Principal characteristics of tide gauges considered in Adriatic Sea. Some of the tide gauge records have been formed by collating partial records from different sources. Such situation is marked by an asterisk after the tide gauge name.
\\n\\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\\n\\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\nFeel free to share this news on social media and help us mark this memorable moment!
\\n\\n\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/237"}},components:[{type:"htmlEditorComponent",content:'
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\nIntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\n\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\nFeel free to share this news on social media and help us mark this memorable moment!
\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"8558",leadTitle:null,fullTitle:"Aerodynamics",title:"Aerodynamics",subtitle:null,reviewType:"peer-reviewed",abstract:"Aerodynamics, the study of air motion around solid objects, allows us to understand and measure the dominating forces acting on aircrafts, buildings, bridges, automobiles, and other structures. The forces that result in an aircraft overcoming gravity and drag are called thrust and lift. Various parameters such as geometrical configurations of objects, as well as physical properties of air, which may be functions of position and time, affect those forces. This book covers some of the latest studies regarding the application of the principles of aerodynamics to the design of many different engineered objects. This book will be of interest to mechanical and aerospace engineering students, academics, and researchers who are looking for new insights into this fascinating branch of fluid mechanics.",isbn:"978-1-83880-168-7",printIsbn:"978-1-83880-167-0",pdfIsbn:"978-1-83880-003-1",doi:"10.5772/intechopen.78935",price:119,priceEur:129,priceUsd:155,slug:"aerodynamics",numberOfPages:248,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"db7263fc198dfb539073ba0260a7f1aa",bookSignature:"Mofid Gorji-Bandpy and Aly-Mousaad Aly",publishedDate:"February 10th 2021",coverURL:"https://cdn.intechopen.com/books/images_new/8558.jpg",numberOfDownloads:8028,numberOfWosCitations:5,numberOfCrossrefCitations:14,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:26,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:45,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 27th 2019",dateEndSecondStepPublish:"September 4th 2019",dateEndThirdStepPublish:"November 3rd 2019",dateEndFourthStepPublish:"January 22nd 2020",dateEndFifthStepPublish:"March 22nd 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"35542",title:"Prof.",name:"Mofid",middleName:null,surname:"Gorji-Bandpy",slug:"mofid-gorji-bandpy",fullName:"Mofid Gorji-Bandpy",profilePictureURL:"https://mts.intechopen.com/storage/users/35542/images/system/35542.jpg",biography:"Dr. Mofid Gorji-Bandpy received his MS in Mechanical Engineering from the Faculty of Engineering, University of Tehran, Iran, in 1978. In 1990, he obtained his Ph.D. in Hydraulic Engineering from the School of Engineering, University of Wales College of Cardiff (UWCC), UK. At present, he is a full professor in the Department of Mechanical Engineering at the Babol Noshirvani University of Technology, Babol, Iran. He is also a visiting professor in the Department of Mechanical and Industrial Engineering at the University of Toronto, Canada. His major interests are in advanced methods of energy-conversion systems, turbo machinery, fluid mechanics, water distribution networks, and solutions to both energy and environmental problems. He has published more than 300 papers in these fields. He has also published several refereed publications in different fields of mechanical engineering, applied mathematics, and aerodynamics. In addition, Dr. Gorji-Bandpy was recognized as a Highly Cited Researcher by Clarivate Analytics in 2017 and 2018.",institutionString:"Babol Noshirvani University of Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Babol Noshirvani University of Technology",institutionURL:null,country:{name:"Iran"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"207384",title:null,name:"Aly-Mousaad",middleName:null,surname:"Aly",slug:"aly-mousaad-aly",fullName:"Aly-Mousaad Aly",profilePictureURL:"https://mts.intechopen.com/storage/users/207384/images/system/207384.png",biography:"Dr. Aly-Mousaad Aly is an associate professor at Louisiana State University (LSU). His research aims at creating fundamental knowledge in wind engineering, dynamics, and control to build more resilient, economic, and recoverable infrastructure to enhance safety and reduce the huge cost of rebuilding after windstorms and earthquakes. He is the director of the LSU Windstorm Impact, Science, and Engineering (WISE) research and education program (wise.lsu.edu). His research enables advanced wind testing, which yields loads that mimic those at full scale. His research advanced the implementation of smart dampers in super-tall structures and a novel probabilistic theory that enables the analytical modeling of semi-active damping.",institutionString:"Louisiana State University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Louisiana State University",institutionURL:null,country:{name:"United States of America"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"682",title:"Aerodynamics",slug:"aerospace-engineering-aerodynamics"}],chapters:[{id:"69247",title:"Application of an Asynchronous Synchronous Alternator for Wind Power Plant of Low, Medium and High Power",doi:"10.5772/intechopen.89255",slug:"application-of-an-asynchronous-synchronous-alternator-for-wind-power-plant-of-low-medium-and-high-po",totalDownloads:692,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The chapter shows the prospects for the development of alternative energy. The growth rate of wind energy is ahead of other types of alternative energy, but the development of wind energy is constrained by a number of technical contradictions that need to be solved. The main problem of wind power is that the power and direction of the wind flow are continuously changing. This leads to the fact that the frequency of rotation of the generator constantly varies and alternator produces energy with nonstandard parameters in amplitude, frequency and phase. Converting this energy into energy with standard parameters is a difficult technical task. A brief analysis of the different directions to solve this problem is shown. It is proved that the promising direction of solving this problem from the point of view of efficiency is the use of double-fed induction alternator (DFIA). The chapter describes the principle of operation of the DFIA, the theory of energy conversion based on equivalent circuits. Approaches to the optimal design of generators based on generalized variables are shown. Two variants of the generator design are described. One option is to contain an additional exciter generator to power the rotor. The design of this 10 kW generator is presented. In another version, the power supply function of the rotor is performed by the battery. In addition, the battery performs the function of accumulation of electricity. It is concluded that the development of wind power in the direction of the DFIA is promising. On the basis of the proposed concept, a number of wind power plants can be built with power from 10 kW to 6 MW. DFIA can operate in standalone mode and in conjunction with electrical grid. The design for the range of wind turbines will be the same type. The DFIA will differ only in size.",signatures:"Sergey Gandzha and Anton Kotov",downloadPdfUrl:"/chapter/pdf-download/69247",previewPdfUrl:"/chapter/pdf-preview/69247",authors:[{id:"303625",title:"Dr.",name:"Sergey",surname:"Gandzha",slug:"sergey-gandzha",fullName:"Sergey Gandzha"},{id:"309534",title:"MSc.",name:"Anton",surname:"Kotov",slug:"anton-kotov",fullName:"Anton Kotov"}],corrections:null},{id:"72520",title:"Aerodynamics of Low-Rise Buildings: Challenges and Recent Advances in Experimental and Computational Methods",doi:"10.5772/intechopen.92794",slug:"aerodynamics-of-low-rise-buildings-challenges-and-recent-advances-in-experimental-and-computational-",totalDownloads:717,totalCrossrefCites:1,totalDimensionsCites:5,hasAltmetrics:0,abstract:"Buildings are bluff bodies, compared to streamline objects, such as airfoil. Wind flow over buildings leads to separation and hence a complex spatial and temporal mechanism that governs the nature and intensity of aerodynamic forces. This complexity mainly comes from the transient nature of incident turbulent winds and the fluctuating flow pattern in the separation bubble. The study of building aerodynamics is vital for the evaluation of cladding pressures, drag, shear, and uplift forces that are essential for safe and economic design. Flow separation makes it challenging to estimate loads without referring to direct physical and/or computational simulation. For several decades, aerodynamic testing has been employed for the estimation of wind pressures and forces on buildings. However, for residential homes and low-rise buildings, it has been always a challenge to predict full-scale pressures by traditional wind tunnel testing, as per the lack of large turbulence and Reynolds number effects, among other factors. The mismatch in flow physics makes it difficult to scale up wind-induced loads as the process can be highly nonlinear, which is the case when full-scale pressure coefficients do not meet those from small-scale aerodynamic testing. This chapter presents the challenges in the modeling and evaluation of aerodynamic forces on low-rise buildings, along with recent advances in both experimental and computational methods.",signatures:"Aly Mousaad Aly, Faiaz Khaled and Hamzeh Gol-Zaroudi",downloadPdfUrl:"/chapter/pdf-download/72520",previewPdfUrl:"/chapter/pdf-preview/72520",authors:[{id:"207384",title:null,name:"Aly-Mousaad",surname:"Aly",slug:"aly-mousaad-aly",fullName:"Aly-Mousaad Aly"}],corrections:null},{id:"71605",title:"Research on Aeroelasticity Phenomenon in Aeronautical Engineering",doi:"10.5772/intechopen.91748",slug:"research-on-aeroelasticity-phenomenon-in-aeronautical-engineering",totalDownloads:704,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Aeroelasticity phenomena arise when structural deformations induce changes on aerodynamic forces due to airplane structures that are not completely rigid. The additional aerodynamic forces cause an increase in the structural deformations, which leads to greater aerodynamic forces in a feedback process. These interactions may become smaller until reaching a condition of equilibrium or may diverge catastrophically if resonance occurs. Flutter is an instability aeroelasticity phenomenon which is the most difficult to predict. In this chapter, a numerical method and an experimental method were realized to predict aeroelastic response and characteristic parameters of a wing structure. The numerical method was firstly