Introduction to AIM/Impact model National Institute for - - PowerPoint PPT Presentation

SLIDE 1

Introduction to AIM/Impact model

National Institute for Environmental Studies

SLIDE 2

Items of the presentation

Overview of AIM/Impact

model

– Structure – Examples of the

assessed results

Reference

– Chapter 3 of AIM BOOK

SLIDE 3

AIM/Impact in AIM Framework

SLIDE 4

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.

SLIDE 5

Framework of the AIM/Impact model

OCEAN

Energy and carbon budget of Ocean

HYDRO

Surface water balance Routing module

WATER

Supply infrastructures demand

ENERGY

Energy technology and resources

CLIMATE

Radiation, Energy balance, Temperature and Sea level rise

FOOD

Production and Demand

LAND

Land-use allocation and GHGs emission

CGE

Supply and demand equilibrium Of goods, energy, water, land and labor

VEG

Vegetation dynamics

POP

Population, Fertility and Mobility

HEALTH

Health impacts of Environmental Change

ENV

Environmental Pressure and counter-measure

CYCLE

Chemistry of GHGs

AIM/Emission AIM/Emission AIM/Climate AIM/Climate

SLIDE 6

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.

SLIDE 7

Computation framework

GRASS database Variable spatial resolution Meshed raster data GRASS model commands

Developed with F77 or C language

GRASS Analysis commands

Visualization Average, etc.

Climate scenario creator

UNIX shell program

Data import interface GRASS commands Original data Climate data GCM results Soil property Land-use Population etc.

GRASS on UNIX Climate scenario Input data Output data Output data GIS data

Analysis on PC

SLIDE 8

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

SLIDE 9

Example of spatial data managed in GRASS GIS

Obserbation climatology GCM results Population density Assessment results

SLIDE 10

Collaboration with climate model

CCSR/NIES CGCM

AIM

(Asian-Pacific Integrated Model)

Emission model Climate model Impact model

Atmosphere Land Surface Ocean Adaptation Socio-Econ. & Emission Scenario Water Resource Landuse Crop Productivity Food Demand And Supply Socio-Econ. Factors

SLIDE 11

Simplified framework

Climate module Climate data GCM outputs Global average temperature increase Future climate change Water balance module Water resource module Crop productivity module Natural ecosystem module Health impact module Global trade module Water demand module Socio-economic scenario Water scarcity evaluation

Water impact Agricultural impact

SLIDE 12

Crop productivity

• 500 0 +500 (kg/ha)

Changes in the potential productivity of rice from 1990 to 2050 under the climatic conditions projected using the CCSR/NIES GCM

Climate data

Temperature Precipitation Radiation Wind Humidity

Soil data

Chemical characteristics Slope Texture

Human Input

Irrigation Machinery Fertilizer

SLIDE 13

River discharge

Annual river discharge in 1990 and 2100 (UIUC climate model) 1990 2100

River routing

Elevation

Surface runoff

Precipitation Evaporanspiration Temperature Soil characteristics

SLIDE 14

Water demand (withdrawal)

1990 2050 0.3 3 30 300 (mm/year)

Driving force

Irrigated area Population Water supply coverage GDP or IVA

Spatial distribution

Population density Cropland distribution

SLIDE 15

Water consumption in India (scenario analysis)

1995 Baseline 2032 Fortress World 2032 Policy Reform

WATER CONSUMPTION 0.0000 100.0000 200.0000 300.0000 400.0000 500.0000 600.0000 700.0000 1990 2000 2010 2020 2030 2040 YEAR CONSUMPTION(km^3/year) MF FW PR GT

1 40 200 1000 5000

m3/ha/year

Change of water consumption from 1995 to 2032 (Domestic + Agriculture + Industry)

SLIDE 16

Surface runoff as Water supply

• 100 -10 0

10 100 (mm/year) CCCma MPI NIES

表面流出量の変化 （2050s－1980s）

Evapotranspiration

Temperature Wind speed Radiation Humidity

Field capacity

Vegetation Soil

Change of surface runoff (2050s – 1980s)

SLIDE 17

River basin for water scarcity assessment

Ganges Chiangjiang Indus Mekong

SLIDE 18

Water Stress Index (=Withdrawal/Renewable Water)

2000 2020 2050 Water Stress Index (ratio between total withdrawal and renewable water resource) ECONOMIC OPTIMUM

0 20 40 60 80 100 ～ (%) 1 5 10 0 20 40 60 80 100 ～ (%) 1 5 10

SLIDE 19

Water scarcity

Ganges Mekong

0.2 0.4 0.6 0.8 1 1.2 2050(1980) 2055(1985) 0.05 0.1 0.15 0.2 0.25 2050(1980) 2055(1985)

CCC ECHAM4 CCSR/NIES LINK (1980-89) Ten-year average (1980-89)

Water stress index = Withdrawal / Surface runoff

SLIDE 20

Malaria

Reproduction rate of malaria vector

Temperature Soil moisture

Expansion of the area affected by malaria

SLIDE 21

Diarrhea

0.0 0.3 0.6 0.9 1.2 1.5 AFRO_D AFRO_E AMRO_A AMRO_B AMRO_D EMRO_B EMRO_D EURO_A EURO_B EURO_C SEARO_D WPRO_A WPRO_B GBD Region Diarrheal incidence per capita per year 2000 A1B A2 B1 B2

Diarrhea incidence per capita per year in 2000 (bar graph) and in 2055 for 4 SRES scenarios (□A1B,△A2,◇B1,○ B2).

Diarrhea / capita

Water supply coverage Temperature

Water supply coverage

GDP/capita Environmental consideration

SLIDE 22

IS92c scenario with low climate sensitivity IS92a scenario with medium climate sensitivity IS92e scenario with high climate sensitivity Diminish of forest Replacement of forest type with the risk of diminishment IS92c scenario with low climate sensitivity

IS92a scenario with medium climate sensitivity IS92e scenario with high climate sensitivity

Diminishment of forest

Forest vegetation

Forest diminishment

Temperature Precipitation Evapotranspiration

• Max. velocity of

forest movement

SLIDE 23

Future extension

Linkage with AIM/CGE model

– Results of

SLIDE 24

Crop productivity

• 500 0 +500 (kg/ha)

Changes in the potential productivity of rice from 1990 to 2050 under the climatic conditions projected using the CCSR/NIES GCM

Climate data

Temperature Precipitation Radiation Wind Humidity

Soil data

Chemical characteristics Slope Texture

Human Input

Irrigation Machinery Fertilizer

SLIDE 25

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 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

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

Services 0.03

• 0.16
• 0.93

0.69 0.02

• 0.02

Production change (%) Rice 0.11

• 0.25
• 1.76

105.99 0.23 2.03 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

Livestock 0.09

• 0.24
• 2.27

0.94 0.03

• 0.22

Other agricultural products 0.11

• 0.27
• 4.73

0.69 0.04

• 0.22

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 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

Production

Crop product- ivity change

• Tech. Improve

Labor Land

Trade

Tariff etc.

Demand

Population Consumer preference