青藏高原东部及东侧地区低值系统与高原积雪的相关研究

在普查青藏高原东部1960-1998年6～8月700hPa天气图上低值系统出现次数的基础上，将其进行多种组合，将组合的资料与青藏高原冬春积雪资料进行同步相关分析，再将通过显著性水平α＝0．01检验的几组资料，用墨西哥帽子波进行计全。对比这些不同时间尺度的子波系数，得到了一些有益的结果。它反映出低值系统与高原积雪间有密切关系。     

利用细分光谱仪数据分析水体泥土含量的方法研究

分析了水中泥土含量对水体光谱特征的影响。对利用水体的光谱反射率计算水体中泥土含量的方法进行了分析，找出了用于泥土含量计算的最佳波段。该方法对今后的利用高光谱遥感图像计算河流和海水中的泥沙含量及估算水土流失具有一定的参考意义。     

信息量直接计算法在甘肃一宁夏一青海地区前兆标志体系研究中的应用

本文提出了异常前兆信息量的直接计算法,实现了各种观测资料前兆异常的无量纲前兆信息量转换。用该方法对甘、宁,青地区５种观测手段共９２个测项的５日均值一阶差分相关异常进行了前兆信息量计算,通过２４次５级以上相关地震的回顾性分析研究,求得了９２个测项的有效单位异常平均信息量,为前兆标志体系的进一步研究打下了良好的基础,又通过７次７级以上相关地震前兆信息量变化特征的统计,给出了一组预报地震三要素参考指标。     

山西夏县中心地震台断层逸出气氡、溶解水氡测值干扰因素分析

山西夏县中心震台断层逸出气氡及溶解水氡分别观测中条山山前断裂土壤逸出气氡及热水井的水中溶解氡值。观测灵敏度高、信息量大,但易受其他因素的干扰。通过对观测值进行分析,发现,夏县台断层逸出气氡测值与气温呈正相关,与气压呈负相关;气温、气压对夏县台热水井溶解水氡测值几乎没有影响,但受水位的影响较明显。     

近60a来南京季节变化特征分析

利用1951年1月-2010年12月南京市逐日气温观测资料,依据张宝堃应用候平均气温稳定通过某一临界值划分四季的标准,建立了近60 a南京的季节平均气温的时间序列,分析了近60a南京春、夏、秋、冬四季开始、结束及持续时间的变化特征,给出了季节气温的变化趋势以及候平均与入季时间、季节持续时间的相关分析.结果表明:近60a,南京入冬时间推迟,入夏时间提前.冬季变短,缩短的平均速率为2.9 d/10a;夏季变长,增加的平均速率为4.1d/10a;秋季变短,缩短的平均速率为1.5d/10a;春季略有些变长.南京冬、春季平均气温升高,且冬季气温升高更为显著,而夏、秋季平均气温下降,秋季气温下降略明显于夏季.冬季最低气温有升高的趋势,夏季最高气温与年较差有下降的趋势.春季入季时间与春季的平均气温成正相关,而秋季的入季时间与秋季平均气温成负相关;夏季的平均最低气温和平均气温与夏季的长度成负相关,冬季的平均最高气温和冬季的长度成正相关.     

二进小波变换方法的地震信号分时分频去噪处理

应用二进小波变换理论,对地震记录剖面进行小波分解,在小波变换域,对各分量剖面进行分时分频相关分析,并依此进行加权处理,最后通过小波反交换算法恢复出地震记录剖面．经实验该方法对衰减地震信号的噪声具有比较好的效果．     

南疆西部沙尘天气长期变化及突变特征分析

利用南疆西部15个国家气象站1961—2019年逐日沙尘天气资料,采用气候倾向率和统计检验等方法对南疆西部沙尘天气的时空变化特征进行分析。研究表明：春季为南疆西部沙尘暴及浮尘天气出现最多的季节、扬沙天气出现次多的季节,分别占全年沙尘暴、扬沙、浮尘的49%、38%、43%;夏季为扬沙天气出现最多的季节、是沙尘暴、浮尘天气出现次多的季节,分别占全年沙尘暴、扬沙、浮尘的35%、43%、35%;冬季为低频季节,发生占比分别为7%、6%、14%。南疆西部沙尘天气呈东多西少特征,山区沙尘天气日数明显少于平原,浮尘天气平原地区分布均匀,沙尘暴、扬沙平原东部和南部区域多于平原腹地。沙尘天气日数年际变化振幅较大,沙尘暴、扬沙、浮尘日数整体呈明显减少趋势。浮尘年际变化周期显著,其次为扬沙与沙尘暴,1984和1977年为沙尘暴、浮尘统计定义上的突变年份,扬沙存在2个突变点,分别为1982和1992年。沙尘暴和扬沙的主导风向为偏西北风,浮尘主导风向为偏东北风,主导风向与地形影响关联密切。     

