Tropical Cyclone Research and Review最新文献

{"title":"Response of aquatic organisms as an eco-biotic indicator with response to cyclonic intervention in the large river system: A case study of river Ganga, India, during cyclone YAAS","authors":"Basanta Kumar Das ,&nbsp;Nitish Kumar Tiwari ,&nbsp;Trupti Rani Mohanty ,&nbsp;Shreya Roy ,&nbsp;Archisman Ray ,&nbsp;Supriti Bayen ,&nbsp;Subhadeep Das Gupta ,&nbsp;Kausik Mondal ,&nbsp;Himanshu Sekhar Swain ,&nbsp;Raju Baitha ,&nbsp;Mitesh Hiradas Ramteke ,&nbsp;Canciyal Johnson ,&nbsp;Thangjam Nirupada Chanu ,&nbsp;Manisha Bhor","doi":"10.1016/j.tcrr.2025.08.001","DOIUrl":"10.1016/j.tcrr.2025.08.001","url":null,"abstract":"<div><div>Cyclonic interferences can adversely affect the riverine ecology and ecological niche of many aquatic organisms. The present study evaluates the impact of the cyclonic storm “Yaas” on the different abiotic as well as biotic variables (Plankton, Fish, and Benthos) of the river Ganga. In the study, it was observed that cyclones have affected the riverine water quality, as prior to Yaas the calculated “National Sanitation Foundation” - Water Quality Index was 70.52 and during the Yaas period, it reduced to 52.8, while, the observed value during the post-Yaas period was 68.2. The phytoplankton density varied from pre-Yaas period (6284 cell⁻¹) to Yass (670 cell⁻¹) and finally during post-Yaas period (196 cell⁻¹). Contrary to phytoplankton, zooplankton responded favorably as its density increased from pre-Yaas period (196 cell⁻¹) to Yaas period (370 cell⁻¹), and during the post-Yaas (24 cell⁻¹). The Fish and Benthic organisms also showed similar responses as to zooplankton.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 3","pages":"Pages 249-269"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247927","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 physics of a new time-dependent theory of tropical cyclone intensification","authors":"Roger K. Smith ,&nbsp;Michael T. Montgomery","doi":"10.1016/j.tcrr.2025.08.004","DOIUrl":"10.1016/j.tcrr.2025.08.004","url":null,"abstract":"<div><div>Recent studies (Wang et al. 2021; Li et al. 2024) propose a new time-dependent theory for tropical cyclone intensification. Here, we examine the physics of this new theory and point out that intensification in the model has to be the result of an unspecified source of absolute angular momentum. For this reason, we are led to question the physical integrity of the theory. We question also the methodology seeking to tune the unknown parameters introduced in the theory.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 3","pages":"Pages 297-300"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247930","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 the frequency and magnitude of hurricanes in the Yucatan Peninsula, Mexico, in the period from 2025 to 2034 using convolutional neural networks (CNNs), Long Short-Term Memory networks (LSTMs) and statistical models","authors":"Hermes De Gracia ,&nbsp;Jorge Celeron ,&nbsp;Consuelo Diaz ,&nbsp;Aristeo Hernandez ,&nbsp;Victoria Serrano","doi":"10.1016/j.tcrr.2025.07.006","DOIUrl":"10.1016/j.tcrr.2025.07.006","url":null,"abstract":"<div><div>Climate change has significantly increased the frequency and severity of extreme weather events, a trend recognized under the United Nations Sustainable Development Goal 13: Climate Action. This study forecasts hurricane activity in the Yucatan Peninsula, Mexico, for the period 2025–2034 using advanced computational models, including Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), Autoregressive Integrated Moving Average models (ARIMA), and Linear Regression (LR). Historical hurricane data were extracted from the HURDAT2 database kept by the National Hurricane Center (NHC) and spatially analyzed in QGIS to assess storm trajectories and wind intensities.</div><div>The data were processed using Python, and each model was trained to predict hurricane frequency within three wind speed categories: &lt;50 knots, 50–100 knots, and &gt;100 knots. Results reveal divergent performance among the models. CNN exhibited high variability for low-speed events, peaking at 4.21 events in 2027 and dropping to 1.27 by 2034. In contrast, LSTM and ARIMA maintained stable forecasts: LSTM fluctuated between 2.7 and 3.0, and ARIMA ranged from 1.5 to 1.8. For the 50–100 knot range, CNN reached an anomalous high of 8.14 events in 2032, while LSTM and ARIMA remained within narrower bands (1.85–2.01 and 1.32–1.99, respectively). At the &gt;100 knot level, ARIMA showed a rising trend from 0.21 in 2025 to 0.57 in 2034, suggesting a potential increase in high-intensity cyclones.</div><div>These findings emphasize the need for adaptive forecasting systems that account for nonlinear behavior under climate change conditions.</div><div>The model outputs offer valuable insights for risk management, contingency planning, and infrastructure resilience in the hurricane-prone Yucatan Peninsula.