assessment of fire risk in boreal forests under the present-day and future climate andrea vajda, ari...
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Assessment of fire risk in boreal forests under the present-day and future climate
Andrea Vajda, Ari Venäläinen and Kirsti Jylhä
Finnish Meteorological Institute (FMI)
ENSEMBLES Annual Meeting, Lund, 20-23 Nov 2006WP6.2 – Linking impact models to probabilistic scenarios of climate
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Outline
• FMI contribution to deliverable D6.9 “Report on an intercomparison study of modelled, Europe-wide forest fire risk for present day conditions” by Giannakopoulos et al. (NOA & FMI) (month 24)
• The impact of climate change on forest fire risk in northern Europe: some first estimates
• Future plans in ENSEMBLES
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Photo © Krister Sanmark
Boreal forests cover nearly 78% of total land area in Finland
Photo © A. Drebs
Finnish fire statistics 2001-2006
0
10
20
30
40
50
60
70
Apr 1 May 1 June 1 July 1 Aug 1 Sep 1 Oct 1
Nu
mb
er o
f fi
res
0
20
40
60
80
100
120
140
Apr 1 May 1 June 1 July 1 Aug 1 Sep 1 Oct 1
Are
a b
urn
ed (
ha)
Average daily number of fires
in April - October
Average daily area burned
Annual number of fires and area burned
0
1000
2000
3000
4000
5000
6000
7000
2001 2002 2003 2004 2005 2006
No
. of
case
s
0
500
1000
1500
2000
2500B
urn
ed a
rea
(ha)
No. of fires
Area burnt
• The average annual number of fires: about 3100• The average annual area burned: about 800 ha=> The mean area burned per event: 0.25 ha
18% of fires ≥ 0.1 ha0.3% of fires ≥ 10 ha
The frequency of fires is highest and the total area burned is largest in May
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Smoke in Helsinki in summer 2006 due to forest fires from abroad
Helsinki 9 Aug 2006 at 1 pm Helsinki 9 Aug 2006 at 2 pm
Photo © Pia Anttila Photo © Pia Anttila
One hour later (a shift in wind direction)
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Evaluation of two forest fire danger indices in the boreal forests environment (Finland)
The Finnish Forest Fire Index (FFI): - Soil surface moisture as an indicator of the fire risk
The Canadian Fire Weather Index (FWI): - Forest fuel moisture content; adjustment to the Finnish conditions
Fire danger classes
FFI (6 classes) FWI (5 classes)
6 very high
5 – 5.9 high
4 – 4.9 moderately high
3 – 3.9 moderately low
2 – 2.9 low
1 – 1.9 very low
>25 extreme
18 – 24.9 high
10 – 17.9 medium
2 – 9.9 low
0 – 1.9 very low
Fire potential threshold for Pinus sylvestris stand
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Correlation between the Finnish and Canadian fire indicesbased on station data in Finland in 1961–2005 (April–September)
A station in southern Finland A station in northern Finland
Finnish index FFI Finnish index FFI
Can
adia
n in
dex
FW
I
Can
adia
n in
dex
FW
I
• The forest fire risk decreases northwards
• FWI responded more rapidly to the meteorological variations (i.e. precipitation) than FFI.
• In northern and central Finland FWI indicated a fire risk more often than FFI, and vice versa in southern Finland
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0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Apr. May June July Aug Sept.
only FFI only FWIFWI and FFI
76
8
8
88
7
4
51
28 3340
70
16
41
63 59
53
26
Monthly distribution of days with FWI and/or FFI indicating fire risk(FWI>10, FFI≥4; central Finland)
• Largest deviations between FFI and FWI in early spring and in autumn
Apr May June July Aug Sep
FWI and FFI only FFI only FWI
• In about 50-60% of the cases both indices indicated a fire risk
Re
lativ
e fr
eq
uen
cy (
%)
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Comparison of fire indices and observed fire events
0.1-0.9 ha ≥1 ha
05
101520253035404550
FWI < 3 FWI ≥ 3
Fre
qu
ency
of
dis
trib
uti
on
(%
)
0
5
10
15
20
25
30
35
40
45
50
FFI < 4 FFI ≥ 4
0.1-0.9 ha ≥1 ha
Fre
qu
ency
of
dis
trib
uti
on
(%
)
size of the fires:
FFI FWIno fire risk a fire risk no fire risk a fire risk
Fre
quen
cy d
istr
ibut
ion
(%)
Fre
quen
cy d
istr
ibut
ion
(%)
0.1-0.9 ha ≥ 1 hasize of the fires:
0.1-0.9 ha ≥ 1 ha
• 54% of the fires ≥0.1 ha occurred when FFI indicated fire risk
• 64% of the fires ≥0.1 ha occurred when FWI indicated fire risk
The fire indices predict the favourable meteorological conditions for the occurrence of fires, but they are not predictors of fire events
Human behaviour, etc
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The impact of climate change on forest fire risk in northern Europe – a preliminary study
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R1d MAM CDD MAM
R1d JJA CDD JJA
Multi-model means
based onRCM-H-A2 runs
MAM and JJA changes (%) in the max 1-day precipitation (left) and max length of dry spells (right) by 2071-2100
increase
decrease
increase
decrease
For R1d: For CDD:
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observations RCA3-E-A2 scenarioRCA3-E-B2 scenario
Temporal variation of the annual number of days with a fire risk (FFI≥4) in Helsinki during 1961-2100based on: Changes in time of the average annual
number of days with a high or a very high forest fire risk (FFI ≥ 5)
The impact of climate change on forest fire risk in northern Europe – a preliminary study (cont.)
Latitude range in Scandinavia and the Baltic countries
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The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2001–2025
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The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2026–2050
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The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2051–2075
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The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2076–2100
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Future plans in the ENSEMBLES project
To produce new estimates of the impact of climate change on forest fire risk in northern Europe on the basis of - various future climate projections and - the Finnish Forest Fire Index (FFI)
To evaluate the impact of the extreme climate events on soil temperature and soil moisture
- Simulations using a coupled heat and mass transfer model for soil-plant-atmosphere system* (COUP model)
- Measured meteorological data / climate models’ output data
- Findings to be compared against results from the Finnish forest fire danger forecasting system
___* Jansson, P.E. & Karlberg, L., 2001: Coupled heat and mass transfer model for soil-plant-atmosphere systems. Royal Institute of Technology, Dept of Civil and Environmental Engineering, Stockholm, 321 pp.
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Year-to-year variation of the onset and end of the fire season
** 5 consecutive days with FWI>11, using a 7 days moving average
Cal
enda
r da
y
FFI start date*FFI end date*
FWI start date**FWI end date**
* first and last days with FFI=4
FWI appeared to respond very quickly to the variation of precipitation events, while FFI indicated smoother changes.