太湖蓝藻水华形成的适宜气象指标

根据2005—2017年卫星遥感反演的太湖蓝藻水华信息,利用区域气象观测数据分析各类气象因子对太湖蓝藻深水华形成的影响,结果表明:①在日平均气温为0～35℃区间内会出现蓝藻聚集现象,其中最适宜气温区间为15.1～35℃,该区间内累计出现蓝藻水华的面积占比达90%、出现大面积蓝藻水华占比达93%;②在卫星观测到蓝藻前6h,平均风速为0.2～4.8m/s区间内能观测到蓝藻水华,其中最适宜的平均风速区间为0.5～3.4m/s,该区间内蓝藻水华累计出现次数占比达94.7%,大面积蓝藻水华主要出现在平均风速2.0m/s的情况下,占比89%;③降水总体上呈负效应,但在观测到有大面积蓝藻水华的情况下,前24h有小雨(10mm)的情形与总降水次数之比达88%,说明小雨的适度扰动有利于形成大面积蓝藻水华;④日照充足有利于蓝藻生长,但并非蓝藻水华形成的必要条件。在此基础上建立的多元回归综合气象指数模型,拟合结果较好,通过了0.001的显著性检验。     

内蒙古呼包鄂地区近56年来大气环境容量变化特征分析

为探讨内蒙古呼包鄂地区大气对污染物承载能力的变化,科学评价气候变化对大气环境的影响,利用1961—2016年呼包鄂地区8个国家气象站降水量、风速、云量资料,分析了该地区气象条件的变化特征及大气环境容量的时空分布特征,并对大气环境容量与气象要素之间的相关性进行了分析。结果显示:呼包鄂地区大气环境容量1月的最小、4月的最大,春季的>秋季的>夏季的>冬季的,年平均大气环境容量为62.4 t/d/km^2;月、季、年平均大气环境容量呈波动减小趋势,特别是20世纪70年代末期之后减小趋势更为显著;有明显的空间分布特征,由城区向郊区逐渐增大,城郊差异冬季最为明显,夏季差异最小;大气环境容量与降水相关性差,与风速和日最大混合层高度呈显著的正相关关系,特别是与风速相关性更显著,与小风日数呈显著的负相关关系。     

CAUSAL ANALYSIS AND NUMERICAL MODELING OF THE INSHORE INTENSIFICATION OF SUPER TYPHOON “HATO”

This paper comprehensively analyzes the characteristics and cause of the inshore intensification of super typhoon "Hato", the 13 th super typhoon in 2017. The aspects of typhoon structure, evolution of large-scale circulation and physical quantity field are analyzed using observation data from the Guangdong Automatic Station, Shenzhen Doppler Radar data, NCEP 1°×1° reanalysis data, NCEP 0.25°×0.25° sea surface temperature(SST) data, etc.Additionally, in order to investigate the influence of SST change on the intensity of "Hato", the WRF model and ECMWF 0.125°×0.125° reanalysis data are combined to conduct 3 sensitivity tests on"Hato". The results show that the favorable conditions for inshore intensification of "Hato"included the strengthening and westward extension of the subtropical high, continuous increase of low level moisture transport, an anomalous warm SST area north of 20°N in the South China Sea, an extreme divergence value in the northern South China Sea exceeding 6 ×10-5 s-1, and vertical environmental wind shear between 1.1 m/s-4.8 m/s. The intensity of"Hato"was very sensitive to changes in SST. When the SST rose or dropped by 2℃, the minimum central pressure of the typhoon changed by about 13 hPa or 11 hPa,respectively. SST indirectly influenced the intensity of the typhoon through affecting latent heat transport and sensible heat transport.     

NUMERICAL PREDICTION OF AN EXTREME RAINSTORM OVER THE PEARL RIVER DELTA REGION ON 7 MAY 2017 BASED ON WRF-ENKF

An ensemble Kalman filter based on the Weather Research and Forecasting Model (WRF-EnKF) is used to explore the effectiveness of the assimilation of surface observation data in an extreme local rainstorm over the Pearl River Delta region on 7 May 2017. Before the occurrence of rainstorm, the signals of weather forecasts in this case are too weak to be predicted by numerical weather model, but the surface temperature over the urban area are high. The results of this study show that the wind field, temperature, and water vapor are obviously adjusted by assimilating surface data of 10-m wind, 2-m temperature, and 2-m water vapor mixing ratio at 2300 BST 6 May, especially below the height of 2 km. The southerly wind over the Pearl River Delta region is enhanced, and the convergence of wind over the northern Guangzhou city is also enhanced. Additionally, temperature, water vapor mixing ratio and pseudoequivalent potential temperature are obviously increased over the urban region, providing favorable conditions for the occurrence of heavy precipitation. After assimilation, the predictions of 12-h rainfall amount, temperature, and relative humidity are significantly improved, and the rainfall intensity and distribution in this case can be successfully reproduced. Moreover, sensitivity tests suggest that the assimilation of 2-m temperature is the key to predict this extreme rainfall and just assimilating data of surface wind or water vapor is not workable, implying that urban heat island effect may be an important factor in this extreme rainstorm.     

