Weather and Climate Extremes最新文献

{"title":"Predictability assessment of marine heatwaves in the Northeast Pacific based on SEAS5","authors":"Zhouhong Liu ,&nbsp;Boni Wang ,&nbsp;Haixia Shan","doi":"10.1016/j.wace.2025.100773","DOIUrl":"10.1016/j.wace.2025.100773","url":null,"abstract":"<div><div>Marine Heatwaves (MHWs), extreme ocean warming events, have attracted global attention. This research utilizes forecast data from SEAS5 (Seasonal Forecasting System 5) and OISST (Optimum Interpolation Sea Surface Temperature), applying a range of evaluation metrics from both deterministic and probabilistic forecasting viewpoints. It assesses the forecasting performance of the SEAS5 in the Northeast Pacific (NEP) over the period from 1994 to 2021, examining both spatial and temporal dimensions. The midwest of the NEP exhibits subpar performance in terms of both deterministic and probabilistic predictions when compared to other regions. Furthermore, the SEAS5's forecast skill for MHWs is significantly influenced by the El Niño-Southern Oscillation (ENSO) and seasonal variations. This study establishes probability thresholds for MHWs' occurrences to assess MHWs' predictability using SEAS5, demonstrating that forecasting effectiveness across NEP subregions strongly depends on probability thresholds. To evaluate model performance in terms of reliability and resolution, the research concentrates on the Brier Score decomposition, revealing that the southeastern NEP region exhibits superior reliability and resolution. Additionally, the study focuses on not only the comprehensive efficacy of SEAS5 forecast on the NEP as a whole, but also on the specific performance across different regions. The proposed reliability categorization of MHWs indicates that the majority of regions within the NEP fall into Category 3 and above (at least marginally useful) across all lead times. The SEAS5 has shown high predictability in forecasting the occurrences of MHWs in the NEP, exhibiting diverse forecasting accuracy for MHWs across various maritime regions.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100773"},"PeriodicalIF":6.1,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143894955","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":"Editorial: Australia's Tinderbox Drought","authors":"Jason P. Evans, Nerilie J. Abram","doi":"10.1016/j.wace.2025.100766","DOIUrl":"https://doi.org/10.1016/j.wace.2025.100766","url":null,"abstract":"","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"41 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880887","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":"Influence of inner-core symmetry on tropical cyclone rapid intensification and its forecasting by a machine learning ensemble model","authors":"Jiali Zhang ,&nbsp;Qinglan Li ,&nbsp;Liguang Wu ,&nbsp;Qifeng Qian ,&nbsp;Xuyang Ge ,&nbsp;Sam Tak Wu Kwong ,&nbsp;Yun Zhang ,&nbsp;Xinyan Lyu ,&nbsp;Guanbo Zhou ,&nbsp;Gaozhen Nie ,&nbsp;Pak Wai Chan ,&nbsp;Wai Kin Wong ,&nbsp;Linwei Zhu","doi":"10.1016/j.wace.2025.100770","DOIUrl":"10.1016/j.wace.2025.100770","url":null,"abstract":"<div><div>This study proposed a novel quantitative index, the Symmetric Ratio, derived from satellite observations to depict Tropical Cyclone (TC) inner-core symmetry. This index is found to be significantly influential in TC Rapid Intensification (RI). We applied four machine learning (ML) models—Decision Tree, Random Forest, Light Gradient Boosting Machine, and Adaptive Boosting to forecast TC RI in the Northwestern Pacific (WNP) and North Atlantic (NA) basins from 2005 to 2023, with lead times of 12 and 24 hours. An ensemble model integrated these ML models to further enhance prediction accuracy. Model training used TC best track and reanalysis data from 2005 to 2020, with validation from 2021 to 2022. Independent forecasting tests from 2016 to 2023 applied real-time TC track data from the Automated Tropical Cyclone Forecasting system and environmental data from the Global Forecast System. Compared with the best deterministic model with the detection probability (POD) of 21 % and false alarm rate (FAR) of 50 % for 24-h RI forecasts in the NA basin during 2016–2020, our ensemble model demonstrated significant improvements, achieving a POD of 0.27 and an FAR of 0.18 for the same period. For 2021–2023, the ensemble model obtained POD values of 0.24 and 0.41, and FAR values of 0.33 and 0.45 for 24-h predictions in the NA and WNP basins, respectively. Key predictors identified include maximum wind speed tendency, vertical wind shear, potential intensity, and Symmetric Ratio. These findings advance our understanding of TC RI mechanisms and improve prediction accuracy.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100770"},"PeriodicalIF":6.