四川茂县叠溪镇新磨村滑坡特征与成因机制初步研究

西藏自治区贡觉县雄松乡至沙东乡金沙江流域作为川藏铁路的必经河流,地形崎岖、地质灾害隐患点多,亟需对该地区隐患点进行全方位的识别。首先,选取61景哨兵一号（Sentinel-1）升轨影像、53景Sentinel-1降轨影像和7景陆地观测技术卫星2号（advanced land observing satellite 2,ALOS-2）升轨影像对研究区域进行滑坡探测与监测。然后,利用合成孔径雷达（interferometric synthetic aperture radar,InSAR）通用型大气改正在线服务（generic atmospheric correction online service for InSAR,GACOS）辅助干涉影像堆叠技术（InSAR Stacking）的方法,获取研究区域雷达视线（line of sight, LOS）方向的InSAR年形变平均速率图,并结合3个轨道的结果提取出沿坡向和垂直滑坡向的平均速率图。最后,与LiCSBAS时间序列分析包的结果进行比较,发现两者具有高度一致性,LOS向年形变速率图像的相关系数在0.92以上,沿坡向和沿垂直滑坡向年形变速率的相关系数在0.85以上,证明了GACOS辅助下InSAR Stacking结果的可靠性。此外,还发现研究区域内沿坡向最大年形变速率为-163 mm/a;结合InSAR形变结果与光学遥感影像解译,可将该滑坡群分为A~G 7个区域进行实时监测。     

我国断层气测量在地震科学研究中的应用现状

氢气被认为是反应断裂活动最灵敏的地球化学组分之一。研究影响断裂带氢浓度动态变化的主要因素,是科学分析断裂带氢与构造活动关系的基础工作。本文基于河南内乡马山口断层气氢气浓度与辅助测项的连续观测资料,重点分析了氢浓度变化与地温、气温、气压的相关关系,确定了主要影响因素。结果表明,氢气浓度日变化极值介于气温和地温之间,极值点靠近地温一侧。使用逐步回归方法分析进一步证明,地温、温度对氢气浓度均有影响,但地温影响更显著,气压影响不显著。总体来讲,氢浓度会受到地温和气温的双重影响,但与地温关系更为密切。     

非常规探测资料在江西一次暖区暴雨过程分析中的应用

综合运用风廓线雷达等多种非常规探测资料,对江西省2013年6月29日暖区大暴雨进行分析,并对比6月28日锋面暴雨,归纳总结短时大暴雨发生的一些前兆信号及可用指标。结果表明:1)风廓线雷达能直观反映暴雨区附近中小尺度扰动、近地面弱冷空气入侵、急流脉动发展等特征,1.5—4 km高度层出现16 m/s以上急流对暖区暴雨发生有利,对强降水的发生有1—3 h提前指示作用。2)0.5—1.5 km高度层正的风垂直切变带对应降水发生发展,正速度带中大于4 m/s风速切变对应下游降水加强。3)PWV值在强降水发生前常出现持续上升或波浪上升。PWV值达到65 mm且维持较长时间,同时配合动力触发条件,有利于强降水的发生;PWV值低于60 mm并持续性下降,对应降水趋于减弱停止;强降水落区出现在湿舌前端的PWV等值线密集区内。4)此次强降水主要发生在TBB小于-40℃区域前端的等值线密集区和地面辐合线附近,且地面辐合线的强度、移向与新生单体的发展密切相关;强回波不断在地面辐合线附近合并加强形成"列车效应",雷达回波上逆风区、急流核、速度对等特征的出现有利于强降水的维持。     

