Improving Satellite-Retrieved Cloud Base Height with Ground-Based Cloud Radar Measurements

Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.

Airborne Measurements of the Impact of Ground-based Glaciogenic Cloud Seeding on Orographic Precipitation

Data from in situ probes and a vertically-pointing ram-wave Doppler radar aboard a research aircraft are used to study the cloud microphysical effect of glaciogenic seeding of cold-season orographic clouds. A previous study （Geerts et al., 2010） has shown that radar reflectivity tends to be higher during seeding periods in a shallow layer above the ground downwind of ground-based silver iodide （AgI） nuclei generators. This finding is based on seven flights, conducted over a mountain in Wyoming （the Unites States）, each with a no-seeding period followed by a seeding period. In order to assess this impact, geographically fixed flight tracks were flown over a target mountain, both upwind and downwind of the AgI generators. This paper examines data from the same flights for further evidence of the cloud seeding impact. Com- posite radar data show that the low-level reflectivity increase is best defined upwind of the mountain crest and downwind of the point where the cloud base intersects the terrain. The main argument that this increase can be attributed to AgI seeding is that it is confined to a shallow layer near the ground where the flow is turbulent. Yet during two flights when clouds were cumuliform and coherent updrafts to flight level were recorded by the radar, the seeding impact was evident in the flight-level updrafts （about 610 m above the mountain peak） as a significant increase in the ice crystal appears short-lived as it is not apparent just downwind of concentration in all size bins. The seeding effect the crest.

Macro-and Micro-physical Characteristics of Different Parts of Mixed Convective-stratiform Clouds and Differences in Their Responses to Seeding

This study investigates the cloud macro-and micro-physical characteristics in the convective and stratiform regions and their different responses to the seeding for mixed convective-stratiform clouds that occurred in Shandong province on 21 May 2018,based on the observations from the aircraft,the Suomi National Polar-Orbiting Partnership(NPP)satellite,and the high-resolution Himawari-8(H8)satellite.The aircraft observations show that convection was deeper and radar echoes were significantly enhanced with higher tops in response to seeding in the convective region.This is linked with the conversion of supercooled liquid droplets to ice crystals with released latent heat,resulting in strengthened updrafts,enhanced radar echoes,higher cloud tops,and more and larger precipitation particles.In contrast,in the stratiform cloud region,after the Silver Iodide(AgI)seeding,the radar echoes become significantly weaker at heights close to the seeding layer,with the echo tops lowered by 1.4–1.7 km.In addition,a hollow structure appears at the height of 6.2–7.8 km with a depth of about 1.6 km and a diameter of about 5.5 km,and features such as icing seeding tracks appear.These suggest that the transformation between droplets and ice particles was accelerated by the seeding in the stratiform part.The NPP and H8 satellites also show that convective activity was stronger in the convective region after seeding;while in the stratiform region,a cloud seeding track with a width of 1–3 km appears 10 km downstream of the seeding layer 15 minutes after the AgI seeding,which moves along the wind direction as width increases.

Preliminary Results of the Ground-Based Orographic Snow Enhancement Experiment for the Easterly Cold Fog (Cloud) at Daegwallyeong during the 2006 Winter

The snow enhancement experiments, carried out by injecting AgI and water vapor into orographically enhanced clouds （fog）, have been conducted to confirm Li and Pitter＇s forced condensation process in a natural situation. Nine ground-based experiments have been conducted at Daegwallyeong in the Taebaek Mountains for the easterly foggy days from January-February 2006. We then obtained the optimized conditions for the Daegwallyeong region as follows： the small seeding rate （1.04 g min-1） of AgI for the easterly cold fog with the high humidity of Gangneung. Additional experiments are needed to statistically estimate the snowfall increment caused by the small AgI seeding into the orographical fog （cloud） over the Taeback Mountains.

Idealized numerical simulation experiment of ice seeding in convective clouds using a bin microphysics scheme

A 2D axisymmetric bin model is used to conduct idealized numerical experiments of cloud seeding.The simulations are performed for two clouds that differ in their initial wind shear.Results show that,although cloud seeding with an ice concentration of 1000 Lin a regime that has relatively high supercooled liquid water can obtain a positive effect,the rainfall enhancement seems more pronounced when the cloud develops in a wind shear environment.In no-shear environment,the change in the microphysical thermodynamic field after seeding shows that,although more graupel is produced via riming and this can increase the surface rainfall intensity,the larger drag force and cooling of melting graupel is unfavorable for the development of cloud.On the contrary,when the cloud develops in a wind shear environment,since the main downdraft is behind the direction of movement of the cloud,its negative effect on precipitation is much weaker.

