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| 1 | 基于EnKF-MCRP模型的生态用地扩张模拟研究显示文摘以生态脆弱区典型县域磴口县为研究区,基于2002、2007、2012、2015年4期遥感影像解译数据,将数据同化技术引入生态源地的变化模拟中,考虑生态障碍和生态阻力构建En KF-MCRP模型,进行磴口县生态用地的变化模拟。结果表明,引入数据同化技术的En KF-CA/Markov模型的模拟总精度达到82.4%,数据同化能够减少误差的积累。根据扩展能力磴口县生态源地共分为5个等级,其中3、4、5级生态源地的空间布局形成东北-西南、西北-西南的沙漠化防护格局。引入生态源地变化的En KF-MCRP模型的生态用地扩张模拟精度最高,生态用地面积与空间布局最接近实际情况,方差达到0.4。此研究可为当前以及未来的生态用地规划和管理提供科学根据。 | 于强 岳德鹏 Di Yang 张启斌 马欢 李宇彤 | 2016 | 农业机械学报2016，47，9： | 17 |
| 2 | Paleoclimate data assimilation: Its motivation, progress and prospects显示文摘Reconstructing past climate is beneficial for researchers to understand the mechanism of past climate change, recognize the context of modern climate change and predict scenarios of future climate change. Paleoclimate data assimilation(PDA), which was first introduced in 2000, is a promising approach and a significant issue in the context of past climate research. PDA has the same theoretical basis as the traditional data assimilation(DA) employed in the fields of atmosphere science, ocean science and land surface science. The main aim of PDA is to optimally estimate past climate states that are both consistent with the climate signal recorded in proxy and the dynamic understanding of the climate system through combining the physical laws and dynamic mechanisms of climate systems represented by climate models with climate signals recorded in proxies(e.g., tree rings, ice cores). After investigating the research status and latest advances of PDA abroad, in this paper, the background, concept and methodology of PAD are briefly introduced. Several special aspects and the development history of PAD are systematically summarized. The theoretical basis and typical cases associated with three frequently-used PAD methods(e.g., nudging, particle filter and ensemble square root filter) are analyzed and demonstrated. Finally, some underlying problems in current studies and key prospects in future research related to PDA are proposed to provide valuable thoughts on and a scientific basis for PDA research. | FANG Miao LI Xin | 2016 | Science China Earth Sciences2016，59，9： | 3 |
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