Machine Learning Analysis of Impact of Western US Fires on Central US Hailstorms

Fires,including wildfires,harm air quality and essential public services like transportation,communication,and utilities.These fires can also influence atmospheric conditions,including temperature and aerosols,potentially affecting severe convective storms.Here,we investigate the remote impacts of fires in the western United States(WUS)on the occurrence of large hail(size:≥2.54 cm)in the central US(CUS)over the 20-year period of 2001–20 using the machine learning(ML),Random Forest(RF),and Extreme Gradient Boosting(XGB)methods.The developed RF and XGB models demonstrate high accuracy(>90%)and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide,particularly in four states(Wyoming,South Dakota,Nebraska,and Kansas).The key contributing variables identified from both ML models include the meteorological variables in the fire region(temperature and moisture),the westerly wind over the plume transport path,and the fire features(i.e.,the maximum fire power and burned area).The results confirm a linkage between WUS fires and severe weather in the CUS,corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.

Numerical Study on a Severe Downburst-Producing Thunderstorm on 23 August 2001 in Beijing

A thunderstorm that produced severe wind, heavy rain and hail on 23 August 2001 in Beijing was studied by a three-dimensional cloud model including hail-bin microphysics. This model can provide important information for hail size at the surface, which is not available in hail parameterization cloud models. The results shows that the cloud model, using hail-bin microphysics, could reasonably reflect the storm＇s characteristics such as life cycle, rainfall distribution and the diameter of the hailstones and also can reproduce developing processes of downbursts, where they can then be compared with the observed features of the storm. The downburst formation mechanism was investigated based on the cloud microphysics of the simulated storm and it was found that the downburst was primarily produced by hail-loading and enhanced by cooling processes that were due to hail melting and rain evaporation. The loading and melting of hail played crucial roles in the formation of downbursts within the storm.

Analysis of the severe group dust storms in eastern part of Northwest China

Based on the available original dust storm records from 60 meteorological stations, we discussed the identification standard of severe dust storms at a single station and constructed a quite complete time series of severe group dust storms in the eastern part of Northwest China in 1954–2001. The result shows that there were 99 severe group dust storms in this region in recent 48 years. The spatial distribution indicates that the Alax Plateau, most parts of the Ordos Plateau and most parts of the Hexi Corridor are the main areas influenced by severe group dust storms. In addition, the season and the month with the most frequent severe group dust storms are spring and April, accounting for 78.8% and 41.4% of the total events respectively. During the past 48 years the lowest rate of severe group dust storms occurred in the 1990s. Compared with the other 4 decades, on the average, the duration and the affected area of severe group dust storms are relatively short and small during the 1990s. In 2000 and 2001, there were separately 4 severe group dust storms as the higher value after 1983 in the eastern part of Northwest China.

ANALYSIS OF A TORNADO-LIKE SEVERE STORM IN THE OUTER REGION OF THE 2007 SUPER TYPHOON SEPAT

When super typhoon Sepat came close to the Fujian coastline on the night of 18 August 2007 (coded as 0709 in Chinese convention), an associated tornado-like severe storm developed at 2307–2320 Beijing Standard Time in Longgang, Cangnan County, Wenzhou Prefecture, Zhejiang Province approximately 300 km away in the forward direction of the typhoon. The storm caused heavy losses in lives and property. Studying the background of the formation of the storm, this paper identifies some of its typical characteristics after analyzing its retrieval of Doppler radar data, vertical wind shear and so on. Synoptic conditions, such as unstable weather processes and TBB, are also studied.

A Linear Diagnostic Equation for the Nonhydrostatic Vertical Motion W in Severe Storms

A linear diagnostic equation for the nonhydrostatic vertical motion W in severe storms is derived in the Cartesian-earth-spherical coordinates. This W diagnostic equation reveals explicitly how forcing factors work together to exert influence on the nonhydrostatic vertical motion in severe storms. If high-resolution global data are available in Cartesian coordinates with guaranteed quality, the Lax-Crank-Nicolson scheme and the Thomas algorithm might provide a promising numerical solution of this diagnostic equation. As a result, quantitative analyses are expected for the evolution mechanisms of severe storms.

Impacts of Two Ice Parameterization Schemes on the Cloud Microphysical Processes and Precipitation of a Severe Storm in Northern China

A severe storm that occurred over Beijing in northern China on 23 June 2011 was simulated with two different ice crystal parameterization schemes(the DeMott scheme and Meyers scheme) by using the Regional Atmospheric Modeling System. Compared with the DeMott scheme, the simulation results with the Meyers scheme have the following characteristics:(1) Updrafts are stronger and more numerous;(2) The cloud is better organized and contains a greater peak of ice-phase hydrometeor mixing ratios;(3) Cloud water and hail mixing ratios increase while graupel mixing ratios decrease;(4) The surface precipitation is initially greater. However, at the end of the simulation, less precipitation is produced. In short, the differences between the two schemes are not obvious, but the De Mott scheme has a relatively more reasonable result.

