Finnish Meteorological Institute, P.O. Box 503, FI Helsinki 2. University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI Joensuu

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1 Storm risks on forestry in Finland - occurrence and risk management Ari Venäläinen 1, Hilppa Gregow 1, Heli Peltola 2, Veli-Pekka Ikonen 2 and Seppo Kellomäki 2 1 Finnish Meteorological Institute, P.O. Box 503, FI Helsinki 2 University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI Joensuu

2 Outline of the presentation 1. Importance of wind risks to forests in Europe, with special focus on Northern Europe 2. Possible impacts of changing climate on the risks of wind damage to forests in Finland 3. Spatial variation of wind extremes in Finland in the current climate and some words of the future wind

3 Major wind catastrophes in Europe in recent decades Date Region Timber lost, million m 3 January 1953 November 1966 January-February 1967 October 1967 January November 1972 January 1976 December 1976 November 1981 November 1982 July 1984 November 1984 October 1987 January-March 1990 December 1999 North-eastern Scotland Austria, Northern Italy Central Europe Denmark Central Scotland Sweden Northern France, Northern Germany Wales, Central England France Denmark Central France North-eastern France Central Germany, southern Belgium Southern England, Central Europe Northern England, Central Europe Central Europe, Sweden and Danmark > January Sweden January Central Europe January Southern France 50

4 SO FAR the damages in Finnish forests have been small compared to Europe Storm Damage, million m 3 Mean and gust wind speed, m s -1 Main region affected Aarno (1978) 2, and Mauri (1982) ) and Etelä-Pohjanmaa, Pirkanmaa (Southern Finland) Lappi (Northern Finland) Manta (1985) and Savo, Pohjois-Karjala ja Länsi-Lappi (Whole Finland) Pyry ja Janika (2001) 7, ) and (Pyry) ) and (Janika) Etelä-Pohjanmaa, Häme (Central, southern Finland) Unto (2002) and Savo(Central, southern Finland) 1) Max mean wind speed of 2 min instead of 10 min: Mauri (Pohjoisen Vaala ja Yli-tornio, max 2 min mean windspeed of 23 m s -1 ), Pyry (Vaasa airport, max 2 min mean windspeed of 27 m s -1 ) ja Janika (Vaasa airport, max 2 min windspeed of 27 m s -1 ).

5 Mechanism of wind (and snow) damage to forests (at new edges) Uprooting of trees at stand edge conditions. HWIND: Peltola et al. (1999)

6 Mechanism of wind (and snow) damage to forests (at new edges) Critical windspeed, m/s Height 12 m Height 16 m Height 20 m Height/DBH ratio 1:100 Scots pine Norway spruce Birch Uprooting of trees at stand edge conditions. HWIND: Peltola et al. (1999)

7 Control climate versus future climate according to FinAdapt A2 scenario IT WILL BE 2-6 C WARMER PRECIPIATION WILL INCREASE BY %

8 Control climate versus future climate according to FinAdapt A2 scenario THERE WILL BE LONGER DRY SEASONS SOIL FROST DECREASES IN THE SOUTH in central Finland as well? soil frost calculations are complicated *next slide Depth of soil frost (m) Depth of soil frost (m)

9 Soil frost and weather in Maaninka (sand land) soil frost (cm), snow(cm), Tdaily ( C) precipitation snow depth 06utc Tdaily soil frost (Finland s environment administration) A sudden increase in soil frost when in December the temperature had risen above zero it had been raining and the snow had melt 17 cm after the short mild and rainy period the temperature dropped rapidly below zero to close to -15 C the soil frost increased fast to 25 cm)

10 Soil frost and wind Wind > 10 m/s Percentage and soil of strong frost winds cm 100 % 90 % 80 % 70 % 60 % 50 % 40 % 30 % 20 % 10 % 0 % Helsinki (N 292) Joensuu (N 46) RISK Jyväskylä (N 99) Kajaani (N 117) Weather station Kauhava (N 173) NO RISK Rovaniemi (N 237) Here the soil frost is calculated with a formula suitable for roads (no snow) Therefore a more realistic interpretation for the uprooting risk of trees based on the figure is in simplicity risk and no risk In southern and central parts of Finland % of the stronger winds in the windy season occur with too little soil frost = risk for uprooting Sodankylä (N 39) frost depth < 1 cm frost depth 1-20 cm frost depth cm frost depth cm frost depth > 61 cm and concurrent snow loading 2 % 1 % 0 % 60 % 50 % 40 % 30 % 20 % 10 % 0 % Wind 5-7 m/s and soil frost 0-20 cm Snow load 0-10 Kg m Wind 5-7 m/s, and soil frost 0-20 cm Snow load = cumulative sum of precipitation (temperature and wind wearing) Helsinki Joensuu Jyväskylä Kajaani Kauhava Rovaniemi Sodankylä Helsinki Joensuu Jyväskylä Kajaani Kauhava Rovaniemi Sodankylä The concurrent risk of wind and snow is greatest in the central and northern parts of Finland

11 Control climate versus future climate FinAdapt A2 scenario: impacts on forests in Finland Changes in proportion of Scots pine, Norway spruce and birch (volume) under changing climate when actively not affecting tree species composition by management (Simulation of forest dynamics was done by ecosystem model SIMA; FinnAdapt A2 climate scenario)

12 Proportion of area at risk (%) Criteria given for proportion of area at risk: Critical wind speed < 17 m/s during autumn time (birch without leaves) Cutting drain (m 3 ha -1 a -1 ) Proportion of area at risk (%) Cutting drain (m 3 ha -1 a -1 ) Proportion of area at risk (%) Cutting drain (m 3 ha -1 a -1 ) Following the current silvicultural recommendations and management for private forest owners the forests in the future will have more birch and pine and less spruce. This implies a smaller wind induced risk to forests when the trees are without leaves.