developed based on the interaction between computational fluid dynamic and computational structural dynamic methods using a coupling system, fluid–solid interaction (FSI), in the ANSYS software. Then, an experiment was set up in suitable conditions to study aeroelasticity characteristics with the goal of comparing the numerical results with the experimental results on the same wing structure at low speed. After that, a developed code based on immersed boundary method (IBM) was realized to predict aeroelasticity response and characteristic parameters of the wing structure. AGARD 445.6 wing model was chosen for this developed procedure at high speed. Obtained results were compared to other numerical and experimental results.",signatures:"Hoang Thi Kim Dung and Nguyen Phu Khanh",downloadPdfUrl:"/chapter/pdf-download/71605",previewPdfUrl:"/chapter/pdf-preview/71605",authors:[{id:"288958",title:"Associate Prof.",name:"Hoang",surname:"Thi Kim Dung",slug:"hoang-thi-kim-dung",fullName:"Hoang Thi Kim Dung"},{id:"290148",title:"Prof.",name:"Nguyen",surname:"Phu Khanh",slug:"nguyen-phu-khanh",fullName:"Nguyen Phu Khanh"}],corrections:null},{id:"69044",title:"Optimization of Lift-Curve Slope for Wing-Fuselage Combination",doi:"10.5772/intechopen.89056",slug:"optimization-of-lift-curve-slope-for-wing-fuselage-combination",totalDownloads:596,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The paper presents results obtained by the author for wing-body interference. The lift-curve slopes of the wing-body combinations are considered. A 2D potential model for cross-flow around the fuselage and a discrete vortex method (DVM) are used. Flat wings of various forms and the circular and elliptical cross sections of the fuselage are considered. It was found that the value of the lift-curve slopes of the wing-body combinations may exceed the same value for an isolated wing. An experimental and theoretical data obtained by other authors earlier confirm this result. Investigations to optimize the wing-body combination were carried within the framework of the proposed model. It was revealed that the maximums of the lift-curve slopes for the optimal midwing configuration with elliptical cross-section body had a sufficiently large relative width (more than 30% of the span wing). The advantage of the wing-fuselage combination with a circular cross section over an isolated wing for wing aspect ratio greater than 6 can reach 7.5% at the relative diameter of fuselage equal to approximately 0.2.",signatures:"Vladimir Frolov",downloadPdfUrl:"/chapter/pdf-download/69044",previewPdfUrl:"/chapter/pdf-preview/69044",authors:[{id:"215894",title:"Associate Prof.",name:"Vladimir",surname:"Frolov",slug:"vladimir-frolov",fullName:"Vladimir Frolov"}],corrections:null},{id:"67946",title:"Wave Drag Modification in the Presence of Discharges",doi:"10.5772/intechopen.86858",slug:"wave-drag-modification-in-the-presence-of-discharges",totalDownloads:466,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"A phenomenological model of wave drag modification following the thermal energy deposition in a hypersonic flow is presented. While most of the previous research was concentrated on finding optimal gas parameter values and the amount of energy, this work points at closer attention to the effect of the parameter distribution and the geometry of experimental arrangements. The approach discussed here is to fill the gap in the understanding of the complex mechanism of the flow transformation leading to the wave drag reduction. Analytical expressions used in the model identify a number of adjustment parameters that can be used to optimize thermal energy input and thus achieve fundamentally lower drag values than that of conventional approaches.",signatures:"Anna Markhotok",downloadPdfUrl:"/chapter/pdf-download/67946",previewPdfUrl:"/chapter/pdf-preview/67946",authors:[{id:"293548",title:"Prof.",name:"Anna",surname:"Markhotok",slug:"anna-markhotok",fullName:"Anna Markhotok"}],corrections:null},{id:"68702",title:"Boundary Layer Theory: New Analytical Approximations with Error and Lambert Functions for Flat Plate without/with Suction",doi:"10.5772/intechopen.88637",slug:"boundary-layer-theory-new-analytical-approximations-with-error-and-lambert-functions-for-flat-plate-",totalDownloads:448,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this work, we investigated the problem of the boundary layer suction on a flat plate with null incidence and without pressure gradient. There is an analytical resolution using the Bianchini approximate integral method. This approximation has been achieved by Lambert or Error functions for boundary layer profiles with uniform suction, even in the case without suction. Based on these new laws, we brought out analytical expressions of several boundary layer features. This gives a necessary data to suction effect modeling for boundary layer control. To recommend our theoretical results, we numerically studied the boundary layer suction on a porous flat plate equipped with trailing edge flap deflected to 40°. We showed that this flap moves the stagnation point on the upper surface, resulting to avoid the formation of the laminar bulb of separation. Good agreement was obtained between the new analytical laws, the numerical results (CFD Fluent), and the literature results.",signatures:"Chedhli Hafien, Adnen Bourehla and Mounir Bouzaiane",downloadPdfUrl:"/chapter/pdf-download/68702",previewPdfUrl:"/chapter/pdf-preview/68702",authors:[{id:"305636",title:"Dr.",name:"Chedhli",surname:"Hafien",slug:"chedhli-hafien",fullName:"Chedhli Hafien"}],corrections:null},{id:"66116",title:"High Entropy Alloys for Aerospace Applications",doi:"10.5772/intechopen.84982",slug:"high-entropy-alloys-for-aerospace-applications",totalDownloads:1650,totalCrossrefCites:9,totalDimensionsCites:14,hasAltmetrics:1,abstract:"In the aerospace industry, materials used as modern engine components must be able to withstand extreme operating temperatures, creep, fatigue crack growth and translational movements of parts at high speed. Therefore, the parts produced must be lightweight and have good elevated-temperature strength, fatigue, resistant to chemical degradation, wear and oxidation resistance. High entropy alloys (HEAs) characterize the cutting edge of high-performance materials. These alloys are materials with complex compositions of multiple elements and striking characteristics in contrast to conventional alloys; their high configuration entropy mixing is more stable at elevated temperatures. This attribute allows suitable alloying elements to increase the properties of the materials based on four core effects , which gives tremendous possibilities as potential structural materials in jet engine applications. Researchers fabricate most of these materials using formative manufacturing technologies; arc melting. However, the challenges of heating the elements together have the tendency to form hypoeutectic that separates itself from the rest of the elements and defects reported are introduced during the casting process. Nevertheless, Laser Engineering Net Shaping (LENS™) and Selective Laser Melting (SLM); a powder-based laser additive manufacturing process offers versatility, accuracy in geometry and fabrication of three-dimensional dense structures layer by layer avoiding production errors.",signatures:"Modupeola Dada, Patricia Popoola, Samson Adeosun and Ntombi Mathe",downloadPdfUrl:"/chapter/pdf-download/66116",previewPdfUrl:"/chapter/pdf-preview/66116",authors:[{id:"169258",title:"Dr.",name:"Patricia",surname:"Popoola",slug:"patricia-popoola",fullName:"Patricia Popoola"},{id:"285697",title:"M.Sc.",name:"Modupeola",surname:"Dada",slug:"modupeola-dada",fullName:"Modupeola Dada"},{id:"292368",title:"Dr.",name:"Samson",surname:"Adeosun",slug:"samson-adeosun",fullName:"Samson Adeosun"},{id:"292369",title:"Dr.",name:"Ntombi",surname:"Mathe",slug:"ntombi-mathe",fullName:"Ntombi Mathe"}],corrections:null},{id:"72028",title:"Flight Vehicle Performance",doi:"10.5772/intechopen.92105",slug:"flight-vehicle-performance",totalDownloads:701,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this chapter, the problem of flight vehicle performance is described. Performance parameters, such as lift-to-drag ratio, maximum and minimum level flight speed, speeds for the best rate of climb, steepest climb, maximum range and endurance, and most economical climb are described using graphical methods, such as drag polar, Zhukovsky curves with combination of analytical derivations. The approach of graphical description of flight vehicle performance allows to understand the physical basics of the aerodynamic properties of flight vehicles easier and to develop deeper connectivity between their interpretations. In addition, flight envelope and operational limits are discussed using both analytical and graphical methods for better understanding.",signatures:"Aram Baghiyan",downloadPdfUrl:"/chapter/pdf-download/72028",previewPdfUrl:"/chapter/pdf-preview/72028",authors:[{id:"315958",title:"Ph.D.",name:"Aram",surname:"Baghiyan",slug:"aram-baghiyan",fullName:"Aram Baghiyan"}],corrections:null},{id:"74839",title:"Critical Mach Numbers of Flow around Two-Dimensional and Axisymmetric Bodies",doi:"10.5772/intechopen.94981",slug:"critical-mach-numbers-of-flow-around-two-dimensional-and-axisymmetric-bodies",totalDownloads:389,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The paper presents the calculated results obtained by the author for critical Mach numbers of the flow around two-dimensional and axisymmetric bodies. Although the previously proposed method was applied by the author for two media, air and water, this chapter is devoted only to air. The main goal of the work is to show the high accuracy of the method. For this purpose, the work presents numerous comparisons with the data of other authors. This method showed acceptable accuracy in comparison with the Dorodnitsyn method of integral relations and other methods. In the method under consideration, the parameters of the compressible flow are calculated from the parameters of the flow of an incompressible fluid up to the Mach number of the incoming flow equal to the critical Mach number. This method does not depend on the means determination parameters of the incompressible flow. The calculation in software Flow Simulation was shown that the viscosity factor does not affect the value critical Mach number. It was found that with an increase in the relative thickness of the body, the value of the critical Mach number decreases. It was also found that the value of the critical Mach number for the two-dimensional case is always less than for the axisymmetric case for bodies with the same cross-section.",signatures:"Vladimir Frolov",downloadPdfUrl:"/chapter/pdf-download/74839",previewPdfUrl:"/chapter/pdf-preview/74839",authors:[{id:"215894",title:"Associate Prof.",name:"Vladimir",surname:"Frolov",slug:"vladimir-frolov",fullName:"Vladimir Frolov"}],corrections:null},{id:"66879",title:"Laser Based