CMIP5模式中El Nino-EAWM关系的模拟对东亚冬季风模拟的影响

本文利用统计学的方法,评估了17个参加第五次国际耦合模式比较计划(CMIP5)的海气耦合模式对东亚冬季风(EAWM)年际变化的模拟。结果表明:多数模式对东亚冬季风的年际变化有一定的模拟能力,其中对东亚大槽年际变化的模拟最好;模式对东亚冬季主要系统的年际变化在空间上的模拟好于强度,对强度的模拟以偏弱为主;通过综合评估得到模拟能力好的模式有:bcc-csm1-1,CCSM4,HadCM3,NorESM1-M。针对模式间对冬季风年际变化模拟能力差别较大的现象,选取了4个模拟能力最好的模式和5个最差的进行讨论;通过评估El Ni?o对东亚冬季环流的影响,发现模式对El Ni?o与EAWM之间相互关系(El Ni?o-EAWM)的模拟能力是模式间对冬季风年际变化模拟偏差较大的原因之一,即对El Ni?o-EAWM模拟好的模式对东亚冬季风年际变化的模拟也好。

基于ELES模型和CD效用函数的“纵横双向”消费结构变动研究

探究消费升级对于促进共同富裕具有深远意义。基于CFPS 2010—2020年数据,结合扩展线性支出模型(ELES)、CD效用函数和门槛回归等方法构建了“纵横双向”识别模型,并实证考察了我国居民消费升级与消费结构状况。研究发现,2010—2020年我国居民家庭消费结构横向上呈升级趋势,但仍以生存型消费支出为主;细分“三型八类”消费,发现生存型与发展型的消费占比上升,享受型消费存在较大的消费偏好,表现出消费分层特征,且家庭消费结构呈多样化发展趋势;家庭年度总支出的三条约束线分别为60100元、122800元及122900元。纵向上发现预算约束线在不断后移,表明消费结构在不断升级。文章运用多门槛回归方法结合ELES模型构建了消费结构的综合识别模型,以此作为判断消费结构升级与否的依据和标准。

基于时空综合分型的El Niňo事件对中国东部降水的影响差异

基于1961—2022年中国高分辨率降水格点资料、合成分析和经验正交函数分解方法,揭示了时空综合分型得到的生命史较长-异常中心位置偏东的低频-东部(LF-EP)型和生命史较短-异常中心位置偏西的准两年-中部(QB-CP)型El Niňo事件对中国东部降水的不同影响。结果表明,LF-EP型事件对降水的影响显著且稳定:自发展年秋季到衰减年夏季长达近4个季节,长江以南区域降水持续地显著偏多,且异常雨带中心自衰减年春季起逐步北抬。QB-CP型事件发生时降水异常特征变化更加复杂多变:发展年夏秋季其空间分布与LF-EP型事件中的特征大致相反,长江以南区域降水整体偏少,冬季开始长江以南逐渐有正异常降水出现,且春季以后异常雨带表现出逐渐南退特征,至衰减年夏季发展为华北-长江中下游-华南地区降水异常“正-负-正”分布。进一步通过比较不同类型事件中大尺度水汽输送的差异探讨了其影响不同的可能机制,发现由海温异常纬向位置差异导致的西太平洋区域大气环流直接响应以及衍生模态响应差异是造成中国东部降水异常空间分布特征差异的重要原因。同时,两类时空事件持续性和转相时间的差异也会使得对降水影响的时间尺度出现差别。

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

我国城镇居民的消费结构变动研究——基于ELES模型实证分析

以城镇居民为研究对象,通过选取2016—2022年全国的城镇居民人均收入、消费支出和消费结构数据,采用时间序列数据,分析了2016—2022年以来我国城镇居民的消费结构变动。运用ELES模型,对城镇居民各项消费支出进行实证分析,研究表明:目前我国城镇居民食品和居住的消费支出仍然占总消费支出的主要部分,其中食品消费支出的比重逐年下降。同时,城镇居民的消费行为更加偏重商品的质量,对医疗保健具有更高的需求,收入弹性更加偏重生活质量的提升。

河北省城乡居民消费结构变动研究——基于ELES模型的实证分析

基于ELES模型,对2013-2021年河北省城乡居民消费结构变动情况进行了研究.从边际消费倾向可以看出,随着生活水平的提高,河北省城乡居民的消费逐渐从“温饱型”向“小康型”转变.消费结构变动度分析显示,除个别年份外,居民消费结构整体变动不大,相对较稳定.通过分析消费结构熵数发现,河北省城乡居民整体消费质量较高,但是消费结构升级速度相对较慢.根据分析结果,提出了增加居民收入、优化消费环境、拓展新型消费、坚持推进城乡融合发展、提高农村居民的社会保障水平等建议.

