Regional Climate Change Scenario over East Asia
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Transcript of Regional Climate Change Scenario over East Asia
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Regional Climate Change ScenarioRegional Climate Change Scenarioover East Asiaover East Asia
2003 JuneTrieste, ICTP RegCM Workshop
Won-Tae KwonMeteorological Research Institute, Korea
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We are interested in the impacts of future climate change in Korea
Climate Change Simulation with CGCM
Regional Climate Change Scenario - dynamical downscaling - statistical adjustment
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• Need for impact assessment and adaptation on future climate change for various socio-economic and natural sectors for the sustainable development
• Korea is located at the eastern coast of the largest continent of the earth – large climate variability
• Meso-scale complex topography and high population density
• Most people want to hear about what will happen in their own back yards
• Need for high-resolution regional climate information for impact study
Issues we need to consider….
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Coupled Climate Model ECHO-G
ECHAM4T30/L19
dt = 30 minuteRoeckner et al. 1996, MPI
HOPE-GT42 + equ. ref. /L20
dt = 2 hoursWolff et al. 1997, DKRZ
OASISdt = 1 day
Valcke et al. 2000, CERFACS
10 fluxes
4 surfaceconditions
MPI M&D* coupled climate model
- AGCM: ECHAM4 T30 (3.75)
- OGCM: HOPE-G T42 (2.8 )
(0.5 at 10S~10N)
sea ice model included
- Coupler: OASIS
Flux corrections
- annual mean heat and fresh-water flux correction - no momentum flux correction
*MPI M&D: Max-Planck Institute for Meteorology Models and Data Group
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ECHO-G 1000-year Control Simulations
Performed at MPI M&D, Germany
Present day values (1990) for
GHG concentrations
Stable global mean surface
temperature and thermohaline
circulation
ENSO
- similar pattern to observed
- 2-year period dominant
(Legutke and Cubasch, 2001)
Annual mean T2m and precipitation rate (red line: 11-yr moving average)
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Performed at METRI/KMA, Korea
Greenhouse gases only
- CO2, CH4, N2O, CFCs etc
- 1860~1990: observed
- 1990~2100: SRES scenarios
SRES updated scenarios
- A2: pessimistic scenario
(CO2 820 ppmv by 2100)
- B2: optimistic scenario
(CO2 610 ppmv by 2100)
A2
B2
ECHO-G SRES A2, B2 scenario simulations
GHGs scenarios for 1860-2100
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ECHO-G Scenario Simulation Results(numbers are 2090s mean)
Glo
bal
Precipitation (%)Temperature( )℃
4.6
3.0
6.5
4.5
4.4
2.8
10.5
6.0
Eas
t A
sia
A2
B2
A2
B2
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2050s Climate Change Patterns: A2 G
loba
l
Precipitation (%)Temperature( )℃
Eas
t A
sia
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2050s Climate Change Patterns: B2G
loba
l
Precipitation (%)Temperature( )℃
Eas
t A
sia
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Seasonal Projection over East AsiaSeasonal Projection over East Asia
DJF
Precipitation (%)Temperature(℃)
MAM
JJA
SON
A2-B2: Mitigation effect
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Climate Change Projection over East Asia (Multi-Model Ensemble)
Climate Change Projection over East Asia (Multi-Model Ensemble)
-2
0
2
4
6
Mean Max Min Std Dev
2020s 2050s 2080s
-2
0
2
4
6
Mean Max Min Std Dev
-5%
0%
5%
10%
15%
Mean Max Min Std Dev
-5%
0%
5%
10%
15%
Mean Max Min Std Dev
A2
B2
Temperature (℃)
Precipitation (%)
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Northern limit of Bamboo habitation
Check point
0 100km
Distribution of Phyllostachys
19th C 2002
경북 영천 자양면 충효리경북 영천 자양면 충효리
경북 예천 풍양면 와룡리경북 예천 풍양면 와룡리
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TOPOGRAPHY (M)
27km resolution
400 km resolution
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ECAHM4/HOPE-G(spectral data)
After post process Initial Condition ( p-level grid data)
Regional Climate Model(MM5)
Horizontal, verticalinterpolation
detailedtopography
CD-Rom
INTERPB
I.CB.C
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Raid storage sever
NAS storage sever
Myrinet hub
10/100 switch hub
Monitoring system
UPS
16 nodes ( dual CPU ) cluster
Electrometer
Myrinet Ethernet
Computing Resources: HPC CLUSTER (ENVICOM)
· CPU - AMD MP2000+ 16Node ( 32 CPUs )· MEMORY - ECC Registered DDR Ram 2 GB· Myrinet - optical cable & switch, 2U high, 3-slot enclosure for switch, 16 ports· NAS - 1.8 TB, Network attached Storage, SCSI raid Storage
15 cpu hours for 1 year integration != 1 week for 10 year integration !