Artificial Seeding Effects of Convective Clouds on the Opening Day of Beijing 2008 Summer Olympics

Using the radar reflectivity and intensive rainfall data, artificial seeding effects of convective clouds in Beijing on 8 August 2008, the opening day of the 29th Summer Olympics, were analyzed. The results indicate that, cloud seeding at single operation site for convective clouds invading from southwest direction may sharply mitigate the rainfall observed at leeward automatic weather stations within 5 - 10 min, while enhances the precipitation at a later stage about 10 - 20 min. Cloud seeding effects of operation sites Yuegezhuangxi, Changgouzhen, and Zhoukou, which are placed along the main moving routes or localized developing convective clouds in the west and center parts of Fangshan district, are very conspicuous. Combining the operation sites distribution and radar echoes, it is found that the site Changgouzhen, which is very close to the convective core, plays an essential role in suppressing the growth of convective cloud, reducing the coverage area of intense echoes classified as 45 - 60 dBZ, as well as mitigating the precipitation from neighboring automatic weather stations. Based on radar reflectivity and rainfall data, we find that the clouds over lots of operation sites in eastern Fangshan district are not cold enough to favor glaciogenic seeding with silver iodide, meanwhile, there is not too much precipitation observed.

Evaluation of cloud seeding project in Yazd Province of Iran using historical regression method(case study:Yazd 1 cloud seeding project,1999)

In this research, the result of the cloud seeding over Yazd province during three months of February, March and April in 1999 has been evaluated using the historical regression method. Hereupon, the rain-gages in Yazd province as the target stations and the rain-gages of the neighboring provinces as the control stations have been selected. The rainfall averages for the three aforementioned months through 25 years (1973-1997) in all control and target stations have been calculated. In the next step, the correlations between the rainfalls of control and target stations have been estimated about 75%, which indicates a good consistency in order to use the historical regression. Then, through the obtained liner correlation equation between the control and target stations the precipitation amount for February, March and April in 1999, over the target region (Yazd province) was estimated about 27.57 mm, whiles the observed amount was 34.23 mm. In fact the precipitation increasing around 19.5% over Yazd province confirmed the success of this cloud seeding project.

Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.

Study of the Influence of Critical Radius on the Cloud Drops Formation in the Seeding Operations

In the seeding operations in order to mitigate the climatic changes or to intervene beneficently on the precipitations process, it is very important to know the roll of the critical radius size of the cloud drops formation and its posterior evolution. In the seeding operations programs, the fundament is to determinate the critical radius in order to obtain efficient results. So, it must consider （a） the critical radius size necessary in order to get the better results; （b） the atmospheric conditions that determine it. In order to get a methodology to calculate the critical radius in each atmospheric condition, the present work has been developed. And with them, it can estimate the nuclei size necessary in order to assure good seeding. The authors had obtained approximate values that were good enough to the goals.

Cloud seeding

Cloud seeding is a method of artificially causing clouds to produce precipitation (降水) in the form of rain or snow.Cloud seeding has also been used in attempts to modify the severity of hail slorms and hurricanes.The effectiveness of cloud seeding remains controversial,but it continues to be used in some regions to try lo

Numerical Simulation of Seeding Extra-Area Effects of Precipitation Using a Three-Dimensional Mesoscale Model

The Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) has been used to investigate the extra-area effects of silver iodide (AgI) seeding on stratiform clouds performed at the supercooled layer.A bulk two-moment microphysical scheme and the new software package for silver iodide are incorporated in MM5.Extra conservation equations are applied to trace the seeding agent,which is transported along the flow field and interacts with the supercooled cloud fields.In this study,the model was run using three nested grids,with 3.3 km × 3.3 km horizontal resolution in the finest grid.The model results showed that seeding with AgI at the 5 to 15℃ levels had microphysical effects on the simulated clouds and that the simulation produced a longer-lasting seeding effect because of the transport of the seeding agent by upper-level winds.Most of the AgI particles acted as deposition nuclei,and the deposition nucleation process contributed mostly to additional cloud ice formation in this study.The results showed that more precipitation results from seeded than unseeded case,and the precipitation was redistributed downwind of the target.Augmented precipitation (varying from 5% to 25% downwind) was confined in space to within 250 km of the seeding target and in time to the 3-h period after initial seeding.