海气相互作用在模式FGOALS-g3模拟东亚夏季风及其对前冬El Niño响应中的贡献

本文基于观测、再分析资料和中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG)最新版本气候系统模式FGOALS-g3,探究了海气相互作用在模拟东亚夏季风及其对前冬El Niño响应中的贡献。大气环流模式(AGCM)模拟的气候态夏季风雨带偏东,东亚季风区表现为干偏差,耦合模式(CGCM)虽模拟出了夏季风雨带的位置,但降水仍偏弱。AGCM由于缺乏海气耦合过程,夏季西北太平洋地区对流模拟过强,使得副热带高压(简称副高)偏东、南中国海季风槽偏东,造成东亚夏季风雨带偏东;东亚陆地区域水汽偏少,也是降水干偏差的一个重要原因,此两项可以解释70%以上的干偏差。在考虑海气相互作用后,西北太平洋的降水正异常减弱了局地海表温度,因此CGCM显著改进了副高以及南中国海季风槽偏东等偏差,使得夏季风雨带位置得到改进,季风区降水干偏差减小了36%,但由于水汽偏少,水汽纬向输送偏少,东亚季风区仍维持着显著的干偏差。另一方面,对前冬El Niño的响应,CGCM能够再现El Niño衰减年夏季印度—西太平洋电容器效应(IPOC机制)对西北太平洋异常反气旋(WNPAC)的维持作用及偶极型分布的降水异常。而AGCM中夏季西北太平洋以及孟加拉湾、印度半岛周围海域对流对于海温的响应过于敏感,一方面西北太平洋局地暖异常造成的对流质量输送一定程度上抑制了WNPAC的建立,另一方面孟加拉湾、印度半岛周围海域过强的上升异常,通过局地环流,抑制了其南侧印度洋的对流异常,导致无法模拟出IPOC机制对衰减年夏季WNPAC的维持作用。因此,缺乏海气耦合过程是AGCM不能模拟出东亚夏季风对前冬El Niño滞后响应的关键原因。

El Niño事件发展期对中国东部夏季极端降水的影响

利用1961−2020年的再分析资料和中国台站观测降水数据集,研究了东部型El Niño事件发展期夏季对中国夏季极端降水的影响.结果表明,东部型El Niño在发展期夏季对中国极端降水的影响主要表现在中国东部地区,造成华北和江南地区极端降水减少,江淮地区极端降水显著增多.进一步分析其中的物理过程发现,当东部型El Niño事件处于发展期夏季时,赤道东太平洋出现显著的海表面温度(sea surface temperature,SST)暖异常,西太平洋区域表现为冷异常,导致反气旋性环流异常.同时,西北太平洋区域存在SST暖异常,对应气旋性环流异常.异常的SST分布激发了“正-负-正(+−+)”的东亚-太平洋型(East Asia-Pacific,EAP)波列异常,对应着“负-正-负(−+−)”的降水配置.在2个异常环流的交汇处有显著的辐合上升运动,为江淮地区带去了充足的水汽.而华北地区主要受到反气旋性环流和蒙古高压的共同控制,并受到来自高纬度地区的异常西北风影响,存在显著的辐散下沉运动,降水的动力条件不足.并且,在东部型El Niño事件发展期夏季,西太平洋副热带高压位置异常偏东,不利于江南地区降水的发生及水汽的输送,进一步造成江南地区极端降水减少.以上结果显示东部型El Niño事件在其发展期夏季对中国极端降水存在重要的影响,为区域极端气候预测提供了理论依据.

EL15-2C风向传感器风向角度缺失问题分析及监测软件设计

目前国家气象站的风向观测主要采用的是光电格雷码式风向传感器,其光电装置和机械部件损坏后仍有观测数据生成,容易被误认为传感器工作正常,使得风向观测仪器故障难以及时发现和排除。为弥补风向数据自动判识的空缺,本文设计并实现了一款名为《县级台站风向角度监测软件》的应用程序,该程序适用于县级基层台站,通过软件自动对风向数据进行分析,绘出此段时间内的风向数据角度分布图,辅助人工判断是正常情况下风向观测数据表现,还是异常的风向规律性角度区间缺失情况,从而尽早在基层台站端发现并排除问题。