13 Spatial variation and wind extremes 1/2 Data 1 ERA-40 reanalyzed meteorological dataset 850 hpa-level winds Calculated to 10 m height above the surface level according to the elevation chart Elevation points Grid points

14 Spatial variation and wind extremes 2/2 Data 2 Wind observations of 23 stations Corine land use 25 m x 25 m spatial resolution 1 km2 grid including 1600 points Surface roughness Summer Winter Surface roughness SUMMER MAIN FEATURES Roughness value mainly 0.3 or above in the 1 km x 1 km grids Lakes and the sea with roughness values or below Some adjustments maybe needed for the inland areas

15 50 year max wind 10 km grid (Based on ERA hPa wind calculated to 10 m height based on the elevation data) 50 year max wind 1 km grid (Based on observations and roughness approximations) ABOVE ABOVE BELOW BELOW

16 Probability 100 y Return values of maximum winds based on observations of 7 stations Return period 10 y 50 y Maximum average wind speed (10 minutes averages) HELSINKI & JYVÄSKYLÄ mean m/s 18,4 20,2 21,0 Return period 10 y 50 y 100 y mean m/s 15,9 17,9 18,8 Helsinki Rovaniemi Kauhava Kajaani Jyväskylä Sodankylä Joensuu Return period 10 y 50 y ROVANIEMI & JOENSUU 100 y mean m/s 17,4 19,5 20,2 Return period 10 y 50 y 100 y mean m/s 13,8 15,6 16,4

17 WIND IN GLOBAL SCALE CLIMATE MODELS (GCM) So far we have preliminary results based on 7 GCMs BCCR-BCM NORWAY Leap year 1.9 A1B, A2 ECHAM5/MPI-OM 2005 GERMANY Leap year 1.4 A1B,B1,A2 CNRM-CM FRANCE Leap year 1.9 A1B,B1,A2 MIROC3.2(hires) 2004 JAPAN Leap year 1.1 A1B,B1 CSIRO-Mk AUSTRALIA NO leap year 1.9 A1B,B1,A2 CGCM3.1(T63) 2005 CANADA NO leap year 1.9 A1B,B1 CCSM USA NO leap year 1.4 A1B,B1,A2 We will extend this to cover 3 more models NEW GFDL-1 MRI-CGCM2 IPSC

18 Changes in the geostrophic wind speed on sea surface level Results shown on the maps are the changes (A1B climate control climate) in SepApr and the significance at 95 % level according to the T-tests for period % % % % %

19 RESULTS OF THE EXTREME ANALYSIS Analysis of the extreme geostrophic wind speeds in southern Finland (location 60 N, 25 E) show that the change in return levels depends much on the model. 15 % 10 % 5 % 0 % -5 % -10 % -15 % Percentual changes in the return level speeds when comparing to control climate 46A1B: 10 46A1B: 25 46A1B: 50 BCCR ECHAM5 MIROC3 CNRM Scenario/return level 4GCM average 46A1B: 10 0 % 46A1B: 25-1 % 46A1B: 50-1 % A1B Total -1 % 46A2: 10 1 % 46A2: 25 2 % 46A2: 50 2 % A2 Total 2 % 46B1: 10 0 % 46B1: 25-2 % 46B1: 50-3 % B1 Total -2 % 81A1B: 10 1 % 81A1B: 25-1 % 81A1B: 50-1 % A1B Total 0 % 81A2: 10 2 % 81A2: 25 4 % 81A2: 50 5 % A2 Total 4 % 81B1: 10-3 % 81B1: 25-4 % 81B1: 50-4 % B1 Total -3 %

20 SUMMARY on the storm risk on forestry in Finland: 1. Decrease of soil frost will increase the overall wind induced risk to forests - despite of any changes in wind climate! 2. The volume of Norway spruce in the forests will decrease as the climate changes and this implies a smaller wind risk 3. The future risks could be reduced both at stand and regional level by proper forest management 4. Important aspects: tree species preference in regeneration and thinning proper tending of seedling stand and type, intensity of thinning, shorter rotation length, proper temporal and spatial patterns of final cuttings. Under the changing climate we need to adapt management to consider the risks of wind damage at regional level

21 RESPONSE NOT POSSIBLE High Risk regarded as intolerable Frequency of damage Low Risk regarded as negligible Risk regarded as significant - action to keep as low as reasonably practicable RESPONSE WORTHWHILE Conclusions? RESPONSE NOT NECESSARY Small Proportion of damage Large

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