南极中山站全天信息采集系统     

王宇  辛玉新  姜鹏  杨勇  伦宝利  王传军  余晓光  常亮  范玉峰 《天文研究与技术》2021,(2):272-282

南极高原拥有独特的天文观测优势,为了对南极中山站夜天文观测条件进行实测研究,中国科学院云南天文台专门研制了一套具有耐低温、自动除雪除霜等适应南极气候特征的全自动全天信息采集系统,该系统可以提供实时的全天云量、天光背景和全天图像,并将信息推送到网页实时显示。介绍了系统的研制及为适应南极气候进行的耐低温实验,统计分析了中山站2016~2017年的全天信息数据,结果显示,中山站2016和2017年的可观测时间为772.21 h和437.38 h,可观测夜数为93 d和51 d,天光背景最大真实值为22.05 Mag/arcsec 2,年平均气温为-10.6℃,最高气温19.1℃,最低气温为-44℃,2016年平均相对湿度为55.2%。  相似文献   

基于云模型的海岸脆弱性评估 ——以厦门岛为例     

朱正涛  蔡锋  曹超  陈沈良 《海洋通报》2019,38(4):462-471

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。  相似文献   

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

《Dynamics of Atmospheres and Oceans》2019

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.  相似文献   

毫米波雷达云回波的自动分类技术研究   总被引：1，自引：0，他引：1       下载免费PDF全文

杨晓  黄兴友  杨军  李培仁  李盈盈  杨敏  刘燕斐  张帅  闫文辉 《气象学报》2019,77(3):541-551

毫米波雷达在云探测方面比厘米波天气雷达和激光雷达具有显著优势,可获得更多的云粒子信息,是研究云特性的主要遥感探测设备。为了开展对毫米波雷达探测的云回波进行自动分类的研究,利用161次云回波的个例数据,统计得到了卷云、高层云、高积云、层云、层积云和积云6类云型的特征量和其他参量的数值范围,利用分级的多参数阈值判别方法,达到了自动分类的目标,通过与人工分类的初步验证,两种分类结果的一致性达到84%,其中,层云和积云的识别一致较低的原因在于样本数据有限,仅有6次层云和8次积云的个例样本数据。通过更多样本的处理,提取的特征参量更可靠,自动分类的准确率会得到提高,以便将基于毫米波雷达的云分类技术应用于将来的云观测自动化业务。   相似文献   

基于双多普勒雷达及闪电资料分析一次强降水过程     

杨丽丽  杨毅  张廷龙  王莹 《高原气象》2015,34(2):546-555

为进一步了解多普勒雷达及闪电资料在中小尺度天气系统方面的应用以及降水系统动力结构的研究,利用合肥和阜阳两部S波段多普勒雷达资料,通过两步变分反演法反演双雷达,并采用模糊逻辑算法进行云类型识别,再结合垂直累计液态水含量VIL、降水和闪电分布特征,分析了2010年6月7-10日发生在安徽合肥和阜阳的一次持续性强降水过程。结果表明:此次持续性强降水过程与风场的低层辐合和高层辐散、风场的气旋性旋转以及水平风切变相关;此次降水过程是以层状云降水为主的积云混合云降水;另外,以降水为主的层状云,其闪电频数低且以负闪为主,闪电之后20 min左右出现强降水;此次暴雨的VIL值不是很大,强降水区对应的VIL值基本3 kg·m-2;云识别结果、降水区、VIL值与雷达回波强度之间的对应关系较好。  相似文献   

2008年1月贵州冻雨的数值模拟和层结结构分析   总被引：2，自引：0，他引：2  

张昕  高守亭  王瑾 《高原气象》2015,34(2):368-377

针对2008年初发生在贵州地区的严重冻雨过程,分别从环流背景、低空急流和水汽输送条件等方面分析了准静止锋维持的原因,并选取本次灾害最严重的第3次过程为典型个例,利用WRF模式针对准静止锋影响下的贵州冻雨进行数值模拟来研究冻雨的发生机制。模拟结果较好地反映出高低空环流形势场特征,强雨雪降水带的走向、落区,以及地面温度的分布,均与观测基本吻合。通过分析高分辨率模式的模拟结果,揭示了准静止锋上贵州地区冻雨的层结结构特征及云物质在冻雨区的分布特征。研究结果表明,贵州中部的冻雨区除一般的三层结构(包含冰晶层、暖层和冷层)外,还具有典型的两层结构特征,即:高空的固体降水粒子稀少,900~600 h Pa深厚的逆温层和0℃以上的暖层使中低空存在大量液态粒子,下落的液滴经过近地面的浅薄冷层,形成大量过冷却雨滴,而后降落至地面迅速冻结。  相似文献   