PERC背钝化工艺卡点位置缺陷导致EL不良研究

以二合一管式PECVD背钝化镀膜工艺过程中出现的石墨舟空心卡点EL发黑品质异常为研究对象,分析讨论二合一管式PECVD背钝化工艺中射频功率、工艺温度、氧化铝沉积厚度等对晶硅太阳电池空心卡点EL发黑品质异常的影响。结果表明,在二合一管式PECVD背钝化工艺时采用12~16 nm厚度的氧化铝薄膜、350~370℃的预淀积工艺温度,能有效解决镀膜空心卡点EL发黑品质异常,显著提升晶硅太阳电池在二合一管式PECVD的镀膜品质。

29insG新突变导致B_(el)亚型的血清学和分子生物学分析1例

目的探讨1例B_(el)亚型的血清学特征和分子机制。方法通过血型血清学方法分析患者ABO血型,吸收放散试验检测患者红细胞上的弱抗原,使用分子生物学方法对ABO血型基因序列分析。结果患者正定型为O型,反定型为B型,正反不相符,吸收放散法确认有弱B抗原。该突变点经查ISBT及相关文献均未发现同种情况,该突变为首次发现。结合3-7外显子序列情况患者血型是B_(el)(29insertG)/O.01.01。结论在临床日常工作中遇到ABO血型正反不相符的情况,结合血清学和分子生物学检测技术可以提高ABO血型鉴定的准确性和可靠性。

Responses of the Southern Ocean mixed layer depth to the eastern and central Pacific El Niño events during austral winter

Based on the Ocean Reanalysis System version 5(ORAS5)and the fifth-generation reanalysis datasets derived from European Centre for Medium-Range Weather Forecasts(ERA5),we investigate the different impacts of the central Pacific(CP)El Niño and the eastern Pacific(EP)El Niño on the Southern Ocean(SO)mixed layer depth(MLD)during austral winter.The MLD response to the EP El Niño shows a dipole pattern in the South Pacific,namely the MLD dipole,which is the leading El Niño-induced MLD variability in the SO.The tropical Pacific warm sea surface temperature anomaly(SSTA)signal associated with the EP El Niño excites a Rossby wave train propagating southeastward and then enhances the Amundsen Sea low(ASL).This results in an anomalous cyclone over the Amundsen Sea.As a result,the anomalous southerly wind to the west of this anomalous cyclone advects colder and drier air into the southeast of New Zealand,leading to surface cooling through less total surface heat flux,especially surface sensible heat(SH)flux and latent heat(LH)flux,and thus contributing to the mix layer(ML)deepening.The east of the anomalous cyclone brings warmer and wetter air to the southwest of Chile,but the total heat flux anomaly shows no significant change.The warm air promotes the sea ice melting and maintains fresh water,which strengthens stratification.This results in a shallower MLD.During the CP El Niño,the response of MLD shows a separate negative MLD anomaly center in the central South Pacific.The Rossby wave train triggered by the warm SSTA in the central Pacific Ocean spreads to the Amundsen Sea,which weakens the ASL.Therefore,the anomalous anticyclone dominates the Amundsen Sea.Consequently,the anomalous northerly wind to the west of anomalous anticyclone advects warmer and wetter air into the central and southern Pacific,causing surface warming through increased SH,LH,and longwave radiation flux,and thus contributing to the ML shoaling.However,to the east of the anomalous anticyclone,there is no statistically significant impact on the MLD.

基于YOLOv5的光伏组件EL照片缺陷检测报告系统研究

基于YOLOv5的光伏组件EL照片缺陷检测报告系统,利用YOLOv5的图像识别能力对光伏组件的EL照片进行缺陷检测,并自动生成检测报告。文章详细介绍系统的设计、实现、测试和优化过程,并探讨系统的实际应用和发展前景。通过该系统,用户可以快速准确地检测光伏组件EL照片中的缺陷,提高光伏组件质量控制的效率和精度。未来,该系统可以进一步扩展应用于其他领域的瑕疵检测,具有广阔的发展前景。

Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer months.Therefore,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them skillfully.The present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 index.The integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 index.These crucial signals are then masked in the initial conditions to verify their roles in the prediction.In addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North Pacific.This approach is also applied to other El Niño events,revealing several new precursor signals.This study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

Estimating the Yield Loss of Winter Wheat from Drought in the United States Southern Plains Region as Influenced by El Niño-Southern Oscillation (ENSO)

Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.

