
February 2008
A closer look at today’s forecast
NCAR researchers study how people use
weather predictions

Researchers in SIP are exploring how
new types of weather forecasts could give the public
a better sense of where the uncertainty lies within
temperature and rainfall outlooks. |
It’s been more than 40 years since Americans were
first introduced to probabilities of precipitation. Instead
of simply conveying a threat of rain or snow without using
numbers, forecasters began to include percentages, as in
“a 60% chance of showers.”
Decades later, most U.S. residents still aren’t precisely
sure what these probability-of-precipitation forecasts mean.
However, they do get the general idea—and many of them
want more such uncertainty information.
These are among the insights arising from a major survey
conducted by NCAR’s Societal Impacts Program. SIP involves
scientists from SERE, RAL, and ESSL, with funding from the
U.S. Weather Research Program.
“Weather forecasts are unavoidably uncertain,” notes
Rebecca Morss, “but most public forecasts come with,
at best, limited information about their uncertainty.”
Rebecca and SIP colleagues Julie Demuth and Jeff Lazo are
sifting through the extensive data gleaned from their 2006
survey. They made several presentations at last month’s
American Meteorological Society meeting, and
two papers are in the works, with more to come.
One of the group’s goals is to provide grounding
and perspective for the National Weather Service (NWS) and
other providers who are now contemplating how best to improve
public weather forecasts. The idea of the survey arose after
a 2006 National Research Council report on estimating and communicating
uncertainty in weather and climate prediction. Rebecca served
with Barb Brown (RAL) on the panel that produced Completing
the Forecast, which was sponsored by the NWS. (See “On
the Web.”)
“Meteorologists often find it challenging to communicate
uncertainty effectively,” Rebecca says. She and her
colleagues found that relatively little research on communicating
the uncertainty in weather forecasts had been published
since the 1980s. “Being on the NRC panel helped clarify
for us that this was an important priority area that hadn’t
been adequately addressed,” she says.
Late in 2006, SIP conducted a nationwide, controlled-access
Internet-based survey, with more than 1,500 U.S. respondents.
The sample was checked to ensure geographic, demographic,
and ethnic diversity; respondents came from every U.S. state
and had similar gender and race characteristics to the public
at large. The survey questions drew on previous research,
asking people how important weather is to them as well as
how they regard, interpret, and use forecasts.
Would you like probabilities
with that?
Thanks to the progress of weather research and the advent
of new technologies, there’s now a basis for creating
far more detailed forecasts, including shades of gray that
don’t fit into the usual template. For example, say
that forecasters predict a 20% chance that a cold front will
arrive soon enough to hold tomorrow’s high down to
70°F, but otherwise they expect temperatures to soar
to 85°F. How best to present these options in a single
outlook? This scenario made for one of the survey’s
more complex questions. More than 90% of the respondents
preferred something other than a flat forecast of 85°F,
and many liked knowing why the forecast was uncertain. Among
seven alternatives offered in the survey, this was the favorite
option: “The high temperature tomorrow will most likely
be 85°F, but it may be 70°F, because a cold front
may move through during the day.”

Left to right: Rebecca Morss, Julie
Demuth, and Jeff Lazo. |
People tend to read between the lines of deterministic
forecasts, those in which the uncertainty isn’t made clear. When
asked what a forecast high of 75°F actually means, the
largest share of respondents in the SIP survey (more than
40%) picked the range 73–77°F. Only about one in
twenty people took the 75°F forecast literally. “These
and other results show that most people have some understanding
of relative uncertainty in forecasts,” Julie says.
Several questions were designed to see how people might take
to different ways of presenting forecasts. When asked whether
they’d prefer a TV weathercaster who presents single-value
predictions (such as a high temperature of 75°F) versus
one who gives ranges (74–78°F), about twice as
many people (45%) chose the latter. About a quarter of the
respondents were comfortable with either choice.
“The majority of people liked information about uncertainty
in a forecast, and many preferred it, at least in the scenarios
we tested,” Julie says.
Several other lines of research are emerging from the survey.
For example, Jeff is leading an analysis of how much people
use and value the forecasts they now get. He says that the
average household gets forecasts 115 times a month. After
accounting for the few survey respondents who don’t
use forecasts, and extrapolating to the public at large,
this means that Americans access more than 300 billion forecasts
a year.
Follow-up work found that the median annual value placed
on forecasts was $285 per household, or about $32 billion
nationwide. Another line of research based on the survey
responses, with psychologist colleague Alan Stewart at the
University of Georgia, examines people’s weather salience—essentially,
how important weather is to them and their lives—and
how that relates to their use of forecasts.
As for the age-old question of whether it’ll rain on
tomorrow’s picnic, the study found that people interpret
a percentage verdict—“a 60% chance of rain”—in
many different ways. “Some of these interpretations
are more sophisticated than meteorologists might expect,” Rebecca
says.
As in most previous studies, only a small fraction of people
chose the explanation closest to the one typically used by
meteorologists: “It will rain on 60% of the days like
tomorrow.” The most popular choice: “60% of weather
forecasters believe that it will rain tomorrow.” Responses
to related survey questions suggest that, as Julie puts it, “most
people don’t know the technical definition of probability
of precipitation, but many seem to have built sufficient
understanding of it through experience.”
Analysis of the survey data is ongoing, and a variety of
interdisciplinary research questions in this area remain
to be addressed, according to the SIP team. It will take
several years for new types of forecasts to be developed,
possibly including innovations such as new icons to express
uncertainty. However, the results to date give SIP scientists
the sense that the public is ready for the next level of
weather predictions. Just as a motorist needn’t understand
every detail of a car’s engine in order to drive safely,
weather consumers should be able to draw added value from
new types of forecasts even if they never look under the
meteorological hood.•
On
the Web
NCAR
Societal Impacts Program
Completing the Forecast (2006 NRC report)
In this issue...
A
closer look at today’s forecast
Internship
programs gear up for summer
The
heart of winter
NCAR/UCAR
media office readies staff for interviews
Short
Takes
Just One Look
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