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Grid size of global Grid size of global modelmodel
Grid size of regional model
ECHAM4 USGS data
96 x 48 (~400 km) 125 x 105 (~27 km)
Orography of global model(bilinear interpolation, ZZechamecham)
Orography of regional model(ZZmm5mm5)
Orography Blending((ZZblnbln) )
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0 100 200 400 600 800 1000 100 200 400 600 800 1000 1500 2000 2500 30000 1500 2000 2500 3000
(a) ECHAM4/HOPE-G (b) NON-BLENDED (c) BLENDED
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Result of Dynamic Downscaling (2001-2030)Result of Dynamic Downscaling (2001-2030)
Seasonal mean 2m air Temp. for 30 yrsECHO-G MM5
10.865
21.983
15.741
2.1
10.026
20.599
12.364
0.5380
5
10
15
20
25
MAM J JA SON DJF
Tem
p. (
C) a
a
ECHAM4/HOPE- G MM5
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Monthly mean 2m air Temperature
ECHAM4/HOPE-G MM5ECHAM4/HOPE-G: y = 0.0018x + 12.531
MM5: y = 0.0059x + 7.2772
2001 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029
- 8
- 7
- 6
- 5
- 4
- 3
- 2
- 1
0
1 2 3 4 5 6 7 8 9 10 11 12
Month
Tem
p.
change (
C)
z z
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[Seasonal mean precipitation for 30 yrs]ECHO-G MM5
2.809
3.635
2.485
1.2942.669
4.033.104
1.385
0
1
2
3
4
5
MAM J JA SON DJF
PRC
P (m
m/d
ay)
aa
ECHAM4/HOPE- G MM5
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Monthly mean precipitation
2001 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029
- 3
- 2
- 1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Month
PR
CP c
hang
e (m
m/d
ay) a
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1860 1950 2000 2030 2100
A2-G
Control
Finished (2002)
In Progress (2003)
Dynamic Downscaling Progress
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We provide regional climate information with dynamic downscaling.
Does it good enough for assessment studies with confidence?
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Transfer function using statistical method 70% of RMS error were reduced
Transfer FunctionTransfer Function
[G2G Pilot transfer function]
RCM ANAL
EOFA
REGA
TCRCM = f(TCANAL)
GRID DATA CORRECTION
Eigen Mode Eigen Mode
Significant Eigen Mode
RCM C_RCM
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TC1 , TC2 in RCM (red), O_KMA (blue), after adjustment (green)
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RMS error
SeasonRCM RCM_C1 RCM_C2
CORRECTED PERCENT
MAM 4.73 1.78 1.48 68.7%
JJA 9.70 1.45 1.31 86.5%
SON 6.64 2.20 1.86 72.0%
DJF 4.03 2.16 2.11 47.6%
ANNUAL 6.29 1.90 1.69 73.1%
RMS error of daily mean temperature
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Summary
• We may be able to provide reasonable future regional climate information for impact assessment studies with combination of dynamic downscaling and statistical adjustment.
• Statistical adjustment is successful for temperature, however, we still need more efforts for precipitation because there is no outstanding eigen mode.
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• Reduction rate of GCM to RCM – a nested domain?• Understanding the variability of future climate change –
mean, range, extreme events, seasonal and local difference, etc. – how can we analyze these issues?
• Statistical downscaling of RCM data• Understanding and communication with experts from
various sectors – what kind of data they need for impact assessment
Further Thoughts on Unsolved Obstacles
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Future Plans…..
• EHCO run with A2 GHG+Aerosol scenario in 2003 and maybe more later on
• Using RegCM3 for the downscaling of EHCO model projections
• Sensitivity test and Optimization for East Asia domain• Statistical downscaling (transfer function) for regional
scenario
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0 100km
IDEAS for Future Works Integrated local climate change assessment
TrendFlood/droughtWater resourceAgricultureFisheryHealthEcosystemForestRoadTourismRecreationEnergy IndustryTransportationConstructionEconomy…
Multi-disciplinary efforts
Local climate change scenario (240 years)
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Thank YouFor Your Attention!