Additive Manufacturing Technology for Fabrication of Titanium Aluminide-Based Composites in Aerospace Component Applications",doi:"10.5772/intechopen.85538",slug:"laser-based-additive-manufacturing-technology-for-fabrication-of-titanium-aluminide-based-composites",totalDownloads:1035,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Titanium aluminides has the potential of replacing nickel-based superalloys in the aerospace industries because its density is almost half that of nickel-based alloys. Nevertheless, the room temperature properties (ductility) have made the wider application of this class of intermetallic alloy far from being realized. This has led to various research been carried out in adjusting the production processing and/or material through alloying, heat treatment, ingot metallurgy, powder metallurgy and most recently additive manufacturing processing. One of the additive manufacturing processing of titanium aluminide is laser engineered net shaping (LENS). It is used to produce components from powders by melting and forming on a substrate based on a computer-aided design (CAD) to shape the components. This contribution will focus on the laser processing of titanium aluminides components for aerospace applications. Also, the challenges confronting this processing techniques as well as suggested finding to solve the problems would be outlined. The objective of this work is to present an insight into how titanium aluminides components have been developed by researchers with emphasis on aerospace applications.",signatures:"Sadiq Abiola Raji, Abimbola Patricia Idowu Popoola, Sisa Leslie Pityana, Olawale Muhmmed Popoola, Fatai Olufemi Aramide, Monnamme Tlotleng and Nana Kwamina Kum Arthur",downloadPdfUrl:"/chapter/pdf-download/66879",previewPdfUrl:"/chapter/pdf-preview/66879",authors:[{id:"169258",title:"Dr.",name:"Patricia",surname:"Popoola",slug:"patricia-popoola",fullName:"Patricia Popoola"},{id:"176896",title:"Dr.",name:"Sisa",surname:"Pityana",slug:"sisa-pityana",fullName:"Sisa Pityana"},{id:"177716",title:"Dr.",name:"Olawale",surname:"Popoola",slug:"olawale-popoola",fullName:"Olawale Popoola"},{id:"283922",title:"Mr.",name:"Sadiq",surname:"Raji",slug:"sadiq-raji",fullName:"Sadiq Raji"},{id:"292715",title:"Dr.",name:"Fatai",surname:"Aramide",slug:"fatai-aramide",fullName:"Fatai Aramide"}],corrections:[{id:"69565",title:"Erratum - Laser Based Additive Manufacturing Technology for Fabrication of Titanium Aluminide-Based Composites in Aerospace Component Applications",doi:null,slug:"erratum-laser-based-additive-manufacturing-technology-for-fabrication-of-titanium-aluminide-based-co",totalDownloads:null,totalCrossrefCites:null,correctionPdfUrl:null}]},{id:"69643",title:"Study of the Wind Speed Forecasting Applying Computational Intelligence",doi:"10.5772/intechopen.89758",slug:"study-of-the-wind-speed-forecasting-applying-computational-intelligence",totalDownloads:631,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:1,abstract:"The conventional sources of energy such as oil, natural gas, coal, or nuclear are finite and generate environmental pollution. Alternatively, renewable energy source like wind is clean and abundantly available in nature. Wind power has a huge potential of becoming a major source of renewable energy for this modern world. It is a clean, emission-free power generation technology. Wind energy has been experiencing very rapid growth in Brazil and in Uruguay; therefore, it’s a promising industry in these countries. Thus, this rapid expansion can bring several regional benefits and contribute to sustainable development, especially in places with low economic development. Therefore, the scope of this chapter is to estimate short-term wind speed forecasting applying computational intelligence, by recurrent neural networks (RNN), using anemometers data collected by an anemometric tower at a height of 100.0 m in Brazil (tropical region) and 101.8 m in Uruguay (subtropical region), both Latin American countries. The results of this study are compared with wind speed prediction results from the literature. In one of the cases investigated, this study proved to be more appropriate when analyzing evaluation metrics (error and regression) of the prediction results obtained by the proposed model.",signatures:"Pedro Junior Zucatelli, Erick Giovani Sperandio Nascimento, Alex Álisson Bandeira Santos, Alejandro Mauricio Gutiérrez Arce and Davidson Martins Moreira",downloadPdfUrl:"/chapter/pdf-download/69643",previewPdfUrl:"/chapter/pdf-preview/69643",authors:[{id:"172442",title:"Dr.",name:"Davidson",surname:"Moreira",slug:"davidson-moreira",fullName:"Davidson Moreira"},{id:"267484",title:"Dr.",name:"Alex",surname:"Santos",slug:"alex-santos",fullName:"Alex Santos"},{id:"307526",title:"Ph.D. Student",name:"Pedro",surname:"Zucatelli",slug:"pedro-zucatelli",fullName:"Pedro Zucatelli"},{id:"310576",title:"Prof.",name:"Erick Giovani",surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio 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\r\n\tNatural resource management deals with the management and utilization of both renewable and nonrenewable resources such as forests, fisheries, water, minerals, air, and animals for present and future use. Recently, natural resource management is facing major challenges in terms of ecosystem sustainability as a result of many competing uses of the resources. There is a growing awareness of the roles of natural resources as the future of natural resource management is under severe threats which may lead to the malfunction of mankind. Therefore, sustainable management of natural resources is extremely important to ensure the natural balance of the ecosystem is maintained. In addition, effective management of these resources would not only avoid over-consumption of the natural resources but also prevent further destruction of the environment. The book will provide a wealth of information by presenting and analyzing current knowledge on the management, planning, policy, and economics of natural resources such as natural and man-made forests, crop protection, water conservation, sustainable agriculture, wildlife and habitat management. Issues and challenges of climate change towards achieving sustainable management of natural resources will also be highlighted.
",isbn:"978-1-83768-454-0",printIsbn:"978-1-83768-453-3",pdfIsbn:"978-1-83768-455-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"1881a08bbd8f5dc1102c5cb7c635bc35",bookSignature:"Dr. Mohd Nazip Suratman and Dr. Engku Azlin Rahayu Engku Ariff",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/12223.jpg",keywords:"Protected Area, National Parks, Biodiversity Conservation, Climate Change, Global Warming, Stand Dynamics, Tropical Rainforests, Community-Based Ecotourism, Ecological Conservation, Agroforestry, Soil Conservation, Water Conservation",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"June 21st 2022",dateEndSecondStepPublish:"July 19th 2022",dateEndThirdStepPublish:"September 17th 2022",dateEndFourthStepPublish:"December 6th 2022",dateEndFifthStepPublish:"February 4th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"22 days",secondStepPassed:!1,areRegistrationsClosed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"A professor of forestry, an editor, author, and co-author of over a dozen books and 200 research publications. 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Her current research focus is in the area of forest modeling, specifically looking at how predictive models can be helpful in assessing the impacts of climate change on the carbon sequestration potential of vegetations.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"144417",title:"Dr.",name:"Mohd Nazip",middleName:null,surname:"Suratman",slug:"mohd-nazip-suratman",fullName:"Mohd Nazip Suratman",profilePictureURL:"https://mts.intechopen.com/storage/users/144417/images/system/144417.jpg",biography:"Mohd Nazip Suratman is a Professor of Forestry at the Faculty of Applied Sciences, and a Principal Fellow at the Institute for Biodiversity and Sustainable Development, Universiti Teknologi MARA (UiTM), Malaysia, He earned a B. Sc in Forestry from Universiti Putra Malaysia (UPM) and an M. S from the University of Nebraska-Lincoln (UNL), USA. He was then honored with a prestigious fellowship from the Canadian Commonwealth to pursue a Ph.D. degree at the University of British Columbia (UBC), Canada, where he worked on the application of remote sensing for forest resources management. He has been involved in numerous collaborative international research projects that led to publications in reputable journals. Altogether, he has published a total of 14 books and more than 200 research publications. His research interests cover several aspects of forestry, mainly forest modeling, forest ecology, and biodiversity. He received the UiTM’s Best Researcher and Top Talent Awards in 2015 and 2021, respectively. He served as the Deputy Vice-Chancellor (Research and Innovation) from 2018 to 2021.",institutionString:"Universiti Teknologi MARA",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"6",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Universiti Teknologi MARA",institutionURL:null,country:{name:"Malaysia"}}}],coeditorOne:{id:"479437",title:"Dr.",name:"Engku Azlin Rahayu",middleName:null,surname:"Engku Ariff",slug:"engku-azlin-rahayu-engku-ariff",fullName:"Engku Azlin Rahayu Engku Ariff",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003SceBMQAZ/Profile_Picture_2022-06-07T14:57:49.PNG",biography:"Engku Azlin Rahayu Engku Ariff is currently a senior lecturer in the Faculty of Applied Sciences, University Teknologi MARA (UiTM) Pahang Branch, and an Associate Fellow of the Institute for Biodiversity and Sustainable Development (IBSD), UiTM, Malaysia. 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Kallos",coverURL:"https://cdn.intechopen.com/books/images_new/1319.jpg",editedByType:"Edited by",editors:[{id:"62719",title:"Prof.",name:"Michael S.",surname:"Kallos",slug:"michael-s.-kallos",fullName:"Michael S. Kallos"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},onlineFirst:{chapter:{type:"chapter",id:"77016",title:"Coastal Sea Level Trends from a Joint Use of Satellite Radar Altimetry, GPS and Tide Gauges: Case Study of the Northern Adriatic Sea",doi:"10.5772/intechopen.98243",slug:"coastal-sea-level-trends-from-a-joint-use-of-satellite-radar-altimetry-gps-and-tide-gauges-case-stud",body:'Sea level rise is primarily an issue at the boundary line with land. It represents a potential threat to infrastructures and population living in low-elevation coastal areas [1]. The land disappears not only because the rising sea changes the coastline, but also because at a place there could be the land moving up or down, therefore contrasting or accelerating sea level rise [2]. Sea level can change significantly from one coastal location to another, as a result of a number of ocean, atmospheric and land processes that occur at various spatial and temporal scales [3].
