Tropical Cyclone Research and Review最新文献_第7页

Analysis of AI-based techniques for forecasting water level according to rainfall 基于人工智能的降雨水位预报技术分析

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-12-01 DOI: 10.1016/j.tcrr.2021.12.002

Chorong Kim, Chung-Soo Kim

{"title":"Analysis of AI-based techniques for forecasting water level according to rainfall","authors":"Chorong Kim, Chung-Soo Kim","doi":"10.1016/j.tcrr.2021.12.002","DOIUrl":"10.1016/j.tcrr.2021.12.002","url":null,"abstract":"<div><p>Water level forecasting according to rainfall is important for water resource management and disaster prevention. Existing hydrological analysis is accompanied by difficulties in water level forecasting analysis such as topographic data and model parameter optimization of the area. Recently, with the improvement of AI (Artificial Intelligence) technology, a research using AI technology in the water resource field is being conducted.</p><p>In this research, water level forecasting was performed using an AI-based technique that can capture the relationship between data. As the watershed for the study, the Seolmacheon catchment which has the rich historical hydrological data, was selected. SVM (Support Vector Machine) and a gradient boosting technique were used for AI machine learning. For AI deep learning, water level forecasting was performed using a Long Short-Term Memory (LSTM) network among Recurrent Neural Networks (RNNs) used for time series analysis.</p><p>The correlation coefficient and NSE (Nash-Sutcliffe Efficiency), which are mainly used forhydrological analysis, were used as performance indicators. As a result of the analysis, all three techniques performed excellently in water level forecasting. Among them, the LSTM network showed higher performance as the correction period using historical data increased.</p><p>When there is a concern about an emergency disaster such as torrential rainfall in Korea, water level forecasting requires quick judgment. It is thought that the above requirements will be satisfied when an AI-based technique that can forecast water level using historical hydrology data is applied.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 4","pages":"Pages 223-228"},"PeriodicalIF":2.9,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603221000461/pdfft?md5=0d0081342740112a8759bcca377f54fc&pid=1-s2.0-S2225603221000461-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47522499","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}

引用次数: 4

Comparison of the performance of a hydrologic model and a deep learning technique for rainfall- runoff analysis 水文模型和深度学习技术在降雨径流分析中的性能比较

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-12-01 DOI: 10.1016/j.tcrr.2021.12.001

Chorong Kim, Chung-Soo Kim

{"title":"Comparison of the performance of a hydrologic model and a deep learning technique for rainfall- runoff analysis","authors":"Chorong Kim, Chung-Soo Kim","doi":"10.1016/j.tcrr.2021.12.001","DOIUrl":"10.1016/j.tcrr.2021.12.001","url":null,"abstract":"<div><p>Rainfall-runoff analysis is the most important and basic analysis in water resources management and planning. Conventional rainfall-runoff analysis methods generally have used hydrologic models. Rainfall-runoff analysis should consider complex interactions in the water cycle process, including precipitation and evapotranspiration. In this study, rainfall-runoff analysis was performed using a deep learning technique that can capture the relationship between a hydrological model used in the existing methodology and the data itself. The study was conducted in the Yeongsan River basin, which forms a large-scale agricultural area even after industrialization, as the study area. As the hydrology model, SWAT (Soil and Water Assessment Tool) was used, and for the deep learning method, a Long Short-Term Memory (LSTM) network was used among RNNs (Recurrent Neural Networks) mainly used in time series analysis. As a result of the analysis, the correlation coefficient and NSE (Nash-Sutcliffe Efficiency), which are performance indicators of the hydrological model, showed higher performance in the LSTM network. In general, the LSTM network performs better with a longer calibration period. In other words, it is worth considering that a data-based model such as an LSTM network will be more useful than a hydrological model that requires a variety of topographical and meteorological data in a watershed with sufficient historical hydrological data.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 4","pages":"Pages 215-222"},"PeriodicalIF":2.9,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S222560322100045X/pdfft?md5=d23bfc73ce457cb23b9328c31b5ddd4c&pid=1-s2.0-S222560322100045X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49549411","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}

引用次数: 9

Review of the achievement of ssop and its inspiration for future regional cooperation 回顾ssop的成就及其对未来区域合作的启示

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-12-01 DOI: 10.1016/j.tcrr.2021.11.001

