International Journal of Climatology最新文献

{"title":"Climate Change Hotspots for Türkiye","authors":"Nazan An,&nbsp;M. Tufan Turp,&nbsp;Elif Bayindir,&nbsp;Yagmur Akverdi,&nbsp;Zeynep Nur Mirza,&nbsp;M. Levent Kurnaz","doi":"10.1002/joc.8825","DOIUrl":"https://doi.org/10.1002/joc.8825","url":null,"abstract":"<div>\u0000 \u0000 <p>Depending on various indicators, climate change may affect each region globally at varying risk levels. Therefore, identifying the ‘hotspots’ most likely to be affected by climate change in the future is a crucial step in ensuring those areas rapidly adapt to it. The study estimated the Standard Euclidean Distance (SED) for identifying hotspots of Türkiye using high-resolution climate projection data (10 × 10 km) and examined regional vulnerability in the long-term future over a 75-year period (2024–2099). The projections were made using RegCM4.4 driven by MPI-ESM-MR under the optimistic (RCP4.5) and pessimistic (RCP8.5) scenarios. The findings indicate that the hotspot regions in Türkiye are Southeastern Anatolia, Eastern Anatolia and the Mediterranean for RCP4.5, and Southeastern Anatolia, Eastern Anatolia, the Mediterranean and Central Anatolia for RCP8.5. The most critical indicators, however, are temperature-related indicators (i.e., Mean Air Temperature, Hot Seasons and Temperature Variability). Based on the findings, it is necessary to take preventive measures, particularly in highly vulnerable regions, to minimise potential damage. Additionally, multi-model ensemble studies should be applied to reduce the uncertainties and model-related variability, as well as to provide robust evidence of climate change.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in Precipitation Patterns in Poland Derived From Projected Downscaled Future Climate Data From CMIP5 and CMIP6","authors":"Agnieszka Rutkowska,&nbsp;Patrick Willems,&nbsp;Santiago Mendoza Paz,&nbsp;Agnieszka Ziernicka-Wojtaszek","doi":"10.1002/joc.8822","DOIUrl":"https://doi.org/10.1002/joc.8822","url":null,"abstract":"<div>\u0000 \u0000 <p>Climate change is affecting the intensity and frequency of precipitation. The main objective was to assess future changes in precipitation patterns in Poland. Ensembles of daily precipitation projections for 70 stations from CMIP5 and CMIP6 under RCP(SSP)4.5, RCP(SSP)8.5 pathways were statistically downscaled using the Quantile Perturbation Method (QPM), covering the reference period 1961–1990 and future period 2071–2100. We assessed annual and seasonal (winter, summer) changes in 12 extreme Precipitation Indices (PIs), their distributions across Poland, and shifts in design annual maximum (AM) precipitation intensities. Statistical measures included distribution fitting, Intensity-Duration-Frequency curves, and return periods. The projected changes (CMIP6-8.5) in summer include: increase in the length of consecutive dry days (5%, on average), number of heavy precipitation days (4%) and 1-, 3-, 5-day maximum intensity (8%, 6%, 5%), and decrease in the number of wet days (6%) and length of consecutive wet days (6%). In winter, projections show an increase in the number of heavy precipitation days (30%), 1-,3-, 5-day maximum intensity (15%, 13%, 12%), and total precipitation (11%). The changes vary across Poland, with a more intense increase in the number of heavy precipitation days in the north-west (summer) and in the 1-day maximum intensity in the south (winter), higher precipitation totals in the south, southeast and coastal areas (winter), and a decrease in total precipitation in the south and east (summer). Uncertainty is large for the number of heavy precipitation days and maximum intensities, while it is low for total precipitation and the number of wet and dry days. Future return periods of extreme events are projected to shorten. A 100-year 1-day AM intensity can become a <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>49</mn>\u0000 <mo>−</mo>\u0000 <mn>66</mn>\u0000 </mrow>\u0000 </semantics></math>-year intensity. The results can be applied in flood and drought management plans, helping to adapt to future changes in precipitation patterns.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ENSO Diversity Regulation of the Impact of MJO on Extreme Snowfall Events in the Peruvian Andes","authors":"Juan Sulca","doi":"10.1002/joc.8790","DOIUrl":"https://doi.org/10.1002/joc.8790","url":null,"abstract":"<p>Extreme snowfall events (ESEs) in the Peruvian Andes (10°–18.4° S, &gt; 4000 m) result in considerable economic losses. Despite their importance, how El Niño-Southern Oscillation (ENSO) diversity modulates the impact of the Madden–Julian Oscillation (MJO) on ESEs in the Peruvian Andes remains unexplored. Daily ERA5 reanalysis data from 1981 to 2018 were analysed. This study examines 16 ESEs. A bandpass filter with a 20–90-day range was applied to isolate the intraseasonal component of the daily anomalies. Additionally, time series data