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Wenjie Dong
Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China

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Journal article
Published: 04 August 2021 in Remote Sensing
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Air pollution in North China (NC) is an important issue affecting the economy and health. In this study, we used a regional climate model, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) to project air pollution in NC and investigate the variations of air pollutions response to future climate changes, which probably has an implication to strategy and control policy for air quality in NC. A comprehensive model evaluation was conducted to verify the simulated aerosol optical depth (AOD) based on MODIS and MISR datasets, and the model also showed reasonable results in aerosol concentrations. Future changes of air pollution in the middle of the 21st century (2031–2050) were projected in the two Representative Concentration Pathways (RCP4.5 and RCP8.5) and compared with the situation in the historical period (1986–2005). In the two RCPs, the simulated averaged PM2.5 concentration was projected with the highest values of 50–250 μg·m−3 over the Bohai Rim Economic Circle (BREC) in winter. The maximum AOD is in the Beijing–Tianjin–Hebei (BTH) region in summer, with an average value of 0.68. In winter, in the RCP4.5 scenario, PM2.5 concentration and AOD obviously declined in BTH and Shandong province. However, in the RCP8.5 scenario, PM2.5 concentration and AOD increased. Results indicated that air pollution would be reduced in winter if society developed in the low emission pathway. Precipitation was projected to increase both in the two RCPs scenarios in spring, summer, and winter, but it was projected to decrease in autumn. The planetary boundary layer height decreased in the two RCPs scenarios in the central region of NC in the summer and winter. The results indicated that changes of meteorological conditions have great impact on air pollution in future scenarios.

ACS Style

Chengrong Dou; Zhenming Ji; Yukun Xiao; Zhiyuan Hu; Xian Zhu; Wenjie Dong. Projection of Air Pollution in Northern China in the Two RCPs Scenarios. Remote Sensing 2021, 13, 3064 .

AMA Style

Chengrong Dou, Zhenming Ji, Yukun Xiao, Zhiyuan Hu, Xian Zhu, Wenjie Dong. Projection of Air Pollution in Northern China in the Two RCPs Scenarios. Remote Sensing. 2021; 13 (16):3064.

Chicago/Turabian Style

Chengrong Dou; Zhenming Ji; Yukun Xiao; Zhiyuan Hu; Xian Zhu; Wenjie Dong. 2021. "Projection of Air Pollution in Northern China in the Two RCPs Scenarios." Remote Sensing 13, no. 16: 3064.

Journal article
Published: 21 July 2021 in Remote Sensing
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In this study, we evaluated the performance of an air pollution forecasting system during a scientific cruise in the South China Sea (SCS) from 9 August to 7 September 2016. The air pollution forecasting system consisted of a Lagrangian transport and dispersion model, the flexible particle dispersion model (FLEXPART), coupled with a high-resolution Weather Research and Forecasting model (WRF). The model system generally reproduced the meteorological variability and reasonably simulated the distribution of aerosols both vertically and horizontally along the cruise path. The forecasting system was further used to study the regional transport of non-local aerosols over the SCS and track its sources during the cruise. The model results showed that Southeast Asia contributed to more than 90% of the non-local aerosols over the northern region of the SCS due to the southwesterly prevailing winds. Specifically, the largest mean contribution was from Vietnam (39.6%), followed by Thailand (25.1%). This study indicates that the model system can be applied to study regional aerosols transport and provide air pollution forecasts in the SCS.

ACS Style

Yuzhang Tang; Zhenming Ji; Yuan Li; Zhiyuan Hu; Xian Zhu; Wenjie Dong. Evaluation of an Air Pollution Forecasting System Based on Micro-Pulse Lidar Cruising Measurements in the South China Sea. Remote Sensing 2021, 13, 2855 .

AMA Style

Yuzhang Tang, Zhenming Ji, Yuan Li, Zhiyuan Hu, Xian Zhu, Wenjie Dong. Evaluation of an Air Pollution Forecasting System Based on Micro-Pulse Lidar Cruising Measurements in the South China Sea. Remote Sensing. 2021; 13 (15):2855.

