Dynamics of Atmospheres and Oceans最新文献

{"title":"Improvement of finescale parameterization through reducing uncertainty in spectrum estimation","authors":"Shumin Jiang ,&nbsp;Dejun Dai ,&nbsp;Dingqi Wang ,&nbsp;Jia Deng ,&nbsp;Jia Sun ,&nbsp;Ying Li ,&nbsp;Jingsong Guo ,&nbsp;Fangli Qiao","doi":"10.1016/j.dynatmoce.2025.101545","DOIUrl":"10.1016/j.dynatmoce.2025.101545","url":null,"abstract":"<div><div>Finescale parameterization (FP) is employed widely to estimate the large-scale distribution of internal wave-induced mixing, which is crucially important for the development of ocean general circulation models. In this study, FP performance was evaluated using hydrographic and microstructure measurements extracted from the Microstructure Program dataset. A general tendency of overestimation with increase in the estimated internal wave energy level was observed. Using the Monte Carlo method, the turbulent dissipation rates under prescribed spectra were estimated to illustrate how uncertainty in spectrum estimation contributes to the bias. The overestimation tendency was replicated under the FP by the commonly used periodogram spectral method. By replacing the periodogram method with an autoregressive (AR) spectral estimator, the overestimation tendency was reduced considerably. Application of FP with the AR method to the collected hydrographic data greatly reduced the bias, with the root mean square error reducing from 0.72 to 0.46, the variance of the bias decreasing from 0.57 to 0.23, and the correlation of the bias with the internal wave energy level reducing from 0.62 to 0.32, in base-10 logarithmic coordinates. Application of FP with the AR spectrum estimator would help in estimating diapycnal mixing within the ocean interior more accurately and increase the robustness of FP.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101545"},"PeriodicalIF":1.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying climate change-driven variations in projected wind condition in the Gulf of Guinea","authors":"Adeola M. Dahunsi ,&nbsp;Frederic Bonou ,&nbsp;Olusegun A. Dada ,&nbsp;Ezinvi Baloïtcha","doi":"10.1016/j.dynatmoce.2025.101543","DOIUrl":"10.1016/j.dynatmoce.2025.101543","url":null,"abstract":"<div><div>Understanding wind climate dynamics in the Gulf of Guinea (GoG) is critical for addressing climate-related challenges and supporting sustainable development in the region. This study evaluates the wind climate using observational buoy data from the PIRATA network and multiple General Circulation Models (GCMs) under historical and future Representative Concentration Pathway (RCP 8.5) scenarios. An ensemble dataset, constructed as the average of GCM outputs, was validated against PIRATA buoy measurements and demonstrated better performance to individual GCMs. The study revealed distinct temporal and spatial variability in wind conditions across the dry and rainy seasons during the baseline period (1961–2014). Projections under RCP 8.5 for mid-century (2026–2060) and end-century (2066–2100) consistently indicate increasing wind speeds, with the most significant changes projected during the rainy season. These findings highlight the critical role of ensemble modelling in mitigating biases inherent in individual datasets and its contribution to a robust understanding of wind dynamics in the region. The observed trends have significant implications for coastal upwelling, maritime safety, renewable energy development, and climate resilience strategies in the GoG. This study highlights the necessity of fine-scale spatio-temporal modelling to improve predictions and guide evidence-based adaptive strategies to mitigate climate change impacts on coastal ecosystems and vulnerable communities.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101543"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Weibull distribution and stable energy concept for numerical solutions of random wave heights","authors":"Nga Thanh Duong ,&nbsp;Loc Xuan Luu ,&nbsp;Linh Hoang Tran ,&nbsp;Khiem Quang Tran","doi":"10.1016/j.dynatmoce.2025.101544","DOIUrl":"10.1016/j.dynatmoce.2025.101544","url":null,"abstract":"<div><div>This study focuses on developing a new energy dissipation model and a corresponding solution for random wave height transformation based on stable energy theory and the Weibull distribution. Eight previously established breaking wave height formulas will be evaluated for compatibility with the new numerical solution in predicting wave height. A range of evaluation criteria (e.g., relative root-mean-square error (<em>RRMSE</em>), root-mean-square error (<em>RMSE</em>), mean absolute error (<em>MAE</em>), and standard deviation (<em>ν</em>)) will be applied to verify the reliability of the developed energy dissipation model alongside 13 existing models, using a large dataset of up to 6007 data points collected from 11 historical experiments. The results indicate that the NK1 solution for wave height transformation derived from the new energy dissipation model DB1 performs best in wave height prediction, with optimal shape and scale parameters of 1.53 and 0.83, respectively. The use of the DB1 model (or, equivalently, the NK1 solution) reduces errors compared to the 13 existing models by 8.1–69.4 % for <em>RRMSE</em>. For other evaluation criteria, DB1 also consistently outperforms the existing models. The findings further suggest that the stable energy concept is a feasible approach despite receiving limited attention from researchers. Additionally, the Weibull distribution is recommended for developing energy dissipation models or solutions for irregular wave height transformation. Therefore, the newly developed DB1 model and corresponding NK1 solution are strongly recommended for calculating random wave height transformation.