Climate Change eduCation through tV WeatherCasts

A field study shows that on-air and online education provided by a TV meteorologist over the

course of one year improved viewers’ understanding of climate change.

CLIMATE CHANGE EDUCATION

THROUGH TV WEATHERCASTS

Results of a Field Experiment

by Xiaoquan Zhao, Edward Maibach, JiM Gandy, JoE wittE, hEidi cullEn, barry a. KlinGEr,

athErinE E. rowan, JaMEs wittE, and andrEw PylE

AFFILIATIONS: Zhao, Maibach, Jo. wittE, KlinGEr, rowan, Ja.

wittE, and PylE—George Mason University, Fairfax, Virginia;

Gandy—WLTX, Columbia, South Carolina; cullEn—Climate

Central, Princeton, New Jersey

CORRESPONDING AUTHOR: Xiaoquan Zhao, Department of

Communication, Center for Climate Change Communication,

George Mason University, 4400 University Drive, MS 3D6,

Fairfax, VA 22030

E-mail: xzhao3@gmu.edu

The abstract for this article can be found in this issue, following the

table of contents.

DOI:10.1175/BAMS-D-12-00144.1

In final form 23 April 2013

he nation’s TV meteorologists and weathercasters

(more about the distinction can be found at

www.ametsoc.org/policy/guidline_term

_meteorologist.html)—the vast majority of whom

work in local TV—are a potentially important source

of informal science education about climate change

for a wide cross section of the U.S. population. Even

though digital news consumption has been steadily

increasing, particularly among young people (Pew

Research Center 2013a), many American adults ages

18 and older still regularly watch local TV news and

network TV news (Miller et al. 2006; Pew Research

Center 2013b); and the daily weather segment is a

perennial favorite among them (Pew Research Center

2013b; Silcock et al. 2006). Furthermore, TV weather

reporters are seen as a trusted source of information

about climate change by a solid majority (60%) of

adult Americans (Leiserowitz et al. 2012). Indeed, TV

weather reports are arguably one of the most com-

mon voluntarily sought forms of science education

in the daily lives of most adult Americans (Wilson

2008). Previous research suggests that weathercasts

can be an important and effective venue for informal

science education on a wide range of topics such as

geography (Earl and Pasternack 1991), public health

(Johnson 2009), and hurricane risk (Demuth et al.

2012).

According to the American Meteorological Society, “a

meteorologist is an individual with specialized education

who uses scientific principles to observe, understand,

explain, or forecast phenomena in Earth’s atmosphere and/

or how the atmosphere affects Earth and life on the planet.”

Individuals who lack formal education in the atmospheric

sciences but disseminate weather information and fore-

casts prepared by others are designated weathercasters.

In this article, we use the terms “meteorologists” and

“weathercasters” loosely to include both in our discussion

of using TV weathercasts as a conduit for informal science

education on climate change.

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January 2014aMErICan METEOrOLOGICaL SOCIETy

In this article, we describe an informal climate

science education initiative conducted by the chief

meteorologist at one local TV station in Columbia,

South Carolina (SC). Branded under the name

“Climate Matters,” this initiative intermittently pro-

duced and aired (during the weather segment, with

reposting to station’s website) brief educational seg-

ments using current weather events to educate viewers

about the local relevance of climate change. To evalu-

ate the impact of the first year of this programming,

we conducted viewer surveys in the Columbia media

market before the educational programming started

and again one year later. The primary outcomes of the

evaluation were perceptions, feelings, and knowledge

about climate change, which we broadly refer to in

this article as climate change beliefs.

BACKGROUND AND RATIONALE. The

problem. Although a solid majority of Americans

agree that “global warming is happening” (70% in

September 2012; Leiserowitz et al. 2012), public un-

derstanding of climate change is more limited. For

example, in fall 2012 only half of the American adult

population (54%) understood that the current global

warming is caused primarily by human activities and

only one-third (44%) understood that most scientists

are convinced that global warming is real.

The most current U.S. National Climate

Assessment (United States Global Change Research

Program 2009) found that a variety of climate

impacts, including rising temperatures and sea level,

changes in precipitation and seasons, and harms to

human and animal health, are already taking place in

every region of the nation. Yet, most Americans see

climate change as distant in both space (i.e., not in

the United States) and time (i.e., not now; Leiserowitz

2005). For example, in September 2012 only 48%

of adult Americans believed that global warming

would harm people in their community “a moderate

amount” or more and only 36% believed that people

in the United States were being harmed currently

(Leiserowitz et al. 2012).

Media-based climate change education. These low

levels of climate knowledge have motivated various

efforts to improve understanding. Some government

agencies, such as the National Aeronautics and Space

Administration (NASA) and the National Oceanic

and Atmospheric Administration (NOAA), have

contributed broadly to climate change education over

the years. But, for the most part, media-based educa-

tion efforts have been limited in scale and systematic

evaluation of their impact has been lacking (Akerlof

and Maibach 2008). Although the evidence is sparse

and mixed (e.g., Staats et al. 1996), at least some

large-scale campaigns do appear to have had some

influence on climate change–related beliefs, attitudes,

and behaviors (Akerlof and Maibach 2008; Cugelman

and Otero 2010; Tremblay et al. 2013).

News media coverage is another way that the

public can learn about climate change (Brulle et al.