我国夏季降水及相关大气环流场未来变化的预估及不确定性分析

利用政府间气候变化专门委员会第四次评估报告(IPCCAR4)的15个耦合气候模式在不同排放情景下的模拟结果,对我国夏季降水及相关大气环流场的未来时空变化特征与模式之间的不确定性作了研究。结果表明,在全球变暖背景下,我国夏季降水表现出较强的局地特征。其中,我国东部和高原地区的降水在21世纪表现出明显的增加趋势,而且这种趋势随着变暖的加剧而增强,同时模式模拟结果之间的一致性也更好,表明这一结果的可信度较高。在全球变暖背景下,我国新疆南部地区表现为持续的降水减少趋势,而我国西南地区夏季降水的变化则呈现出先减少(21世纪初)后增加的特征,不同模式对降水这些局地特征的模拟也都表现出较好的一致性。其他地区夏季降水在21世纪的变化不大,同时模式模拟的一致性也较差。多模式模拟的我国未来百年夏季降水的这些变化特征在温室气体高、中、低不同排放情景下基本一致,A2情景预估结果变化最大,A1B次之,B1相对最小。东亚夏季大气环流场的预估结果显示,在全球变暖的背景下,大部分模式的模拟结果都表明,东亚夏季风环流有所增强,从而使得由低纬度大洋和南海地区向我国大陆的水汽输送增加,造成该地区大气含水量的增多,从而为我国东部地区夏季降水的增加提供有利条件。此外,随着全球变暖的加剧,西太平洋副热带高压持续增强,其变化对我国东部地区夏季降水的影响程度和范围也明显增大。这些环流场及其不确定性的分析结果进一步加强了我国夏季降水未来变化预估结果的可信度。     

The assessment of landslide susceptibility mapping using random forest and decision tree methods in the Three Gorges Reservoir area,China

Landslide susceptibility mapping is an indispensable prerequisite for landslide prevention and reduction. At present, research into landslide susceptibility mapping has begun to combine machine learning with remote sensing and geographic information system (GIS) techniques. The random forest model is a new integrated classification method, but its application to landslide susceptibility mapping remains limited. Landslides represent a serious threat to the lives and property of people living in the Zigui–Badong area in the Three Gorges region of China, as well as to the operation of the Three Gorges Reservoir. However, the geological structure of this region is complex, involving steep mountains and deep valleys. The purpose of the current study is to produce a landslide susceptibility map of the Zigui–Badong area using a random forest model, multisource data, GIS, and remote sensing data. In total, 300 pre-existing landslide locations were obtained from a landslide inventory map. These landslides were identified using visual interpretation of high-resolution remote sensing images, topographic and geologic data, and extensive field surveys. The occurrence of landslides is closely related to a series of environmental parameters. Topographic, geologic, Landsat-8 image, raining data, and seismic data were used as the primary data sources to extract the geo-environmental factors influencing landslides. Thirty-four layers of causative factors were prepared as predictor variables, which can mainly be categorized as topographic, geological, hydrological, land cover, and environmental trigger parameters. The random forest method is an ensemble classification technique that extends diversity among the classification trees by resampling the data with replacement and randomly changing the predictive variable sets during the different tree induction processes. A random forest model was adopted to calculate the quantitative relationships between the landslide-conditioning factors and the landslide inventory map and then generate a landslide susceptibility map. The analytical results were compared with known landslide locations in terms of area under the receiver operating characteristic curve. The random forest model has an area ratio of 86.10%. In contrast to the random forest (whole factors, WF), random forest (12 major factors, 12F), decision tree (WF), decision tree (12F), the final result shows that random forest (12F) has a higher prediction accuracy. Meanwhile, the random forest models have higher prediction accuracy than the decision tree model. Subsequently, the landslide susceptibility map was classified into five classes (very low, low, moderate, high, and very high). The results demonstrate that the random forest model achieved a reasonable accuracy in landslide susceptibility mapping. The landslide hazard zone information will be useful for general development planning and landslide risk management.     