Chicago/Turabian Style

Yuzhang Tang; Zhenming Ji; Yuan Li; Zhiyuan Hu; Xian Zhu; Wenjie Dong. 2021. "Evaluation of an Air Pollution Forecasting System Based on Micro-Pulse Lidar Cruising Measurements in the South China Sea." Remote Sensing 13, no. 15: 2855.

Article
Published: 22 May 2021 in Climate Dynamics
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Based on four reanalyses or gridded data sets (ERA5, 20CR, APHRODITE and REGEN), we provide an overview of 23 Historical and 7 HighResMIP experiments’ performance from the Coupled Model Intercomparison Project Phase 6 (CMIP6) (for short, 6-Hist, HighRes) in simulating seven extreme precipitation indices over Asia defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We compare them with 28 Historical experiments in CMIP5 (5-Hist). CMIP5 and CMIP6 models are generally able to reproduce extreme precipitation’s spatial distribution and their trend patterns in comparison to the benchmark data set (APHRODITE). The overall performance of individual model is summarized by a “portrait” diagram based on four statistics for each index. We divide all 58 models into three groups (A, the top 20%; B, the median 60% and C group, the last 20%) according to MR rankings (the comprehensive ranking measure). Based on the “portrait” diagram and MR rankings, models that perform relatively well for all seven extreme precipitation indices include HadCM3, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES from 5-Hist, EC-Earth3, EC-Earth3-Veg from 6-Hist and ECMWF-IFS-HR, ECMWF-IFS-LR, ECMWF-IFS-MR from HighRes. The simulated performance of CMIP6 is polarized, for the top four and the last five ranking models are both from CMIP6. Compared with the counterpart models in CMIP6 and CMIP5, the improvement of PCC (pattern correlation coefficient) is more obvious. Furthermore, the dry biases of CMIP6 (both 6-Hist and HighRes) in Southern China and India and the wet biases of CMIP6 in Tibet are reduced compared to CMIP5. This may benefit from the improvement that CMIP6 models can capture the characteristics of meridional moisture flux convergence, and improve the overestimation or underestimation of meridional and zonal specific humidity eddies compared to CMIP5.

ACS Style

Tianyun Dong; Wenjie Dong. Evaluation of extreme precipitation over Asia in CMIP6 models. Climate Dynamics 2021, 1 -19.

AMA Style

Tianyun Dong, Wenjie Dong. Evaluation of extreme precipitation over Asia in CMIP6 models. Climate Dynamics. 2021; ():1-19.

Chicago/Turabian Style

Tianyun Dong; Wenjie Dong. 2021. "Evaluation of extreme precipitation over Asia in CMIP6 models." Climate Dynamics , no. : 1-19.

Article
Published: 27 April 2021 in Climate Dynamics
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The western North Pacific (WNP) intraseasonal oscillation (ISO) is the strongest over the globe, its prediction is the cornerstone for subseasonal prediction of the Asian summer monsoon. Yet, our understanding of the diversity of the WNP ISO is limited, which challenges our modeling and prediction efforts. We study the diversity of observed WNP ISO by performing cluster analysis on propagation patterns of ISO events, targeting three clusters: westward, northeastward, and northwestward propagations. The westward cluster exists within the WNP, while the other two are related to the northeastward propagating rain band originated from the central equatorial Indian Ocean and to the northwestward propagating dipole across the western Pacific and Indian Ocean, respectively. Moist static energy (MSE) tendency contributing to these different propagations is mainly due to horizontal advection, while radiative heating mainly maintains the ISO’s development. Background sea surface temperature (SST) and MSE anomalies partly determine this ISO diversity, especially for those ISOs with large similarity. The westward cluster is related to warm SST anomalies in the western Indian Ocean, as a combination of seasonal cycle and internal interannual-to-interdecadal variability. The northeastward cluster is related to the cold Pacific Meridional Mode and La Niña-like pattern, while the northwestward cluster is related to the opposite warm background, both as the internal variability. Our finding of the background-affected ISO diversity over the WNP can be conducive to both model simulation and subseasonal prediction of the Asian summer monsoon.

