Long-Lived Microbursts in the Decimetric Wavelength Range and Their Connection with Noise Storms

In the present work a statistical analysis of long-lived microbursts (MBs) in the decimetric wavelength range was performed for the first time. Long-lived microbursts at decimetric wavelengths were observed with one-dimensional scans on the RATAN-600 radio telescope in intensity and circular polarization with a sensitivity of about 5 – 10 Jy. MBs have fluxes in the range of 0.001 – 0.1 s.f.u. and polarization degrees of 10 – 100%, and the duration of individual bursts is about 1 – 2 s. Microbursts and background sources exist for several days and appear at the sites of prolonged energy release. In this work MBs were compared with noise storms (NSs) in the metric wavelength range. Our analysis shows with high confidence that MBs are manifestation of NSs in the decimetric wavelength range. The reason for the significant difference in flux between MBs and NSs could be because MBs (unlike NSs) are related to incoherent generation of Langmuir waves. The nature of the MB emission is similar to the smoothly varying (background) emission of the NSs, butthe MB emission is impulsive because of the high rate of pitch-angle diffusion.     

塔西北下寒武统风暴活动特征及其沉积学响应

在塔西北阿克苏露头区发育多套类型不同的下寒武统肖尔布拉克组风暴岩,它们宏观上与微生物丘混生或共生,微观上可见不同类型的微生物结构,但与此相关的研究甚少。以露头观察和室内鉴定为基础,在苏盖特布拉克地区和昆盖阔坦地区划分出4类8种各具特色的微生物丘—风暴岩沉积序列,并归纳总结了塔西北地区下寒武统肖尔布拉克组风暴沉积模式,认为其发育位置和沉积特征主要受控于“三面”,包括平均海平面(MSL)、正常浪基面(FWB)和风暴浪基面(SWB);“四期”,包括平静期、高峰期、衰减期与停息期;“五流态”,包括风暴涡流、风暴下部回流(包括风暴碎屑流和风暴浊流)沉积与风暴上部回流(包括风暴漫流和风暴潮流)。另外古风暴中心的发育位置也可影响风暴沉积特征。最后在前人研究的基础上,对“贫乏骨骼的风暴海”的形成条件进行探讨。     

一个适用于我国北方的沙尘暴天气数值预测系统及其应用试验

将澳大利亚新南威尔士大学(UNSW)邵亚平发展的具有清晰风蚀物理学概念的起沙数值模式、输送模式与PSU/NCAR的中尺度气象预报模式MM5进行耦合,以高精度中国区域的GIS(Geographic Information System)数据为基础,建立了一个较完整的沙尘暴起沙和输送过程的预测系统.该预测系统可以预测地面起沙率和大气中沙尘浓度.在此基础上,采用该系统对2002年3～4月3次影响我国北方大部分地区的沙尘(暴)天气的起沙和输送过程进行了模拟试验.试验结果表明模拟的沙尘浓度与地面天气现象及卫星云图的沙尘天气范围比较一致,预测系统对沙尘天气的起沙和输送过程有较好的模拟能力.北方上述大范围沙尘天气的沙尘源地为蒙古国的南戈壁省、东戈壁省,内蒙古中西部,河北省北部,山西省东北部,甘肃和青海北部等地区.起沙中贡献最大的粒子粒径为2～11μm和11～22 μm,能够长时间、长距离输送的沙尘也是上述大小的粒子,沙尘粒子的垂直输送高度一般在500 hPa以下.     

Multi-step ahead short-term predictions of storm surge level using CNN and LSTM network

Storm surges pose significant danger and havoc to the coastal residents' safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4％–6％. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10％ at all forecasting steps.     

Tracking historical storm records from high-barrier lagoon deposits on the southeastern coast of Hainan Island,China

The relationship between storm activity and global warming remains uncertain. To better understand storm–climate relationships, coastal lagoon deposits are increasingly being investigated because they could provide high-resolution storm records long enough to cover past climate changes. However, site-specific sediment dynamics and high barriers may bias storm reconstructions. Here, we aimed to investigate these factors through the reconstruction of five distinct storm records (XCL-01, XC-03, XC-06, XC-07, XC-08) from different water depths in a lagoon with a high barrier (i.e., Xincun Lagoon of Hainan Island). Sediment cores were characterized using high-resolution grain size and XRF measurements, to identify storm events. These data were coupled with a numerical simulation to obtain bed shear stress data with high-spatial resolution to better understand storm-induced sediment transport mechanisms. 210Pb dating and Pb pollution chronostratigraphic markers indicated that the chronology of the storm deposit sequences of the cores span the period between 117 a and 348 a. The grain size and XRF results indicated numerous, highly variable and short-duration fluctuations, suggesting that storm-induced coarse-grained sediments were deposited at these core sites. The inconsistent storm events recorded in these cores suggest that these sites have different preservation potentials for storm deposits. However, the consistence between storm sediment records and historical documents for Core XCL-01 indicates that high-barrier lagoons could provide long-term storm event records with high preservation potential.     