2012; Russell 2008). Several studies have examined

the relationship between news consumption and

people’s understanding of climate change. A study

using data from 74 separate surveys over a 9-yr period

found that media coverage is an important influence

on public concern over climate change (Brulle et al.

2012). Another study showed that the news coverage

of climate science—even when satirized—can help

members of the public develop a more science-based

understanding of the issue (Feldman et al. 2011).

Research focusing on learning from digital news

sources is lacking. But one study did find that Internet

use in general contributed to perceived knowledge

and concern over global warming (Zhao 2009).

These positive findings make the paucity of research

on media campaigns and news coverage of climate

change both conspicuous and problematic (Maibach

et al. 2008).

The potential of news media–based climate change

education. Many professional communities routinely

study and use strategic communication as an asset in

their public education efforts (Abroms and Maibach

2008). Most notably in the public health commu-

nity, campaigns have been shown to contribute to

important improvements in public health outcomes

(Hornik 2002a). A brief review of what has been

learned in other fields provides a useful context as to

why TV meteorologists have considerable potential

as climate educators.

In any form of public communication, exposure

is a prerequisite for the intended effects (McGuire

2012). A meta-analysis of public health communica-

tion campaigns found a strong positive correlation

(r = 0.47) between reach—the percentage of the

audience exposed to campaign messages at least

once—and campaign effects (Snyder and Hamilton

2002). Yet, adequate exposure is often difficult to

achieve in media-based education efforts because

media campaign resources are often limited and

campaign messages have to compete with myriad

inconsistent and irrelevant messages in a cluttered

information environment (Hornik 2002b; Randolph

and Viswanath 2004). The nation’s broadcast meteo-

rologists, however, are exceptionally well positioned

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January 2014

to generate effective exposure locally and nationally.

Although an increasing number of Americans, par-

ticularly young people, are turning to the Internet and

mobile devices for their news, television remains a

dominant source of local information (Pew Research

Center 2013a,b). Approximately 70% of American

adults ages 18 and older watch local TV news at least

once a week (Miller et al. 2006; Pew Research Center

2013b) and their primary reason for doing so is to

learn about the weather (Pew Research Center 2013b;

Silcock et al. 2006; Smith 2007).

Apart from limited exposure, media-based

education campaigns may also face the problem of

limited public trust in the communicator (i.e., the

information source). A long tradition in commu-

nication research shows that trust in the source is

a critical factor in message effectiveness (Hovland

and Weiss 1951). Recent research in the specific

context of climate change also attests to the impor-

tance of trust in improving public understanding

of the climate change science (Malka et al. 2009).

It should be noted, however, that climate change is

one of the most controversial issues in public dis-

course in the United States today (Hulme 2009). In

issue contexts teeming with contradictory messages

and political strategizing, cynicism and distrust in

sources are likely to arise (Cappella and Jamieson

1997; Herreros and Criado 2008). While scientists

are the professional community that the public trusts

most about climate change (Leiserowitz et al. 2012),

there are several important limitations on scientists’

potential as climate educators. Public trust in scien-

tists has shown a general decline over the past few

decades, particularly among conservatives (Gauchat

2012). Perhaps more importantly, scientists have

relatively limited access to the public—few members

of the public can even name a single living scientist

(Research!America 2013). TV weathercasters, on the

other hand, have excellent access to a broad cross sec-

tion of the public on a regular basis (as documented

above). They also have outstanding credibility—they

are second only to research scientists and government

science agencies as trusted sources of information

about climate change (Leiserowitz et al. 2012).

Harnessing opportunities for experiential learning.

Cognitive science research has identified two parallel

interacting modes of information processing, one of

which is “slow” and effort based and the other is “fast”

and effortless (Kahneman 2011). The slow effortful

processing system is analytical, logical, and delibera-

tive, and it encodes reality in abstract symbols, words,

and numbers (such as the abstractions and statistics

of climate science). By contrast, the fast effortless

processing system is holistic, affective, and intuitive,

and it encodes reality in concrete images, metaphors,

and narratives linked in associative networks, often

derived from repeated patterns of direct experience.

“Experientially derived knowledge is often more com-

pelling and more likely to influence behavior than is

abstract knowledge” (Epstein 1994, p. 711). Likewise,

vivid, concrete information has a greater influence on

perceptions and inferences than does “pallid” (e.g.,

abstract and technical) information (Nisbett and

Ross 1980). Recent research has shown that people

who learn about climate change through personal

experience are much more likely to engage with the

issue (and seek more information) than people who

learn about it merely through exposure to analytical

(didactic) information (Leiserowitz 2006; Marx et al.

2007; Spence et al. 2011; Weber 2006, 2010).

Local TV weather reports provide a context and

conduit for experientially based climate change edu-

cation that offers distinctive advantages over tradi-

tional media campaigns. As discussed earlier, climate

change education embedded in local weather reports

is likely to reach large audiences both efficiently and

effectively. Local television meteorologists are also

a trusted source of global warming information for

many viewers. Severe weather provides powerful

experience-based opportunities for meteorologists to

educate their viewers about the relationship between

weather (e.g., extreme precipitation) and climatic

events (e.g., droughts) and climate change. While

the nature and extent of this relationship have been a

subject of ongoing investigation, there is evidence that

heat waves, droughts, hurricanes, and other extremes

have intensified and will intensify farther in the future

(Trenberth et al. 2007; United States Global Change

Research Program 2009; Knutson et al. 2010). Such

phenomena provide opportunities to help the public

understand the difference between weather and cli-

mate; how climate change affects extreme weather

events; how an individual extreme weather event can

never be wholly attributed to climate change, yet can

be consistent with climate trends and projections;

and how a series of extreme weather events in a wider

geographic context or longer temporal scale provides

evidence of global climate change (Friedman et al.

