Cliff Mass
Department of Atmospheric Sciences
University of Washington
Society needs reliable information on
the regional implications of climate
change
• Infrastructure decisions are
being made now for assets
that will last well into the
current century when the
impact of GW will be
substantial
• Adaptation planning
• Motivation for mitigation
efforts
Bottom Line of the Talk
There is only one viable method for producing
the required regional climate predictions:
dynamical downscaling of global
climate models
But to do this right, there is much that is
required.
Requirements
1. The use of large numbers of global model simulations
(GCMs) to explore initial condition, model, and physics
uncertainty.
2. Filtering to remove GCMs unable to simulate realistically
the current climate
3. Use of sufficient resolution in the regional climate models
(minimum 12-15 km grid spacing) to get realistic NW
circulations
4. Use of an appropriate nested domain structure of the
regional simulations (MUST include the Rockies with
sufficient resolution)
5. Must have sophisticated post-processing to reduce biases
and get reliable probabilities.
Two Sobering Facts
• No one in the NW has done such downscaling
right yet
– Too few GCM’s applied to dynamical downscaling
– Primitive post-processing
– Statistical downscaling
• Getting the wrong answers from inadequate
efforts can be either useless or costly for
society. No answer is better than the wrong
answer.
Why haven’t we done it
correctly?
• Lack of computer resources and personnel
• Too few GCM runs available, so uncertainty
has not been explored.
• Lack of filtering of unrealistic GCMs
• Deficiencies of regional climate models (e.g.,
snow in NOAH Land Surface Model)
• Lack of familiarity of some climate groups
with mesoscale meteorology of the region
And we have not even talked
about another essential
component of regional climate
prediction
• Coupling the regional climate simulations
with:
–
–
–
–
Hydrological models
Air quality models
Coastal ocean models
Fire models and others
The Challenge:
Can We Do This Right,
Together?
• Combine regional resources and personnel
so that together we can do what one group
cannot accomplish alone.
• There is a precedent for such combination
of resources: the Northwest Modeling
Consortium.
Many of the technical issues are
very similar….
Dynamical Downscaling Not
Statistical Downscaling
• Only fully dynamical downscaling can hope to
simulate the non-linearities and complexities
of the future climate response.
• Examples:
– Location and distribution of precipitation changes
as stability changes.
– Onshore flow and coastal marine clouds enhanced
by greater onshore pressure gradients
– Albedo feedbacks as snow melts.
Echam-5 versus WRF
Removing Unrealistic GCMs
• The quality of the available (CMIP-5)
GCMs vary, with some unable to produce a
realistic simulation of the contemporary
climate over the western U.S.
• These must be removed from consideration
for downscaling work.
Dozens of downscaled GCM
runs not 1-3
• There is substantial uncertainty in the GCM
simulations and a handful of simulations
can not get a handle on the inherent
uncertainties.
• Sources: physics uncertainty, initial state
uncertainty, emission uncertainty, and many
more.
• GCMs produce a wide variety of local
solutions
Initial Condition Uncertainy
• Dr. Clara Deser of NCAR showed that
simply by varying the start times of
simulations of the same GCM can produce
very different regional results decades
hence.
Sufficient resolution and
proper domains
Over the Northwest, the
simulations must have a grid
spacing of a least 12-15 km grid
spacing
Based on over 10 years of twicedaily simulations at 36-12-4-1.3 km
at the University of Washington,
with objective verification
150 km versus 12 km
36-km
12-km
The Proper Domain Structure is
Crucial
• GCMs have insufficient resolution to define
key regional weather features (e.g., major
terrain features), resulting in large simulation
errors that make their results unreliable for
local decision making.
• Regional climate simulation must have
enough resolution (~50km) on a large
enough grid to get the Rockies right—or cold
air spills over the Northwest from the cold
interior
Cold Waves Under Global
Warming
PCM
Cold
Wave
Under
Global
Warming
12 Feb 1990
Seattle 2050
PCM and ECHAM-5 Driving Small
Domain MM5: Crazy Cold
Waves
Sophisticated post-processing
• Remove systematic bias based on
contemporary periods.
• Weight ensemble of climate simulations
based on their quality.
• Produce calibrated probabilistic guidance.
Use Bayesian Model Averaging,
calibrated on a contemporary period,
to produce probabilistic regional
climate predictions.
Proven approach for weather forecasting
Integration of ancillary
physics/applications (e.g, hydro,
coastal ocean, air quality) to
create a total environmental
modeling system
The Northwest Climate Modeling
Consortium: A Proposal
• Combine resources of regional government
entities, state and Federal agencies,
foundations, academic institutions, tribes,
and other to create the most robust climate
predictions possible.
• Similar to the NW modeling consortium,
decisions could be make by contributing
stakeholders
Tasks
• Acquire or secure sufficient computer
resources for regional climate downscaling
and to run additional GCM simulations.
• Develop GCM filtering approaches.
• Acquire CMIP-5 (6) GCM runs and
run/acquire additional simulations.
• Run large numbers of regional climate
simulations
Tasks
• Run applications models (e.g., hydro)
• Optimally post-process and combine
regional climate simulations to provide
robust probabilistic guidance
The tasks will be distributed
over several groups according
to resources/ability
The University of Washington is the largest
group and is willing to take on management
responsibilities.
Products
• Model grids and custom products will be
available to supporting stakeholders and
their designees.
• Grids can also be made available to regional
climate impacts group (Oregon State, UW
CIG, etc.)
The END