期刊文献+
共找到2,321篇文章
< 1 2 117 >
每页显示 20 50 100
基于设计哲学视角的技术功能理论
1
作者 任远 焦雯雯 《学术研究》 CSSCI 北大核心 2024年第8期32-38,177,共8页
技术哲学经数次转向后形成的设计哲学注重技术人工物本身,而技术人工物作为物理实体具有结构—功能双重属性。人工物作为设计的结果,其设计的过程既包括物理结构的实现,又包括功能的实现,因此可以说设计就是技术人工物两重属性之间的连... 技术哲学经数次转向后形成的设计哲学注重技术人工物本身,而技术人工物作为物理实体具有结构—功能双重属性。人工物作为设计的结果,其设计的过程既包括物理结构的实现,又包括功能的实现,因此可以说设计就是技术人工物两重属性之间的连接机制。胡克斯与弗玛斯提出的使用—计划进路下的ICE理论,通过给出设计者和使用者视角的功能归属定义及其阐释,一方面化解了人工物的结构—功能两重性难题,另一方面也克服了单纯的意向理论、因果—角色理论和进化理论各自的理论不足。尽管如此,ICE功能理论对于技术人工物的本体论地位的解释仍然是单薄的,功能归属并不能为技术人工物提供个体化标准。技术人工物的双重属性要求更深入完整地理解设计、使用与功能之间的关系。 展开更多
关键词 设计哲学 技术人工物 两重性难题 ICE功能理论
下载PDF
典型插电混动车型高压系统的原理及检修(一)
2
作者 李韬 李文雅 《汽车维修与保养》 2024年第2期42-45,共4页
一、典型插电式混合动力汽车高压部件1.典型插电式混合动力汽车架构插电式混合动力电动汽车(PHEV)使用电池为电机提供动力,使用另一种燃料(如汽油)为内燃机(ICE)提供动力。PHEV电池可以通过壁装插座或充电桩设备、ICE或再生制动进行充... 一、典型插电式混合动力汽车高压部件1.典型插电式混合动力汽车架构插电式混合动力电动汽车(PHEV)使用电池为电机提供动力,使用另一种燃料(如汽油)为内燃机(ICE)提供动力。PHEV电池可以通过壁装插座或充电桩设备、ICE或再生制动进行充电。车辆通常依靠电力运行,直到电池几乎耗尽,然后汽车自动切换到使用ICE。本文以2018款路虎揽胜运动型P400e为例,来介绍典型PHEV,2015-2023年间生产的很多车型,都采用了这一架构。初期生产的车辆目前已到了社会维修期. 展开更多
关键词 插电式混合动力汽车 插电式混合动力电动汽车 再生制动 充电桩 高压系统 PHEV ICE 自动切换
下载PDF
Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression 被引量:1
3
作者 DONG Wen-bo ZHOU Li +2 位作者 DING Shi-feng WANG Ai-ming CAI Jin-yan 《China Ocean Engineering》 SCIE EI CSCD 2024年第2期313-325,共13页
Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ... Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second. 展开更多
关键词 ice channel ship navigation IDENTIFICATION image segmentation corner point regression
下载PDF
深低温保存下高效抗冻多肽的合理设计和机理探讨 被引量:1
4
作者 Haishan Qi Yihang Gao +6 位作者 Lin Zhang Zhongxin Cui Xiaojie Sui Jianfan Ma Jing Yang Zhiquan Shu Lei Zhang 《Engineering》 SCIE EI CAS CSCD 2024年第3期164-173,共10页
The development of effective antifreeze peptides to control ice growth has attracted a significant amount of attention yet still remains a great challenge.Here,we propose a novel design method based on in-depth invest... The development of effective antifreeze peptides to control ice growth has attracted a significant amount of attention yet still remains a great challenge.Here,we propose a novel design method based on in-depth investigation of repetitive motifs in various ice-binding proteins(IBPs)with evolution analysis.In this way,several peptides with notable antifreeze activity were developed.In particular,a designed antifreeze peptide named AVD exhibits ideal ice recrystallization inhibition(IRI),solubility,and biocompatibility,making it suitable for use as a cryoprotective agent(CPA).A mutation analysis and molecular dynamics(MD)simulations indicated that the Thr6 and Asn8 residues of the AVD peptide are fundamental to its ice-binding capacity,while the Ser18 residue can synergistically enhance their interaction with ice,revealing the antifreeze mechanism of AVD.Furthermore,to evaluate the cryoprotection potential of AVD,the peptide was successfully employed for the cryopreservation of various cells,which demonstrated significant post-freezing cell recovery.This work opens up a new avenue for designing antifreeze materials and provides peptide-based functional modules for synthetic biology. 展开更多
关键词 Antifreeze peptides Evolution analysis Ice recrystallization inhibition Molecular dynamics simulation CRYOPRESERVATION Synthetic biology
下载PDF
毛竹ICE基因家族的全基因组鉴定及低温胁迫下的表达模式分析
5
作者 王书伟 周明兵 《浙江农林大学学报》 CAS CSCD 北大核心 2024年第3期568-576,共9页
【目的】对毛竹Phyllostachys edulis ICE基因家族进行鉴定及分析,找出响应毛竹抗寒关键家族成员,研究毛竹ICE基因的生物学功能、响应低温胁迫的分子机制及遗传转化,为提高毛竹抗寒性奠定理论基础。【方法】利用生物信息学方法分析毛竹... 【目的】对毛竹Phyllostachys edulis ICE基因家族进行鉴定及分析,找出响应毛竹抗寒关键家族成员,研究毛竹ICE基因的生物学功能、响应低温胁迫的分子机制及遗传转化,为提高毛竹抗寒性奠定理论基础。【方法】利用生物信息学方法分析毛竹ICE基因家族成员,并对4、0、−2℃低温处理0(对照)、0.5、1.0、24.0、48.0 h的毛竹生理指标和ICE基因的表达模式进行分析。【结果】共鉴定了4个毛竹ICE基因。保守结构域和多重序列比对分析表明:PeICE基因结构高度相似。系统发育关系及启动子顺式作用元件分析显示:PeICE基因与水稻Oryza sativa亲缘关系更近,同时存在大量与非生物胁迫相关的顺式作用元件。活性氧自由基(ROS)染色发现随着处理时间增长,ROS染色逐渐加深,但是其0℃处理24.0 h、−2℃处理1.0 h后染色逐渐减弱。脯氨酸(Pro)质量摩尔浓度、超氧化物歧化酶(SOD)活性显示:4和0℃条件下,Pro质量摩尔浓度和SOD活性整体增加,但−2℃时低于对照。过氧化物酶(POD)活性显示:在3个低温处理下均增加。ICE基因表达模式分析发现:4、0℃处理时PeICE表达量整体增加,且都以PeICE3增量最明显;而−2℃处理下PeICE整体表达量水平低于对照。【结论】随着温度降低和处理时间增强,毛竹受到的损伤不断增强,其内酶活系统以及ICE基因积极响应低温胁迫,其中,PeICE3对低温胁迫最为敏感,但在−2℃时,ICE基因表达量并未增加,推测该基因家族响应了寒冷胁迫而非冷冻胁迫。 展开更多