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101544"},"PeriodicalIF":1.9,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing coastal wind simulation in the WRF model: Updates in sea surface temperature and roughness length through dynamic boundary conditions","authors":"Chunlei Wu ,&nbsp;Nina Wang ,&nbsp;Yan Zhao ,&nbsp;Xue Dong ,&nbsp;Wei Huang","doi":"10.1016/j.dynatmoce.2025.101542","DOIUrl":"10.1016/j.dynatmoce.2025.101542","url":null,"abstract":"<div><div>This study develops a dynamic lateral boundary condition for the Weather Research and Forecasting (WRF) model by integrating updates to sea surface temperature (SST) and roughness length (Z₀). By incorporating an ocean model and roughness schemes, time-varying SST and Z₀ were employed to enhance wind simulations over coastal areas. The results demonstrate significant improvements in the accuracy of wind speed and direction simulations, with consistent error reduction across observations. Statistical metrics, including correlation coefficients, mean bias, and root mean square error, highlight these improvements and underscore the need for continuous refinement of boundary conditions to ensure reliable meteorological forecasts. The impact of SST and Z₀ updates is particularly notable under stable atmospheric stratification, where they reduce wind speeds near the sea surface and exhibit spatial and temporal variability, with coastal regions responding more strongly than offshore areas. Additionally, the concurrent application of Z₀ updates mitigates anomalies that might arise from SST updates alone, emphasizing the importance of integrating both parameters for balanced and robust simulations. Overall, this work provides critical insights into the role of boundary condition updates in advancing offshore wind simulations, contributing to more informed decision-making and improved efficiency in wind energy generation.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101542"},"PeriodicalIF":1.9,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting ionospheric VTEC in the Indian equatorial and low-latitude region amid geomagnetic storms using the VECM model","authors":"Sumitra Padmanabhan ,&nbsp;Daivik Padmanabhan ,&nbsp;Yogesh Jadhav ,&nbsp;Harsh Taneja","doi":"10.1016/j.dynatmoce.2025.101541","DOIUrl":"10.1016/j.dynatmoce.2025.101541","url":null,"abstract":"<div><div>Geomagnetic storms are one of the major causes of irregular variations in the ionosphere. The effect of a geomagnetic storm on Vertical Total Electron Content (VTEC) variation, especially in the equatorial regions, is very complex and uncertain due to the Equatorial Ionization Anomaly (EIA). Thus, the VTEC exhibits large and complex spatio-temporal variations in the equatorial region. A deeper study of the relationship between the past values of geomagnetic storm variables and the present value of VTEC, and vice versa can help better understand the dynamics of the variables and processes’ long-term equilibrium between the variables. Causal dependence between the variables has been found helpful in determining the temporal dependencies in econometrics where parameters are uncertain, and variability patterns are complex. In this study, causality was used for investigating the impact of the highly complex geomagnetic processes on VTEC. Causality between the geomagnetic indices and deviation in VTEC was investigated to understand the interconnection between the dynamical variables, the nonlinear correlations between them, and the underlying physical processes to predict the deviation in VTEC. Based on causality, a Vector Error-Correction (VECM) forecast model was developed for a two-step ahead forecast of VTEC on geomagnetic storm days. The forecast results were compared with the actual values of GPS VTEC and the International Reference Ionosphere (IRI) model. Two metrics, namely RMSE and the correlation coefficient, were used to test the performance. The forecasted values were compared with the actual values, and the RMSE and correlation coefficients were calculated. The model’s performance was also compared with the reference model IRI 2016. For most of the days, the model could predict with low RMSE for two-step-ahead prediction (1 h).</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101541"},"PeriodicalIF":1.