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The 27 th Annual Conference International Association for Impact Assessment 3-9 June 2007, COEX Convention Center, Seoul, Korea. Prediction of Plant Communities Using Regional Climate Model in Korea. 5 June, 2007. Jae-Uk KIM, Dong-Kun LEE (Seoul National University, Korea). Contents.
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The 27th Annual Conference International Association for Impact Assessment 3-9 June 2007, COEX Convention Center, Seoul, Korea Prediction of Plant Communities Using Regional Climate Model in Korea 5 June, 2007 Jae-Uk KIM, Dong-Kun LEE (Seoul National University, Korea)
Contents 1. Backgrounds 2. Objectives 3. Materials 4. Methods 5. Results and Discussion 6. Conclusion
Backgrounds Global mean temperature near the Earth's surface rose 0.74±0.18°C during the past century. Climate models referenced by the IPCC project that global surface temperatures are likely to increase by 1.1 to 6.4 °C between 1990 and 2100. The effects of global warming is becoming more apparent on various parts of the world including dynamics in natural ecosystems.
2005 ① Camellia japonica L. 2000 1996 ③Quercus mongolica ② Sasa quelpaertensis Nakai Backgrounds ③ ① ②
Objectives To choose a suitable climate model in the Korea To verify connection between plant communities and environmental factors To predict potential distribution of Pinus densiflora, Quercus Spp., Alpine Plants and Evergreen Broad-Leaved Plants To assess a vulnerable area in climate change
Materials-Climate Models Center Acronym Model SRES scenario Time period A2 National Institute for Environmental Studies (NIES) NIES/RAMS NIES/RAMS RCM 1981-1990 2041-2050 Hadley Centre for Climate Prediction and Research HCCPR HadCM3 A2 B2 1950-2099 Australia’s Common Wealth Scientific and Industrial Research Organization CSIRO CSIRO-Mk2 A1 A2 B1 B2 1990-2100 Canadian Center for Climate Modeling and Analysis CCCma CGCM2 A2 B2 1900-2100 Center for Climate Research Studies (CCSR) National Institute for Environmental Studies (NIES) CCSR/NIES CCSR/NIES AGCM +CCSR OGCM A1 A2 B1 B2 1890-2100
Materials-Climate Models CCSR-NIES CGCM2 NIES-RAMS CSIRO-Mk2 HadCM3 Regional Climate Model General Circulation Model
Materials-Plant communities Total : 170 communities
Results-Current climate (1971~2000) Temperature Precipitation
Results-Future climate (2050) HADCM3 GCM CSIRO-Mk2 GCM CGCM2 GCM CCSR/NIES GCM
Results-Future climate (2050) NIES/RAMS RCM (Temperature) NIES/RAMS RCM (Precipitation)
Results-4GCMs vs 1RCM (1981~1990) Precipitation Temperature
Simulated (1971~2000) Results-Pinus densiflora Present (1990) Pinus densiflora = 0.0015×DEM – 0.00252×Ptotal + 0.0175×Tdjf + 1.8593
Results-Pinus densiflora NIESRAMS Predicted (2041~2050) CCSRNIES Predicted (2041~2050) CGCM2 Predicted (2041~2050) CRIRO-Mk2 Predicted (2041~2050) HADCM3 Predicted (2041~2050)
Simulated (1971~2000) Results-Quercus Spp. Present (1990) Quercus Spp. = 0.2405×CI – 0.00461×DEM – 1.0309×Tmin – 1.3920
Results-Quercus Spp. NIESRAMS Predicted (2041~2050) CCSRNIES Predicted (2041~2050) CGCM2 Predicted (2041~2050) CRIRO-Mk2 Predicted (2041~2050) HADCM3 Predicted (2041~2050)
Simulated (1971~2000) Results-Alpine Plants Present (1990) Alpine plants = 0.2586×WI + 0.00434×DEM – 0.0029×Ttotal – 1.8873×Tmam – 10.8265
Results-Alpine Plants NIESRAMS Predicted (2041~2050) CCSRNIES Predicted (2041~2050) CGCM2 Predicted (2041~2050) CRIRO-Mk2 Predicted (2041~2050) HADCM3 Predicted (2041~2050)
Simulated (1971~2000) Results-Evergreen Broad-Leaved Plants Present (1990) Evergreen Broad-Leaved Plants = 0.6503×CI – 0.7949×Tmin
Results-Evergreen Broad-Leaved Plants NIESRAMS Predicted (2041~2050) CCSRNIES Predicted (2041~2050) CGCM2 Predicted (2041~2050) CRIRO-Mk2 Predicted (2041~2050) HADCM3 Predicted (2041~2050)
Conclusion Achievements To challenges associated with predicting and assessing the future climate using RCM distribution of communities to climate change in Korea Limitations and Considerations To examine the potential distribution of communities by correlating the environmental factors without reflecting the natural succession processes Variabilities of multiple RCM output results under various climate change scenarios were not sufficiently considered Ground truth field surveys to enhance the accuracy of the results were not conducted