关键词 毛竹 低温胁迫 ICE基因家族 基因鉴定 表达分析
下载PDF
Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness 被引量:1
6
作者 Chentao SONG Jiang ZHU Xichen LI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第7期1379-1390,共12页
In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,ma... In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications. 展开更多
关键词 Arctic sea ice thickness deep learning spatiotemporal sequence prediction transfer learning
下载PDF
Arctic Sea Ice Variations in the First Half of the 20th Century:A New Reconstruction Based on Hydrometeorological Data 被引量:1
7
作者 Vladimir A.SEMENOV Tatiana A.ALDONINA +2 位作者 Fei LI Noel Sebastian KEENLYSIDE Lin WANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第8期1483-1495,1686-1693,共21页
The shrinking Arctic sea-ice area(SIA) in recent decades is a striking manifestation of the ongoing climate change.Variations of the Arctic sea ice have been continuously observed by satellites since 1979, relatively ... The shrinking Arctic sea-ice area(SIA) in recent decades is a striking manifestation of the ongoing climate change.Variations of the Arctic sea ice have been continuously observed by satellites since 1979, relatively well monitored since the 1950s, but are highly uncertain in the earlier period due to a lack of observations. Several reconstructions of the historical gridded sea-ice concentration(SIC) data were recently presented based on synthesized regional sea-ice observations or by applying a hybrid model–empirical approach. Here, we present an SIC reconstruction for the period1901–2019 based on established co-variability between SIC and surface air temperature, sea surface temperature, and sea level pressure patterns. The reconstructed sea-ice data for March and September are compared to the frequently used Had ISST1.1 and SIBT1850 datasets. Our reconstruction shows a large decrease in SIA from the 1920 to 1940 concurrent with the Early 20th Century Warming event in the Arctic. Such a negative SIA anomaly is absent in Had ISST1.1 data. The amplitude of the SIA anomaly reaches about 0.8 mln km^(2) in March and 1.5 mln km^(2) in September. The anomaly is about three times stronger than that in the SIBT1850 dataset. The larger decrease in SIA in September is largely due to the stronger SIC reduction in the western sector of the Arctic Ocean in the 70°–80°N latitudinal zone. Our reconstruction provides gridded monthly data that can be used as boundary conditions for atmospheric reanalyses and model experiments to study the Arctic climate for the first half of the 20th century. 展开更多
关键词 Arctic sea ice Arctic climate early 20th century warming climate variability
下载PDF
The Role of Underlying Boundary Forcing in Shaping the Recent Decadal Change of Persistent Anomalous Activity over the Ural Mountains 被引量:1
8
作者 Ting LEI Shuanglin LI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第8期1496-1510,1661-1667,共22页
Observational analyses demonstrate that the Ural persistent positive height anomaly event(PAE) experienced a decadal increase around the year 2000, exhibiting a southward displacement afterward. These decadal variatio... Observational analyses demonstrate that the Ural persistent positive height anomaly event(PAE) experienced a decadal increase around the year 2000, exhibiting a southward displacement afterward. These decadal variations are related to a large-scale circulation shift over the Eurasian Continent. The effects of underlying sea ice and sea surface temperature(SST) anomalies on the Ural PAE and the related atmospheric circulation were explored by Atmospheric Model Intercomparison Project(AMIP) experiments from the Coupled Model Intercomparison Project Phase 6 and by sensitivity experiments using the Atmospheric General Circulation Model(AGCM). The AMIP experiment results suggest that the underlying sea ice and SST anomalies