气候模式中云的垂直重叠及其辐射传输问题研究进展

概述了全球气候模式中云的垂直重叠的处理方法及其辐射物理过程的最新研究进展。从云垂直重叠模型的构造、模型在气候模式中的实现方式,得到与观测一致的云重叠结构所采用的数据和方法、重叠云的辐射传输等方面,给出了针对这一国际研究难点问题的最新研究进展。关于气候模式中云的垂直重叠问题的研究至今已取得了许多成果,表现在:重叠模型上有了更为科学的描述形式(如指数衰减重叠);重叠云的辐射传输也有了更快速的处理方法(如蒙特卡洛独立柱近似)并被广泛应用;连续的三维云遥感观测(如CloudSat/CALIPSO)和云分辨尺度的三维云模式的发展为在气候模式中精确描述云的垂直结构提供了丰富的观测资料和模式数据。但是,气候模式中现有的云重叠结构处理及其辐射传输方法还远不够完善,仍然存在很多没有解决的问题需要在未来进行探索。     

高性能计算技术在气象领域的应用

高性能计算通过应用超级计算机与并行处理技术解决复杂的计算问题,是信息技术发展比较迅猛的领域之一。气象应用始终是高性能计算的重要领域,高性能计算技术有效地解决了高分辨率、高精度气象数值预报模式发展限制,在气象预报预测业务中发挥着核心支撑作用。数十年以来,由于数值天气模式研究和业务运行对计算资源的强烈需求,国内外气象领域高性能计算机及应用迅速发展起来。气象领域对高性能计算能力及系统的可靠性需求日益提升。高性能计算技术将与气象预报应用日益融合,相互影响促进,不断创新发展。为满足气象预报预测业务和科研工作需求,中国气象部门将进一步提升高性能计算能力,并致力于优化集约高性能计算系统布局,高效管理计算资源,发挥最大效益。     

天山山区水汽和云水含量的空间分布特征

利用欧洲数值预报中心(ECMWF)发布的第一代全球分辨率ERA-Interim再分析数据,分析了1979～2014年天山山区水汽含量和云水含量的空间分布特征。结果显示：(1)水汽含量的高值中心出现在伊犁河谷地区,中心值域在10—11kg m-2之间,低值区位于天山中部的巴音布鲁克附近,中心值域在5—6kg m-2之间;夏季水汽含量最丰富,在8—11kg m-2之间。(2)云液水含量的高值区出现在博格达山北坡,而云冰水含量的高值区在西天山海拔较高的托木尔峰地区,低值区均在伊犁河谷等海拔低的地区;夏季云液水含量、云冰水含量均呈减少趋势,云冰水含量较云液水减少的更为明显,下降速率为0.28kg kg-1/10a;(3)垂直分布上,云液水含量在600hpa左右的高空出现高值区,中心最大值为10kg kg-1;云冰水含量的高值区则出现在500hpa左右的高空,为11kg kg-1;在对流层大气中云冰水含量值远大于云液水,且云冰水发展的高度较云液水更高。     

基于神经网络的页岩微纳米孔隙微结构分析的正则化和最优化方法

页岩气成藏机理与页岩内部孔隙结构紧密相关,对页岩孔隙结构的研究成为页岩气勘探开发技术中至关重要的一环。页岩内部不同结构体组分对X-射线的吸收能谱不一样,这样就导致观测数据是由不同页岩组分衰减不同波段的X-射线构成的。经过对CT图像分割,能够获得页岩微孔结构的图像,尤其是获得有机质中孔隙类别、形状、尺寸、空间分布、连通特性。本文利用同步辐射X射线扫描重构的页岩CT数据,研究并设计基于多能CT图像的神经网络图像分割技术和算法,以期得到页岩体三维结构特征及空间分布,可以为建立有机质种类和无机矿物组成与微纳孔隙特征的联系以及最终实现页岩气的资源储量评估和勘探开发提供技术支持。     

On the linkage between changes in cloud cover and precipitation extremes over Central India

In this study, linkage between changing characteristics of precipitation extremes and cloud covers over Central India is explored during summer monsoon period using Satellite data (1998–2015). This is a first attempt to relate the changes in cloud cover to the changes in precipitation extremes. Non-rainy cirrus clouds are excluded from this study. Results show that heavy rainfall (≥ 60 mm/day) is associated with cold cloud tops (Tb≤220 K) while moderate rainfall (<60 mm/day and ≥20 mm) occurs mostly with middle clouds (Tb>220 K and ≤245 K). Low level clouds (Tb> 245 K) are responsible for light rainfall (<20 mm/day). Increases in top 20%, 10%, 5% and 1% heavy precipitation relate well with the increases in very deep convective, deep convective and convective cloud cover. Among these relations, increase in top 5% heavy precipitation relates best with increase in very deep convective cloud cover. Decrease in bottom 30% low precipitation relates with decrease in low level cloud cover. The results reported in this study fit into the framework of how weather extremes respond to climate change.     

Soft computing approach for real-time estimation of missing wave heights

This paper presents soft computing approach for estimation of missing wave heights at a particular location on a real-time basis using wave heights at other locations. Six such buoy networks are developed in Eastern Gulf of Mexico using soft computing techniques of Artificial Neural Networks (ANN) and Genetic Programming (GP). Wave heights at five stations are used to estimate wave height at the sixth station. Though ANN is now an established tool in time series analysis, use of GP in the field of time series forecasting/analysis particularly in the area of Ocean Engineering is relatively new and needs to be explored further. Both ANN and GP approach perform well in terms of accuracy of estimation as evident from values of various statistical parameters employed. The GP models work better in case of extreme events. Results of both approaches are also compared with the performance of large-scale continuous wave modeling/forecasting system WAVEWATCH III. The models are also applied on real time basis for 3 months in the year 2007. A software is developed using evolved GP codes (C++) as back end with Visual Basic as the Front End tool for real-time application of wave estimation model.     

Parallelization of the flow-path network model using a particle-set strategy

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).     

基于云模型的海岸脆弱性评估 ——以厦门岛为例

脆弱性评估很大程度上存在着模糊性和随机性,为有效解决评估过程中定性概念与评估指标按隶属函数定量描述这一不确定转换问题,本文基于云理论本文选取海岸地貌、海岸高程、海岸坡度、海岸缓冲能力、有效波高、道路价值和建筑价值为指标,构建了厦门岛海岸脆弱性评估指标体系,运用云模型评估手段定量测度了厦门岛海岸脆弱性空间分异特征。评估结果与客观情况比较吻合,检验了指标体系的合理性和评估模型的适用性。本文提出了海岸脆弱性综合评估模型,实用有效,可以推广到与厦门岛类似的区域,为海岸管理及规划提供科学指导。     

结合云计算与大数据的出租房消防安全监管GIS

我国城镇化进程和经济发展效果卓著,但消防建设规划与城市扩张发展之间并不协调。虽然现有研究已经运用GIS技术到消防安全监管当中,但依然存在信息联动性不强,可视化程度低的问题。为此,本文基于地理信息系统技术对城市开发区内地理信息数据、多源多时态遥感及航空影像、巡查数据、出租房数据等进行有效整合完善,以建立时空地理信息大数据。笔者利用虚拟化、云计算等技术建立出租房消防安全动态监管平台。此平台为管理部门提供了基于地理信息的决策支持,提升了出租房管理的高效性和科学性。系统的建成和应用对我国的出租房管理信息化工作的开展具有重要意义。