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850719","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":"Exploring synoptic patterns contributing to extreme rainfall from landfalling tropical cyclones in China","authors":"Xiaoting Fan ,&nbsp;Dajun Zhao ,&nbsp;Ying Li ,&nbsp;Xin Zhang ,&nbsp;Yiyun Xie ,&nbsp;Lianshou Chen","doi":"10.1016/j.wace.2025.100768","DOIUrl":"10.1016/j.wace.2025.100768","url":null,"abstract":"<div><div>Extreme rainfall resulted from landfalling tropical cyclones (ERLTC) can lead to severe disasters and enormous economic losses across China, highlighting the critical need to improve ERLTC forecasting accuracy for disaster prevention and mitigation. This study examines 789 ERLTC days in China from 1979 to 2019. These ERLTC days are classified into four dominant synoptic patterns (P1 to P4) using the self-organizing map method based on the configurations of landfalling tropical cyclones (TCs), the western Pacific subtropical high (WPSH), and associated low-level water vapor transport. These four patterns are characterized as follows: P1 (33.0 %) reflects a typical mid-summer circulation with WPSH and south Asian high (SAH) ridge lines around 25°N; P2 (30.0 %) exhibits a northward-shifted WPSH and SAH with double TC circulations; P3 (20.3 %) features a southward-shifted WPSH and SAH with the weakest TC and monsoon circulation; P4 (16.7 %) shows an eastward-shifted WPSH and SAH with the strongest TC circulation. Compared to P1, TCs are positioned further north in P2, further south in P3, and further east in P4. The intensity centers of ERLTC correspond closely with regions of column-integrated water vapor flux convergence and high-level divergence, located in southern coast areas under P1 and P3, southeast mainland and around Bohai Bay under P2, and along eastern coastal areas under P4. Meanwhile, ERLTC is confined to regions south of 30°N in P3 due to weaker water vapor transport. These findings offer valuable insights to comprehensively understand ERLTC events in China.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100768"},"PeriodicalIF":6.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856101","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 enhanced integration of proven techniques to quantify the uncertainty of forecasting extreme flood events based on numerical weather prediction models","authors":"Mitra Tanhapour ,&nbsp;Jaber Soltani ,&nbsp;Hadi Shakibian ,&nbsp;Bahram Malekmohammadi ,&nbsp;Kamila Hlavcova ,&nbsp;Silvia Kohnova ,&nbsp;Peter Valent","doi":"10.1016/j.wace.2025.100767","DOIUrl":"10.1016/j.wace.2025.100767","url":null,"abstract":"<div><div>Skillful forecasting of reservoir inflow is one of the main prerequisites for determining reservoir operation and management policies. This research incorporates proven techniques in a novel way to develop a comprehensive framework for forecasting event-based inflow floods with sub-daily time steps (6-h intervals), considering the uncertainty of Numerical Weather Prediction (NWP) models. Accordingly, raw precipitation forecasts were extracted for six extreme flood events in the Dez River basin, Iran. A Multi-Model Ensemble (MME) system was developed using the Group Method of Data Handling (GMDH) and Weighted Average-Weighted Least Square Regression (WA-WLSR) models to post-process raw precipitation forecasts. We thereupon proposed an approach that combined the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological model with the Long-Short Term Memory (LSTM) network (HBV-LSTM model) to enhance flood forecasting. Moreover, a comparative analysis was performed between the modeling approaches, i.e., probabilistic inflow forecasting and deterministic inflow forecasting. The results revealed that the forecasting skill of the MME model built using the WA-WLSR model was higher than that of the GMDH model. Accordingly, the highest Continuous Ranked Probability Skill Scores (CRPSS) of 0.61 and 0.67 were achieved by the GMDH and WA-WLSR models, respectively, based on a precipitation threshold of 10 mm. Additionally, both the HBV-LSTM model and the LSTM network outperformed the individual HBV model in producing inflow flood hydrographs. Based on the best flood forecasting approach, i.e., the HBV-LSTM model, the <span><math><mrow><mtext>NSE</mtext></mrow></math></span> exceeded 0.95, and the <span><math><mrow><mtext>NRMSE</mtext></mrow></math></span> remained below 0.09 for various flood events. The outcomes indicated a variability of 2–10 % in the relative peak error using the HBV-LSTM approach for different flood events. Our findings provide valuable insights for determining the key elements of reservoir operations and enhancing management strategies under flood conditions.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100767"},"PeriodicalIF":6.1,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850718","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":"Sub-hourly precipitation and rainstorm event profiles in a convection-permitting multi-GCM ensemble","authors":"Marie Hundhausen ,&nbsp;Hayley J. Fowler ,&nbsp;Hendrik Feldmann ,&nbsp;Joaquim G. Pinto","doi":"10.1016/j.wace.2025.100764","DOIUrl":"10.1016/j.wace.2025.100764","url":null,"abstract":"<div><div>Extreme precipitation on short, sub-hourly time scales has the potential to trigger flash floods, is a particular threat to urban areas, and is expected to increase with climate change. However, little is known about sub-hourly precipitation extremes in convection-permitting climate models (CPMs). We investigate sub-hourly precipitation in the KIT-KLIWA ensemble — a CPM climate ensemble driven by 3 CMIP5 GCMs coupled to the regional climate model COSMO-CLM. The domain is centred over Germany with a grid resolution of 0.025<!