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Toshio KoikeThe University of Tokyo
Climate Chang Impacts on Water and Societyand
Adaptation Strategy in Africa
Jomo Kenyatta University of Agriculture and Technology, 15-16 August, 2013
- Climate and Water Changes, unequivocal and uncertain
- Date Integration, a science and technology challenge- GEOSS, a coordination mechanism for working together
Toshio KoikeThe University of Tokyo
Climate Chang Impacts on Water and Societyand
Adaptation Strategy in Africa
Jomo Kenyatta University of Agriculture and Technology, 15-16 August, 2013
- Climate and Water Changes, unequivocal and uncertain
- Date Integration, a science and technology challenge- GEOSS, a coordination mechanism for working together
Warming of the climate system is unequivocal.(IPCC AR4, 2007)
3
58 simulations by 14 models19 simulations by 5 models
Projected changesin extremes
It is very likely thatheavy precipitationevents will continue tobecome more frequent.
IPCC AR4
It is likely that areaaffected by droughtincreases.
5 5
Variability of Climate and Water Cycle: Unique Roles of Water
6
Radiative Cooling
Radiative Cooling
Surface Heating
UpwardLong Wave Radiation
cloudDownwardLong Wave Radiation Radiative Warming
Stefan-Boltzmann Law: Material emits radiativeenergy with the forth power of the surface temperature.
7
Variability of Climate and Water Cycle: Unique Roles of Water
warm wet
Warm Air - Cool Air and Dry Air - Wet Air
warmcool drywet
Regardless of kinds of gases,a same number of molecules isincluded in a certain volume of gasunder a certain temperature andpressure.
Dry air consists of nitrogen (MW=28)and oxygen (MW=16).The ratio is 4 to 1. Average MW=28.8In wet air, a certain number ofmolecules of nitrogen and oxygen arereplaced with the same number ofwater molecules of water (MW=18)
28.8
28.8
28.8
28.8 28.8
perfectly dry air
28.8
18.0
28.8
28.8 28.8
a little bit wet air
28.8
18.0
18.0
28.8 18.0
very wet air
Variability of Climate and Water Cycle: Unique Roles of Water
Which isHeavier?
Variability of Climate and Water Cycle: Unique Roles of Water
warm wet
Variability of Climate and Water Cycle: Unique Roles of Water
11 11
C02 increase
long-wave radiation
convection
sunshine
subsidence dry subsidence dryHeavyRainfall
radiation(green house effect)
--- convection equilibrium
Variability of Climate and Water Cycle: Unique Roles of Water
Temperature Saturated Water Vapor Pressure Cloud Formation
12 12
2XCo2
CO2
Heavier Rainfallin Smaller Area
Impacts of CO2 Increaseon the Water Cycle
Predicted by Models
Bigger Annual Variationof the Summer Rainfall in India
Heavy Rainfall around Japan（CCSR-NIES-JAMSTEC）
Variability of Climate and Water Cycle: Unique Roles of Water
Recent trends, assessment of human influence on the trend and projections forextreme weather events for which there is an observed late-20th century trend.
14
Toshio KoikeThe University of Tokyo
Climate Chang Impacts on Water and Societyand
Adaptation Strategy in Africa
Jomo Kenyatta University of Agriculture and Technology, 15-16 August, 2013
- Climate and Water Changes, unequivocal and uncertain
- Date Integration, a science and technology challenge- GEOSS, a coordination mechanism for working together
mitigation adaptation
ClimateSystem
WaterResources
ManagementSystem
WaterCycle
Agriculture/FoodBiodiversity/Ecosystem
HealthEnergy
Coordinated and Integrated Efforts for Working Together
MDGsClimate Change Biodiversity
Climate Change
Sustainable Development
16
3rd GEOSS African Water Cycle Coordination Initiative (AfWCCI) Workshop : - El Jadida, Morocco4-5 February, 20133rd GEOSS African Water Cycle Coordination Initiative (AfWCCI) Workshop : - El Jadida, Morocco4-5 February, 2013
17
Reanalysis &Observations
20th CenturyGCM
Regional andSynoptic Changes
in Climate
Futureprojections
Select GCMsSelect GCMs
Numericalmodeling
Numericalmodeling
Global WeatherForecasts
Ground-basedObservations
Downscaling&
Bias correction
Downscaling&
Bias correction
CurrentFloods
Flood ForecastingAdaptation
FutureFloods
Downscaled ClimateVariables
Understanding ofLocal Circulation
MechanismsExtreme
weather events
Basin scale | Mesoscale | Regional scaleBasin scale | Mesoscale | Regional scale
FUTU
REPAST / PRESEN
T
Flood modelingFlood modeling
Satellite DataAssimilation
by Dr. Mutua
18
DB
DB
0
50
100
150
200
250
300
350
199219941996199820002002200420062008201020122014201620182020
A 1:高度成長社会
A2：多元化型
B1:持続発展型
B2：地域共存型
DB
DB
DB
DB
DB0
50
100
150
200
250
300
350
199219941996199820002002200420062008201020122014201620182020
A 1:高度成長社会
A2：多元化型
B1:持続発展型
B2：地域共存型
DB
DB0
50
100
150
200
250
300
350
199219941996199820002002200420062008201020122014201620182020
A 1:高度成長社会
A2：多元化型
B1:持続発展型
B2：地域共存型
DB
DB
DB
Meteorology
Ecosystem
AgricultureHydrology
LandUse
Climatology
Health
农业
เกษตรกรรม
농업
Where is data?How to access?
