We have examined an unusual rocket-triggered lightning flash during the summer campaign of the SHAndong Triggered Lightning Experiment(SHATLE)in 2018.High-speed video camera observations and three-dimensional(3D)light...We have examined an unusual rocket-triggered lightning flash during the summer campaign of the SHAndong Triggered Lightning Experiment(SHATLE)in 2018.High-speed video camera observations and three-dimensional(3D)lightning mapping show that the upward positive leader split into two branched channels(referred to as branch A&branch B,respectively)at a height of about 370 m,and then progressed into different charge regions of the thundercloud.Branch A initially developed upward before turning northwest from the trigger point;ten pronounced intermittent negative leaders were observed propagating downward along this branch channel,causing strong current pulses.Branch B propagated obliquely upward towards the northeast before continuing northward to a region of weak radar echo at 3 km altitude,resulting in a large-scale charge transfer of approximately–250 C(C=Coulomb)and generating a sustained,strong current exceeding 2 kA.Furthermore,downward dart leaders propagating along branch A connected to the active channel of branch B at the bifurcation point.This connection generated a surge of large current pulses(M-components)superimposed on the continuing current.Evidence from 3D lightning mapping and concurrent channel-base current measurements suggests that the 10th negative dart leader split during its downward propagation,with one branch propagating to ground,while the other entered into a positive charge reservoir.This initiated a positive charge transfer to ground via the existing channel,ultimately triggering the final stroke which exhibited a bi-polarity current pulse.展开更多
Fine-scale structures can be observed in small field-of-view(FOV)auroral observations,but they are often overlooked because they appear only sporadically in all-sky observations.Such forms are of great interest becaus...Fine-scale structures can be observed in small field-of-view(FOV)auroral observations,but they are often overlooked because they appear only sporadically in all-sky observations.Such forms are of great interest because they may embody specific magnetosphere-ionosphere coupling processes,reveal localized energy deposition pathways,and provide new insights into cross-scale plasma dynamics and instabilities.However,their limited spatial extent,transient occurrence,and scarcity in wide-FOV observations make systematic investigation challenging.Traditional manual analysis struggles to capture these subtle structures within vast all-sky datasets,while automated detection faces severe data imbalance and morphological ambiguity.To address these challenges,we propose a synthetic-to-real progressive learning framework for cross-FOV retrieval of rare auroral forms.A Generative Adversarial Network(GAN)is employed to perform cross-FOV transformation between unpaired small-FOV images containing rare aurora forms and all-sky images(ASI)without such structures,thereby generating large numbers of synthetic ASI with rare auroral morphology.These synthetic samples are used to train an initial detection model,which subsequently undergoes iterative fine-tuning through feedback-guided learning:The model performs inference on new all-sky data,and the progressively accumulated real detections are incorporated into the training set.Experimental results demonstrate that the proposed method achieves over 92%detection accuracy on ASI,enabling high-precision retrieval of small-scale auroral structures across large-scale observations.This framework provides a scalable and effective approach to rediscovering rare auroral phenomena in continuous all-sky monitoring,offering new opportunities for exploring the fine-scale dynamics of the upper atmosphere.展开更多
基金supported by National Key R&D Program of China(2023YFC3007703,2017YFC1501501)the CAS Project of Stable Support for Youth Team in Basic Research Field(YSBR-018)+2 种基金National Natural Science Foundation of China(41875006,and U1938115)Youth Innovation Fund Project of the University(WK2080000172)the Chinese Meridian Project.
文摘We have examined an unusual rocket-triggered lightning flash during the summer campaign of the SHAndong Triggered Lightning Experiment(SHATLE)in 2018.High-speed video camera observations and three-dimensional(3D)lightning mapping show that the upward positive leader split into two branched channels(referred to as branch A&branch B,respectively)at a height of about 370 m,and then progressed into different charge regions of the thundercloud.Branch A initially developed upward before turning northwest from the trigger point;ten pronounced intermittent negative leaders were observed propagating downward along this branch channel,causing strong current pulses.Branch B propagated obliquely upward towards the northeast before continuing northward to a region of weak radar echo at 3 km altitude,resulting in a large-scale charge transfer of approximately–250 C(C=Coulomb)and generating a sustained,strong current exceeding 2 kA.Furthermore,downward dart leaders propagating along branch A connected to the active channel of branch B at the bifurcation point.This connection generated a surge of large current pulses(M-components)superimposed on the continuing current.Evidence from 3D lightning mapping and concurrent channel-base current measurements suggests that the 10th negative dart leader split during its downward propagation,with one branch propagating to ground,while the other entered into a positive charge reservoir.This initiated a positive charge transfer to ground via the existing channel,ultimately triggering the final stroke which exhibited a bi-polarity current pulse.
基金supported by the National Natural Science Foundation of China(Grant no.41874173).
文摘Fine-scale structures can be observed in small field-of-view(FOV)auroral observations,but they are often overlooked because they appear only sporadically in all-sky observations.Such forms are of great interest because they may embody specific magnetosphere-ionosphere coupling processes,reveal localized energy deposition pathways,and provide new insights into cross-scale plasma dynamics and instabilities.However,their limited spatial extent,transient occurrence,and scarcity in wide-FOV observations make systematic investigation challenging.Traditional manual analysis struggles to capture these subtle structures within vast all-sky datasets,while automated detection faces severe data imbalance and morphological ambiguity.To address these challenges,we propose a synthetic-to-real progressive learning framework for cross-FOV retrieval of rare auroral forms.A Generative Adversarial Network(GAN)is employed to perform cross-FOV transformation between unpaired small-FOV images containing rare aurora forms and all-sky images(ASI)without such structures,thereby generating large numbers of synthetic ASI with rare auroral morphology.These synthetic samples are used to train an initial detection model,which subsequently undergoes iterative fine-tuning through feedback-guided learning:The model performs inference on new all-sky data,and the progressively accumulated real detections are incorporated into the training set.Experimental results demonstrate that the proposed method achieves over 92%detection accuracy on ASI,enabling high-precision retrieval of small-scale auroral structures across large-scale observations.This framework provides a scalable and effective approach to rediscovering rare auroral phenomena in continuous all-sky monitoring,offering new opportunities for exploring the fine-scale dynamics of the upper atmosphere.
