Meteorological Applications最新文献

{"title":"Impacts of aerosol meteorological feedback on China's yield potential of soybean","authors":"Xinyan Wang,&nbsp;Linxiao Zhu,&nbsp;Yueting Hao,&nbsp;Zilin Wang,&nbsp;Lian Xue,&nbsp;Ke Ding,&nbsp;Xin Huang","doi":"10.1002/met.2198","DOIUrl":"https://doi.org/10.1002/met.2198","url":null,"abstract":"<p>China's severe particle pollution could affect the regional climate and weather conditions that consequently threaten local to global food security. Yet, the underlying mechanisms and quantitative assessment of aerosols on crop yields remain unknown. Here, by integrating a meteorology–chemistry model and a crop model, we show the impacts of atmospheric aerosols on China's meteorology and soybean yields. We find that the potential yields of soybean would decrease in most parts of China due to direct aerosol radiation effects, while showing diverse responses in parts of the Northeast and North China Plain. Moreover, because of the high sensitivity of soybean growth to water, potential yield fluctuations are closely related to aerosol-induced precipitation changes in most soybean-growing regions of China. In particular, aerosols play the most important role during soybean's pod-filling stage, in which the influence of both precipitation perturbations and negative solar radiative forcing is about 5–10 times that of air temperature on crop yield. Our study thereby identifies aerosol mitigation can bring a notable increase in crop yields, highlighting the potential for important co-benefits in food security across polluting developing countries.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2198","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648086","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":"Deep learning-based postprocessing for hourly temperature forecasting","authors":"Li Zhou,&nbsp;He Chen,&nbsp;Lin Xu,&nbsp;Rong-Hui Cai,&nbsp;Dong Chen","doi":"10.1002/met.2194","DOIUrl":"https://doi.org/10.1002/met.2194","url":null,"abstract":"<p>In this article, a prediction model based on spatiotemporal stacked ResNet (Res-STS) for hourly temperature prediction is designed. On the timescale, the Res-STS removes the gate structure of the long short-term memory (LSTM) model, and the data of multiple consecutive time nodes are stacked together to preserve all temporal characteristics of the data. A point-to-point data mapping relationship is developed on the spatial scale to maximize the impact of large-scale environmental background field characteristics on a single grid point. Based on the historical gridded data from the China Meteorological Administration land data assimilation system (CLDAS) and the optimal factor dataset of the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) from 2017 to 2020, hourly temperature prediction models based on convolutional long short-term memory (ConvLSTM) and Res-STS model are developed, respectively. Furthermore, the prediction results of the two models in 2021 are compared with the ECMWF-IFS. The results show that the root mean square error (RMSE) of the prediction results by ConvLSTM and Res-STS models are both smaller than that of ECMWF-IFS. Specially, the Res-STS model performs best: it reduces the RMSE by 20.8% (24.5%) compared with the ConvLSTM (ECMWF-IFS). Specifically, the RMSE peaks in the afternoon when the daily maximum temperature occurs, while it is relatively smaller at night. Res-STS demonstrates a significant improvement in forecast performance compared with ECMWF-IFS, while ConvLSTM's correction during the period of maximum temperature occurrence has been enhanced. Moreover, the forecast performance of the Res-STS model is least affected by terrain compared with those of the ConvLSTM and ECMWF-IFS. For the regions with terrain height greater than 1 km, the model Res-STS evidently improves the RMSE.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2194","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648088","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":"Characteristics of mesoscale convective systems and related precipitation in the three-river-source region of China","authors":"Qiyu Xie,&nbsp;Xiuping Yao","doi":"10.1002/met.2181","DOIUrl":"https://doi.org/10.1002/met.2181","url":null,"abstract":"<p>Mesoscale convective systems (MCSs) are important air water sources to the Three-river-source (TRS) region known as the “Chinese water tower.” Using hourly equivalent blackbody temperature (<i>T</i>_BB) data from geostationary satellites of Chinese Fengyun-2 series during the warm season (May–August) in 2005–2020 and an objective algorithm, MCSs in the TRS are divided into meso-α (M_αCS), meso-β (M_βCS), and meso-γ (M_γCS), and M_αCS and M_βCS are subdivided into larger meso-α (LM_αCS), smaller meso-α (SM_αCS), larger meso-β (LM_βCS), and smaller meso-β (SM_βCS). Results show that a high-frequency zone of MCSs in the TRS distributes along the source of the rivers. Most MCSs, except LM_αCS, develop and dissipate in situ. The interannual variation in MCS frequency exhibits a decreasing trend, especially after 2013, mainly due to the decrease in MCSs in the source region of the Yellow–Lancang River. The occurrence of MCSs peaks in August, but MCSs are most likely to produce precipitation in July and usually generate between 1600–2200 h LST (UTC + 8). The precipitation caused by MCSs to the total precipitation (precipitation ratio, PR) accounts for about 40%; MCS PR is closely related to, and increases with, the horizontal scale of the MCS, with M_αCS PR being the highest, exceeding 67%. The contribution of MCSs to precipitation is mainly reflected in weak precipitation, smaller than 10.0 mm/h. Most of the maximum precipitation of MCSs appears after MCSs reach their prime, with the maximum lag by M_αCS up to 2 h.