Download User-driven downscaling: advances in data apportioning and

Assessing climate change impacts on
water resources in Chile
Ed Maurer
Civil Engineering Department
Reunión profesores Estadounidenses Fulbright
Valparaiso, Chile
15 setiembre 2011
Global Climate is Changing
• Temperatures are
increasing globally
• Most recent warming
attributed to humandriven GHG
emissions
• Some impacts
already evident and
attributable to
warming
Source: U.S. Global Change Research Program (USGCRP)
Observed Changes: 1970-2004
• High confidence
changes in:
– rainfall intensity
– extreme
temperatures
– regional drought
– glacier melt
– early snowmelt
– lake warming
• Changes are
consistent with
observed
warming, if not
attributable
Source: IPCC Climate Change 2007:
Impacts, Adaptation, and Vulnerability -Summary for Policymakers.
Projections of Global Change
• Range of
‘likely
warming’ by
end of 21st
century
variable
• By mid-21st
century most
differences
smaller
2010
1.8°
2.4°
2.8° 3.4° 4.0°
Which pathway are we on?
• Current emissions are tracking
above the most intense IPCC
emission scenario
10
Carbon Dioxide Information Analysis Center
International Energy Agency
-1
Fossil Fuel Emission (GtC y )
• Scenarios trends
are averages
across all models
available for
each scenario
class.
Raupach et al., PNAS, 2007
Global Carbon Project, 2009
9
A1B
8
A1FI
A1T
A2
7
B1
B2
6
5
1990
1995
2000
2005
2010
2015
Looking toward the
future: end of 21st century
21 modeled changes for A1B
emissions
2080-2099 minus 1980-1999
Precipitation
Warming is large-scale,
certain
Precipitation changes more
regional, less confident
Regional changes drive
regional impacts
.
Figure 11.12
number of models out of 21 that
source: IPCC, 2007
project increases in precipitation
Figure 11.12
How do changes in Chile
compare to the California
Case?
21 modeled changes for A1B
emissions
2080-2099 minus 1980-1999
Warming is large-scale,
certain
Precipitation changes more
regional, less confident
Regional changes drive
regional impacts
.
Regional Changes
• Projected
changes
non-uniform
• Impacts also
non-uniform
Extreme urban heat events
Worsening air quality episodes
Ocean fishery migration
Increased severe flooding events
Greater water scarcity
More wildfires
Accelerating invasive species
Tourism, recreation impacts
Agricultural vulnerability
Median runoff change, 2041-2060 minus 1901-1970
Source: U.S. Global Change Research Program (USGCRP)
Estimating regional impacts
4. Land surface
(Hydrology) Model
2. Global Climate
Model
1. GHG
Emissions
Scenario
5.
Operations/impacts
Models
3. “Downscaling”
Adapted from Cayan and Knowles, SCRIPPS/USGS, 2003
Availability of GCM Simulations
 20th century through 2100 and beyond
 >20 GCMs
 Multiple Future Emissions Scenarios
Need for Downscaling
• Dynamic
– Better representation of terrain
captures local processes and
feedbacks
– Computationally expensive
– Still contain biases
• Statistical
– Assumes stationary transfer function
Images: IPCC
Image: Canadian Climate Change Scenarios Network
Downscaling for Impacts Models
• Bias correct and spatially downscale GCM
output
• Run hydrology model with projected climate
Raw
GCM
Output
Downscaling
Flow,
Snow, etc.
Multi-Model Ensemble Projections for
Feather River
•Increase Dec-Feb Flows
+77% for A2
+55% for B1
•Decrease May-Jul
-30% for A2
-21% for B1
Snow water equivalent on April 1, mm
Impact Probabilities for Planning
Point at:
120ºW, 38ºN
2/3 chance that loss will
be at least 40% by mid
century, 70% by end of
century
• Combine many future scenarios,
models, since we don’t know
which path we’ll follow (22
futures here)
• Choose appropriate level of risk
Translating this approach to Chile
Four key basins
Ecologically and economically important
Mataquito Basin
Tmed, Tmax, Tmin, P
Qdía
• Series diarias
• Se rellenan de series incompletas de P y Q
• Análisis (1) estacional, (2) periodo pluvial y nival, (3) anual
• Variables hidroclimatológicas e índices representativos
• Tendencias (Mann-Kendall y Regresión Lineal)
Escenarios de Cambio Climático
específicos cuenca Mataquito
Para un solo escenario (A1b) pero ahora estudiando un poco cambios
en variabilidad
Snow Cover and
Extreme Events
• Two events:
23 may 2008
27 may 2002
2002
2008
P 2 días previos (mm)
103.6
83.9
Caudal Máximo (m3/s)
931
2690
Tmax promedio (°C)
13,0
17,4
Cota estimada línea de
nieve (m)
1700
2200
* A partir de P’s y T’s
en Curicó, adoptando
una tasa de lapso de 9
°C/Km
2002
2008
Mataquito cuenca con nieve a 1700m
Mataquito cuenca con nieve a 2200m
2008, with lower total rain produced
greater peak stream flow.
Capturing Uncertainties in an
Ensemble - Temperature
• Internal variability (forecast) important first few years
• Model Uncertainty dominates through mid-21st century
• Uncertain emissions pathway most important after that
Hawkins & Sutton, BAMS, 2009
Does this capture the range of
uncertainties?
• Perturbed physics experiments and
theoretical feedback analyses extend tail to
right
• Uncertainty in emissions is on same order if
planning horizon includes end of 21st century
or beyond
Roe and Baker, 2007
Temperatura
Media Anual
(Celsius)
Precipitaciones
(mm/año)
Caudales
(mm/año)