Iso-MATSIRO development & results

Iso-MATSIRO development & results

Kei YOSHIMURAIIS, Univ.of Tokyo

JAPAN HH

18O16OH

H

HD16O

Outlines

Descriptions of Iso-MATSIRO EQY1 results

Issues on “Plausibility” Suggestions of experiments at new sites

Yakutsk/Russia (Siberia) Tak/Thailand (Sub-tropics & Paddy field)

(GSWP-like) Global run Previous Studies

“Reanalyses-forced” Atmos. Isotope Circulation Model Colored Moisture Analysis (CMA)

MATSIRO (Takata et al., 2003, GPC)(Minimal Advanced Treatments of Surface Interaction and RunOff)

SiB-type LSM 5 soil layers (default):

Richards equation for vertical water movement C&H for hydraulic conductivity

TOP model for base flow Ground water table depth is considered

Snow cover and Glacier formation 12 soil types (Cosby et al., 1984) 13 veg. types No Mosaic (currently)

Iso-MATSIRO

Each of water-related variables has its isotopic concentration.

Water Mass and Isotopic Mass are always balanced.

Kinetic fractionations of Soil evap./subl. Intercepted water

evap./subl. Transpiration Snow sublimation

are taken into account. No soil diffusion

δEt

δR

δEb

δEc

δSs

Rs

Rb

IsoMAT Calculation Flow1. Albedo (Canopy / Snow / Ice )

Upward Radiations2. Turbulence Parameters

(Bulk coefficients for bare soil / Canopy / Stomata) Soil / Canopy / Stomatal resistance for with/without snow) Roughness

3. Sensible / Latent heat fluxes with/without snow4. Soil / Canopy / Stomatal Isotopic fluxes for with/without snow5. Canopy water balance6. Snow Area / Snow water balance (max. 3 layers)

Snow Albedo7. Runoff (Saturated / Infiltration excess / Overflow / Baseflow )8. Soil water (Ice formation/melting) (5 layers)9. Vegetation water (1 layer)

Kinetic Fractionation-Jouzel’s modification of C&G

Ro

Req, qeq

h=1

Rair, qair h=0~1

V

Equilibrium

Diffusion

h

hRR

C

C

E

ER aireq

E

isoEiso

1

_

Evaporation flux

Isotopic flux

Isotopic ratio of evaporation flux

Assume that C&G is applicable to any surface conditions (Canopy/Stomata/Soil, etc).

Dfor 0.88 O,for 1

)m/s(700082.0000285.01

)m/s(7006.01

18

_

kin

kinE

isoE

VV

V

C

C

)(

)(

___ isoairisoeqisoEiso

aireqE

qqVCE

qqVCE

EQY1 Simulations

Iterate 1 year until equilibrium. Manaus, Munich, & Tumbarumba Forcing: REMOiso, 15min. Parameter:

Soil type (given) Veg. type

Manaus: Broadleaf evergreen forest Munich: High latitude deciduous forest & Woodland Tumb: Broadleaf deciduous forest & Woodland

LAI (given)

Times for Equilibrium Compare 00:00, 1 Jan and 24:00, 30, Dec.

Water Threshold:10-5mm in all soil water

Isotopic Threshold: 10-5mm*SMOW in all soil water

Manaus 2y for H2O, 4y for H2

18O, 5y for HDO Munich

4y for H2O, 8y for H218O, 10y for HDO

Tumbarumba 3y for H2O, 3y for H2

18O, 5y for HDO

Some Results (pls see Matt’s HP)

Seasonal changes…18O in Canopy Evap at Munich

18O in Soil Evap. at Manaus

Plausible? –Vertical profile of Soil SWI

0

50

100

150

200

-12 -8 -4 0 4 8

Plausible? 2-Annual budget and seasonal variability

0

200

400

600

800

1000

1200

1400

1600

P R Rs Ri Ro Rb ET Eb Et Ei

δ18O

in w

ate

r flux (

‰)

Wate

r Fl

ux (

mm

/year)

-15

-10

-5

0

5P R Rs Ri Ro Rb ET Eb Et Ei

0

500

1000

1500

2000

2500

3000

3500


-15

-10

-5

0


δ18O

in w

ate

r flux (

‰)

Wate

r Fl

ux (

mm

/year) Manaus

Tumbarumba

Manaus

Tumbarumba

Plausible? 3-Diurnal Change of SWI in Veg.

