Weather and Climate Extremes最新文献

{"title":"Distinguishing environmental controls on strong vs. extreme wind gusts","authors":"Greeshma Surendran ,&nbsp;Steven Sherwood ,&nbsp;Jason Evans ,&nbsp;Moutassem El Rafei ,&nbsp;Andrew Dowdy ,&nbsp;Fei Ji ,&nbsp;Andrew Brown","doi":"10.1016/j.wace.2025.100788","DOIUrl":"10.1016/j.wace.2025.100788","url":null,"abstract":"<div><div>Statistical and theoretical models of wind gusts may be dominated by more common strong events, rather than rare but damaging extreme ones. We address this by combining case studies of six extreme gust cases in New South Wales (NSW), Australia, with statistical and machine-learning (random forest) models to identify environmental factors distinguishing “strong” (<span><math><mrow><mo>≥</mo><mn>18</mn><mspace></mspace><mi>m/s</mi></mrow></math></span>) vs. “extreme” (<span><math><mrow><mo>≥</mo><mn>25</mn><mspace></mspace><mi>m/s</mi></mrow></math></span>) gust events in a 20-year dataset. The BARRA-SY high-resolution regional reanalysis is used to augment in-situ observations and provide a model gust speed diagnostic for evaluation, as well as environmental prediction metrics. All the extreme wind cases were linked to deep convection, often organized into linear systems. A random forest model achieved 89% accuracy for predicting strong winds generally, with the gust diagnostic and environmental background wind speeds as the top predictors. For distinguishing extreme from strong gusts, the model’s accuracy was 79%, but with a high false alarm rate. Both statistical and machine-learning analyses highlight convective instability metrics — Most Unstable Convective Available Potential Energy (MUCAPE), Derecho Composite Parameter (DCP), and k_index - as key predictors of extreme gusts. The BARRA-SY gust speed diagnostic thus informs about strong wind gusts, but not extremes, which depend on variables it ignores. Instability measures, however, are also imperfect predictors of extreme gusts because they fail to capture storm trigger conditions, seen in some of the case studies. These findings demonstrate that the factors driving extreme wind gusts differ substantially from those driving strong but less extreme gusts. Therefore, statistical analyses or predictive models that consider all strong gusts collectively will likely fail to uncover the environmental factors responsible for the most extreme events with greatest impact.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100788"},"PeriodicalIF":6.9,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-task feature transfer deep learning-based tropical cyclone center estimation (MFT–TC) using geostationary satellite observations","authors":"Juhyun Lee ,&nbsp;Il-Ju Moon ,&nbsp;Jungho Im ,&nbsp;Dong-Hoon Kim ,&nbsp;Hyeyoon Jung","doi":"10.1016/j.wace.2025.100796","DOIUrl":"10.1016/j.wace.2025.100796","url":null,"abstract":"<div><div>Accurate and rapid tropical cyclone (TC) monitoring is crucial for precise forecasting and appropriate response to mitigate socio-economic damages. Geostationary satellite-based observations are the only tools that allow continuous monitoring of TCs throughout their entire lifetime, from formation to dissipation. However, owing to the diversity of TC structures, the automatic extraction of TC information using geostationary satellite-based cloud-top observations is still challenging. To address this limitation, several deep-learning-based approaches for extracting TC information have been developed. Here, we propose a novel deep learning-based TC center estimation approach using real-time geostationary satellite observations. To reduce computational costs while capturing both the entire TC structure and high-resolution spiral patterns, we propose a multi-task feature transfer deep learning-based TC center estimation (MFT–TC). This model effectively considers both the entire spiral band and focuses on specific local characteristics of TC while maintaining high computing efficiency, reducing computing costs by 47 %). Compared to the conventional single-CNN-based TC center determination model, which has been widely used in previous studies, the proposed model achieved significant improvements, with skill score increases ranging from 12 % to 39 %. Additionally, since there are significant structural differences between TCs with and without an eye, MFT–TC was evaluated under two different schemes based on the training sets: scheme 1, which uses separate training datasets depending on whether the TC has an eye (MFT–TC-div) and scheme 2, which uses all TC cases combined (MFT–TC-whl). Evaluation results showed scheme 1-based MFT–TC achieved a 14.8 % improvement over scheme 2-based MFT–TC, suggesting that separating training samples based on TC eye presence enhances the accuracy of TC center estimation. Furthermore, using the explainable artificial intelligence (XAI) approach, we demonstrated that MFT–TC efficiently captures both overall cyclonic structures and center-specific spatial characteristics to estimate the TC center accurately.