12000-02-14

Chinese Cryosphere

Information System

Li XinLi Xin

Cold and Arid Regions Environment and Cold and Arid Regions Environment and Engineering Research Institute, CASEngineering Research Institute, CAS

22000-02-14

1. Introduction: Cryosphere and Climate Change 1. Introduction: Cryosphere and Climate Change

32000-02-14

2. Structure of CCIS

data classification andgeo-coding system

system architectureand composition

software and hardwareenvironment

system standard

map projection andscale

data model

databaseimplementation

database

spatial analysis

spatial simulation

application models

application

data exchangeinterface

user interface

systemdemostration

system interface

Ch inese Cryosph eric In fo rm ation System

2000-02-14 4

Hardware and Software Environment in CCIS

ARC/INFO

UNIX Workstation NT Workstation

ArcView

Applications in different environment

PC

52000-02-14

3. Main Case Study Areas of CCIS

Qinghai-Tibet Plateau

Qinghai-Tibet Highway

Urumqi River Basin, Tienshan Mountains

62000-02-14

3.1 CCIS:3.1 CCIS: Qinghai-Tibet PlateauQinghai-Tibet Plateau

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DEMDEM

82000-02-14Map of Frozen GroundMap of Frozen Ground

92000-02-14

Vegetation Map of the QTPVegetation Map of the QTP

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3.2 CCIS:3.2 CCIS: Regions alongRegions along the the Qinghai-Tibet highwayQinghai-Tibet highway

112000-02-14

Database of frozen Soil Engineering Properties along the Qinghai-Tibet Highway

122000-02-14

3.3 CCIS:3.3 CCIS: Urumqi River Urumqi River Basin in the Tienshan Basin in the Tienshan

MountainsMountains

132000-02-14

DEMs of Glacier

2000-02-14 14

4. Spatial Interpolation of Climatic Variables

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ÆøΠ£¨Kriging£©-18­-­-17.6-17.6­-­-16-16­-­-14.5-14.5­-­-12.9-12.9­-­-11.4-11.4­-­-9.8-9.8­-­-8.3-8.3­-­-6.7-6.7­-­-5.2-5.2­-­-3.6-3.6­-­-2.1-2.1­-­-0.5-0.5­-­11­-­2.62.6­-­4.14.1­-­5.75.7­-­7.27.2­-­8

ÆøÏó Õ¾1ÔÂƽ¾ùÆøÎÂ# -18­-­-15# -15­-­-11.9# -11.9­-­-8.9# -8.9­-­-5.8# -5.8­-­-2.8# -2.8­-­0.3# 0.3­-­3.4# 3.4­-­6.4

# 6.4­-­9.5

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250 0 250 500 750 1000 1250 1500 1750 2000 2250 2500 K ilometersN

Çà²Ø¸ßÔ­30Ä꣨1961- 1990£©1ÔÂƽ¾ùÆøΠ·Ö²¼£¨Kr i gi ngÄڲ壩

Missing data estimation

Data gridding

2000-02-14 15

Classification and Procedure of Spatial Interpolation

Geometric method Statistical method Geostatistical method Functional method Stochastic simulation Physical model

simulation Combined method

Data

Model Specification

Estimation of surface mean

Estimation of second order (covariance, variogram)

properties of surface

Model evaluation

Interpolation

162000-02-14

Meteorological Stations in the Qinghai-Tibet Plateau

2000-02-14 17

Inverse Distance Weighting

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air temperature (IDW )-17.6 - -16-16 - -14.5-14.5 - -12.9-12.9 - -11.4-11.4 - -9.8-9.8 - -8.3-8.3 - -6.7-6.7 - -5.2-5.2 - -3.6-3.6 - -2.1-2.1 - -0.5-0.5 - 11 - 2.62.6 - 4.14.1 - 5.75.7 - 7.2

air temperature at meteorological stations

# -18 - -15# -15 - -11.9# -11.9 - -8.9# -8.9 - -5.8# -5.8 - -2.8

# -2.8 - 0.3

# 0.3 - 3.4

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# 6.4 - 9.5

# 9.5 - 12.5

Interpolation results of inverse distance square

2000-02-14 19

Trend Surface

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202000-02-14

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Pishanair temperature (trend surface)