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the connection between large-scale climate indices and rainfall variability in Iraq","authors":"Sherien Fadhel ,&nbsp;Dawei Han","doi":"10.1016/j.dynatmoce.2025.101540","DOIUrl":"10.1016/j.dynatmoce.2025.101540","url":null,"abstract":"<div><div>This study investigates the teleconnection between climate indices and rainfall variability in Iraq to identify the factors influencing rainfall variability. The correlation between seven climate indices and rainfall variability across eight Iraqi cities was analyzed for the period 1951–2020, with a focus on January, the month with the highest amount of rainfall for most cities in the country. Bivariate wavelet coherence (WTC) and improved partial wavelet coherence (IPWC) methods were adopted for the analysis, and the significance of the correlations was quantified by the percentage of significant coherence (PoSC). The study aimed to determine whether specific climate indices have major connection with rainfall variability in Iraq, and whether this connection is identified through integration with other indices (i.e. using WTC), or by removing the mutual dependence of these climate indices (i.e. using IPWC). Results indicated that IPWC generally yielded a higher PoSC than WTC. The highest PoSC for the IPWC was achieved not by eliminating all climate indices but by selectively removing certain indices while retaining others. For instance, each of the three indices (PDO, AMO, DMI) produced the highest PoSC by removing four climate indices and keeping both the SOI and the NAO. In addition, the correlation between the reconstructed rainfall and the seven climate indices on different frequency bands explains and confirms the results of deleting some indices and keeping others to gain the greatest revelation on rainfall variability since no single dominant index can fully explain such rainfall variation. In addition, the combined NAO &amp; SOI indices found to be the main connection with rainfall variability over Iraq, especially when this combination is linked to any SST indices. However, the second driver of rainfall variability over Iraq was revealed by the combined WeMO &amp; SOI indices when they are linked to any climate indices. The above findings were found to be helpful and improved the accuracy of rainfall prediction. This study on searching for the drivers that affect the rainfall variation through multiple Large-Scale Climate Oscillation (LSCO) indices is the first in Iraq, and it has importance for other studies such as rainfall prediction, flooding analysis, and flooding mitigation.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101540"},"PeriodicalIF":1.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Projected changes in wind speed and wind energy resources over the Persian Gulf based on bias corrected CMIP6 models","authors":"Amirmahdi Gohari ,&nbsp;Adem Akpınar","doi":"10.1016/j.dynatmoce.2025.101539","DOIUrl":"10.1016/j.dynatmoce.2025.101539","url":null,"abstract":"<div><div>This study investigates future wind speed and wind energy changes in the Persian Gulf using a multi-model ensemble mean (MMM) derived from 20 CMIP6 models under the SSP5–8.5 scenario. ERA5 reanalysis wind speed data for the historical period (1995–2015) is compared to projections for the mid-future (2040–2059) and far-future (2080–2099). Quantile mapping based on Weibull distribution as a bias correction technique applied to the raw future data to obtain more reliable projections. Results show suitable wind conditions for power generation are expected to increase slightly, by 1.16 % in the mid-future and 0.75 % in the far-future. However, average annual wind speed and wind power density are projected to decrease by up to 2 % and 7 % respectively. The winter season is consistently shown to have the highest average wind speed, projected to increase over 5–7 % in the future. Spatial analysis identifies current and future wind energy hot spots, with a northward shift by the far-future. Assessments of variability over time highlight potential future alterations. The future change analysis reveals irregular regional shifts, indicating decreases in wind strength nearshore in the northern Gulf, while the southern part may experience increases, suggesting a promising trend for wind energy potential there.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101539"},"PeriodicalIF":1.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Future projections of climate variables and meteorological drought: Insight from CMIP6 models in Southeast Ethiopia","authors":"Amanuel Tsegaye Tadase ,&nbsp;Andinet Kebede Tekile","doi":"10.1016/j.dynatmoce.2025.101538","DOIUrl":"10.1016/j.dynatmoce.2025.101538","url":null,"abstract":"<div><div>Climate change has profound effects on precipitation, temperature, and meteorological drought patterns. This study addressed the knowledge gap regarding the future impacts of climate change on these variables in the Arsi Zone, Southeast Ethiopia. By utilizing data simulation from the Coupled Model Intercomparison Phase six (CMIP6) under two shared socioeconomic pathways (SSP2–4.5 and SSP5–8.5), future climatic conditions were projected. The quantile mapping (QM) bias correction technique was implemented in R to improve reliability. The nonparametric Mann–Kendall method and the standardized precipitation index (SPI-3) were employed for the climate variables trend analysis and to estimate drought characteristics, respectively. The findings of this study indicated an increasing trend in future precipitation and maximum temperature across both socioeconomic pathway scenarios from 2020 to 2100, with a more pronounced increase under the SSP5–8.5 scenario. The drought duration, severity, and intensity were also projected to increase from 1985–2014–2020–2049 under both scenarios. The intensity increased by 0.26 and 0.15 under SSP2–4.5 and SSP5–8.5, respectively; however, these values exhibited different trends in the two scenarios from 2020 to 2049–2080–2100. The SSP2–4.5 scenario suggested more frequent drought events, requiring specific strategies for water resource management. However, the SSP5–8.5 scenario exhibited variability in drought projections. As conclusion, there is a need for specific strategies to address the more frequent drought events projected under the SSP2–4.5 scenario, whereas the SSP5–8.5 scenario requires adaptable strategies due to the variable frequencies and it underlines the urgent need for comprehensive adaptation and mitigation strategies.