In a global change scenario, as speculated in Li et al. [4], a slow rise of the sea level of few cm associated to climate change would make a difference to the coastline. It would not retreat from land, making it permanent. The flooding line of transient events (e.g., storm surges, tsunamis, etc.) would also uplift, increasing the risk of more frequent land inundation and more inland propagation [5]. An example is the City of Venice that has long been vulnerable to short duration flooding during winter [6]. The problem was so important that a system of 78 storm gates, known as MOSE [7] has been constructed to protect the city when high water is expected in Venice [8]. Long-term rising sea levels will represent additional challenges in the future [8].
Understanding the climate-related contribution to the sea level change and how much it will likely affect coastal regions is a major challenge, as it also requires local-scale measurements of the land effects. In this chapter, we review the sea level trend measuring system involving the integration of recent satellite-based observations from radar altimeters and Global Positioning System (GPS) receivers with historical data from tide gauge stations. The latest advances in open ocean and coastal altimetry to measure sea level changes close to the coasts over the satellite radar altimetry era are also summarized. A more robust inverse method to estimate sea level trends is also presented. It has been tested in the Northern Adriatic Sea, where GPS data are available to conduct a realistic assessment of uncertainties.
Since Roman period, sea level has been measured nearby land just sticking a graduated pole within protected piscinae [9]. Since the 19th Century, tide gauges have been used in some coastal places around the world to measure the local change in sea level relative to the adjacent land [10, 11]. The baseline for measuring sea level over time is typically a mean sea level computed by averaging all the measurements over a period of years at each location. This relative sea level that will rise if ocean levels rise and/or land levels fall is the net change in the sea level and is the quantity of interest to the local coastal community in the real-time monitoring.
However, understanding the future coastal sea level changes and their relative significance requires to remove the effect of waves, tides, and other short-term fluctuations. But tide gauges alone cannot determine whether the sea level is rising, the land is sinking, or both. Sea level can rise or retreat in the long-term in response to the natural processes that alter the volume of water, including the climate-related contribution. The land level changing over time (the so-called vertical land motion, VLM or subsidence/uplift) can rise or fall due to natural processes (e.g., tectonic shifts; sediment loading, glacial isostatic adjustment, etc.) but also as a consequence of man-made factors (e.g., ground water extraction; oil and gas pumping, etc.).
There are various techniques for measuring VLM, e.g., geotechnical investigations using spirit levels and borehole extensometers [12]; geodetic surveying with Global Positioning System (GPS) satellite technology [13]; satellite remote sensing observations that use a technique called interferometric synthetic aperture radar (InSAR) [14]. The advantage of satellites is that they ensure almost global coverage in a repeatable manner and consistency of the measuring system over long time periods that is an important requirement for the detection of slow changes over time.
The quantification of VLM before the modern satellite era is difficult due to the poor coverage of geotechnical investigations. The advent of GPS receivers and their co-location with tide gauges made possible to continuously measure land elevation changes with simultaneous sea level reading at the same location [15]. GPS sensors return vertical and horizontal positions. The vertical position is a measure of the elevation of the land surface relative to the center of Earth, also referred as absolute. It is generally two to three times less precise than the horizontal components. The present picture is that, while there are many tide gauges around the world, not all have permanent GPS receivers co-located or near them [16].
The InSAR tool uses repeating multiple satellite radar imagery to create a time profile of land elevation change. The advantage respect to the GPS technology is the much higher density of VLM measuring points in the imaged area. The technique to provide statistically significant results requires a sufficient number of images and reduced scattering over time for the area of interest. The availability of images from the first satellites (e.g., ERS and Envisat) can be very irregular both in time and space [17]. Only the recent Sentinel-1 constellation provides global coverage and more frequent revisiting. Other satellite missions (e.g., COSMO-SkyMed, RADARSAT, etc.) only provide imagery on demand.
Sea level can be also measured with satellites using radar altimeters. These instruments send microwave pulses down along the satellite’s ground track and measure their echoes, revisiting the same place every 10 days or more depending on the mission. The time their echoes take to bounce back allows the system to measure the satellite’s altitude above the sea surface (the so-called range). It can be then corrected for instrumental and environmental effects. Knowing the satellite orbit with respect to Earth’s center of mass, the absolute, not relative, sea level can be thus calculated, and its change tracked over time.
Routine sea level observations began in 1992 with the TOPEX/Poseidon spacecraft on a 10-day repeat cycle, and this has subsequently been followed up by the Jason 1/2/3 series and the recent Sentinel-6 mission, providing a near-global fully consistent along track data set of sea level to understand how sea levels have changed over the past nearly three decades. Over the years, various satellite missions with different orbital configurations and other scientific objectives were launched, e.g., ERS-1/2, Envisat, Sentinel-3, SARAL, CryoSat-2 and HY-2A/B.
But single satellites have limitations. The sea level is tracked along paths whose distance is relatively large. A satellite alone could not fly in the region of interest, as it is for example the case of Venice for the T/P-Jason-Sentinel-6 family. Moreover, it has been difficult to retrieve data near coast where both the presence of land and more complex ocean surface scattering make the standard processing problematic [18].
The satellite radar altimetry system has been initially conceived for usage in open ocean. The processing of radar echoes and the development of corrections is now at mature stage in this domain, with the various datasets routinely used for global sea level studies. However, data were normally flagged as bad and therefore rejected in the coastal zone. But the situation rapidly changed in the last ten years for two reasons: (1) the prospect of recovering a valuable long-term sea level data around the global coastline; (2) the improved suitability of the new and future altimeters (like those on CryoSat-2, AltiKa, Sentinel-3, Sentinel-6, Crystal). Therefore, a new domain “coastal altimetry”, i.e. the extension of altimetry into the oceanic coastal zone has been emerging, with a community around it developing a set of coastal altimetry techniques in order to get more and better sea level data closer to the coast.
The analyses of radar echoes revealed that pulse-limited missions, if reprocessed with dedicated models, could provide reliable range measurements to few km from the coastline. An example is the Adaptive Leading Edge Subwaveform (ALES) retracking algorithm, that has been validated and applied successfully to sea level research, demonstrating the ability to increase the quality and the quantity of sea level retrievals in coastal areas [19].
In addition, it was noted that geophysical corrections that must be applied to altimeter range data have a significant impact in coastal altimetry and therefore their constant improvement is crucial. There have been noticeable developments to improve the tropospheric delay [20], the tidal sea level where global models have still large errors [21] and the mean sea surface models, suitable for the observation of the coastal sea level [22]. There have been also improvements in procedures to avoid aliasing of major tidal signals and short-period ocean response to meteorological forcing aliases onto low frequency signals [23].
The wet tropospheric correction is the major source of uncertainty in altimetry budget error, due to its large spatial and temporal variability: this is reason why a multi-channel passive microwave radiometer is on the same platform as the altimeter. Unfortunately, this estimate gets quickly corrupted as soon as land enters the radiometer footprint, i.e. 20–50 Km from the coast. Alternative corrections have been devised and appear to be successful at least in some particular conditions [24]. A very promising approach was the one attempting to estimate the wet tropospheric path delay from GPS measurements known as GPD (GNSS-derived Path Delay), and its latest version called GPD+ (Plus) [25].
The classical data editing used in open ocean was also considered excessively restrictive and revisited with novel editing/re-interpolation approaches (e.g., [26]). The new data from the various reprocessing efforts are now bringing altimetry around the global coastline, with a higher spatial resolution and precision that was previously not available in coastal and shelf sea areas, while constant improvement [18] and validation [27] are still ongoing. The new coastal altimetry datasets open a new opportunity to study sea level change from open ocean to coast and differences in trend and variability at various distances from the coast, also nearby tide gauges [28].
Several radar altimetry missions have been in operation since the first launch in 1973 (see Figure 1). The TOPEX/Poseidon and Jason series (with the addition of the just launched Sentinel-6) is the reference mission for long-term sea level studies, as it is ensured the continuity in the same orbit [29]. However, a single altimeter only provides measurement along a track from open ocean closer to coast. There is always a trade-off between temporal sampling and ground-track spatial coverage. A single altimeter always leaves gaps along the coast between neighboring tracks: tenths to hundred km are not covered, so that the vast majority of the worldwide coast is not sampled. The coverage can be augmented with additional existing altimeters.
