climate and social changes in the anthropocenejspsusa.org/symposium/2013/dr.oki.pdf · climate and...

http://hydro.iis.u-tokyo.ac.jp/

Climate and Social Changes in the Anthropocene

Taikan Oki Institute of Industrial Science, The University of Tokyo

“Climate Change” Symposium Cosmos Club, Washington, DC, USA, February 22, 2013

2 Rojana Industrial Park, Thailand (11:47, Oct. 21, 2011, photo by JICA)

The impacts of climate change in many regions are predominantly linked to the water system, in particular through increased exposure to floods and droughts (SREX Ch8, Box8-4).

http://ipcc-wg2.gov/SREX/

IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance

Climate Change Adaptation (SREX)

3 Rojana Industrial Park, Thailand (9:27, Dec. 01, 2011)

In the Mekong region, dikes, dams, drains, and diversions established for flood protection have unexpected consequences for risk over the longer term, because they influence risk-taking behavior (SREX Ch8.2.4).

4 Rojana Industrial Park, Thailand (9:27, Dec. 01, 2011)

In considering adaptation to future flood risk in the Thames Estuary, the UK Environment Agency applied four scenarios over three time periods to flood management (SREX Ch8.6.1).

5 (Pathunthani, Thailand, 11:50, Nov. 21, 2011)

Attribution of single extreme events to anthropogenic climate change is challenging. (SREX, SPM)

NOT due to climate change. Changing hydrography, reservoir operation, and land conversion are more important in setting the scale of the disaster [Peterson, et al, BAMS, 2012]

in SPM… There have been statistically significant trends in the number of heavy precipitation events in some regions.

6

Why heavier rain?

http://hydro.iis.u-tokyo.ac.jp/ 8

0

10

20

30

40

50

60

70

80

-50 -40 -30 -20 -10 0 10 20 30 40温度(℃)

飽和

蒸気

圧(h

Pa)

水面氷面

0

2

4

6

8

10

12

-60 -40 -20 0 20 40 60 80 100 120

気温℃

気温

1度

上昇

に対

する

飽和

水蒸

気の

増加

率(%

)

Saturated water vapor pressure increases approximately 6% at 30℃

Higher Temperature, More Water Vapor

Air Temperature Satu

rate

d W

ater

Vap

or P

ress

ure

(hPa

)

Air Temperature (deg.C) Incr

ease

rat

e (%

) of w

ater

vap

or p

ress

ure

for i

ncre

ase

of a

ir te

mpe

ratu

re 1

deg

. C

Water Ice

9

EU

IC AU

JP NA

IN

deg.C

mm

/day

Top 1% rainfall v.s. Daily Temp.

(Utsumi et al., 2011, GRL)


(%/oC)

(b)

Slope of Ext. P v.s. Mean Temp. (daily)

Clausius-Clapeyron

(Utsumi et al., 2011, GRL )

in SPM… It is likely that the frequency of heavy precipitation or the proportion of total rainfall from heavy falls will increase in the 21st century over many areas of the globe.

11

(IPCC SREX SPM, 2011)

Projected return periods for a daily precipitation event that was exceeded in the late-20th-century on average once during a 20-year period (1981–2000). A decrease in return period implies more frequent extreme precipitation events (i.e., less time between events on average). The box plots show results for regionally averaged projections for two time horizons, 2046 to 2065 and 2081 to 2100, as compared to the late-20th-century, and for three different SRES emissions scenarios (B1, A1B, A2) (see legend). Results are based on 14 GCMs contributing to the CMIP3. The level of agreement among the models is indicated by the size of the colored boxes (in which 50% of the model projections are contained), and the length of the whiskers (indicating the maximum and minimum projections from all models). See legend for defined extent of regions. Values are computed for land points only. The “Globe” inset box displays the values computed using all land grid points.