1999; Dessai et al. 2004; Doherty and Barnhurst 2009).

Moreover, from a learning perspective, many people

rely upon broadcast meteorologists to interpret and

respond to extreme weather events (Henson 2010),

which often generate strong emotional reactions and

which in turn can focus attention and support new

learning (e.g., Slovic et al. 2004).

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Large numbers of TV meteorologists are

willing and eager to adopt the role of climate

educator (Maibach 2012). This is consistent with

an expanded professional role (and identity) that

has been developed and promoted by the American

Meteorological Society over the past several years:

that of weathercaster as “station scientist” (Posegate

2008; Wilson 2009). It should be noted, however, that

TV meteorologists do not hold uniform positions on

climate change. Although a large majority of them

(82%) believe that global warming is happening,

many (63%) have doubts whether global warming

is primarily human caused (Maibach et al. 2011).

How to improve science-based understanding in the

meteorologist population at large thus is in itself an

important challenge (Nese et al. 2012).

DESIGN AND DELIVERY OF CLIMATE

MATTE R S . Education materials. In its first year, twelve

educational segments were produced and aired. The

core content for each segment consisted of a script and

supporting graphical materials. These were developed

by broadcast meteorologists, climate scientists, com-

munication scientists, writers, and graphic designers

from a number of collaborating institutions, including

George Mason University, Climate Central, and

WLTX TV in Columbia, SC. Scientific journals and

government websites [such as http://climate.nasa.gov

(NASA) and www.climate.gov (NOAA)] were utilized

as sources of climate science research and education

materials. The chief meteorologist at WLTX produced

each segment on the day it aired. Segments typically

ran about a minute and a half, including brief intro-

ductory comments. Each segment was self-contained,

focused on one or two related points, and connected

as much as possible to the experience of the viewers.

Seven of the segments addressed extreme weather

(and were intended for airing during or just after the

relevant extreme weather or climatic event) and five

addressed “evergreen” topics (and could be aired

anytime). The specific focus of each segment is pre-

sented in Table 1. Most of the segments explained

probable impacts of climate change on the weather,

environment, and people of the specific Columbia

area or South Carolina more generally. The goal was

for viewers to see that climate change was a real phe-

nomenon that could have real and noticeable effects

on matters they care about.

The extreme weather segments included varia-

tions on the relationship between global warming

Table 1. Climate Matters timeline and educational segments. Segment length is given in minutes and seconds.

Date Activity

11 May–15 Jul 2010 Baseline survey of panel sample

2 Aug 2010 Campaign began

Segment name Description (length)

2 Aug 2010

(again 8 Sep 2010)

High temperatures Increasing number of ≥95°F days as GHG emissions increase—separate

segment for each summer month (1:18).

12 Aug 2010 Extreme heat Increasing likelihood of ≥101°F days for today, 2040s, and 2070s (1:16).

25 Aug 2010 Climate Baseball statistics analogy explains difference between weather and

climate (1:54).

16 Sep 2010 Hurricanes Climate change may make hurricanes less frequent but more intense (1:30).

1 Oct 2010 Intense storms Climate change may be making intense rainfall more intense in the United

States (1:55).

12 Nov 2010 Sea level rise Rate of sea level rise along South Carolina coast may triple (1:54).

9 Mar 2011 Poison ivy More CO

may make some plant pests like poison ivy grow better (1:31).

22 Apr 2011 Human cause How we know greenhouse gas (GHG) increase is due to people (1:20).

12 May 2011 Air quality Connection between warmer temperature and code red smog days (1:07).

31 May 2011 Heat and human health Heat is already the top weather-related killer in the United States, and

GHGs will likely increase heat index in the Southeast (1:23).

9 Jun 2011 Drought Drought outlook to explain risk for increased drought in a warmer world

(2:23).

12 Jun 2011 Global weirding Global warming can cause opposite weather extremes (1:26).

10 Jul–30 Aug 2011 Follow-up survey of panel sample; survey of new cross-sectional sample.

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and heat waves and the connection of heat waves to

air pollution and heat-related fatalities. Other seg-

ments focused on drought, extreme precipitation

events, and hurricanes. Three of the evergreen seg-

ments also focused on impacts including sea level

rise, extreme weather events (of various kinds), and

increased potency of poison ivy. The other evergreen

segments focused on fundamental—and therefore

more abstract—explanations of climate and global

warming. (All of these segments can be viewed online

at www.wltx.com/weather/climate/default.aspx.)

Intervention delivery. The Climate Matters segments

began airing in evening newscasts in early August

2010, in response to current weather events. Columbia

experienced its hottest summer to date in 2010, and

many of the heat-related segments were aired then;

others were aired at appropriate times throughout

the year. Typically, but not in all cases, the segments

immediately preceded the weather forecast and

were set up by a news anchor creating a segue (such

as a question, or statement, about climate change)

responded to by the chief meteorologist. The seg-

ments were never advertised or used in teasers.

