Download David Retchless, PhD candidate [email protected] Paper #GC43B

Mapping Climate Change Uncertainty: Effects on Risk Perceptions and Decision Making
David Retchless, PhD candidate
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Paper #GC43B-1024
III. Maps: Bivariate
I. Research Questions:
•
[email protected]
Texture – Spots
Which maps of temperature change and uncertainty are easiest to
understand?
Do map users combine magnitude and certainty of change when:
– assessing risks?
– making decisions?
Which maps do users prefer?
Texture – Squares
Transparency –
Unclassed
Texture – Lines
HUE
(Yellow to Red)
HUE
(Yellow to Red)
HUE
(Yellow to Red)
HUE
(Yellow to Red)
II. Methods
VALUE
(Light to Dark)
VALUE
(Light to Dark)
VALUE
(Light to Dark)
VALUE
(Light to Dark)
•
•
Texture
(Noisy to Ordered)
Texture
(Sparse to Solid)
Texture
(Dense to Sparse)
CHROMA
(Gray to Vivid)
•
•
Survey: Mechanical Turk & Survey Gizmo
4 Ranking Questions, each ranking 7 map regions
– Temperature change
UNDERSTANDING
– Certainty (signal/noise,
TEMPERATURE
described as precision)
AND CERTAINTY
– Harm to environment
COMBINING
– Suitability for nature reserve
TEMPERATURE
(given temperature requirements)
AND CERTAINTY
274 respondents,
randomly assigned
1 of 20 maps:
– 10 types of maps
– 2 emissions scenarios
(high & low)
– ~14 respondents/map
– Data from CMIP5
Note: Based on Figure SPM.7, WG 1, IPCC AR4 (2007).
Color –
Yellow/Purple to
Gray
Transparency Classed
Color – Blue/
Red to White
Color – Yellow/
Purple to Light
HUE
(Yellow to Red)
HUE
(Yellow to Purple)
HUE
(Yellow to Purple)
HUE
(Blue to Reddish
Purple)
VALUE
(Light to Dark)
VALUE
(Light to Dark)
VALUE
(Light to Dark)
VALUE
(Light to Dark)
CHROMA
(Gray to Vivid)
CHROMA
(Gray to Vivid)
CHROMA
(Gray to Vivid)
CHROMA
(Gray to Vivid)
HIGH: RCP 8.5
LOW: RCP 4.5
Note: Based on Kaye et al. (2011).
III. Maps: Controls
V. Results: Ranking Certainty
VI. Results: Ranking
Environmental Harm
Based on the map, rank the regions (A-G) from highest overall certainty (#1) to lowest overall certainty
(#7). Your ranking should be based on the average certainty over the entire extent of each region.
Median Certainty Ranks, Weak Performers
1
2
2
Median Environmental Harm Ranks
Control
Texture - Squares
3
3
Color - Yellow/Purple to Gray
Texture - Spots
4
Color - Blue/Red to White
2
Texture - Lines
Color - Yellow/Purple to White
5
1
Control w/ Small Map
Rank
Rank
IV. Results: Ranking Temperature Change
Transparency - Classed
Control
Objective Temperature
5
6
6
7
A
F
G
C
B
D
E
4
5
A
F
G
C
B
D
Control w/ Small Map
Texture - Squares
E
Texture - Spots
3
Texture - Lines
Texture - Squares
Transparency - Unclassed
Texture - Lines
Transparency - Classed
7
Control
Texture - Spots
3
Rank
Objective Temperature
2
Control w/ Small Map
Objective Certainty
Objective Certainty
Based on the map, rank the regions (A-G) from largest overall increase
in temperature (#1) to smallest overall increase in temperature (#7).
Your ranking should be based on the average temperature increase
over the entire extent of each region.
Median Reserve Suitability Ranks
1
Transparency - Unclassed
4
Scientists would like to create a nature reserve in
a region (A-G) where temperatures across the
entire region are likely to increase by less than 4
°F by 2100. Based on the map, rank the regions
from most suitable (#1) to least suitable (#7) for
the nature reserve.
Rank
Control with Small
Certainty Map
Control (Temperature Only)
Based on the map, which regions (A-G) will likely
experience the most extensive harm to plants
and animals over the next 100 years? Rank the
regions from most extensive harm (#1) to least
extensive harm (#7).
Median Certainty Ranks, Strong Performers
1
VII. Results: Ranking
Reserve Suitability
Transparency - Unclassed
4
Color - Yellow/Purple to Gray
Transparency - Classed
Color - Yellow/Purple to Light
Color - Yellow/Purple to Gray
Color - Blue/Red to White
5
Color - Yellow/Purple to Light
Color - Blue/Red to White
Objective Certainty
6
Objective Temperature
Objective Certainty
6
Objective Temperature
7
C
Median Temperature Ranks
D
G
F
A
E
7
C
1
VIII. Results: Correlations (Kendall’s tau-b)
B
D
G
F
A
E
IX. Results: User Preference
Texture - Spots
2
Control
5.37% 1.24%
Control w/ Small Map
Texture - Spots
3
Color - Blue/Red to
White
6.61%
Texture - Squares
Rank
B
Texture - Lines
4
Transparency - Unclassed
32.23%
7.44%
Transparency - Classed
Color Yellow/Purple to
Gray
Transparency Classed
Color - Yellow/Purple to Gray
5
Color - Yellow/Purple to Light
7.85%
Color - Blue/Red to White
6
Objective Temperature
Color Yellow/Purple to
Light
Texture - Squares
8.26%
7
C
B
D
G
F
A
Transparency Unclassed
E
16.94%
14.05%
Texture - Lines
X. Conclusions
• Temperature ranking was easy, uncertainty
ranking was hard.
• Consistent with MacEachren et al. (1998),
texture outperformed color for uncertainty
ranking.
• Best maps for uncertainty ranking: Control
w/ small map, Texture–Lines, Texture–Spots
• Magnitude was primary driver of risk
assessment and decisions.
References
IPCC. 2007. Summary for Policymakers. In Climate Change 2007: The Physical Science
Basis. Contribution of Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change, eds. S. Solomon et al. Cambridge, UK
and New
York, NY, USA: Cambridge University Press.
Kaye, N., A. Hartley, and D. Hemming. 2011. Mapping the climate: guidance on
appropriate techniques to map climate variables and
their uncertainty.
Geoscientific Model Development Discussions 4:1875–1906.
MacEachren, A. M., C. A. Brewer, and L. W. Pickle. 1998. Visualizing georeferenced
data: representing reliability of health statistics. Environment and Planning A 30:1547–
1562.