future climate projection and using future climate data to ... · as stress test to test robustness...

Future Climate Projection and Using Future Climate Data to Support Development Planning

Suppakorn Chinvanno Southeast Asia START Regional Center

Chulalongkorn University

Regional training workshop on adaptation for the Asian LDCs Siem Reap, Cambodia

20-24 August 2013

IPCC Fourth Assessment Report

SEA START RC copyright 2013

• Future climate projection and dataset for Southeast Asia

• Working with future climate data

• Examples: Using future climate data to support development planning

Topics

IPCC Fourth Assessment Report SEA START RC copyright 2013

Future Climate Projection and Dataset for Southeast Asia



We can observe that climate change has occurred in the 20th century.

How can we know what the future holds

Future climate projection and dataset for Southeast Asia

Climate change is slow and complex process Study on climate change is based on scenarios from

future climate projection


Future GHG Scenario

Future climate Scenario

Climate model - simulation



Global Climate Model – concern on scale resolution

• Projecting future climate scenario needs to simulate the whole globe – single system at the global scale

• Very time and resource consuming process

• Compromise with details loss – to recalculate to regain more details later

• Downscale process using regional climate model to add more details



Regional climate scenario • Dynamic downscaling by using ECHAM4 and ECHAM5 GCM

dataset (ECMWF Atmospheric General Circulation Model coupled with

University of Hamburg Ocean Circulation Model) • Global resolution ~2.8° • Forced by level of atmospheric CO2 according to IPCC SRES

A2/B2/A1B scenario

Future climate change scenario: An overview of Southeast Asia


Regional climate scenario for mainland Southeast Asia

• Resolution - geographic: 0.22 degree (approx. 25x25 km.)

• Resolution - temporal: daily

• GCM dataset:

• ECHAM4 (A2&B2) & ECHAM5 (A1B) Max-Planck-Institute for Meteorology / HadCM3 (A1B) – Hadley Center

• Timeframe

• 1970 - 2099 (ECHAM4)

• 1980 – 2069 (ECHAM5)

• 1980 – 2069 (HadCM3)

• Coverage

• Lat. 0-35ºN

• Lon. 90º-112ºE



Example – simulation result – ECHAM4 A2: Average daily maximum temperature (oC)



Example – simulation result – ECHAM4 A2: Average annual maximum temperature (oC)

Hottest day of the year



Example – simulation result – ECHAM4 A2: Number of hot days in a year (>=35 oC)



Example – simulation result – ECHAM4 A2: Average daily minimum temperature (oC)

Climate change in Thailand: Scenario of the future


Coolest day of the year

Example – simulation result – ECHAM4 A2: Average annual minimum temperature (oC)



Example – simulation result – ECHAM4 A2: Number of cool day in a year (<=16 oC)



Example – simulation result – ECHAM4 A2: Change in annual precipitation compare to 1980’s (%)



Note: Climate change is not uniform across space and time – multi-dimensions of change

Change in average maximum temperature

Change in hot period over the year

Working with Future Climate Data


Climate change in SEA at a glance

• SEA tends to be slightly warmer, but the hot area will be much wider

• Hot period of the year will be much warmer and longer

• Summertime will expand into winter

• Higher precipitation, increasing intensity as the length of rainy season tend to be more or less the same

Warmer and wetter

Different systems have different concern on the climate change



Issues of concern about climate scenario:

• Climate scenario is only a plausible future – NOT forecast

• Need to use these data in climate context – NOT weather – consider climate pattern over period of time

• Data from climate scenario is not “truth” – need to be interpreted with care – it indicates direction and magnitude of future change in a broad sense, limitation on pinpoint accuracy

• Good and less good information, never perfect information

• Uncertainty – need for multiple scenarios

• New and/or improved method and technique for generating climate scenario is yet to come



Frequently asked question:

1. What climate model is best?

2. If we cannot be certain about result of climate models, how can we justify climate change adaptation plan?

These questions are not relevant!

Change in thinking paradigm

Dealing with Uncertainty of Climate Model

What could be risk from consequences of future change?

To what extent can we accept such risk?