Technical Termsamong
DifferentDisciplines
Quality?Reliability?
18
10
10
10
10
10
10
9
10
11
12
13
14
10
10
15
16
1010 10 10 1010 10 10
Dat
a Si
ze,
Byte
s
2001
TeraFLOPSGigaFLOPS PetaFLOPS
109 1410 11 12 13 15 16 17 18
ExaFLOPS
Real Demonstrated Performance doing useful Science
10Compute Speed, FLOPS
2020
Computational Modeling in Two Stages;Computational Modeling in Two Stages;Driving Evolution & Enabling RevolutionDriving Evolution & Enabling Revolution
EvolutionaryEvolutionary
RevolutionaryRevolutionary
2010
2x 2 resolution;synoptic scales
2005
.25x .25 resolution;hurricanes, storm fronts
.25x .25 resolution;add cloud, chemistry,& radiation effects
Fully interactive (biology,chemistry, physics)ensemble simulations inan operational mode
2015
Nanotechnology
InformationPower Grid
HeterogeneousCluster
HomogeneousCluster
Interactivephysics, biology,chemistry;assimilation ofsatellite data
IPCC AR4 (2007): 40TB AR5 (2012): 2.6PB
19
20
Mejerda RiverPrecipitation Oct – Jan (1981-2000)
cccma_cgcm31
cccma_cgcm31_t63
Miroc32_hires
Mpi_echam5
Mri_cgcm23_2
Ukmo_hadcm3
GPCP
bccr_bcm20
cnrm_cm3
csiro_mk30
gfdl_cm21
csiro_mk35
gfdl_cm20
giss_model_eh
giss_model_er giss_aom iap_fgoals
1miroc32_
nedres
miub_echog
ncar_ccsm30
ncar_pcm1
ukmo_hadgem1
ingv_echam4
inmcm_30
ipsl_cm421
It is virtually certain thatdrought will become more severe.
0
200
400
600
800
1000
rain
fall
mm
/yea
r
Annual Average Rainfall
1986-20002051-2065
0
200
400
600
800
1000
rain
fall
mm
/yea
r
Annual Average Rainfall
1986-20002051-2065
0
200
400
600
800
1000
rain
fall
mm
/yea
r
Annual Average Rainfall1986-20002051-2065
AIN BEYA OUED SLOUGUIAKALAAT ESSENAM
Mejerda River
22
23
GCOM-W
GCOM-C
EarthCARE
GPM
ALOS-2 ALOS
Cryosat-2
SMOS
ADM-Aeolus
METEOSAT
MSGMTG
EPS Metop
Post EPS
SMAP
Satellite Observation Integration
26
m
0
0.4
0.8
1.2
1.6
2
0
2
4
6 Bir Lakhdar Souk Sebt 2
cm
Groundwater Level Variations (satellite-observed)
Groundwater Level Variations (ground-observed)
-10
-5
0
5
10
2002 2003 2004 2005 2006 2007 2008
Future GW Variations
-1.3mm/year
GW
sto
rage
ano
mal
y (c
m)
18/20G
W s
tora
ge a
nom
aly
(cm
)GW (TWS – SM)GW (LDAS-WEBDHM)Inter-comparison
28
Soil Moisture Snow
MicrowaveRadiometer
Precipitation
Surface Emissivity & Temp.
Aqua
TRMM
Data Assimilation Coupled with Microwave Radiometer
LandSurfaceScheme
SnowPhysicsModel
CloudPhysicsModel
Passive Microwave Remote Sensing
Prec
ipita
tion
pred
icta
bilit
y us
ing
DA
& P
MW
R/S
29
Surface roughnessField Experiment
Improved surfaceemission modeling
ARPS/LDAS
LA-RTM
Improvedsurface
conditions
IMDAS
DMRTw-t
A-RTMImproved
atmosphereconditions
Shadowing effectSatellite TBs
Low freq.
Satellite TBsHigh freq.