ACS Style

Hui Wang; Fei Liu; Bin Wang; Guosen Chen; Wenjie Dong. Diversity of intraseasonal oscillation over the western North Pacific. Climate Dynamics 2021, 1 -13.

AMA Style

Hui Wang, Fei Liu, Bin Wang, Guosen Chen, Wenjie Dong. Diversity of intraseasonal oscillation over the western North Pacific. Climate Dynamics. 2021; ():1-13.

Chicago/Turabian Style

Hui Wang; Fei Liu; Bin Wang; Guosen Chen; Wenjie Dong. 2021. "Diversity of intraseasonal oscillation over the western North Pacific." Climate Dynamics , no. : 1-13.

Article
Published: 17 April 2021 in Climate Dynamics
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Climate extremes can severely impact socio-economic development. Climate trends of three temperature and three precipitation climate indices were evaluated in observational data, 23 models from the 5th Coupled Model Intercomparison Projects (CMIP5), and 20 models from CMIP6. The climate indices were calculated over the whole of China, and individually over the basins of its three major rivers. The indices are the spatio-temporal evolution characteristics of annual mean temperature (Tas), minimum of daily minimum temperature (TNn), maximum of daily maximum temperature (TXx), number of tropical nights (TR), daily precipitation (Pre), very heavy precipitation days (R20mm), maximum consecutive 5-day precipitation (Rx5day) and consecutive dry days (CDD). From 1961 to 2018, most of China has warmed; Tas, TNn, TXx and TR over China has increased by 1.7 °C, 2.8 °C, 1.1 °C and 9 days, respectively. Changes of Tas, TNn and TXx over the Yellow River Basin, Yangtze River Basin and Pearl River Basin were generally similar in sign. The most significant increase of TR was seen over the Pearl River Basin. Historical Tas was well reproduced by both CMIP5 and CMIP6 over the study regions, but obvious uncertainties exist in the simulation of Pre. In general, CMIP6 models were improved from CMIP5 models. Climate projections were calculated for the 2021–2100 period. Future warming over China would be stronger with higher SSP scenarios; TNn over China would warm seven times more under the SSP5-8.5 scenario (5.6 °C) compared to the SSP1-2.6 scenario. Future wetting over China would be stronger with higher the SSP scenarios; Under the SSP5-8.5 scenario, Pre, R20mm, Rx5day would increase by 28%, 150%, and 38%, respectively. Projected changes of CDD different by region—decreasing over most of China and the Yellow River Basin, but increasing over the Yangtze and Pearl River Basins. The higher of the emission scenario, the less significant the reduction of CDD over the two basins. This suggests that the temporal distribution of precipitation over China will become more uneven in the future, especially under the higher SSP scenarios.

ACS Style

Xian Zhu; Shao-Yi Lee; Xiaohang Wen; Zhenming Ji; Lei Lin; Zhigang Wei; Zhiyuan Zheng; Danya Xu; Wenjie Dong. Extreme climate changes over three major river basins in China as seen in CMIP5 and CMIP6. Climate Dynamics 2021, 1 -19.

AMA Style

Xian Zhu, Shao-Yi Lee, Xiaohang Wen, Zhenming Ji, Lei Lin, Zhigang Wei, Zhiyuan Zheng, Danya Xu, Wenjie Dong. Extreme climate changes over three major river basins in China as seen in CMIP5 and CMIP6. Climate Dynamics. 2021; ():1-19.

Chicago/Turabian Style

Xian Zhu; Shao-Yi Lee; Xiaohang Wen; Zhenming Ji; Lei Lin; Zhigang Wei; Zhiyuan Zheng; Danya Xu; Wenjie Dong. 2021. "Extreme climate changes over three major river basins in China as seen in CMIP5 and CMIP6." Climate Dynamics , no. : 1-19.