--> <!-->°(2.8<!--> <!-->km). In an event-based analysis, we compare extreme precipitation down to 5-min resolution for a historical simulation (1971–2000) with the dense radar and raingauge observation network in Germany. We find that 5-min CPM precipitation data adequately reproduces the frequency distribution from radar measurements. To improve the understanding of the precipitation bias in CPM simulations we propose an event-based analysis, that reveals a tendency for the CPM to overestimate the occurrence of longer events, and for a simulation bias in the representation of heavy and short, likely convective, precipitation events. The CPM historical simulations mostly reproduce the event precipitation sum for events leading to 1<!--> <!-->h and 6<!--> <!-->h annual maxima. Maximum 5-min peak intensities of these extreme precipitation events agree with spatially-aggregated radar data but are well below intensity maxima observed in station data. A dominant (very) front-loaded shape for precipitation events leading to 1<!--> <!-->h annual maxima is reproduced by the CPM ensemble. The demonstration that CPMs effectively capture the key features of rainstorm profiles, opens up opportunities for climate change studies and their application in hydrological modelling.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100764"},"PeriodicalIF":6.1,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143847797","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":"Filtering CMIP6 models in the Euro-Mediterranean based on a circulation patterns approach","authors":"Matías Ezequiel Olmo ,&nbsp;Pep Cos ,&nbsp;Diego Campos ,&nbsp;Ángel G. Muñoz ,&nbsp;Vicent Altava-Ortiz ,&nbsp;Antoni Barrera-Escoda ,&nbsp;Martin Jury ,&nbsp;Saskia Loosveldt-Tomas ,&nbsp;Pierre-Antoine Bretonniere ,&nbsp;Francisco Doblas-Reyes ,&nbsp;Albert Soret","doi":"10.1016/j.wace.2025.100765","DOIUrl":"10.1016/j.wace.2025.100765","url":null,"abstract":"<div><div>The performance of a set of 26 CMIP6 global climate models (GCMs) in the Euro-Mediterranean region is analyzed based on a classification of atmospheric circulation patterns (CPs). Their spatial and temporal variability representation, including the associated surface conditions in ERA5 during 1950–2014, allows a ranking of the best-performing GCMs. GCMs manage to reproduce the annual cycle of the CPs frequency, with a dominant summer CP enhancing warm and dry conditions. However, the correct timing of this pattern and the transitional CPs often need to be more accurate. The analysis of the surface patterns related to the different CPs presents overall good model performance, higher for temperatures than for precipitation, particularly in the transition seasons, for which the GCMs spread in their skill score increases. By blending both the spatial and temporal features of the CPs, the EC-Earth3-CC, IPSL-CM6A-LR, EC-Earth3-Veg-LR, MIROC6, and GFDL-ESM4 arise as the best-performing GCMs. This ranking is used to construct multiple model ensembles of climate projections, also taking into account model dependence and spread. Results from this assessment show that future projections of extreme climate indices (2070–2 100)—including the expected increases in the frequency of warm days and dry spells—can be “performance-constrained” and their uncertainty can be more reliably assessed by selecting specific subsets of GCMs, generating tailored climate information at a regional scale. In particular, the warming and drying signals are clearer in the best-performing GCMs, with more robust results in summer than in winter.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100765"},"PeriodicalIF":6.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Observational analysis of long-term streamflow response to flash drought in the Mississippi River Basin","authors":"Bakar Sophia ,&nbsp;Kim Hyunglok ,&nbsp;Basara Jeffrey ,&nbsp;Lakshmi Venkataraman","doi":"10.1016/j.wace.2025.100762","DOIUrl":"10.1016/j.wace.2025.100762","url":null,"abstract":"<div><div>Flash droughts, characterized by rapid onset and severe intensity, pose significant challenges to water resource management. This study investigates the relationship between meteorological conditions and streamflow dynamics during flash drought events within the Mississippi River Basin (MRB) over the period 1980–2022. The MRB has been a hot spot for flash drought events in recent years with significant ecological, agricultural, and economic damages. Existing literature has predominantly focused on studying the meteorological conditions preceding and during flash drought events. However, the media attention on low flows during flash drought events in 2022 and 2023 in the MRB has highlighted the adverse impact of flash droughts on streamflow levels, emphasizing the need to study the connection between flash drought conditions and streamflow dynamics. This study employs the Standardized Antecedent Precipitation Evapotranspiration Index (SAPEI), a daily drought index, to identify flash droughts at the catchment scale and assess the response of streamflow to the identified events across the MRB. Over 1000 flash drought events were identified at the catchment scale. The analysis of these events