Evolving Partnerships for
Integrating Climate and
Forecast Information into Fire
Management Planning in the
Western United States
Anthony Westerling
California Applications Program
NOAA OGP, USFS, CEC
Wildfire Management & Climate
• Wildfire risks driven by climate on
regional scales
May
June
0.0
August
0.1
0.2
0.3
September
July
0.4
0.5
0.6
October
Wildfire Management & Climate
• Time scales: Hours to Days, Seasonal
to interannual variability, decadal
variability
PDO, ENSO and Annual Area Burned in the Southwest
Wildfire Management & Climate
• Complex institutional structure
Figure 2: Wildland Fire Management Organizational Flowchart
USDI / USDA
Natio
nal
National Interagency
Fire Center (Boise)
National Office
of NPS / USFS
Fire Weather
Service
Mobilizat
ion
RISAs
Geographic Area
Coordinating Center
Climate
information
Comple
te
Regio
nal
Comple
te
Regional Office
of NPS / USFS
Mobilizat Budg
ion
et
Park / Forest
budget:
National Park /
National Forest
Key:
Resource requests and allocations
Information flows
Wildfire Management & Climate
• Multiple opportunities / applications
Decisions
Suppression
Rx and Fire Use
Seasonal Staffing
Budgeting
Special: Santa Ana
Decisions
Suppression
Rx and Fire Use
Seasonal Staffing
Budgeting
Special: Pile Burning
Decisions
Suppression
Rx and Fire Use
Seasonal Staffing
Budgeting
Special: Monsoon
J
J
J
M
Southern California
A
M
J
J
A
S
O
N
D
F
M
Northern California
A
M
J
J
A
S
O
N
D
F
Arizona & New Mexico
M
A
M
J
J
A
S
O
N
D
F
Role of CLIMAS Workshops
• Interaction with scientists and managers
in workshops
– Structured
• Designed to elicit manager’s views on forecast
tools (skill, confidence, resolution, timing, etc)
– Contact with diverse audience
• USFS, NPS, BLM
• Operations, Management/Planning, Science
• Diverse levels of capacity, interest
Some Benefits
• Ideas for applications
• Establish relationships with multiple
potential partners
– Fire management (forecasting, operations
and planning), Federal researchers,
Academia
Taking the Initiative
• Entrepreneurship
– Us: we developed data sets, tested models,
developed prototype forecasts
• Price of entry - demonstrated value
– Them: NIFC predictive services identified our
work through conference proceedings abstracts,
interaction in workshops and conferences
How do we get from research
to operational applications?
• Resources
– Shouldn’t stakeholders contribute resources at
some stage?
– Challenge: (our) research-to-applications too
applied for their research program, too esoteric for
operations?
– Not formally funded as transition project, but
USFS is a big organization…
How do we get from research
to operational applications?
– Predictive Services identified our research as
being of value for specific applications
– Encouraged collaborations from within
•
•
•
•
•
Resources
Partnerships
Data
Applications
Competition?
– Unofficial imprimatur?
• Gradual transfer of research and forecast technology to
multiple Forest Service researchers (RMRS, SRS,
Northwest GACC)
• Eventually it wont be my product that they use
– But elements of my research will be incorporated
It’s a Two-way Street
• “They” are learning from us
– Data sets
– Forecast methods
– Forecast limitations
• “We” are learning from them
– Data sets
– Applications
– Forecast methods
– Forecast limitations
Defining Characteristics
• Public Stakeholders are large Federal
Agencies
• Diverse Resources and Capacities
• Lead Agency
– USFS has considerable resources:
• research bureaucracy
– Cross-cutting, centralized.
• NPS research infrastructure based in individual parks
• Multiple, overlapping (competing?) research
collaborations
• Entrepreneurship
• Inter/Intra agency Coordination
USFS Forecast
Development & Assessment
•
•
•
•
•
•
USDA Forest Service
Budgeting
2yr Fiscal cycle
Wanted: Longer lead times, custom area
Reallocation across activities, regions
Suppression budget variability dominated by
temperature sensitive forest wildfire regimes
• T forecasts -> improved seasonal forecasts
• Challenge: A categorical forecast
• Challenge: Timing
Decision Calendars for Wildfire Management
Decisions
Suppression
Rx and Fire Use
Seasonal Staffing
Budgeting
Special: Santa Ana
Decisions
Suppression
Rx and Fire Use
Seasonal Staffing
Budgeting
Special: Pile Burning
Decisions
Suppression
Rx and Fire Use
Seasonal Staffing
Budgeting
Special: Monsoon
J
J
J
M
Southern California
A
M
J
J
A
S
O
N
D
F
M
Northern California
A
M
J
J
A
S
O
N
D
F
Arizona & New Mexico
M
A
M
J
J
A
S
O
N
D
F
With B. Morehouse and T. Corringham
Application: Forecasting for Forest Service Suppression Budgeting
Temperature matters …
… But it’s really only good for a categorical forecast
We Use Patterns in March Sea Surface Temperature and PDSI
to forecast patterns in
spring and summer
temperatures
after Alfaro, Gershunov and Cayan 2005
Table 2: Northern Rockies Contingency Table: Observations versus Forecasts of
Extreme Fire YearsÕSuppression Costs
Forecast
Observed
< $65 Million
> $65 Million
< $65 Million
21
1
> $65 Million
0
5
Really is a categorical forecast….
But somehow…
2005 Forest Service “Early Warning”
Suppression Cost Forecast and Confidence Bands
95% Confidence Band
90% Confidence Band
307
818
346
776
Point Estimate=552
Mean Forecast=560
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.