Main characteristics of satellite altimetry missions operating until now and planned for the future.
Data from the various altimeter missions were used to create several datasets. Examples include RADS [30], X-TRACK [28], etc. that also provide sea level estimates. Since 1992, at least two altimeter satellites have been operating simultaneously, and during some periods, even more than two. Such data can be combined in a single product to provide a consistent long-term sea level data set, globally with sufficient spatial coverage over almost three decades. However, altimeter missions need to be accurately homogenized and cross-calibrated to reduce biases and uncertainties [31].
A satellite-based sea level data set to analyze long-term trends that uses the available historic observations from the various radar altimeters is key requirement for the climate community [32]. A recent reprocessing within the European Space Agency (ESA) Sea Level Climate Change Initiative (SLCCI) has produced a gridded altimetry product with a spatial resolution of 0.25° (which is around 25 km resolution) from 1993 to 2015 [33, 34], thus permitting a more detailed view of sea-level change around the world coastlines.
The sea level Environment Climate Variable (ECV) (at global and regional scales) is now operationally produced by the Copernicus Climate Change Service (C3S) [35] by applying the altimetry processing standards developed in the SLCCI initiative. The C3S product ensures a stable number of two altimeters since the beginning and the reference field used to compute sea level anomalies (SLA) is a homogeneous mean sea surface for all missions. The C3S record is a regional product, gridded at 0.125° in the Mediterranean Sea, starting in 1993 and offering ongoing coverage [36]. Both the SLCCI and the C3S datasets are state-of-the-art products designed to be a reference for climate-related sea level studies.
In the case-study illustrated in the chapter, the SLCCI and C3S datasets are used to assess their maturity as state-of-the-art altimetry datasets in climatological studies. The multi-mission gridded products have not still tuned for last 10 km from the coast, where the amount of valid data might decrease. The ESA CCI + Sea Level project, started in 2017, is extending the processing to the coastal zone, and an experimental coastal sea level product is going to be released to the public, in six selected regions: Northern Europe, Mediterranean Sea, Western Africa, North Indian Ocean, Southeast Asia and Australia [37]. This product is along-track and combines the enhanced spatial resolution provided by high-rate data (20-Hz), the post-processing strategy of X-TRACK and the advantage of the ALES retracker [38]. The product relies on the GPD+ wet tropospheric correction [39] and the FES2014 tidal corrections [40]. The X-TRACK/ALES SLCCI 20 Hz along-track dataset will be indicated with SLCCI-AT hereinafter.
The trend is an indicator describing how sea level has changed over long time. It provides a simple predictive scenario if what observed in the past might be representative in the near future. The classical approach is to calculate a straight line through sea level data using a linear regression. The most used method for fitting data is least squares. However, other methods based on more complex models exist to estimate trends from sea level time series [41]. The trend estimation is sensitive to the length of the record and start/end periods. There might be variability at different inter-annual to decadal timescales occurring within the data. Moreover, in addition to the linear trend, there might be autocorrelation of the noise in the data [42].
A single tide gauge cannot explain to what extent the observed trend is related to ocean and/or land changes, without any nearby GPS. With the advent of satellite radar altimetry and the possibility to use altimeter passages nearby tide gauges a new method was proposed by Cazenave et al. [43]. It assumes that both the tide gauge and altimetry system measure the same ocean signal and the difference is a measure of VLM at the gauge: hereinafter we refer to this method as the “direct” or “classical” method. Another assumption is that there are no instrumental errors introducing significant drifts. This direct method provides VLM at the selected tide gauge station only.
Different implementations of the basic idea were successively proposed involving more tide gauges, more rigorous error analysis with mitigation of the uncertainties introduced by the assumptions and taking advantage of longer and improved altimeter-derived time series available at that time (e.g., [44, 45, 46, 47] and others).
An advanced method to estimate VLM that includes supplementary constraints from adjacent tide gauges has been proposed by Kuo et al. [48]. Its solution is based on the inversion of a linear system, formed mixing differences of altimetry- and tide gauge-derived trends, and differences of trends from neighboring tide gauges only, introduced in the linear system through Lagrange multipliers. As the solution of such a system requires its inversion, the method is referred to as Linear Inverse Problem with Constraints (LIPWC), or shortly “inverse” method. The new method optimally combines short-term altimetry records with long-term tide gauge observations. It assumes that absolute sea level change at tide gauges over a long time span is the same. The advantage of the method is that long (>40 years) tide gauge records contribute to reduce the error in the final VLM solution, and random and systematic errors in one or more time series trend are shared among all the other, cutting down the impact on the originating one. The disadvantage is that the method cannot be applied if the absolute sea level change is different from place to place. Nevertheless, this method can be useful in closed and semi-enclosed basins and could be adapted to work also in case a GPS at the coast is used instead of a tide gauge.
Kuo et al. [48] applied the inverse method within a semi-enclosed sea (Baltic Sea region of Fennoscandia). The results showed a significant reduction of uncertainties compared with those from conventional approaches, which are limited to the overlapping periods between altimetry and tide gauges. An extension of the method has been applied to Great Lakes and in open ocean regions, such as Alaskan coast [49]. It has been also extended along the coasts of southern Europe [50] with constraints between pairs of tide gauges based on correlation and overlapping periods. The same method has been extended to open ocean in New Zealand straddles, the Tasman Sea and Pacific Ocean [51]. All studies confirmed the superiority of the inverse method to the classical direct approach.
A new variant of the inverse method considers to difference sea level trends between pairs of tide gauge records and pairs of altimetry records [52]. Another study proposed different mathematical and statistical models, which enable simultaneous estimation of absolute and relative sea level trends and VLM at a tide gauge station merging altimetry and tide gauge records without the aid of geological information or GPS measurements [53].
The linear inverse model proposed by Kuo et al. [48, 49], and then by Wöppelmann and Marcos [50], assumes that the absolute sea level change rates are similar at all the tide gauge (TG) sites. This assumption is particularly important for the successful inversion. The explanation will be provided in this section.
The difference between the absolute sea level rise (ASLR) and the relative sea level rise (RSLR) rates, i.e. the velocities at which the sea level vertical motion is observed by satellite altimeters and TGs, denoted respectively with
Eq. (1) is sufficient to obtain good estimates of the VLM rates at each TG, provided that all the variables in the equation refer to the same period and to coherent geophysical processes and have negligible inherent drifts and errors. Eq. (1) can be expressed in vector–matrix notation:
where
At this stage, the constraints still contain explicitly the ASLR at sites
leaving out any reference to the ASLRs. Containing only the differences of the RSLR, Eq. (4) can be extended to the whole period of overlapping observations of the two TGs, which usually are longer and affected by lower errors. To distinguish the RSLR observed at the TG in the altimetry era from that observed in the common, longer period of observations of TGs
where we used the Greek letter
The two linear systems for the Eqs. (2) and (5) are written in vector–matrix form as:
The matrix
Not always assumption
A unique linear system incorporating the constraints (7) in the system (6) is formed recurring to the Lagrange multipliers technique: the inverse linear problem with constraints [56] (LIPWC). It stems from the minimization of the expression
which is a linear system of the form
The standard errors of the
where N and L are respectively the number of parameters
A possible attenuation of the condition that
In other words, we overcome the limitation of equal ASLR at all TGs by removing from both, the TG time series and the altimetry time series associated with the TG, a linear trend equal to that measured by the altimeter. Such change of variables (COV) does not alter the statistical properties of the TG and altimetry time series but eliminates any difference in relative sea level changes due to different absolute sea level changes. For it to work two assumptions are necessary:
All the time series have a linear trend in every period in which they are considered.
The absolute sea level rates observed by satellite altimetry in its era can be extended backward in time to cover the timespan of the associated TG relative sea level time series.
While the first assumption can be easily verified by visual inspection or with more precise statistical methods, as the goodness-of-fit R2 test [59], the second assumption, needed to permit the third change of variable in Eq. (12), can be more difficult to assess. In general, the linearity of a TG’s RSLR trend can partly corroborate the validity of the second assumption, as the probability that two different, non-linear trends of the local ASLR and VLM perfectly combine by chance, to give an overall linear trend, is obviously low.
The method of derivation of VLM described in the previous section will now be applied to a real case. To this end we have chosen the Adriatic Sea for its complexity and for the interest in this area. Indeed, several historical heritage cities and commercial/productive sites lie in the coastal area of the region, not to mention the number of people leaving along the Adriatic Sea coast, which at the end of last century was already higher than 3.5 million [60]. First, we will derive the VLM values in the Adriatic Sea using the classical LIPWC technique. After that, the LIPWC method will be applied to the same data using the change of variable presented in Eq. (12), and the results of the two strategies compared.
The TG in the Adriatic Sea for which long time series of monthly sea level are available are few. Table 1 reports their name, position, and data availability. The records of the TGs have been formed in some case from different sources, principally the Permanent Service for Mean Sea Level (PSMSL) [61], the Venice Tide Forecast and Early Warning Center (Centro Previsioni e Segnalazioni Maree, CPSM) of Venice Municipality, the Istituto Superiore per la Protezione e la Ricerca Ambientale (Italian Institute for Environmental Protection and Research (ISPRA)) and the Institute of Marine Sciences of the National Research Council of Italy (CNR-ISMAR).