from the real-time multivariate MJO (RMM) index and Eastern and Central ENSO (E and C) indices were utilised. Composites were performed to describe the atmospheric circulation patterns related to ESEs in the Peruvian Andes under neutral, El Niño and La Niña conditions in the central and eastern Pacific Ocean. Under non-ENSO conditions, the MJO alone does not trigger ESEs in the Peruvian Andes during the DJF season. The absence of a well-organised convection system over the Peruvian Andes prevents ESEs. Conversely, during the JJA season, MJO Phases 5, 6 and 7 induce ESEs in the southern Peruvian Andes by enhancing moisture flux from the east through the equatorward propagation of an extratropical Rossby wave train that crosses South America and reaches the Altiplano region. In terms of ENSO diversity, the combined effects of the Central La Niña and MJO Phases 6 + 7 induce ESEs across the Western Cordillera of the southern Peruvian Andes during the DJF season. During austral winter, the interaction between the Central El Niño and MJO Phases 8 + 1, Eastern El Niño and MJO Phases 2 + 3, and Eastern La Niña and MJO Phases 8 + 1 induce ESEs across the Peruvian Andes.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8790","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Improved Trend Analysis With EOFs and Application to Warming of Polar Regions","authors":"Ewan T. Phillips,&nbsp;Holger Kantz","doi":"10.1002/joc.8823","DOIUrl":"https://doi.org/10.1002/joc.8823","url":null,"abstract":"<p>Given the complexity of climate systems, trends are generally expected to have both global and local features. The use of Empirical Orthogonal Function (EOF) analysis to decompose these different trends has been brought into question. In this paper we show that for land regions of the order of size of most countries the first Principal Component (PC) obtained by EOF analysis in fact captures the entire trend of the time series. We demonstrate a simple linear relation relating the amount of variance described by PCs and the size of the system. We provide a novel normalisation and ordering of the PCs, and show that this provides important insight for larger more complex regions where several PCs are added. We apply this framework along with a recently introduced method to deal with long range correlations to the study of warming trends in the polar regions between 1979 and 2023. We find a significant Arctic warming trend of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <mn>0.71</mn>\u0000 <mspace></mspace>\u0000 <mo>±</mo>\u0000 <mspace></mspace>\u0000 <mn>0.26</mn>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow>\u0000 </semantics></math> K/dec. In the case of Antarctica we find insignificant trends both for West Antarctica and East Antarctica (including ice sheets) of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <mn>0.09</mn>\u0000 <mspace></mspace>\u0000 <mo>±</mo>\u0000 <mspace></mspace>\u0000 <mn>0.13</mn>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow>\u0000 </semantics></math> K/dec. and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <mn>0.08</mn>\u0000 <mspace></mspace>\u0000 <mo>±</mo>\u0000 <mspace></mspace>\u0000 <mn>0.17</mn>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow>\u0000 </semantics></math> K/dec. respectively.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8823","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Characterising Daily Precipitation Concentration and Interannual Variability in China","authors":"Ci Li,&nbsp;Tingju Zhu,&nbsp;A. Sankarasubramanian,&nbsp;Hongbo Zhang,&nbsp;Sadia Bibi","doi":"10.1002/joc.8826","DOIUrl":"https://doi.org/10.1002/joc.8826","url":null,"abstract":"<p>Heavy precipitation events can have catastrophic socioeconomic impacts. Daily distribution of annual precipitation amount is strongly linked to potentially disastrous events—both floods and droughts. Hence, investigating the spatial and temporal characteristics of daily precipitation concentration is of great importance. Here we analysed the concentration index (CI), an indicator that measures the concentration of daily precipitation in a year, and the corresponding percentages of annual precipitation in the 25% rainiest days (hereafter called P-25%) each year from 1960 to 2016 at 602 weather stations across China. Based on the scatter plots of CI and P-25%, we delineated three contiguous zones across the country. The consistency between CI and P-25% is improved within each zone, compared to being evaluated across different zones. We further identified high CI areas in each zone and found the areas of high CI values were shrinking in all zones during 1960–2016. The Mann–Kendall time tendency tests of CI and annual max 1-day precipitation (Rx1day) reveal that extreme precipitation occurs in more concentrated areas in the southeast part of China. Additionally, the coefficient of variation (CV) in CI and P-25% shows their inter-annual variation is less strong in the southern humid regions than in the northwest arid regions. The spatial extent and temporal variation of such areas with high precipitation concentration provide a new perspective for improving preparedness for heavy rain-caused natural disasters such as floods and debris flows.