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0:10 3:10 6:10 9:10 12:10 15:10 18:10 21:10

0

10

20

30

40

50

60

70

80

90

100

DJF_VegW18 JJA_VegW18DJF_T JJA_T

Tran

spiratio

n (W

/m2)

del

ta-1

8O (

‰)

Local Time

0

1

2

3

4

5

6

7

8

0:30 3:30 6:30 9:30 12:30 15:30 18:30 21:30

05101520253035404550


Tran

spiratio

n (W

/m2)

del

ta-1

8O (

‰)

Local Time

del

ta-1

8O (

‰)

Tran

spiratio

n (W

/m2)

Local Time0

1

2

3

4

5

6

0:30 3:30 6:30 9:30 12:30 15:30 18:30 21:30

0

50

100

150

200

250

300


Manaus Tumbarumba

Munich

Plausible? 4- Delta-Plot for Monthly Scale

-140

-90

-40

10

60

-20 -10 0 10

MWL RCANV18 QVEGT18QVEGE18 QSOIL18 Evap18CanopInt18 VegW18 H18SOI1H18SOI5

Delta-18O (‰)

Delta-D

(‰)

Tumbarumba

The Questions for each ILSS from Kendal Why the variation in amplitude of diurnal cycles in del

tas? Reservoirs: (if not reservoir size changes,) Seem t

o depend on degree of corresponded water fluxes. Fluxes: ?? What mechanisms are causing isotope variations? 1. Isotopic Forcings (of course) 2. Humidity variation (diurnal/seasonal) 3. Reservoirs sizes (soil/canopy/vegetation) 4. Latent heat partitioning (in case w/o tree?)

Suggestions for New Sites??

Sub-Tropics, Thailand Permafrost, Siberia

1. Tak, Thailand

Farm and grass landBare soilDeciduous ForestEarly deciduous forestWaterPaddy

N

10 km



NN

10 kmTak Tower

Made by Dr. Shin Miyazaki

P

ERdS RdL RdS T4

H

G

Q Ta

TG WG

U

30m

0m

An

AP

Instruments

Automatic monitoring from 2002

100m


View from tower (dry and rainy seasons)


MATSIRO Performance at tropical monsoon climate

in Tak, Thailand

By Shin Miyazaki (IIS, U-Tokyo), Wonsik Kim (NIAES),

and Kei Yoshimura (IIS, U-Tokyo)

0

20

40

60

80

100

120

101

116

131

215

302

317

401

416

501

516

531

615

630

715

730

814

829

913

92810

1310

2811

1211

2712

1212

27

Date

Pre

cipi

tati

on (

mm

/day

)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

Vol

umet

ric

soil

wat

er c

onte

nt

P

Wz_1_2_sim

Wz_1_2_obs

Soil moisture up-most (IGBP)

•Dry: Obs≒ sim, Rainy: Obs>>sim 　

Rainy season

Dry season-1

Dry season-2

Red： observation, black：simulation


0

20

40

60

80

100

120

140

160

180

200

101

116

131

215

302

317

401

416

501

516

531

615

630

715

730

814

829

913

928

1013

1028

1112

1127

1212

1227

Date

Lat

ent

heat

flu

x (W

/m^

2)

LE_sim

LE_obs

E_sim E_obsYear 741.7 783.6Dry 178.4 251.2Rainy 563.3 532.1Precipitation 873.8Runoff 155.7

Latent heat flux (IGBP)

•Dry: sim obs,≒ Rainy:sim obs ≒

Red： observation, black：simulation


Yakutsk

•Great forest with little precip.(=200mm/y)•Lena river basin•Permafrost

2. Yakutsk, RussiaSpasskaya Pad Experimental forest of IBPC: GAME/Siberia field observation site

Made by Dr. Atsuko Sugimoto

Precip 18O in Yakutsk

Summer

　 18O - high d value - low

Winter

18O - low d value - high

18O

(‰)

d ex

cess

(‰

)


JJA prec (mm)

46

177

81

1998

1999

2000

Different precip.amt.From year to year

DRY!!

