基于审查回归模型的公众气象服务支付意愿影响因素分析——以无锡、武汉和西安为例

采用审查回归模型,分别选取了中国东、中、西部的三个典型城市无锡、武汉和西安,计算了三城市受访者的支付意愿值,并对其影响因素进行了分析。结果表明：（1）支付意愿值与地区经济发展水平直接相关。无锡、武汉和西安受访者的支付意愿分别为21.68,17.15和10.07元/年;（2）年龄越长者,由于其天气知识更丰富、日常消费较节俭,对气象服务的支付意愿越低;（3）文化程度越高者,更能理解和支持气象服务事业,对气象服务的支付意愿越高;（4）月收入变量对气象服务的支付意愿有显著影响,但就不同城市的受访者而言,影响的方向并不一致。     

Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration (PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year^?1, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1–16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by ?10.2 to ?2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed.     

机载多光谱LiDAR的随机森林地物分类

机载多光谱LiDAR技术利用激光进行探测和测距,不仅可以快速获取地面物体的三维坐标,还可以获得多个波段的地物光谱信息,可广泛用于地形测绘、土地覆盖分类、环境建模、森林资源调查等。本文提出了多光谱LiDAR的随机森林地物分类方法。该方法通过对LiDAR强度数据和高程数据提取分类特征,完成多光谱LiDAR的随机森林地物分类;并分析随机森林的特征贡献度特性,采用后向特征选择方法实现分类特征选择。通过对加拿大Optech Titan多光谱LiDAR数据的试验表明：随机森林方法可以获得较好的地物分类精度,而且可以适当地去除部分冗余和相关的特征,从而有效提高分类精度。     

Determination of kolmogorov entropy of chaotic attractor included in one—dimensional time series of meteorological data

The 1970-1985 day to day averaged pressure dataset of Shanghai and the extension method in phase space are used to calculate the correlation dimension D and the second-order Renyi entropy K2 of the approximation of Kolmogorov’s entropy, the fractional dimension D = 7.7~7.9 and the positive value K2 ≈ 0.1 are obtained. This shows that the attractor for the short-term weather evolution in the monsoon region of China exhibits a chaotic mo-tion. The estimate of K2 yields a predictable time scale of about ten days. This result is in agreement with that ob-tained earlier by the dynamic-statistical approach.The effects of the lag time τ on the estimate of D and K2 are investigated. The results show that D and K2 are convergent with respect to τ. The day to day averaged pressure series used in this paper are treated for the extensive phase space with τ = 5, the coordinate components are independent of each other; therefore, the dynamical character quantities of the system are stable and reliable.     

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. To eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments of the surface. Instead of developing independent ML-based algorithms, we add surface variables in a binary way that enhances the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by ~5%, while at the same time, reducing misjudgment by ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels. Overall, our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations. We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.     

中国避暑型气候的地域类型及其时空分布特征

由于中国各地纬度、地形及海陆位置的地域差异,形成了多种多样的避暑型气候。本文采用1993-2012年756个国家基本站和122个辐射站逐日气象数据,基于通用热气候指数(UTCI)模型计算各气象站点的人体感知温度,结合聚类分析方法对避暑型气候的地域类型进行了研究,并对其空间分布、时间变化和舒适特征进行了分析。结果表明：中国避暑型气候主要包括西南高原型、中东部山岳型、东北山地平原型、西北山地高原型和环渤海低山丘陵型5种地域类型;各类避暑型气候具有显著的地域特色：西南高原型避暑气候纬度低、海拔高,太阳辐射较强;中东部山岳型避暑气候地势高、风速大,夏季舒适偏冷;环渤海低山丘陵型避暑气候地势低、湿度大,夏季舒适偏热且舒适度受海风影响明显;西北山地高原型避暑气候温度适宜、天气晴朗,但略显干燥;东北山地平原型避暑气候凉爽、风速不大、辐射不强、湿度适中,综合条件相对优越。从各类避暑型气候夏季人体感知温度的变化来看,环渤海低山丘陵型舒适期较短,其余类型舒适期相对较长,东北山地平原型和西北山地高原型人体感知温度曲线呈良好的单峰对称变化,其余类型大致呈单峰不对称形态。本文不仅丰富了避暑型气候研究的理论成果,而且也可为避暑型旅游资源的开发与规划提供科学依据,进一步指导人们的避暑旅游活动。     