reveals spatial variations in the frequency, intensity, and duration of flash droughts. The eastern MRB experiences frequent but shorter flash droughts, while the northwest experiences lengthier but less frequent events. The southern region grapples with the most severe drought conditions and is heavily influenced by upstream water management practices. The analysis between SAPEI and streamflow anomalies showed a strong positive correlation in 221 of the 258 catchments with an average ρ of 0.64. The SAPEI-based method for identifying flash droughts and the subsequent comparison with streamflow anomalies is highly transferable, providing a valuable framework for assessing the impacts of flash drought on streamflow and informing water management strategies in other regions. This research significantly contributes to advancing our understanding of flash droughts, offering critical insights for informed water resource management, and bolstering resilience against the impacts of flash droughts.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100762"},"PeriodicalIF":6.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"40-Year statistics of warm-season extreme hourly precipitation over North China","authors":"Zilan Pei ,&nbsp;Xiaopeng Cui ,&nbsp;Rouyi Jiang","doi":"10.1016/j.wace.2025.100761","DOIUrl":"10.1016/j.wace.2025.100761","url":null,"abstract":"<div><div>North China (NC) is confronted with high risks of extreme precipitation events due to global warming and anthropogenic activities. Based on hourly gauge data from May to September during 1983–2022, this study investigates the distributions and trends of extreme hourly precipitation (EHP) and maximum hourly precipitation (MHP) in NC, and their linkages with elevation of stations. EHP is defined as the hourly precipitation exceeding the relative threshold (95th percentile). The results show that the threshold and EHP intensity increase from west to east, while the EHP amount rises from northwest to southeast. Overall, a significant increasing trend is observed in “station-mean” EHP amount in NC from 1983 to 2022, primarily driven by notable increase of EHP frequency. The distribution of EHP variables is closely correlated with elevation. Among the different terrain zones in NC, significant increases in EHP variables are observed both in plains (≤50 m) and mountains (&gt;300 m). Notably, mountain stations show the most pronounced increase in EHP variables, with a noticeable rise in the probability of high-intensity EHP during the latter 20 years of the study period (2003–2022). Analysis of the anomalous circulation and long-term changes of circulation factors reveal that the westward leap expansion of the western Pacific subtropical high (WPSH), and significant increases in temperature and moisture are likely the direct causes of the overall increase of EHP and MHP in NC.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100761"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Breakdown and recovery of the eyewall of Super Typhoon Rai (2021) crossing the Philippine Islands","authors":"Yuki Nakamura,&nbsp;Ryuichi Kawamura,&nbsp;Tetsuya Kawano,&nbsp;Takashi Mochizuki","doi":"10.1016/j.wace.2025.100763","DOIUrl":"10.1016/j.wace.2025.100763","url":null,"abstract":"<div><div>To advance the comprehensive knowledge of the breakdown and recovery processes of tropical cyclones (TCs) that cross the Philippine Islands, we highlighted Super Typhoon Rai (2021)and performed a control (CTL) run and two sensitivity runs in which the topography of the islands was modified, using a regional atmospheric model. The two sensitivity runs consisted of the Flat Land (FL) run, in which the mountain elevation was modified to 0 m, and the Ocean (OC) run, in which the islands were replaced by the ocean. Rai attenuated rapidly in the CTL and FL runs during landfall, and its weakening rate was mostly the same between the two runs. In the two runs, similar decreases in the diabatic heating rate, equivalent potential temperature in the planetary boundary layer (PBL), tangential wind speed, and PBL inflow characterized the eyewall breakdown, suggesting that land surface friction and less surface evaporation facilitate the breakdown process. In contrast, the eyewall recovery was earlier in the FL run than in the CTL run. The wind-terrain interaction due to mountainous terrain may cause the differences in the recovery process between the two runs. When Rai entered the South China Sea, its intensity in the two runs was reinforced rapidly and became comparable to that in the OC run. It was also found that a distinctive change in the observed eye size before and after Rai passes through the islands is not due to the modification forced by the terrain because the eye size in the OC run expands continuously. At the second peak phase of Rai's intensity, the TC sizes in the CTL and FL runs were smaller than that in the OC run, implying that the presence and absence of the eyewall breakdown lead to such a difference. The expansion of the TC size was inhibited even though the eyewall recovered completely after crossing the islands.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"48 ","pages":"Article 100763"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}