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 3","pages":"Pages 237-248"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247926","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":"The influence of El Niño-Southern Oscillation (ENSO) on the characteristics of tropical cyclones in Indonesia waters","authors":"Kadek Krisna Yulianti ,&nbsp;Nining Sari Ningsih ,&nbsp;Rima Rachmayani ,&nbsp;Eko Prasetyo","doi":"10.1016/j.tcrr.2025.08.002","DOIUrl":"10.1016/j.tcrr.2025.08.002","url":null,"abstract":"<div><div>Indonesia, bordered by the Indian and Pacific Oceans, is influenced by tropical cyclone (TC) activity and phenomena such as the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). This study examines TC variations across four Indonesian regions, focusing on ENSO events when the IOD is neutral. Over the past 50 years (1973–2022), 2,885 tropical cyclones (TCs) have passed through Indonesian waters, with the most active area being Region 2. During El Niño, TC occurrences across Indonesia increase, while La Niña sees fewer TCs overall but with regional variations. Region 2 experiences a 12.5 % monthly decrease in TCs during La Niña due to less favourable environmental factors like vertical wind shear (VWS) and vorticity. Conversely, Regions 3 and 4 show increases of 38.1 % and 45.7 %, respectively, attributed to supportive conditions such as sea surface temperature and humidity. Accumulated Cyclone Energy (ACE) analysis reveals significant changes, with increases of 65.4 % in region 1 and 12.4 % in region 2 during El Niño, while region 2 decreases by 35.3 % during La Niña. Kernel Density Estimation (KDE) highlights seasonal and ENSO-driven spatial shifts, with density centres generally moving eastward during La Niña, except for region 2, which shifts westward. The largest shift, 632.1 km, occurred in region 4 during La Niña, moving TC formations from near West Nusa Tenggara to the Timor Sea. Analysis of Significant Wave Height (SWH) during ENSO periods for each tropical cyclone event in different regions shows that shifts in density centers during El Niño and La Niña also influence SWH variability in Indonesian waters. These findings underscore the impact of ENSO on TC activity in Indonesian waters, providing valuable insights for improving preparedness and marine safety.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 3","pages":"Pages 270-286"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247928","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":"A microwave-based machine learning approach for predicting eyewall replacement cycles","authors":"Lorenzo Pulmano","doi":"10.1016/j.tcrr.2025.07.001","DOIUrl":"10.1016/j.tcrr.2025.07.001","url":null,"abstract":"<div><div>Eyewall replacement cycles (ERCs) greatly increase the destructive potential of tropical cyclones (TCs) by affecting the maximum wind speed, wind field size, and storm surge severity while simultaneously reducing confidence in TC forecasts, most prominently in intensity forecasting. Machine learning (ML) presents new opportunities to improve current forecasting and predictive capabilities, and its application will benefit forecasters and ultimately the public. The objective of this project was to create a proof-of-concept ML convolutional neural network (CNN) to predict ERCs using the 89 GHz microwave band for training and testing. The training set was comprised of North Atlantic basin (NATL) storms from 1999 to 2009. The testing set included NATL storms from 2019 to 2022. Twelve models were created, together known as the CNN Ensemble for Predicting Eyewall Replacement Cycles (CE-PERCY), with each individual member achieving at least 80 % in-training accuracy. Two versions were created: versions A and B. Using synthetic aperture radar, land-based radar, aircraft reconnaissance, Microwave-based Probability of ERC (M-PERC), National Hurricane Center reports, and microwave imagery, ERC analysis was conducted on the testing set. 28 ERCs were identified throughout 14 hurricanes from 2019 to 2022. CE-PERCY performs well for a proof-of-concept, with versions A and B predicting 21 and 23 ERCs, respectively. This project successfully introduces a foundation for using ML CNNs in ERC prediction, demonstrates the viability of the technique, and proves that a large enough dataset of microwave imagery can be used in this specific application.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 3","pages":"Pages 171-184"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247921","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":"Typhoon science meets artificial intelligence: A roundtable on bridging physics-based and data-driven paradigms","authors":"Zeyi Niu ,&nbsp;Zhe-Min Tan ,&nbsp;Hui Yu ,&nbsp;Jian-Feng Gu ,&nbsp;Guomin Chen ,&nbsp;Wei Huang","doi":"10.1016/j.tcrr.2025.08.006","DOIUrl":"10.1016/j.tcrr.2025.08.006","url":null,"abstract":"<div><div>This paper summarizes the ‘Artificial Intelligence (AI) + Typhoon’ session and a subordinated roundtable forum at the 21st China National Workshop on Tropical Cyclones (NWTC-XXI, 16–18 April. 