Work with multiple scenarios to increase robustness of adaptation/development plan



• Work with multiple projections – use every climate projections as stress test to test robustness of any future plan

0

50

100

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1 2 3 4 5 6 7 8 9 10 11 12

mm

Month

Bangkok

cccma_cgcm3_1

cnrm_cm3

csiro_mk3_0

gfdl_cm2_0

giss_model_e_r

ipsl_cm4

mpi_echam5

NCEP/NCAR reanalysis

Monthly average precipitation in the future




• Work with range of future change – worst case scenarios

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mm

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Bangkok

NCEP/NCAR reanalysis

Max

Min

Median

Monthly precipitation




• Find consensus among results of climate models

a) May to October

0.0

0.1

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0.9

1.0

0.0 0.1 0.2 0.3 0.4

RMS Error (mm/day)

Corr

ela

tion

b) November to April

0.0

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RMS Error (mm/day)

Corr

ela

tion

ukmo_hadgem1

ukmo_hadcm3

ncar_pcm1

ncar_ccsm3_0

mri_cgcm2_3_2a

mpi_echam5

miub_echo_g

miroc3_2_medres

miroc3_2_hires

ipsl_cm4

inmcm3_0

ingv_echam4

iap_fgoals1_0_g

giss_model_e_r

giss_model_e_h

giss_aom

gfdl_cm2_1

gfdl_cm2_0

csiro_mk3_5

csiro_mk3_0

cnrm_cm3

cccma_cgcm3_1_t63

cccma_cgcm3_1

bccr_bcm2_0

Source: Dr.Judy Eastham – CSIRO Land and Water

Concerns on use of climate scenario data




http://cc.start.or.th/

Climate data for distribution

• Daily maximum temperature (º C)

• Daily minimum temperature (º C)

• Daily precipitation (mm)

• Solar radiation (watt/m2)

• Wind speed (m / sec)

• Wind direction (degree from north)

• Relative humidity

Available in text file format for ease of use

Each file = 1 variable / 1 year

Total data size (A2/B2) approx. 100GB



• CC Distribution http://cc.start.or.th/




• CC Distribution http://cc.start.or.th/

Extracting climate change data for further analysis



Data represents centroid of the grids

Data be distributed to users in smaller domain of focus: • Watershed • Administrative boundary • Freehand selection

Data structure



Selecting data from relevant grids(s) for further analysis

• Selecting data from multiple grids for area analysis

(large area – using GIS tool to select data)

• Selecting data from selected grid(s) for analysis

(small area – hand pick grid(s) to select data based on lat./lon. coordinate)

How to conduct climate change risk assessment with limited dataset



Grid data – Savannakhet province Using GIS tool to select grids



Using climate change data to analyze change in future trend



CHANGE IN ANNUAL PRECIPITATION

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500

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2500

mm

Annual precipitation : comparison ECHAM4 A2 vs B2

Udonthani-Thailand

A2

B2



2,934 2,956 3,093

3,726

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500

1000

1500

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2500

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3500

4000

BASELINE 2020s 2030s 2040s

Wettest Year

2,562

2,655

2,512

2,685

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2450

2500

2550

2600

2650

2700


Median year

1,925

2,407 2,373 2,282

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1000

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Driest year

1000

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3500

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Precipitation In Svannakhet

CHANGE IN ANNUAL PRECIPITATION – EXTREME YEAR VS MEDIAN YEAR



CHANGE IN FREQUENCY OF HEAVY RAINFALL YEAR OVER THE DECADE

6 8



0

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mm

Precipitation

Baseline Median

Shift of rainy season

SHIFT AND CHANGE IN RAINFALL DISTRIBUTION PATTERN/RAINY SEASON

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Baseline

Future



91 94

108112

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120

Baseline 2020s 2030s 2040s

Number of hot day (>35°C)

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15 15

13

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25

Baseline 2020s 2030s 2040s

Number of cool day (<16 °C)

CHANGE IN LENGTH OF SUMMER /WINTER - SAVANNAKHET



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PRECIS ECHAM4

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PRECIS ECHAM4

2045-2064

1961-2000



Using climate change data to analyze impact and risk



Climate scenarios Land use/cover scenarios

Flood profiles Other hydrological regime

Hydrological Model Precipitation/ Tmax/ Tmin/ windspeed

Runoff profiles

Case studies: hydrological analysis

Input to impact analysis for risk assessment – quantitative analysis



Case study in Lower Songkram River basin - Thailand

Study area



Change in flood boundary in lower Songkram River basin

Source: WUP-Fin Group, MRCS Future

Now



Future Climate scenarios Crop management scheme

Crop Yield Scenarios

Crop Model

How does future climate pattern alter rice productivity?