play important roles. The individual contributions of sea ice loss in the Barents-Kara Seas and the SST anomalies linked to the phase transition of the Pacific Decadal Oscillation(PDO) and Atlantic Multidecadal Oscillation(AMO) are further investigated by AGCM sensitivity experiments isolating the respective forcings.The sea ice decline in Barents-Kara Seas triggers an atmospheric wave train over the Eurasian mid-to-high latitudes with positive anomalies over the Urals, favoring the occurrence of Ural PAEs. The shift in the PDO to its negative phase triggers a wave train propagating downstream from the North Pacific. One positive anomaly lobe of the wave train is located over the Ural Mountains and increases the PAE there. The negative-to-positive transition of the AMO phase since the late-1990s causes positive 500-h Pa height anomalies south of the Ural Mountains, which promote a southward shift of Ural PAE. 展开更多
关键词 Ural persistent anomaly Pacific decadal oscillation Atlantic multidecadal oscillation sea ice loss in Barents-Kara Seas
下载PDF
Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence 被引量:1
9
作者 Jiazhen ZHAO Shengping HE +2 位作者 Ke FAN Huijun WANG Fei LI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第8期1465-1482,共18页
Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Ar... Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained). 展开更多
关键词 wintertime newly formed Arctic sea ice model democracy model weighting scheme model performance model independence
下载PDF
Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2 被引量:1
10
作者 Shengping HE Helge DRANGE +4 位作者 Tore FUREVIK Huijun WANG Ke FAN Lise Seland GRAFF Yvan J.ORSOLINI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第8期1511-1526,共16页
To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simu... To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling. 展开更多
关键词 Arctic sea ice loss warm Arctic–cold East Asia atmospheric internal variability large-ensemble simulation NorESM2 PAMIP
下载PDF
Joint Probability Analysis and Prediction of Sea Ice Conditions in Liaodong Bay
11
作者 LIAO Zhenkun DONG Sheng +2 位作者 TAO Shanshan HUA Yunfei JIA Ning 《Journal of Ocean University of China》 CAS CSCD 2024年第1期57-68,共12页
Sea ice conditions in Liaodong Bay of China are often described by sea ice grades,which classify annual sea ice conditions based on the annual maximum sea ice thickness(AM-SIT)and annual maximum floating ice extent(AM... Sea ice conditions in Liaodong Bay of China are often described by sea ice grades,which classify annual sea ice conditions based on the annual maximum sea ice thickness(AM-SIT)and annual maximum floating ice extent(AM-FIE).The joint probability distribution of AM-SIT and AM-FIE was established on the basis of their data pairs from 1949/1950 to 2019/2020 in Liaodong Bay.The joint intensity index of the sea ice condition in the current year is calculated,and the joint classification criteria of the sea ice grades in past years are established on the basis of the joint intensity index series.A comparison of the joint criteria with the 1973 and 2022 criteria revealed that the joint criteria of the sea ice grade match well,and the joint intensity index can be used to quantify the sea ice condition over the years.A time series analysis of the sea ice grades and the joint intensity index sequences based on the joint criteria are then performed.Results show a decreasing trend of the sea ice condition from 1949/1950 to 2019/2020,a mutation in 1990/1991,and a period of approximately 91 years of the sea ice condition.In addition,the Gray-Markov model(GMM)is applied to predict the joint sea ice grade and the joint intensity index of the sea ice condition series in future years,and the error between the results and the actual sea ice condition in 2020/2021 is small. 展开更多
关键词 sea ice grade ice thickness floating ice extent Liaodong Bay COPULA
下载PDF
Spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice in multiple dimensions during 1979 to 2020