Jixin Yu, Jinping Liu, Lisa Kou

{"title":"Review of the achievement of ssop and its inspiration for future regional cooperation","authors":"Jixin Yu, Jinping Liu, Lisa Kou","doi":"10.1016/j.tcrr.2021.11.001","DOIUrl":"https://doi.org/10.1016/j.tcrr.2021.11.001","url":null,"abstract":"<div><p>Countries in Asia and the Pacific are more prone to natural disasters than those in other parts of the world. Because of this, there is an urgent need to continue developing effective, end-to-end early warning systems that lead to an effective response by emergency managers and people at risk. ESCAP/WMO Typhoon Committee (TC), in cooperation with WMO/ESCAP Panel on Tropical Cyclones (PTC), conducted a regional cooperation project on Synergized Standard Operating Procedures for Coastal Multi-Hazards Early Warning System (SSOP) with fund support from ESCAP Multi-Donor Trust Fund for Tsunami, Disaster and Climate Preparedness in Indian Ocean and South East Asia. SSOP project was conducted successfully and achieved its proposed goals. Its results and achievements greatly benefit the Members not only in the region but also in all other regions of WMO. The paper reviewed its implementation process, strategy and activities; briefed its main achievements including SSOP Manual, capacity building and cooperation mechanism between TC and PTC; summarized the experiences and lessons from project implementation; and highlighted its sustainability. The paper also suggested the approaches to enhance the sustainability of SSOP results and the cooperation between two regional bodies TC and PTC.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 4","pages":"Pages 229-236"},"PeriodicalIF":2.9,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603221000357/pdfft?md5=7f7695e738f5c9953ceefccd91b7dd4b&pid=1-s2.0-S2225603221000357-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91780298","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}

引用次数: 1

An Evaluation of the Advanced Dvorak Technique (9.0) for the tropical cyclones over the North Indian Ocean 先进Dvorak技术(9.0)对北印度洋热带气旋的评价

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-12-01 DOI: 10.1016/j.tcrr.2021.11.003

Rizwan Ahmed , M. Mohapatra , Ram Kumar Giri , Suneet Dwivedi

引用次数: 2

Review of the achievement of ssop and its Inspiration for furture regional cooperation 回顾ssop的成果及其对未来区域合作的启示

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-11-01 DOI: 10.1016/j.tcrr.2021.11.001

Jixin Yu, Jinping Liu, Lisa Kou

引用次数: 1

Characteristics of fog in relation to tropical cyclone intensity: A case study for IGI airport New Delhi 与热带气旋强度有关的雾的特征:以新德里IGI机场为例

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-09-01 DOI: 10.1016/j.tcrr.2021.09.004

Rizwan Ahmed , Narendra G. Dhangar , Suneet Dwivedi , Ram Kumar Giri , Prakash Pithani , Sachin D. Ghude

{"title":"Characteristics of fog in relation to tropical cyclone intensity: A case study for IGI airport New Delhi","authors":"Rizwan Ahmed , Narendra G. Dhangar , Suneet Dwivedi , Ram Kumar Giri , Prakash Pithani , Sachin D. Ghude","doi":"10.1016/j.tcrr.2021.09.004","DOIUrl":"10.1016/j.tcrr.2021.09.004","url":null,"abstract":"<div><p>Widespread catastrophic fog episodes in polluted northern India have been attributed to tropical cyclone activity in the Bay of Bengal & Arabian Sea; however, limited studies have been conducted on the effect of tropical cyclone intensity (‘T’ Numbers) on different fog characteristics in Indo Gangetic Basin, Northern India. In this study, different characteristics, including persistence, intensity, and areal extension, were analyzed at the Indira Gandhi International Airport, New Delhi during 1998–99, 2013–14, and 2016–17. A high-intensity tropical cyclone (Severe to Very Severe Cyclonic Storm) has been found to significantly increase the persistence, intensity, and areal extension of fog by inducing strong subsidence over the IGI Airport/Indo-Gangetic Basin. This knowledge is vital for improving the short-term forecasting of fog in the Indo-Gangetic Basin of Northern India and will further support the Government agencies to take preventive safety measures and planning well in advance time.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 3","pages":"Pages 170-181"},"PeriodicalIF":2.9,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S222560322100028X/pdfft?md5=d975b3d335f94a5e8e9a879e24179c6a&pid=1-s2.0-S222560322100028X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42273719","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}

