Recently,extreme meteorological droughts have affected China,causing terrible socioeconomic impacts.Despite previous research on the spatiotemporal characteristics and mechanisms of drought,two crucial issues remain s...Recently,extreme meteorological droughts have affected China,causing terrible socioeconomic impacts.Despite previous research on the spatiotemporal characteristics and mechanisms of drought,two crucial issues remain seldom explored.First,an event-oriented drought chronology with detailed spatiotemporal evolutions is urgently required.Second,the complex migration patterns and diversity of synchronous temperature extremes need to be quantitatively investigated.Accordingly,the main achievements of our investigation are as follows.We produced an event-oriented set of extreme meteorological droughts over China through the application of a newly developed 3D DBSCAN-based detection method(deposited on https://doi.org/10.25452/figshare.plus.25512334),which was verified with a historical atlas and monographs on a case-by-case basis.In addition,distinctive migration patterns(i.e.,stationary/propagation types)are identified and ranked,considering the differences in latitudinal zones and coastal/inland locations.We also analyze the diversity of synchronous temperature extremes(e.g.,hotness and coldness).Notably,an increasing trend in hot droughts occurred over China since the late 1990s,predominantly appearing to the south of 30°N and north of 40°N.All drought events and synchronous temperature extremes are ranked using a comprehensive magnitude index,with the 2022 summer-autumn Yangtze River hot drought being the hottest.Furthermore,Liang-Kleeman information flow-based causality analysis emphasizes key areas where the PDO and AMO influenced decadal variations in coverages of droughts and temperature extremes.We believe that the achievements in this study may offer new insights into sequential mechanism exploration and prediction-related issues.展开更多
This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI(region of interest) w...This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI(region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions: positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.展开更多
基金jointly supported by the National Key R&D Program of China(Grant No.2022YFC3002801)the National Natural Science Foundation of China Grants(Grant Nos.42192563,42120104001)+1 种基金the National Natural Science Foundation of China for Youth(Grant No.42205191)the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab).
文摘Recently,extreme meteorological droughts have affected China,causing terrible socioeconomic impacts.Despite previous research on the spatiotemporal characteristics and mechanisms of drought,two crucial issues remain seldom explored.First,an event-oriented drought chronology with detailed spatiotemporal evolutions is urgently required.Second,the complex migration patterns and diversity of synchronous temperature extremes need to be quantitatively investigated.Accordingly,the main achievements of our investigation are as follows.We produced an event-oriented set of extreme meteorological droughts over China through the application of a newly developed 3D DBSCAN-based detection method(deposited on https://doi.org/10.25452/figshare.plus.25512334),which was verified with a historical atlas and monographs on a case-by-case basis.In addition,distinctive migration patterns(i.e.,stationary/propagation types)are identified and ranked,considering the differences in latitudinal zones and coastal/inland locations.We also analyze the diversity of synchronous temperature extremes(e.g.,hotness and coldness).Notably,an increasing trend in hot droughts occurred over China since the late 1990s,predominantly appearing to the south of 30°N and north of 40°N.All drought events and synchronous temperature extremes are ranked using a comprehensive magnitude index,with the 2022 summer-autumn Yangtze River hot drought being the hottest.Furthermore,Liang-Kleeman information flow-based causality analysis emphasizes key areas where the PDO and AMO influenced decadal variations in coverages of droughts and temperature extremes.We believe that the achievements in this study may offer new insights into sequential mechanism exploration and prediction-related issues.
基金PHD Site from Chinese Educational Department,Grant number:20040699015
文摘This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI(region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions: positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.
