Integrated Social Science-Weather Research Julie L. Demuth – jdemuth@ucar.edu National Center for...

Integrated Social Science-Weather

ResearchJulie L. Demuth – jdemuth@ucar.edu

National Center for Atmospheric Research, Societal Impacts Program

Colorado State University, Dept. of Journalism and Technical Communication

13 June 2012

Ex. 1 Q: “According to the forecast, what is the chance there

will be 1 inch of snow in the period from noon to 6 pm on Feb 28?”

Ex. 2 -- Marion’s story

“Then the 2nd siren warning went off … then I took notice and I decided this is something serious. And my son-in-law next

door … called me, and he at that point was concerned”

“We were going to stay there in a closet … but then he went out and looked and he saw the tornado coming, and he said

we’re going over to the storm cellar. And that’s what we did.”

“I didn’t consider doing that earlier because it’s an old storm cellar and I myself could not have gotten into it because the

door is so heavy—it’s a steel door. But he could.”

“I’ve lived here for 36 years … and we hadn’t ever used [the storm cellar] before.”

About me

School BS and MS in meteorology Pursuing my PhD in risk communication

Career path From remote sensing of hurricanes (@ CSU) … to science

policy (in DC) … to hospice (almost) … to my passion, integrated social science-weather research

I love… My job, hiking and backpacking, animals, IPA and trippel

beers, Italian red wine, snowshoeing, music, scotch, sunshine, mountains, clouds, sparking water, cappuccinos and coffee, painting, pizza, bouldering, the number 422, laughing, weather, my family and friends, hospice, … and so much more!

Social sciences

The study and understanding of human cognition, behavior, and culture Atmospheric scientists are

humans too!

Social scientists follow the scientific method. We have theories, concepts, conceptual models … but they’re dynamic.

vs.

Observation

Theory

Hypothesis

Data collection

Data Analysis

Findings

dp = -rgdz

Example theoretical model

Extended Parallel Process Model – Kim Witte et al. 1996

Social sciences: Disciplines & methods

“Social sciences” is an umbrella term referring to many fields, similar to “physical/natural sciences” Anthropology Communication Economics Education

Qualitative and quantitative approaches Interviews Surveys Focus groups Experiments

Human geography Sociology Psychology

Content analysis Direct observation Participatory activities

Some of “My” (Collaborative) Research

#1: Creating & communicating hurricane risk information (CHI) Jointly funded NSF-NOAA grant Study goals

Better understand how hurricane warning message content is generated through different actors

Help improve the content and process of hurricane risk communication to promote effective decision-making

Focus on the communicators!

CHI – methods

Greater Miami area (parallel study in Houston area) Semi-structured interviews

5 forecasters (3 NHC, 2 WFO) 2 emergency managers 9 media from 4 TV and 4 radio stations (including non-

English-speaking) Observational sessions with forecasters as they

created mock hurricane forecast products Follow-on survey of the public

CHI – partnership results

3 groups have different roles and specialties, orientations, and environments

3 groups have common, overarching goals to (1) save lives and (2) reduce injury, property loss, economic disruption, and overall harm

“I couldn’t do my job without [the NHC and WFO]. … With the hurricane, I don’t have the tools, the data, and the knowledge that they do … so I rely on them almost 100% for info that I’m getting. … I’m an extension of them to get out their hard work.” (Media)

CHI – challenges re: NWS products

Challenge for media to easily extract needed info“Those [products] are unwieldy … and you have to ferret through all of this stuff that gets mixed in together.” (Media)

Scientific and technical content can be confusing “Sometimes scientists speak like scientists and not like people. You know, some people don’t know what low pressure means, what high pressure means, and some people don’t know and don’t care what millibars are. They don’t care … They want to know three things: what does it mean to them, what does it mean to their family, and what do they need to do right now. And so don’t speak like a meteorologist. Tell me what we need to know. … I can’t tell you in the middle of an emergency how many times we’ve looked at each other in the news room and said, “Well, that was no help whatsoever,” because we couldn’t get numbers, specifics, what the public needed to know at that moment.” (Media)

CHI – challenges re: uncertainty

EMs account for hurricane forecast uncertainty by being conservative, assuming higher-end scenario

NWS forecasters sometimes think EMs don’t want uncertainty if they don’t use specific NWS info

“We say, ‘When [the hurricane] comes straight nonstop and it intensifies,’ that’s how we plan for the uncertainty.” (EM)

“[Emergency managers] typically don’t like probabilistic. They usually get frustrated and don’t want to mess with it.” (NHC forecaster)

All results available via AMS early online release:Demuth, Morss, Morrow, and Lazo, 2012: Creating and Communicating Hurricane Information. Bulletin of the American Meteorological Society, in press.

Theoretical applications to weather!

Remember the Extended Parallel Process Model Self efficacy, response efficacy Susceptibility and severity Fear appeals

#2: Assessing and improving NWS point-and-click webpage (ForAAG)

Weather.gov is the face of NWS NWS point-and-click (PnC) page

is a key channel for conveying local forecasts, including hazardous weather forecasts

Overarching goalConduct robust, representative

research to guide NWS policy changes for improving communication effectiveness of PnC forecast

information

ForAAG methods

Experimental design in a survey Manipulate variables (holding

everything else constant) then measure an outcome then examine the effect

Allows for causal inference Separate designs for short-fused

and long-fused threats

1st haz wx survey (short-fused event)

2 x 2 x 2 factorial design – 3 information pieces (variables) each with 2 levels (with/without) Box – to convey threat timing and existence Bar – to convey threat timing and existence Until text – to convey threat end time

Total of 8 different designs; each respondent gets only 1

No Box BoxBar No Bar Bar No Bar

Until Forecast 1 Forecast 2 Forecast 3 Forecast 4

No until Forecast 5 Forecast 6 (status quo/control) Forecast 7 Forecast 8

Short-fuse – Severe t-storm warning

Results The punchline

Current forecast (status quo) poorest overall Bar not effective (!) in helping people notice the

threat, understand timing, and not perceived favorably Until text mostly effective; exception is it seems to

make people think the threat is already in effect Box mostly effective; minor hiccup is may be

confusing some people about the threat end time when coupled with the “until” information

2nd haz wx survey

Prob forecast – understanding Q: “According to the forecast, what is the chance there will be 1

inch of snow in the period from…” (for 6-hr prob) “…noon to 6 pm on Feb 28?” (for 12-hr prob) “…6 pm Feb 28 to 6 am Feb 29?”

60%95%

Understanding responses Poor understanding overall

Less than ½ of respondents answer correctly Nearly ¼ indicate they don’t know

n=3717

n=3747

Take home thoughts from a meteoro-communic-ologist

Information in action out

Forecast & response

information

(watch, warning, media message,

EM message, multi-media

briefing)

People’s interpretation

& response

Mediating & moderating variables!

Most people respond; very few outright reject/ignore the warning…but “response” is complex and NOT just about weather

Recognize and work within this reality

We make lots of assumptions

That people …are complacent …ignore threats due to false alarms …feel overwarned …have an “ideal” warning lead-time …should be highly literate about weather information

These are empirical questions and they vary based on the weather situation!

Atmos + soc sciences

Humans are like the atmosphere … both are nonlinear and dynamic, but there are common patterns

We each have our own focused area of expertise … it behooves us to recognize that and work with others

There are a LOT of exciting research problems that fall at the interface of weather/climate and society

jdemuth@ucar.edu