Communication
Published: 17 March 2021 in Remote Sensing
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To forecast the terrestrial carbon cycle and monitor food security, vegetation growth must be accurately predicted; however, current process-based ecosystem and crop-growth models are limited in their effectiveness. This study developed a machine learning model using the extreme gradient boosting method to predict vegetation growth throughout the growing season in China from 2001 to 2018. The model used satellite-derived vegetation data for the first month of each growing season, CO2 concentration, and several meteorological factors as data sources for the explanatory variables. Results showed that the model could reproduce the spatiotemporal distribution of vegetation growth as represented by the satellite-derived normalized difference vegetation index (NDVI). The predictive error for the growing season NDVI was less than 5% for more than 98% of vegetated areas in China; the model represented seasonal variations in NDVI well. The coefficient of determination (R2) between the monthly observed and predicted NDVI was 0.83, and more than 69% of vegetated areas had an R2 > 0.8. The effectiveness of the model was examined for a severe drought year (2009), and results showed that the model could reproduce the spatiotemporal distribution of NDVI even under extreme conditions. This model provides an alternative method for predicting vegetation growth and has great potential for monitoring vegetation dynamics and crop growth.

ACS Style

Xiangqian Li; Wenping Yuan; Wenjie Dong. A Machine Learning Method for Predicting Vegetation Indices in China. Remote Sensing 2021, 13, 1147 .

AMA Style

Xiangqian Li, Wenping Yuan, Wenjie Dong. A Machine Learning Method for Predicting Vegetation Indices in China. Remote Sensing. 2021; 13 (6):1147.

Chicago/Turabian Style

Xiangqian Li; Wenping Yuan; Wenjie Dong. 2021. "A Machine Learning Method for Predicting Vegetation Indices in China." Remote Sensing 13, no. 6: 1147.

Correction
Published: 06 February 2021 in Climate Dynamics
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ACS Style

Tianyun Dong; Wenjie Dong; Taichen Feng; Xian Zhu. Correction to: Reversed impacts of the Arctic oscillation on the precipitation over the South China Sea and its surrounding areas in October and November. Climate Dynamics 2021, 56, 2023 -2024.

AMA Style

Tianyun Dong, Wenjie Dong, Taichen Feng, Xian Zhu. Correction to: Reversed impacts of the Arctic oscillation on the precipitation over the South China Sea and its surrounding areas in October and November. Climate Dynamics. 2021; 56 (5-6):2023-2024.

Chicago/Turabian Style

Tianyun Dong; Wenjie Dong; Taichen Feng; Xian Zhu. 2021. "Correction to: Reversed impacts of the Arctic oscillation on the precipitation over the South China Sea and its surrounding areas in October and November." Climate Dynamics 56, no. 5-6: 2023-2024.

Article
Published: 09 October 2020 in Climate Dynamics
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The reversed impacts of the Arctic oscillation (AO) on precipitation over the South China Sea and its surrounding areas (SCSA) in October and November during 1979–2014 are investigated. The correlation coefficients between AO and the precipitation in October and November are 0.44 and − 0.31, which are statistically significant at the 99% and 90% confidence levels, respectively. In October (November), the specific humidity exhibits obvious positive (negative) anomalies in the SCSA, and an upward (downward) airflow moving from ground to the upper troposphere (1000–150 hPa) between 10°N and 30°N (10°N and 20°N) is observed with more (less) cloud cover. Moisture budget diagnosis suggests that the precipitation’s increasing (decreasing) in October (November) mainly contributed by zonal moisture flux convergence (divergence). Furthermore, the Rossby wave guided by westerlies tends to motivate positive geopotential height in the upper troposphere over approximately 20°–30°N, 40°–80°E in October, which is accompanied by a stronger anticyclone in the Arabian Sea region. However, in November, the wave train propagating from the Arabian Sea to the Bay of Bengal is observed in the form of cyclones and anticyclones. Further analysis reveal that the AO in October may increase precipitation through the southern wave train (along the westerly jet stream from North Africa to the Middle East and South China). Moreover, air-sea interactions over the North Pacific might also generate horseshoe-shaped sea surface temperature (SST) anomalies characterized by positive SST in the central subtropical North Pacific surrounded by negative SST, which may affect the precipitation in the SCSA. Ensemble-mean results from CMIP6 historical simulations further confirm these relationships, and the models that can better simulate the observed positive geopotential height in the Arabian Sea present more consistent precipitation’s increasing over the SCSA in October.