12
作者 Yu Guo Xiaoli Wang +1 位作者 He Xu Xiyong Hou 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2024年第3期102-114,共13页
Arctic sea ice is broadly regarded as an indicator and amplifier of global climate change.The rapid changes in Arctic sea ice have been widely concerned.However,the spatiotemporal changes in the horizontal and vertica... Arctic sea ice is broadly regarded as an indicator and amplifier of global climate change.The rapid changes in Arctic sea ice have been widely concerned.However,the spatiotemporal changes in the horizontal and vertical dimensions of Arctic sea ice and its asymmetry during the melt and freeze seasons are rarely quantified simultaneously based on multiple sources of the same long time series.In this study,the spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice were investigated from both the horizontal and vertical dimensions during 1979–2020 based on remote sensing and assimilation data.The results indicated that Arctic sea ice was declining at a remarkably high rate of–5.4×10^(4) km^(2)/a in sea ice area(SIA)and–2.2 cm/a in sea ice thickness(SIT)during 1979 to 2020,and the reduction of SIA and SIT was the largest in summer and the smallest in winter.Spatially,compared with other sub-regions,SIA showed a sharper declining trend in the Barents Sea,Kara Sea,and East Siberian Sea,while SIT presented a larger downward trend in the northern Canadian Archipelago,northern Greenland,and the East Siberian Sea.Regarding to the seasonal trend of sea ice on sub-region scale,the reduction rate of SIA exhibited an apparent spatial heterogeneity among seasons,especially in summer and winter,i.e.,the sub-regions linked to the open ocean exhibited a higher decline rate in winter;however,the other sub-regions blocked by the coastlines presented a greater decline rate in summer.For SIT,the sub-regions such as the Beaufort Sea,East Siberian Sea,Chukchi Sea,Central Arctic,and Canadian Archipelago always showed a higher downward rate in all seasons.Furthermore,a striking freeze-thaw asymmetry of Arctic sea ice was also detected.Comparing sea ice changes in different dimensions,sea ice over most regions in the Arctic showed an early retreat and rapid advance in the horizontal dimension but late melting and gradual freezing in the vertical dimension.The amount of sea ice melting and freezing was disequilibrium in the Arctic during the considered period,and the rate of sea ice melting was 0.3×10^(4) km^(2)/a and 0.01 cm/a higher than that of freezing in the horizontal and vertical dimensions,respectively.Moreover,there were notable shifts in the melting and freezing of Arctic sea ice in 1997/2003 and 2000/2004,respectively,in the horizontal/vertical dimension. 展开更多
关键词 Arctic sea ice sea ice area sea ice thickness spatiotemporal variation freeze-thaw asymmetry
下载PDF
Parameterization, sensitivity, and uncertainty of 1-D thermodynamic thin-ice thickness retrieval
13
作者 Tianyu Zhang Mohammed Shokr +5 位作者 Zhida Zhang Fengming Hui Xiao Cheng Zhilun Zhang Jiechen Zhao Chunlei Mi 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2024年第7期93-111,共19页
Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article ex... Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article examines the deviation of the classical model’s TIT output when using different parameterization schemes and the sensitivity of the output to the ice thickness.Moreover,it estimates the uncertainty of the output in response to the uncertainties of the input variables.The parameterized independent variables include atmospheric longwave emissivity,air density,specific heat of air,latent heat of ice,conductivity of ice,snow depth,and snow conductivity.Measured input parameters include air temperature,ice surface temperature,and wind speed.Among the independent variables,the results show that the highest deviation is caused by adjusting the parameterization of snow conductivity and depth,followed ice conductivity.The