Meteorological Applications最新文献

{"title":"Distribution of PM10, PM2.5, and NO2 in the Cergy-Pontoise urban area (France)","authors":"Souad Lagmiri,&nbsp;Salem Dahech","doi":"10.1002/met.2223","DOIUrl":"10.1002/met.2223","url":null,"abstract":"<p>This study employed a network comprising 16 fixed “Ecosmart” sensors deployed in the Cergy-Pontoise conurbation. Continuous measurements of PM₁₀, PM_2.5, and NO₂, significant pollutants in the Paris region, were conducted from April 8 to June 6, 2022. The collected data were represented as statistically composite spatial matrices due to the heterogeneous urban landscape and the overlapping of multiple pollution sources. Temporal variations on a daily basis were influenced by both traffic and meteorological conditions. Daytime, characterized by denser traffic compared to nighttime, exhibited higher concentrations of PM₁₀ and PM_2.5. Conversely, NO₂ concentration levels displayed two peaks associated with traffic volume, and relatively elevated nocturnal values compared with midday due to atmospheric vertical stability during the nighttime phase. The analysis of weather-type impacts revealed that during unstable weather conditions, elevated particle concentrations stemmed from dust resuspension from the ground and long-range transport. Maximum NO₂ concentrations were observed during stable weather conditions, whereas minimum concentrations occurred during unstable weather.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141946671","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":"Skilful probabilistic medium-range precipitation and temperature forecasts over Vietnam for the development of a future dengue early warning system","authors":"Lucy Main,&nbsp;Sarah Sparrow,&nbsp;Antje Weisheimer,&nbsp;Matthew Wright","doi":"10.1002/met.2222","DOIUrl":"https://doi.org/10.1002/met.2222","url":null,"abstract":"<p>Dengue fever is a source of substantial health burden in Vietnam. Given the well-established influence of temperature and precipitation on vector biology and disease transmission, predictions of meteorological variables, such as those issued by ECMWF as a world-leading provider of global ensemble forecasts, are likely to be valuable model inputs to a future dengue early warning system. In the absence of established verification at municipal and regional scales, this study assesses the skill of rainy season (May–October) ensemble precipitation and 2-m temperature retrospective forecasts over North and South Vietnam initialized for dates during the period 2001–2020, evaluated against the ERA5 reanalysis for the same period. Forecasts are found to be significantly skilful compared with both climatology and persistence for lead times up to 10 days, including for cumulative precipitation values considered against independent rain gauge data. Rank histograms demonstrate that ensembles generally avoid excessive bias and consistently positive CRPSS values indicate substantial skill for temperature and cumulative precipitation forecasts for all spatial scales considered, despite differences in rainy season characteristics between North and South Vietnam. This forecast reliability demonstrates that meteorological input data based on ECMWF ensemble forecasts would add appreciably more value to the development of a future dengue early warning system compared to reference forecasts like climatology or persistence. These results raise hope for further exploration of predictive skill for relevant meteorological variables, particularly focused on their downscaling to produce district-level epidemiological forecasts for urban areas where dengue is most prevalent.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141967588","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":"Utilization of the Google Earth Engine for the evaluation of daily soil temperature derived from Global Land Data Assimilation System in two different depths over a semiarid region","authors":"Abolghasem Akbari,&nbsp;Majid Rajabi Jaghargh,&nbsp;Azizan Abu Samah,&nbsp;Jonathan Peter Cox,&nbsp;Mojtaba Gholamzadeh,&nbsp;Alireza Araghi,&nbsp;Patricia M. Saco,&nbsp;Khabat Khosravi","doi":"10.1002/met.2221","DOIUrl":"10.1002/met.2221","url":null,"abstract":"<p>The Google Earth Engine (GEE) was used to investigate the performance of the Global Land Data Assimilation System (GLDAS) soil temperature (ST) data against observed ST from 13 synoptic stations over a semiarid region in Iran. Three-hourly ST data were collected and analyzed in two depths (0–10 cm; 40–100 cm) and 5 years. In each depth, GLDAS-Noah ST data were evaluated for daily minimum, maximum, and average ST (i.e., <i>T</i>_min, <i>T</i>_max, and <i>T</i>_avg). Based on the correlation coefficient, Kling–Gupta Efficiency, and Nash–Sutcliffe Efficiency the overall performance of the GLDAS-Noah is 0.96, 0.66, and 0.79 for <i>T</i>_min; 0.97, 0.84, and 0.89 for <i>T</i>_avg; and 0.95, 0.89, and 0.89 for <i>T</i>_max, respectively in the first layer. Likewise, 0.97, 0.85, and 0.86 for <i>T</i>_min; 0.97, 0.77, and 0.80 for <i>T</i>_avg; and 0.97, 0.69, and 0.69 for <i>T</i>_max are obtained in the second layer. However, there is a significant negative bias which tends to underestimate ST in the two investigated layers, given by an average bias over all the stations analyzed of −24%, −12%, and −5% for <i>T</i>_min, <i>T</i>_avg, and <i>T</i>_max in the first layer, and average bias of −8%, −13%, and −17% for <i>T</i>_min, <i>T</i>_avg, and <i>T</i>_max in the second layer. This study reveals that GLDAS-Noah-derived ST can be used in arid regions where little or no observation data is available. Moreover, GEE performed as an advanced geospatial processing tool in regional scale analysis of ST in different layers.