Extremes of Severe Storm Environments under a Changing Climate

One of the more critical issues in a changing climate is the behavior of extreme weather events, such as severe tornadic storms as seen recently in Moore and El Reno, Oklahoma. It is generally thought that such events would increase under a changing climate. How to evaluate this extreme behavior is a topic currently under much debate and investigation. One approach is to look at the behavior of large scale indicators of severe weather. The use of the generalized extreme value distribution for annual maxima is explored for a combination product of convective available potential energy and wind shear. Results from this initial study show successful modeling and high quantile prediction using extreme value methods. Predicted large scale values are consistent across different extreme value modeling frameworks, and a general increase over time in predicted values is indicated. A case study utilizing this methodology considers the large scale atmospheric indicators for the region of Moore, Oklahoma for Class EF5 tornadoes on May 3, 1999 and more recently on May 20, 2013, and for the class EF5 storm in El Reno, Oklahoma on May 31, 2013.

2000—2022年严重影响珠江口的台风暴潮增水规律分析

台风暴潮严重影响社会经济发展,近年来在珠江口呈愈发严重的趋势。结合珠江口风暴潮特点定义了严重影响的风暴潮等级,筛选2000—2022年严重影响珠江口的热带气旋,对时空分布、路径、结构、极端风暴潮等特性进行分析,结果表明:①严重影响珠江口的台风暴潮每年发生0~2次,7—9月尤其是8、9月为珠江口防台关键期;②珠江口风暴潮遭遇天文潮概率具有一定随机性;③西北或西北偏西方向路径行进,珠江口以西、尤其是珠海至茂名一带登陆、登陆时中心风力达12级或以上的台风最易给珠江口带来严重风暴潮;④珠江口以西登陆的12级或以上的台风,登陆点距珠江口近的,即使风圈结构较小,也易导致严重风暴潮,但登陆点距离更远的,若风圈很大,同样会导致严重风暴潮;⑤珠江口极端风暴潮强度呈增强趋势,台风结构和路径特点存在一些共性和差异,其风暴潮增水过程特点其结构路径变化特点相一致,上游来水、天文潮状态和遭遇降雨情况均会影响风暴潮上溯过程。研究成果可为珠江口未来的风暴潮预报及防御工作提供借鉴。

急性重症感染后炎症细胞因子风暴下心肌状态及超声心动图心脏检测的价值

目的探讨急性重症感染后炎症细胞因子风暴下的心肌状态及超声心动图心脏检测的价值。方法选取2020年1月—2023年2月在海南西部中心医院就诊的急性重症感染患者110例,其中,合并细胞因子风暴患者45例(观察组),无细胞因子风暴患者65例(对照组)。比较两组患者的临床资料、心肌损伤标志物、心电图、超声心动图参数等差异。结果观察组患者年龄高于对照组(P<0.05);观察组乳酸脱氢酶、肌酸激酶、肌酸激酶同工酶、肌钙蛋白T、肌钙蛋白I和N-末端B型脑钠肽原高于对照组(P<0.05);观察组白细胞计数和中性粒细胞计数高于对照组(P<0.05),而血小板计数和红细胞计数低于对照组(P<0.05);观察组心房颤动、室性期前收缩、房性期前收缩和异常Q波占比高于对照组(P<0.05);观察组左心室舒张末期内径、左心室收缩末期内径、左心室舒张末期容积、左心室收缩末期容积、E峰、三尖瓣反流压差和肺动脉收缩压高于对照组(P<0.05),而左室射血分数和A峰低于对照组(P<0.05)。结论急性重症感染后炎症细胞因子风暴下患者心肌损伤明显,超声心动图可直观检测心脏情况。

Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric state.Ensemble-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state variables.Because the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions.In cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors.The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance.Just how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model variables.Horizontal correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 km.The horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 km.The results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of BTs.They also provide insights on the most efficient and effective use of the different water vapor channels.