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery     

Myung-Sook Park  Chang-Hoi Ho  Heeje Cho  Yong-Sang Choi 《大气科学进展》2015,32(3):375-388

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.  相似文献   

模糊因子分析在地下水污染评估中的应用——以河南省洛阳市为例   总被引：3，自引：0，他引：3  

马荣  石建省 《地球学报》2011,32(5):611-622

传统的多元统计法难以定量化表征不同污染源对单个样本点的影响,本文引入了一种新的方法——模糊因子分析法.将该方法应用于洛阳市地下水污染来源解析研究,通过模糊聚类和因子分析对研究区样品进行分类,探明主要的污染源类型及其对整个研究区和单个样品点的污染贡献率.计算结果表明:洛阳市浅层地下水主要有以下四个污染源:基岩风化、加工制...  相似文献   

南京市紫外线辐射强度的变化及影响因子   总被引：1，自引：0，他引：1  

毛宇清  沈澄  姜爱军  严文莲  叶香 《气象科学》2011,31(5):621-625

利用南京市2005-02—2009-01共4 a的紫外线辐射观测资料,分析了到达地面的紫外线辐射强度的变化特征,并探讨了云、污染物浓度和雾、霾天气等对紫外线辐射强度的影响。结果表明,低云量对紫外线强度的衰减更明显,最大达58.15%,蔽光性云层对紫外线辐射强度的衰减可达71%～80%;紫外线辐射强度与污染物浓度呈负相关,其中与NO2的相关性最好,为-0.39;晴空条件下,严重霾对紫外线辐射强度的衰减率可达20%以上,浓雾对紫外线辐射强度的衰减接近50%。  相似文献   

Improving the assessment of ICESat water altimetry accuracy accounting for autocorrelation     

Hani Abdallah  Jean-Stéphane Bailly  Nicolas Baghdadi  Nicolas Lemarquand 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):833-844

Given that water resources are scarce and are strained by competing demands, it has become crucial to develop and improve techniques to observe the temporal and spatial variations in the inland water volume. Due to the lack of data and the heterogeneity of water level stations, remote sensing, and especially altimetry from space, appear as complementary techniques for water level monitoring. In addition to spatial resolution and sampling rates in space or time, one of the most relevant criteria for satellite altimetry on inland water is the accuracy of the elevation data. Here, the accuracy of ICESat LIDAR altimetry product is assessed over the Great Lakes in North America. The accuracy assessment method used in this paper emphasizes on autocorrelation in high temporal frequency ICESat measurements. It also considers uncertainties resulting from both in situ lake level reference data. A probabilistic upscaling process was developed. This process is based on several successive ICESat shots averaged in a spatial transect accounting for autocorrelation between successive shots. The method also applies pre-processing of the ICESat data with saturation correction of ICESat waveforms, spatial filtering to avoid measurement disturbance from the land–water transition effects on waveform saturation and data selection to avoid trends in water elevations across space. Initially this paper analyzes 237 collected ICESat transects, consistent with the available hydrometric ground stations for four of the Great Lakes. By adapting a geostatistical framework, a high frequency autocorrelation between successive shot elevation values was observed and then modeled for 45% of the 237 transects. The modeled autocorrelation was therefore used to estimate water elevations at the transect scale and the resulting uncertainty for the 117 transects without trend. This uncertainty was 8 times greater than the usual computed uncertainty, when no temporal correlation is taken into account. This temporal correlation, corresponding to approximately 11 consecutive ICESat shots, could be linked to low transmitted ICESat GLAS energy and to poor weather conditions. Assuming Gaussian uncertainties for both reference data and ICESat data upscaled at the transect scale, we derived GLAS deviations statistics by averaging the results at station and lake scales. An overall bias of −4.6 cm (underestimation) and an overall standard deviation of 11.6 cm were computed for all lakes. Results demonstrated the relevance of taking autocorrelation into account in satellite data uncertainty assesment.  相似文献