天津雾和霾自动观测与人工观测的对比评估

为适应地面气象观测业务调整方向,提高新型自动气象站观测资料的质量及可用性,研究中对天津地区10个地面气象站1951—2014年历年2月人工观测及2014年2月自动观测和人工观测的轻雾、雾、霾现象进行对比评估。结果表明:天津地区历年2月轻雾的平均日数为10 d,雾和霾均为2 d,轻雾和霾同期出现的日数占有天气现象的7.4%,而雾和霾同期出现日数仅占0.7%;平行观测期的对比分析得到人工观测轻雾日数比自动观测多11 d,雾日数和霾日数均比自动观测少6 d,其中,轻雾和雾的判别差异集中出现在每日08:00(北京时,下同),霾则基本出现在每日08:00,14:00,17:00,20:00;通过对比自动观测和人工观测的能见度数据发现,二者相对偏差达25.1%,能见度小于15.0 km时,自动观测的能见度有60%~76%数值偏小,特别是08:00和20:00, 因此,在相对湿度满足条件的情况下,能见度的判别误差是导致自动观测与人工观测轻雾、雾、霾现象判别差异的重要原因。     

江苏省能见度的人工与自动观测差异分析

对江苏省2011年全年逐时能见度的自动、人工观测数据进行了统计分析,结果表明:二者具有相当一致的统计特征,全省总相关系数0.73,一致率95.03%;但亦存在一定差异,整体上人工较自动观测数据偏大数公里,偏大程度在17%~55%,且空间差异显著;对不同条件下能见度的对比分析显示,自动与人工观测在低能见度条件下最为接近,且二者差异存在着明显的日变化特征;对能见度自动与人工观测偏差长序列的初步分析,显示统计订正是可能的,但对于不同级别的能见度,自动观测相对与人工有不同的倾向。     

ENSO预测的目标观测敏感区在热带太平洋海温的多模式集合预报中的应用

本文将ENSO预测的目标观测敏感区与多模式集合预报方法相结合, 提出了一种能够有效提高预报技巧且又具有较小计算成本的多模式集合预报方法。该方法在目标观测敏感区内采用模式不等权的多模式超级集合预报方法(SUP), 而在其他区域采用相对简单的等权的多模式消除偏差集合平均方法(BREM)。利用CMIP5中15个气候系统模式的工业革命前参照试验(pi-Control)数据, 针对热带太平洋海温的长期演变开展了理想预报试验。将新集合预报方法与现有的多模式集合预报方法进行了比较。结果表明, 在所考察的预报期内(即1～20年), 新集合预报方法与整个热带太平洋区域使用SUP方法具有相当的预报技巧, 但前者的计算成本明显小于后者, 计算时间仅为后者的1/4。可见, 新方法是一个具有较高预报技巧且计算成本较小的多模式集合预报方法。同时, 其较高的预报技巧强调了热带太平洋SST预测对ENSO目标观测敏感区内的模式误差也是极端敏感的, 也正因如此, 多模式集合预报方法才能够有效过滤模式误差的影响, 具有较高的预报技巧。     

NVST多通道成像观测系统的数据同步采集

为了在1 m红外太阳望远镜多通道高分辨率成像观测系统中实现多个波段太阳图像的同步高分辨率统计重建,需要1 m太阳望远镜多个观测通道图像采集系统同步。研究了如何采用CCD相机外触发工作模式、计算机PCI总线硬件中断技术和全球定位系统时间相结合实现1 m太阳望远镜多个观测通道图像的同步采集,并在现有的Hα和Ti O两个成像观测通道上搭建实验平台。通过一系列的波形时序测试,数据记录和分析等实验证明本文所采用的这一数据同步采集技术能满足1 m太阳望远镜多个观测通道图像的同步采集要求。     

Photometry and the determination of oscillation modes for high amplitude Delta Scuti (HADS) variable GSC 1566-2802

CCD photometry observation of a newly discovered, high amplitude Delta Scuti star GSC 1566-2802, with a visible filter, is presented. The observations were carried out at Alborz Observatory located in Mahdasht, Karaj, Iran.The main goal of this project was to update our knowledge of the periodic variations of the target star. This paper covers three analyses, first calculating a new ephemeris and plotting a new light curve based on 19 times of maxima; then a Fourier analysis of the observed data points which results in determining probable oscillation modes, as well as computing its physical parameters which guide us to its harmonics and pulsation modes.     