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648089","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":"Global hydrological reanalyses: The value of river discharge information for world-wide downstream applications – The example of the Global Flood Awareness System GloFAS","authors":"Christel Prudhomme,&nbsp;Ervin Zsótér,&nbsp;Gwyneth Matthews,&nbsp;Angelique Melet,&nbsp;Stefania Grimaldi,&nbsp;Hao Zuo,&nbsp;Eleanor Hansford,&nbsp;Shaun Harrigan,&nbsp;Cinzia Mazzetti,&nbsp;Eric de Boisseson,&nbsp;Peter Salamon,&nbsp;Gilles Garric","doi":"10.1002/met.2192","DOIUrl":"https://doi.org/10.1002/met.2192","url":null,"abstract":"<p>Global hydrological reanalyses are modelled datasets providing information on river discharge evolution everywhere in the world. With multi-decadal daily timeseries, they provide long-term context to identify extreme hydrological events such as floods and droughts. By covering the majority of the world's land masses, they can fill the many gaps in river discharge in-situ observational data, especially in the global South. These gaps impede knowledge of both hydrological status and future evolution and hamper the development of reliable early warning systems for hydrological-related disaster reduction. River discharge is a natural integrator of the water cycle over land. Global hydrological reanalysis datasets offer an understanding of its spatio-temporal variability and are therefore critical for addressing the water–energy–food–environment nexus. This paper describes how global hydrological reanalyses can fill the lack of ground measurements by using earth system or hydrological models to provide river discharge time series. Following an inventory of alternative sources of river discharge datasets, reviewing their advantages and limitations, the paper introduces the Copernicus Emergency Management Service (CEMS) Global Flood Awareness System (GloFAS) modelling chain and its reanalysis dataset as an example of a global hydrological reanalysis dataset. It then reviews examples of downstream applications for global hydrological reanalyses, including monitoring of land water resources and ocean dynamics, understanding large-scale hydrological extreme fluctuations, early warning systems, earth system model diagnostics and the calibration and training of models, with examples from three Copernicus Services (Emergency Management, Marine and Climate Change).</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2192","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140550187","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":"Causes of an extremely low visibility event in Northeast China","authors":"Dianbin Cao,&nbsp;Xuelong Chen,&nbsp;Qiang Zhang,&nbsp;Yanluan Lin,&nbsp;Qinghong Zhang,&nbsp;Yaoming Ma","doi":"10.1002/met.2199","DOIUrl":"https://doi.org/10.1002/met.2199","url":null,"abstract":"<p>An extreme haze-fog event occurred during October 20–22, 2013, in Harbin, Northeast China, which lasted for nearly 60 h with local visibility as low as 20 m. However, causes of the extreme haze-fog formation remain unclear. Through the analysis of in situ data and objective weather circulation classification, it is revealed that high pollutant emissions from biomass burning played a very important role in the extreme event. Stable weather conditions under the circulation type 8 (CT8), marked by weak high-pressure control, strong inversion (6.55°C), shallow boundary layer depth (&lt;300 m), and high relative humidity (&gt;90%), aided in the accumulation of pollutants and hygroscopic aerosol growth. All of these factors collectively contributed to the extreme haze-fog formation. The insights derived from this study can improve the predictability of extreme haze-fog events, and indicate that pollution emissions should be tightly controlled in the adverse meteorological circulation type in Northeast China.