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林岩銮 黄小猛 梁逸爽 秦怡 徐世明 黄文誉 徐芳华 刘利 王勇 彭怡然 王兰宁 薛巍 付昊桓 张广俊 王斌 李锐喆 张诚 卢麾 阳坤 罗勇 白玉琪 宋振亚 王敏琦 赵文婕 张峰 徐敬蘅 赵曦 陆春松 骆亦其 陈奕兆 胡勇 唐强 陈德训 杨广文 宫鹏 《气候变化研究进展》2019,15(5):545-550
世界气候研究计划(WCRP)组织实施第六次国际耦合模式比较计划(CMIP6),清华大学联合国内多家单位,通过多年的模式研发,完成联合地球系统模式(CIESM),除了CMIP6的气候诊断、评估和描述试验(DECK)和历史气候模拟试验(Historical),模式拟参与6个CMIP6子计划。通过介绍该模式的基本情况及其参与的试验子计划,为今后模式试验数据使用者提供参考。 相似文献
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2001-2010 年内蒙古植被覆盖度时空变化特征 总被引:65,自引:4,他引:61
基于MODIS-NDVI 遥感数据反演了内蒙古地区2001-2010 年植被覆盖度的空间格局和变化规律, 并结合该地区同期降雨量和温度数据, 分别从不同空间和时间尺度上分析了森林生态区、草原生态区和荒漠生态区植被的年际变化和月际变化对气候变化的响应。结果表明:(1) 内蒙古植被覆盖度在空间上呈现东高西低的分布特征, 自西向东的变化速率为0.2/10°N, 10 年间森林、草原和荒漠生态区的年均植被覆盖度分别为0.57、0.4 和0.16;(2) 2001-2010年, 内蒙古植被覆盖度总体上呈上升趋势, 研究区内植被覆盖度极显著增加和显著增加的面积分别占总面积的11.25%和29.13%, 二者之和大于植被覆盖度极显著减少和显著减少的面积比例之和, 后者分别为7.65%和26.61%;(3) 在年际水平上, 内蒙古植被生长总体上与降雨量的关系更加密切, 而在月际水平上, 降雨量和温度对植被生长的影响作用相当, 说明年内植被生长更依赖于水热组合的共同作用, 而与单一气候因子的相关性降低;(4) 森林生态区植被覆盖度在年/月际水平上均与温度的相关性较强, 荒漠生态区植被覆盖度在年/月际水平上均与降雨量相关性较强, 而草原生态区植被覆盖度在年际水平上主要受降雨影响, 在月际水平上与二者相关性相当;(5) 草原区月植被覆盖度对降雨量的响应存在时滞效应。 相似文献
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内蒙古植被覆盖度的时空动态变化及其与气候因子的关系(英文) 总被引:3,自引:2,他引:3
The vegetation coverage dynamics and its relationship with climate factors on different spatial and temporal scales in Inner Mongolia during 2001-2010 were analyzed based on MODIS-NDVI data and climate data.The results indicated that vegetation coverage in Inner Mongolia showed obvious longitudinal zonality,increasing from west to east across the region with a change rate of 0.2/10°N.During 2001-2010,the mean vegetation coverage was 0.57,0.4 and 0.16 in forest,grassland and desert biome,respectively,exhibiting evident spatial heterogeneities.Totally,vegetation coverage had a slight increasing trend during the study period.Across Inner Mongolia,the area of which the vegetation coverage showed extremely significant and significant increase accounted for 11.25% and 29.13% of the area of whole region,respectively,while the area of which the vegetation coverage showed extremely significant and significant decrease accounted for 7.65% and 26.61%,respectively.On inter-annual time scale,precipitation was the dominant driving force of vegetation coverage for the whole region.On inter-monthly scale,the change of vegetation coverage was consistent with both the change of temperature and precipitation,implying that the vegetation growth within a year is more sensitive to the combined effects of water and heat rather than either single climate factor.The vegetation coverage in forest biome was mainly driven by temperature on both inter-annual and inter-monthly scales,while that in desert biome was mainly influenced by precipitation on both the two temporal scales.In grassland biome,the yearly vegetation coverage had a better correlation with precipitation,while the monthly vegetation coverage was influenced by both temperature and precipitation.In grassland biome,the impacts of precipitation on monthly vegetation coverage showed time-delay effects. 相似文献
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GIMMS(Global Inventory Modeling and Mapping Studies) NDVI(Normalised Difference Vegetation Index) from 1982 to 2006 and MODIS(Moderate Resolution Imaging Spectroradiometer) NDVI from 2001 to 2010 were blended to extract the grass coverage and analyze its spatial pattern. The response of grass coverage to climatic variations at annual and monthly time scales was analyzed. Grass coverage distribution had increased from northwest to southeast across China. During 1982–2010, the mean nationwide grass coverage was 34% but exhibited apparent spatial heterogeneity, being the highest(61.4%) in slope grasslands and the lowest(17.1%) in desert grasslands. There was a slight increase of the grass coverage with a rate of 0.17% per year. Increase in slope grasslands coverage was as high as 0.27% per year, while in the plain grasslands and meadows the grass coverage increase was the lowest(being 0.11% per year and 0.1% per year, respectively). Across China, the grass coverage with extremely significant increase(P0.01) and significant increase(P0.05) accounted for 46.03% and 11% of the total grassland area, respectively, while those with extremely significant and significant decrease accounted for only 4.1% and 3.24%, respectively. At the annual time scale, there are no significant correlations between grass coverage and annual mean temperature and precipitation. However, the grass coverage was somewhat affected by temperature in alpine and sub-alpine grassland, alpine and sub-alpine meadow, slope grassland and meadow, while grass coverage in desert grassland and plain grassland was more affected by precipitation. At the monthly time-scale, there are significant correlations between grass coverage with both temperature and precipitation, indicating that the grass coverage is more affected by seasonal fluctuations of hydrothermal conditions. Additionally, there is one-month time lag-effect between grass coverage and climate factors for each grassland types. 相似文献
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