Summary

YUE-HASM has highly quickened computational speed and greatly increased simulation accuracy, compared to relative classical methods. YUE-HASM might efficiently solve the error, real-time, direct modeling, and

Figure 3 (Continued)

multiscale problems of current GIS. However, there is Parallelization of YUE-HASM is of particular impor-

great potential for considerably improving the efficiency tance. For many applications, even today's supercomputers of YUE-HASM. are not powerful enough even if the multigrid methods

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were used. It is generally agreed that further accelerations in the supercomputer range will principally be achieved by an increasing degree of parallelism since possible improvements of single processors seem to be much more limited. Methods lacking either parallelism or numerical efficiency will not be suitable for the challenging problems of the future. How to design an ideal parallel multigrid algorithm depends on the concrete parallel architecture to be employed: whether a parallel system with shared, distributed, or some hierarchical memory is used, whether it consists of vector, cache, or scalar processors, and which type of interconnection network is used.

An adaptive simulation approach with grid selection strategies is highly significant for YUE-HASM, which is a very

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desirable feature for an accurate analysis and an efficient simulation. The adaptive approach can be distinguished into predefined refinement and self-adaptive refinement. In predefined refinement, the refinement is determined before the solution process is started; in self-adaptive approaches, the grid refinements are carried out dynamically during the solution process. In practice, the predefined refinement and self-adaptive refinement may be combined. The adaptive grid selection strategies generally have to provide a discretization approach with a domain-partitioning method capable of adapting the size of the discretization cells locally and to supply an adaptive simulation approach with a method for the evaluation and control of the discrete approximation errors during simulation. In addition, construction of adaptive grids and the control of the discrete approximation accuracy should be performed both in space and time

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Cool temperate wet Forest Cool temperate rain forest Warm temperate moist forest B Warm temperate wet forest ■ Subtropical moist forest Subtropical wet forest

Figure 3 The real-world simulation of climate change trend and ecosystem change in Jiangxi province of China: (a) weather observation stations scattered over and around Jiangxi province; (b) change trend of annual mean temperature simulated by operating YUE-HASM on data from the weather observation stations (C1 is the annual mean temperature in 1960s, C2 in 1970s, C3 in 1980s, and C4 in 1990s); (c) change trend of annual mean precipitation simulated by operating YUE-HASM on data from the weather observation stations (D1 is the annual mean precipitation in 1960s, D2 in 1970s, D3 in 1980s, and D4 in 1990s); and (d) HLZ ecosystem change during the period from 1960s to 1990s by operating HLZ model on YUE-HASM climatic surfaces.

dimensions. Adaptive grid structures should allow for easy and efficient local modifications without introducing unnecessary refined domain areas and be as regular as possible in order to supply an acceptable order of consistency and to minimize the errors introduced with data transfers between different grid structures.

Widespread access to the Internet, the ubiquity of browsers, and the explosion of geographical information have made it possible to develop new forms of multimedia geor-epresentations on the web, which is defined as 'web GIS'. The creation, manipulation, and exploration of georefer-enced virtual environments can be carried out by GIS, which is called as 'virtual reality GIS'. It has become possible to monitor, transmit, record, and analyze the movement of mobile agents with the development of real-time positioning systems and cost-effective mobile communications, which is named as 'real-time GIS'. OpenGIS provides a framework for developers to create software that enables users to access and process geographic data from a variety of sources, using a common computing interface within an open information technology environment. GRASS GIS enables users to perform geographic visualization tasks on tiled high-resolution displays powered by the clusters of commodity personal computers.

The development of web GIS, virtual GIS, real-time GIS, OpenGIS, and GRASS GIS would make YUE-HASM play an essential role in earth system science because YUE-HASM has much higher accuracy and faster computational speed. YUE-HASM would be an essential part of ecological informatics that studies the fundamental issues arising from the creation, storage, processing, analyzing, and modeling of ecological information.

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