Performance of Convective Parameterization Schemes in Asia Using RegCM:Simulations in Three Typical Regions for the Period 1998–2002

This study discusses the sensitivity of convective parameterization schemes(CPSs) in the Regional Climate Model(version 4.3)(Reg CM4.3) over East/South Asia. The simulations using different CPSs in Reg CM are compared to discover a suitable scheme for this region, as the performance of different schemes is greatly influenced by region and seasonality. Over Southeast China and the Bay of Bengal, the Grell scheme exhibits the lowest RMSEs of summer precipitation compared to observed data. Moreover, the Emanuel over land and Grell over ocean(ELGO) scheme enhances the simulation, in comparison with any single CPS(Grell/Emanuel) over Western Ghats, Sri Lanka, and Southeast India. Over the Huang–Huai–Hai Plain(3H) and Tibetan Plateau(TP) regions of China, the Tiedtke scheme simulates the more reasonable summer precipitation with high correlation coefficient and comparable amplitude. Especially, it reproduces a minimum convective precipitation bias of 8 mm d-1and the lowest RMSEs throughout the year over East/South Asia. Furthermore, for seasonal variation of precipitation, the Tiedtke scheme results are closer to the observed data over the 3H and TP regions. However, none of the CPSs is able to simulate the seasonal variation over North Pakistan(NP). In comparison with previous research, the results of this study support the Grell scheme over South Asia. However, the Tiedtke scheme shows superiority for the 3H, TP and NP regions. The thicker PBL, less surface latent heat flux, the unique ability of deep convection and the entrainment process in the Tiedtke scheme are responsible for reducing the wet bias.     

Advances in cloud physics and weather modification in China

The capabilities of cloud-resolving numerical models, observational instruments and cloud seeding have improved greatly over recent years in China. The subject of this review focuses on the main progresses made in China in the areas of cloud modeling, field observations, aerosol–cloud interactions, the effects of urbanization on cloud and precipitation, and weather modification.Well-equipped aircraft and ground-based advanced Doppler and polarized radars have been rapidly applied in cloudseeding operations. The combined use of modern techniques such as the Global Positioning System, remote sensing, and Geographical Information Systems has greatly decreased the blindness and uncertainties in weather-modification activities.Weather-modification models based on state-of-the-art cloud-resolving models are operationally run at the National Weather Modification Centre in China for guiding weather-modification programs.Despite important progress having been made, many critical issues or challenges remain to be solved, or require stronger scientific evidence and support, such as the chain of physical events involved in the effects induced by cloud seeding. Current important progresses in measurements and seeding techniques provide the opportunity and possibility to reduce these deficiencies. Long-term scientific projects aimed at reducing these key uncertainties are extremely urgent and important for weather-modification activities in China.     

C波段调频连续波天气雷达探测系统及观测试验

对降水云更高时、空分辨率观测资料的需求推动了天气雷达技术的发展,调频连续波雷达(FMCW)系统采用收发分置双天线体制,采用数字直接移相(DDS)技术和快速傅里叶变换(FFT)信号处理技术,获取高度分辨率达到15、30 m,探测周期2—3 s的回波功率谱分布和谱参数,具有脉冲多普勒雷达无法比拟的探测优势。C波段FMCW(C-FMCW)雷达最小可测信号功率达到-170 dBm,微弱信号的定量标校是技术难点。采用标准信号源输出单频信号,经过数字直接移相扩展为与雷达系统相同扫频范围信号,得到最小输入功率可达-169.77 dBm的定标曲线,由定量标校后的谱分布计算得到回波强度谱密度分布。该雷达于2013年6月起在安徽定远开始观测,利用8月24日降水过程探测数据,与距离该地48 km的蚌埠和83 km的合肥SA扫描雷达观测数据,分别进行对流云与层状云的观测比对分析。对于均匀分布的层状降水云,C-FMCW雷达与SA雷达探测结果基本接近, C-FMCW雷达与蚌埠SA雷达的平均均方根误差为1.75 dB,与合肥SA雷达的平均均方根误差为2.02 dB,C-FMCW雷达与两部SA雷达探测的回波强度差异小于1 dB。对观测试验谱参数及回波强度谱密度分布进行了初步分析,C-FMCW雷达在研究降水云体的相态分区、晴空大气边界层回波等方面有较好的应用前景,有助于加深对强降水云中垂直运动的强烈变化的探测和认识。     

