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
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
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
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)
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
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
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 (
%)
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
The impact of climate change on forest fire risk in northern Europe – a preliminary study
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:
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
The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2001–2025
The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2026–2050
The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2051–2075
The annual number of days with a forest fire risk (FFI ≥ 4)– preliminary results
Based on the RCA3-E-A2 simulation
2076–2100
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.
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.