(Decrease in return period implies more frequent extreme precipitation events)

13

X年確率降水量（年最大日降水量）

60.9

69.4

73.2

77.7

87.7

66.6

75.4

79.5

84.1

89.2

94.8

82.1

60

65

70

75

80

85

90

95

100

0 100 200 300 400 500 600

"XX年に1度の豪雨"

日降

水量

(mm

/day)

20C

21C

10% increase of rain intensity ≒3 times more frequent storms

in this case

(CCSR/NIES K-1 Simulation Grid point near Tokyo) Heavy Rainfall in X year return period

Dai

ly R

ainf

all (

mm

/day

) Expected Annual Maximum Daily Rainfall in X year return period


Impact Assessments with CC and SC

Probability of Non-Exceedance

Add

ition

al D

amag

e by

CC

More frequent with Climate

Change

Same magnitude of hazard will cause different

damage

Current relationship

How will it change with ΔT or GHG level?

(mitigation) How will it be

changed by investments in

adaptation?

rare & severe hazard


Future Flood Risk (daily P.–inundation) Future: 2080-2099

193 bil. JPY/y 1208 events/year

Present: 1979-1998 117 billion JPY/year 562 events/year

15

1171

Log10 (x108) JPY

Doubled

Damage depends on social vulnerability and the place where severe rainfall will occur

GCM20

27 times more severe rainfall

Log10 (x108) JPY

(Fukubayashi et al., submitted)


GCM20

MIROC5 RCP4.5

MIROC5 RCP8.5

Changes in extreme rainfall (GCM20, MIROC5 RCP4.5, RCP8.5)

Change in the ratio of the frequency of once in 100 year rainfall

Current:1979-1998 Future: 2080-2099



Future Flood Risk (Daily P.-inundation)

17

1171

138-679 billion JPY/y by MIROC5

562 events- 117 billion JPY/y

↓ 1208 events-

193 billion JPY/y by GCM20

Number of ensemble members is critical.


Ann

ual I

nund

atio

n R

isk

(0

.1 b

illio

n JP

Y/y

ear)

How about drought?

http://hydro.iis.u-tokyo.ac.jp/ Impacts of possible future changes

Impacts of population and water withdrawal changes are larger than that of river discharge.

0

500

1000

1500

2000

2500

0 1 1.5 2 2.5 3

GLobal

ly in

cre

ased H

WSP

(m

illio

ins)

dT (oC)

Q_fixed

0

500

1000

1500

2000

2500

0 1 1.5 2 2.5 3

Glo

bal

ly in

cre

ased H

WSP

(m

illio

ns)

dT (oC)

wu_fixed

0

500

1000

1500

2000

2500

0 1 1.5 2 2.5 3

Glo

bally

incr

ease

d H

WS

P (m

illion

s)

dT (oC)

Pop is constant W is constant

Q is constant A1B

Temperature Increase

Q’s contribution

Pop’s contribution

W’s contribution

Q: discharge, Pop: population, W: water withdrawal

(Kiguchi et al., submitted) ensemble of 6 GCMs

Q, Pop, & W changes

Hig

hly

Wat

er S

tres

sed

Popu

latio

n


Land Surface Models (LSMs) are designed to be coupled with GCMs No Human Impacts (HI) representation

Numerous Global Hydrological Models (GHMs) with HI representation exist, but Mostly designed for offline simulations Simple ET parameterizations (energy balance not considered) Vegetation dynamics/Carbon cycles are not accounted.

MATSIRO & H08

H08: Hanasaki et al. (2008a, 2008b)

Land surface hydrology scheme is a simple Bucket Model

Vegetation : accounted implicitly Further, new irrigation scheme for MATSIRO LSM is developed Water table dynamics and a newly developed pumping scheme

MATSIRO: Takata et al. (2003)

Water table dynamics (Yeh and Eltahir, 2005)

Pumping scheme Koirala et al.

(Pokhrel, et al., J. Hydrometeor., 2012) 20

Impact of Climate Change on Low Flow

Drought days will be alleviated by reservoirs and ground water depletion

Climate Change (natural) With Anthropogenic Activities

Large Scale Reservoirs

Decrease

Changes in the Future (RCP8.5) Days below Q90 in 20th Century

Increase

Middle Scale Reservoirs

21

(Sato, et al., in preparation)


Unsustainable Water Use (NNBW) Major hotspots of unsustainable water use: NW India, Pakistan,

Western US, Spain ….