Aerosol-Cloud-Precipitation Interactions in WRF Model: Sensitivity to Autoconversion Parameterization

Cloud-to-rain autoconversion process is an important player in aerosol loading, cloud morphology, and precipitation variations because it can modulate cloud microphysical characteristics depending on the participation of aerosols, and affects the spatio-temporal distribution and total amount of precipitation. By applying the Kessler, the Khairoutdinov-Kogan(KK), and the Dispersion autoconversion parameterization schemes in a set of sensitivity experiments, the indirect effects of aerosols on clouds and precipitation are investigated for a deep convective cloud system in Beijing under various aerosol concentration backgrounds from 50 to 10000 cm-3. Numerical experiments show that aerosol-induced precipitation change is strongly dependent on autoconversion parameterization schemes. For the Kessler scheme, the average cumulative precipitation is enhanced slightly with increasing aerosols, whereas surface precipitation is reduced significantly with increasing aerosols for the KK scheme. Moreover, precipitation varies non-monotonically for the Dispersion scheme, increasing with aerosols at lower concentrations and decreasing at higher concentrations.These different trends of aerosol-induced precipitation change are mainly ascribed to differences in rain water content under these three autoconversion parameterization schemes. Therefore, this study suggests that accurate parameterization of cloud microphysical processes, particularly the cloud-to-rain autoconversion process, is needed for improving the scientific understanding of aerosol-cloud-precipitation interactions.     

A Remote Sensing Model to Estimate Sunshine Duration in the Ningxia Hui Autonomous Region, China

Sunshine duration (SD) is strongly correlated with solar radiation, and is most widely used to estimate the latter. This study builds a remote sensing model on a 100 m × 100 m spatial resolution to est...     

Sensitivity of Precipitation over China to Different Cumulus Parameterization Schemes in RegCM4

The effect of different cumulus parameterization schemes(CPSs) on precipitation over China is investigated by using the International Centre for Theoretical Physics(ICTP) Regional Climate Model version 4.3(Reg CM-4.3) coupled with the land surface model BATS1e(Biosphere-Atmosphere Transfer Scheme version1e). The ERA-interim data are utilized to drive a group of simulations over a 31-yr period from September1982 to December 2012. Two typically sensitive regions, i.e., the eastern Tibetan Plateau(TP; 29°–38°N,90°–100°E) and eastern China(EC; 26°–32°N, 110°–120°E), are focused on. The results show that all the CPSs have well reproduced the spatial distribution of annual precipitation in China. The simulation with the Emanuel scheme shows an overall overestimation of precipitation in China, different from the other three CPSs which only overestimate over northern and northwestern China but underestimate over southern China. Seasonally, the Tiedtke scheme shows the smallest overestimation in winter and summer, and the best simulation of the annual variance of precipitation. Interannual variations of precipitation among the four CPSs are generally simulated better in summer than in winter, and better for entire China than in the subregions of TP and EC. The precipitation trend is simulated better over EC than over TP, and better in summer than in winter. An overestimate(underestimate) of the East Asian summer monsoon index(EASMI) exists in the simulations with the Grell and the Emanuel(the Kuo and the Tiedtke) schemes.The smallest EASMI bias in the Tiedtke simulation could explain its small precipitation bias. A negative correlation between the EASMI and summer precipitation over the middle and lower reaches of Yangtze River is found in the Grell and the Emanuel simulations, but was missed by the simulations using the Kuo and the Tiedtke schemes.     