A Climate Matters section was created for the

TV station’s website. The website included climate-

related news stories, climate-related information from

the National Weather Service, a blog written by the

station’s chief meteorologist, and (after each educa-

tional segment was produced and aired) the Climate

Matters educational videos. The blog was mostly

related to the videos but occasionally also addressed

other important issues and research related to cli-

mate change. The blog was updated intermittently,

depending on availability of time and materials for

the chief meteorologist.

EVALUATION METHOD. Overview. The impact

of Climate Matters was evaluated using a quasi-

experimental design employing both panel and

cross-sectional surveys (see Table 1 for timeline).

The target population was adult local TV viewers 18

and older in the Columbia media market. Because

no prior research of this kind was available to guide

our power calculation, we determined sample sizes

based on the general assumption of a small learn-

ing effect. This assumption is consistent with the

typical effect size observed in public communication

campaigns in other domains (Snyder and Hamilton

2002). Availability of resources was also considered in

the determination of sample sizes. The target sample

size for the baseline survey of the panel was 1,000,

anticipating a 50%–60% retention rate at follow-up.

The target sample size for the cross-sectional survey

was 800.

To establish baseline measures, prior to the

intervention we conducted a telephone survey of

adult TV news viewers in the Columbia media market

using random digit dialing (RDD; N = 1,068). We

screened respondents based on the local news station

they watched most frequently to create a final sample

with similar numbers of WLTX viewers and viewers

of competing stations. Approximately one year later,

we resurveyed all available members of the baseline

cohort (n = 502), and we surveyed a new independent

sample of randomly selected residents (N = 910).

Each survey assessed a range of beliefs about global

warming. The follow-up surveys also assessed

exposure to Climate Matters. Learning effects were

investigated by examining the association between

exposure to Climate Matters and beliefs about climate

change in both the panel data and in the additional

cross-sectional data. Sample characteristics are sum-

marized in Table 2.

Survey administration. All surveys were conducted

using computer assisted telephone interviewing

(CATI) facilities. After training the interview staff

and pretesting the survey instrument with trial calls,

the baseline telephone interviews began 11 May 2010

and continued through 15 July 2010. The response

rate for the survey was 9.2% based on the American

Association of Public Opinion Research (AAPOR

2011) standard definitions (response rate 4). The

relatively low response rate is likely due to both gen-

eral and specific factors. In general, telephone survey

response rates have been declining for many years

(Curtin et al. 2005; Holbrook et al. 2007). Specific to

our survey, the interview was relatively long (approxi-

mately 25 min) and, as the baseline of a longitudinal

study, respondents were informed that the research

would involve a follow-up survey a year later. The

screening questions based on TV viewing habits

(see below) also led some potential respondents to

mistake our study for a marketing survey and refuse

to participate.

The follow-up interviews began in early July 2011.

Just under half (47%) of the respondents to the baseline

interviews completed a follow-up interview. Another

independent cross-sectional survey was also con-

ducted at the same time. Response rate for the cross-

sectional survey was 8.0% (AAPOR response rate 4).

Questionnaire. The questionnaire used in the base-

line, follow-up, and post-only surveys began with

screening questions to identify viewers of WLTX

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versus other local stations. Those reporting watching

news on WLTX at least once a week and not watching

news on any of the competing stations were desig-

nated as WLTX viewers in our analysis. Those report-

ing watching news only on non-WLTX stations were

labeled non-WLTX viewers.

The questionnaire then asked a series of questions

to assess beliefs and attitudes about global warming.

We chose to focus on global warming because it is a

familiar concept to the public and a central phenom-

enon in global climate change. Global warming was

also the underlying theme for most of the educational

segments used in Climate Matters. We assessed beliefs

about the certainty, human cause, and harms of global

warming as the primary outcomes of the evaluation.

Secondary outcomes included a number of additional

beliefs that could also be influenced by the interven-

tion even though they were not directly targeted.

These included worry, perceived importance, prior-

ity of the issue for the president/congress, timing

of harm, injunctive norm, and perceived scientific

agreement. Measurement details on these outcomes

are provided in Table 3. Response scales varied for

these measures in accordance with the nature of

the questions as well as the preference to use verbal

response options in a telephone survey.

Exploratory factor analysis of the secondary

outcomes (not including perceived scientific agree-

ment) showed that these variables all loaded on a

single underlying factor. This factor was able to

account for 61% of the variance among the variables

in the panel baseline data, 69% in the panel follow-

up data, and 62% in the cross-sectional data. These

variables were converted to standardized scores and

averaged into a general measure of concern over

global warming.

Table 2. Sample characteristics. Note that percentages do not always add up to 100% because of

missing data (as a result of refusal, no applicable answers, and/or recording error).