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2199","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140550188","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":"The potential value of seasonal drought forecasts in the context of climate change: A case study of the African elephant conservation sector","authors":"Emily Black,&nbsp;Victoria Boult,&nbsp;Linda Hirons,&nbsp;Steven Woolnough","doi":"10.1002/met.2190","DOIUrl":"https://doi.org/10.1002/met.2190","url":null,"abstract":"<p>This study investigates meteorological drought in sub-Saharan Africa within the context of elephant conservation. Prolonged drought significantly impacts elephants, leading to increased mortality rates and heightened human–elephant conflicts. We assess both the anticipated 21st century changes in impact-relevant meteorological drought metrics and the efficacy of existing forecasting systems in predicting such droughts on seasonal time scales. The climate change element of our study uses the 6th Coupled Model Intercomparison Project (CMIP6) ensemble to evaluate projected change in 3-month Standardized Precipitation Index (SPI3). We then carry out a quantitative assessment of seasonal forecast skill, utilizing 110 years of precipitation hindcasts generated by the European Centre for Medium Range Forecasting (ECMWF) system. Our findings indicate that persistent drought is projected to become more frequent over the 21st century in southern Africa, where the majority of elephants reside. Analysis of seasonal hindcasts indicates that, while the forecasts have greater skill than climatology, they remain highly uncertain. Previous work suggests that it may be possible to reduce this uncertainty by contextualizing forecasts within specific climate regimes. However, even with improved forecast skill, effective action hinges on the alignment of forecasts with the practical needs of conservation practitioners. Over the next decades, a co-production approach will be critical for leveraging seasonal forecasts for climate change adaptation within the conservation sector.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2190","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140310309","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":"Operational scheme for predicting tropical cyclone wind radius based on a statistical–dynamical approach and track pattern clustering","authors":"Hye-Ji Kim,&nbsp;Il-Ju Moon,&nbsp;Seong-Hee Won","doi":"10.1002/met.2193","DOIUrl":"https://doi.org/10.1002/met.2193","url":null,"abstract":"<p>An operational scheme for predicting the symmetric R30 and R50 of tropical cyclones (TCs) in the western North Pacific was developed using a statistical regression method and track pattern clustering (four clusters). The statistical–dynamical model employs multiple linear regressions of two to eight variables at each cluster and forecast lead time. The dependent variable for prediction was the change in the 5-kt wind radius (R5)—a proxy of TC size—relative to the initial time. The performance of the model was compared for the training (2008–2016) and testing (2017–2018) periods. The effect of clustering on TC size prediction was evaluated by comparing the performance of the non-clustering and clustering models. The clustering model improved the prediction of TC size by 3%–24% at all lead times during the training period, especially with a significant improvement of up to 43% in Cluster 2. In Cluster 2, because most TCs tend to develop strongly and continue to increase in size, it greatly reduced the variability in TC size through clustering, allowed for smarter predictor selection, and ultimately improved TC size prediction. In the real-time R30 and R50 predictions for the 2017 and 2018 TCs, the error of the clustered model was 18%–19% less than that of the non-clustered model. The analysis results revealed that the real-time prediction errors of the current model increase when the TC tracks are difficult to classify into specific clusters, the predicted environments and TC tracks are inaccurate, and the size and intensity of a TC rapidly increase.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2193","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140188616","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":"Revisiting reference evapotranspiration calculation under regional advection and its effect on single and dual crop coefficients: An empirical approach for quinoa crop","authors":"Mohammad Hadi Razmavaran,&nbsp;Ali Reza Sepaskhah,&nbsp;Seyed Hamid Ahmadi","doi":"10.1002/met.2189","DOIUrl":"https://doi.org/10.1002/met.2189","url":null,"abstract":"<p>Advection is a prevailing meteorological phenomenon in the arid and semi-arid environments that directly affects the crop and soil hydrology. It could have a great impact on the rate of standard crop evapotranspiration (ET_c) in the irrigated areas. Therefore, it is required to take it into consideration while computing crop water requirement through the physically based meteorological procedures. The objectives of this study are (1) simple modification of the Penman–Monteith (PM) equation in calculation of the grass reference evapotranspiration (ET_o) to implement the local advection, (2) comparing the single (K_c) and dual crop coefficient (K_cb) of two quinoa cultivars (Titicaca, and Q5) with and without advection correction and (3) presenting a simple model to calculate the advection factor using the maximum air temperature and mean relative humidity for the future crop growth modelling studies. Both Q5 and Titicaca showed unexpectedly very high ET_c and potential transpiration (T_p) as 1568 mm and 1003 mm, and 1156 mm