恐龙谷南缘微地貌地形特征要素提取及分析

地形特征信息是地学研究中的重要依据,用于描述地形变化的总体样貌,决定了基础地形地貌形态特征。本文对禄丰恐龙谷南缘环状微地貌的地形特征进行提取及分析。首先,采用无人机测量技术获取测区影像数据,通过影像数据处理构建测区0.5 m分辨率的DOM数据与点云数据,并基于TerraSolid软件平台搭建滤波规则对点云数据进行分类、抽稀压缩处理,提取测区地面点,以地面点数据为基础数据构建测区2 m分辨率的DEM;然后,通过叠加ArcGIS空间分析中最大值提取与正负地形提取,完成地形特征点的提取分析;并结合ArcGIS中水文分析、平面曲率与坡型组合的方法,完成地形特征线提取分析;最后,在eCognition 9.0中通过面向对象的方法,实现地形面状特征提取。试验结果表明：①提取鞍部点的最佳分析窗口为11×11。②通过鞍部点位及两种方法提取脊—谷线,其中水文分析提取脊线更为细致,整体连贯性更为突出且从山体两侧脊线分布密集,试验区山体崎岖处提取鞍部点,即说明恐龙谷南缘整体受亚热带低纬度高原季风气候影响,山体受一定程度风化侵蚀。③恐龙谷南缘地形面状特征中裸岩、裸地两者面积占比较大,两者相加后占测区总面积64.2%,结合实地干湿分明的气候特点和实际勘察植被相对低矮的特征,在一定程度上说明该区域表层土壤疏松,需注意水土流失引起的生态问题。     

基于云架构的中国地质调查信息网格平台关键技术研究与实现

目前中国地质调查网格结点体系已基本形成,初步实现门户的自治,结点资源与门户资源的共享与协同。随着信息技术的发展,以及云GIS、大数据、北斗等技术在网格平台中的开展、应用,从网格平台基于云架构体系升级入手,阐述了基于云架构非结构化地质数据存储与管理、快速搭建地质调查业务系统中间件和野外地质调查工作管理与安全保障服务等一系列关键技术的研究与实现,为网格平台的下一步发展提供了研究基础。     

夏季念青唐古拉峰地区云结构分析

利用2006—2010年夏季6~8月CloudSat资料对念青唐古拉峰地区云水分布和云类型特征进行分析,从而为研究高原天气过程与其水循环过程的相互作用提供理论依据。结果表明,云水含量垂直分布结构与云类型有关,而冰川区和非冰川区云类型差异主要为降水云类型不同,其中有冰川覆盖的高山上空降水云以深厚对流云为主,无冰川覆盖的高山降水云类型以雨层云为主。念青唐古拉峰南坡冰川区云水平均含量为0.14 g/m3,非冰川区云水平均含量为0.18 g/m3,一定程度说明来自孟加拉湾的水汽在经过冰川附近时,多会产生降水,反映了冰川对水汽传输的阻碍作用。     

基于改进RANSAC算法的复杂建筑物屋顶点云分割

屋顶模型重建影响到建筑物完整模型重建质量,屋顶面点云分割质量对屋顶模型重建具有重要意义。针对传统RANSAC算法在屋顶点云面片分割时易产生错分割、过分割等问题,本文顾及点云位置信息,提出一种对点云重新分配的改进RANSAC点云分割算法。算法暂时剔除非平面内点,选取平面内点集中3个点作为初始样本,平面拟合判定邻域是否有效,从有效邻域中选取标准差值最小的3个点为初始模型。利用RANSAC算法对屋顶点云进行分割。利用K近邻算法统计误分类点与面片的距离降低误分类,优化过分割面片并进行连通性分析,利用距离及法向量一致性检验的方法重分配非平面内点。为验证本文算法有效性,选取芬兰Helsinki地区的3栋相互独立的复杂建筑物屋顶以及上海某小区的6栋建筑物群屋顶作为实验数据。在2组数据中,本文提出的改进RANSAC算法分割屋顶面片的平均准确率分别为92.17%、87.82%,78%的建筑物屋顶不存在过分割。在第2组数据中,所有分割面片上的点与其对应的最佳拟合平面的距离的标准差的平均值为0.030 m。实验结果表明,本文算法分割建筑物屋顶面片的准确率较高,较好的抑制了过分割现象,且抗噪能力强。