2025, Changsha China), highlighting recent advances in AI techniques for typhoon monitoring, forecasting, and impact assessment, as well as the deep integration of state-of-the-art artificial-intelligence weather prediction (AIWP) models with traditional physics-based numerical weather prediction (NWP) models. Key insights from the round-table forum are synthesized, emphasizing the strengths, limitations, and future development directions for AI models in typhoon forecasting. As a forward-looking perspective, we should be ready for embracing the emerging AI for research (AI4R) paradigm to advance typhoon science and technology.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 3","pages":"Pages 311-316"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247932","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":"Assessing the impact of climate change on land-falling tropical cyclones (LFTCs) over the North Indian Ocean (NIO) and their effects on coastal agriculture in Maharashtra: A case study","authors":"Shahenaz Mulla ,&nbsp;Sudhir Kumar Singh ,&nbsp;Rizwan Ahmed","doi":"10.1016/j.tcrr.2025.04.003","DOIUrl":"10.1016/j.tcrr.2025.04.003","url":null,"abstract":"<div><div>The intensity of tropical cyclonic storms formed over the North Indian Ocean (NIO) has increased over the last two decades. The increasing severity of cyclonic storms has serious socioeconomic and agricultural consequences. Many people are concerned about the impact of global warming caused by climate change on extreme weather events, such as the frequency and intensity of Tropical Cyclones (TCs) that form over global ocean basins. High-intensity cyclones have become more common in the NIO, posing significant risks and vulnerability to coastal communities.</div><div>The World Meteorological Organization (WMO) reported that the warmest year was 2015–21, and the warmest decade was 2011–2020, which could be attributed to increased levels of greenhouse gases. However, few studies on the impact of climate change on various characteristics of Land-falling Tropical Cyclones (LFTCs) between 2001 and 2021 have been conducted. As a result, we performed an analysis to evaluate the impact of climate change on various characteristics of LFTCs, such as TC patterns, eye scenes, over land duration, Land-falling intensity (LFI) of LFTCs formed between the years 2000 and 2021. TCs formed over the NIO (2001–2021) crossed the coast with higher LFI and have shown a significant increasing trend in current intensity. Furthermore, more overland duration, eye-pattern TCs, and eye scenes were observed between 2000 and 2021.</div><div>This study also assessed the impact of Severe Cyclonic Storm (SCS) Nisarga on coastal agriculture of Maharashtra in terms of vegetation, and shoreline dynamics. The Nisarga’s landfall caused huge socioeconomic as well as agricultural damages including torrential rainfall, storm surges, and saltwater intrusion, causing biodiversity loss and prolonged soil degradation. Normalized differential vegetation index (NDVI) and Enhanced Vegetation Index (EVI) indices revealed a sharp decline in vegetation health during post-cyclone with slow recovery in the subsequent months. The findings of this study could be used to improve the accuracy of operational forecasting of TCs over the North Indian Ocean basins. The results also highlight the need for targeted coastal management, including mangrove restoration and adaptive agricultural strategies, to enhance resilience against future LFTCs.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 2","pages":"Pages 132-144"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138231","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":"Assessment of the impacts of Super Typhoon Saola and the record-breaking rainstorm due to the remnant of Severe Typhoon Haikui on Hong Kong in September 2023","authors":"Yuk Sing Lui,&nbsp;The Hong Kong Federation of Insurers,&nbsp;Andy Wang-chun Lai,&nbsp;Chun-wing Choy,&nbsp;Tsz-cheung Lee","doi":"10.1016/j.tcrr.2025.04.002","DOIUrl":"10.1016/j.tcrr.2025.04.002","url":null,"abstract":"<div><div>In early September 2023, Hong Kong was severely impacted by the ferocious strike of Super Typhoon Saola on 1–2 September and the phenomenal rainstorm on 7–8 September triggered by the remnant of TC Haikui. Given the rarity of these two successive extreme weather events which wreaked havoc in Hong Kong within 10 days, impact assessment on the damage and economic loss in Hong Kong due to these two extreme events was conducted. Utilizing available data from government reports, media, surveys, and insurance claims, the direct economic losses incurred by Super Typhoon Saola on 1–2 September and the record-breaking rainstorm on 7–8 September were estimated to be around HK$0.48 billion and HK$1.74 billion respectively. Moreover, the impacts of Saola and the record-breaking rainstorm in September 2023 are compared with other super typhoons and Black Rainstorm events in Hong Kong mainly in the last decade for reference. It is noted that, when compared with the Super Typhoons Hato and Mangkhut which also necessitated the issuance of Hurricane Signal No. 10 in Hong Kong respectively in 2017 and 2018, the overall impact of Saola in 2023 was less than those of Hato and Mangkhut. In terms of rainstorm events, the impact of the Black Rainstorm event on 7–8 September 2023 was significantly higher than those of the Black Rainstorm events in March 2014 and June 2020. The possible attributing factors related to the differences in the impact of these super typhoon and rainstorm events were also briefly discussed.