Mafic and felsic magmatism in the Wadi Kalalat area, South Eastern Desert, Egypt: mineralogy, geochemistry and geodynamic evolution during the Neoproterozoic in the Nubian Shield

In the south Eastern Desert of Egypt,two contrasting types of magmatism(mafic and felsic) are recorded in the Wadi Kalalat area,and form the Gabal El Motaghiarat and Gabal Batuga intrusions,respectively.The two intrusions post-dates ophiolitic and arc associations represented by serpentinite and metagabbro-diorite,respectively.The mafic intrusion has a basal ultramafic member represented by fresh peridotite,which is followed upward by olivine gabbro and anorthositic or leucogabbro.This mafic intrusion pertains to the Alaskan-type mafic-ultramafic intrusions in the Arabian-Nubian Shield(ANS)being of tholeiitic nature and emplaced in a typical arc setting.On the other hand,the Gabal Batuga intrusion comprises three varieties of fresh A-type granites of high K-calc alkaline nature,which is peraluminous and garnetbearing in parts.A narrow thermal aureole in the olivine gabbro of the mafic intrusion was developed due to the intrusion of the Batuga granites.This results in the development of a hornfelsic melagabbro variety in which the composition changed from tholeiitic to a calc-alkaline composition due to the addition of S_(i)O_(2),Al_(2)O_(3),alkalis,lithosphile elements(LILEs) such as Rb(70 ppm) and Y(28 ppm) from the felsic intrusion.Outside the thermal aureole,Rb amounts 2-8 ppm and Y lies in the range <2-6ppm.It is believed that the Gabal Batuga felsic intrusion started to emplace during the waning stage of an arc system,with transition from the pre-collisional(i.e.,arc setting) to post-collisional and within plate settings.Magma from which the Gabal Batuga granites were fractionated is high-K calc-alkaline giving rise to a typical post-collisional A-type granite(A_(2)-subtype) indicating an origin from an underplating crustal source.Accordingly,it is stressed here that the younger granites in the ANS are not exclusively post-collisional and within-plate but most likely they started to develop before closure of the arc system.The possible source(s) of mafic magmas that resulted in the formation of the two intrusions are discussed.Mineralogical and geochemical data of the post-intrusion dykes(mafic and felsic) suggest typical active continental rift/within-plate settings.

Geochemistry, mineral paragenesis and geothermal conditions of oreforming fluids from the Ain El Bey Cu–Fe deposit: potential occurrence of native gold and precious metal traces (North African orogenic belt, Northern Tunisia)

The Ain El Bey abandoned mine, in North-West Tunisia, fits into the geodynamic context of the European and African plate boundary. Ore deposit corresponds to veins and breccia of multiphase Cu–Fe-rich mineralization related to various hydrothermal fluid circulations. Petromineralogical studies indicate a rich mineral paragenesis with a minimum of seven mineralization phases and, at least, six pyrite generations. As is also the case for galena and native silver, native gold is observed for the first time as inclusion in quartz which opens up, thus, new perspectives for prospecting and evaluating the potential for noble metals associated with the mineralization. Scanning Electron Microscope--Energy Dispersive Spectroscopy and Transmission electron microscopy analyses show, in addition, a large incorporation of trace elements, including Ag and Au, in mineral structures such as fahlores(tetrahedrite-tennantite) and chalcopyrite ones. The mineral/mineral associations, used as geothermometers, gave estimated temperatures for the mineralizing fluids varying from 254 to 330 ℃ for phase Ⅲ, from 254 to 350 ℃ for phase Ⅳ, and from 200 to 300 ℃ for phases Ⅴ and Ⅵ. The seventh and last identified mineralization phase, marked by a deposit of native gold, reflects a drop in the mineralizing fluid’s temperature(< 200 ℃) compatible with boiling conditions. Such results open up perspectives for the development of precious metal research and the revaluation of the Cu–Fe ore deposit at the Ain El Bey abandoned mine, as well as at the surrounding areas fitting in the geodynamic framework of the Africa-Europe plate boundary.

SHEL:a semantically enhanced hardware-friendly entity linking method

With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of training data using large pre-trained language models,which is a hardware threshold to accomplish this task.Some researchers have achieved competitive results with less training data through ingenious methods,such as utilizing information provided by the named entity recognition model.This paper presents a novel semantic-enhancement-based entity linking approach,named semantically enhanced hardware-friendly entity linking(SHEL),which is designed to be hardware friendly and efficient while maintaining good performance.Specifically,SHEL's semantic enhancement approach consists of three aspects:(1)semantic compression of entity descriptions using a text summarization model;(2)maximizing the capture of mention contexts using asymmetric heuristics;(3)calculating a fixed size mention representation through pooling operations.These series of semantic enhancement methods effectively improve the model's ability to capture semantic information while taking into account the hardware constraints,and significantly improve the model's convergence speed by more than 50%compared with the strong baseline model proposed in this paper.In terms of performance,SHEL is comparable to the previous method,with superior performance on six well-established datasets,even though SHEL is trained using a smaller pre-trained language model as the encoder.

Different El Niño Flavors and Associated Atmospheric Teleconnections as Simulated in a Hybrid Coupled Model

A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.