引用次数: 3

Large tropical cyclone track forecast errors of global numerical weather prediction models in western North Pacific basin 北太平洋西部盆地全球数值天气预报模式的大热带气旋路径预报误差

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-09-01 DOI: 10.1016/j.tcrr.2021.07.001

Chi Kit Tang , Johnny C.L. Chan , Munehiko Yamaguchi

{"title":"Large tropical cyclone track forecast errors of global numerical weather prediction models in western North Pacific basin","authors":"Chi Kit Tang , Johnny C.L. Chan , Munehiko Yamaguchi","doi":"10.1016/j.tcrr.2021.07.001","DOIUrl":"10.1016/j.tcrr.2021.07.001","url":null,"abstract":"<div><p>Although tropical cyclone (TC) track forecast errors (TFEs) of operational warning centres have substantially decreased in recent decades, there are still many cases with large TFEs. The International Grand Global Ensemble (TIGGE) data are used to study the possible reasons for the large TFE cases and to compare the performance of different numerical weather prediction (NWP) models. Forty-four TCs in the western North Pacific during the period 2007–2014 with TFEs (+24 to +120 h) larger than the 75th percentile of the annual error distribution (with a total of 93 cases) are identified.</p><p>Four categories of situations are found to be associated with large TFEs. These include the interaction of the outer structure of the TC with tropical weather systems, the intensity of the TC, the extension of the subtropical high (SH) and the interaction with the westerly trough. The crucial factor of each category attributed to the large TFE is discussed.</p><p>Among the TIGGE model predictions, the models of the European Centre for Medium-Range Weather Forecasts and the UK Met Office generally have a smaller TFE. The performance of different models in different situations is discussed.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 3","pages":"Pages 151-169"},"PeriodicalIF":2.9,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.tcrr.2021.07.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42986418","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}

引用次数: 7

2020 tropical cyclones in the Philippines: A review 2020年菲律宾热带气旋:回顾

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-09-01 DOI: 10.1016/j.tcrr.2021.09.003

Gemma Dela Cruz Santos

{"title":"2020 tropical cyclones in the Philippines: A review","authors":"Gemma Dela Cruz Santos","doi":"10.1016/j.tcrr.2021.09.003","DOIUrl":"10.1016/j.tcrr.2021.09.003","url":null,"abstract":"<div><p>The official website of the Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA) said more tropical cyclones (TCs) enter the Philippine Area of Responsibility (PAR) than anywhere else in the world. With the average of 20 TCs per year, about eight (8) or nine (9) of them are crossing the Philippines. The peak of the typhoon season is July through October, when nearly 70% of all typhoons develop (http://bagong.pagasa.dost.gov.ph/climate/tropical-cyclone-information). Based on the report of the Asian Disaster Reduction Center (ADRC), five of the typhoons that visit the country are destructive and being situated in the “Pacific Ring of Fire” makes the country vulnerable to frequent earthquakes and volcanic eruptions. Its geographical location and physical environment also contribute to its high susceptibility to tsunami, sea-level rise, storm surges, landslides, flash/flood/flooding, and drought (https://www.adrc.asia/nationinformation.php?NationCode = 608&Lang = en). For the past years, some typhoons that visited the country brought serious damages and kill many Filipinos by floods and landslides. The researcher comes up with the idea of assessing the aftermath of 2020 typhoons that visited the country. The data used by the researcher were collected from different sources, namely NDRRMC (National Disaster Risk Reduction and Management Council), PAGASA, social media and other websites. The result of the study reveals that the most destructive typhoon in 2020 that caused huge damage on the infrastructure and agriculture is Ulysses followed by Rolly, Quinta, Ambo, Vicky, Pepito, Ofel, and Marce. Most of the affected areas are those nearer to water bodies, surrounded by mountains with few trees to absorb a huge amount of water and situated in the low-lying areas.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 3","pages":"Pages 191-199"},"PeriodicalIF":2.9,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603221000278/pdfft?md5=caca1ea0bcd3101e4f7817b7f2275b67&pid=1-s2.0-S2225603221000278-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41379262","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}

引用次数: 16

An observational and modeling study of a sea fog event over the yellow and east China seas on 17 March 2014 2014年3月17日黄海和东海一次海雾事件的观测和模拟研究

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-09-01 DOI: 10.1016/j.tcrr.2021.09.001