sensitivity of the output TIT to ice thickness is highest when using parameterization of ice conductivity,atmospheric emissivity,and snow conductivity and depth.The retrieved TIT obtained using each parameterization scheme is validated using in situ measurements and satellite-retrieved data.From in situ measurements,the uncertainties of the measured air temperature and surface temperature are found to be high.The resulting uncertainties of TIT are evaluated using perturbations of the input data selected based on the probability distribution of the measurement error.The results show that the overall uncertainty of TIT to air temperature,surface temperature,and wind speed uncertainty is around 0.09 m,0.049 m,and−0.005 m,respectively. 展开更多
关键词 Arctic sea ice 1-D thermodynamic ice model thin-ice thickness sea ice parameterization
下载PDF
Acoustic Velocity-Based Inversion of the Physical Properties of Sea Ice in the Central Arctic Region
14
作者 KONG Yadong XING Junhui +1 位作者 XU Haowei XU Chong 《Journal of Ocean University of China》 SCIE CAS CSCD 2024年第5期1213-1220,共8页
Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and e... Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and environment.One of the key research aspects is the investigation of the temperature,salinity,and density parameters of sea ice to obtain essential insights.During the 11th Chinese National Arctic Research Expedition,acoustic velocity was measured on an ice core at a short-term ice station,however,temperature,salinity,and density were not measured.In the present work,we utilized a genetic algorithm to invert these obtained acoustic velocity data to sea ice temperature,salinity,and density parameters on the basis of the relationship between acoustic velocity and the physical properties of Arctic summer sea ice.We validated the effectiveness of this inversion procedure by comparing its findings with those of other researchers.The results indicate that within the normalized depth range of 0.43-0.94,the ranges for temperature,salinity,and density are -0.48--0.29℃,1.63-3.35,and 793.1-904.1 kg m^(-3),respectively. 展开更多
关键词 acoustic velocity Arctic sea ice inversion of sea ice properties genetic algorithm
下载PDF
Quantifying freeze-melt dynamics of lakes on the Tibetan Plateau using Sentinel-1 synthetic aperture radar imagery
15
作者 JIN Lu CHEN Jun +3 位作者 CAI Yu KONG Yecheng WANG Yongfeng DUAN Zheng 《Journal of Mountain Science》 SCIE CSCD 2024年第3期805-819,共15页
The ice phenology of alpine lakes on the Tibetan Plateau(TP)is a rapid and direct responder to climate changes,and the variations in lake ice exhibit high temporal frequency characteristics.MODIS and passive microwave... The ice phenology of alpine lakes on the Tibetan Plateau(TP)is a rapid and direct responder to climate changes,and the variations in lake ice exhibit high temporal frequency characteristics.MODIS and passive microwave data are widely used to monitor lake ice changes with high temporal resolution.However,the low spatial resolutions make it difficult to effectively quantify the freeze-melt dynamics of lakes.This work used Sentinel-1 synthetic aperture radar(SAR)data to derive high-resolution ice maps(about 6 days),then with the aid of Sentinel-2 optical images to quantify freeze-melt processes in three typical lakes on the TP(e.g.Selin Co,Ayakekumu Lake,and Nam Co).The results showed that three lakes had an average annual ice period of 125-157 days and a complete ice cover period of 72-115 days,from 2018 to 2022.They exhibit different ice phenology patterns.Nam Co is characterized by repeated episodes of freezing,melting,and refreezing,resulting in a prolonged freeze-up period.Meanwhile,the break-up period of Nam Co lasts for a longer duration(about 19 days),and the break-up exhibits a smooth process.Similarly,Ayakekumu Lake showed more significant inter-annual fluctuations in the freeze-up period,with deviations of up to 28 days observed among different years.Compared to the other two lakes,Selin Co experienced a relatively short freeze-up and break-up period.In short,Sentinel-1 SAR data can effectively monitor the weekly and seasonal variations in lake ice on the TP.Particularly,this data facilitates quantification of the freeze-melt dynamics. 展开更多
