青藏铁路多年冻土区含融化夹层路基的热状态

基于青藏铁路K1496+750监测断面含融化夹层路基长达10 a的地温监测数据,分析了在气候转暖及工程活动下天然场地及路基左右路肩下多年冻土热状态年变化过程、融化夹层的年变化过程及其对多年冻土热状态的影响。结果表明：监测断面天然场地、左右路肩下多年冻土上限逐年下降,热稳定性逐年降低;观测期内,左路肩下发育有融化夹层,融化夹层厚度在波动中呈增厚趋势,且其增厚主要是由多年冻土人为上限下降所致,而天然场地及右路肩下未发育融化夹层;多年冻土上限附近土体热积累显著,进而导致多年冻土上限逐年下降及其附近土体温度逐年升高,弱化了多年冻土的热稳定性;后期增加的块石护坡和热管两种具有“主动冷却”效能的工程补强措施很好的改善了路基的热稳定性,右路肩经工程补强措施后,多年冻土人为上限得到显著抬升,热稳定性得到显著改善,而左路肩由于融化夹层的存在,工程补强措施仅仅维持了当前多年冻土热状态,融化夹层的存在一定程度上弱化了工程补强措施所产生的冷却效能。     

An Innovative Bias-Correction Approach to CMA-GD Hourly QuantitativePrecipitation Forecasts

This paper proposes a simple and powerful optimal integration (OPI) method for improving hourly quantitative precipitation forecasts (QPFs, 0-24 h) of a single-model by integrating the benefits of different bias- corrected methods using the high-resolution CMA-GD model from the Guangzhou Institute of Tropical and Marine Meteorology of China Meteorological Administration (CMA). Three techniques are used to generate multi-method calibrated members for OPI: deep neural network (DNN), frequency-matching (FM), and optimal threat score (OTS). The results are as follows: (1) The QPF using DNN follows the basic physical patterns of CMA-GD. Despite providing superior improvements for clear-rainy and weak precipitation, DNN cannot improve the predictions for severe precipitation, while OTS can significantly strengthen these predictions. As a result, DNN and OTS are the optimal members to be incorporated into OPI. (2) Our new approach achieves state-of-the-art performances on a single model for all magnitudes of precipitation. Compared with the CMA-GD, OPI improves the TS by 2.5%, 5.4%, 7.8%, 8.3%, and 6.1% for QPFs from clear-rainy to rainstorms in the verification dataset. Moreover, OPI shows good stability in the test dataset. (3) It is also noted that the rainstorm pattern of OPI relies heavily on the original model and that OPI cannot correct for deviations in the location of severe precipitation. Therefore, improvements in predicting severe precipitation using this method should be further realized by improving the numerical model’s forecasting capability.     

哈萨克斯坦科扎萨伊油田优快钻井技术

哈萨克斯坦科扎萨伊油田钻井地质环境复杂,储层位于盐下,钻遇的地层层系多,地层性质差异大,具多套压力系统。钻井过程中发生地层漏失、坍塌、掉块及盐膏层蠕变等复杂情况,严重影响了钻井时效和钻井安全。针对这些技术难题,开展了油田井身结构、井身质量、提速潜力、高效钻头等分析与优化,提出了预弯曲钻具高倾角地层井斜控制技术、混合钻头减震提速技术,以及PDC-孕镶块复合钻头高研磨性地层提速技术。现场应用取得了较好的效果,平均机械钻速提高50%以上,钻井周期缩短28%。     

沁水煤田15号煤中氟的赋存状态及其沉积环境分析

氟是煤中有害元素之一,燃煤型氟排放造成的污染已经对人类的健康安全构成威胁。研究煤中氟赋存状态及其沉积环境,对掌握高氟煤分布规律及控制燃煤造成的氟排放具有重要意义。通过对沁水煤田内6座煤矿15号煤样品的分析发现:煤中氟含量与灰分显著相关,与黄铁矿硫、有机硫无相关关系,表明煤中氟主要以无机物形式赋存,且与含硫矿物无关;与钾、镁、硅、铝等元素含量具有显著的相关关系,表明氟有可能的主要赋存形式为金云母、氟金云母等矿物,以及以吸附存在于高岭石、勃姆石、伊蒙混层等黏土矿物中;与钙、磷元素含量无显著相关性,表明氟不以氟磷灰石、含氟羟基磷灰石等矿物大量赋存。此外,通过对沁水煤田15号煤的沉积环境分析发现,弱还原环境、较低盐度、偏酸性、较强的水动力条件有利于该区域煤中氟的富集。     