-18 - -17.6-17.6 - -16-16 - -14.5-14.5 - -12.9-12.9 - -11.4-11.4 - -9.8-9.8 - -8.3-8.3 - -6.7-6.7 - -5.2-5.2 - -3.6-3.6 - -2.1-2.1 - -0.5-0.5 - 11 - 2.62.6 - 4.14.1 - 5.75.7 - 7.27.2 - 8

air temperature at meteorological stations

# -18 - -15# -15 - -11.9# -11.9 - -8.9# -8.9 - -5.8# -5.8 - -2.8

# -2.8 - 0.3

# 0.3 - 3.4

# 3.4 - 6.4

# 6.4 - 9.5

# 9.5 - 12.5

Interpolation results of trend surface

2000-02-14 21

Kriging methodKriging method

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2000-02-14 22

Exploratory Spatial Data AnalysisExploratory Spatial Data Analysis The mathematical expectation of the difference

between two points separated by distance h is zero:

0)]()([( hxZxZE The variance of the difference between two points

separated by distance h is minimized as:

Hence, the semi-variance can be calculated from data samples by the following equation:

)(2]})()({[)]()([ 2'' hxxEhxZxZVar

2

1

])()([2

1)(

n

iii hxzxz

nh

2000-02-14 23

Basic variogram models

0 h

(h)

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Nugget model Spherical model Exponential model

Gaussian model Holesin model Linear model

2000-02-14 24

Cokriging methodCokriging method

cokriging introduces a new hypothesis, the variance of the

difference between two variables is minimized

The equation of cross-variogram is as follows:

)(2)]()([ hxZxZVar kk

)]()(][)()([2

1)(

1

hxzxzhxzxzn

h ik

ik

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k

252000-02-14

Fit of simple and cross-variogram

262000-02-14

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air temperature (cokriging)-18 - -17.6-17.6 - -16-16 - -14.5-14.5 - -12.9-12.9 - -11.4-11.4 - -9.8-9.8 - -8.3-8.3 - -6.7-6.7 - -5.2-5.2 - -3.6-3.6 - -2.1-2.1 - -0.5-0.5 - 11 - 2.62.6 - 4.14.1 - 5.75.7 - 7.27.2 - 8

air temperature at meteorological stations

# -18 - -15# -15 - -11.9# -11.9 - -8.9# -8.9 - -5.8# -5.8 - -2.8

# -2.8 - 0.3

# 0.3 - 3.4

# 3.4 - 6.4

# 6.4 - 9.5

# 9.5 - 12.5

Interpolation results of cokriging

2000-02-14 27

Combined methodCombined method Assuming that spatial variable consists of three

components: one structural component, one

stochastic and spatial correlated component, and

one stochastic noise or residual. Let x denotes a

two-dimensional or three-dimensional vector,

spatial variable Z(x) can be expressed as:

'')(')()( xxmxZ

282000-02-14

Lapse rates of different latitudinal and Lapse rates of different latitudinal and altitudinal zones in the altitudinal zones in the

Qinghai-Tibet Plateau (Qinghai-Tibet Plateau (C/100m)C/100m)

