Xuan Ma

Xizang Minzu University

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Hong‐He Xu

Nanjing Institute of Geology and Paleontology

Fei Xie

Chinese PLA General Hospital

Qing Xia

PLA Information Engineering University

Wenshou Tian

Lanzhou University

Jiankai Zhang

Lanzhou University

Yan-Sen Chen

Nanjing Institute of Geology and Paleontology

Zhibin Niu

Tianjin University

Sheng Liu

China Mobile (China)

Jianping Li

Ocean University of China

Yanyan Zhu

University of California System

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Chinese Academy of Sciences

Nanjing Institute of Geology and Paleontology

Ocean University of China

North China Electric Power University

Qingdao National Laboratory for Marine Science and Technology

Beijing Normal University

Wuhan University

Cardiff University

Guangxi University

Shanghai Jiao Tong University

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Effects of Arctic stratospheric ozone changes on spring precipitation in the northwestern United States

Xuan Ma Fei Xie Jianping Li Wenshou Tian Ruiqiang Ding

Abstract. Using observations and reanalysis, we find that changes in April precipitation variations in the northwestern US are strongly linked to March Arctic stratospheric ozone (ASO). An increase (decrease) in ASO can result in enhanced (weakened) westerlies in the high and low latitudes of the North Pacific but weakened (enhanced) westerlies in the mid-latitudes. The anomalous circulation over the North Pacific can extend eastward to western North America, facilitating (impeding) the flow of a dry and cold airstream from the middle of North America to the North Pacific and enhancing (weakening) downwelling in the northwestern US, which results in decreased (increased) precipitation there. Model simulations using WACCM4 support the statistical analysis of observations and reanalysis data, and further reveal that the ASO influences circulation anomalies over the northwestern US in two ways. Stratospheric circulation anomalies caused by the ASO changes can propagate downward to the troposphere in the North Pacific and then eastward to influence the strength of the circulation anomalies over the northwestern US. In addition, the ASO changes cause sea surface temperature anomalies over the North Pacific that would cooperate with the ASO changes to modify the circulation anomalies over the northwestern US. Our results suggest that ASO variations could be a useful predictor of spring precipitation changes in the northwestern US; The northwestern US may become dryer in future springs due to ASO recovery.

Westerlies

Atmospheric Circulation

Downwelling

10.5194/acp-2018-414

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Defect detection of nuclear fuel assembly based on deep neural network

Annals of Nuclear Energy (2019)

Zhangpeng Guo Zhiwang Wu Sheng Liu Xuan Ma Chaoyi Wang

Deep Neural Networks

10.1016/j.anucene.2019.107078

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Ordovician to Silurian graptolite specimen images for global correlation and shale gas exploration

Hong‐He Xu Zhibin Niu Yan-Sen Chen Xuan Ma Xiao-Jing Tong

Abstract. Multi- elemental and -dimensional data are more and more important during the development of data-driven research, as is the case in modern palaeontology, in which visual examination, by experts or someday the artificial intelligence, to every fossil specimen acts a crucial and fundamental role. We here release an integrated image dataset of 113 Ordovician to Silurian graptolite species or subspecies that are significant in global stratigraphy and shale gas exploration. The dataset contains 1550 high-resolution graptolite specimen images and scientific information related to the specimen, e.g., every specimen's taxonomic, geologic, geographic, and related references. We develop a tool, FSIDvis (Fossil Specimen Image Dataset Visualiser), to facilitate the human-interactive exploration of the rich-attribution image dataset. A nonlinear dimension reduction technique, t-SNE (t-Distributed Stochastic Neighbor Embedding), is employed to project the images into the two-dimensional space to visualise and explore the similarities. Our dataset potentially contributes to the analysis of the global biostratigraphic correlations and improves the shale gas exploration efficiency by developing an image-based automated classification model. All images are available from https://doi.org/10.5281/zenodo.5205216 (Xu, 2021).

Shale Gas

10.5194/essd-2021-280

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Citations (12)