Introduction to AIM/Impact model National Institute for Environmental Studies
Items of the presentation � Overview of AIM/Impact model – Structure – Examples of the assessed results � Reference – Chapter 3 of AIM BOOK
AIM/Impact in AIM Framework
Objective of AIM/Impact � Projection of potential impacts of climate change on sensitive sectors. � Consideration of linkages among affected sectors. � Proposition of effective adaptation measures to cope with climate change. � Accounting feedback effects on GHGs concentration and climate system.
Framework of the AIM/Impact model AIM/Climate AIM/Climate HEALTH POP Health impacts of Population, Fertility and Mobility Environmental CLIMATE Change Radiation, Energy balance, Temperature and ENV Sea level rise ENERGY CYCLE Environmental Pressure and counter-measure Energy technology OCEAN and resources Chemistry of GHGs CGE Energy and AIM/Emission AIM/Emission carbon budget of Supply and demand equilibrium Ocean Of goods, energy, water, land and labor LAND FOOD WATER Supply infrastructures Land-use allocation and Production and demand Demand GHGs emission HYDRO VEG Surface water balance Vegetation dynamics Routing module
Characteristics of AIM/Impact � Area focused: Whole Asia to Global � Spatial analysis (Modules run on GIS) � Consistency between socio-economic scenario and climate change scenario. � Integration of emission (WG3), climate (WG1) and impact and adaptation (WG2) in the institute.
Computation framework GRASS on UNIX Original data GRASS database GRASS commands Climate data Variable spatial resolution Data import interface GCM results Meshed raster data Soil property Land-use Climate Output Output Input Population GIS data scenario data data data etc. Climate scenario GRASS model GRASS Analysis creator commands commands UNIX shell program Developed with Visualization F77 or C language Average, etc. Analysis on PC
GRASS (Geographic Resoucres Analysis Support System) � Gegraphical Information System Software � Run on unix oprating systems (Solaris, Linux, etc.) � Advantage – Distributed on internet (Free) – Raster (gridded) data – Source codes available (C language) – Modules can be developed by users with the GRASS developers' library. � Disadvantage – Unix – Inexcelent graphical user interface
Example of spatial data managed in GRASS GIS Obserbation climatology Population density Assessment results GCM results
Collaboration with climate model Atmosphere Climate model Emission model CCSR/NIES CGCM Ocean Land Surface AIM Socio-Econ. & Emission Scenario (Asian-Pacific Integrated Water Landuse Resource Model) Crop Socio-Econ. Productivity Factors Food Demand And Supply Impact model Adaptation
Simplified framework Global average Climate data GCM outputs temperature increase Climate module Socio-economic Future climate change scenario Water balance module Water resource module Water demand module Water scarcity evaluation Water impact Crop productivity module Global trade module Agricultural impact Natural ecosystem module Health impact module
Crop productivity Climate data Soil data Chemical Temperature characteristics Precipitation Slope Radiation Texture Wind Humidity Human Input Irrigation Changes in the potential productivity of rice from 1990 to 2050 under the climatic conditions -500 0 +500 (kg/ha) Machinery projected using the CCSR/NIES GCM Fertilizer
River discharge Surface runoff River routing Precipitation Elevation Evaporanspiration Temperature Soil characteristics 2100 1990 Annual river discharge in 1990 and 2100 (UIUC climate model)
Water demand (withdrawal) Driving force Spatial distribution Population density Irrigated area Cropland distribution Population Water supply 1990 coverage GDP or IVA 2050 (mm/year) 30 300 0.3 3