台风“利奇马”对渤海风暴潮影响研究

利用实测资料对比和FVCOM数值模拟等方法,研究了"利奇马"台风风暴潮在渤海的演变规律。研究表明:渤海沿岸的风暴潮过程是由局地风"直接作用"及外部天气系统"间接影响"共同作用引起的,且它们引起的风暴潮时空分布明显不同。在"利奇马"台风风暴潮中,"直接作用"引起的风暴增水在渤海湾和莱州湾沿岸分别约占总风暴增水的2/3和1/2。     

The effect of storm movement on infiltration,runoff and soil erosion in a semi-arid catchment

Rainfall characteristics are key factors influencing infiltration and runoff generation in catchment hydrology, particularly for arid and semiarid catchments. Although the effect of storm movement on rainfall-runoff processes has been evaluated and emphasized since the 1960s, the effect on the infiltration process has barely been considered. In this study, a physically based distributed hydrological model (InHM) was applied to a typical semi-arid catchment (Shejiagou, 4.26 km²) located in the Loess Plateau, China, to investigate the effect of storm movement on infiltration, runoff and soil erosion at the catchment scale. Simulations of 84 scenarios of storm movement were conducted, including storms moving across the catchment in both the upstream and downstream directions along the main channel, while in each direction considering four storm moving speeds, three rainfall depths and two storm ranges. The simulation results showed that, on both the hillslopes facing downstream (facing south) and in the main channel, the duration of the overland flow process under the upstream-moving storms was longer than that under the downstream-moving storms. Thus, the duration and volume of infiltration under upstream-moving storms were larger in these areas. For the Shejiagou catchment, as there are more hillslopes facing downstream, more infiltration occurred under the upstream-moving storms than the downstream-moving storms. Therefore, downstream-moving storms generated up to 69% larger total runoff and up to 351% more soil loss in the catchment than upstream-moving storms. The difference in infiltration between the storms moving upstream and downstream decreased as the storm moving speed increased. The relative difference in total runoff and sediment yield between the storms moving upstream and downstream decreased with increasing rainfall depth and storm speed. The results of this study revealed that the infiltration differences under moving storms largely influenced the total runoff and sediment yield at the catchment scale, which is of importance in runoff prediction and flood management. The infiltration differences may be a potential factor leading to different groundwater, vegetation cover and ecology conditions for the different sides of the hillslopes.     

An ensemble approach for the analysis of extreme rainfall under climate change in Naples (Italy)

In the present paper, an ensemble approach is proposed to estimate possible modifications caused by climate changes in the extreme precipitation regime, with the rain gauge Napoli Servizio Idrografico (Naples, Italy) chosen as test case. The proposed research, focused on the analysis of extremes on the basis of climate model simulations and rainfall observations, is structured in several consecutive steps. In the first step, all the dynamically downscaled EURO‐CORDEX simulations at about 12 km horizontal resolution are collected for the current period 1971–2000 and the future period 2071–2100, for the RCP4.5 and the RCP8.5 concentration scenarios. In the second step, the significance of climate change effects on extreme precipitation is statistically tested by comparing current and future simulated data and bias‐correction is performed by means of a novel approach based on a combination of simple delta change and quantile delta mapping, in compliance with the storm index method. In the third step, two different ensemble models are proposed, accounting for the variabilities given by the use of different climate models and for their hindcast performances. Finally, the ensemble models are used to build novel intensity–duration–frequency curves, and their effects on the early warning system thresholds for the area of interest are evaluated.     

台风风暴潮情景构建与时空推演

因台风风暴潮的突发性、情景演变时间的连续性和路径的不确定性,导致应急决策者在应急救援中难以做出正确决策,针对这一现状,将“情景—应对”应用在台风风暴潮应急决策中。本文在分析台风风暴潮情景、情景要素的概念模型基础上,首先通过资料搜集、属性识别等方法提取关键情景要素,采用框架表示法构建情景;然后分析台风风暴潮情景演变规律及演变路径;其次通过动态贝叶斯网络法构建台风风暴潮动态情景网络;最后利用先验概率与条件概率计算情景状态概率,实现了台风风暴潮的关键情景推演。本文以2018年9月16日11时至17时山竹台风对广东省沿海城市影响为例,演示了台风风暴潮的情景推演流程及关键技术。实证分析结果表明,溃堤、海水倒灌、洪水、滑坡发生的概率分别为85%、81%、74%、54%,验证了情景推演在风暴潮中应用的合理性。     

The Characteristics of Storm Wave Behavior and Its Effect on Cage Culture Using the ADCIRC+SWAN Model in Houshui Bay,China

The current storm wave hazard assessment tends to rely on a statistical method using wave models and fewer historical data which do not consider the effects of tidal and storm surge.In this paper,the wave-current coupled model ADCIRC+SWAN was used to hindcast storm events in the last 30 years.We simulated storm wave on the basis of a large set of historical storms in the North-West Pacific Basin between 1985 and 2015 in Houshui Bay using the wave-current coupled model ADCIRC+SWAN to obtain the storm wave level maps.The results were used for the statistical analysis of the maximum significant wave heights in Houshui Bay and the behavior of wave associated with storm track.Comparisons made between observations and simulated results during typhoon Rammasun(2014)indicate agreement.In addition,results demonstrate that significant wave height in Houshui Bay is dominated by the storm wind velocity and the storm track.Two groups of synthetic storm tracks were designed to further investigate the worst case of typhoon scenarios.The storm wave analysis method developed for the Houshui Bay is significant in assisting government's decision-making in rational planning of deep sea net-cage culture.The method can be applied to other bays in the Hainan Island as well.