Location | TG Name | Lat (° N) | Long (° E) | Data (%) | Time Span (Years) | Record Length (Years) |
---|---|---|---|---|---|---|
Venice | VENEZIA * | 45°25′51.45″ | 12°20′13.39″ | 97 | 1872–2018 | 147 |
Venice off-shore | VEPTF | 45°18′51.29″ | 12°30′29.69″ | 100 | 1974–2018 | 45 |
Trieste | TRIESTE * | 45°38′50.00″ | 13°45′33.90″ | 89 | 1875–2018 | 145 |
Rovinj | ROVINJ | 45°05′01.18″ | 13°37′44.86″ | 99 | 1955–2018 | 64 |
Split | SPLIT * | 43°30′23.88″ | 16°26′18.44″ | 100 | 1952–2018 | 67 |
Dubrovnik | DUBROVNIK | 42°39′28.40″ | 18°03′38.84″ | 99 | 1956–2018 | 63 |
Principal characteristics of tide gauges considered in Adriatic Sea. Some of the tide gauge records have been formed by collating partial records from different sources. Such situation is marked by an asterisk after the tide gauge name.
Figure 2 shows the position of the TGs on the map of the Adriatic Sea region. Some of the TG records have been formed by collating partial records from different sources. Such TGs are marked by an asterisk. The individual positions of the TGs with respect to the twelve closest nodes of the.
Positions of six tide gauges in Adriatic Sea. Color bar indicates length of available time series of sea level at tide gauges; shortest time series is about 50 years.
C3S altimetry grid are shown in Figure 3: note that some of the grid nodes are represented over land. This is an artifact of the gridding procedure that partially extrapolates over land the SLA field [36].
Geographical location of the six tide gauges and position of the twelve nearest grid points of C3S altimetry SLA. Tide gauges are marked by black squares. Altimetry grid nodes are red dots. Blue triangle marks the grid node with best correlation match. Also shown (green circle) the lowest root mean square difference of the TG and altimetry monthly time series.
VEPTF is the shortest record in the set, as it started sea level recordings only in 1974. Nonetheless, its length is almost double that of the altimetry era, and abundantly double the period of the lunar nodal tide. To treat evenly all the TG records, we consider in situ sea level data from 1974 up to 2018 for all the TGs.
Plots of the in situ, as well as of the altimetry sea level anomaly monthly means observed at the six locations in the Adriatic Sea are reported in Figure 4: the seasonal and tidal signals have been removed from both the in situ and the altimetry datasets. The altimetry grid node associated to the TG time series has been chosen as the one whose time series has the higher correlation coefficient with the sea level time series of the TG, among the twelve grid nodes closest to the latter. All the sea level trend errors have been calculated considering serial correlation and are given with a 95% confidence interval.
Plots of the sea level anomalies registered by tide gauges (1974–2018, in blue) and observed by the satellite altimetry (1993–2018, C3S dataset, in orange).
The altimetry dataset used to represent sea level anomaly in Figure 4 is C3S. The in situ and the remotely sensed sea level records are in good agreement, as the lowest Pearson’s correlation coefficient between altimetry and TG sea level time series is 0.82 at the Rovinj station, while all the others reach values larger than 0.91.
However, in some period a marked difference between in situ and altimetry SLA are seen, as for example in VENEZIA during 2012–2019 (TG sea level higher than altimetry), which is also confirmed by the nearby TG of VEPTF and seems to interest in a lesser extent also TRIESTE and DUBROVNIK, and for ROVINJ in 2014–2015 (TG sea level lower than altimetry), and also SPLIT in 2002–2005 (TG higher than altimetry). On the other hand, common patterns are identified in all the records throughout the observation period.
Global positioning system (GPS) observations are synergistically included in our analysis. Several sources of GPS data, at different elaboration levels, are currently available online for geocentric surface velocity data and trends from continuous GPS (CGPS) stations at selected locations, in particular near TGs: Système d’Observation du Niveau des Eaux Littorales (SONEL)/Université La Rochelle (ULR) [62], Nevada Geodetic Laboratory (NGL, University of Nevada) [63]. Other sources of information are available from local and national public agencies: in this study we used for the VENEZIA TG station also data acquired and processed by ISPRA at the PSAL tide gauge [64], which provides a relevant part of the VENEZIA sea level record. Table 2 reports the vertical velocities registered at five of the six tide gauges considered in this study, with their time span and the values provided by one or more centers for the same TG by one or more GPS stations nearby.
GPS station | NGL (mm y−1) Span (yr) | SONEL (mm y−1) Span (yr) | ISPRA (mm y−1) Span (yr) | Distance from TG (Km) | Pooled Mean (mm y−1) |
---|---|---|---|---|---|
PSAL VENEZIA | −1.70 ± 0.80 2014–2020 | — | −1.46 ± 0.09 2010–2015 | 0.01 | −1.59 ± 0.65 2014–2020 |
TRIE TRIESTE | −0.52 ± 0.45 2003–2020 | 0.20 ± 0.26 2003–2013 | — | 6.97 | −0.25 ± 0.52 2003–2020 |
PORE ROVINJ | −1.51 ± 1.03 2011–2021 | — | — | 16.62 | −1.51 ± 1.03 2011–2021 |
SPLT SPLIT | 0.45 ± 0.68 2004–2012 | −0.25 ± 0.34 2004–2012 | — | < 4.00 | 0.10 ± 0.64 2004–2012 |
DUBR+DUB2 DUBROVNIK | −1.83 ± 0.70 2000–2020 | — | — | 4.15 | −1.83 ± 0.70 2000–2020 |
Geocentric surface vertical velocities at three locations in the Adriatic Sea from GPS stations.
PSAL is almost co-located with the VENEZIA PUNTA DELLA SALUTE TG. For SPLIT, data from the CGPS station of SPLT were acquired. It is worth mentioning that SPLT is, with PSAL in VENEZIA, among the few CGPS co-located with TGs in the Adriatic Sea. The TRIE CGPS station is the nearest to the TRIESTE TG, but 6.9 km far from it, over a hill north-west of Trieste: for this reason, TRIE CGPS station cannot be considered co-located with the TRIESTE TG. Neither can the PORE CGPS station for ROVNIJ be considered as such, and the DUBR and DUB2 CGPS stations in DUBROVNIK: PORE is located 16 km north of Rovinj along the coast, while DUBR and DUB2 are located 4 km away and 400 m in height.
With the data described so far, the VLM can be derived with the classical method, i.e. subtracting the TG RSLR from the ASLR observed by altimetry at the associated grid point. This approach, described in [43], allows to estimate the VLM separately at each location for which RSL and ASL records are available. The error associated to these estimates is drastically reduced when the linear trend of VLM is calculated by differencing the time series of the ASL and RSL, instead of combining the two errors of ASLR and RSLR as they were two independent measurements. From here on, all the errors on the sea level change rate are calculated according to this convention. The results of such approach are shown in Table 3: in column 1 appear the TG locations, in column 2 the ASLR derived by altimetry, in column 3 the RSLR derived by the TG, and in column 4 the VLM (
Location | (mm y−1) | (mm y−1) | (mm y−1) |
---|---|---|---|
VENEZIA | 3.36 ± 1.45 | 5.15 ± 1.73 | −1.79 ± 0.65 |
VEPTF | 3.38 ± 1.46 | 5.50 ± 1.73 | −2.12 ± 0.67 |
TRIESTE | 3.75 ± 1.58 | 3.56 ± 1.66 | 0.18 ± 0.60 |
ROVINJ | 3.33 ± 1.58 | 1.03 ± 1.85 | 2.30 ± 1.06 |
SPLIT | 3.60 ± 1.36 | 2.92 ± 1.65 | 0.68 ± 0.63 |
DUBROVNIK | 3.34 ± 1.22 | 3.79 ± 1.48 | −0.45 ± 0.55 |
Results of calculations using C3S altimetry dataset (1993–2018). Column 1 reports the TG location; columns 2 and 3 the absolute and relative sea level rates in the altimetry era; column 4 the VLM calculated with the classical approach (ALT-TG). All data are in mm y−1.
First of all we note that the error of the VLM estimates in the fourth column, obtained as standard error of the trend of the differenced time series (ASL-RSL) are much lower than that provided by the error propagation formula for the difference of the trend estimates of two statistically-independent time series, as in this case the error propagation formula would provide
A second aspect worth to note is the independence of each VLM determination from all the others. That means if one of the VLM estimates is affected by large errors or relies on data of bad quality (RSL and/or ASL), it does not influence the evaluation of the others.
The third observation about the numbers reported in Table 3 is that while the ASLR is almost constant at all sites of the Adriatic Sea considered in this study, the RSLR observed at the TGs are much more varied, determining VLM estimates going from −2.12 to +2.30 mm y−1. From one side, this means that the vertical velocity field applicable to the Adriatic area is not constant, potentially revealing that different processes could be at the base of the observed crustal motions. From the other side, such numbers reveal also that the VLM is an essential parameter in sea level studies conducted mainly from tide gauge data. Thus, every methodology able to estimate the VLM at the TG is of extreme interest to correct the RSL observed at the TGs themselves, in particular where no geodetic measurements are available to estimate the VLM.
To conclude this section about the classical approach to VLM estimate from sea level data, we report a comparison of the two gridded altimetry datasets: C3S and SLCCI. To provide a fair comparison, both datasets have been limited to the same common period of temporal coverage: 1993–2015. The results of the classical approach to VLM estimate are given in Table 4.