Water consumption in India (scenario analysis) 1995 2032 Baseline Fortress World WATER CONSUMPTION 2032 700.0000 Policy Reform 600.0000 500.0000 CONSUMPTION(km^3/year) 400.0000 300.0000 200.0000 MF 100.0000 FW PR GT 0.0000 1990 2000 2010 2020 2030 2040 YEAR Change of water consumption from 1995 to 2032 m 3 /ha/year (Domestic + Agriculture + Industry) 1 40 200 1000 5000
Surface runoff as Water supply Field capacity Evapotranspiration Vegetation Temperature Soil Wind speed Radiation CCCma NIES Humidity 表面流出量の変化 Change of surface runoff （ 2050s － 1980s ） (2050s – 1980s) 10 100 (mm/year) -100 -10 0 MPI
River basin for water scarcity Chiangjiang Mekong Ganges assessment Indus
Water Stress Index (=Withdrawal/Renewable Water) 2000 2020 1 5 10 1 5 10 0 20 40 60 80 100 ～ 0 20 40 60 80 100 ～ (%) (%) Water Stress Index (ratio between total withdrawal and renewable water resource) 2050 ECONOMIC OPTIMUM
Water stress index = Withdrawal / Surface runoff Water scarcity 1.2 0.25 1 0.2 0.8 0.15 0.6 0.1 0.4 0.05 0.2 0 0 2050(1980) 2055(1985) 2050(1980) 2055(1985) Ganges Mekong CCC LINK (1980-89) ECHAM4 Ten-year average (1980-89) CCSR/NIES
Malaria Reproduction rate of malaria vector Temperature Soil moisture Expansion of the area affected by malaria
Diarrhea / capita Water supply coverage Temperature Diarrhea Water supply coverage GDP/capita Environmental 1.5 2000 A1B A2 Diarrheal incidence per capita per year consideration B1 B2 1.2 0.9 0.6 0.3 0.0 EMRO_B EURO_B EURO_C EMRO_D EURO_A SEARO_D AFRO_D AFRO_E AMRO_B AMRO_D WPRO_B AMRO_A WPRO_A Diarrhea incidence per capita per year in 2000 (bar graph) and GBD Region in 2055 for 4 SRES scenarios ( □ A1B, △ A2, ◇ B1, ○ B2).
Forest vegetation IS92c scenario with low climate sensitivity IS92c scenario with low climate sensitivity Forest diminishment Temperature Precipitation Evapotranspiration IS92a scenario with medium climate sensitivity IS92a scenario with medium climate sensitivity Max. velocity of forest movement IS92e scenario with high climate sensitivity IS92e scenario with high climate sensitivity Diminishment of forest Diminish of forest Replacement of forest type with the risk of diminishment
Future extension � Linkage with AIM/CGE model – Results of
Crop productivity Climate data Soil data Chemical Temperature characteristics Precipitation Slope Radiation Texture Wind Humidity Human Input Irrigation Changes in the potential productivity of rice from 1990 to 2050 under the climatic conditions -500 0 +500 (kg/ha) Machinery projected using the CCSR/NIES GCM Fertilizer
Agricultural trade JPN CHN IDI CAN USA E_U Producer price change (%) Rice -0.01 -1.58 17.96 -40.16 -0.06 -4.93 Wheat 4.91 8.47 125.11 -13.10 4.76 8.92 Production Demand Other grains 1.81 0.79 1.80 -43.59 -1.46 -3.36 Other crops -0.01 -0.28 1.90 2.76 -0.10 -0.05 Livestock -0.19 -0.09 2.84 -1.22 -0.59 -0.04 Crop product- Population Other agricultural products -0.15 -0.01 0.30 -0.35 -0.07 0.04 Manufacture 0.03 -0.12 -1.10 0.61 0.03 -0.02 ivity change Services 0.03 -0.16 Consumer -0.93 0.69 0.02 -0.02 Production change (%) Rice 0.11 -0.25 -1.76 105.99 0.23 2.03 Tech. Improve preference Wheat -6.60 -3.97 -7.64 115.07 2.87 -3.64 Other grains -15.56 -1.39 -1.33 89.41 -4.04 -6.50 Other crops 0.11 -0.07 -4.25 -2.26 0.25 -0.03 Labor Livestock 0.09 -0.24 -2.27 0.94 0.03 -0.22 Trade Other agricultural products 0.11 -0.27 -4.73 0.69 0.04 -0.22 Land Manufacture -0.01 0.31 -0.37 -1.62 0.03 0.05 Services 0.00 0.00 -2.62 -0.02 0.01 0.01 Tariff etc. Consumer price index (%) 0.001 0.001 6.047 0.513 0.017 -0.010 Income change per capita (%) 0.026 -0.236 -0.617 0.833 0.026 -0.009 Social welfare change (%) 0.022 -0.219 -4.892 0.343 0.009 0.003
Recommend
More recommend