ACS Style

Tianyun Dong; Wenjie Dong; Taichen Feng; Xian Zhu. Reversed impacts of the Arctic oscillation on the precipitation over the South China Sea and its surrounding areas in October and November. Climate Dynamics 2020, 56, 65 -85.

AMA Style

Tianyun Dong, Wenjie Dong, Taichen Feng, Xian Zhu. Reversed impacts of the Arctic oscillation on the precipitation over the South China Sea and its surrounding areas in October and November. Climate Dynamics. 2020; 56 (1-2):65-85.

Chicago/Turabian Style

Tianyun Dong; Wenjie Dong; Taichen Feng; Xian Zhu. 2020. "Reversed impacts of the Arctic oscillation on the precipitation over the South China Sea and its surrounding areas in October and November." Climate Dynamics 56, no. 1-2: 65-85.

Journal article
Published: 25 May 2020 in Remote Sensing
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A shipborne micro-pulse lidar (Sigma Space Mini-MPL) was used to measure aerosol extinction coefficient over the northern region of the South China Sea from 9 August to 7 September 2016, the first time a mini-MPL was used for aerosol observation over the cruise region. The goal of the experiment was to investigate if the compact and affordable mini-MPL was usable for aerosol observation over this region. The measurements were used to calculate vertical profiles of volume extinction coefficient, depolarization ratio, and atmospheric boundary layer height. Aerosol optical depth (AOD) was lower over the southwest side of the cruise region, compared to the northeast side. Most attenuation occurred below 3.5 km, and maximum extinction values over coastal areas were generally about double of values offshore. The extinction coefficients at 532 nm (aerosol and molecular combined) over coastal and offshore areas were on average 0.04 km−1 and 0.02 km−1, respectively. Maximum values reached 0.2 km−1 and 0.14 km−1, respectively. Vertical profiles and back-trajectory calculations indicated vertical and horizontal layering of aerosols from different terrestrial sources. The mean volume depolarization ratio of the aerosols along the cruise was 0.04. The mean atmospheric boundary layer height along the cruise was 653 m, with a diurnal cycle reaching its mean maximum of 1041 m at 12:00 local time, and its mean minimum of 450 m at 20:00 local time. Unfortunately, only 11% of the measurements were usable. This was due to ship instability in rough cruise conditions, lack of stabilization rig, water condensation attached to the eye lens, and high humidity attenuating the echo signal. We recommend against the use of the mini-MPL in this cruise region unless substantial improvements are made to the default setup, e.g., instrument stabilization, instrument protection cover, and more theoretical work taking into account atmospheric gas scattering or absorption.

ACS Style

Yuan Li; Baomin Wang; Shao-Yi Lee; Zhijie Zhang; Ye Wang; Wenjie Dong. Micro-Pulse Lidar Cruising Measurements in Northern South China Sea. Remote Sensing 2020, 12, 1695 .

AMA Style

Yuan Li, Baomin Wang, Shao-Yi Lee, Zhijie Zhang, Ye Wang, Wenjie Dong. Micro-Pulse Lidar Cruising Measurements in Northern South China Sea. Remote Sensing. 2020; 12 (10):1695.

Chicago/Turabian Style

Yuan Li; Baomin Wang; Shao-Yi Lee; Zhijie Zhang; Ye Wang; Wenjie Dong. 2020. "Micro-Pulse Lidar Cruising Measurements in Northern South China Sea." Remote Sensing 12, no. 10: 1695.

