Tropical Cyclone Research and Review最新文献

{"title":"Phase transitions between tropical, subtropical, and extratropical cyclones: A review from IWTC-10","authors":"Kimberly Wood ,&nbsp;Wataru Yanase ,&nbsp;Jack Beven ,&nbsp;Suzana J. Camargo ,&nbsp;Joseph B. Courtney ,&nbsp;Chris Fogarty ,&nbsp;Junya Fukuda ,&nbsp;Naoko Kitabatake ,&nbsp;Matthew Kucas ,&nbsp;Ron McTaggart-Cowan ,&nbsp;Michelle Simões Reboita ,&nbsp;Jacopo Riboldi","doi":"10.1016/j.tcrr.2023.11.002","DOIUrl":"10.1016/j.tcrr.2023.11.002","url":null,"abstract":"<div><div>This review, which was adapted from a Tenth International Workshop on Tropical Cyclones (IWTC-10) report, discusses research findings and operational practices relevant to cyclone types and phase transitions (extratropical, subtropical, and tropical). The cyclone phase space (CPS) method is widely used in both historical investigations and real-time evaluation of cyclone type and transition; however, CPS parameter values depend on input data resolution, and universal thresholds do not currently exist to delineate when a cyclone transitions from one type to another. Assessments of phase transitions in a changing climate highlight potential latitude shifts in extratropical transition and increased potential for tropical transition, but realistic projections of future trends likely require high-resolution simulations that can capture the cyclone warm core.</div><div>Operational meteorological centers apply varied approaches to cyclone classification via CPS parameters and other criteria, some of which depend on the tropical basin, yet these approaches cannot fully address challenges in operational classification and subsequently in communicating risks associated with these phase transitions. We recommend a multivariate historical assessment of tropical and subtropical cyclones across all basins in which they occur, including the South Atlantic Ocean and the Mediterranean Sea, to identify the potential for a more universal cyclone classification approach that meets operational needs.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 4","pages":"Pages 294-308"},"PeriodicalIF":2.4,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143241452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of big-data and AI application in typhoon-related disaster risk early warning in Typhoon Committee region","authors":"Jinping Liu ,&nbsp;Jeonghye Lee ,&nbsp;Ruide Zhou","doi":"10.1016/j.tcrr.2023.12.004","DOIUrl":"10.1016/j.tcrr.2023.12.004","url":null,"abstract":"<div><div>ESCAP/WMO Typhoon Committee Members are directly or indirectly affected by typhoons every year. Members have accumulated rich experiences dealing with typhoons' negative impact and developed the technologies and measures on typhoon-related disaster risk forecasting and early warning in various ways to reduce the damage caused by typhoon. However, it is still facing many difficulties and challenges to accurately forecast the occurrence of typhoons and warning the potential impacts in an early stage due to the continuously changing weather conditions. With the development of information technology (IT) and computing science, and increasing accumulated hydro-meteorological data in recent decades, scientists, researchers and operationers keep trying to improve forecasting models based on the application of big data and artificial intelligent (AI) technology to promote the capacity of typhoon-related disaster risk forecasting and early warning. This paper reviewed the current status of application of big data and AI technology in the aspect of typhoon-related disaster risk forecasting and early warning, and discussed the challenges and limitations that must be addressed to effectively harness the power of big data and AI technology application in typhoon-related disaster risk reduction in the future.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 4","pages":"Pages 341-353"},"PeriodicalIF":2.4,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139189456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent advances in operational tropical cyclone genesis forecast","authors":"K.K. Hon ,&nbsp;Robert Ballard ,&nbsp;Eric Blake ,&nbsp;Steph Bond ,&nbsp;Robb Gile ,&nbsp;Daniel Halperin ,&nbsp;Charles Helms ,&nbsp;Hoang Lam ,&nbsp;Xinyan Lyu ,&nbsp;Mrutyunjay Mohapatra ,&nbsp;Monica Sharma ,&nbsp;Akira Shimokobe ,&nbsp;Ralf Toumi ,&nbsp;Seonghee Won","doi":"10.1016/j.tcrr.2023.12.001","DOIUrl":"10.1016/j.tcrr.2023.12.001","url":null,"abstract":"<div><div>Tropical cyclone (TC) genesis prediction is a major scientific challenge to the TC operation and research community. This report surveys the current status of TC genesis forecasts