ANALYSIS OF CAUSATION OF ASYMMETRIC PRECIPITATION ASSOCIATED WITH SEVERE TYPHOON DAMREY

Severe typhoon Damrey moved across Hainan Island from 00:00 UTC 25 September to 00:00 UTC 27 September in 2005 and gave rise to a significant rain process during its 48-h passage.The precipitation intensity on the southern part of the island is stronger than that on the northern,showing obvious asymmetric distribution.Using Tropical Rainfall Measuring Mission(TRMM) data,the associated mesoscale characteristics of the precipitation were analyzed and the formation of asymmetric rainfall distribution was investigated in the context of a subsynoptic scale disturbance,vertical wind shear and orographic factors.The results are shown as follows.(1) The subsynoptic scale system provided favorable dynamic conditions to the genesis of mesoscale rain clusters and rainbands.(2) The southern Hainan Island was located to the left of the leeward direction of downshear all the time,being favorable to the development of convection and leading to the asymmetric rainfall distribution.(3) Mountain terrain in the southern Hainan Island stimulated the genesis,combination and development of convective cells,promoting the formation of mesoscale precipitation systems and ultimately resulting in rainfall increase in the southern island.

考虑地磁暴期间电网电压下降的GIC-Q计算及易损区域识别

地磁暴诱发的GIC及其次生GIC-Q对电网的不同变电站影响程度不同,目前计算GIC-Q没有考虑电网电压下降,因此有必要提高GIC-Q的准确性和识别出易损区域以指导电网安全运行。文中提出了考虑地磁暴期间电网电压下降的GIC-Q计算方法,以新疆电网为算例计算了角度为90°,大小为1 V/km的地电场作用时各变电站变压器GIC;根据潮流计算模型,比较了是否考虑地磁暴期间电网电压下降的各变电站GIC-Q和电压的计算结果,以及喀什站GIC-Q和电压随地电场强度变化趋势;分析了地磁暴期间发电机无功储备对电网电压影响,以及线路有功功率和无功功率分布变化;分别提出了GIC严重度和电压越限严重度描述GIC对变压器的影响程度和GIC-Q对电网电压的影响程度,根据提出的变电站易损严重度来描述地电场对变电站的危害程度,并识别了新疆电网易损区域。结果表明,考虑地磁暴期间电网电压下降可以修正GIC-Q和节点电压计算结果,电网易损区域一般位于网络边缘。

计及多维隐患因素的输变电设备中长期故障率建模方法

随着新能源并网比例的不断提高,电网装备水平和管理模式快速发展,电网的风险管理面临新的不确定因素挑战。本文提出一种计及多维隐患因素的输变电设备中长期故障率建模方法。该方法首先运用头脑风暴法汇总相关业务部门对不同类型设备风险隐患因素的经验化筛选结果,完成设备风险隐患因素的识别,再按照不同的维度对隐患因素进行归类,在对每一个维度的故障频度进行单独建模后,经加权得到设备的中长期故障率。通过西北电网750kV罐式断路器的风险评估案例分析,展示了所提方法的实际应用效果。

1例重度主动脉瓣狭窄术后并发交感电风暴患者的急救护理

南京大学医学院附属鼓楼医院于2021年11月27日收治1例重度主动脉瓣狭窄的患者,患者在行外科术后第2天并发交感电风暴,并出现严重的心源性休克,经过积极救治和个体化护理,于术后42 d康复出院。作者总结并报道了急救护理要点如下:密切观察病情变化,早期识别异常心电图;精细化容量管理;紧急电除颤护理;抗心律失常用药护理;个体化心理护理。

牙周炎与新型冠状病毒感染关系研究

牙周炎是细菌侵犯牙周组织引起的慢性感染性疾病,与多种呼吸系统疾病密切相关。新型冠状病毒感染(Corona Virus Disease 2019,COVID-19)是一种由急性呼吸综合征冠状病毒-2引起的呼吸系统炎症性疾病,传染性强,重型或危重型致死率高,严重威胁人类生命健康。研究发现牙周炎与COVID-19的严重程度之间可能相关,COVID-19伴牙周炎患者的住院风险和死亡风险较无牙周炎者显著升高,干嗽、乏力和呼吸困难等临床症状也较无牙周炎患者明显增加,可能的机制为牙周深袋为SARS-CoV-2提供储存场所,促进其在全身的传播,或牙周细菌及细菌毒性产物通过参与全身的免疫炎症反应,影响COVID-19的发展。本文就牙周炎与COVID-19可能的关系及作用机制作一综述,以期为牙周炎与COVID-19关系的深入研究及防治策略提供参考。

1998年4月14～15日强沙尘暴过程分析

利用卫星云图 ,数值预报产品以及常规气象资料对 1998年 4月 14～ 15日发生在我国西部地区的沙尘暴天气进行了分析 ,指出本次过程发生在大气环流形势调整过程中 ,是由斜压槽及冷锋触发的。也重点分析了两个强沙尘暴中心的成因 ,发现第一个强沙尘暴区是由加强的冷锋云带造成的 ,而第二个强沙尘暴区是由三条云带共同作用造成的。强沙尘暴区位于高空急流出口区右侧、5 0 0hPa正涡度中心下风方和次级反环流的上升区内。并用动力气象学原理做了初步讨论 。

