抚仙湖流域植被覆盖度时空分异及其与坡度的关系

采用像元二分模型,以1974-2014年间的10期Landsat 5/8影像和DEM数据,对抚仙湖流域植被覆盖动态变化进行监测,并结合基础地理信息数据、行政区划界资料、行业部门专题资料等,分析流域植被覆盖时空分异及其与坡度的关系.结果表明:(1)1974-2014年,抚仙湖流域裸地(Ⅰ级)面积波动极小,低植被覆盖(Ⅱ级)、中低植被覆盖(Ⅲ级)、中高植被覆盖(Ⅳ级)面积变化波动大,变化趋势线数次出现谷值和峰值,高植被覆盖(Ⅴ级)面积则呈增加趋势.(2)坡度较小、地势较平缓的区域(0°~15°)以裸地和低植被覆盖为主;中低植被覆盖度、中高植被覆盖和高植被覆盖度主要分布在地势比较陡峭的区域(>15°).(3)抚仙湖流域各年份植被覆盖度Ⅰ级面积最大,1974,1977,1989,1996年Ⅱ,Ⅲ级面积较大,而Ⅳ,Ⅴ级面积较小;2000年后的Ⅱ,Ⅲ,Ⅳ级面积变化较小;2006,2009,2012,2014年Ⅳ,Ⅴ级的面积较大,Ⅱ,Ⅲ级的面积较小.     

Assessment of ski condition reliability in the Spanish and Andorran Pyrenees for the second half of the 20th century

In this study temporal trends of 14 climate and snow parameters related to ski conditions were analyzed for 11 ski stations located in the central Pyrenees (Spain and Andorra). We also investigated whether there was a temporal association for the analyzed parameters, such that the occurrence in a particular year of good (or bad) climate or snow conditions as represented by one parameter was similarly reflected by the other parameters. The lack of reliable climate and snow measurements was overcome by the use of simulated climate data retrieved from a high resolution hindcast simulation available for the period 1960–2006. These data were also used as inputs for an energy and mass snow energy model to obtain snow series. The results showed trends in ski reliability parameters for the 1960–2006 period. The number of days having a snowpack deeper than 30 cm and 100 cm showed declines at low and mid altitudes. The start of the ski season appears progressively delayed for all stations, and the ski season shortened. The frequency of rainy days increased at 3 stations and decreased at 8, while the frequency of days having heavy snowfall increased at 8 stations and declined at 3. Days having potential for snowmaking declined at all stations. The number of days having a wind-chill < −20 °C also decreased markedly, as overall did the number of days having a wind speed greater than 80th percentile. The main findings from the assessment of temporal associations between climate and snow parameters were positive correlations between snow depth and windy conditions. Seasons having a higher frequency of very cold days had a lower frequency of heavy snowfall and rainy days. Thus, the adverse effects on the ski industry of lesser snow availability may have been partially negated by the occurrence of fewer days of closure because of high winds, or other adverse meteorological factors.     

CO2 seasonal variation and global change: Test global warming from another point of view

CO₂ and temperature records at Mauna Loa, Hawaii, and other observation stations show that the correlation between CO₂ and temperature is not significant. These stations are located away from big cities, and in various latitudes and hemispheres. But the correlation is significant in global mean data. Over the last five decades, CO₂ has grown at an accelerating rate with no corresponding rise in temperature in the stations. This discrepancy indicates that CO₂ probably is not the driving force of temperature change globally but only locally (mainly in big cities). We suggest that the Earth''s atmospheric concentration of CO₂ is too low to drive global temperature change. Our empirical perception of the global warming record is due to the urban heat island effect:temperature rises in areas with rising population density and rising industrial activity. This effect mainly occurs in the areas with high population and intense human activities, and is not representative of global warming. Regions far from cities, such as the Mauna Loa highland, show no evident warming trend. The global monthly mean temperature calculated by record data, widely used by academic researchers, shows R²=0.765, a high degree of correlation with CO₂. However, the R² shows much less significance (mean R²=0.024) if calculated by each record for 188 selected stations over the world. This test suggests that the inflated high correlation between CO₂ and temperature (mean R²=0.765-0.024=0.741) used in reports from the Intergovernmental Panel on Climate Change (IPCC) was very likely produced during data correction and processing. This untrue global monthly mean temperature has created a picture:human emission drives global warming.     