Article
Published: 09 December 2019 in Climate Dynamics
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Using hindcast and forecast data from the National Centers for Environmental Prediction (NCEP) climate forecast system version 2 (CFSv2) for the period 1982–2017, we comprehensively assess the predictability of the climatology, interannual variability, and dominant modes of the wintertime 500 hPa height over Ural-Siberia (40–80° N and 30–100° E). Although the climatic mean 500 hPa height over Ural-Siberia simulated by NCEP CFSv2 has a negative bias, especially over the eastern part of the region, NCEP CFSv2 well predicts the spatial distribution of the two major modes (EOF1 and EOF2) over this region 2 months in advance. The forecasting skill of the principal component (PC) of the two major modes, PC1 (PC2), is highest 1 (0) month in advance, where the linear correlation coefficient between the predicted and observed time series reaches + 0.36 (+ 0.67), exceeding the 95% confidence level. Conversely, the forecasting skill of PC1 (PC2) is very low 0 (1) month in advance. The main reason for the poorer (better) prediction of PC1 0 (1) month in advance is associated with a less (more) accurate response of the Eurasian pattern to SST anomalies over the southwestern Atlantic. For PC2, the better (poorer) prediction of PC2 0 (1) month in advance may be due to more (less) accurate responses of the stratospheric polar vortex and the Scandinavian pattern to the dipole SST anomalies over the North Pacific. These results are useful for evaluating the predictability of the East Asian winter climate.

ACS Style

Shaobo Qiao; Meng Zou; Ho Nam Cheung; Wen Zhou; Qingxiang Li; Guolin Feng; Wenjie Dong. Predictability of the wintertime 500 hPa geopotential height over Ural-Siberia in the NCEP climate forecast system. Climate Dynamics 2019, 54, 1591 -1606.

AMA Style

Shaobo Qiao, Meng Zou, Ho Nam Cheung, Wen Zhou, Qingxiang Li, Guolin Feng, Wenjie Dong. Predictability of the wintertime 500 hPa geopotential height over Ural-Siberia in the NCEP climate forecast system. Climate Dynamics. 2019; 54 (3-4):1591-1606.

Chicago/Turabian Style

Shaobo Qiao; Meng Zou; Ho Nam Cheung; Wen Zhou; Qingxiang Li; Guolin Feng; Wenjie Dong. 2019. "Predictability of the wintertime 500 hPa geopotential height over Ural-Siberia in the NCEP climate forecast system." Climate Dynamics 54, no. 3-4: 1591-1606.

Journal article
Published: 09 November 2019 in Atmosphere
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This study evaluates 32 climate models from CMIP5 compared with a daily gridded observation dataset of extreme precipitation indices including total extreme precipitation (R95p), maximum consecutive five days of precipitation (RX5day) and wet days larger than 10 mm of precipitation (R10mm) over Northern China during the historical period (1986–2005). Results show the majority models have good performance on spatial distribution but overestimate the amplitude of precipitation over Northern China. Most models can also capture interannual variation of R95p and RX5d, but with poor simulations on R10mm. Considering both spatial and temporal factors, the best multi-model ensemble (Group 1) has been selected and improved by 42%, 34%, and 37% for R95p, RX5d, and R10mm, respectively. Projection of extreme precipitation indicates that the fastest-rising region is in Northwest China due to the enhanced rainfall intensity. However, the uncertainty analysis shows the increase of extreme rainfall over Northwest China has a low confidence level. The projection of increasing extreme rainfall over Northeast China from Group 1 due to the longer extreme rainfall days is more credible. The weak subtropical high and southwest winds from Arabian Sea lead to the low wet biases from Group 1 and the cyclonic anomalies over Northeast China, which result in more extreme precipitation.

ACS Style

Xiaoqiang Rao; Xi Lu; Wenjie Dong. Evaluation and Projection of Extreme Precipitation over Northern China in CMIP5 Models. Atmosphere 2019, 10, 691 .

AMA Style

Xiaoqiang Rao, Xi Lu, Wenjie Dong. Evaluation and Projection of Extreme Precipitation over Northern China in CMIP5 Models. Atmosphere. 2019; 10 (11):691.

Chicago/Turabian Style

Xiaoqiang Rao; Xi Lu; Wenjie Dong. 2019. "Evaluation and Projection of Extreme Precipitation over Northern China in CMIP5 Models." Atmosphere 10, no. 11: 691.