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8826","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Cold Waves in Poland: The Relations to Atmospheric Circulation and Arctic Warming","authors":"Joanna Jędruszkiewicz,&nbsp;Joanna Wibig,&nbsp;Piotr Piotrowski","doi":"10.1002/joc.8813","DOIUrl":"https://doi.org/10.1002/joc.8813","url":null,"abstract":"<p>Winter warming in Europe is most apparent in the northeastern parts. The minimum temperature is increasing there at the rate of 0.5°C–0.7°C per decade. The main objective of the paper was to investigate the changes in the characteristics of cold days (CDs) and cold waves (CWs) in Poland. Then, to study the relationships and changes in the large-scale circulation with regard to CWs in Poland. Due to the increasing minimum temperature, Poland is characterised by a decreasing number of CDs and CWs from November to March 1978–2023. In recent years, CDs in Poland have been significantly less severe and are less extended, whereas CWs occur less frequently and are shorter. Recent changes in temperature and sea-ice cover in the Arctic region entail changes in the large-scale circulation in mid and high latitudes. In the 20th century, CWs in Poland were mainly related to blocking created over Scandinavia and the North Atlantic (Iceland). In the 21st century, some shifts in the centers of action were found, and CWs in Poland are primarily associated with strong blocking created over the Greenland and Ural regions. These blocking situations are followed by a negative NAO/AO and positive Greenland Blocking Index or positive Scandinavian (SCAND) pattern, which are significantly correlated with CWs in winter (SCAND only in February). It needs to be emphasised that the Arctic region is one of the most important source areas of the air masses that reach Poland during the CDs, and this area faces the greatest warming around the globe.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8813","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Predictability of Precipitation and Intraseasonal Variability: Insights From ECMWF Model Skill Over Brazil","authors":"Camila R. Sapucci,&nbsp;Víctor C. Mayta,&nbsp;Pedro L. Silva Dias","doi":"10.1002/joc.8820","DOIUrl":"https://doi.org/10.1002/joc.8820","url":null,"abstract":"<p>This study assesses the capabilities and limitations of the state-of-the-art European Centre for Medium-Range Weather Forecasts (ECMWF) subseasonal to seasonal (S2S) model in forecasting precipitation and a regional intraseasonal oscillation index over Brazil. Distinct from previous studies, we employ a regional index rather than a global one, enabling a more focused analysis of the complex intraseasonal variability. Weekly accumulated precipitation forecasts are evaluated against satellite-derived precipitation data for selected regions within Brazil. Our findings indicate that the ECMWF model demonstrates enhanced forecast skill for up to 4 weeks along the northern coast of Northeast Brazil, where tropical–tropical teleconnections linked to the Madden–Julian Oscillation significantly improve predictability. However, forecast accuracy decays after 2 weeks in subtropical and extratropical areas, such as the South Atlantic Convergence Zone and Southern Brazil, primarily due to challenges in capturing synoptic-scale systems and tropical–extratropical interactions. Additionally, the ECMWF model shows strong predictability for the regional intraseasonal oscillation index up to 10 days, offering valuable insights for planning and decision-making in the face of extreme weather events. This regional index achieves a level of accuracy not possible with a global index, which is less effective at capturing the intraseasonal signals specific to South America and their impacts on extreme weather.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8820","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Projections on Regional Climate and Compound Events in East Asia Based on QDM-Corrected Multiple High-Resolution CORDEX Simulations","authors":"Jueying Chen,&nbsp;Xiaoyu Zhu,&nbsp;Jianping Tang,&nbsp;Shuyu Wang,&nbsp;Yi Yang","doi":"10.1002/joc.8824","DOIUrl":"https://doi.org/10.1002/joc.8824","url":null,"abstract":"<div>\u0000 \u0000 <p>Following the Coordinated Regional Downscaling Experiment East Asia Phase II (CORDEX-EA-II) setting, two regional climate models (RCMs) driven by four global climate models (GCMs) have been used to provide climate change information on surface air temperature and daily precipitation. A trend-preserving bias correction method, quantile delta mapping (QDM), is first validated for the