On May 16, ICLR hosted a special webinar which provided a forecast of the 2018 wildfire season. The session was led by Richard Carr, Fire Research Analyst for the Canadian Forest Service. The interactive webinar summarized the current conditions in Canada and provided a forecast for the 2018 fire season. Richard provides fire weather processing for the Canadian Wildland Fire Information System (CWFIS) and international projects. He provides fire weather briefings to the Canadian Forest Service (CFS) fire group, the Canadian Interagency Forest Fire Centre (CIFFC), and to federal emergency response personnel, and helps provide seasonal forecasting of fire risk. He also helps provide information to the North American Seasonal Fire Assessment Outlook, and the North American Drought Monitor via AAFC’s Canadian Drought Monitor. He represents NRCan-CFS in the CIFFC Forest and Fire Meteorology Working Group.
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Agenda
This presentation
• Provides some background information
• Revisits last year’s fire season
• Summarizes current global and Canadian conditions
• Describes the forecast methodology
• Provides the 2018 forecast (May 1 run)
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4. Forecasts: General points
Forecasts of seasonal wildland fire risk are available on
• Canadian Wildland Fire Information System (CWFIS) web site:
http://cwfis.cfs.nrcan.gc.ca
• North American Seasonal Forecast Assessment Outlook:
http://www.predictiveservices.nifc.gov/outlooks/NA_Outlook.pdf
Forecasts are based on:
• Environment and Climate Change Canada (ECCC) seasonal forecasts
• Information contained in the CWFIS
• North American outlook areas use visual assessment of other climate
models’ output
• Advice provided by provincial agencies
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Drought Code
The Canadian FWI System allows for adjustment of fall
conditions to the spring using winter precipitation.
Fuel moisture codes represent moisture at three forest floor depths:
Moisture Depth Layer Woody Fuel Precip
Code Threshold
FFMC 0-2 cm Litter layer L Fine twigs, needles, etc 0.5mm
DMC 2-5 cm Fibric layer F Bark, small branches 1.5mm
DC 5+ cm Humic layer H Logs, large branches 2.8mm
Drought Code (DC) based on forest floor moisture capacity of ~200mm
L
F
H
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What affects spring DC?
• Spring DC (and FWI) can depend on El Niño/Southern
Oscillation (ENSO) events
• La Niña (negative phase) and El Niño (positive phase) are major
drivers of seasonal weather
• Other oscillations (PNA, PDO, AO, MJO, …) likely effect DC,
but at different timescales, intensities; effects not as well-
described
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El Niño – Southern Oscillation (ENSO)
El Niño:
• Warm ocean temperature anomaly in eastern Pacific; atmospheric
pressure higher over Darwin thanTahiti
La Niña:
• Cold ocean temperature anomaly in eastern Pacific; atmospheric
pressure higher overTahiti than Darwin
Events may cause extreme global weather (floods, droughts)
Events persist 9-12 months; sometimes 2+ years
Events recur every 2 to 7 years
Develop often during April-June
Reach maximum strength Dec-Feb
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ENSO forecasts: Climate Ensembles
ENSO and other influences represented in climate models
Models used by ECCC’s Canadian Meteorological Centre (CMC):
• Were developed by Canadian Centre for Climate modeling and analysis
(CCCma)
• Provide temperature and precipitation forecasts
• Ensembles of ten members each produce 12-month forecasts
• CanCM3 uses atmospheric model CanAM3 (AGCM3)
• CanCM4 uses atmospheric model CanAM4 (AGCM4)
• CanSIPS: Canadian Seasonal to Interannual Prediction System
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2017 Predictions
March June
The seasonal fire severity forecast changed
with ENSO forecast changes.
Weak “Modoki” ENSO, positive PDO, and
MJO may have helped shape the 2017
season.
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2017 NASFAO: 2-month lead time
May’s forecast for July June’s forecast for August July’s forecast for September
http://www.predictiveservices.nifc.gov/outlooks/NA_Outlook.pdf
• Uncertainty in climate predictions affected severity forecasts
• 2-month lead time resulted in poor predictions
• Countries use different methodologies
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Oops! We found a coding error in
the cm4 precipitation file reading
…
Fixed for May 1 run
Year DJF JFM FMA MAM AMJ MJJ JJA JAS ASO SON OND NDJ
2012 -0.8 -0.6 -0.5 -0.4 -0.2 0.1 0.3 0.3 0.3 0.2 0.0 -0.2
2013 -0.4 -0.3 -0.2 -0.2 -0.3 -0.3 -0.4 -0.4 -0.3 -0.2 -0.2 -0.3
2014 -0.4 -0.4 -0.2 0.1 0.3 0.2 0.1 0.0 0.2 0.4 0.6 0.7
2015 0.6 0.6 0.6 0.8 1.0 1.2 1.5 1.8 2.1 2.4 2.5 2.6
2016 2.5 2.2 1.7 1.0 0.5 0.0 -0.3 -0.6 -0.7 -0.7 -0.7 -0.6
2017 -0.3 -0.1 0.1 0.3 0.4 0.4 0.2 -0.1 -0.4 -0.7 -0.9 -1.0
2018 -0.9 -0.8 -0.6 ?
Possible problems with 2017 predictions
2016-18: Rapid ENSO fluctuations
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2017 Fall conditions
Many locations in top 10th percentile
for the time of year
Drought Code
Oct 28, 2017
• 0.0 – 250.0
• 250.0 – 500.0
• 500.0 – 750.0
• 750.0 – 1000.0
• 1000.0 – 1250.0
Does CWFIS need a
new DC class?
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0 50 100 150
051015202530
CYEG
Days from Apr 1
Temp-cm3
Seasonal Forecast Methodology
1.Use fall conditions to help assess
spring start-up
2. Calculate average daily weather
4. Calculate fire weather anomaly 3. Apply seasonal predictions
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NRCan-CFS Seasonal Prediction -- New
More fully automated – less chance of failed runs
Classification of anomalies: shows below average and more
distinct classes
New summary map content: areas may use visual assessment
of other models’ predictions
• Included in NASFAO but not CWFIS yet
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What’s up with the large temperature departure on
one ensemble element?
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Notes
Forecast temperature higher in many places in May
run than April’s
Does positive Pacific Decadal Oscillation reduce
spring rain in southwestern Canada?
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NRCan-CFS Seasonal Prediction– Future?
One more step needed to refine anomaly map classes
Add software to CWFIS architecture
Better snowmelt estimate
Understand ensemble members and apparent biases
Input from other climate models
Reconcile CWFIS and NASFAO presentation methods
Incorporate provincial methodologies
Assessment of model performance
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Watch for …
New forecasts done in the first week of each month
New anomaly class scheme
Daily conditions on the CWFIS
and/or provincial fire weather
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