Journal article
Published: 15 August 2019 in Atmosphere
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Four cross-coupled models were used to investigate the relative contributions of atmospheric and oceanic components to the asymmetry of the El Niño–Southern Oscillation (ENSO). Strong El Niño and La Niña events related to the negative heat flux feedbacks were found to be determined mainly by the atmospheric component, and the stronger sea surface temperature (SST) anomalies in the warm phase did not lead to an increased SST asymmetry. The skewness of the four models could be affected by both atmospheric and oceanic components; the atmospheric component determines the strength of positive and negative SST anomalies, and the oceanic component affects the strength of the negative SST anomalies in the cold phase under the same atmospheric component group. The Bjerknes stability index (BJ index) of warm and cold phases contributed to the El Niño–La Niña SSTA asymmetries in observation, but the BJ index did not necessarily explain the El Niño–La Niña SSTA asymmetries in climate model simulations. The SST asymmetries in these four models were closely associated with convective precipitation and wind stress asymmetries, which are also determined by both the atmospheric and oceanic components.

ACS Style

Yanli Tang; Lijuan Li; Bin Wang; Pengfei Lin; Wenjie Dong; Kun Xia. The Collective Contribution of Atmospheric and Oceanic Components to ENSO Asymmetry. Atmosphere 2019, 10, 469 .

AMA Style

Yanli Tang, Lijuan Li, Bin Wang, Pengfei Lin, Wenjie Dong, Kun Xia. The Collective Contribution of Atmospheric and Oceanic Components to ENSO Asymmetry. Atmosphere. 2019; 10 (8):469.

Chicago/Turabian Style

Yanli Tang; Lijuan Li; Bin Wang; Pengfei Lin; Wenjie Dong; Kun Xia. 2019. "The Collective Contribution of Atmospheric and Oceanic Components to ENSO Asymmetry." Atmosphere 10, no. 8: 469.

Journal article
Published: 21 December 2018 in Sustainability
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Understanding the temporal and spatial distribution in disasters plays an important role in disaster risk management. The present study aims to explore the long-term trends in drought and floods over China and estimate the economic losses they cause. A peak-over-threshold approach is used to identify flood peaks, and the relationship between the disasters and climate indices is investigated using Poisson regression. The major results are as follows: (1) the northeastern part of China was severely affected by drought disasters (average damaged area was 6.44 million hectares); (2) the northern part of East China and Central China upstream of the Yangtze River were severely affected by flood disasters (average damaged area was 3.97 million hectares); (3) in the Yangtze River Basin, there are increasing trends in terms of drought and extreme precipitation, especially upstream of the Yangtze River, accompanied by severe disaster losses; and (4) by combining the trends in drought and extreme precipitation days with the spatial distribution of damaged areas, the study indicates that the increasing trend in droughts has shifted gradually from north to south, and the increasing trend in extreme precipitation gradually has shifted from south to north.

ACS Style

Jieming Chou; Tian Xian; Wenjie Dong; Yuan Xu. Regional Temporal and Spatial Trends in Drought and Flood Disasters in China and Assessment of Economic Losses in Recent Years. Sustainability 2018, 11, 55 .

AMA Style

Jieming Chou, Tian Xian, Wenjie Dong, Yuan Xu. Regional Temporal and Spatial Trends in Drought and Flood Disasters in China and Assessment of Economic Losses in Recent Years. Sustainability. 2018; 11 (1):55.

Chicago/Turabian Style

Jieming Chou; Tian Xian; Wenjie Dong; Yuan Xu. 2018. "Regional Temporal and Spatial Trends in Drought and Flood Disasters in China and Assessment of Economic Losses in Recent Years." Sustainability 11, no. 1: 55.