Precipitation/ Tmax/ Tmin/ SRAD

Rice productivity: kg/ha



Rain-fed rice yield during 1990s vs 2030s vs 2050s



Commercial farming

Subsistence farming

Food crop Energy crop

Now: Business as usual

Food Bowl Green Energy –

Bio-Fuel

Example: Different agriculture strategy and future crop production scenarios in Chi-Mun river basin

Different development directions / government policy schemes bring

different context to think about climate change adaptation



Which development pathway would be more climate resilience in the future? Less risky with better economic potential?

Change in future crop production area – example of future land use scenarios

Cassava Maize Sugar cane



Use future climate data and crop model to determine development pathway that is less risky with better economic return

Flood during farming period (especially Aug. – Sept.)

More Simplified Analysis: Putting climate change into context

Higher risk due to higher precipitation

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1980-2009 2020-2049

mm

Total rain during Aug-Sep (median Year)

Note: Also higher chance of tropical storm which causes flood. (IPCC AR4)



Farmer - Wet season rain-fed system paddy rice

Dry spell

(little rain during July – Sept.)

Farmer - Wet season rain-fed system paddy rice

Less risk – Due to less dry-day occurrence during July and September in the future

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1980-2009 2020-2049

day

s Number of dry day occurrences (daily rainfall <3mm.)

during Jul-Sep (median Year)



Farmer - Wet season Farmer - Upland/Shift cultivation

Less risk – Rainy season seems to start slightly earlier with evenly

distribution of rainfall in the early part of the season, but higher precipitation

in the late season.

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200

7-Jan 7-Feb 7-Mar 7-Apr 7-May 7-Jun 7-Jul 7-Aug 7-Sep 7-Oct 7-Nov 7-Dec

mm

Julian date

7-day accumulated rainfall, 30-year average (moving sum)

1980-2009

2020-2049

Threshold

Dry spell (little rain during

July – Sept.)



Farmer – Dry season – irrigated system

Less risk – Slightly higher average annual total rainfall, which indicates

no change or slightly more water availability in wetland for dry season

rice farming

Low flow in stream / less water in

natural reservoir during dry season

(during Dec. – Apr.)

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Ap

r

May Jun

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Au

g

Sep

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No

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mm

Average annual accumulated rainfall

1980-2009

2020-2049



Farmer – Dry season – irrigated system

Higher risk – Warmer and longer hot period during March (day with max.

temp. is above 37ºC)

Heat stress in dry season crop

(especially in March)

28.0

33.0

38.0

43.0

Jan

Feb

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r

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g

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gree

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lsiu

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Average monthly extreme maximum temperature

1980-2009

2020-2049

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s

Degree Celsius

Daily maximum temperature distribution in March (days / month)

1980-2009 (>37°C = 21 days)

2020-2049 (>37°C = 26 days)



Using Future Climate Data to Support Development Planning



• Key sectors are under climate stress

• Future climate risk may not be the same as it has been due to climate change caused by global warming

• Development plan may not yield desirable outcome as planned

• How should development plan address this issue?

Climate change and challenges in developing country

Clear needs to extend vision of development planning into far future,

which requires different frame of thought

Source: Handoko Tjung, Indonesia



Vulnerability Adaptation Impact

Conventional approach

Future climate

projection

Future climate change impact

analysis - sector

Vulnerability analysis

Adaptation options aim at solving future problem – maintain

status quo

Climate change

Always create dilemma about certainty of future situation If we cannot be certain about future change, how can we plan for adaptation?

Or we may move to alternative approach – Climate wise development planning



Breaking dilemma: Climate wise development in light of climate change

• Scenario-based study and uncertainty >> shifting in policy planning paradigm

• Use scenarios of future as conditions to test resilience of community or robustness of policy and plan

• Adaptation in reality >> linking present situation and future change




Risk and resilience of

system/sector (now)

Change profile?