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 2","pages":"Pages 158-169"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138233","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":"Towards understanding the tropical cyclone life cycle","authors":"Roger K. Smith ,&nbsp;Michael T. Montgomery","doi":"10.1016/j.tcrr.2025.02.003","DOIUrl":"10.1016/j.tcrr.2025.02.003","url":null,"abstract":"<div><div>Conceptual frameworks are discussed for understanding the physics of the tropical cyclone life cycle in an idealized, three-dimensional, numerical simulation in a quiescent environment. Both axisymmetric and three-dimensional frameworks are discussed. A central feature of one of the two axisymmetric frameworks is the assumption that absolute angular momentum is materially conserved above the frictional boundary layer, at least in the classical Eliassen balance formulation. Such conservation implies that vortex spin up requires radial inflow above the friction layer, while radial outflow there leads to spin down. Many of the ideas are illustrated by two simple laboratory experiments.</div><div>In the other axisymmetric framework, the so-called WISHE framework the material conservation of absolute angular momentum is dispensed with in favour of assuming that the saturated moist equivalent potential vorticity is everywhere zero. This assumption limits the applicability of the WISHE framework at best to a small portion of the storm’s life cycle, even if one were able to justify the implicit angular momentum source thereby introduced. Analysis of a recent three-dimensional numerical simulation of the tropical cyclone life cycle unveils a causality problem with the assumptions underlying these models.</div><div>In a three-dimensional framework, the rotating-convection paradigm highlights the importance for vortex spin up of the deep, convectively-induced overturning circulation being strong enough to generate inflow above the frictional boundary layer in the presence of the ubiquitous tendency of the boundary layer to generate outflow there. When deep convection is too weak to ventilate all the mass that is converging in the boundary layer to the upper troposphere, there is net outflow above the boundary layer and the vortex weakens. This behaviour appears to be ruled out in the WISHE models by their assumption of global moist neutrality, but is a feature of the classical Eliassen model.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 2","pages":"Pages 119-131"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138230","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":"Can one reconcile the classical theories and the WISHE theories of tropical cyclone intensification?","authors":"Roger K. Smith ,&nbsp;Michael T. Montgomery ,&nbsp;Shanghong Wang","doi":"10.1016/j.tcrr.2025.02.002","DOIUrl":"10.1016/j.tcrr.2025.02.002","url":null,"abstract":"<div><div>An effort is made to reconcile the classical balance theories of tropical cyclone intensification by Shapiro and Willoughby and Schubert and Hack and the various prognostic (or WISHE-) theories of Emanuel. As a start, it proves insightful to extend the classical theories to account for explicit latent heat release in slantwise ascending air. While such an effort uncovers enroute a range of old modelling issues concerning the representation of deep convection in a balance framework, the analysis provides a new perspective on these issues. The bottom line is that the two theories cannot be reconciled.</div><div>The behaviour of the classical model with explicit latent heat release included is illustrated by a particular calculation starting with an axisymmetric vortex in a conditionally-unstable atmosphere. As soon as condensation occurs aloft, the moist Eliassen equation for the overturning circulation becomes hyperbolic in the convectively-unstable region and the model cannot be advanced forwards beyond this time unless the Eliassen equation is suitably regularized to remove these hyperbolic regions. However, regularization suppresses deep moist convection, leaving no mechanism to reverse the frictionally-induced outflow in the lower troposphere required to concentrate absolute angular momentum there. For this reason, the initial vortex spins down, even following the formation of elevated cloud with the accompanying latent heat release.</div><div>The fact that the flow configuration in the explicit moist version of the classical theories is similar to that in the WISHE theories raises several fundamental questions concerning the physics of vortex spin up in the WISHE theories, calling into question the utility of these theories for understanding tropical cyclone intensification in nature.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"14 2","pages":"Pages 105-118"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138229","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}