动力和能量参数在强对流天气预报中的应用研究

较强的热力不稳定和适宜的动力环境是强对流发展的基础 ,造成灾害的强对流一般是一种深厚对流 ,深对流指数和对流有效位能可反映对流上升运动的潜势和强度 ,对流有效位能还隐含地反映了对流层大气总体垂直热力结构。下沉对流有效位能和大风指数反映了对流下沉运动和下击暴流潜势 ,对流下沉和中层干空气的入侵高度、干燥程度及对流层中下层的稳定度和湿度有关。强风暴特别是超级单体一般都具有很高的螺旋性 ,高螺旋度有利于风暴生命的维持 ,而风暴相对螺旋度则对风暴发生及风暴类型有一定的预示。粗里查逊数反映了对流能量和环境场动力之间的平衡关系 ,能量螺旋度指数反映了动力和能量对强对流天气发展的共同效应 ,它们都综合了动力和热力两方面的因子 ,对强风暴及其类型的预报有指示意义。风暴强度指数和瑞士雷暴指数成功地把动力和对流能量参数结合起来 ,在实际研究和业务工作中这种方法值得借鉴。随着高分辨率中尺度和风暴模式的发展 ,模式输出的对流动力和能量参数将有广泛的应用前景。

北京一次大风和强降水天气过程形成机理的数值模拟

利用 3维强风暴冰雹分档模式 (IPA- HBM)对 2 0 0 1年 8月 2 3日北京的一次伴有大风、暴雨和冰雹的强对流天气过程进行模拟和分析 ,并与部分观测资料进行了比较分析。结果表明 ,该模式对此次强风暴的生命史、降水分布、降雹的大小等要素做了较好的模拟 ,并能够模拟出伴随强风暴过程所产生的强下沉气流和及地面强风速切变 (下击暴流 )。从云微物理学角度分析了此次局地性大风的形成原因 ,认为由高空冰雹粒子的拖曳产生的负浮力作用是促发强下沉气流产生的主要原因 ,其次是冰雹的融化和雨水蒸发冷却对下沉气流起加速作用 ,冰雹的拖曳和融化作用对下沉气流具有决定性作用。

淮北地区一次强风暴的弓形回波分析

2005年7月16日淮北地区发生了一次强风暴天气过程。主要使用新建成的阜阳CINRAD-SA多普勒天气雷达观测资料,辅以天气图、本站高空观测、地面观测资料,对此过程进行了综合分析。结果表明:这是一次以灾害性大风为主、有雨暴相伴随、局部还有冰雹发生的强对流天气过程。影响系统是一条中-β尺度的弓形飑线回波带。弓形回波带是由更早些时间出现的弧形的阵风锋触发而成的。中层干冷空气的侵入加强了对流云体中的下沉气流和低层出流,形成阵风锋。在如何综合应用如此丰富的雷达产品做好临近预报方面作了初步的尝试。

一次弓状回波、强对流风暴及合并过程研究Ⅰ:以单多普勒雷达资料为主的综合分析

利用济南CINRAD/SA雷达探测资料,结合卫星、自动站和其他常规天气资料,分析了一次弓状回波和强对流风暴的发生、发展,弓状回波和强对流风暴合并形成新弓状回波后又演变成逗点回波的过程。结果表明:(1)强对流过程发生在东北低涡横槽转竖过程,大气环境具有较大的对流有效位能和中等强度的低层垂直风切变。FY-2C卫星的红外云图显示,产生弓状回波的云团是在邻近云团的出流边界影响下发展、加强的,而地面自动站资料清楚地显示出弓状回波影响区域温、压、湿等在20min内发生的剧烈变化。(2)多普勒雷达产品资料分析表明,这是一次典型的弓状回波过程,系统演变经历了典型弓状回波演变过程的每一个阶段:高大对流回波、弓形和矛状阶段及逗点回波阶段。(3)强对流风暴出现在弓状回波前沿约75km的暖区中,具有普通超级单体的一些特征,移动缓慢。(4)弓状回波和强对流风暴合并阶段,弓状回波已处于逗点云系的后期。超级单体逐渐靠近弓状回波的颈部,在短时减弱后又快速发展并填补了弓状回波减弱部分。在弓状回波后侧强入流作用下,超级单体发展成弓状回波,并很快演变成逗点云系,其旋转头部发展很强并产生灾害性大风。