A 3-D coupled ice sheet model, GLIMMER model is introduced, and an idealized ice sheet experiment under the EISMINT-1 criterion of moving boundary condition is presented. The results of the experiment reveal that for ...A 3-D coupled ice sheet model, GLIMMER model is introduced, and an idealized ice sheet experiment under the EISMINT-1 criterion of moving boundary condition is presented. The results of the experiment reveal that for a steady-state ice sheet profile the characteristic curves describe the process of evolution which are accordant with theoretical estimates. By solving the coupled thermodynamics equations of ice sheet, one may find the characteristic curves which derived from the conservation of the mass, energy and momentum to the ice flow profile. At the same time, an agreement, approximate to the GLIMMER case and the confirmed theoretical results, is found. Present study is explorihg work to introduce and discuss the handicaps of EISMINT criterion and GLIMMER, and prospect a few directions of the GLIMMER model.展开更多
GLI MMER(Genie Land Ice Model with Multipy-Enabled Regions)是英国Edinburgh大学开发的3D热动力陆冰模式,由运动方程、连续方程、热力学方程构成其主要物理框架,能与全球气候模式进行耦合,适用于冰川过程机理研究和冰川数值预报.介...GLI MMER(Genie Land Ice Model with Multipy-Enabled Regions)是英国Edinburgh大学开发的3D热动力陆冰模式,由运动方程、连续方程、热力学方程构成其主要物理框架,能与全球气候模式进行耦合,适用于冰川过程机理研究和冰川数值预报.介绍了3D GLI MMER陆冰模式,包括它的动力框架、边界条件、数值积分方法和外部强迫.此外,以青藏高原现代冰川为例进行数值试验,考察模式对冰川的模拟能力.结果表明:3D GLI MMER模式可以较好地模拟青藏高原冰川,所模拟的冰川分布、冰厚、冰温和冰速与实际观测比较接近.展开更多
Remote sensing technology has been widely used for marine monitoring.However,due to the limitations of sensor technologies and data sources,effective monitoring of marine ships at night remains challenging.To address ...Remote sensing technology has been widely used for marine monitoring.However,due to the limitations of sensor technologies and data sources,effective monitoring of marine ships at night remains challenging.To address these challenges,our study developed SDGST,a high-resolution glimmer marine ship dataset from SDGSAT-1 satellite and proposed a ship detection and identification method based on the YOLOv5s model,the Glimmer YOLO model.Considering the characteristics of glimmer images,our model has made several effective improvements to the original YOLOv5s model.In particular,the improved model incorporates a new layer for detecting small targets and integrates the CA(Coordinate Attention)mechanism.To enhance the original feature fusion strategy,we introduced BiFPN(Bi-directional Feature Pyramid Network).We also adopted the EIOU Loss function and replaced the initially defined anchors with clustering results,thus improving detection performance.The mean Average Precision(mAP%)reaches 96.7%,which is a 5.1%improvement over the YOLOv5s model.Notably,it significantly improves the detection of small ships.This model demonstrates superior performance in ship detection under glimmer conditions compared to the original YOLOv5s model and other popular target detection models,and may serve as a valuable reference for achieving high-precision nighttime marine monitoring.展开更多
基金supported by Polar Science Youth Innovational Foundation,PRIC (Grant No.JDQ200602)China National Bureau of Oeanography Youth Science Foundation (Grant No.2007219)Polar Strategy Research Foundation in China(Grant No.20070215).
文摘A 3-D coupled ice sheet model, GLIMMER model is introduced, and an idealized ice sheet experiment under the EISMINT-1 criterion of moving boundary condition is presented. The results of the experiment reveal that for a steady-state ice sheet profile the characteristic curves describe the process of evolution which are accordant with theoretical estimates. By solving the coupled thermodynamics equations of ice sheet, one may find the characteristic curves which derived from the conservation of the mass, energy and momentum to the ice flow profile. At the same time, an agreement, approximate to the GLIMMER case and the confirmed theoretical results, is found. Present study is explorihg work to introduce and discuss the handicaps of EISMINT criterion and GLIMMER, and prospect a few directions of the GLIMMER model.
文摘GLI MMER(Genie Land Ice Model with Multipy-Enabled Regions)是英国Edinburgh大学开发的3D热动力陆冰模式,由运动方程、连续方程、热力学方程构成其主要物理框架,能与全球气候模式进行耦合,适用于冰川过程机理研究和冰川数值预报.介绍了3D GLI MMER陆冰模式,包括它的动力框架、边界条件、数值积分方法和外部强迫.此外,以青藏高原现代冰川为例进行数值试验,考察模式对冰川的模拟能力.结果表明:3D GLI MMER模式可以较好地模拟青藏高原冰川,所模拟的冰川分布、冰厚、冰温和冰速与实际观测比较接近.
基金funded by Operation and Maintenance Project of Big Earth Data Center of the Chinese Academy of Sciences[grant no CAS-WX2022SDC-XK13]Joint HKU-CAS Laboratory for iEarth[grant no 313GJHZ2022074MI].
文摘Remote sensing technology has been widely used for marine monitoring.However,due to the limitations of sensor technologies and data sources,effective monitoring of marine ships at night remains challenging.To address these challenges,our study developed SDGST,a high-resolution glimmer marine ship dataset from SDGSAT-1 satellite and proposed a ship detection and identification method based on the YOLOv5s model,the Glimmer YOLO model.Considering the characteristics of glimmer images,our model has made several effective improvements to the original YOLOv5s model.In particular,the improved model incorporates a new layer for detecting small targets and integrates the CA(Coordinate Attention)mechanism.To enhance the original feature fusion strategy,we introduced BiFPN(Bi-directional Feature Pyramid Network).We also adopted the EIOU Loss function and replaced the initially defined anchors with clustering results,thus improving detection performance.The mean Average Precision(mAP%)reaches 96.7%,which is a 5.1%improvement over the YOLOv5s model.Notably,it significantly improves the detection of small ships.This model demonstrates superior performance in ship detection under glimmer conditions compared to the original YOLOv5s model and other popular target detection models,and may serve as a valuable reference for achieving high-precision nighttime marine monitoring.