表 4-1 青藏高原气温垂直梯度（℃/100米）

海拔（米） 北 纬

1500-2000 2000-2500 2500-3000 3000-3500 3500-4000 4000-4500 4500-5000 平 均

28° 0. 52 0. 52 0. 52 0. 52 0. 54 0. 52 0. 52 0. 52

30° 0. 48 0. 50 0. 48 0. 50 0. 48 0. 50 0. 50 0. 49

32° 0. 54 0. 52 0. 54 0. 54 0. 54 0. 54 0. 54 0. 54

34° 0. 46 0. 44 0. 46 0. 46 0. 46 0. 46 0. 46 0. 46

36° 0. 48 0. 46 0. 48 0. 46 0. 48 0. 48 0. 46 0. 47

平­ ­均 0. 50 0. 49 0. 50 0. 50 0. 50 0. 50 0. 50 0. 50

292000-02-14

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ÆøΠ£¨3000Ã×£©-17.6­-­-16-16­-­-14.5-14.5­-­-12.9-12.9­-­-11.4-11.4­-­-9.8-9.8­-­-8.3-8.3­-­-6.7-6.7­-­-5.2-5.2­-­-3.6-3.6­-­-2.1-2.1­-­-0.5-0.5­-­1

ÆøÏó Õ¾1ÔÂƽ¾ùÆøÎÂ# -18­-­-15# -15­-­-11.9# -11.9­-­-8.9# -8.9­-­-5.8# -5.8­-­-2.8# -2.8­-­0.3# 0.3­-­3.4# 3.4­-­6.4

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250 0 250 500 750 1000 1250 1500 1750 2000 2250 2500 K ilometersN

Çà²Ø¸ßÔ­30Ä꣨1961- 1990£©1ÔÂƽ¾ùÆøΠ·Ö²¼£¨3000Ã×̧߶ȣ©

302000-02-14

a sum of nugget, linear and Gaussian variogram models

312000-02-14

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ÆøΠ£¨×ÛºÏ £©-25.4­-­-22.5-22.5­-­-20-20­-­-17.6-17.6­-­-16-16­-­-14.5-14.5­-­-12.9-12.9­-­-11.4-11.4­-­-9.8-9.8­-­-8.3-8.3­-­-6.7-6.7­-­-5.2-5.2­-­-3.6-3.6­-­-2.1-2.1­-­-0.5-0.5­-­11­-­2.62.6­-­4.14.1­-­5.75.7­-­7.27.2­-­8

ÆøÏó Õ¾1ÔÂƽ¾ùÆøÎÂ# -18­-­-15# -15­-­-11.9# -11.9­-­-8.9# -8.9­-­-5.8# -5.8­-­-2.8# -2.8­-­0.3

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·½²î0. 22­ - ­ 1. 941. 94­ - ­ 3. 663. 66­ - ­ 5. 385. 38­ - ­ 7. 17. 1­ - ­ 8. 828. 82­ - ­ 10. 5410. 54­ - ­ 12. 2612. 26­ - ­ 13. 9813. 98­ - ­ 15. 71

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2000-02-14 33

ConclusionConclusion Spatial interpolation is a very important spatial analysis tool

in GIS. As for the cryospheric regions with sparsely and irrationally distributed meteorological stations, spatial interpolation is a basic method for the study of spatial distribution of climatic variables and also a prerequisite for the establishment of cryospheric models based on GIS.

There is no absolutely optimal spatial interpolation method; there is only relatively optimal interpolation method in special situation. Hence, the best spatial interpolation method should be selected in accordance with the qualitative analysis of the data, exploratory spatial data analysis and repeated experiments.

