the
recipient can take to improve outcomes. Useful forecasts are those
that meet recipients' needs in terms of such attributes as timing,
lead time, and currency; climate
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parameters; spatial and temporal resolution; and accuracy. The
usefulness of climate forecast information also depends on the
strategies recipients use for coping with climatic variability,
which are often culturally, regionally, and sectorally specific.
Although many coping strategies are widely available in principle,
the ones available to any particular set of actors, and the
relative costs of using them, can be known only by observation.
Because the usefulness of forecasts is dependent on both their
accuracy and their relationship to recipients' informational needs
and coping strategies, we find that the utility of forecasts can
be increased by systematic efforts to bring scientific outputs and
users' needs together. These systematic efforts should focus on
two scientific questions:
1.
Which regions, sectors, and actors would benefit from
improved forecast information, and which forecast information would
potentially be of the greatest benefit?
2.
Which regions, sectors, and actors can benefit most from
current forecast skill?
Research on the first question would aim to set an agenda for
climate science to make its outputs more useful to recipients: it
would provide a voice of consumer demand to the climate science
community. Research on the second would proceed from the viewpoint
of climate science and would explore ways to get the most social
benefit from currently available forecast information. For both
kinds of research, two scientific strategies are appropriate and
should be conducted in parallel. One uses models and other analytic
techniques to identify and estimate the benefits that particular
recipients could gain from optimal use of particular kinds of
forecast information. The other relies on querying potential users
of climate forecast information about their informational needs,
either by using survey methodologies or via structured discussions
involving the producers and consumers of forecasts. Some of the
research on these questions should be directed at improving the
effectiveness of participatory, structured discussion methods.
Dissemination of Climate Forecast
Information
The limited evidence from past climate forecasts and a much
larger body of evidence on the use of analogous kinds of
information show that the effectiveness of forecast information
depends strongly on the systems that distribute the information,
the channels of distribution, recipients' modes of understanding
and judgment about the information sources, and the ways in which
the information is presented. This evidence suggests that
information deliv-
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ery systems will be most effective when organized to meet
recipients' needs in terms of their coping strategies, cultural
traits, and specific situations; that participatory strategies are
likely to be most useful in designing effective climate forecast
information systems; that new organizations delivering climate
forecast information will require a period of social learning to
become fully effective; and that useful information is likely to
flow first to the wealthiest and most educated in any target
group.
Individual and organizational responses to climate forecasts are
likely to conform to known generalities about responses to similar
kinds of new information. For example, interpretations of forecast
information are likely to be strongly affected by individuals'
preexisting mental models and organizations' preexisting routines
and role responsibilities. Knowledge about information processing
suggests several specific hypotheses about the use of forecast
information, such as that forecasts that turn out to be wrong have
a strong negative influence on the future use of forecast
information.
Research on five scientific questions can advance knowledge
about how to improve the dissemination of climate forecast
information:
3.
How do individuals conceptualize climate variability and
react to climate forecasts? What roles do their expectations of
climate variability play in their acceptance and use of
forecasts?
4.
How do organizations interpret climatic information and react
to climate forecasts? What are the roles of organizational
routines, cultures, structures, and responsibilities in the use and
acceptance of forecasts?
5.
How do recipients of forecasts deal with forecast
uncertainty, the risk of forecast failure, and actual forecast
failure? What are the implications of these reactions for the
design of forecast information?
6.
How are the effects of forecasts shaped by aspects of the
systems that disseminate information (e.g., weather forecasting
agencies, mass media) and of the forecast messages? How do these
effects interact with attributes of the forecast users?
7.
What are the ethical and legal issues created by the
dissemination of skillful, but uncertain, climate
forecasts?
Research on these scientific questions can usefully begin with
generalizations and hypotheses derived from existing knowledge,
based largely on analogous situations of information dissemination.
It should expand and refine this knowledge by studying responses to
climate forecast information. Responses to past climate forecasts,
including those for the 1997-1998 El Niño, are an essential
source of information for addressing these scientific
questions.
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Consequences of Climatic Variations
and of Climate Forecasts
Climatic events and forecasts have differing effects across
regions, sectors, and actors (e.g., farmers, firms). Moreover,
these effects are shaped by a complex mosaic of anticipatory (ex
ante) strategies that individuals, organizations, and societies
have developed for coping with climate variability, including risk
sharing (e.g., insurance), technological innovations (e.g.,
irrigation), and information delivery systems. Some coping
strategies interact synergistically, some compete and offset one
another, and some substitute for others. These coping strategies
are neither universally available to nor used consistently by all
actors at all times. To understand and estimate the consequences of
climatic events and of skillful forecasts, it is necessary to take
these coping strategies and differences in their use into account.
It is also necessary to consider that social, environmental, and
economic forces having little or nothing to do with climate
variability will partly govern the sensitivity or vulnerability to
climatic events and determine the types of information needed to
respond. Building an improved capability to estimate the human
consequences of climatic variation requires improved basic
understanding of these nonclimatic phenomena and of how they
interact with climatic ones.
Various quantitative and qualitative methods exist for
estimating the consequences of climate variability and the value of
forecasts. However, the methods now in use have important
methodological and conceptual limitations, such as overreliance on
simplifying assumptions; oversimplification of the dynamic
relationships between climate and human consequences; imprecise
definitions of key concepts such as adaptation, sensitivity, and
vulnerability; lack of distinction between potential and actual
value of climate forecasts; lack of attention to outcomes that are
not easily measured; lack of explicit attention to the distribution
of damages and benefits, especially the impacts of catastrophically
large negative events on highly vulnerable activities or groups;
and lack of reliable strategies for defining baseline conditions of
actors, regions, sectors, and populations. Estimating consequences
is also complicated by the fact that the resolution of data in
space and time determines the ability to model and detect certain
types of consequences. Many governments and other organizations
collect potentially relevant data, but little or no meta-data exist
describing the availability, quality, resolution, and other
essential traits of these data.
Research on five scientific questions can improve the ability to
estimate the consequences of climatic variations and the value of
climate forecasts:
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8.
How are the human consequences of climate variability shaped
by the conjunctions and dynamics of climatic events and social and
other nonclimatic factors (e.g., technological and economic change,
the availability of insurance, the adequacy of emergency warning
and response systems)? How do seasonal forecasts interact with
other factors and types of information in ways that affect the
value of forecasts?
9.
How are the effects of forecasts shaped by the coping systems
available to affected groups and sectors? How might improved
forecasts change coping mechanisms and how might changes in coping
systems make climate forecasts more valuable?
10.
Which methods should be used to estimate the effects of
climate variation and climate forecasts?
11.
How will the gains and losses from improved forecasts be
distributed among those affected? To what extent might improved
forecasting skill exacerbate socioeconomic inequalities among
individuals, sectors, and countries? How might the distribution of
gains and losses be affected by policies specially aimed at
bringing the benefits of forecasts to marginalized and vulnerable
groups?
12.
How adequate are existing data for addressing questions about
the consequences of climate variability and the value and
consequences of climate forecasts? To what extent are existing data
sources under-exploited?
Representative terms from entire chapter:
climate forecasts