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100796"},"PeriodicalIF":6.9,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144669788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decadal swing in NAO variability and summertime heat extremes in South Korea over recent decades","authors":"Jung-Hee Ryu ,&nbsp;Song-Lak Kang","doi":"10.1016/j.wace.2025.100795","DOIUrl":"10.1016/j.wace.2025.100795","url":null,"abstract":"<div><div>South Korea experienced a lull in heatwave occurrences from the late 1990s to the early 2010s (referred to as “P1”), followed by significant heatwaves in the early 2010s (referred to as “P2”). To understand this decadal variation despite ongoing global warming, we examined the link between heatwaves in South Korea and decadal shifts in North Atlantic Oscillation (NAO) variability. Planetary-scale waves originating from Greenland in response to the NAO influence atmospheric circulation across Europe, Northeast Asia (including the Korean Peninsula), and North America, primarily on interannual scales. Specifically, positive NAO phases enhance anticyclonic circulations over the Korean Peninsula, increasing surface temperatures and heatwave frequency. During P1, the NAO exhibited a declining trend and reduced interannual variability, influenced by remote tropical Pacific forcing. Our results also suggested the potential influence of the Atlantic Ocean forcing on the rising trend of the NAO during P2, alongside a phase shift in tropical Pacific forcing. These findings highlight the role of large-scale climate variability—shaped by complex interactions among NAO trends, tropical Pacific forcing, and North Atlantic forcing, with potential contributions from anthropogenic forcing—in driving the decadal fluctuations in local heat extremes, particularly in South Korea.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100795"},"PeriodicalIF":6.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144622628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 contribution of climate drivers to compound drought and extreme temperature events increased in recent decades","authors":"Siyi Li ,&nbsp;Bin Wang ,&nbsp;De Li Liu ,&nbsp;Chao Chen ,&nbsp;Puyu Feng ,&nbsp;Alfredo Huete ,&nbsp;Keyu Xiang ,&nbsp;Qiang Yu","doi":"10.1016/j.wace.2025.100793","DOIUrl":"10.1016/j.wace.2025.100793","url":null,"abstract":"<div><div>Compound climate extremes severely impact crops more than individual events. Understanding historical changes in compound extreme events and their drivers is crucial for managing climate risks and protecting crop survival. Using a hybrid biophysical-statistical modeling approach, we investigated the connections between large-scale climate drivers of El Niño Southern Oscillation (ENSO)/Indian Ocean Dipole (IOD) and compound drought and extreme temperature (DET) across Australia's wheat belt from 1900 to 2020. DET in eastern Australia's wheat belt was more responsive to ENSO/IOD compared to the west. El Niño and positive IOD phases intensified DET and increased the probability of high-intensity DET, whereas La Niña and negative IOD reduced them. Probabilities of high-intensity DET have exhibited a temporal increase, during the strong El Niño phase and the positive IOD phase. Our findings highlight the need to assess the spatial-temporal response of compound events to climate drivers for effective early warning and mitigation.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100793"},"PeriodicalIF":6.1,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144596184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends and variability of heat waves in Europe and the association with large-scale circulation patterns","authors":"Loredana Boboc ,&nbsp;Mihai Dima ,&nbsp;Petru Vaideanu ,&nbsp;Monica Ionita","doi":"10.1016/j.wace.2025.100794","DOIUrl":"10.1016/j.wace.2025.100794","url":null,"abstract":"<div><div>Heat waves, defined by consecutive days of abnormally high temperatures exceeding local or regional norms, have been extensively studied during the summer season. However, their characteristics and driving forces in mid-to-late spring (April and May) and early autumn (September) remain poorly understood. This study employed Empirical Orthogonal Functions and composite analysis to investigate the frequency, trend, and spatio-temporal variability of heat waves across Europe from 1921 to 2021. Our analysis reveals a significant upward trend in heat wave occurrences across most European regions, with a notable surge in the last three decades, beginning in the early 1990s. Furthermore, an increase in heat wave events has been observed in both mid-to-late spring and early autumn. The decade of 2011-2021 exhibited the highest number of recorded heat waves, with particularly intense periods, in terms of both frequency and spatial extent, occurring in 2003, 2007, 2012, 2015, and 2018. The most pronounced rise in heat wave frequency is evident in southern regions, including Spain, France, and Italy, extending through Central Europe and the Fennoscandian Peninsula. Southern and eastern regions display the most significant increase compared to previous periods. We identified three distinct blocking patterns potentially influencing the observed spatial and temporal variability of heat waves across spring, summer, and autumn. The first pattern corresponds to the positive phase of the North Atlantic Oscillation. The second is characterized by a blocking pattern over Fennoscandia (Scandinavian blocking). The third exhibits a high-pressure system in the west and low-pressure anomalies in the east. These findings contribute to a more comprehensive understanding of the seasonal characteristics, underlying mechanisms, and driving forces of heat waves in Europe.