The GRASS GIS temporal framework

The availability of continental and global-scale spatio-temporal geographical data sets and the requirement to efficiently process, analyse and manage them led to the development of the temporally enabled Geographic Resources Analysis Support System (GRASS GIS). We present the temporal framework that extends GRASS GIS with spatio-temporal capabilities. The framework provides comprehensive functionality to implement a full-featured temporal geographic information system (GIS) based on a combined field and object-based approach. A significantly improved snapshot approach is used to manage spatial fields of raster, three-dimensional raster and vector type in time. The resulting timestamped spatial fields are organised in spatio-temporal fields referred to as space-time data sets. Both types of fields are handled as objects in our framework. The spatio-temporal extent of the objects and related metadata is stored in relational databases, thus providing additional functionalities to perform SQL-based analysis. We present our combined field and object-based approach in detail and show the management, analysis and processing of spatio-temporal data sets with complex spatio-temporal topologies. A key feature is the hierarchical processing of spatio-temporal data ranging from topological analysis of spatio-temporal fields over boolean operations on spatio-temporal extents, to single pixel, voxel and vector feature access. The linear scalability of our approach is demonstrated by handling up to 1,000,000 raster layers in a single space-time data set. We provide several code examples to show the capabilities of the GRASS GIS Temporal Framework and present the spatio-temporal intersection of trajectory data which demonstrates the object-based ability of our framework.     

晚新生代红粘土的粒度分布及其指示的冬季风演变

晚新生代黄土高原红粘土的粒度分布具有明显的三峰分布 ,分别在 2～ 2 0、2 0～ 10 0和 0 .0 4～ 1μm出现峰值 ,每个峰值对应于不同的形成过程 ,与晚第四纪黄土一致。方式 C粒子 (0 .0 4～ 1μm)可能代表本底气溶胶粒子的沉积物 ,方式 A粒子 (2 0～ 10 0μm)代表冬季风尘暴搬运的大气粉尘 ,方式 B粒子 (2～ 2 0μm)代表冬季风正常搬运的大气粉尘。红粘土的粒度分布表明 ,东亚冬季风环流而非北半球西风环流控制着红粘土物质的堆积过程。红粘土中 >19μm的粗粒子组分指示了东亚冬季风演化历史 :6 .5 Ma BP冬季风开始发育 ,5 .2～ 4.5 Ma BP冬季风减弱并达到最低值 ,4.5～ 3.6 Ma BP冬季风由弱变强 ,3.6～ 2 .6 Ma BP冬季风快速增强并达到最大值。     

中国沿岸相对海面变化的本征分析和预测

利用经验正交函数的方法，将平均海面分解为正交时，空函数积的代数和。采用起主导作用的正交函数进行组合，得到修正的海平面变化值，它消除了某些随机的影响。去掉平均海面主要时间本征函数中的主要周期部分，求得剩余部分的变化率，乘以空间本征函数可得各站平均海面的变化速率，对未来的时间本征函数作出预报，便可得到未来的平均海面预报值。     

江淮梅雨区1960—2014年夏季极端降水变化特征及影响因素

利用江淮梅雨区66个测站1960—2014年逐日降水数据和同期NCEP/NCAR再分析资料,基于多个极端降水指数,通过趋势分析、EOF分析和合成分析等手段,探究该区夏季极端降水事件的时空变化特征及影响因素。结果表明：(1)夏季极端降水指数以上升为主,显著上升区主要位于东部。(2)夏季极端降水指数第一特征向量呈全“+”分布形态,北部地区更强,第二特征向量呈“西北+东南-”分布形态;第一模态时间系数呈上升趋势,第二模态时间系数变化趋势不明显。(3)在强（弱）夏季极端降水典型年,西太平洋副热带高压位置偏西（东),中纬度地区表现出经（纬）向型环流分布特征,利于（不利于）江淮地区极端降水发生;同时,对流层中、低层上升运动增强（中层气流辐散增强),水汽通量增强、辐合（减弱、辐散),因此,梅雨区极端降水异常增强（减弱)。     

舟山海雾特征及其对数值模式的初步订正

采用舟山海域1962—2015年的4个气象观测站资料、2014—2015年2 a的逐时自动气象数据和浮标站数据,统计分析了舟山海雾特征,结果表明:海雾总是在大尺度背景条件和一定的气象水文条件下发生;海雾春季最多,秋季最少,一天中多发生在夜间和早晨,又以下半夜到早晨最多,雾散一般在11∶00以后;海雾按天气形势可分4型,不同类型其季节变化和日变化存在差异;浓雾发生的要素特征为,气温5~27℃,海温9~27℃,气温露点差0~4℃,90%的浓雾发生在2 m相对湿度≥95%、气海温差-3.7~3.2℃时,浓雾风向主要落在东南风和偏南风之间,平均风力一般在1~5级;利用要素阈值对WRF能见度模式进行订正检验,发现对提高浓雾的定性预报准确率有较明显的作用。