关键词 Lake ice Sentinel-1 SAR Tibetan Plateau Climate change
下载PDF
Preface to the Special Topic on Ocean, Sea Ice and Northern Hemisphere Climate:In Remembrance of Professor Yongqi GAO's Key Contributions
16
作者 Noel KEENLYSIDE Shengping HE Fei LI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第8期1463-1464,共2页
This special issue commemorates the life work of Prof. Yongqi GAO who passed away in July 2021, his time cut short by illness. He had many great achievements, but still much more to contribute. The seven articles in t... This special issue commemorates the life work of Prof. Yongqi GAO who passed away in July 2021, his time cut short by illness. He had many great achievements, but still much more to contribute. The seven articles in this special issue are from research areas where he contributed, and they illustrate how his close colleagues are continuing his work. 展开更多
关键词 Ice HEMISPHERE CLIMATE
下载PDF
Deep Learning Shows Promise for Seasonal Prediction of Antarctic Sea Ice in a Rapid Decline Scenario
17
作者 Xiaoran DONG Yafei NIE +6 位作者 Jinfei WANG Hao LUO Yuchun GAO Yun WANG Jiping LIU Dake CHEN Qinghua YANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第8期1569-1573,共5页
The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South's latest call, this study presents the refo... The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South's latest call, this study presents the reforecast results of Antarctic sea-ice area and extent from December to June of the coming year with a Convolutional Long Short-Term Memory(Conv LSTM)Network. The reforecast experiments demonstrate that Conv LSTM captures the interannual and interseasonal variability of Antarctic sea ice successfully, and performs better than the European Centre for Medium-Range Weather Forecasts. Based on this, we present the prediction from December 2023 to June 2024, indicating that the Antarctic sea ice will remain at lows, but may not create a new record low. This research highlights the promising application of deep learning in Antarctic sea-ice prediction. 展开更多
关键词 deep learning ANTARCTIC sea ice seasonal prediction
下载PDF
Snow and regolith albedo variations using CRISM data at McMurdo crater,Mars
18
作者 Sehajpal Singh Deepak Singh 《Earth and Planetary Physics》 EI CAS CSCD 2024年第2期338-355,共18页
The cryosphere component provides the most reliable and insightful indications of any planet’s climate dynamics.Using data from the Compact Reconnaissance Imaging Spectrometer for Mars(CRISM),we develop a novel appro... The cryosphere component provides the most reliable and insightful indications of any planet’s climate dynamics.Using data from the Compact Reconnaissance Imaging Spectrometer for Mars(CRISM),we develop a novel approach to determining the broadband Visible and Near Infrared(VNIR)albedo of the Martian surface.This study focuses on albedo changes in the McMurdo crater,part of Mars’s south polar layer deposits.We compare seasonal and interannual variations of the McMurdo surface albedo before,during,and after the Global Dust Storm(GDS)of Martian Year(MY)34.As the seasons progressed from spring to summer,the mean albedo in MY 32 and 34 plunged by over 40%,by about 35%in MY 33,and by slightly more than 30%in MY 35.Compared interannually,however,mean albedo values within both seasons(spring and summer)exhibited no significant differences in those same years.Notably,interannual albedo difference maps reveal albedo variation of more than±0.3 in certain regions of the crater.Considering only snow-covered pixels,interannual albedo differences suggest that Mars dust had a pervasive impact on Mars’s cryosphere.Variations in maximum and minimum albedo values as high as 0.5 were observed,depending upon differences in the dust levels in Martian snow/ice.The maximum and the minimum snow albedo values were lowest in MY 34,indicating the effect of the intense dust storm event that year.The average snow albedo decreased from 0.45 in MY 32 to 0.40 in MY 33 and to 0.33 in MY 34,and then rose back to 0.40 in MY 35.This trajectory suggests a temporary deposition of dust,partially reversed after the GDS by self-cleaning mechanisms(local aeolian process and CO_(2)sublimation/deposition cycle). 展开更多