Panel sample (N = 502) Cross-sectional sample (N = 910)

Unweighted

percentage

Weighted

percentage

Unweighted

percentage

Weighted

percentage

Gender

Male 31.9 47. 3 34 47

Female 67.7 52.3 66 53

Race

White 62.7 55.1 60.2 59

Black 30.7 39.6 33.7 37

Other 4.8 3.5 5 3.2

Age

18–34 9.8 33.9 14.8 32.5

35–44 10.8 19.4 14.2 20.9

45–64 47.6 29.9 43.6 29.2

65 and above 30.9 15.8 26 16.2

Education

Less than high school 11.6 19 8.2 18.1

High school graduate 20.9 26.2 21.9 28.7

Some college 28.3 26.8 29.2 28.3

Bachelor’s degree 18.5 18.8 21.5 16.7

Graduate or professional degree 19.3 7.7 18.5 7.8

Political Party

Republican 28.5 25.4 24.1 25.7

Democrat 33.3 36.6 34.7 31.2

Independent 20.5 17.7 21 18.5

Other 12.8 16.2 16.5 19.9

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In the follow-up and independent cross-sectional

surveys, exposure to Climate Matters was measured.

Respondents were asked whether in the past year they

had seen any special segments during the local weather

forecast that focused on global warming or climate

change. Response to this question (yes vs no and not

sure) was taken as a measure of general campaign

awareness. Respondents were also presented with brief

descriptions of four educational segments and asked to

indicate whether they remembered seeing each of them

on TV. These four segments were randomly selected

from the twelve that aired. The number of affirmative

answers was treated as a measure of recognition.

Background information on the respondents was

gathered at the end of the questionnaire. In addi-

tion to basic demographics (gender, race, age, and

education), we also asked questions about political

party (Republican, Democrat, or Independent/other)

and political ideology [1 (very liberal) to 5 (very

conservative)].

Analysis strategy. With a series of regression analyses,

we tested two hypotheses.

• H1: WLTX viewers will demonstrate greater

learning gains than will viewers of other stations.

• H2: Regardless of initial station preference, viewers

with more exposure to Climate Matters will dem-

onstrate greater learning gains than viewers with

less exposure.

WLTX viewership was used as the independent

variable to test H1, and Climate Matters awareness

and recognition were used as independent variables

to test H2. Global warming beliefs served as the

dependent variables.

These analyses were conducted on both the panel

sample and the post-only cross-sectional sample. In

all analyses, we controlled for a range of demographic

and political background variables, including gender,

age, race, and education, as well as political party and

Table 3. Key outcome questions in the evaluation surveys.

Questions Coded responses

Primary outcomes

Certainty Do you think that global warming is happening?

How sure are you that global warming is (is not)

happening?

-4 (complete certainty that global warming is not

occurring) to 0 (not certain/do not know) to

4 (complete certainty that global warming is

occurring)

Human causation Assuming global warming is happening, do you

think it is . . .

0 (not happening or caused mostly by natural

changes in the environment) to 1 (caused mostly

by human activities)

Harm extent How much do you think global warming will harm

you personally/future generations of people (two

items, α

panel

= 0.84 and α

x-sectional

= 0.75)

1 (not at all) to 4 (a great deal)

Secondary outcomes

Concern Average of worry, importance, priority, harm timing, and injunctive norm after converting each to

Z scores (α

panel baseline

= 0.81, α

panel follow-up

= 0.87, and α

x-sectional

= 0.82)

Worry How worried are you about global warming? 1 (not at all worried) to 4 (very worried)

Importance How important is the issue of global warming to

you personally?

1 (not at all important) to 5 (extremely important)

Priority Do you think global warming should be a low,

medium, high, or very high priority for the

president and congress?

1 (low) to 4 (very high)

Harm timing When do you think global warming will start to

harm people in the United States?

1 (never) to 6 (now)

Injunctive norm Do you think citizens themselves should be doing

more or less to address global warming?

1 (much less) to 5 (much more)

Perceived scientific

agreement

Which comes closer to your own view? 0 [consensus not understood (a lot of

disagreement among scientific or most scientists

think global warming is not happening, or do not

know enough to say)] to 1 [consensus understood

(most scientists think global warming is happening)]

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ideology. In the panel analysis, we also controlled

for the outcome belief at baseline. The panel analysis

essentially assessed the change in the outcome vari-

able over time as a function of campaign exposure

and other control variables. The cross-sectional

analysis, on the other hand, examined the contem-

poraneous relationship between the current outcome

and campaign exposure. For both analyses, statistical

significance was set at p < 0.05 (i.e., when the prob-

ability of observing an effect by chance is less than

5%). When the outcome variable was continuous

(or treated as such, e.g., certainty), we used multiple

linear regression. When the outcome variable was

dichotomous (e.g., human causation), we used logistic

regression.

To facilitate understanding, we report predicted

values (for multiple linear regression) and predicted

probabilities (for logistic regression) instead of regu-

lar regression coefficients. These results are presented

with respect to specific groups (e.g., WLTX viewers

versus non-WLTX viewers) and can be compared to

see how the intervention did (or did not) influence

the outcomes, while assuming no group differences

on the control variables.

RE S ULTS . Longitudinal analysis. Before conducting

the final analysis, we examined the comparability of

panel sample participants who completed the follow-

up survey to those who did not. The two groups

were not significantly different with regard to race

(p = 0.26), political party membership (p = 0.10), edu-

cation (p = 0.87), income (p = 0.80), or WLTX viewer-

ship (p = 0.42), although there were between-group

differences on gender (p = 0.04) and age (p < 0.001).