用T—矩阵法分析降水粒子在微波段下的ZDR特性

本文采用Ｔ－矩阵方法从理论计算的角度分析了在Ｘ、Ｃ和Ｓ波段下不同轴此,大小和相态的扁椭球降水粒子的差反射率因子ＺＤＲ,对为三种波长的双偏振雷达实际动用提出了更合理的解释,得到若干有用的结论,文中还对Ｔ－矩阵方法的准确性进行地评价。     

阿尔山地区积雪变化特征

选取阿尔山气象站1981—2015年冷季(10月—次年4月)气象资料,利用滑动平均、线性倾向估计和Mann-Kendall等方法,对年最大积雪深度、积雪日数、气温和降水量进行分析。结果表明,阿尔山地区年最大积雪深度主要发生在1月至3月,其中2月份概率最大,达50%;34 a内最大积雪深度呈上升趋势(2.77 cm/10a),年平均增加0.98%,且年最大积雪深度在1998年发生了突变,即在1998年之前增长缓慢,在2000年以后上升趋势显著。积雪日数的统计分析表明,初始积雪日数和有效积雪日数呈现略微减少趋势,而稳定积雪日数有微弱的增加趋势;通常初始积雪日数比有效积雪日数大30天左右。年最大积雪深度与稳定积雪时期的降水量、积雪日数、日照时数有显著的相关性,相关系数分别为0.647、0.515、0.584,但与稳定积雪时期的气温没有明显的相关性。在全球变暖的大环境下,积雪深度随着降水量和日照时数的增加而增加,且积雪深度受降水量的影响大于日照时数的影响。     

Impact of satellite observed microwave SST on the simulation of tropical cyclones

The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold’s SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold’s and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial resolution showed sharper gradient when compared to the Reynold’s SST. The use of TMI SST improved the WRF cyclone intensity prediction when compared to that using Reynold’s SST for both the cases studied. The improvements in intensity were mainly due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold’s SST improved cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification and movement of tropical cyclones over the Indian Ocean.     

长江口现代潮滩沉积物粒度特征及其在沉积相识别中的应用

本研究通过对长江口现代潮滩6个柱状样沉积物的粒度精细分析,试图提取研究区潮滩沉积相识别的粒度敏感指标,并通过对长江三角洲南部平原一个全新世钻孔(SL67孔)潮滩沉积物的粒度研究,检验现代沉积粒度敏感指标在全新世钻孔潮滩沉积相识别中的应用。研究显示,长江口现代高潮滩和中潮滩的黏性颗粒(8μm)和粗粉砂(32~63μm)含量差异显著,可以成为区分高潮滩和中潮滩的敏感组分;在开敞型的中、低潮滩之间,砂(63μm)和细粉砂含量(8~32μm)也差异明显。长江口现代潮滩沉积物的粒度频率曲线及众数值也可以有效协助区分高潮滩、中潮滩和低潮滩沉积物。利用上述粒度敏感组分和众数指标检验SL67孔全新世早中期在海平面波动控制下的潮滩演替过程,并揭示了7.5 cal ka BP前后的一次海平面加速上升事件。     

Analysis of decade-long time series of GPS-based polar motion estimates at 15-min temporal resolution

We present results from the generation of 10-year-long continuous time series of the Earth’s polar motion at 15-min temporal resolution using Global Positioning System ground data. From our results, we infer an overall noise level in our high-rate polar motion time series of 60 \(\upmu \hbox {as}\) (RMS). However, a spectral decomposition of our estimates indicates a noise floor of 4 \(\upmu \hbox {as}\) at periods shorter than 2 days, which enables recovery of diurnal and semidiurnal tidally induced polar motion. We deliberately place no constraints on retrograde diurnal polar motion despite its inherent ambiguity with long-period nutation. With this approach, we are able to resolve damped manifestations of the effects of the diurnal ocean tides on retrograde polar motion. As such, our approach is at least capable of discriminating between a historical background nutation model that excludes the effects of the diurnal ocean tides and modern models that include those effects. To assess the quality of our polar motion solution outside of the retrograde diurnal frequency band, we focus on its capability to recover tidally driven and non-tidal variations manifesting at the ultra-rapid (intra-daily) and rapid (characterized by periods ranging from 2 to 20 days) periods. We find that our best estimates of diurnal and semidiurnal tidally induced polar motion result from an approach that adopts, at the observation level, a reasonable background model of these effects. We also demonstrate that our high-rate polar motion estimates yield similar results to daily-resolved polar motion estimates, and therefore do not compromise the ability to resolve polar motion at periods of 2–20 days.