WET!!


-25 -20 -15 -10

Aug 1

Aug 4

Aug 51998

1999 1997

plant water

summer rainfall

frozen

1999

H

Aug 3, 1998

1998 1997

0

50

100

150

200

Aug 22000

Soil water storage function for coming years

Dry Summer

Upward water flux Melted ice was used for

transpiration.

Wet Summer

Downward water flux Water remained after

transpiration

Pass winter as ice.

Stabilize transpiration

frozen

Soil water+Ice (g/cm3)

0.4 0.8

Soil water 18O

Ice lenz

Dry Wet


Soil water storage

JJA prec (mm)

46

177

81

0

100

200

300

400

5002001 at L site

Wa

ter

eq

uiv

ale

nt (

mm

)

20012000 fall

May

90-120cm

60cm

30cm

15cm

0cm

Jun Jul Aug Sep

2001

Wat

er e

quiv

alen

t (m

m)

(Sugimoto et al., 2003)

Large Inter-annual variation

1998

1999

2000

2001

P=E+R+Q

Innegligible!!!

1998

1999

2000


Outlines






ICM

Upper Meteor.Qu, Qv, W, P, E

Isotopically A-L Coupled Global Simulation (still offline)

Iso-MAT

Surface Meteor.U, V, q, T, p, P

Isotopes in vapor/precip.

Isotopes in Evap.

GAME-Rean.

ＮｏＦｒａｃｔｉｏｎａｔｉｏｎ

Ｐ，δ ｐ

Ｗ，δ ｗ

Ｅ，δ ｅ

Ｗ＊，δ ｗ＊Ｗ´，δ ｗ́

ＲａｙｌｅｉｇｈＥｑｕａｔｉｏｎ

Ｄｅｐｅｎｄｅｎｔｏｎｌａｎｄ／ｓｅａｔｙｐｅ

Ｒｅｐｅａｔ

Ｑλ

ＱΦ

▽ ・δ ｗＱ→


Ｐ，δ ｐ

Ｗ，δ ｗ

Ｅ，δ ｅ




Ｒｅｐｅａｔ

Ｑλ

ＱΦ

▽ ・δ ｗＱ→▽ ・δ ｗＱ→

Calculation flow for Each Time step

δ18O Distribution, Apr-Oct, 98

Surface Soil Water

Precipitation Total Evaporation

Total Runoff

-20

-15

-10

-5

0

5

98/4/1 98/5/1 98/6/1 98/7/1 98/8/1 98/9/1 98/10/1

Obs_P_iso

L-A Coupled

Simple L

Validation in Chiangmai, 99E:18N (Precip.δ18O)

Prc

p.

δ18

O (

‰)

Bias Cor. RMSE

-3.2‰ 0.74 4.2‰

Bias Cor. RMSE

0.3‰ 0.76 2.7‰

y = 0.8636x + 2.0454

R2 = 0.4767

y = 1.1305x - 0.2293

R2 = 0.4968

-30

-20

-10

0

-30 -20 -10 0

LxSxPx_125

LoSoPo_100

Global Validation (Prcp.δ18O)

GN

IP δ

18O

(‰)

Simulated δ18O (‰)

Bias Cor. RMSE

-3.4‰ 0.69 4.6‰

Bias Cor. RMSE

1.0‰ 0.70 3.1‰

Honestly, this is NOT evidence of land impact on atm is large. It tells reasonable range of vapor isotopes are supplied.

River discharge isotope estimates with iso-TRIP

Observations

SR δsr

v

δsr1 δsr2 δsr3

O1

O2

O3

O

Rδr

Original TRIP:Oki and Sud (1998)

Isotopic variation at the estuary of Chaophraya

Runoff from Iso-Bucket is always through soil buffer, whereas iso-MAT runoff is mainly precip.-direct. Too large fluctuation

-16

-12

-8

-4

0

98/4/1 98/5/1 98/6/1 98/7/1 98/8/1 98/9/1 98/10/1

iso-MAT

iso-BUK

δ18

O (

‰)

Obs. range

Outlines







Ｐ，δ ｐ

Ｗ，δ ｗ

Ｅ，δ ｅ




Ｒｅｐｅａｔ

Ｑλ

ＱΦ

▽ ・δ ｗＱ→


Ｐ，δ ｐ

Ｗ，δ ｗ

Ｅ，δ ｅ




Ｒｅｐｅａｔ

Ｑλ

ＱΦ

▽ ・δ ｗＱ→▽ ・δ ｗＱ→

“Reanalyses-forced” offline atmospheric model.