Journal article
Published: 05 June 2018 in Sustainability
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Climate policy plays an important role in keeping global temperature rises below the target of 1.5–2 °C above pre-industrial levels, and technological innovations are key to determining the effectiveness of climate policy. In this study, we investigated the climate impact of the USA’s policy choices using the enforced multi-factor regional climate and economy system (EMRICES,) and the Earth system model from Beijing Normal University (BNU-ESM). Three emission scenarios were designed based on the assumption of whether or not the US follows its proposed nationally determined contribution (NDC) and makes use of technological innovations. The results showed that if the US does not implement the NDC and had no technological progress, there would be an extra 176.7 Gt of cumulative carbon emissions by the end of the 21st century compared to that of all the countries that follow their NDC. The additional emissions would lead to an increase of 62 ppm in CO2 concentration and a 0.4 °C increase in global warming by 2100. It would also lead to a 2% loss for the US and Chinese economies, compared to the NDC scenario. The Earth system model results also show that even if all the countries follow the DNC, it would be difficult to keep the temperature from increasing less than 1.5 °C. This study implies that the US withdrawal from the Paris Agreement and their refusal to adopt technological progress is not conducive to achieving the 1.5 °C goal, and more stringent emission reduction targets or technology innovations would be required for the world to control global warming to a level below 1.5 °C.

ACS Style

Shili Yang; Changxin Liu; Wenjie Dong; Jieming Chou; Di Tian; Ting Wei; Yuan Tian. Quantifying the Climate Impact of the US Policy Choices Using an Economic and Earth System Model. Sustainability 2018, 10, 1884 .

AMA Style

Shili Yang, Changxin Liu, Wenjie Dong, Jieming Chou, Di Tian, Ting Wei, Yuan Tian. Quantifying the Climate Impact of the US Policy Choices Using an Economic and Earth System Model. Sustainability. 2018; 10 (6):1884.

Chicago/Turabian Style

Shili Yang; Changxin Liu; Wenjie Dong; Jieming Chou; Di Tian; Ting Wei; Yuan Tian. 2018. "Quantifying the Climate Impact of the US Policy Choices Using an Economic and Earth System Model." Sustainability 10, no. 6: 1884.

Journal article
Published: 01 January 2015 in Atmospheric and Oceanic Science Letters
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Xiu Jin-Feng; Chou Jie-Ming; Dong Wen-Jie; Yang Zhi-Yong; Dai Ru-Feng. Carbon Reduction Policies: A Regional Comparison of Their Contributions to CO2Abatement in Six Carbon Trading Pilot Schemes in China. Atmospheric and Oceanic Science Letters 2015, 8, 233 -237.

AMA Style

Xiu Jin-Feng, Chou Jie-Ming, Dong Wen-Jie, Yang Zhi-Yong, Dai Ru-Feng. Carbon Reduction Policies: A Regional Comparison of Their Contributions to CO2Abatement in Six Carbon Trading Pilot Schemes in China. Atmospheric and Oceanic Science Letters. 2015; 8 (4):233-237.

Chicago/Turabian Style

Xiu Jin-Feng; Chou Jie-Ming; Dong Wen-Jie; Yang Zhi-Yong; Dai Ru-Feng. 2015. "Carbon Reduction Policies: A Regional Comparison of Their Contributions to CO2Abatement in Six Carbon Trading Pilot Schemes in China." Atmospheric and Oceanic Science Letters 8, no. 4: 233-237.

Journal article
Published: 01 September 2013 in Advances in Climate Change Research
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ACS Style

Guo Yan; Dong Wen-Jie; Ren Fu-Min; Zhao Zong-Ci; Huang Jian-Bin. Surface Air Temperature Simulations over China with CMIP5 and CMIP3. Advances in Climate Change Research 2013, 4, 145 -152.

AMA Style

Guo Yan, Dong Wen-Jie, Ren Fu-Min, Zhao Zong-Ci, Huang Jian-Bin. Surface Air Temperature Simulations over China with CMIP5 and CMIP3. Advances in Climate Change Research. 2013; 4 (3):145-152.

Chicago/Turabian Style

Guo Yan; Dong Wen-Jie; Ren Fu-Min; Zhao Zong-Ci; Huang Jian-Bin. 2013. "Surface Air Temperature Simulations over China with CMIP5 and CMIP3." Advances in Climate Change Research 4, no. 3: 145-152.