Men (57.8%) were slightly more likely than women

(51.1%) to drop out of the study, and participants

younger than 45 (64.5%) were more likely than those

45 and older (49.2%) to drop out. While these differ-

ences deserve attention, they do not appear to suggest

a strong confounding factor for intervention effects

because gender and age were not strongly correlated

with the outcome variables (most correlations were

around 0.10). At the same time, the fact that the

other variables, particularly WLTX viewership and

party membership, did not vary significantly between

retained and lost cases further alleviates concerns

that attrition might work to bias evaluation results.

Other preliminary analysis revealed that news sta-

tion viewership in the Columbia media market was

not stable during the study period. Notably, among

those who reported never watching WLTX for local

news at baseline, more than half (59.6%) reported

watching WLTX at least once a week for local news

at follow-up. On the other hand, only 7.3% of WLTX

viewers at baseline reported never watching WLTX

at follow-up. To account for the significant shift of

viewership, particularly from non-WLTX viewers to

WLTX viewers, we created a new viewership vari-

able with three categories: persistent WLTX viewers

(n = 231), new WLTX viewers (n = 146), and persistent

non-WLTX viewers (n = 99).

This new viewership

variable was used in all subsequent analysis.

Results of the final regression analyses with

panel data are summarized in Table 4. The panel

data show some—but not full—support for the two

hypotheses among the primary outcome variables.

All else controlled to be equal (including the baseline

values of the outcome measures), new WLTX viewers

were more likely to believe at follow-up that global

warming was primarily human caused than non-

WLTX viewers (53% vs 41%, p < 0.05); those who

recognized more stories from Climate Matters were

more certain that global warming was happening

compared to those who recognized fewer (2.01 for

four stories vs 1.39 for zero stories, p < 0.05); and

those who remembered seeing Climate Matters in

local news saw greater harm of global warming than

those who did not (3.04 vs 2.74, p < 0.01). No other

relationships between campaign exposure and the

primary outcomes were significant.

There is also some support for both hypotheses

among the secondary outcome beliefs (presented

in the bottom half of Table 4). All else being equal,

those who were aware of Climate Matters were more

concerned about global warming at follow-up than

those who were not (0.09 vs –0.04, p < 0.05). Those

recognizing more Climate Matters stories were

more concerned (0.16 for four stories vs –0.08 for

zero stories, p < 0.05) and more likely to believe that

scientists are in agreement regarding the reality of

global warming (55% vs 22%, p < 0.01) than those

recognizing none. Persistent WLTX viewers were

also more concerned about global warming than non-

WLTX viewers (0.02 vs –0.10), but this difference did

not reach statistical significance (p < 0.10). No other

relationships in the regressions were significant.

Cross-sectional analysis. With two differences—WLTX

viewership only having two categories (WLTX

viewers vs non-WLTX viewers) and no control for

WLTX viewers at baseline who reported not watching WLTX at all at follow-up were excluded from data analysis for their

small number (n = 18).

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January 2014

baseline—all of the analyses described above were

replicated with the cross-sectional (post only) data.

Results from these analyses are summarized in

Table 5.

These analyses show more consistent support for

the hypotheses. After holding potential confounders

constant, WLTX viewers were more certain about the

occurrence of global warming (1.73 vs 1.35, p < 0.05)

and perceived greater harm from it (2.84 vs 2.63,

p < 0.01) than non-WLTX viewers, but the two groups

did not differ on the belief about the human cause

of global warming. As far as exposure is concerned,

compared to those who did not remember seeing

Climate Matters, those who did were more certain

that global warming was happening (1.96 vs 1.45,

p < 0.01), more likely to believe that global warming

was primarily human caused (45% vs 36%, p < 0.05),

and perceived greater harm of global warming

(2.93 vs 2.67, p < 0.01). Compared to those recognizing

fewer stories from Climate Matters, those recognizing

Table 4. Panel analysis results—predicted values or probabilities.

Viewership Campaign exposure

Non -WLT X Persistent WLTX New WLTX ΔR

Awareness Recognition

ΔR

No Yes

Zero

stories

Four

stories

Primary outcomes

Certainty

1.47 1.70 1.46 0.002/0.54 1.46 1.85* 1.39 2.01* 0.01/0.55

Human causation

41% 45% 53%* 0.01/0.38 38% 26% 35% 38% 0.01/0.37

Harm extent

2.80 2.76 2.84 0.001/0.51 2.74 3.04** 2.75 2.94 0.02/0.53

Secondary outcomes

Concern

-0.10

0.02

-0.01

0.001/0.70

-0.04

0.09*

-0.08

0.16* 0.01/0.70

Perceived scientific

agreement

33% 36% 35% 0.00/0.21 29% 24% 22% 55%** 0.02/0.23

Note that

p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001. All analysis is controlled for gender, age, race, education, political party,

ideology, and baseline outcome.

ΔR

represents additional variance explained by the independent variables after control variables are

already entered into the regression model.

Numbers are predicted values of the outcome variable. The R

values are adjusted R

values from multiple linear regression.

Numbers are predicted probability of answering yes to the outcome question. The R

values are Nagelkerke R

values from logistic

regression.

Table 5. Cross-sectional analysis results—predicted values and probabilities.