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2221","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868828","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":"What can we learn from nested IoT low-cost sensor networks for air quality? A case study of PM2.5 in Birmingham, UK","authors":"Nicole Cowell,&nbsp;Clarissa Baldo,&nbsp;Lee Chapman,&nbsp;William Bloss,&nbsp;Jian Zhong","doi":"10.1002/met.2220","DOIUrl":"10.1002/met.2220","url":null,"abstract":"<p>Low-cost sensing and the Internet of Things (IoT), present new possibilities for unconventional monitoring of environmental parameters. This paper describes a series of intersecting networks of particulate matter sensors that were deployed across the Birmingham conurbation for a 12-month period. The networks consisted of a combination of commercially available sensors and University developed sensors. Data from these networks were assimilated with data from a third-party Zephyr deployment, along with the DEFRA AURN network, which was hosted on an open-source online platform. This nesting of sensor networks allowed for new insights into sensor performance, including the accuracy of a large network to detect regional concentrations and the number of sensors needed for effective monitoring beyond indicative measurements. After comprehensive data validation steps, the sensors were shown to perform well during co-location with reference instrumentation (exhibiting slopes of 0.74–1.3). The sensors demonstrated good capability of detecting temporal patterns of regional PM_2.5 with the mean of the entire sensor network recording an annual mean PM_2.5 concentration within 0.2 μgm⁻³ of the regulatory network annual mean observation. Network-derived statistics for estimating urban background concentrations compared to a reference site increase in-line with the number of sensors available, however when assessing this for near-source concentrations the importance of sensor location rather than the number of sensors is highlighted. Overall, the network provided novel insights into local concentrations, detecting similar hotspots to those identified by a high-resolution model. The increased spatial coverage afforded by the sensor network has the potential to support higher resolution evaluation of models and provide unprecedented spatial evidence for air pollution management interventions.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2220","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785517","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":"Severe compound events of low wind and cold temperature for the British power system","authors":"Lucie J. Lücke,&nbsp;Chris J. Dent,&nbsp;Gabriele C. Hegerl,&nbsp;Amy L. Wilson,&nbsp;Andrew P. Schurer","doi":"10.1002/met.2219","DOIUrl":"https://doi.org/10.1002/met.2219","url":null,"abstract":"<p>Britain's power system has shifted towards a major contribution from wind energy. However, wind is highly variable, and exceptionally low wind events can simultaneously occur with cold conditions, which increase demand. These conditions can pose a threat for the security of energy supply. Here we use bias-corrected wind supply data and the estimated temperature-related part of demand to analyse events of potential weather-related energy shortfall based on the historic meteorological record. We conduct sensitivity studies with varying scenarios of Britain's total wind energy capacity and the temperature sensitivity of national demand. These scenarios are estimates for present-day conditions as well as potential future changes of the power system. We apply a new methodology to estimate the potential severity of an event for the power system, and analyse the atmospheric conditions associated with the most severe events. We find that events of potentially severe shortfall are relatively rare and short-lived, and often occur with an atmospheric pattern broadly resembling a negative North Atlantic Oscillation. This broad tendency emerges from a wide range of individual daily weather patterns that cause cold and still conditions. With an increase in wind capacity, it is likely that severe events will become rarer, although the most severe days of the record are relatively insensitive to changes in wind supply and temperature sensitivity of demand under our assumptions.