historical period of 1981–2005 and then applied to the future period of 2040–2060 under the Representative Concentration Pathway (RCP) 8.5 scenarios. Results show that QDM is competent in correcting model biases on temperature, precipitation and compound events (CEs, defined as the concurrent occurrence of temperature and precipitation anomalies) for both spatial distributions and annual cycles. For future assessments, a widespread warming is projected over the region, with average temperature changes higher than 1.6°C. Changes in precipitation are more region-variated. Increased precipitation is most significant in the northwestern part of the CORDEX-EA region, and some models also present a decreased precipitation in southeastern China. Climate changes on CEs correspond with the effect of global warming; RCMs present a significant increase in the frequency of hot CEs and an obvious decrease in cold-dry CEs. These results are expected to be useful for future climate assessments and for better understanding of the bias correction technique under climate change situations.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Climate Change Impacts on Streamflow Changes in the Source Region of Yellow River: A Bayesian Vine Copula Machine Learning (BVC-ML) Approach","authors":"Xiaowen Zhuang,&nbsp;Yurui Fan,&nbsp;Baogui Xin","doi":"10.1002/joc.8821","DOIUrl":"https://doi.org/10.1002/joc.8821","url":null,"abstract":"<div>\u0000 \u0000 <p>In this study, we proposed a Bayesian Vine Copula Machine Learning (BVC-ML) method to predict streamflow changes in the Yellow River source area based on projections from three GCMs under various climate change scenarios. The BVC-ML method was to (i) use the vine copula method to reflect the interdependence between the predicted variable (i.e., streamflow) and predictions from different machine learning (ML) techniques, (ii) derive deterministic and probabilistic predictions from the vine copula model conditional on corresponding ML predictions and (iii) integrate predictions from different vine copula models to generate the final results. The proposed BVC-ML method was then applied for future streamflow projections based on outputs from CMIP6. The results from the BVC-ML method show that the studied area would generally experience more streamflow increases in most months, and the increases would become more significant as the climate change shifts from SSP126 to SSP585. The outputs from different GCM models also lead to various streamflow changes in the studied area, with the projections from ACCESS-CM2 leading to the highest streamflow increases. Furthermore, the BVC-ML method is capable of deriving both deterministic and probabilistic predictions from the conditional distributions, and the 10% and 90% quantiles can reflect predictive uncertainties. The results from the quantile predictions show that May, July and October would have the highest increases in streamflow, which are consistent with the mean streamflow increases. Overall, the proposed BVC-ML method is demonstrated to be a promising tool for predicting streamflow changes under different climate change scenarios. The findings would have significant implications for water resource management and climate adaptation over the studied region.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Characteristics and Evolution Mechanisms of the Indian Ocean Tripole Mode and Its Impact on Rainfall Patterns Over India","authors":"Prerna Malik,&nbsp;Bhasha H. Vachharajani,&nbsp;B. Praveen Kumar,&nbsp;P. G. Remya","doi":"10.1002/joc.8815","DOIUrl":"https://doi.org/10.1002/joc.8815","url":null,"abstract":"<div>\u0000 \u0000 <p>The IOT mode is an interannual climate pattern in the Tropical Indian Ocean (TIO), characterised by negative SSTA in both the eastern and western TIO, and positive SSTA in the south-central TIO. Distinct from the IOD, which accounts for 10% of SSTA variability in the TIO, the IOT explains 8% of this variance. This study reveals that strong south-westerly wind anomalies along the Somali coast and Arabian Sea associated with a positive IOT drive intense surface cooling, which spreads across the western basin through lateral advection. A typical positive IOT enhances monsoon winds over northern India, leading to increased rainfall across the Indo-Gangetic Plains, while deflecting monsoon winds further south over the southern peninsula, resulting in reduced rainfall there. Additionally, a cyclonic wind anomaly in the Bay of Bengal dampens winds over regions of northeastern India, suppressing summer monsoon rainfall. The findings underscore the significant role of the IOT in modulating monsoon rainfall and its spatial distribution. This study highlights the IOT's potential to enhance understanding of monsoon variability, and its incorporation into predictive models could improve climate resilience in monsoon-dependent regions.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}