关键词 MARS Martian ice ALBEDO dust storm Mars surface Martian climate
下载PDF
An ensemble learning method to retrieve sea ice roughness from Sentinel-1 SAR images
19
作者 Pengyi Chen Zhongbiao Chen +1 位作者 Runxia Sun Yijun He 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2024年第5期78-90,共13页
Sea ice surface roughness(SIR)affects the energy transfer between the atmosphere and the ocean,and it is also an important indicator for sea ice characteristics.To obtain a small-scale SIR with high spatial resolution... Sea ice surface roughness(SIR)affects the energy transfer between the atmosphere and the ocean,and it is also an important indicator for sea ice characteristics.To obtain a small-scale SIR with high spatial resolution,a novel method is proposed to retrieve SIR from Sentinel-1 synthetic aperture radar(SAR)images,utilizing an ensemble learning method.Firstly,the two-dimensional continuous wavelet transform is applied to obtain the spatial information of sea ice,including the scale and direction of ice patterns.Secondly,a model is developed using the Adaboost Regression model to establish a relationship among SIR,radar backscatter and the spatial information of sea ice.The proposed method is validated by using the SIR retrieved from SAR images and comparing it to the measurements obtained by the Airborne Topographic Mapper(ATM)in the summer Beaufort Sea.The determination of coefficient,mean absolute error,root-mean-square error and mean absolute percentage error of the testing data are 0.91,1.71 cm,2.82 cm,and 36.37%,respectively,which are reasonable.Moreover,K-fold cross-validation and learning curves are analyzed,which also demonstrate the method’s applicability in retrieving SIR from SAR images. 展开更多
关键词 2-D Cauchy continuous wavelet transform(CWT) Adaboost Regression sea ice sea ice surface roughness
下载PDF
Advances in ice avalanches on the Tibetan Plateau
20
作者 TANG Minggao LI Guang +4 位作者 ZHAO Huanle XU Qiang WU Guangjian YANG Wei GUO Daojing 《Journal of Mountain Science》 SCIE CSCD 2024年第6期1814-1829,共16页
As some of the greatest natural disasters in the cryosphere,ice avalanches(IAs)seriously threaten lives and cause catastrophic damage to the resource environment,but a comprehensive overview of the state of knowledge ... As some of the greatest natural disasters in the cryosphere,ice avalanches(IAs)seriously threaten lives and cause catastrophic damage to the resource environment,but a comprehensive overview of the state of knowledge on IAs remains lacking.We summarized 63 IAs on the Tibetan Plateau(TP)since the 20th century,of which,over 20 IAs occurred after the 21st century.The distributions of IAs are mainly concentrated in the southeastern and northwestern TP,and the occurrence time of IAs is mostly concentrated from July to September.We highlight recent advances in mechanical properties and genetic mechanisms of IAs and emphasize that temperature,rainfall,and seismicity are the inducing factors.The failure modes of IAs are summarized into 6 categories by examples:slip pulling type,slip toppling type,slip breaking type,water level collapse type,cave roof collapse type,and wedge failure type.Finally,we deliver recommendations concerning the risk assessment and prediction of IAs.The results provide important scientific value for addressing climate change and resisting glacier-related hazards. 展开更多
关键词 Ice avalanche Global warming Genetic mechanism Risk assessment Tibetan Plateau
下载PDF
上一页 1 2 117 下一页 到第
使用帮助 返回顶部