Obs. oper.
coupling
Feed back mechanism
GCM ReanalysisOutput
Research Framework by Dr. Kuria
3rd GEOSS African Water Cycle Coordination Initiative (AfWCCI) Workshop : - El Jadida, Morocco4-5 February, 20133rd GEOSS African Water Cycle Coordination Initiative (AfWCCI) Workshop : - El Jadida, Morocco4-5 February, 2013
Experiments
TRMM (Obs.) No assimilation Assimilation (qv,qc,qs,qi)
After 1 hour
After 3 hours
TRMM (Obs.) • No assimilation poor simulation of theevent
• Simulates the eventwrong place• Persistent overestimation NW ~(32E,0N)
• Assimilation improves fore cast• Spatial pattern similar to observed(TRMM)• Quantitatively: still a way to go
by Dr. Mutua
1. Carbon Allocation Model allocates net primary production toleaf and root carbon pool.
2. Carbon-pool Update Model calculates carbon loss as normalturnover and drought stress loss.
3. Carbon-LAI conversion model calculates leaf area index,which is needed to run land surface model at next time step.
Hydro-SiB Dynamic Vegetation Model (DVM)
Seasonal Change of LAI by Coupled Model and Satellites
MODIS LAI
Simulated LAI
LAI: Simulated vs. MODIS
Standardized anomaly index (SA) for estimatedannual maximum leaf area index (green line) fromWEBDHM+DVM and observed annual crop productionin Tunisia (orange line).
River Runoff
33
Figure 5.7. Same as Figure 5.6., but for daily maximum land surface temperature.
Climate ChangeImpact Assessmentof Biomass Productionin the Volta River Basin
Precipitation Change Projected each Model
Air Temperature Change Projected each Model
issuesstake-holder
stake-holder
stake-holder
stake-holder
stake-holder
Sharing Data and InformationExchanging Knowledge, Experiences and Ideas
Working Together
Climate ChangeFlood, DroughtWater QualityFood SecurityBiodiversity
EnergyPolicyMaker
RiverManager NPO
Farmers
Public
HydrologyClimatologyEngineering
AgricultureEcology
RSGIS IT
Toshio KoikeThe University of Tokyo
Climate Chang Impacts on Water and Societyand
Adaptation Strategy in Africa
Jomo Kenyatta University of Agriculture and Technology, 15-16 August, 2013
- Climate and Water Changes, unequivocal and uncertain
- Date Integration, a science and technology challenge- GEOSS, a coordination mechanism for working together
GEO, the Group on Earth ObservationsAn Intergovernmental Body
with 89 Members & 64 Participating Organizations• Earth Observation Summit I (July 2003: Washington DC)• EO Summit II (April 2004: Tokyo)• EO Summit III (February 2005: Brussels)• EO Summit IV (November 2007: Cape Town)• EO Summit V (November 2010: Beijing)
A Global, Coordinated, Comprehensive and SustainedSystem of Observing Systems
GEOSS
GEOSSGlobal Earth Observation System of Systems
Vision for GEOSSThe vision for GEOSS is to realize a future
wherein decisions and actions for the benefit ofhumankind are informed by coordinated,
comprehensive and sustained Earthobservations and information.
37
38
Jan. 2009
Feb. 2011
Sept. 2009
Feb. 2012
Jan. 2012
Feb. 2013
1st GEOSS African Water Cycle Symposiumin Tunis, Water-related Issues & Roles of EO
1st Task Team Meetingin Geneva, Strategyfor CoordinatedEO and CB
2nd African Water Cycle Symposium in Addis AbabaPlanning for Demonstration
GEO-UNESCO Joint Workshop in NairobiReport on Demonstrations and IWRM CB Program
3rd African Water Cycle Symposium in LibrevilleBasic Idea of Implementation, Statement to Rio+20
3rd African Water Cycle Coordination InitiativeWorkshop in El Jadida, Draft Implementation Plan
39Nov. 2013 1st GEOSS Africa & Asia Joint Water Cycle Symposium in Tokyo1st AfWCCI Implementation Plan and 2nd AWCI Implementation Plan
40
GEOSS African Water Cycle Coordination Initiative(AfWCCI)
Based on a collaboration between the Group on Earth Observations(GEO) and RBOs in Africa, Global Earth Observation System ofSystems (GEOSS) supports application of coordinated, comprehensiveand sustained Earth Observations and information across trans-boundary river basins in Africa, particularly focusing on:
Goal : To facilitate better managementin trans-boundary rivers in Africa
●Observation and data management●Capacity development on:observationdata archivingModelingPredictionclimate changeimpact assessmentdata integration
Improvement ofthe water resourcesmanagement capacity
ParticipatingMedjerda, Niger, Nile, L/Victoria, L/Chad, Okavango,Orange-Senqu, Senegal, Zambezi, Oum Er-Rabia,L’Ogooue
