Chinese Cryosphere Information System Li Xin Cold and Arid Regions Environment and Engineering Research Institute, CAS

Introduction: Cryosphere and Climate Change

Structure of CCIS

Hardware and Software Environment in CCIS ARC/INFO UNIX WorkstationNT Workstation ArcView Applications in different environment PC

Main Case Study Areas of CCIS Qinghai-Tibet Plateau Qinghai-Tibet Highway Urumqi River Basin, Tienshan Mountains

CCIS: Qinghai-Tibet Plateau

DEM

8 Map of Frozen Ground

Vegetation Map of the QTP

CCIS: Regions along the Qinghai-Tibet highway

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

CCIS: Urumqi River Basin in the Tienshan Mountains

DEMs of Glacier

Spatial Interpolation of Climatic Variables l Missing data estimation l Data gridding

Classification and Procedure of Spatial Interpolation Geometric method Statistical method Geostatistical method Functional method Stochastic simulation Physical model simulation l Combined method Data Model Specification Estimation of surface mean Estimation of second order (covariance, variogram) properties of surface Model evaluation Interpolation

Meteorological Stations in the Qinghai-Tibet Plateau

Inverse Distance Weighting

Interpolation results of inverse distance square

Trend Surface

Interpolation results of trend surface

Kriging method

Exploratory Spatial Data Analysis l The mathematical expectation of the difference between two points separated by distance h is zero: l The variance of the difference between two points separated by distance h is minimized as: l Hence, the semi-variance can be calculated from data samples by the following equation:

Basic variogram models

Cokriging method l cokriging introduces a new hypothesis, the variance of the difference between two variables is minimized l The equation of cross-variogram is as follows:

Fit of simple and cross-variogram

Interpolation results of cokriging

Combined method l 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:

Lapse rates of different latitudinal and altitudinal zones in the Qinghai-Tibet Plateau (  C/100m)

a sum of nugget, linear and Gaussian variogram models

Conclusion l 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. l 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.

Response of Permafrost to Global Change on the Qinghai-Tibet Plateau - A GIS Aided Model

Permafrost Response to Climate Change Permafrost Forecast Physical Model Frost Number Model Altitude Model Permafrost Map GCM Model Climate Change Scenarios GIS

Altitude Model

Geo thermal Regime GCM Scenarios Data Flow in the Altitude Model

DEM of Qinghai-Tibet Plateau

Diagram of HADCM2

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

Nelson Frost Number Model

Assumptions: l The Gaussian function that describes high altitude permafrost distribution will not change according to the climate warming. l If air temperature increases 1  C, 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: l Lakes, glaciers, deserts will not change

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

Permafrost Change on the Qinghai-Tibet Plateau

Other Models

Solar Radiation Model over Rugged Terrain l Duration of possible sunshine Ω ： defined as the set of duration when the sloping grid can receive direct solar radiation during the entire day. l Isotropic view factor V iso ： defined as the ratio of the area of the visible 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. l Circum-solar view factor V 1 ： defined as the ratio of the exoatmospheric 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. l Shape factor F ij ： defined as the ratio of the energy reached another sloping grid to the energy emitted from the source sloping grid.

Duration of Possible Sunshine

Obstruction of solar radiation by the surrounding terrain x y z 被地形遮蔽的光线 未被地形遮蔽的光线

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 algorithm

x y z h Isotropic View Factor

Shape Factor r ii jj A i dA i A j dA j

太阳辐射分量计算

with a Windows 95 Style User Interface Spectral reflectance Inverse

Obstruct in winter Obstruct in summer

Result - Net Solar Radiation

Relationship between mass balance, solar radiation and air temperature

Relationship between mass balance, solar radiation and air temperature of Glacier No. 1 B j =844—71.3T —37.3Ip correlation coefficient (R)=0.9121; R 2 =0.8320

Present Change of Permafrost-Engineering Properties along the Qinghai-Tibet Highway (Tutuhe ) <-5  C: Extreme Stable type -5  C to -3  C: Stable type -3  C to -1.5  C: Sub-stable type -1.5  C to -0.5  C: Transit type -0.5  C to 0.5  C: Unstable type >0.5  C: Extreme unstable type

The change of permafrost stability along the Qinghai-Tibet Highway

A Distributed Calculation Method for Glacier Volume Change 1964

Calculation of glacier mass balance using GIS

Thanks