Mingyuan He

East China Normal University

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Haihong Wu

East China Normal University

Buxing Han

Beijing National Laboratory for Molecular Sciences

Zheng Sheng

National University of Defense Technology

Yang He

National University of Defense Technology

Shuaiqiang Jia

East China Normal University

Jianxin Zhai

East China Normal University

Shitao Han

East China Normal University

Jie Zhang

National University of Defense Technology

Xiaoqian Zhu

National University of Defense Technology

Chunjun Chen

Beijing National Laboratory for Molecular Sciences

Cooperative Institutions

University of Surrey

166

Chinese Academy of Sciences

155

Instituto de Ciencias Agrarias

151

East China Normal University

101

University of Chinese Academy of Sciences

Fudan University

Shanghai Jiao Tong University

Chinese Academy of Medical Sciences & Peking Union Medical College

Sun Yat-sen University

Peking University

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Boosting nitrate electroreduction to ammonia on NbO_xvia constructing oxygen vacancies

Green Chemistry (2022)

Xuefei Wan Weiwei Guo Xue Dong Haihong Wu Xiaofu Sun

A NbO x catalyst with oxygen vacancies is synthesized and used for nitrate electroreduction to ammonia. The faradaic efficiency of 94.5% and the NH 3 formation rate of 55.0 μg h −1 mg cat −1 can be achieved in a neutral electrolyte.

Natural bond orbital

10.1039/d1gc04483d

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Citations (53)

Synthesis, crystal structure, and properties of copper(II) and manganese(II) complexes with azide and 3,4-di(2′-pyridyl)-1,2,5-oxadiazole

Structural Chemistry (2006)

Na Liu Ai-Ling Cheng Hui-Qi Peng En‐Qing Gao Mingyuan He

Oxadiazole

Octahedral molecular geometry

10.1007/s11224-006-9117-y

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Citations (10)

Analysis of the Positive Arctic Oscillation Index Event and Its Influence in the Winter and Spring of 2019/2020

Frontiers in Earth Science (2021)

Jie Zhang Zheng Sheng Yantong Ma Yang He Xinjie Zuo

There were continuous positive Arctic Oscillation index (AOI) and large-scale weather and climate anomalies in the Northern Hemisphere in the winter and spring of 2019/2020, and the relationship between these anomalies is an important issue for subseasonal to seasonal (S2S) predictability. This study shows that an AOI event with splitting characteristics occurred in the Northern Hemisphere and that there was a gap between the periods in event, which has not been observed in any of the 12 previous positive AOI events. The 3 stages of upward propagating planetary wave (UPPW) variation caused the gap between the periods. First, in early November, the westerly flow from the troposphere to the stratosphere weakened, resulting in persistent weak UPPWs that allowed a strong polar vortex to form. Then, the two strong UPPWs in January and early February caused the original westerlies to decelerate and induced warming in the lower stratosphere. However, the UPPWs caused only moderate changes in the geopotential height and temperature due to the strong polar vortex that had formed in the previous stage. This moderate AOI decline resulted in the conditions that divided the positive event into two periods. Finally, the low-level westerlies became stronger and strengthened the UPPWs into the stable stratosphere, which ended the second positive AOI period in late March. The role of zonal circulation anomalies (ZCA) in the upper stratosphere as metrics of and intermediates in UPPW-AO interactions is revealed in this study. The typical ZCA development mode was identified by statistical analysis and a composite treatment based on eight historical positive AOI events. In this mode, when strong UPPWs occur and lead to the consequent propagation of the ZCA from the stratosphere to the troposphere, the geopotential height field in the lower troposphere changes away from a typical AO mode; eventually, the AOI becomes abnormal. The temperature anomaly and ZCA produced in the two positive AOI periods during the winter and spring of 2019/2020 led to increasing precipitation in the eastern polar region, northern Asia, and areas along 60°N latitude.

Westerlies

Geopotential height

Arctic oscillation

Predictability

Polar night

10.3389/feart.2020.580601

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Citations (15)

The Atmospheric Heating Mechanism over the Tharsis Bulge of Mars and the Impact of Global Dust Storms

Remote Sensing (2024)

Jie Zhang Zheng Sheng Mingyuan He

Mars atmospheric dynamics are crucial for understanding its climate and weather patterns, especially over plateaus. Previous studies have explored localized atmospheric heating mechanisms over Mars plateaus only to a little extent. The local atmospheric heating dynamics over the Tharsis plateau, especially during global dust storms (GDSs), have not been quantitatively analyzed before. Based on reanalysis datasets, our analysis reveals that the central highlands of Tharsis experience ~130 K diurnal temperature fluctuations, driven by intense daytime convective activity. Surface temperature and near-surface air temperatures show fluctuations approximately 25 K and 20 K higher than those at similar latitudes, respectively. We quantify a super-adiabatic lapse rate around noon that suggests strong atmospheric instability, previously unquantified in this region. By dusk, the atmosphere stabilizes, presenting a homogenized condition. At aphelion, sensible heating and adiabatic terms control the atmospheric heating, while, at perihelion, radiative and sensible heating predominate. Notably, the onset of GDS significantly alters this dynamic, reducing the ground–air temperature gap from 17 K to 5 K and enhancing diabatic heating (adiabatic cooling) in the mid-to-lower (mid-to-upper) troposphere, with increases in radiative components up to 60 W/m2.