and 829 mm, respectively, due to occurrence of regional advection, whereas very high unrealistic K_c and K_cb values for Q5 revealed the impact of strong local advection and external energy. Therefore, we modified ET_o to implement the advection effect through introducing the advection factor, ET_c/R_n (R_n is the net radiation), as a function of maximum air temperature and mean relative air humidity during the growing season [ET_c/R_n = exp (0.025T_max – 0.015RH_avg)] which resulted in higher ET_o values, and consequently lower and more realistic K_c and K_cb. As a result, modified maximum K_c values of 1.14 and 1.55 and the modified maximum K_cb of 0.94 and 1.0 were obtained for Titicaca and Q5 cultivars, respectively. This procedure leads to a more accurate site-specific K_c estimation and indirectly reliable ET_c estimation as a function of advection factor and its multiplication by the non-modified ET_o. Furthermore, for direct estimation of ET_c through the PM equation, the coefficients of aerodynamic and canopy resistance components of PM equation were modified for estimation of ET_c by the non-modified R_n, which resulted in accurate estimation of ET_c.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135404","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":"Climatic interactions between cold surges in the South China Sea and North Pacific extratropical cyclones","authors":"Lan Xia,&nbsp;Jialin Zhang,&nbsp;Yao Hu","doi":"10.1002/met.2182","DOIUrl":"https://doi.org/10.1002/met.2182","url":null,"abstract":"<p>Cold surge events in the South China Sea (over 110–117.5° E longitude at 15° N latitude) from 1979 to 2019 are divided into four types depending on their correlation with North Pacific extratropical cyclones (ECs). Climatologic relationships between the two phenomena reveal that 92% (39%) of all cold surges are accompanied by ECs (explosive extratropical cyclones, abbreviated as EC-E), while 31% of ECs are accompanied by cold surges. The occurrence and development of ECs favour eruptions of cold air from higher latitudes, which in turn produce conditions conducive to cold surges. In the North Pacific, ECs travel in a northeastward direction, ultimately contributing to the Aleutian low. Meanwhile, the westerly jet is observed to strengthen following cold surge events. Both actions drive further EC activity, which in turn facilitates subsequent cold surges. Therefore, when ECs occur before and after cold surges, the cold surge event itself tends to be relatively strong and long lived. The transmission of energy by ECs is a primary link between the high and middle latitudes and contributes to the impact of cold surges on low latitudes. This study also explores the respective influences of the Siberia High and Aleutian Low on cold surges. The majority of cold surges that do not involve ECs occur in the context of the weaker Siberia High and Aleutian Low. Cold surges accompanied with ECs can be even stronger and longer lasting when the Siberia High and Aleutian Low strengthen.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2182","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140114341","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":"High performance computing to support land, climate, and user-oriented services: The HIGHLANDER Data Portal","authors":"Michele Bottazzi,&nbsp;Lucía Rodríguez-Muñoz,&nbsp;Beatrice Chiavarini,&nbsp;Cinzia Caroli,&nbsp;Giuseppe Trotta,&nbsp;Chiara Dellacasa,&nbsp;Gian Franco Marras,&nbsp;Margherita Montanari,&nbsp;Monia Santini,&nbsp;Marco Mancini,&nbsp;Alessandro D'Anca,&nbsp;Paola Mercogliano,&nbsp;Mario Raffa,&nbsp;Giulia Villani,&nbsp;Fausto Tomei,&nbsp;Nicola Loglisci,&nbsp;Estíbaliz Gascón,&nbsp;Timothy Hewson,&nbsp;Giovanni Chillemi,&nbsp;Riccardo Valentini,&nbsp;Damiano Gianelle,&nbsp;Elena Massarenti,&nbsp;Martina Forconi,&nbsp;Lucia Mazzoni,&nbsp;Gabriella Scipione","doi":"10.1002/met.2166","DOIUrl":"https://doi.org/10.1002/met.2166","url":null,"abstract":"<p>The Italian territory is located at the heart of one of the global hot spots of climate change, where the implementation of climate-smart land management practices is imperative to guarantee the present and future maintenance of ecosystem functions as well as the sustainability of human socioeconomic activities. The project HIGHLANDER (HIGH performance computing to support smart LAND sERvices) led by Cineca aims at building a comprehensive and multi-sector framework for land-management decision-making in Italy. The project relies on high quality information on different components of the landscape, with a focus on climate-driven processes, and state-of-the-art computing infrastructures. The HIGHLANDER Data Portal maximizes the impact of HIGHLANDER results by providing access to data products and services. In this article, we describe the architectural features of the platform, as well as the available HIGHLANDER datasets and downstream applications.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2166","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140114215","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}