Cloud Seedability Study with a Dual-Model System

In this research, one-dimensional stratiform a novel dual-model system, cold cloud model （1DSC） coupled to Weather Research and Forecast （WRF） model （WRF-1DSC for short）, was employed to investigate the effects of cloud seeding by silver iodide （AgI） on rain enhancement. Driven by changing environmental conditions extracted from the WRF model, WRF-1DSC could be used to assess the cloud seeding effects quantitatively. The employment of WRF- 1DSC, in place of a one-dimen- sional two-moment cloud seeding model applied to a three-dimensional mesoscale cloud-resolving model, was found to result in massive reduction of computational resources. Numerical experiments with WRF-1DSC were conducted for a real stratiform precipitation event ob- served on 4-5 July 2004, in Northeast China. A good agreement between the observed and modeled cloud system ensured the ability of WRF-1DSC to simulate the observed precipitation process efficiently. Sensitivity tests were performed with different seeding times, locations, and amounts. Experimental results showed that the optimum seeding effect （defined as the percentage of rain enhancement or rain enhancement rate） could be achieved through proper seeding at locations of maximum cloud water content when the updraft was strong. The optimum seeding effect was found to increase by 5.61% when the cloud was seeded at 5.5 km above ground level around 2300 UTC 4 July 2004, with the maximum AgI mixing ratio （As） equaling 15 ng kg-1. On the other hand, for an overseeded cloud, a significant reduction occurred in the accumulated precipitation （-12.42%） as Xs reached 100 ng kg^-1. This study demonstrates the potential of WRF- 1DSC in determining the optimal AgI seeding strategy in practical operations of precipitation enhancement.

祁连山无人机增雨(雪)作业积冰条件分析及防除冰技术路线

无人机作为新型人工增雨(雪)作业技术手段,研究其防冰和除冰对业务化具有重要意义。基于飞行积冰报告及外场探测资料、探空及再分析资料,对祁连山地区大型无人机积冰分布气象条件进行统计分析,结合电加热法防除冰试验,形成适用于祁连山地区的无人机防除冰技术路线。研究表明,大型无人机开展人工增雨(雪)作业的强烈积冰区为-8~-2℃,且当云粒子浓度大于0.93 cm^(-3)、云水含量大于0.0043 g·m^(-3)时更容易出现积冰。祁连山地区春、秋、冬三季容易出现积冰的高度在4000—5500 m,夏季在5000—5500 m,积冰中心高度在5000 m上下。搭载电加热防除冰系统可有效解决大型无人机的积冰问题。

ESTIMATION OF ARTIFICIAL PRECIPITATION ENHANCEMENT RESOURCE CONDITION AND CLOUD SEEDING POTENTIAL BY GROUND-BASED REMOTE SENSING DATA

In this paper,the data of continuous atmospheric vertical integral vapour and liquid water content during April-June of 1992-1994 obtained by a ground-based dual-channel microwave radiometer are used to analyse the statistical characteristics of atmospheric vapour and liquid water content,and the relative distribution characteristics of vapour and liquid water content in cloudy atmosphere,the correlative relation of integral liquid water content L and ground precipitation intensity I.and precipitation transform rate of precipitation system.Finally,the weather modification condition of precipitus stratiform clouds and seeding potential is analyzed and discussed.

基于集合预报的浙江省积层混合云人工增雨数值模拟研究

目前人工增雨催化数值模拟研究较少考虑环境场误差对模拟效果的影响,结论往往具有很大的不确定性。有鉴于此,本文将初始场扰动集合预报技术与包含催化模块的柱状云模式进行单向耦合(One Way Coupling),利用中尺度模式所提供包含环境场扰动误差的多组热力、微物理量廓线实时驱动柱状云模式,对2022年1月23日浙江省积层混合云降水过程进行多成员、单/多格点AgI催化数值试验,尝试从概率的角度探讨最佳播撒方案以及对应的增雨潜力。从单站(杭州站)的模拟效果来看,23日15:00(协调世界时)在3.6 km高度(−5.2℃)处使用AgI(碘化银催化剂量为1.2×10^(−7)~1.2×10^(−4)g kg^(−1))播撒时所有集合成员均能够取得正增雨效果,其中采用1.2×10^(−5)g kg^(−1)剂量时增雨率最大,所有成员的均值为4.67%,99%分位数为7.77%。在单点模拟中,初始场扰动对于过量播撒是否导致减雨的判断有很大影响,例如,播撒剂量增加至1.2×10^(−2)g kg^(−1)后,超过50%的集合成员表现为减雨效果,但仍然有部分成员表现为增雨。针对这次过程,多格点催化试验表明增雨效果发生概率最优的区域位于浙西北和浙北北部区域,尤其在嘉兴东北部和临安附近,从概率预报的角度来说也往往对应着相对较高的平均过冷水含量和较低的冰晶数浓度均值。