Viewership Campaign exposure

Non -WLT X WLTX ΔR

Awareness Recognition

ΔR

No Yes Zero stories Four stories

Primary outcomes

Certainty

1.35 1.73* 0.01/0.15 1.45 1.96** 1.14 2.83*** 0.05/0.20

Human causation

38% 38% 0.00/0.07 36% 45%* 37% 40% 0.01/0.08

Harm extent

2.63 2.84** 0.01/0.15 2.67 2.93** 2 .61 3.07*** 0.03/0.16

Secondary outcomes

Concern

-0 .11

0.03** 0.01/0.18

-0.10

0.21***

-0.18

0.43*** 0.07/0.24

Perceived scientific

agreement

26% 43%*** 0.03/0.10 31% 43%** 27% 58%*** 0.05/0.11

Note that * p < 0.05, ** p < 0.01, *** p < 0.001. All analysis is controlled for gender, age, race, education, political party, and

ideology.

ΔR

represents additional variance explained by the independent variables after control variables are already entered into

the regression model.

Numbers are predicted values of the outcome variable. The R

values are adjusted R

values from multiple linear regression.

Numbers are predicted probability of answering yes to the outcome question. The R

values are Nagelkerke R

values from logistic

regression.

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January 2014aMErICan METEOrOLOGICaL SOCIETy

more stories were more certain about global warming

(2.83 for four stories vs 1.14 for zero stories, p < 0.01),

and saw greater harm from it (3.07 for four stories vs

2.61 for zero stories, p < 0.001), but they did not differ

on their perceptions about human cause.

Full support of the hypotheses was obtained

with the secondary outcomes. WLTX viewers were

more concerned about global warming (0.03 vs

–0.11, p < 0.01) and more likely to perceive scientific

agreement (43% vs 26%, p < 0.001) than non-WLTX

viewers. Those aware of Climate Matters were more

concerned (0.21 vs –0.10, p < 0.001) and more likely

to think scientists were in agreement (43% vs 31%,

p < 0.01) than those who were not. Similarly, those

who recognized more stories from Climate Matters

were more concerned (0.43 for four stories vs –0.18

for zero stories, p < 0.001) and more likely to report

scientific agreement (58% for four stories vs 27% for

zero stories, p < 0.001) than those who recognized

fewer stories.

DISCUSSION. Overall assessment. Our evaluation

of Climate Matters showed supportive evidence of

educational effectiveness, although the results did

not fully support our two hypotheses. For this reason,

the findings of this study should be read with care,

and the impact of the tested intervention strategy

should not be overstated. But still, the general results

of this study were consistent with our expectations.

Compared to non-WLTX viewers, WLTX viewers—

both loyal followers and recent converts—tended

to hold beliefs that were more consistent with the

climate science. Furthermore, regardless of their

station preference, viewers who reported exposure

to and recall of Climate Matters were also more

likely to report science-based beliefs and concern over

global warming. This pattern of findings—which are

consistent with experiential learning theory—was

observed in both the panel data and the independent

cross-sectional data. The panel analysis controlled

for baseline values of the outcome measures, which

strengthens the case that the intervention produced

the changes in the outcome measures that were

documented. The cross-sectional analysis does not

allow for causal interpretation. But to the extent that

it showed the same pattern of associations as the panel

analysis, we consider its findings further evidence

that the intervention had produced the intended,

favorable impact on its target audience.

In total, this evidence suggests that Climate

Matters was a successful informal climate change

education effort. Through Climate Matters, we sought

to explain a problem that is normally considered

remote, complex, and confusing in a form (in terms

of both content and medium) that is proximate, con-

crete, and trustworthy. By connecting local weather

patterns, particularly extreme local weather events, to

global climate change through local TV weathercasts,

our intervention appears to have helped viewers in

Columbia, SC, better understand the causes, pro-

cesses, and impacts of climate change.

Limitations of evaluation study and evidence. Before

reflecting on the Climate Matters experience any

further, it is important to note some of the limitations

of the evaluation. Most important, perhaps, is the

fact that TV viewership in Columbia, SC, turned out

to be much more fluid than we expected. More than

half of the non-WLTX viewers identified at baseline

reported watching WLTX at least once a week in

the follow-up survey. This indicates considerable

cross-contamination between the intervention and

comparison groups in our study design. Although

we took this into account in our data analysis, the

ability of our tests to detect differences between the

intervention and comparison groups was still lower

than planned because of the contamination and loss

of sample size in the comparison group. Whether

such fluidity in viewership is unique to Columbia,

SC, or reflective of a broad market phenomenon is not

clear. Audience tracking data from a variety of differ-

ent markets, if available, might help to ascertain the

generality of the problem. Second, and related to the

point above, because this study was the first to test our

informal science education approach in a local media

market, the extent to which the findings of this study

might also apply to other markets in the United States

is not clear. Third, our surveys had fairly low response

rates, which carried increased risk of sample biases.

Higher response rates would enhance confidence in

the accuracy of our findings.

Moreover, our findings did not fully support

our hypotheses. First, not every outcome variable

showed a statistically significant effect—particularly

in the panel analysis. Second, the amount of variance

explained by the independent variables was generally

small. It is possible that other important and more

sensitive outcome variables might have been left out

in our evaluation. For these reasons, it is inadvisable

to overstate the impact of the intervention. But at the

same time, it should be noted that almost all of the

relationships observed in our analyses, significant

or not, were in a direction that indicated positive

learning effects. Furthermore, to remove the influ-

ence of many potential confounders, we controlled for

a large number of variables in the data analysis that

126

January 2014

limited the amount of variance available for the in-

tervention variables to explain.

