Article
Environmental Sciences
Nathan Beech, Thomas Rackow, Tido Semmler, Sergey Danilov, Qiang Wang, Thomas Jung
Summary: This study investigates the long-term response of ocean eddy activity to anthropogenic climate change using a climate model. The results show that eddy kinetic energy will shift poleward in eddy-rich regions and intensify in certain current regions while decreasing in the Gulf Stream. These changes are linked to broader climate factors such as the decline in Atlantic meridional overturning circulation, intensified Agulhas leakage, and shifting Southern Hemisphere westerlies.
NATURE CLIMATE CHANGE
(2022)
Review
Meteorology & Atmospheric Sciences
Guidi Zhou, Xuhua Cheng
Summary: This paper reviews the progress in understanding the atmospheric response to midlatitude oceanic fronts and eddies, with a focus on the Kuroshio-Oyashio Extension (KOE) region. Oceanic fronts play a significant role in maintaining the storm track, but current research is still subject to uncertainties arising from inadequate data resolution.
ADVANCES IN ATMOSPHERIC SCIENCES
(2022)
Review
Oceanography
Lionel Renault, James C. McWilliams, Faycal Kessouri, Alexandre Jousse, Hartmut Frenzel, Ru Chen, Curtis Deutsch
Summary: This paper presents a 16-year hindcast solution of the California Current System using a coupled physical and biogeochemical model along the U.S. West Coast. The model is validated against various fields and shows good agreement with observational data. The simulation highlights the importance of high-resolution atmospheric and oceanic models for accurately representing oceanic processes and interactions.
PROGRESS IN OCEANOGRAPHY
(2021)
Article
Meteorology & Atmospheric Sciences
E. E. Tsartsali, R. J. Haarsma, P. J. Athanasiadis, A. Bellucci, H. de Vries, S. Drijfhout, I. E. de Vries, D. Putrahasan, M. J. Roberts, E. Sanchez-Gomez, C. D. Roberts
Summary: This study investigates the resolution dependence of ocean-atmosphere coupling along the Gulf Stream using six Global Climate Models. It explores two interaction mechanisms and finds that increasing resolution leads to stronger coupling and better agreement with observations.
Article
Meteorology & Atmospheric Sciences
Clea Denamiel, Iva Tojcic, Ivica Vilibic
Summary: The study indicates that kilometer-scale atmospheric models should be used to properly reproduce dense water formation during severe bora events and the long-term thermohaline circulation in the Adriatic-Ionian basin.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2021)
Article
Multidisciplinary Sciences
Eitarou Oka, Shusaku Sugimoto, Fumiaki Kobashi, Hatsumi Nishikawa, Sachie Kanada, Tomoe Nasuno, Ryuichi Kawamura, Masami Nonaka
Summary: In the subtropical North Pacific Ocean, the thickness variation of Subtropical Mode Water (STMW) affects the thermal structure above and has significant impacts on sea surface temperature, upper ocean heat content, and typhoon intensification rate, making it crucial for understanding climate change.
Article
Astronomy & Astrophysics
Mina Rohanizadegan, Richard M. Petrone, John W. Pomeroy, Branko Kosovic, Domingo Munoz-Esparza, Warren D. Helgason
Summary: This study focuses on improving the accuracy of calculating land-atmosphere fluxes of heat and water vapor in mountain terrain by better resolving thermally driven diurnal winds. A weather research and forecasting model was used to simulate the flow in large-eddy simulation mode over two research basins in the Canadian Rockies. The study found that a local smoothing approach can effectively reduce numerical errors and instability when simulating flow over steep terrain. Additionally, the geometry and volume of valleys are relevant to the breakup of inversion layers, removal of cold-air pools, and strength of thermally driven winds.
EARTH AND SPACE SCIENCE
(2023)
Article
Oceanography
Guidi Zhou, Xuhua Cheng
Summary: This paper evaluates the importance of residual kinetic energy (RKE) in ocean energetics, proposing methods for its assessment and handling, including Reynolds decomposition and spectral truncation. Through practical ocean observations, variations in MREE under different conditions were identified, highlighting the necessity of estimating MREE before analyzing energy budgets.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2021)
Article
Oceanography
Bowen Sun, Baofu Li, Jingyu Yan, Yuqi Zhou, Shuo Zhou
Summary: This study investigates the seasonal variation in the atmospheric response to oceanic mesoscale eddies in the North Pacific Subtropical Countercurrent, with findings showing that the impact of eddies on sea surface temperature and wind speed is stronger in winter, while their effect on precipitation rate is more significant in summer.