东海陆扰海域铜、铅、锌、镉重金属排海通量及海洋环境容量估算

汇总并分析了20世纪80年代初以来东海陆扰海域重金属排海通量年变化规律及主要来源,应用多介质海洋环境中重金属迁移-转化模型,估算了东海陆扰海域重金属海洋环境容量。20世纪80年代初以来,东海陆扰海域铜、铅、锌、镉排海总量整体上呈不对称的倒"U"形变化趋势,基本符合"环境库兹涅茨曲线",20世纪90年代达到最大值,当前排海总量仍高于20世纪80年代初期的水平。东海陆扰海域铜、铅、锌、镉污染物主要来源于以河流为主的陆源排放,其中88.0%左右来源于河流排放,7.5%左右来源于排污口,只有4.5%左右来源于大气沉降。长江流域排海通量占东海陆扰海域排海总量的比例最大,平均为92.4%左右,钱塘江流域平均只有3.9%左右,闽江流域平均只有3.7%左右。东海陆扰海域铜、铅、锌、镉污染物海洋环境容量分别约为17.0,4.7,113.1,0.71 kt/a。当前铅、锌、镉污染物排海总量没有超过东海陆扰海域海洋环境容量,但铜的排海总量超过其海洋环境容量大约8%。     

The assimilation of spectral sensing and the WOFOST model for the dynamic simulation of cadmium accumulation in rice tissues

The accurate detection of heavy metal-induced stress on crop growth is important for food security and agricultural, ecological and environmental protection. Spectral sensing offers an efficient and undamaged observation tool to monitor soil and vegetation contamination. This study proposed a methodology for dynamically estimating the total cadmium (Cd) accumulation in rice tissues by assimilating spectral information into WOFOST (World Food Study) model. Based on the differences among ground hyperspectral data of rice in three experiments fields under different Cd concentration levels, the spectral indices MCARI1, NREP and RH were selected to reflect the rice stress condition and dry matter production of rice. With assimilating these sensitive spectral indices into the WOFOST + PROSPECT + SAIL model to optimize the Cd pollution stress factor f_wi, the dynamic dry matter production processes of rice were adjusted. Based on the relation between dry matter production and Cd accumulation, we dynamically simulating the Cd accumulation in rice tissues. The results showed that the method performed well in dynamically estimating the total amount of Cd accumulation in rice tissues with R² over 85%. This study suggests that the proposed method of integrating the spectral information and the crop growth model could successfully dynamically simulate the Cd accumulation in rice tissues.     

Interannual and Decadal Variations of Surface Solar Radiation over East China in the First Half of the 20th Century

Variability and long-term trends of sunshine duration(SSD) and total cloud cover(TCC) were studied based on surface observations from 10 meteorological stations over East China in the first half of the 20 th century. The correlation coefficients between SSD and diurnal temperature range(DTR), as well as TCC, were analyzed. SSD experienced a significant increasing trend(0.16 h d-1 per decade) from 1908 to 1936, and the maximum brightening was in autumn(0.33 h d-1 per decade). The good agreement between the variability of SSD and DTR, supported by the correlation coefficient between them of 0.72, implies that the SSD measurements were reliable. TCC showed a decreasing trend(-0.93% per decade) and was significantly inversely related to SSD(-0.74), indicating the variation of SSD was attributable to changes in cloud cover. The result was obviously different to that since the 1960 s, when clouds could not account for the decadal trend of surface solar radiation in China.     

基于云依赖背景场误差协方差的雷达资料同化及对降雨预报影响研究

传统变分同化方法中使用各向同性和均质的背景场误差协方差,忽略了背景场误差协方差的天气系统依赖性,而在变分框架下引入集合流依赖的背景场误差协方差还需要额外的集合预报。为在变分同化中引入更合理的背景场误差协方差,通过引入云指数构建“云依赖”背景场误差协方差,提出了一种云依赖背景场误差协方差的同化方案,并应用于雷达等多源观测资料同化。基于云依赖背景场误差协方差的资料同化方案,开展了一系列单点观测试验、梅雨期批量循环同化预报试验以及降雨个例详细诊断分析。从单点观测试验看,云依赖背景场误差协方差可以实时动态地调整各格点背景场误差,使分析增量具有明显的各向异性和对云雨特征的依赖;批量循环同化与预报试验表明采用云依赖背景场误差协方差的雷达资料同化可以稳定提高降水预报能力,对大量级降水评分的改善尤为明显;对强对流暴雨过程的诊断进一步表明,云依赖背景场误差协方差的应用改进了动力、热力、水汽和水凝物场的预报。基于云依赖背景场误差协方差的同化方案,能在变分同化框架下引入更符合实时天气特征的背景场误差协方差信息,为更好地同化高分辨率雷达资料提供了基础,有效提高了降雨预报的效果。