Global total of ~450km3/year compares fairly well with the documented records

(Pokhrel, et al., Nature Geoscience, 2012)


Sea Level Change: Anthropogenic TWS Contributions

TWSC

Capacity - Storage



Contributions to Sea-level change in previous estimates

Wad

a et

al.,

201

0 K

onik

ow, 2

011

Gor

nitz

et a

l., 1

997

Cha

o et

al.,

200

8 Le

ttenm

aier

and

Mill

y,, 2

009

Ngo

-Duc

et a

l., 2

009

Wad

a et

al.,

201

2



Web of Impacts Direct Impacts of Climate Change Temp., CO2, & sea level rises, hydrological changes Sea water intrusion, P, ET, GW recharge, floods &

droughts, snow & ice, … human health, eco-system, energy production (hydropower & cooling), water quality, soil erosion, turbidity and pathogens, CSO, navigation, …

Impacts of mitigation and adaptation Bioenergy crops, CCS, afforestation, agriculture

(practice and irrigation), LULCC quantity and quality of surface and ground water GHGs

Hydropower and/or reservoir ecosystems, cost new operation/management rules and/or infrastructure

Hydrological Change quantity, quality, timing,

frequency of extreme events, ground water recharge, available

water resources, …

Non-structural measures

early warning system,

Infrastructure dykes, dams and

reservoirs, …

Water Management

Water Demand Change

due to demand changes in food,

energy, …

Land Use Land Cover

Change Settlement, forest, …

Changes in pollutant load

Non-climatic Drivers

Impacts and Risks for humans and ecosystems

Socio-Economic Changes GDP, population, urbanization, …

Climate Change Precip, Temp, SLC, …

Changes in Hazard flood, drought, quality…

Changes in exposure and vulnerability

GHG Aerosol

concentration

Mitigation

Adaptation

Version 0.6 26


Remarks Social changes would have comparable impacts

on the changes in future water related risks. Imagine more globalized world for impacts. CC is one of multiple stressors demanding

changes for future water resources management. Damage function translates CC impacts to area of

protection (e.g., $/¥, human health, bio diversity, …) Number of ensembles is crucial for proper future

projections considering vulnerability and exposure. Proper bias correction is critical for quantitative assessment.

(Watanabe, et al., JGR, 2012)

Policy design through prediction improvement

Operational use for fishery, sea route, weather forecast, and

climate monitoring

Understanding of the climate system and the global

warming

3°C

Air temperature prediction

Prediction results GCOM observation

• Improvement of parameterization about radiation budget and carbon cycle, etc. in climate prediction model.

• Verification and improvement of prediction of the earth environment change including the water cycle by comparison with the satellite observation.

Radiation budget • Surface albedo • Snow ice • Cloud/ aerosol • SST/ LST

Carbon cycle • Vegetation cover • Primary production • Coastal environment

• Surface temperature • Sea level • Snow and sea ice area • Environmental change • Rain/drought distribution

• Extreme weather frequency

• Land cover

Climate system model

Comparison

Input

Model prediction

Improve accuracy

Future prediction

Cooperation with the climate model research institutions

Water cycle • Water vapor, cloud,

precipitation • Soil moisture • Sea ice, snow • SST, wind

Data application Knowledge

GCOM-C GCOM-W

Satellite/sensor and algorithm development

GCOM observation

Frequent and long-term (>10yer) global observation system required for earth environment change monitoring and prediction

Products or radiance with radiative transfer

• Monitor “Global Change” by continuous (>10yr) and consistent observations. • Estimate model parameters with satellite observations and products.

2

ICE

Land Sea

Atmos.

(Oki and Kanae, Science, 2006)

3

Sea Surface Temp.

Cloud Liquid Water

Sea Ice Concent.

Sea Surf. Wind

GCOM W1 GPM

Land Cover

GCOM C1

Radiation Budget

Global Water Cycles and Earth Obs.

29

September average in 1980s September 16, 2012 by AMSR2

The most smallest sea ice extent on satellite record !

GCOM-W1

GCOM-W1 is now on the A-Train

Thank You!

climate and social changes in the anthropocenejspsusa.org/symposium/2013/dr.oki.pdf · climate and...

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