ACTA OCEANOLOGICA SINICA
(2022)
Article
Materials Science, Coatings & Films
Rodion Zhukovskii, Christophe Chazelas, Vincent Rat, Armelle Vardelle, Ronald J. Molz
Summary: In a DC plasma spray torch, the cathode arc attachment, which is highly heated and accelerated, plays a crucial role in plasma jet formation and cathode operation. However, most numerical studies focus on transferred arcs or conventional plasma torches. In this study, a 3D time-dependent two-temperature model of electric arc combined with a cathode sheath model is used to investigate the effect of the cathode sheath model and bidirectional cathode-plasma coupling on the predicted cathode arc attachment and plasma flow. The results show that including the cathode sheath model improves the accuracy and reliability of the predictions.
JOURNAL OF THERMAL SPRAY TECHNOLOGY
(2023)
Article
Energy & Fuels
Junpeng Ma, Feiyan Liu, Chenggang Xiao, Kairan Wang, Zirui Liu
Summary: A high-resolution wind resource assessment method for wind farms based on mesoscale atmospheric model and CFD technology is studied to accurately simulate relevant data of wind resources and improve the assessment effect. The mesoscale WRF numerical model is used to solve the regional data of wind farms and obtain the mesoscale meteorological analysis data. The CFD micro scale model is utilized to obtain the wind speed and wind speed frequency at the height of the fan impeller, and the large eddy simulation method is employed to simulate the operation of wind farms.
Article
Remote Sensing
Hee-Ae Kim, Sung-Rae Chung, Soo Min Oh, Byung-Il Lee, In-Chul Shin
Summary: This paper examines the impact of the temporal gap between satellite images and target size on the mesoscale atmospheric motion vector (AMV) algorithm. The study suggests that shorter temporal gaps and smaller target sizes are advantageous for AMV calculations in the lower layer of the atmosphere.
KOREAN JOURNAL OF REMOTE SENSING
(2021)
Article
Meteorology & Atmospheric Sciences
Jianlin Yong, Shaoqing Zhang, Zhengyu Liu, Yang Gao, Lixin Wu, Jianping Li, Lv Lu, Yingjing Jiang, Xiaolin Yu, Mingkui Li, Haoran Zhao, Xiaopei Lin
Summary: This study examines the linear behaviors of initial-value, boundary-value and joint initial-boundary-value predictability using the anomaly correlation coefficients between system states. It finds that boundary-value predictability efficiently extends the total predictability when the prediction skill induced from external forcing exceeds the skill from the initial condition.
Article
Meteorology & Atmospheric Sciences
Rong-Hua Zhang, Guanghui Zhou, Hai Zhi, Chuan Gao, Hongna Wang, Licheng Feng
Summary: This study examines the salinity variability and its relationship with temperature in the western equatorial Pacific. The results show pronounced interdecadal variations in salinity, accompanied by surface freshening and warming in the 1980s and 1990s, and saltening and cooling in the 2000s. The combined effects of temperature and salinity can be density-compensated or density-uncompensated, depending on the anomaly signs. The effects are phase- and depth-dependent, with different relationships observed in the subsurface and surface layers.
Article
Meteorology & Atmospheric Sciences
Junya Hu, Hongna Wang, Chuan Gao, Lu Zhou, Rong-Hua Zhang
Summary: This study examines the role of interdecadal wind stress variability in the genesis of ENSO diversity using an intermediate coupled model (ICM) in the tropical Pacific. The results show that when the interdecadal wind stress effect is included, the simulated ENSO events become highly irregular with interdecadal variations in the amplitude and asymmetry. Furthermore, the study illustrates the different roles of the Interdecadal Pacific Oscillation (IPO) in modulating different types of El Nino.
Correction
Meteorology & Atmospheric Sciences
Junya Hu, Hongna Wang, Chuan Gao, Lu Zhou, Rong-Hua Zhang
Article
Environmental Sciences
Yuankang Ye, Feng Gao, Wei Cheng, Chang Liu, Shaoqing Zhang
Summary: Convolution-based recurrent neural networks and convolutional neural networks are widely used in spatiotemporal prediction. However, they tend to focus on fixed-scale state transitions and overlook the complexity of spatiotemporal motion. Through statistical analysis, the researchers propose a Multi-scale Spatiotemporal Neural Network (MSSTNet) based on 3D convolution, which achieves state-of-the-art results in spatiotemporal prediction tasks and demonstrates positive significance for precipitation nowcasting.
Article
Environmental Sciences
Yuhang Jiang, Wei Cheng, Feng Gao, Shaoqing Zhang, Chang Liu, Jingzhe Sun
Summary: This paper proposes a deep learning method for predicting satellite observation images and achieves excellent predictive performance for the FY-4A satellite. By combining the multi-band prediction results, the method is also able to accurately detect precipitation areas.