基于激光三维重建的种薯芽眼识别方法研究

种薯芽眼的准确识别是实现智能切块的重要前提。为解决种薯芽眼机器视觉识别易出现误判和不易获取芽眼三维位置信息而导致切块不均匀的问题,提出一种基于激光三维重建的种薯芽眼识别方法。确定点云获取过程中ROI区域消除采集过程中背景的影响,通过工业相机与线激光器相配合连续采集移动种薯的激光光条图像获取其点云数据;根据点云密度去除随机噪声和裙边噪声,提高点云质量,降低芽眼误判率。采用体素滤波算法稀疏点云,提高识别效率;通过对种薯表面任意点的局部邻域进行平面拟合后获取点云法向量,构建加权协方差矩阵参数化种薯表面点云,根据矩阵特征值大小设定的动态阈值对种薯表面点云进行初步筛选,得到种薯芽眼判别的候选点,采用欧式聚类算法获取候选点的点云簇,选取每个点云簇中最大特征值点为关键点,利用计算关键点和邻域内其他点构成的中心线连线向量与法向量夹角余弦值对关键点再次筛选,最终确定种薯各个芽眼位置。试验结果表明,芽眼识别率为95.13%,芽眼误识别率为4.87%,可为马铃薯种薯智能化切块时芽眼识别提供参考。

一种改进的机载LiDAR数据构建DEM地面种子点选取方法

针对机载激光雷达(LiDAR)数据使用传统方法获取的地面种子点密度低,种子点之间空白区域的地形信息缺失,不利于后续提取地面点和构建高质量数字高程模型(DEM)的问题,本文提出了一种基于新的网格遍历规则的地面种子点选取方法。与传统方法中的起始网格在X和Y方向上每次移动1个规则网格宽度不同,该方法每次移动1/2个网格宽度,增加规则网格数量,获取的地面种子点个数相较于传统方法提高约200%,可补充种子点之间空白区域的地形信息,有利于提高后续点云数据处理的精度和相关产品的可靠性。

基于手持式扫描仪的种子几何参数高通量测量

在数字化考种、表型组学及数字农业仿真等前沿研究中,精确且丰富的种子几何参数至关重要。为实现种子几何参数的高通量测量,该研究提出了一种基于手持式扫描仪的种子几何参数自动测量方法,主要包括:1)针对批量扫描中数据缺失问题,提出了一种基于椭圆拟合和平滑插值的点云补全算法;2)为实现样本自动筛选,提出了一种基于主成分分析的统计模型典型的样本筛选方法。试验覆盖8类形态各异的植物种子(3400个样本)。结果表明,点云补全平均误差低至0.017 mm,显著提升了数据的完整性;样本筛选平均误差0.80%,确保了样本的代表性和准确性;几何参数平均测量误差0.41%,实现了种子几何参数的批量、自动和高精度测量。该研究为智慧农业领域基础研究提供了一种高效的基础数据测量方法。

环境湿度影响人工催化消减雨效果的数值模拟研究

利用耦合了碘化银催化过程的WRF(Weather Research and Forecast)模式,对2014年8月16日南京青奥会开幕式当天实施的人工催化作业开展数值模拟,评估催化效果并通过敏感性数值试验调查低空环境干层对催化效果的影响。结果表明,催化作业产生了减雨效果,低空干区的存在是影响催化效果的关键。当低空存在深厚的相对湿度很小的干层时,催化导致减雨效果;当增加低层的相对湿度即弱化低空干层,催化减雨效果减弱甚至出现增雨效果。催化增强了雪的形成过程但减弱了雪的增长过程尤其是凝华增长,导致雪粒子浓度增加但粒径减小,融化产生更多的小雨滴增强了蒸发过程,最终导致地面降水减少。

无人播种平台的设计与分析

为解决传统农业种植过程中人力资源短缺和效率低下的问题,该文针对无人播种平台开展设计与分析,该平台由一个自动驾驶的播种机器人和一个云端控制系统组成,可以通过预先设定的种植方案进行自动化播种。在设计过程中,需要考虑机器人的导航和避障能力、种子的储存和投放方式,以及云端控制系统的实现,可以显著提高种植效率、降低成本和人力资源需求。然而,也需要克服一些问题与挑战,如机器人的可靠性和稳定性、不同农作物的种植要求等。最后系统分析无人播种平台的应用效益。研究结果旨在为现代化农业进程提供新的发展思路与研究方案。