现行业务湿度传感器测量不确定度研究

依据JJF1059.1-2012《测量不确定度评定与表示》,针对自动气象站各要素传感器的测量误差会随时间、温度等环境因素的变化而发生漂移。为确保观测数据的准确、可靠,以CP340恒温恒湿箱为湿度发生环境、采用英国michell公司的Optidew Vision精密露点仪为标准器,介绍了利用HMP155A温湿度传感器进行湿度测量不确定度评定的一般方法和详细步骤。最后给出一个评定实例,在温度为22℃和40℃,相对湿度为30%RH~75%RH时,通过对测量不确定度的各分量进行分析和计算,得到HMP155A温湿度传感器测量结果的扩展不确定度分别为1.50%和1.46%。     

Remote sensing for mapping natural habitats and their conservation status – New opportunities and challenges

Safeguarding the diversity of natural and semi-natural habitats in Europe is one of the aims set out by the Habitats Directive (Council Directive 92/43/EEC on the conservation of natural habitats and of wild fauna and flora) and one of the targets of the European 2020 Biodiversity Strategy, and is to be accomplished by maintaining a favourable conservation status. To reach this aim a high-level understanding of the distribution and conditions of these habitats is needed. Remote sensing can considerably contribute to habitat mapping and their observation over time. Several European projects and a large number of scientific studies have addressed the issue of mapping and monitoring natural habitats via remote sensing and the deriving of indicators on their conservation status. The multitude of utilized remote sensing sensors and applied methods used in these studies, however, impede a common understanding of what is achievable with current state-of-the-art technologies. The aim of this paper is to provide a synthesis on what is currently feasible in terms of detection and monitoring of natural and semi-natural habitats with remote sensing. To focus this endeavour, we concentrate on those studies aimed at direct mapping of individual habitat types or discriminating between different types of habitats occurring in relatively large, spatially contiguous units. By this we uncover the potential of remote sensing to better understand the distribution of habitats and the assessment of their conservation status in Europe.     

Impact of the spatial resolution of climatic data and soil physical properties on regional corn yield predictions using the STICS crop model

The assimilation of Earth observation (EO) data into crop models has proven to be an efficient way to improve yield prediction at a regional scale by estimating key unknown crop management practices. However, the efficiency of prediction depends on the uncertainty associated with the data provided to crop models, particularly climatic data and soil physical properties. In this study, the performance of the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model for predicting corn yield after assimilation of leaf area index derived from EO data was evaluated under different scenarios. The scenarios were designed to examine the impact of using fine-resolution soil physical properties, as well as the impact of using climatic data from either one or four weather stations across the region of interest. The results indicate that when only one weather station was used, the average annual yield by producer was predicted well (absolute error <5%), but the spatial variability lacked accuracy (root mean square error = 1.3 t ha⁻¹). The model root mean square error for yield prediction was highly correlated with the distance between the weather stations and the fields, for distances smaller than 10 km, and reached 0.5 t ha⁻¹ for a 5-km distance when fine-resolution soil properties were used. When four weather stations were used, no significant improvement in model performance was observed. This was because of a marginal decrease (30%) in the average distance between fields and weather stations (from 10 to 7 km). However, the yield predictions were improved by approximately 15% with fine-resolution soil properties regardless of the number of weather stations used. The impact of the uncertainty associated with the EO-derived soil textures and the impact of alterations in rainfall distribution were also evaluated. A variation of about 10% in any of the soil physical textures resulted in a change in dry yield of 0.4 t ha⁻¹. Changes in rainfall distribution between two abundant rainfalls during the growing season led to a significant change in yield (0.5 t ha⁻¹ on average). Our results highlight the importance of using fine-resolution gridded daily precipitation data to capture spatial variations of rainfall as well as using fine-resolution soil properties instead of coarse-resolution soil properties from the Canadian soil dataset, especially for regions with high pedodiversity.     

三频BDS电离层延迟改正分析

针对电离层改正会引起观测噪声放大,尤其三频二阶改正致使观测噪声被过分放大的不足,该文分别推导了BDS电离层双频一阶改正、三频一阶改正和三频二阶改正模型及三频载波无电离层组合模型。改正电离层延迟的同时会不同程度地放大观测噪声,为此分析比较了各种方法改正后的观测值精度和观测噪声,并对不同方法的应用进行了分析。     

北斗三频数据线性组合优化分析

随着GPS现代化的实施和欧洲Galileo计划的实行,多频数据组合逐渐成为卫星导航定位的发展方向。针对关于北斗导航定位系统多频数据组合的研究较少这一现状,该文首先简要介绍了北斗导航定位系统,并在分析BDS三频数据线性组合的数学模型和确保模糊度参数整数特性的基础之上,给出了BDS三频数据线性组合的优化选取标准;然后从消除或减弱电离层延迟、对流层延迟和观测噪声三个方面系统地分析了BDS三频数据线性组合系数的优化选取问题;最后通过MATLAB模拟,给出了一些典型的组合,分析了它们可能的应用。