the scenarios network for alaska and arctic planning is a collaborative network of the university of...
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SNAP CLIMATE MODELS:TOOLS FOR PLANNERS AT EVERY LEVEL OF DECISION-MAKING
What is SNAP?
The Scenarios Network for Alaska and Arctic Planning is a collaborative network of the University of Alaska, state, federal, and local agencies, NGOs, and industry partners.
Its mission is to provide timely access to scenarios of future conditions in Alaska and the Arctic for more effective planning by decision-makers, communities, and industry.
Understanding the Science of Climate Change
There is now clear scientific evidence that our planet is warming
How this will affect climate systems around the globe is an enormously complex question
Uncertainty and variability are inevitable
Climate change presents significant risks to natural and cultural resources
Understanding how to address uncertainty is an important part of climate change planning
Measuring and modeling change
Global Circulation Models (GCMs) Complex coupled models created by
national and international labs Interactions of oceans, atmosphere, and
radiation balance
Calculated which 5 of 15 models were most accurate in the far north A1B, B1 and A2 emissions scenarios Temperature and precipitation projections by
month to 2100
Historical data Weather station data Interpolated and gridded CRU data 1901-2008
GCM output (ECHAM5) 2.5 x 2.5 degrees
Downscaling
Baseline values = PRISM mean monthly precipitation and temperature, 800m, 1971-2000
Adjusted and interpolated GCM outputs to historical baseline
Effectively removed model biases while scaling down the GCM projections
Frankenberg et al., Science, Sept. 11, 2009
Major Sources of Uncertainty:Global Climate Models (GCMs)
Inputs to GCMs Solar radiation is essentially a known quantity Levels of greenhouse gases are uncertain, but accounted for
by varying emissions scenarios GCM algorithms
Oceanic and atmospheric circulation are hard to predict and model
May include thresholds (tipping points) such as ocean currents shifting
Don’t fully account for short-term phenomena such as the Pacific Decadal Oscillation (PDO)
The PDO causes significant climate shifts on a decadal scale
Primary Products
1. Projections of future conditions that are linked to present and past conditions
2. Detailed explanations of the rules, models, and assumptions underlying the projections
3. Objective interpretations of scenarios based on these projections
www.snap.uaf.edu
Complex linked models:Permafrost thaw
Torre Jorgensen
(Geophysical Institute Permafrost
Lab, UAF)
Torre Jorgenson
Soil temperature at 1-meter depth:
1980s, 2040s, and 2080s
Complex linked models:ALFRESCO Fire Model
SimulatedEmpirical
.
Climate Change in Alaska: the bottom line
Change is happening, and will continue for decades regardless of mitigation efforts.
Key tipping points may be crossed, e.g fire, permafrost, sea ice, biome shift, glacial loss.
High uncertainty results in divergent possible futures for many important variables.
www.nenananewslink.com
alaskarenewableenergy.org
Forecast Planning One Future
Scenario Planning Multiple Futures
Scenario Planning vs. Forecasting
What we know today
+10%-10% Uncertainties
Global Business Network (GBN) -- A member of the Monitor Group Copyright 2010 Monitor Company Group
What we know today
Scenarios: “what if” stories
Everyday choices are based on scenarios
Examining scenarios What are possible outcomes? What is the likelihood of each
outcome? How much do we want to
avoid the bad outcomes? How desirable are the good
outcomes? How do we balance time and
costs against risks?
http://mareeconway.com/blog
Hedge Your Bets
Hedge Your Bets
Hedge Your Bets
Hedge Your Bets
Core
RobustSatellite
Satellite
Bet theFarm
Hedge Your Bets
Hedge Your Bets
Hedge Your Bets
Hedge Your Bets
Core
RobustSatellite
Satellite
Bet theFarm
From data to scenarios
Collaboration rather than top-down information transfer
What are the most pressing questions? Differ from region to region Depend on needs on stakeholder
What questions can SNAP help address? What data are and are NOT available? How much time/funding is available? Role of uncertainty
Desired products Maps, reports, presentations, websites, etc.
Climate questions at every scale
Broad-scale
Regional
Local
Big-picture example:Climate-Biome Shift
Describing the clusters:growing degree days, season length, and snowfall
0
500
1000
1500
2000
2500
3000
50
70
90
110
130
150
170
190
210
230
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Gro
win
g de
gree
day
s
Day
s ab
ove
free
zing
cluster
Days above freezing
Growing Degree Days
0
200
400
600
800
1000
1200
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Tota
l pre
cipi
tatio
n, m
m (
rain
wat
er e
quiv
alen
t)
Clusters
total for months with mean temperature below freezing
total for months with mean temperature above freezing
Length of above-freezing season and GDD by cluster. Days above freezing were estimated via linear interpolation between monthly mean temperatures. Growing degree days (GDD) were calculated using 0°C as a baseline.
Warm-season and cold-season precipitation by cluster. The majority of precipitation in months with mean temperatures below freezing is assumed to be snow (measured as rainwater equivalent).