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2219","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730217","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":"Mitigating against the between-ensemble-member precipitation bias in a lagged sub-seasonal ensemble","authors":"Marion Mittermaier,&nbsp;Seshagiri Rao Kolusu,&nbsp;Joanne Robbins","doi":"10.1002/met.2197","DOIUrl":"https://doi.org/10.1002/met.2197","url":null,"abstract":"<p>The Met Office GloSea5-GC2 sub-seasonal-to-seasonal 40-member lagged ensemble consists of members who are up to 10 days different in age such that the between-ensemble-member bias is not internally consistent. Reforecasts tend to be used to convert these ensemble forecasts into anomalies from a normal state. These anomalies are however not that useful for applications where individual ensemble members are needed to drive downstream applications in the hazard and impact space. Here we explore whether there is a way of correcting for the within-ensemble bias without using reforecasts. An investigation into the individual daily precipitation distributions from the JJAS 2019 Indian monsoon season, stratified by forecast horizon, highlights how the distribution changes, and shows that the model distribution is markedly different to the observed. Initial results suggest that it could be better to use recent model forecast distribution(s) as the reference for adjusting the model rainfall accumulations as a function of lead day horizon, that is, not attempting to correct the members to a vastly different (observed) distribution shape, but a more subtle shift towards the model's best guess of reality, rather than reality itself, to remove the between-ensemble-member bias. A combination of Exponential and Generalized Pareto distributions are used for parametric quantile mapping to remove this internal ensemble bias using computationally efficient pre-computed lookup tables. Within- and out-of-sample results for the 2019 and 2020 monsoon seasons show that the method is effective in tightening precipitation gradients, with improvements in spread, accuracy and skill, especially for low accumulations.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2197","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326510","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":"Celebrating the 30th anniversary of Meteorological Applications","authors":"Cristina Charlton-Perez,&nbsp;Dino Zardi","doi":"10.1002/met.2214","DOIUrl":"https://doi.org/10.1002/met.2214","url":null,"abstract":"&lt;p&gt;It is with great pride that we mark the 30th anniversary of the journal &lt;i&gt;Meteorological Applications&lt;/i&gt;, and we take this opportunity to provide our readers with a review of the journal's accomplishments to date and with historical context. Indeed, this journal belongs to the forecasters, applied meteorologists, climate scientists and all users or providers of meteorological and climate services, including early career scientists and both graduate and undergraduate students who read and publish contributions on all aspects of meteorological science, including both weather and climate. We hope that in this editorial we can share with our readers the pleasure that we have had in revisiting our journal's history and the excitement we feel while looking toward the future of our “&lt;i&gt;Met Apps&lt;/i&gt;.”&lt;/p&gt;&lt;p&gt;Founding Editor-in-Chief, Dr. Bob Riddaway, shared many stories with us so that we could give our readers a taste of what it was like to produce Met Apps in its early days. Bob told us that Professor Keith Browning approached him about the idea of creating a new journal for the publication of applied meteorological papers. Bob named our journal specifically to stand out from the plethora of journals at the time that were named “The Journal of…” and he also came up with our nickname “&lt;i&gt;Met Apps&lt;/i&gt;.”&lt;/p&gt;&lt;p&gt;When Met Apps was first published, it was delivered as a paper journal via a subscription service in the post. No online magic in 1994! The journal was published four times per year, and Bob had to make the journey to Bristol each time to proofread every page before it could be printed and distributed. The entire submission and review process of manuscripts was conducted via post which, you can imagine, slowed down time to publication when compared with today.&lt;/p&gt;&lt;p&gt;In 1994, the published scope described Met Apps as including “&lt;i&gt;Science and technology needed to support meteorological applications&lt;/i&gt;.” Today Met Apps has a tagline encapsulating that spirit and also showing how climate is relevant to our journal: “&lt;i&gt;Science and Technology for Weather and Climate&lt;/i&gt;.”&lt;/p&gt;&lt;p&gt;The aims and scope has changed very little, and throughout its life, Met Apps has constantly strived to increase the depth and range of contributions from scientists, forecasters and industry colleagues from all over the world and to provide a positive author experience for all. We think that we can still achieve this by continuing to improve practices that lead to fairness, transparency and prompt and in–depth, expert scientific reviews that are not coloured by bias.&lt;/p&gt;&lt;p&gt;In recent years, we have made quite a few changes to the submission and review processes, always keeping the above goals in mind.&lt;/p&gt;&lt;p&gt;Our authors can now benefit from an easier submission process as Met Apps has moved to a free-format submission process. This also supports accessibility, as there is no longer any requirement for templates or specific software to be used to create a manuscript. We have ","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2214","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308887","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":"Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation","authors":"Magdalena Pasierb,&nbsp;Zofia Bałdysz,&nbsp;Jan Szturc,&nbsp;Grzegorz Nykiel,&nbsp;Anna Jurczyk,&nbsp;Katarzyna Ośródka,&nbsp;Mariusz Figurski,&nbsp;Marcin Wojtczak,&nbsp;Cezary Wojtkowski","doi":"10.1002/met.2218","DOIUrl":"https://doi.org/10.1002/met.2218","url":null,"abstract":"<p>Precipitation