中国地区集合预报产品自适应递减平均偏差订正法的改进研究

基于中国地区T213集合预报产品2 m温度预报数据,采用卡尔曼滤波类型的自适应递减平均法进行偏差订正处理,原方案在剧烈降温天气订正效果表现不理想。通过对递减平均参数w的重新构建得到改进的订正方案w(i,p)(i为站点信息,p为天气过程信息),在此基础上进一步优化对历史信息的有效提取,得到改进的方案w(i,p)相似法和w(i,p)统计法,并进行效果检验。结果表明:改进为包含空间和天气过程信息的函数w(i,p)后方案的订正效果得到不同程度的提高,其中24 h剧烈降温预报各成员预报均方根误差平均减小了0. 15℃;而进一步改进的w(i,p)统计法在当前几种剧烈降温预报中订正效果最优,其集合平均偏差与w(i,p)方案相比减小2. 54℃。     

基于最优概率的中期延伸期过程累计降水量分级订正预报

采用ECMWF集合预报降水量资料和中国降水量观测资料,研发了基于最优概率的过程累计降水量分级订正预报(OPPF)技术,并在遵循总体技术思路的基础上设计出三种不同的OPPF计算方案(OPPF1、OPPF2、OPPF3),继而选用2015—2017年汛期(5—9月)中国91次区域性强降水过程进行回报试验和预报效果对比评估,结果表明:(1)在中期延伸期预报时效(96~360小时),对强降水和有无降水的预报效果,三种OPPF均明显优于集合平均(EMPF)和控制预报(CTPF);对中等以上或较强以上强度降水的预报效果,OPPF1和OPPF3明显优于CTPF、与EMPF基本接近。(2)三种OPPF相比,OPPF3的预报效果较OPPF1总体略胜一筹,两者均好于OPPF2。(3)预报效果存在明显的地域差异,南方地区强降水预报的TS评分明显大于北方地区,且OPPF3预报效果明显优于EMPF;在96~240小时预报时效,东北地区东部OPPF3强降水的预报效果也明显好于EMPF。      

上地幔超高压流体的金刚石压砧实验研究

地球深部流体主要是NaCl-H2O溶液,越到地球深部,它赋存的温度、压力越高,性质状态也不断变化,反之,亦然。当NaCl-H2O流体进入和脱离(上升过程)超临界状态时,其性质会发生截然不同的变化,影响着各种地质过程。使用金刚石压砧在高温高压下原位观测流体的实验,用谱学方法,结合同步辐射光源技术,成为定量化研究地球深部高温超高压流体的有效方法。作者使用同步辐射光源的红外谱研究了10GPa下的NaCl-H2O溶液;在地球化学动力学实验室研究了3GPa,650℃下的NaCl-H2O溶液红外谱,此测量方法可以提供温度压力和体积等数据,能研究其状态。NaCl-H2O溶液红外谱表明水分子主要振动谱受压力和温度影响是不同的。压力增加促使水分子主要振动谱向低波数变化。但是温度增加的效应相反。常温高压下水被压缩,结晶向紧密堆积变化。高温高压下的水有气、液、固和超临界流体各相。水分子间的氢键在近临界态开始减弱,氢键网络被破坏。     

国家数字地震台数据处理研究

为了突显被淹没在噪声背景下的有用信息,对国家数字地震台的数据处理方法进行了研究,并用Matlab程序给出了详细的设计过程。     

Study on applying optimal path to land valuation

Introduction Thebasiclandpriceistheaveragepriceofev eryequalparceloreverylandclassspecifiedby thegovernment,accordingtodifferentuseof landsuchascommerce,industry,residence,etc.Asanimportantroleplayingintheurban landpricesystem,thebasiclandpriceinstructs a…     

Applications of conditional nonlinear optimal perturbation to the study of the stability and sensitivity of the Jovian atmosphere

A two-layer quasi-geostrophic model is used to study the stability and sensitivity of motions on smallscale vortices in Jupiter’s atmosphere. Conditional nonlinear optimal perturbations (CNOPs) and linear singular vectors (LSVs) are both obtained numerically and compared in this paper. The results show that CNOPs can capture the nonlinear characteristics of motions in small-scale vortices in Jupiter’s atmosphere and show great difference from LSVs under the condition that the initial constraint condition is large or the optimization time is not very short or both. Besides, in some basic states, local CNOPs are found. The pattern of LSV is more similar to local CNOP than global CNOP in some cases. The elementary application of the method of CNOP to the Jovian atmosphere helps us to explore the stability of variousscale motions of Jupiter’s atmosphere and to compare the stability of motions in Jupiter’s atmosphere and Earth’s atmosphere further.