by a number of major operational centers covering the key ocean basins across both hemispheres. Since IWTC-9, we see an emergence of probabilistic TC genesis forecast products by operational centers, typically supported by the statistical processing of a combination of ensemble prediction and satellite analysis, covering time periods of couple of days to weeks ahead. The prevalence of multi-center grand ensemble approach highlights the uncertainties involved and the forecast challenges in quantitative genesis prediction. While operational practice might differ across agencies, verification efforts generally report a steady or slightly improving skill level in terms of reliability, which likely results from the continual improvement in global numerical weather prediction capability.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 4","pages":"Pages 323-340"},"PeriodicalIF":2.4,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139018499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unusual tracks: Statistical, controlling factors and model prediction","authors":"Ying Li ,&nbsp;Julian Heming ,&nbsp;Ryan D. Torn ,&nbsp;Shaojun Lai ,&nbsp;Yinglong Xu ,&nbsp;Xiaomeng Chen","doi":"10.1016/j.tcrr.2023.12.002","DOIUrl":"10.1016/j.tcrr.2023.12.002","url":null,"abstract":"<div><div>The progress of research and forecast techniques for tropical cyclone (TC) unusual tracks (UTs) in recent years is reviewed. A major research focus has been understanding which processes contribute to the evolution of the TC and steering flow over time, especially the reasons for the sharp changes in TC motion over a short period of time. When TCs are located in the vicinity of monsoon gyres, TC track forecast become more difficult to forecast due to the complex interaction between the TCs and the gyres. Moreover, the convection and latent heat can also feed back into the synoptic-scale features and in turn modify the steering flow. In this report, two cases with UTs are examined, along with an assessment of numerical model forecasts. Advances in numerical modelling and in particular the development of ensemble forecasting systems have proved beneficial in the prediction of such TCs. There are still great challenges in operational track forecasts and warnings, such as the initial TC track forecast, which is based on a poor pre-genesis analysis, TC track forecasts during interaction between two or more TCs and track predictions after landfall. Recently, artificial intelligence (AI) methods such as machine learning or deep learning have been widely applied in the field of TC forecasting. For TC track forecasting, a more effective method of center location is obtained by combining data from various sources and fully exploring the potential of AI, which provides more possibilities for improving TC prediction.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 4","pages":"Pages 309-322"},"PeriodicalIF":2.4,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138986493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote sensing and analysis of tropical cyclones: Current and emerging satellite sensors","authors":"Lucrezia Ricciardulli ,&nbsp;Brian Howell ,&nbsp;Christopher R. Jackson ,&nbsp;Jeff Hawkins ,&nbsp;Joe Courtney ,&nbsp;Ad Stoffelen ,&nbsp;Sebastian Langlade ,&nbsp;Chris Fogarty ,&nbsp;Alexis Mouche ,&nbsp;William Blackwell ,&nbsp;Thomas Meissner ,&nbsp;Julian Heming ,&nbsp;Brett Candy ,&nbsp;Tony McNally ,&nbsp;Masahiro Kazumori ,&nbsp;Chinmay Khadke ,&nbsp;Maria Ana Glaiza Escullar","doi":"10.1016/j.tcrr.2023.12.003","DOIUrl":"10.1016/j.tcrr.2023.12.003","url":null,"abstract":"<div><div>This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones (TC) fine structure, wind field, and temporal evolution. The article is based on a World Meteorological Organization (WMO) report prepared for the 10th International Workshop on Tropical Cyclones (IWTC), held in Bali in December 2022, and its objective is to present updates in TC research and operation every four years. Here we focus on updates regarding the most recent space-based TC observations, and we cover new methodologies and techniques using polar orbiting sensors, such as C-band synthetic aperture radars (SARs), L-band and combined C/X-band radiometers, scatterometers, and microwave imagers/sounders. We additionally address progress made with the new generation of geostationary and small satellites, and discuss future sensors planned to be launched in the next years. We then briefly describe some examples on how the newest sensors are used in operations and data assimilation for TC forecasting and research, and conclude the article with a discussion on the remaining challenges of TC space-based observations and possible ways to address them in the near future.