estimation models are typically sourced by rain gauges, weather radars and satellite observations. A relatively new technique of precipitation estimation relies on the network of Commercial Microwave Links (CMLs) employed for cellular communication networks: the rain-inducted attenuation in the links enables the precipitation estimation. In the paper, it is analysed to what extent the precipitation derived from CML attenuation data is useful in estimation of the precipitation field with the high temporal and spatial resolution required in nowcasting models. Two methods of determination of precipitation along CMLs from attenuation of signal with several frequencies were proposed. Then, in order to generate precipitation field, three approaches for assigning appropriate precipitation values to a specific point or set of pixels along the link are developed and tested. The CML-based estimates are compared with point observations from manual rain gauges and multi-source precipitation fields using daily and half-hourly accumulations. It was found that the CML-based precipitation fields are much worse than radar-derived estimates. At the same time, they had slightly poorer reliability than spatially interpolated telemetric rain gauge data and significantly higher reliability than satellite estimates. Furthermore, the impact of link characteristics, such as length and frequency, on the reliability of CML-based precipitation estimates is analysed.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2218","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304250","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":"Pre-tactical convection prediction for air traffic flow management using LSTM neural network","authors":"Aniel Jardines,&nbsp;Manuel Soler,&nbsp;Javier García-Heras,&nbsp;Matteo Ponzano,&nbsp;Laure Raynaud","doi":"10.1002/met.2215","DOIUrl":"https://doi.org/10.1002/met.2215","url":null,"abstract":"<p>This paper aims to explore machine learning techniques for post-processing high-resolution Numerical Weather Prediction (NWP) products for the early detection of convection. Data from the Arome Ensemble Prediction System and satellite observations from the Rapidly Developing Thunderstorm (RDT) product by Météo-France are used to train a recurrent neural network model to predict areas of total convection and moderate convection. The learning task is formulated as a binary classification problem using a long short-term memory (LSTM) network architecture. Results from the LSTM model are compared with an object-based probabilistic approach to forecast convection using metrics such as a receiver operating characteristics (ROC) curve, the Brier score and reliability. Results indicate that the LSTM model performs similarly to the object-based probabilistic benchmark when classifying moderate convection areas and shows improved skill when classifying areas of total convective. Finally, the LSTM model results are presented within an air traffic management context to showcase the potential use of machine learning models within an operational application.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141286862","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":"Establish an agricultural drought index that is independent of historical element probabilities","authors":"Yongdi Pan,&nbsp;Jingjing Xiao,&nbsp;Yanhua Pan","doi":"10.1002/met.2216","DOIUrl":"https://doi.org/10.1002/met.2216","url":null,"abstract":"<p>Currently, there are three main shortcomings in meteorological drought indices: first, they rely on historical climate probability functions; second, the timescale used in calculations has a certain degree of subjectivity; third, the same index value may correspond to vastly different levels of actual drought in different climate types of regions. The purpose of this article is to establish a meteorological drought index that does not rely on historical meteorological element probability functions. Through theoretical derivation, four drought-level maintenance lines are established on the cumulative precipitation-cumulative water surface evaporation coordinate plane, and the coordinate quadrant is divided into five drought-level areas. Through forward daily rolling accumulation, the maximum distance point is selected from the dynamically changing coordinate points to determine the corresponding cumulative precipitation and cumulative evaporation. The meteorological drought index is established by the distance from the selected coordinate point to each drought-level maintenance line. Using daily precipitation and evaporation data from meteorological observation stations, the index is calculated based on the established meteorological drought index model, and compared with actual drought evolution and drought disaster records. The results show that the index can capture the development of drought well, and its changes are very consistent with drought disaster records. The index is of great significance for drought monitoring or assessment, and can provide guidance for water resource allocation, crop layout, and urban planning. Furthermore, it can also provide a way of thinking that does not rely on historical element probabilities for future drought research.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2216","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141264665","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}