342000-02-14

5. Response of Permafrost to Global 5. Response of Permafrost to Global

Change on the Qinghai-Tibet Plateau Change on the Qinghai-Tibet Plateau

- A GIS Aided Model- A GIS Aided Model

2000-02-14

Permafrost Response to Climate Change

Permafrost Forecast

Physical ModelFrost Number Model

Altitude Model

Permafrost Map

GCM Model

Climate Change Scenarios

Geocode l ongi tude Lati tude Ai r­ Temperatureof ­Warmest­Month

Ai r­ Temperatureof ­ Col dest­Month

180 100. 65 35. 27 11. 65 -13. 22181 101. 98 35. 90 19. 21 -6. 22182 101. 47 35. 03 8. 71 -14. 63183 102. 45 35. 82 19. 86 -5. 34184 102. 08 35. 50 16. 03 -7. 96185 104. 08 35. 85 18. 93 -7. 95186 103. 18 35. 58 17. 96 -6. 92187 103. 87 35. 37 18. 47 -7. 36188 105. 15 35. 63 18. 14 -6. 95189 104. 60 35. 50 18. 28 -7. 77190 105. 00 35. 38 14. 70 -8. 80191 80. 08 32. 50 13. 51 -12. 29192 84. 42 32. 15 11. 52 -13. 23193 90. 02 31. 37 8. 52 -11. 03194 91. 10 32. 35 7. 66 -14. 73

GIS

2000-02-14

H 3650 0 003 2537 14282exp[ . ( . ) ]

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Altitude Altitude ModelModel

2000-02-14

Geo thermal Regime

GCM Scenarios

Data Flow in the Altitude Model

2000-02-14

DEM of Qinghai-Tibet PlateauDEM of Qinghai-Tibet Plateau

392000-02-14

Diagram of HADCM2Diagram of HADCM2

402000-02-14

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N

2049ÄêÇà²Ø¸ßÔ­ÆøΠÉý¸ß·ù ¶È

The Air Temperature Rise on the The Air Temperature Rise on the Qinghai-Tibet Plateau in 2049Qinghai-Tibet Plateau in 2049

412000-02-14

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Qinghai Lake

legendPermafrostSeasonal­­Frozen­GroundGlacierDesertLake

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Simulation­Result­of­the­Altitue­Model

2000-02-14

FDDF

DDF DDT

Nelson Frost Number ModelNelson Frost Number Model

432000-02-14

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Namuchu Lake

Qinghai Lake

Legendcontinous­permafrostdiscontinous­permafrostseasonal­frozen­groundglacierdesertlake

500 0 500 1000 1500 2000 2500 Kilometers

N

EW

S

Permafrost Distribution on the Qinghai-Xizang PLateau(Using the Frost Number Model)

2000-02-14 44

Assumptions:Assumptions: The Gaussian function that describes high altitude

permafrost distribution will not change according to the climate warming.

If air temperature increases 1C, the vertical zonation will rise a certain height agreeing on the lapse rate, the lower limit of the high-altitude permafrost will rise the same height. Therefore, a relation can be established between the air temperature rise (ΔT) and the increased height of permafrost lower limit (ΔH). The relation is:

T

H

Lakes, glaciers, deserts will not change

452000-02-14

40¡ã

35¡ã

30¡ã

25¡ã

80¡ã75¡ã 85¡ã 90¡ã 95¡ã 100¡ã 105¡ã

# #

#

#

#

#

#

Golmu

Shiquanhe

Lasa

Cuona

Yushu

Changdu

Xining

Se lingc uo LakeNamucuo Lake

Qinghai Lake

40¡ã

35¡ã

30¡ã

25¡ã

80¡ã75¡ã 85¡ã 90¡ã 95¡ã 100¡ã 105¡ã

500 0 500 1000 1500 2000 Kilometers

LegendPermafrostSeasonal­Frozen­GroundGlacierDesertLake

N

40¡ã

35¡ã

30¡ã

25¡ã

80¡ã75¡ã 85¡ã 90¡ã 95¡ã 100¡ã 105¡ã

Present Permafrost Distribution

40¡ã

35¡ã

30¡ã

25¡ã

80¡ã75¡ã 85¡ã 90¡ã 95¡ã 100¡ã 105¡ã40¡ã

35¡ã

30¡ã

25¡ã

80¡ã75¡ã 85¡ã 90¡ã 95¡ã 100¡ã 105¡ã

40¡ã

35¡ã

30¡ã

25¡ã

80¡ã75¡ã 85¡ã 90¡ã 95¡ã 100¡ã 105¡ã

Permafrost Change when Air Temperature Rise 0.51°C

Permafrost Change when Air Temperature Rise 1.10°C

Permafrost Change when Air Temperature Rise 2.91°C

462000-02-14

1190

1056

541

1294

0.00

0.51

1.10

2.91

0

200

400

600

800

1000

1200

1400

1990 2009 2049 2099

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50Permafrost Area

Air Temperature Rise

Permafrost Change on the Qinghai-Tibet Permafrost Change on the Qinghai-Tibet PlateauPlateau