Jibing Guo , Jie Xu , Xiangming Xu

{"title":"An observational and modeling study of a sea fog event over the yellow and east China seas on 17 March 2014","authors":"Jibing Guo , Jie Xu , Xiangming Xu","doi":"10.1016/j.tcrr.2021.09.001","DOIUrl":"10.1016/j.tcrr.2021.09.001","url":null,"abstract":"<div><p>The Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery, weather charts, objectively reanalyzed data, the observational data and station sounding data were analyzed to investigate a sea fog event occurred over the Yellow and East China Seas on March 17, 2014. The sounding profiles, weather situations and the related meteorological factors during the development and dissipation stages of this sea fog event were documented. Weather Research Forecast (WRF) model was applied to simulate this sea fog case. The simulated horizontal atmospheric visibility, cloud water, humidity, and vertical wind profile during the different stages of this fog event were analyzed. During the development stage of this sea fog, a southerly lower-jet with 16–18 ms-1, an inversion layer and a cold center over the Yellow Sea were detected. The relative humidity in the fog area was above 95%. The specific humidity over the East China Sea was higher than that over the Yellow Sea. Southerly was dominated in fog area. However, during the dissipation stage of this sea fog, westerly replaced the southerly and at the lower level, southerly jet disappeared. A dry air area formed over the Shandong Peninsula and moved eastwards. Moreover, the WRF modeling result showed that the simulated atmospheric horizontal visibility and cloud water were approximately consistent with the MODIS satellite imagery. Most of cloud water concentrated below 200–400 m, and the cloud water in the southern part of fog area extended to a higher height than the northern part. While both of air temperature and dew-point temperature were close to sea surface temperature.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 3","pages":"Pages 182-190"},"PeriodicalIF":2.9,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603221000254/pdfft?md5=e691dea075571674d22caa5570099db1&pid=1-s2.0-S2225603221000254-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43844179","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}

引用次数: 1

Estimating tropical cyclone surface winds: Current status, emerging technologies, historical evolution, and a look to the future 估计热带气旋地面风:现状、新兴技术、历史演变和展望未来

IF 2.9 4区地球科学

Tropical Cyclone Research and Review Pub Date : 2021-09-01 DOI: 10.1016/j.tcrr.2021.09.002

John A. Knaff , Charles R. Sampson , Matthew E. Kucas , Christopher J. Slocum , Michael J. Brennan , Thomas Meissner , Lucrezia Ricciardulli , Alexis Mouche , Nicolas Reul , Mary Morris , Galina Chirokova , Philippe Caroff

{"title":"Estimating tropical cyclone surface winds: Current status, emerging technologies, historical evolution, and a look to the future","authors":"John A. Knaff , Charles R. Sampson , Matthew E. Kucas , Christopher J. Slocum , Michael J. Brennan , Thomas Meissner , Lucrezia Ricciardulli , Alexis Mouche , Nicolas Reul , Mary Morris , Galina Chirokova , Philippe Caroff","doi":"10.1016/j.tcrr.2021.09.002","DOIUrl":"10.1016/j.tcrr.2021.09.002","url":null,"abstract":"<div><p>This article provides a review of tropical cyclone (TC) surface wind estimation from an operational forecasting perspective. First, we provide a summary of operational forecast center practices and historical databases. Next, we discuss current and emerging objective estimates of TC surface winds, including algorithms, archive datasets, and individual algorithm strengths and weaknesses as applied to operational TC surface wind forecast parameters. Our review leads to recommendations about required surface coverage – an area covering at least 1100 km from center of TC at a 2-km resolution in the inner-core, and at a frequency of at least once every 6 h. This is enough coverage to support a complete analysis of the TC surface wind field from center to the extent of the 34-kt (17 m s<sup>−1</sup>) winds at 6-h intervals. We also suggest future designs of TC surface wind capabilities include funding to ensure near real-time data delivery to operators so that operational evaluation and use are feasible within proposed budgets. Finally, we suggest that users of archived operational wind radii datasets contact operational organizations to ensure these datasets are appropriate for their needs as the datasets vary in quality through time and space, even from a single organisation.</p></div>","PeriodicalId":44442,"journal":{"name":"Tropical Cyclone Research and Review","volume":"10 3","pages":"Pages 125-150"},"PeriodicalIF":2.9,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2225603221000266/pdfft?md5=405475d5a2504542b2dcb2d4800b9107&pid=1-s2.0-S2225603221000266-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48691973","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}

引用次数: 27