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101538"},"PeriodicalIF":1.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate variability and heat wave dynamics in India: Insights from land- atmospheric interactions","authors":"C.S. Neethu,&nbsp;B. Abish","doi":"10.1016/j.dynatmoce.2025.101537","DOIUrl":"10.1016/j.dynatmoce.2025.101537","url":null,"abstract":"<div><div>Heat waves have emerged as one of the most severe and destructive meteorological phenomena, significantly threatening human health, agricultural productivity, and ecosystems due to their increasing frequency, duration, and intensity. In India, these extreme events predominantly occur during the pre-monsoon months (March to mid-June), with recent years (2016, 2019, 2022, and 2023) showing a clear intensification in their occurrence. This study aims to explore the dynamics of heat waves, synoptic conditions, surface land-atmosphere interactions, and regional variations in recent years across India, utilizing maximum temperature data from the India Meteorological Department (IMD) and heat wave indices to evaluate their intensity and impact. Analysis of maximum temperature data and heatwave indices highlights a notable rise in heatwave frequency and duration, particularly in northern and central India. The 2-meter (2 m) temperature anomaly in north, central, and southern India exceeded 2.5°C, while the 925hPa temperature showed significant warming trends in north and northwest India. The analysis of the spatial distribution of the planetary boundary layer (PBL) and total cloud cover (TCC) indicates reduced cloud cover and an increased PBL, intensifying heat wave conditions across north and central regions. The warm air advection and sinking air in the descending limb of the Walker circulation ensured a stable and drier atmosphere, favoring heatwave conditions. Moreover, a persistent anticyclonic circulation and its associated high-pressure system enabled heat-trapping within the atmosphere, leading to prolonged and intensified heat wave conditions. The study indicates a shift in the position and strength of the subtropical jet stream (STJ) during these years, highlighting its significant role in developing and intensifying heat waves.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101537"},"PeriodicalIF":1.9,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Satellite-derived ocean color data for monitoring pCO2 dynamics in the North Indian Ocean","authors":"Ibrahim Shaik ,&nbsp;M.P. Fida Fathima ,&nbsp;P.V. Nagamani ,&nbsp;Sandesh Yadav ,&nbsp;Sibu Behera ,&nbsp;Yash Manmode ,&nbsp;G. Srinivasa Rao","doi":"10.1016/j.dynatmoce.2025.101534","DOIUrl":"10.1016/j.dynatmoce.2025.101534","url":null,"abstract":"<div><div>The partial pressure of carbon dioxide (<em>p</em>CO₂) in the North Indian Ocean (NIO) undergoes significant variations due to factors such as biological activity, ocean circulation patterns, and atmospheric influences. Understanding these variations is crucial for assessing the ocean role in the global carbon cycle and their impact on climate change. Estimating <em>p</em>CO₂ through in-situ platforms is challenging due to the time-consuming, expensive, and complex nature of water sample collection, particularly under rough oceanic conditions. Conversely, remote sensing technology offers high spatiotemporal resolution data over extensive synoptic scales, making it a valuable tool for <em>p</em>CO₂ estimation. Current models for estimating <em>p</em>CO₂ in the NIO region are limited due to the improper selection of model parameters and the scarcity of in-situ measurements, highlighting the need for a more accurate approach. This study develops a Multiparametric Linear Regression (MLR) method, integrating satellite and in-situ observations of sea surface temperature (SST), sea surface salinity (SSS), and chlorophyll-a (Chla) concentration. To develop and validate this model, in-situ data were sourced from the Global Ocean Data Analysis Project (GLODAP). Validation results showed that the proposed MLR approach outperformed existing global models, achieving low mean relative error (MRE = 0.08), mean normalized bias (MNB = 0.013), and root mean square error (RMSE = 7.26 μatm), with a high correlation coefficient (R² = 0.96). This study has the potential to improve understanding of carbon dynamics in the NIO region and its contribution to the global carbon cycle. The <em>p</em>CO₂ maps generated in this study improve climate modeling and monitoring, supporting predictions and mitigation efforts. This accurate model also aids policy-making, environmental management, and ecological assessments.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"110 ","pages":"Article 101534"},"PeriodicalIF":1.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}