8.03

18.45

58.18

4799-11-20

6. Other Models6. Other Models

482000-02-14

6.1 6.1 Solar Radiation Model over Rugged TerrainSolar Radiation Model over Rugged Terrain

Duration of possible sunshine Ω： defined as the set of duration when the sloping grid can receive direct solar radiation during the entire day.

Isotropic view factor Viso： defined as the ratio of the area of the visi

ble part to the area of semi-sphere on a sloping grid. It stands for the influence of the surrounding terrain to the isotopic diffuse radiation.

Circum-solar view factor V1： defined as the ratio of the exoatmosph

eric radiance obstructed by surrounding and self-shadowing to the exoatmospheric radiance obstructed only by self-shadowing. It stands for the influence of the surrounding terrain to the circum-solar diffuse radiation.

Shape factor Fij： defined as the ratio of the energy reached another sloping

grid to the energy emitted from the source sloping grid.

492000-02-14

Duration of Possible SunshineDuration of Possible Sunshine1 ) T h e c r i t e r i a f o r t h e e x i s t e n c e ( h a s r e a l r o o t s ) o f c r i t i c a l - t i m e ω h 1 a n d ω h 2 o n a

s lo p i n g g r id1 . 1 I f f o r a n y [ , ]h h1 2 ， t h e r e i s c o r r e s p o n d in g s o la r r a d ia t io n e n e r g y S 0 > = 0，

t h e n

[ , ] [ , ]r s h h 1 2 ( 1 )

1 . 2 I f f o r a n y [ , ]h 1 , a n d [ , ]h 2 ， t h e r e i s c o r r e s p o n d in g s o la r r a d ia t io ne n e r g y S 0 > = 0， t h e n

[ , ] [ , ] [ , ]h r s h1 2 ( 2 )

1 . 3 I f f o r a n y [ , ] ， t h e r e i s c o r r e s p o n d in g s o la r r a d i a t io n e n e r g y S 0 < 0， t h e n

( 3 )2） T h e c r i t e r i a f o r t h e n o n - e x i s t e n c e ( h a s i m a g i n a r y r o o t s ) o f c r i t i c a l - t i m e ω h 1 a n d ω

h 2 o n a s lo p i n g g r id2 . 1 I f f o r a n y [ , ] ， t h e r e i s c o r r e s p o n d in g s o la r r a d i a t io n e n e r g y S 0 > = 0， t h e n

[ , ]r s （ 4）2 . 2 I f f o r a n y [ , ] ， t h e r e i s c o r r e s p o n d in g s o la r r a d i a t io n e n e r g y S 0 < 0， t h e n

（ 5）

2000-02-14 50

Obstruction of solar radiation by the Obstruction of solar radiation by the surrounding terrainsurrounding terrain