Article
Geosciences, Multidisciplinary
Chuan Gao, Lu Zhou, Rong-Hua Zhang
Summary: In this study, a purely data-driven and transformer-based model is used to successfully predict the second-year cooling conditions following the 2020 La Nina event. The reasons for the successful prediction are comprehensively explored through sensitivity experiments and comparison analysis. The study demonstrates the potential of deep learning-based purely data-driven models in El Nino and Southern Oscillation research.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Multidisciplinary Sciences
Chenyu Zhu, Zhengyu Liu, Shaoqing Zhang, Lixin Wu
Summary: An optimal salinity fingerprint is proposed to detect the long-term Atlantic meridional overturning circulation (AMOC) response to anthropogenic forcing. A real-word application suggests a likely accelerated weakening of the AMOC in recent decades. Our study provides observational and modeling evidence for a likely accelerated weakening of the AMOC since the 1980s under the combined forcing of anthropogenic greenhouse gases and aerosols. This finding has significant implications for understanding the future climate impacts associated with AMOC weakening.
NATURE COMMUNICATIONS
(2023)
Article
Oceanography
Qidong Shi, Rong-Hua Zhang, Feng Tian
Summary: This study investigates the effects of the deep chlorophyll maximum (DCM) on the ocean state in the equatorial Pacific Ocean using a coupled ocean general circulation model (OGCM)-ocean ecosystem model. The results show that DCM acts to reduce mean sea surface temperature (SST) in the eastern equatorial Pacific and increase the amplitude of El Nino-Southern Oscillation (ENSO). Two competing mechanisms, including direct warming and indirect cooling, are identified to be responsible for the DCM effects.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2023)
Article
Oceanography
Lingjiang Tao, Mu Mu, Lei Wang, Xianghui Fang, Wansuo Duan, Rong-Hua Zhang
Summary: Perturbations in the thermocline and surface zonal current have significant impacts on the evolutions of EP and CP El Nino events. Studies have mainly focused on the influence of initial uncertainties in ocean temperature, while the impact of initial zonal current has been less explored. Using a coupled air-sea model, this study found that the optimal initial zonal current errors with the severest impact on El Nino prediction are mainly concentrated in the western and central tropical Pacific. These errors cause larger prediction errors for CP El Nino than for EP El Nino. By reducing the initial zonal current errors in these regions, the predictability barrier phenomena of El Nino can be weakened and the predictions of El Nino diversity can be improved.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2023)
Article
Multidisciplinary Sciences
Lu Zhou, Rong-Hua Zhang
Summary: A self-attention-based neural network model called 3D-Geoformer is developed for ENSO predictions, which achieves high correlation skills and has great potential for multidimensional spatiotemporal modeling in geoscience.
Article
Engineering, Marine
Kai Mao, Chang Liu, Shaoqing Zhang, Feng Gao
Summary: This study proposes an intelligent algorithm based on Dual Path Convolutional Neural Networks (DP-CNNs) to reconstruct the subsurface temperature (ST) and subsurface salinity (SS) using sea surface information. The DP-CNN models have higher reconstruction accuracy than the traditional CNN models and effectively mitigate the loss of detailed information.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Environmental Sciences
Yuhang Jiang, Feng Gao, Shaoqing Zhang, Wei Cheng, Chang Liu, Shudong Wang
Summary: Accurate precipitation forecasting is crucial for disaster prevention and mitigation. In this study, a multi-channel satellite precipitation forecasting network (MCSPF-Net) based on 3D convolutional neural networks is proposed. By using real-time multi-channel satellite observations, the network can forecast precipitation for the next 4 hours with wide coverage. Experimental results show that MCSPF-Net has a high correlation with the Global Precipitation Measurement product and outperforms the numerical weather prediction model in terms of critical success index, correlation coefficients, and mean square error. Therefore, the multi-channel satellite observation-driven MCSPF-Net proves to be an effective approach for near future precipitation forecasting.
Article
Oceanography
Feng Tian, Rong-Hua Zhang
Summary: Shortwave penetration (Q(pen)) through the bottom of the oceanic mixed layer has a profound impact on the thermal structure in the upper ocean and contributes to sea surface temperature change. Using ensemble earth system model simulations, we found that globally averaged Q(pen) increased in the second half of the 21st century, leading to surface cooling but also warming the mixed layer through ocean dynamical change. Recognizing the role played by Q(pen) is essential for understanding the global oceanic mixed layer heat balance.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2023)
Article
Oceanography
Zikuan Lin, Shaoqing Zhang, Zhengguang Zhang, Xiaolin Yu, Yang Gao
Summary: This study aims to interpret the predictive ability of machine learning models in Earth sciences and establish a connection between the models and physical mechanisms through physical equations. The research findings show that the ML model's skill in predicting Rossby normal modes partially explains its skill in predicting SLA, providing a clearer understanding of how the model operates and arrives at its forecasts.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2023)