冬季北半球风暴轴的多尺度能量变化特征及其可能机制

基于1971—2016年NCEP/NCAR(美国环境预报中心和国家大气研究中心)的逐日再分析资料及NCPC(美国国家海洋和大气管理局气候预报中心)的海温、大气环流及海洋指数等资料通过多尺度能量分析(MS-EVA)等方法,把冬季北半球风暴轴看做一整体,分析了风暴轴区域多尺度的能量变化特征及其可能机制。主要结论概括如下:(1)多年气候平均状态下,风暴轴的动能来源主要表现为在风暴轴中上游先由低频尺度向天气尺度输送有效位能,随后在风暴轴主体区再由天气尺度有效位能转换为天气尺度动能,其中风暴轴西端可直接由低频尺度向天气尺度输送动能。(2)北半球三大风暴轴联合EOF结果表明:第一模态下,主要体现了北西伯利亚风暴轴与北太平洋风暴轴强度的减弱(增强),同时伴随着北大西洋风暴轴位置北抬(南压);第二模态下,主要体现了北西伯利亚风暴轴强度减弱(增强),同时北太平洋风暴轴位置北抬(南压)中东部强度增强(减弱),而北大西洋风暴轴位置南压(北抬)。(3)回归分析表明:北半球风暴轴异常在不同模态下与低频尺度环流联系密切。低频尺度波动可通过海温及西风急流等异常变化先影响风暴轴区域多尺度间的能量转换,进而影响风暴轴整体的异常变化。     

Main Detrainment Height of Deep Convection Systems over the Tibetan Plateau and Its Southern Slope

Deep convection systems (DCSs) can rapidly lift water vapor and other pollutants from the lower troposphere to the upper troposphere and lower stratosphere. The main detrainment height determines the level to which the air parcel is lifted. We analyzed the main detrainment height over the Tibetan Plateau and its southern slope based on the CloudSat Cloud Profiling Radar 2B_GEOPROF dataset and the Aura Microwave Limb Sounder Level 2 cloud ice product onboard the A-train constellation of Earth-observing satellites. It was found that the DCSs over the Tibetan Plateau and its southern slope have a higher main detrainment height (about 10?16 km) than other regions in the same latitude. The mean main detrainment heights are 12.9 and 13.3 km over the Tibetan Plateau and its southern slope, respectively. The cloud ice water path decreases by 16.8% after excluding the influences of DCSs, and the height with the maximum increase in cloud ice water content is located at 178 hPa (about 13 km). The main detrainment height and outflow horizontal range are higher and larger over the central and eastern Tibetan Plateau, the west of the southern slope, and the southeastern edge of the Tibetan Plateau than that over the northwestern Tibetan Plateau. The main detrainment height and outflow horizontal range are lower and broader at nighttime than during daytime.     

利用FY-2F快速扫描资料分析对流初生阶段的云顶物理量特征

基于FY-2F静止气象卫星提供的2015年5—9月的高分辨率数据,通过温度阈值法识别出深、浅对流后,分析和比较了深、浅对流在对流初生(convective initiation,CI)至发展阶段中云顶高度、云顶快速降温率(cloud top cooling rate,CTC)以及多通道差值等云顶物理量特征的变化异同。结果表明:深、浅对流在CI阶段的云顶物理量特征具有相似变化特征,即云顶高度均在短时间内快速上升,CTC值均先减小后增大;深、浅对流差异表现为深(浅)对流云顶上升高度能(不能)超越水汽层高度;深对流CTC最低值较浅对流CTC最低值更低。基于CI阶段深、浅对流的CTC最低值的差异,通过个例验证,表明利用深、浅对流CTC最低值的差异,可以在识别出CI的基础,判断出CI是否发展成为深对流,从而能提前做出预警。     

具有随机扰动和混合时滞的两层异质网络的同步研究

在现实生活中,很多复杂的系统不是由单个网络来表示,而是由一组相互依赖的网络系统来表示的.本文研究了具有随机扰动和混合时滞的两层异质网络的对应节点的同步控制问题.基于随机微分时滞方程的LaSalle不变原理和Lyapunov稳定性理论,采用牵制控制方法,对部分节点实施控制,给出了实现同步的充分条件.为了降低反馈控制的增益,结合自适应控制的方法,进一步弱化了两层异质网络实现同步的条件.最后,通过数值仿真,验证了理论结果的有效性.     

基于机器学习的重庆长江航道雾图像特征识别研究

基于重庆市境内长江航道雷达站拍摄的雾天气过程影像资料,利用K最近邻、支持向量机、BP神经网络、随机森林等机器学习算法,对无雾和5类有雾天气个例进行图像识别训练,构建雾图像识别模型,并检验了识别准确率。结果表明：机器学习能够有效识别雾图像,随机森林算法的识别效果优于其余3种算法。对于能见度超过1500 m的无雾天气,模型的识别准确率为100%,对于能见度在1000—1500 m范围内的轻雾、能见度低于50 m的强浓雾,模型的识别准确率在90%以上,对于能见度在50—1000 m范围内的雾、大雾和浓雾,识别准确率超过70%。     

青藏高原东部新生代钾质碱性系列岩石地球化学特征:岩石成因及其地质意义

青藏高原东部新生代钾质碱性系列的岩石,包括深成岩、火山岩和煌斑岩,在时空上具有一致性,岩石化学成分均富碱、高钾、K2O/Na2O比值远大于1,高度富集Sr、Ba等大离子亲石元素(LILE)和轻稀土元素(LREE),亏损Nb、Ta等高场强元素(HFSE),及物质来源于富集地幔源区的Sr、Nd、Pb同位素组成等,均显示钾质碱性系列的岩石特有的特征,其形成与印度和欧亚两大陆碰撞,导致青藏高原北、东部在40Ma左右出现的大型走滑拉分带,致使地壳变薄以及地幔上拱的构造背景有关。