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Describing the clusters: existing land classification
http://land cover.usgs.gov/nalcms.php
North American Land Change Monitoring System (NALCMS 2005)
AVHRR Land cover, 1995
Created 2/4/11 3:00 PM by Conservation Biology Institute
GlobCover 2009
Alaska Biomes and Canadian Ecoregions.
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Projected cliomes for the five-model composite, A1B (mid-range ) climate scenario.
Alaska and the Yukon are shown at 2km resolution and NWT at 10 minute lat/long resolution .
Future Projections
Original 18 clusters
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Regional Climate Scenarios: National Park Service
Changing climatic conditions are rapidly impacting environmental, social, and economic conditions in and around National Park System areas in Alaska.
Alaska park managers need to better understand possible climate change trends in order to better manage Arctic, subarctic, and coastal ecosystems and human uses.
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NPS and SNAP are collaborating on a three-year project that will help Alaska NPS managers, cooperating personnel, and key stakeholders to develop plausible climate change scenarios for all NPS areas in Alaska.
Southwest Alaska Parks and Sites
Aleutian WWII not included in assessment
Aniakchak
Lake Clark
Kenai Fjords
Katmai 20
SNAP regional projections
Mean winter precipitation. These maps show the projected precipitation for December, January, and February for selected decades. Although increased precipitation is expected, warmer temperatures may result in less snow.
Mean annual ground temperature at one meter depth. Based on SNAP climate data and GIPL permafrost modeling, these maps depict likely ground temperature conditions. Widespread loss of frozen ground is likely by the end of the century.
Climate Scenarios example: NPS Southwest Alaska Network
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Matrix showing the intersection of changes thaw days (summer season) and precipitation, as each pertains to inland (riverine) regions. Each quadrant yields a set of future conditions which are plausible, challenging, relevant, and divergent.
“Juneau/Helly Hansen”
B
”Smokey”
A
“Freeze-Dried”
C”Little Ice Age”
D
Thaw Days
More, with warming PDO
High variationLess Variation
Less, with cold phase PDO
Precipitation
Climate scenario (example)
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“SMOKEY”
Drought stressed vegetation
Increase in disease/pests Longer growing season Maximum shrub expansion
(less overland access) Long-term reduction stream
flow Initially higher stream flows
from seasonal glacial melt Reduction/loss glaciers Increased fire on landscape 40% reduction in salmon fry
due to smaller fry.
Katmai Brooks Camp barge requires glacier melt for high lake levels…this world would minimize access with warming and less precipitation.
Less biting insects Decrease in waterfowl Exposure of cultural resources Lowering of groundwater
tables. More fugitive dust with Pebble
Mine Decrease in stream flow Increase competition in water. Decrease in subsistence
(difficult winter travel)
Nested Scenarios
Matrix showing Riverine climate scenarios nested in a social and institutional framework. Each quadrant yields four linked scenarios; three are selected in red.
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Implications: “Smokey” in “Wheel-Spinning”
FacilitiesInfrastructure risks, fire protection costsMelting permafrost, damage to infrastructure (buildings)Interpretation and EducationMaintaining relevant agency in-reach effortsPublic/visitor education costs and challengesGreater need for public application of ecosystem servicesProtectionFire management, public safety risksF&W regulations, harvest quotas, seasons
Physical ResourcesHydrological cycle changesReduction in available water Reduction in available waterBiological ResourcesMajor biome shiftIncrease in fire, increase in pests/diseasePond Conversion to uplandsESA Issues Species management concernsCultural ResourcesExposure of artifactsSocio/EconomicConservation of F&W for subsistence & recreationAccess and transportation issues
Narratives: the power of story
Name Species Hair/Fur Age Appetite
Level Size
Preliminary Porridge
Assessment
Preliminary Mattress
Assessment
Goldilocks Human Blonde 8 Moderate Petite N/A N/A
Papa Bear Brown 12 High Big Too Hot Too Hard
Mama Bear Tawny 11 Moderate Medium Too Cold Too Soft
Baby BearRed-
Brown3 Low Small Just Right Just Right
Global Business Network (GBN) -- A member of the Monitor Group Copyright 2010 Monitor Company Group
No regrets actions when combined with other scenarios
Data, research and monitoring
Create seamless data sets Collaborate with
researchers and monitoring programs to track changes in PDO and ocean acidification
Increase fluidity and connections between research and monitoring
Conduct coastal/marine/onshore ecosystem monitoring
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Collaboration and outreach Coordinate communication with
other agencies Get missing players to the climate
change scenario table at subsequent meetings
Provide science outreach and education to multiple audiences
Identify and cooperate with private/public entities for partnerships
Re-imagine how institutions can work together to solve common problems.
Flexibility and innovation Tune planning process to
account for multiple possibilities
Model, collaborate and promote energy efficient technologies
Create portable, flexible structures
The local level: Community Charts
Local example:Agriculture – Fairbanks NSB
InterviewsGrowing Degree Day Analysis
Photo by Nancy TarnaiEllen Hatch (Thesis project, SNRAS)
Local Agriculture
Collaborative Products
All SNAP data and outputs are available under a Creative Commons license. Currently, 24 ongoing and completed projects are linked on the SNAP website, in addition to reports, videos, presentations, and papers.
www.snap.uaf.edu