Location | (mm y−1) | (mm y−1) | (mm y−1) | C3S (mm y−1) | SLCCI (mm y−1) |
---|---|---|---|---|---|
VENEZIA | 4.16 ± 1.71 | 4.47 ± 2.07 | 6.08 ± 2.08 | −1.93 ± 0.79 | −1.61 ± 0.91 |
VEPTF | 4.17 ± 1.73 | 4.47 ± 2.07 | 6.44 ± 2.07 | −2.27 ± 0.81 | −1.97 ± 0.93 |
TRIESTE | 4.51 ± 1.84 | 3.42 ± 1.78 | 4.49 ± 1.98 | 0.02 ± 0.71 | −1.07 ± 0.74 |
ROVINJ | 4.09 ± 1.85 | 4.37 ± 1.86 | 1.91 ± 2.04 | 2.18 ± 1.17 | 2.46 ± 1.04 |
SPLIT | 4.44 ± 1.57 | 4.15 ± 1.48 | 4.15 ± 1.87 | 0.29 ± 0.70 | 0.00 ± 0.76 |
DUBROVNIK | 4.01 ± 1.42 | 3.98 ± 1.45 | 4.67 ± 1.70 | −0.66 ± 0.62 | −0.69 ± 0.70 |
VLM estimates from in situ RSL and remotely observed C3S and SLCCI ASL 1993-2015.
Column 4 of Table 4 reports the RSLR, which is common to both ways to calculate VLM, the classical and the LIPWC.. In columns 2 and 3, differences can be seen in the ASLR measured by C3S and SLCCI: the most notable refers to TRIESTE, which appears to observe an ASLR of 4.51 mm y−1 in the C3S dataset, and 3.42 mm y−1 in the SLCCI dataset: these numbers differ by more than 1 mm y−1. The difference in ASLR for TRIESTE is reflected in the final VLM rate. Regardless the marked difference for TRIESTE, the other rates appear in good agreement between the two datasets, even if in general C3S supplies lower errors.
So far, we have shown the results of the classical approach to VLM determination from altimetry and tide gauge. From now on we present and analyze the results of the linear inverse problem with constraints, in the modified version which exploit a change of variable to disentangle the contribution of the ASLR from the system. To do so we examine only the results relative to the C3S dataset, for three reasons: first of all, the final results do not differ much between the two datasets; second, the C3S gridded product has an enhanced resolution in the Mediterranean Sea, and an appropriate regional processing; third, the C3S dataset has a time span longer than SLCCI, and most important, it is intended to be continuously updated in the future. VLM results derived with the LIPWC-COV approach are shown in Table 5, together with the values of the ASLR and RSLR values used for the calculation, and the VLM derived with the classical approach for ease of comparison.
Location | (mm y−1) | (mm y−1) | (mm y−1) | (mm y−1) | LIPWC-COV (mm y−1) | GPS (mm y−1) |
---|---|---|---|---|---|---|
VENEZIA | 3.36 ± 1.45 | 5.15 ± 1.73 | 3.26 ± 0.73 | −1.79 ± 0.65 | −0.93 ± 0.39 | −1.59 ± 0.65 |
VEPTF | 3.38 ± 1.46 | 5.50 ± 1.73 | 3.78 ± 0.73 | −2.12 ± 0.67 | −1.41 ± 0.47 | — |
TRIESTE | 3.75 ± 1.58 | 3.56 ± 1.66 | 2.30 ± 0.67 | 0.18 ± 0.60 | 0.42 ± 0.33 | −0.25 ± 0.52 |
ROVINJ | 3.33 ± 1.58 | 1.03 ± 1.85 | 1.36 ± 0.71 | 2.30 ± 1.06 | 0.93 ± 0.37 | −1.51 ± 1.03 |
SPLIT | 3.60 ± 1.36 | 2.92 ± 1.65 | 2.20 ± 0.66 | 0.68 ± 0.63 | 0.37 ± 0.33 | 0.10 ± 0.64 |
DUBROVNIK | 3.34 ± 1.22 | 3.79 ± 1.48 | 2.69 ± 0.58 | −0.45 ± 0.55 | −0.41 ± 0.46 | −1.83 ± 0.70 |
VLM results using C3S altimetry dataset (1993–2018). Location in column 1; ASLR in column 2; RSLR in the altimetry era (1993-2018) in column 3; RSLR 1974-2018 in column 4; VLM calculated with the classical approach in column 5, as in column 4 of Table 3, and with the LIPWC-COV in column 6. Columns 7 reports the VLM values directly detected by the GPS stations associated with three TGs.
The difference between the results obtained in the classical approach and the LIPWC-COV approach is evident; while the classical approach range of VLMs is [−2.12 2.30] mm y−1, that provided by LIPWC-COV is almost half as wide: [−1.41 0.93]. This is to the result of the introduction of the constraints in Eq. (7), which enter the linear system, propagating the structure and values of the relative vertical motion between the TGs in the solution. The effect of the constraints is best seen in Figure 5, where the plot of the LIPWC-COV solution follows the general form of the classical solution, but with a reduced spread.
Scatterplots of VLM values derived with the classical
In Figure 5 are reported also the VLM values measured by the CGPS stations of PSAL (VENEZIA), TRIE (TRIESTE) and SPLT (SPLIT), and the values of VLM estimated by Wöppelmann and Marcos [50] with the LIPWC technique without the change of variable.
In the classical approach, as there is no optimization of errors as in the LIPWC technique, we see a wide spread of the VLM values. This is particularly evident for ROVINJ TG, whose
The discrepancy observed between this study and that of Wöppelmann and Marcos can largely be ascribed to the different periods covered by the altimetry datasets (C3S and SLCCI datasets cover time periods respectively 44% and 23% longer than the study of Wöppelmann and Marcos). Other factors that may contribute to explain the difference between the results of the two studies are the processing of the altimetry data and the inclusion of the VEPTF TG in this study. The rates of absolute sea level change at the TGs, calculated as the sum of relative sea level change and VLMs derived in this study with the LIPWC-COV approach, for the whole period covered by the TG record, are reported in Table 6.
Location | |
---|---|
VENEZIA | 2.33 ± 0.83 |
VEPTF | 2.37 ± 0.86 |
TRIESTE | 2.71 ± 0.75 |
ROVINJ | 2.29 ± 0.80 |
SPLIT | 2.57 ± 0.74 |
DUBROVNIK | 2.28 ± 0.74 |
Pooled mean | 2.43 ± 0.80 |
Sample mean | 2.43 ± 0.18 |
ASLR from TG records over whole period 1974–2018, corrected for VLM estimated with the LIPWC-COV approach. All data are in mm y−1.
The uncertainty of the sample mean (last row of Table 6) was obtained as standard error of the sample mean, considering the rates as random and independent variables. The absolute sea level change rates vary in a very narrow interval, 2.33–2.71, with a sample mean of 2.43 mm y−1. The standard deviation of the sample is much lower than the precision of each individual determination of SL change rate at the TGs. As pointed out by Wöppelmann and Marcos [50], such a low dispersion is unlikely to be determined from estimates of independent random variables: it is instead the evidence of the high performance of LIPWC method for determining accurate VLM rates from TG and altimetry differenced time series. The ASLR rates calculated by altimetry in 1993–2018 and through the LIPWC-COV technique (1974–2018) are shown in Figure 6.
Absolute sea level change rates as calculated by altimetry 1993–2018, and by the LIPWC-COV approach integrating data from TGs in 1974–2018.
Clearly, the ASLR values calculated for the longer period are smaller than those calculated in the shorter one, but the modulation of the rate from TG to TG is apparently reflected in the LIPWC-COV approach. As already noted, the errors associated to the ASLR rates derived in the LIPWC-COV are also smaller, thanks to the introduction of the constraints on the relative vertical land motion between paired TGs. The mean value of the ASLR calculated for the Adriatic Sea with the LIPWC-COV approach, is in general agreement with both regional studies on the Mediterranean Sea (0.7 ± 0.2 mm y−1 (1945–2000) [65]; 1.60 ± 0.35 mm y−1 (1992–2010) [50]; 2.44 ± 0.5 mm y−1 (1993–2012) [66]; 2.87 ± 0.33 mm y−1 (1992–2016) [67]), and at global scale (2.0 ± 0.3 mm y−1 (1971–2010) [68]; 3.0 ± 0.7 mm y−1 (1993–2010) [69]; 2.8 ± 0.5 mm y−1 (1993–2010) [68]; 3.1 mm y−1 (1992–2018) [32]).
Among the ASLR altimetry rates associated with the six TGs in the Adriatic Sea, those for TRIESTE are very different in the C3S and SLCCI dataset. In order to investigate such a large difference (0.02 ± 0.71 mm y−1 SLCCI; −1.07 ± 0.74 mm y−1 C3S; see Table 4) the SLCCI-AT X-TRACK/ALES 20 Hz along-track coastal altimetry dataset has been used.
The analysis focuses on the descending track 196 of the Jason-1 (2001–2013) and Jason-2 (2008–2019) altimetry missions and covers the period 2002–2016 with 532 cycles (from 22 Jan 2002 to 23 Jun 2016 at 350 m resolution along-track) with MSSH computed using cycles from 1 to 517. The position of the track 196 and the geographical setting are shown in Figure 7.