(Atmospheric) Isotope (18O) Circulation ModelYoshimura et al. 2003, 2004, JGR

Reproduced Daily δ18O Variations well

GAME＋

GPCP

Cor. RMSE

ChiSukBan

0.800.770.60

2.9 ‰2.8 ‰ 2.8 ‰

Cor. RMSE

ChiSukBan

0.760.740.56

4.2 ‰4.1 ‰ 3.5 ‰

GAMEonly

Yoshimura et al., 2003, JGR

Global Distribution of δ18O is reproduced,

too.

Yoshimura et al., 2004, JGR

Corr.coef. b/w monthly obs’d&est’d prcp iso. for 1979-93. (blue is good)

Int-ann. variations of prcp iso.

“Tag” spatial attribution onto evaporated water

Sea:60， Land:202D grid-plume model (vertical one layer)

Fully mix in a timestep (10 min.)Variables (Q, W, P, E) are

externally given.

EP

QUin QUout

QVout

QVin

W1.25˚x1.25˚

Colored Moisture Analysis

Indian Ocean

Pacific Ocean

IndochinaPen.

BengalGulf

Contents of water on todayare analyzed

How Indian Ocean water moves?

On a global scale

Continental cycling Ratio

Yoshimura et al.,2004, JMSJ

Chiangmai, Apr.-Oct. 1998

Contents of each origin in water vapor (precipitable water)

Bangkok, Apr.-Oct. 1998

Contents of each origin in water vapor (precipitable water)

Thanks for your attention! Yoshimura, K., T. Oki, and K. Ichiyanagi, Evaluation of two-dimension

al atmospheric water circulation fields in reanalyses by using precipitation isotopes databases, J. Geophys. Res., 109, doi:10.1029/2004JD004764, 2004.

Yoshimura, K., T. Oki, N. Ohte, and S. Kanae, Colored moisture analysis estimates of variations in 1998 Asian monsoon water sources, J. Meteor. Soc. Japan, 82, 1315-1329, 2004.

Yoshimura, K., T. Oki, N. Ohte, and S. Kanae, A quantitative analysis of short-term 18O variability with a Rayleigh-type isotope circulation model. J. Geophys. Res., 108(D20), 4647, doi:10.1029/2003JD003477, 2003.

E-mail: [email protected] Happy to have good cooperation with you

Sensitivity test - # of layers

58 layers2m4m depth

0

50

100

150

200

250

300

350

400

-15 -10 -5 0 50

50

100

150

200

-15 -10 -5 0 5δ18O in soil water (‰)

Dep

th (cm

)

Water/Isotopes Partitioningat 100E17N

0

500

1000

1500

2000

2500

3000


-20

-15

-10

-5


δ18O

in w

ate

r (‰

)m

m/y

ear

0

500

1000

1500

2000

2500

3000


-20

-15

-10

-5


However, Systematic underestimation. Possibly due to land originated water??

Land originated water becomes more

Line: Sim.Bar: Obs.

Underestimation becomes larger

CMA results

Yoshimura 2004, JMSJ

1998

Global d-excess (δD-8*δ18O) estimation

Comparison with GNIP Systematic bias

δ18O, δD, d-excess in Chiangmai

-18

-16

-14

-12

-10

-8

-6

-4

-2

0

2

4

98/5/1 98/6/1 98/7/1 98/8/1 98/9/1 98/10/1

obs_OpOp

-140

-120

-100

-80

-60

-40

-20

0

20

40

98/5/1 98/6/1 98/7/1 98/8/1 98/9/1 98/10/1

obs_DpDp

0

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10

15

20

25

98/5/1 98/6/1 98/7/1 98/8/1 98/9/1 98/10/1

0

2

4

6

8

10

12

14

obs_d-ex_pd-ex_p d-excess

δ18O

δD

Iso-MATSIRO development & results

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