Regional Climate Change ScenarioRegional Climate Change Scenarioover East Asiaover East Asia

2003 JuneTrieste, ICTP RegCM Workshop

Won-Tae KwonMeteorological Research Institute, Korea

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

• 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….

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

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)

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

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

2050s Climate Change Patterns: A2 G

loba

l

Precipitation (%)Temperature( )℃

Eas

t A

sia

2050s Climate Change Patterns: B2G

loba

l

Precipitation (%)Temperature( )℃

Eas

t A

sia

Seasonal Projection over East AsiaSeasonal Projection over East Asia

DJF

Precipitation (%)Temperature(℃)

MAM

JJA

SON

A2-B2: Mitigation effect

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 (%)

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

TOPOGRAPHY (M)

27km resolution

400 km resolution

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

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 !

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) )

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

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

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

[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

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

1860 1950 2000 2030 2100

A2-G

Control

Finished (2002)

In Progress (2003)

Dynamic Downscaling Progress

We provide regional climate information with dynamic downscaling.

Does it good enough for assessment studies with confidence?

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

TC1 , TC2 in RCM (red), O_KMA (blue), after adjustment (green)

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

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.

• 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

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

0 100km

IDEAS for Future Works Integrated local climate change assessment

TrendFlood/droughtWater resourceAgricultureFisheryHealthEcosystemForestRoadTourismRecreationEnergy IndustryTransportationConstructionEconomy…

Multi-disciplinary efforts

Local climate change scenario (240 years)

Thank YouFor Your Attention!