利用油藏地质地球化学特征综合划分含油气系统

含油气系统的划分和范围的确定关系到油气勘探的方向和有利区带的选择,油源对比是含油气系统划分的关键.在缺乏成熟烃源岩样品的情况下,须结合油气藏的地质特征和演化历史,才能科学地划分含油气系统.据中非Muglad盆地Nugara坳陷同-构造上两个油田的地质分析和原油地球化学分析,把坳陷划分为两个独立的含油气系统,不同油田属于不同的系统.这一思路可为今后复杂构造演化区和裂谷盆地含油气系统研究提供借鉴.     

Recent Sea Level and Sea Surface Temperature Trends Along the Bangladesh Coast in Relation to the Frequency of Intense Cyclones

Bangladesh, one of the most densely populated countries in the world, is a victim of frequent natural calamities like tropical cyclones, tornadoes, floods, storm surges and droughts. Now the sea level rise (SLR) has also been included in these natural calamities. The SLR is likely to have greater impact on that part of Bangladesh having low topography and a wide flood plain. Since 21% of the population lives in the low coastal belt, any increase in sea level will be a problem of ominous proportion for Bangladesh. Since the cyclogenesis enhances over the Bay of Bengal during May and November, the sea level and sea surface temperature (SST) trends of these two months have been analyzed and calculated. The results of the selected stations one in the eastern coast and another in the western coast of Bangladesh show that Bangladesh coastal sea level is rising in the same way as the global sea level, but the magnitude is quite different. The difference in the behavior of sea level rise along the Bangladesh coast and the global trend may be due to the tectonic activity such as subsidence of the land. The mean tide level at Hiron Point (in Sunderbans) has shown an increasing trend of about 2.5 mm/year in May and 8.5 mm/year in November. Similarly near Cox?s Bazar (in the eastern coast of Bangladesh) it has registered a positive trend of about 4.3 mm/year in May and 10.9 mm/year in November. Thus the increment in the sea level along the Bangladesh coast during cyclone months is much more pronounced. In coastal waters near Hiron Point the SST has registered an increasing trend of about 1°C in May and 0.5°C in November during the 14-year period from 1985?1998. Near Cox?s Bazar, SST has shown a rising trend of about 0.8°C in May and about 0.4°C in November during the same 14-year period. The magnitude of SST trend is slightly more along the west coast. Any change in the frequency and intensity of tropical cyclones will have far reaching implications in the South Asian region. The rise in SST in the cyclone months seems to be correlated with the frequency and intensity of tropical cyclones. During these months, an increasing trend in the frequency and intensity of severe cyclones has been observed.     

Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China

The profile characteristics and the temporal dynamics of soil moisture variation were studied at 26 locations in Da Nangou catchment (3.5 km²) in the loess area of China. Soil moisture measurements were performed biweekly at five depths in the soil profile (0–5, 10–15, 20–25, 40–45 and 70–75 cm) from May to October 1998 using Delta-T theta probe. Soil moisture profile type and temporal variation type and their relationship to topography and land use were identified by detrended canonical correspondence analysis (DCCA) and correlation analysis. The profile distribution of time-averaged soil moisture content can be classified into three types i.e. decreasing-type, waving-type and increasing-type. The profile features of soil moisture (e.g. profile gradient and profile variability) are influenced by different environmental factors. The profile type of soil moisture is only attributed to land use while profile gradient and profile variability of soil moisture is mainly related to land use and topography (e.g. landform type and slope). The temporal dynamics of layer-averaged soil moisture content is grouped into three types including three-peak type, synchro-four-peak type and lagged-four-peak type. These types are controlled by topography rather than by land use. The temporal dynamic type of soil moisture shows significant correlation with relative elevation, slope, aspect, while temporal variance displays significant relation with slope shape. The mean soil moisture is related to both the profile and dynamics features of soil moisture and is controlled by both land use and topography (e.g. aspect, position, slope and relative elevation). The spatial variability of soil moisture across landscape varies with both soil depths and temporal evolution.