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100794"},"PeriodicalIF":6.1,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144596185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of solar radiation modification on temperature extremes and heatwaves in Southeast Asia","authors":"Zeqian Feng ,&nbsp;Mou Leong Tan ,&nbsp;Mohd Amirul Mahamud ,&nbsp;Joon Chuah ,&nbsp;Fei Zhang","doi":"10.1016/j.wace.2025.100789","DOIUrl":"10.1016/j.wace.2025.100789","url":null,"abstract":"<div><div>Solar Radiation Modification (SRM) has been proposed as a rapid solution to mitigate temperature rise, but its effects on regional temperature extremes and heatwaves remain underexplored. Southeast Asia, a region highly vulnerable to climate change due to its unique environmental and socio-economic conditions, necessitates detailed assessments of SRM impacts. This study evaluates the effects of SRM using two scenarios, G6Solar and G6Sulfur, alongside traditional emissions pathways (SSP245 and SSP585). Downscaled and bias-corrected GeoMIP6 datasets are analyzed for selected temperature and heatwave indices across 20 Southeast Asian sub-regions from 2020 to 2099. Under SSP585, annual maximum temperatures (TXx) by 2099 are projected to increase by 4–6 °C relative to the baseline, with heatwave characteristics intensifying substantially. Heatwave duration (HWD) could rise by 40–180 days, while occurrences (HWN) may increase 3–5 times, and intensity (HWA) could escalate by 5–6 °C. In contrast, SRM scenarios effectively moderate these impacts, aligning closer to the moderate SSP245 scenario. Between the two SRM approaches, G6Sulfur proves slightly more effective than G6Solar in reducing temperature extremes particularly in continental regions. Under SRM, heatwave frequency, duration, and intensity are less severe compared to SSP585, though spatial variability in effectiveness is observed and with minimal differences in mainland Southeast Asia. This study presents a comprehensive assessment of SRM's impacts on temperature extremes and heatwaves in Southeast Asia, utilizing a multi-model ensemble across multiple SRM and SSP scenarios. By focusing on a region often underrepresented in SRM research, this work offers critical insights for policymakers considering SRM as a climate mitigation strategy.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100789"},"PeriodicalIF":6.1,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamical systems methods to understand projected heatwave intensification","authors":"Eylon Vakrat,&nbsp;Paul J. Kushner","doi":"10.1016/j.wace.2025.100791","DOIUrl":"10.1016/j.wace.2025.100791","url":null,"abstract":"<div><div>Heatwaves pose well-known health dangers, and carry socio-economic and ecological consequences. Blocking highs typically drive such heatwaves during the European summer. The dynamics, surface impacts, and sensitivity to climate forcing of such events are of great interest, but because analysis of these events is sensitive to methodological details, a multi-faceted approach is needed to derive robust results. Such an analysis is carried out here, for observations and future projections. Heatwaves at meteorological stations, defined in terms of the discomfort index, which combines temperature and humidity, are well-captured in reanalysis. Reanalysis also reveals an expected equivalent-barotropic anticyclonic anomaly, with anomalously slow midtropospheric westerlies, associated with these heatwaves. A strong spatial correspondence to this structure is also found with a dynamical-systems theoretic analysis. The latter extracts the most-persistent patterns of midtropospheric flow in terms of the so-called ‘persistence metric’, <span><math><mrow><msup><mi>θ</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>. Heatwaves and blocks are far more likely to occur during persistent states. Historic and end-of-21st-century projections capture similar behavior, and the distribution of projected <span><math><mrow><msup><mi>θ</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span> remains largely unchanged, indicating little change in extreme-event persistence. Neither the frequency nor the duration of persistent blocks changes in end-of-century projections, but heatwave intensity does increase. The conclusion is thus that the projected intensification of heatwaves arises from a thermodynamic mechanism and not a dynamic one. This conclusion depends on removing a multi-year running mean background from the flow for the persistence analysis. Without this high-pass filtering, a projected secular increase in persistence arises as the flow becomes characterized by a regional warming trend pattern.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100791"},"PeriodicalIF":6.1,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144596451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vegetation drought condition index for probabilistic monitoring and forecasting of vegetation drought","authors":"Jeongeun Won ,&nbsp;Jeongju Lee ,&nbsp;Sangdan Kim","doi":"10.1016/j.wace.2025.100786","DOIUrl":"10.1016/j.wace.2025.100786","url":null,"abstract":"<div><div>As the impacts of meteorological drought on vegetation have intensified, there is a growing need for a system that can quantitatively assess and forecast vegetation drought. This study proposes a vegetation drought monitoring and forecasting framework utilizing a copula-based probabilistic approach to address this need. By constructing a joint probability distribution between a meteorological drought index and a vegetation index, we developed the Vegetation Drought