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 4","pages":"Pages 267-293"},"PeriodicalIF":2.4,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139192563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Objective satellite methods including AI algorithms reviewed for the tenth International workshop on tropical cyclones (IWTC-10)","authors":"Quoc-Phi Duong ,&nbsp;Anthony Wimmers ,&nbsp;Derrick Herndon ,&nbsp;Zhe-Min Tan ,&nbsp;Jing-Yi Zhuo ,&nbsp;John Knaff ,&nbsp;Ibrahim Al Abdulsalam ,&nbsp;Takeshi Horinouchi ,&nbsp;Ryota Miyata ,&nbsp;Arthur Avenas","doi":"10.1016/j.tcrr.2023.11.001","DOIUrl":"10.1016/j.tcrr.2023.11.001","url":null,"abstract":"<div><div>Here we explore the latest four years (2019–2022) of using satellite data to objectively analyze tropical cyclones (TC) and issue recommendations for improved analysis. We first discuss new methods of direct retrieval from SAR and geostationary imagers. Next, we survey some of the most prominent new techniques in AI and discuss their major capabilities (especially accuracy in nonlinear TC behavior, characterization of model uncertainty and creation of synthetic satellite imagery) and limitations (especially lack of transparency and limited amount of training data). We also identify concerns with biases and unlabeled uncertainties in the Best Track records as being a first-order limitation for further progress in objective methods. The article concludes with recommendations to improve future objective methods, especially in the area of more accurate and reliable training data sets.</div></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 4","pages":"Pages 259-266"},"PeriodicalIF":2.4,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139292443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of recent research progress on the effect of external influences on tropical cyclone intensity change","authors":"Joshua B. Wadler ,&nbsp;Johna E. Rudzin ,&nbsp;Benjamin Jaimes de la Cruz ,&nbsp;Jie Chen ,&nbsp;Michael Fischer ,&nbsp;Guanghua Chen ,&nbsp;Nannan Qin ,&nbsp;Brian Tang ,&nbsp;Qingqing Li","doi":"10.1016/j.tcrr.2023.09.001","DOIUrl":"10.1016/j.tcrr.2023.09.001","url":null,"abstract":"<div><p>Over the past four years, significant research has advanced our understanding of how external factors influence tropical cyclone (TC) intensity changes. Research on air-sea interactions shows that increasing the moisture disequilibrium is a very effective way to increase surface heat fluxes and that ocean salinity-stratification plays a non-negligible part in TC intensity change. Vertical wind shear from the environment induces vortex misalignment, which controls the onset of significant TC intensification. Blocking due to upper-level outflow from TCs can reduce the magnitude of vertical wind shear, making for TC intensification. Enhanced TC-trough interactions are vital for rapid intensification in some TC cases because of strengthened warm air advection, but upper-level troughs are found to limit TC intensification in other cases due to dry midlevel air intrusions and increased shear. Aerosol effects on TCs can be divided into direct effects involving aerosol-radiation interactions and indirect effects involving aerosol-cloud interactions. The radiation absorption by the aerosols can change the temperature profile and affect outer rainbands through changes in stability and microphysics. Sea spray and sea salt aerosols are more important in the inner region, where the aerosols increase precipitation and latent heating, promoting more intensification. For landfalling TCs, the intensity decay is initially more sensitive to surface roughness than soil moisture, and the subsequent decay is mainly due to the rapid reduction in surface moisture fluxes. These new insights further sharpen our understanding of the mechanisms by which external factors influence TC intensity changes.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 3","pages":"Pages 200-215"},"PeriodicalIF":2.