x

y

z

被地形遮蔽的光线

未被地形遮蔽的光线

12

34

2000-02-14 51

开始

设置追踪深度

追踪数 =0；遮蔽 =假

是否与多边形相交

求交点

追踪单元小于追踪深度

交点是否在多边形内

结束

否

是

是

遮蔽 =真

是

否

否

Ray trace Ray trace algorithmalgorithm

2000-02-14 52

x

y

z

h

Isotropic View FactorIsotropic View Factor

n

iiiso h

nV

1

)sin1(1

ihk sin1

2000-02-14 53

Shape FactorShape Factor

ji

A A

ji

iij dAHIDdA

rAF

i j

2

coscos1

i jA A

jijjjii

ij dzdzrdydyrdxdxrA

F ))ln()ln()(ln(ln(2

1

HIDd

F jiij 2

coscos

ri

j

A i

dA i

A jdAj

2000-02-14 54

太阳辐射分量计算

n

i

t dSE

Qis

ir1

00

,

,

cos2

)]1)(cos1(2

1

cos

cos[

001 h

hdir

isoZ

h

hdirh

diftdif Q

QV

Q

QVQQ

)}1)](1([8.0)1(5.0{330 awroro

hhdif QQ

ttdir QQ 0

n

iij

tidif

tidir

ti

tjref FQQAQ

1,,, )(

tref

tdif

tdir

t QQQQ

552000-02-14

--with a Windows 95 Style User Interface--with a Windows 95 Style User InterfaceSpectral reflectance Inverse Spectral reflectance Inverse

562000-02-14

Obstruct in winterObstruct in winter

Obstruct in summerObstruct in summer

2000-02-14 57

Result - Net Solar Radiation

582000-02-14

R2=0. 6886-1. 5

-1. 0

-0. 5

0. 0

0. 5

1. 0

-300 -200 -100 0 100

测点平均物质平衡(mm)

5-9月平均气温(0C) 1号冰川

R2=0. 619124

25

26

27

28

-300 -200 -100 0 100测点平均物质平衡(mm)

最大可能辐射

(MJ/cm2.d)

1号冰川

R2=0. 9886-0. 5

0. 5

1. 5

2. 5

3. 5

4. 5

-300. 0 -200. 0 -100. 0 0. 0 100. 0测点平均物质平衡(mm)

5-9月平均气温(0C)

Gries冰川

R2=0. 1407

15

17

19

21

23

25

-300. 0 -200. 0 -100. 0 0. 0 100. 0

测点平均物质平衡(mm)

最大可能辐射

(MJ/cm2.d)

Gri es冰川

6.2 Relationship between mass balance, solar radiation and air temperature

592000-02-14

Relationship between mass balance, solar Relationship between mass balance, solar radiation and air temperature of Glacier No. 1radiation and air temperature of Glacier No. 1

Bj=844—71.3T —37.3Ip

correlation coefficient (R)=0.9121; R2=0.8320

602000-02-14

- 300- 250- 200- 150- 100- 50

050

3768. 4 3843. 7 3933. 7 4006. 2 4077. 4

(m)高度

(mm)

平均物质平衡

计算值

实测值

612000-02-14

Present

2009

2049

2099

6.3 Change of Permafrost-Engineering 6.3 Change of Permafrost-Engineering Properties along the Qinghai-Tibet Properties along the Qinghai-Tibet

Highway (Tutuhe )Highway (Tutuhe )

<-5C: Extreme Stable type-5C to -3C: Stable type-3C to -1.5C: Sub-stable type-1.5C to -0.5C: Transit type-0.5C to 0.5C: Unstable type>0.5C: Extreme unstable type

622000-02-14

The change of permafrost stability alongThe change of permafrost stability alongthe Qinghai-Tibet Highwaythe Qinghai-Tibet Highway

%青藏公路沿线地温带各年代的面积变化（

）

0

5

10

15

20

25

30

35

40

<-5.0 0C -5.0 to -3.0 0C -3.0 to -1.5 0C -1.5 to -0.5 0C -0.5 to +0.5 0C >+0.5 0C

ÏÖÔÚ

2009Äê

2049Äê

2099Äê

Present200920492099

Extreme stable type Stable type Sub-stable type Transit type unstable type Extreme unstable type

%

632000-02-14

6.4 A Distributed Calculation Method 6.4 A Distributed Calculation Method for Glacier Volume Changefor Glacier Volume Change

1964

642000-02-14

Calculation of glacier mass Calculation of glacier mass balance using GISbalance using GIS

S

x iy i

)( )(1k

ji

n

kjkiji SSSHHSVVV

652000-02-14

Thanks