Socio-economic condition (past – present)

Climate (Past – present)

New ideas & innovation in risk

management Future climate

Risk (future)

Socio-economic condition (Future)

Sustainable / flexible Development

Global warming NOW FUTURE

Response to current situation

Still applicable

action?

Alternate development

pathway

Different way to drive development

strategy

Adaptation


Example 1: Alter livelihood strategy in light of climate change

• Case study of the upland farmer, Champone, Champasak, Lao PDR

• Changing government policy putting community exposed to greater climate risk and risk profile will also change under future climate change



Rice cultivation –

shifting cultivation

Loss in yield

Collect NTFP as addition

income

Fixed upland

rice farming

Soil degradation – soil erosion

Higher competition in NTFP collecting

Change from rice to perennial

plant

eco-tourism

Gov. policy – Conservation area –

no more shifting cultivation

Improved road network

Fluctuation in rainfall pattern

Higher rainfall intensity

NOW FUTURE

Adaptation strategy

ADB-EOC, 2012

Better access to market – Easier access by outsiders


Development

Climate & climate change SEA START RC copyright 2013

Example 2: Change option to mobilize development strategy Farmer community in northeast region, Thailand

Lao-oi district, Kalasin Province, Thailand



Farming community: wet-season rice / community is located along river

Vulnerability to climate threat: high exposure to flood with limited coping capacity

Community strategy: Won’t fight with flood – change to dry season rice – use water from main river through pumping station and underground pipe system

Development plan leads to dead end in light of climate change?

Example - Case study: Lao-oi District, Thailand

5



Climate change trend: higher rainfall in rainy season – longer and warmer summer


Source: IPCC AR4

Source: SEA START RC



To revise development plan Alternative in mobilizing strategy / alternate investment

New source of water for irrigation – harvest water during flood season for dry season agriculture

To be embedded in water resource development plan


Climate resilience now and sustained in light of climate change

7



Example 3: Alternate livelihood options

• Case study of Agriculture community in Krabi Province, Thailand



Rice farming under climate threat from strong wind and storm surge causing saltwater intrusion into rice paddy



Change in wind speed and increasing sea level



Improved dike system – increase investment

Change from rice to crab farming

Higher risk in the future from higher chance of saltwater intrusion



Rice farming under climate threat from strong wind and storm surge causing saltwater intrusion into rice paddy

Example 4: Town planning strategy in light of climate change

• Case study of the Town of Pun-pin, Suratthani Province, Thailand



Land-use zoning and town planning does not match with climate threat, thus put large number of population exposed to flood risk.

The new road which link new airport to the old town blocks natural flood way, causes flood risk to the Punpin Town.

More settlements along the new road has worsen the situation.


Change in 1/20 year heavy rain event & change in rainfall amount of 1/20 year heavy rain event:

Shorter return period and higher rainfall in heavy rain event (5 & 7 days accumulate rainfall)

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ฝนรวม 7 วัน

ฝนรวม 5 วัน

รอบปีเกิดซ ้ำ

การเปลี่ยนแปลงรอบปีการเกิดซ ้าของฝนที่มีโอกาสเกิดหนึ่งครั งในรอบ 20 ปีในปัจจุบัน

รอบปีเกิดซ ้ำในช่วง 1990-2009 รอบปีเกิดซ ้ำในช่วง 2030-2049

633

693 662

756

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1100

ฝนรวม 5 วัน ฝนรวม 7 วัน

มม.

การเปลี่ยนแปลงปริมาณฝนรวมที่มีโอกาสเกิดหนึ่งครั งในรอบ 20 ปีในอนาคต

รอบปีเกิดซ ้ำในช่วง 1990-2009 รอบปีเกิดซ ้ำในช่วง 2030-2049



Dual town centers – development strategy for Punpin Town

In order to cope with more serious flood in the future, dual town center concept and new land use plan are proposed for development plan.


Climate change is NOT environmental issue to be handled by environmental agencies

Broaden climate change adaptation context – development planning in light of climate change / different risk management in future

Planning in the unfamiliar timeframe

Scenario thinking – move away from “predict-then-act” approach

Different scale of adaptation – different context and approach

Sectoral assessment VS Area-based holistic development strategy VS community scale adaptation



THANK YOU


future climate projection and using future climate data to ... · as stress test to test robustness...

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