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603223000395/pdfft?md5=75c970bfed66038f97ab660225e84a79&pid=1-s2.0-S2225603223000395-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent progress in research and forecasting of tropical cyclone outer size","authors":"Benjamin A. Schenkel ,&nbsp;Chris Noble ,&nbsp;Daniel Chavas ,&nbsp;Kelvin T.F. Chan ,&nbsp;Stephen J. Barlow ,&nbsp;Amit Singh ,&nbsp;Kate Musgrave","doi":"10.1016/j.tcrr.2023.09.002","DOIUrl":"10.1016/j.tcrr.2023.09.002","url":null,"abstract":"<div><p>This review article summarizes the current understanding and recent updates to tropical cyclone outer size and structure forecasting and research primarily since 2018 as part of the World Meteorological Organization's 10th International Workshop on Tropical Cyclones. A more complete understanding of tropical cyclone outer wind and precipitation is key to anticipating storm intensification and the scale and magnitude of landfalling hazards. We first discuss the relevance of tropical cyclone outer size and structure, improvements in our understanding of its life cycle and inter-basin variability, and the processes that impact outer size changes. We next focus on current forecasting practices and differences among warning centers, recent advances in operational forecasting, and new observations of the storm outer wind field. We also summarize recent research on projected tropical cyclone outer size and structure changes by the late 21st century. Finally, we discuss recommendations for the future of tropical cyclone outer size forecasting and research.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 3","pages":"Pages 151-164"},"PeriodicalIF":2.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603223000401/pdfft?md5=821c1b4e7efb4bd8f4a078e234fbd72e&pid=1-s2.0-S2225603223000401-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135347833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent advances in seasonal and multi-annual tropical cyclone forecasting","authors":"Yuhei Takaya ,&nbsp;Louis-Philippe Caron ,&nbsp;Eric Blake ,&nbsp;François Bonnardot ,&nbsp;Nicolas Bruneau ,&nbsp;Joanne Camp ,&nbsp;Johnny Chan ,&nbsp;Paul Gregory ,&nbsp;Jhordanne J. Jones ,&nbsp;Namyoung Kang ,&nbsp;Philip J. Klotzbach ,&nbsp;Yuriy Kuleshov ,&nbsp;Marie-Dominique Leroux ,&nbsp;Julia F. Lockwood ,&nbsp;Hiroyuki Murakami ,&nbsp;Akio Nishimura ,&nbsp;Dushmanta R. Pattanaik ,&nbsp;Tom J. Philp ,&nbsp;Yohan Ruprich-Robert ,&nbsp;Ralf Toumi ,&nbsp;Ruifen Zhan","doi":"10.1016/j.tcrr.2023.09.003","DOIUrl":"10.1016/j.tcrr.2023.09.003","url":null,"abstract":"<div><p>Seasonal tropical cyclone (TC) forecasting has evolved substantially since its commencement in the early 1980s. However, present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders: current operational products are mainly basin-scale information, while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making. To fill this gap and make the TC science and services move forward, this paper reviews recent research and development in seasonal tropical cyclone (TC) forecasting. In particular, this paper features new research topics on seasonal TC predictability in neutral conditions of El Niño–Southern Oscillation (ENSO), emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence, and multi-annual TC predictions. We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic, Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's expectations. New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 3","pages":"Pages 182-199"},"PeriodicalIF":2.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603223000413/pdfft?md5=b08b9f4a6eb459664a016d67b63ba13f&pid=1-s2.0-S2225603223000413-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135348355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones","authors":"Suzana J. Camargo ,&nbsp;Hiroyuki Murakami ,&nbsp;Nadia Bloemendaal ,&nbsp;Savin S. Chand ,&nbsp;Medha S. Deshpande ,&nbsp;Christian Dominguez-Sarmiento ,&nbsp;Juan Jesús González-Alemán ,&nbsp;Thomas R. Knutson ,&nbsp;I.-I. Lin ,&nbsp;Il-Ju Moon ,&nbsp;Christina M. Patricola ,&nbsp;Kevin A. Reed ,&nbsp;Malcolm J. Roberts ,&nbsp;Enrico Scoccimarro ,&nbsp;Chi Yung (Francis) Tam ,&nbsp;Elizabeth J. Wallace ,&nbsp;Liguang Wu ,&nbsp;Yohei Yamada ,&nbsp;Wei Zhang ,&nbsp;Haikun Zhao","doi":"10.1016/j.tcrr.2023.10.001","DOIUrl":"10.1016/j.tcrr.2023.10.001","url":null,"abstract":"<div><p>A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic, and the limitations of observed TC records. The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models. A new paradigm, TC seeds, has been proposed, and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency. New studies also highlighted the importance of large-scale environmental fields on TC activity, such as snow cover and air-sea interactions. Future projections on TC translation speed and medicanes are new additional focus topics in our report. Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"12 3","pages":"Pages 216-239"},"PeriodicalIF":2.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603223000437/pdfft?md5=da849840a8fa5d957f8661c9bf34ba21&pid=1-s2.0-S2225603223000437-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135760939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}