This was particularly

the case in the panel analysis, where we controlled for

the baseline levels of the outcome measures; those

measures alone would account for the majority of the

variance in the outcomes at follow-up. Given this level

of control, it is indeed impressive that the intervention

variables were able to consistently explain additional

variance in the outcome variables.

Recognition of the limits of the evaluation and

the strengths of the evidence obtained helps put the

appraisal of Climate Matters in a proper perspective.

Despite the issues discussed above, the evidence

overall is clear and strong enough to warrant the

conclusion that Climate Matters was a successful

intervention. In what follows, we discuss lessons

learned in this intervention, both in terms of what

was done well and what could have been improved.

Our hope is that future efforts using this approach to

climate education can be strengthened by learning

from the current case.

Lessons learned. By using a local meteorologist as

its message source and local weather reports as the

conduit for message delivery, Climate Matters was

able to reach its target audience with both efficiency

and effectiveness. This laid the important foundation

for the intervention to achieve its goals of enhancing

knowledge and changing attitudes and beliefs related

to climate change. Noted, however, that digital news

consumption has been increasing, particularly

among young people (Pew Research Center 2013a),

Climate Matters tried to reach digital news consum-

ers through web posting of videos, blogs, Facebook,

and Twitter. But these efforts were of a supplemental

nature and the extent of their independent impact

was uncertain.

One major obstacle to weathercasters reporting

on the climate science is the lack of time for field

producing (Maibach et al. 2010). Field producing is a

full time job and the weathercaster’s days are already

filled with myriad duties in addition to broadcasts

including web positing, blogging, tweeting, and

community visits. Moreover, there are few rewards

for the extra time required to become a competent

science reporter or climate educator. The team-based

approach we used to research and produce stories for

Climate Matters can take the burden off the shoulders

of local TV meteorologists. This type of support can

make it more feasible for weathercasters to embrace

the role of climate educator, should they wish to.

Time on air is a second major obstacle to reporting

on climate change. We encountered this obstacle

directly and in a variety of ways in Climate Matters

(including the fact that morning broadcasts—in

which weathercasts are more compressed—proved

not to fit the approach we developed). The develop-

ment of shorter length materials—that can be pro-

ductively used in 10–20 seconds—may result in more

time on air for climate education throughout the day.

Climate Matters also had other challenges during

implementation. The station switched to a new

weather graphics system immediately prior to the

launch of Climate Matters and to high definition TV

at the end of 2010, both of which caused temporary

interruptions in the ability to produce and air Climate

Matters segments. Breaking news events—including

some weather-related news events—precluded airing

several segments on their originally scheduled dates.

And renovations to the station’s website took the

meteorologist’s blog offline for nine weeks, although

the Climate Matters page remained up and active.

In short, broadcast news is a dynamic and changing

environment where even the best laid plans will

be challenged. Indeed, most of the challenges we

experienced in Climate Matters were unanticipated.

Hopefully, the experience of climate education “early

adopters” can be leveraged to help anticipate and

identify solutions to these challenges.

Finally, the evaluation of Climate Matters exem-

plified the many difficulties one might encounter in

conducting such a large-scale field study. Although

considerable care was exercised in designing the study

and data collection, the quality of our data was still

compromised by an unexpected shift in viewership

and low survey response rates. As a result, our find-

ings should be considered strongly suggestive but not

definitive; additional research in other markets and

populations is warranted. Future evaluation research

should be aware of the limitations of this study and

find creative ways to overcome them.

One method to strengthen the current design is

to conduct the experiment across several comparable

media markets, with the meteorologist-led education

campaign launched in some markets but not others.

The two groups of markets will be compared both at

baseline and again at a follow-up point. Increased un-

derstanding and concern about climate change over

It should be noted that the control variables included in our analysis are mostly demographic variables. Obviously, what

viewers learned from Climate Matters was not the only knowledge they possessed. How viewers’ existing knowledge and

attitudes might influence their reception of climate change education messages is an interesting topic for future research.

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January 2014aMErICan METEOrOLOGICaL SOCIETy

time in the treatment markets relative to the control

markets will provide strong evidence for the effective-

ness of the educational intervention. This design will

also effectively get around the problem of viewership

shift within individual markets that was the cause

of some ambiguity in the current data. In addition

to replicate this study with more rigorous designs,

researchers should also complement large-scale quan-

titative testing with small-scale highly contextualized

qualitative research. By conducting ethnographic

observations, in-depth interviews, focus groups, and

so forth, a more nuanced understanding of how the

current educational approach might work among the

local TV audience can be obtained, which will, in

turn, inform further implementation of this educa-

tion method in other and broader contexts.

CONCLUSIONS. Using an experiential learning

approach, Climate Matters was an innovative educa-

tional initiative that tried to leverage both the proxim-

ity of local weather events and the credibility of local

TV meteorologists to educate the public about the

relationships among weather, climate, and climate

change. Our evaluation found some evidence for the

effectiveness of this new climate education model.

Further research and development of this educational

method appears to be warranted.

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