Tharsis

Dust storm

10.3390/rs16111950

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Application of the combination index (CI)-isobologram equation to research the toxicological interactions of clothianidin, thiamethoxam, and dinotefuran in honeybee, Apis mellifera

Chemosphere (2017)

Yanmei Liu Sihong Liu Hui Zhang Yanping Gu Xuesheng Li

Clothianidin

Neonicotinoid

Beneficial insects

Environmental toxicology

10.1016/j.chemosphere.2017.06.045

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Citations (29)

Spectral Analysis of Gravity Waves from Near Space High-Resolution Balloon Data in Northwest China

Atmosphere (2020)

Yang He Zheng Sheng Mingyuan He

Using a set of near space high-resolution balloon data released in Hami, Xinjiang, we explored the spectral characteristics of temperature fluctuations and three-dimensional wind field fluctuations. As different from previous studies, which were based on radiosondes, we have increased the height range of spectral analysis to the stratosphere (38 km), which can explore the variation of spectral features with altitude, and can analyze higher wavenumber regions. The results show that horizontal wind field disturbances are isotropic, meridional and zonal winds have relatively consistent spectral structures, while vertical wind fluctuations have completely different spectral structures, which cannot be explained by the existing “universal spectrum” theory. The observed spectrum of horizontal wind field can be explained well by the “wind-shifting” theory. The ratio of spectral kinetic energy to potential energy is approximately constant only in the high wavenumber region but it varies at different height intervals. This study is a necessary extension of the observation for the characteristics of the vertical wavenumber spectrum in northwestern China, and it is also an experimental observation of spectral characteristics using radiosonde data at higher altitudes.

Wavenumber

Spectral slope

Spectral resolution

Spectral space

10.3390/atmos11020133

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Citations (39)

Adaptive Variational Mode Decomposition Method for Eliminating Instrument Noise in Turbulence Detection

Journal of Atmospheric and Oceanic Technology (2020)

Yang He Zheng Sheng Yanwei Zhu Mingyuan He

Abstract Noise removal is a key issue in the retrieval of turbulence from meteorological radiosonde data using the method proposed by Thorpe. Only by reducing as much as possible the influence of noise in the potential temperature fluctuations can the retrieval results reflect the turbulence characteristics of the real atmosphere. In this paper, an adaptive variational mode decomposition (VMD) method is proposed that is used to remove noise fluctuations from the potential temperature profile, and particle swarm optimization and mutual information are used to optimize the preset VMD parameters. The Thorpe method is applied to the denoised potential temperature profile to identify and characterize turbulent regions. The results show that the adaptive VMD method is very effective for denoising the potential temperature profile in both simulation experiments and actual detection data. The real turbulence overturn can be selected from the inversions by optimal smoothing and statistical tests. This method is an improvement on the Wilson method and allows the Thorpe method to be applied to daytime sounding data, avoiding the confusion between noise and turbulence that results in the distortion of the turbulence scale.

Smoothing

Distortion (music)

10.1175/jtech-d-20-0004.1

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Citations (7)

Monthly Arctic Sea Ice Concentration Prediction Based on the ConvLSTM Model

2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI) (2021)

Penglun Li Hongze Leng Beibei Ma Mingyuan He

Sea ice concentration (SIC) reanalysis data is important inputs to the coupled ocean-atmosphere system (COAS). Using simple and fast methods to forecast arctic SIC in the mid-long term will be conducive to the construction of the COAS. In this paper, the convolution LSTM model (ConvLSTM) was used to iteratively predict the monthly series of arctic SIC reanalysis data for 6 to 12 months. B y comparing the root mean square error (RMSE) of SIC distribution in the process of monthly prediction and iterative prediction, this paper preliminarily demonstrates the influence of different seasons on the iterative prediction accuracy of the model, and evaluates the feasibility of ConvLSTM model in the prediction of periodic tensor data such as sea ice. On the compressed dataset, the RMSE of the SIC distribution varies from 0.06 to 0.15, with an average of 0.1. The experimental results verify the prediction ability of ConvLSTM model for the periodic change of monthly tensor data of SIC, that is, the fluctuation of iterative prediction results affected by seasons is small, and the prediction deviation of freezing period is slightly higher than that of melting period and is within an acceptable range. In addition, in order to obtain a high-resolution prediction matrix, it is necessary to add a reasonable block mechanism to the model and evaluate the requirements of ConvLSTM model for computing resources and environment.

Long-term prediction

Convolution (computer science)

10.1109/cisai54367.2021.00038

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Citations (3)

Synthesis of 2,4-diisopropyl-5,5-dimethyl-1,3-dioxane catalyzed by Brønsted acidic ionic liquids

Science Bulletin (2008)

Wenjuan Wang Youfei Wang Wenping Cheng Jian Wang Jian‐Guo Yang

Isobutyraldehyde

Brønsted–Lowry acid–base theory

10.1007/s11434-008-0377-3

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