Condition Index (VDCI), which was then integrated with numerical weather prediction data to establish a probabilistic vegetation drought forecasting framework. The VDCI is capable of selectively detecting vegetation stress caused by meteorological conditions and enables the quantitative assessment of drought severity through a four-level vegetation drought classification criteria. Spatial and temporal analyses confirmed that the VDCI can identify vegetation drought more clearly than individual indices. Moreover, the probabilistic forecasting framework demonstrated excellent forecasting performance with an average F1-score of approximately 0.9 across all pixels. This study proposes a framework enabling quantitative monitoring and forecasting of vegetation drought based on the probabilistic relationship between meteorological drought and vegetation response, and is expected to contribute to the development of ecosystem-based drought early warning and response strategies in the future.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100786"},"PeriodicalIF":6.1,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attribution of heat extremes and its health effects in Yangtze River Basin in late summer 2024","authors":"Liwen Ren ,&nbsp;Yi Li ,&nbsp;Hui Chen ,&nbsp;Zhen Liao ,&nbsp;Yihui Ding","doi":"10.1016/j.wace.2025.100787","DOIUrl":"10.1016/j.wace.2025.100787","url":null,"abstract":"<div><div>During the summer of 2024, the Yangtze River Basin (YZB) suffered from relentless heat. In particular, the late summer (from the 20th August to the 20th September) witnessed record-breaking high temperature anomalies ranging from daily to monthly timescales, reaching 5.19 °C (∼4.42 standard deviations) above the 1981–2010 mean. The Sichuan Basin was the most affected areas. Our analysis suggested that such heat event would not have occurred without past human activities, and the occurrence probability of similar events is expected to increase by 91 times by the end of the 21st century under the SSP2-4.5 scenario. We further assessed population exposure to heat-related health risks during the heat event, based on the Heat Health Risk Early Warning Level recommended by China CDC. During the summer of 2024, the late summer phase suffered the most from a prolonged period of the highest-level heat health risks (level-3), with 20 % of the population exposed. Simultaneously, there is a growing vulnerability of the population to all levels of heat health risks over the past decades, with exposures to both level-1 and level-2 reaching historical peaks in 2024. With a substantial increase in heat days, this increasing trend of population exposure to heat health risks is expected to continue in the future. Under the SSP2-4.5 scenario, for the level-1 heat health risk, an extra 20 % of the YZB population might face such conditions by 2035 comparable to the 2024 exposure. By the 2090s, the population exposure to record-breaking heat registered in late summer of 2024 will be normal, affecting 40 % of the projected population. Our study provides critical insights into the association between climate change and heat health risks from the 2024-like heat event in the YZB, highlighting the urgent need for heat health early warnings and adaptive measures.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100787"},"PeriodicalIF":6.1,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 hybrid statistical-dynamical method to translate past extreme temperature days into the future climate","authors":"Julien Boé,&nbsp;Margot Bador,&nbsp;Laurent Terray","doi":"10.1016/j.wace.2025.100785","DOIUrl":"10.1016/j.wace.2025.100785","url":null,"abstract":"<div><div>This study presents a novel hybrid statistical-dynamical method intended to translate past observed weather events into the future climate, and applies it to warm and cold extreme temperature days over western Europe. The method estimates the temperature anomalies that would result if an observed event of the 1940–2023 period, defined in terms of atmospheric circulation, were to occur at the end of the 21st century, under new climatological conditions. In practice, constructed analogues of observed extreme events are built using data from regional climate projections. Three regional climate projections under the RCP8.5 emissions pathway are used in order to assess the role of model uncertainties in this context. The same approach is also used beforehand to assess the role of large-scale circulation in the observed extreme temperature days, and the ability of regional climate models to capture it is evaluated. The study finds significant variability in the role of atmospheric dynamics in extreme temperature days, contributing 35–80 % of the temperature anomaly for warm days and 20–90 % for cold days, with other factors such as land-atmosphere interactions playing an amplifying role. Regional climate models generally capture the dynamical part of temperature anomalies quite correctly. Not surprisingly extreme temperature days become more intense in the future climate, but a large inter-event spread exists. Some of the events could become much warmer, while others would not change much. Moreover, this intensification varies widely between regional climate models, and not necessarily in line with the average warming.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"49 ","pages":"Article 100785"},"PeriodicalIF":6.1,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}