Gulf of Trieste. The positions of the SLCCI along-track 20 Hz altimetric product version 1.0 samples of the descending track 196 (white circles), and the TRIESTE TG stations (red triangle). Umag in Croatia and Grado in Italy are also shown (green circles).
Altimetry data at the 71 observation points of track 196 are compared to 10′ interval RSL observations of the TRIESTE TG. The TG time series did not undergo any filtering or processing, and the astronomical tide and Dynamic Atmospheric Correction (DAC) corrections are not applied to the altimetry time series.
The goal of the investigation is to explore the possible causes of the different ASLR rates obtained by the two gridded altimetry datasets near Trieste, to look for clues directly into the original along track data from the Jason missions, reprocessed with advanced and coastal specific re-tracking (ALES) and improved coastal processing (X-TRACK). We also want to ascertain the suitability of the new SLCCI-AT record in long term coastal sea level monitoring. We concentrated on the altimeter track 196 of the SLCCI-AT dataset, which first crosses Marano Lagoon and a 0.5 km wide sandbar before entering the Gulf of Trieste from north, near Grado, and then flies over Umag and the full extent of the Istria peninsula. The retrieval is particularly problematic in the gulf area due to the complex morphology of the land. Moreover, some data loss could be due to sea-to-land and land-to-sea crossings that might influence the behavior of the on-board tracker. Operational altimetry products do not provide data over this section of the Gulf of Trieste, while the SLCCI-AT dataset provides 71 points along track, most of which yield over 70% of valid data (blue box in Figure 8). The most improvement is near the Istrian peninsula with more than 90% of data recovered. The valid data percentages decrease abruptly over a distance ranging 5 km from the coast. The reduced performance over the lagoon and islet (almost all data have been rejected) is probably related to the data corruption in the land-sea-transition. Note that at 1 Hz, any coastal altimetry along track product would give no more than 3–4 points along this 24 km long stretch of track 196.
J1 + J2 track 196 geographical settings. Left: Percentage of valid data along the track. Right: Correlation with TRIESTE tide gauge. Adapted from the coastal sea level project of the ESA climate change initiative (SL_CCI bridging phase) document “Part II: Validation Results” (
The data accuracy can be assessed in more detail comparing the altimeter-derived 20-Hz SLA with corresponding tide gauge sea level measurements. It should be noted that the TRIESTE TG is located in the harbor, and therefore it does not measure exactly the same ocean dynamics as the altimeter flying offshore. Nonetheless, the Pearson’s linear correlation coefficient of most of the 71 points along the section of track 196 facing the Trieste harbor exceeds 0.9 (red box in Figure 8). The RMS difference between altimetry observations and tide gauge measurements of instantaneous sea level is almost constant along the track 196 section in the Gulf of Trieste, and around 10 cm (not shown).
From the time series of SLCCI-AT SLA at each data point of the track 196 facing Trieste, we have calculated the slopes of the fitting lines, gradually growing the confidence interval from 68–95%, and performed Mann-Kendall statistical significance tests [70, 71] modified for autocorrelated data [72] on all the 71 fitting lines. The Mann-Kendall test is commonly employed to detect monotonic trends in time series. The null hypothesis is that the data come from a population with independent realizations and are identically distributed. The alternative hypothesis is that the data follow a monotonic trend. In Figure 9 the results of such calculation are reported for a preliminary version of the SLCCI-AT dataset at 20 Hz. The black diamonds mark the acceptance or rejection of the null hypothesis following this scheme:
1 - the null hypothesis “the sample has no trend” is rejected.
0 - the null hypothesis “the sample has no trend” cannot be rejected.
Slopes and slop errors of the lines fitting the time series of along track SLA at every data point of track 196 near Trieste. Also plotted the Mann-Kendall test results. Black diamonds: 1 - rejection of the null hypothesis (the sample has no trend); 0 - no rejection. Green line: p_value. Adapted from the coastal sea level project of the ESA climate change initiative (SL_CCI bridging phase) document “Part II: Validation Results” (
Already with a 68% confidence interval the null hypothesis (the trend is not statistically significant) is rejected in less than 24% of the data points. With a 95% confidence interval only for four fitting lines out of 71 the null hypothesis is rejected. In both cases the errors associated to the slopes are higher than the slopes themselves.
A similar analysis replicated on the final version of the SLCCI-AT dataset, published at the end of the SLCCI project, gave better results. Figure 10 reports the representation of the statistical characteristics of the slopes derived from the last version of the data of the SLCCI-AT X-TRACK/ALES SLA 20 Hz, with 95% confidence interval. The left panel shows slopes and associated errors at every data point latitude (low latitudes are near Umag, high latitudes near Grado); different colors indicate the statistical significance of the Mann-Kendall test (blue: significant; orange: not significant). The right panel shows the box and whisker plots of the two distributions (left: not significant; right: significant). The number of statistically significant slopes is much higher in the final version of the dataset, even if the variability is still rather high and difficult to explain because of the limited spatial variability along the track. Slopes are higher towards north (Grado), and lower near Umag. Considering only the statistically significant slopes in the SLCCI-AT dataset, their sample mean and standard deviation result to be 3.40 ± 1.01 mm y−1 (Feb-2002 – Jun-2016) which is not far from the trends we have found in the Adriatic Sea at all the tide gauges. We recalculated the altimetry trends near TRIESTE in the SLCCI and C3S gridded products. The altimetry ASLR trends found so far in the analysis are summarized in Table 7.
SLCCI SLA 20 Hz. Left: Slopes and slope errors of the lines fitting every data point of the track 196 in the Gulf of Trieste. Blue: Statistically significant slopes according to the Mann-Kendall test. Orange: Slopes not significant. Right: Box and whisker plots for the statistically significant and non-significant slopes. Red: Median value. Box: Upper and lower quartiles. Whiskers: Highest and lowest observations. Adapted from the coastal sea level project of the ESA climate change initiative (SL_CCI bridging phase) document “Part II: Validation Results” (
SLCCI-AT (mm y−1) | SLCCI (mm y−1) | C3S (mm y−1) |
---|---|---|
3.40 ± 1.01 | 3.66 ± 3.97 | 5.07 ± 3.64 |
Trends for Trieste in February 2002 – June 2016 from SLCCI project and C3S altimetry. Column 1: SLCCI-AT along track 20 Hz product. Column 2: SLCCI gridded product. Column 3: C3S gridded product.
The trends calculated with the SLCCI dataset (along track and gridded) are in good agreement, apart from the different errors affecting the two results, due to the different methods used to calculate them. The C3S trend is instead higher than the other two. We believe that the difference between the results is to be ascribed to the different methodologies used in the two products. In any case the difference between the SLCCI and the C3S results is not yet explained by this further analysis, and the Gulf of Trieste remains a controversial place for the derivation of climatologically relevant oceanic variables from altimetry, because of the proximity of the land and the geometry of the surrounding coastline, and the very short time coverage of the altimetric datasets.
The sea level is a key variable of the climate system. Tide gauges measuring sea level variability are in operation since the 1900s. Satellite-based observations of sea level changes are more recent. Nevertheless, they play a crucial role in understanding the future coastal sea level changes. Advance in the processing of satellite radar altimetry have expanded the utility of this data set for climate-related studies and extended the potential exploitation in the coastal zone. The joint usage of the two different measuring systems (in situ and satellite) has two challenges. First how the two data sets can be consistently and systematically used in synergy to address that objective of estimating robust coastal sea level trends. Second how using high-rate (i.e. 20 Hz) altimeter measurements with a coastal-oriented processing could improve the satellite-based trend estimates with respect to the standard (1 Hz) data, especially near coast.
In this chapter, a more robust inverse method (called LIPWC-COV) has been proposed and tested in the Northern Adriatic Sea, where GPS data are available to conduct a realistic assessment of uncertainties. The results show that the classical approach of estimating VLMs provides less accurate trends than the LIPWC-COV method, and with lower errors. Moreover, the LIPWC-COV has demonstrated to compare better than the classic method with GPS derived VLMs.
In this chapter, the experimental SLCCI data set (high resolution along track) coastal sea level product (developed within SLCCI project) has been also assessed in the Gulf of Trieste, as it was possible only at that site. The retrieval is particularly problematic in the gulf area due to the complex morphology of the land. The trends calculated with the gridded and along track datasets show some differences, probably due to the different methodologies used in the generation of the products.
This study offers a more consolidated and improved understanding of the sea level trend variability in the Northern Adriatic Sea. The next step is to extend the application of the new methodology to the Mediterranean Sea.
The authors want to thank the European Space Agency, which propelled the Climate Change Initiative to produce a climate quality record of sea level from satellite altimetry. Likewise, the authors express gratitude to the European Union for making available the satellite altimetry data record through the Copernicus Earth Observation Programme Services. The authors also want to acknowledge Centro Previsioni e Segnalazioni Maree (CPSM) and Alvise Papa for providing tide gauge data under the CNR-ISP/CPSM technical–scientific collaboration agreement 2019–2022; the CNES distribution service AVISO+ for the dynamic atmospheric correction data; the Italian Institute for Environmental Protection and Research (ISPRA) for providing tide gauge and GPS data; CNR-ISMAR and Fabio Raicich for the time series of the Trieste tide gauge; PSMSL, national Oceanographic Centre, Liverpool, UK, for making available the tide gauge global record. The authors thank the SONEL Data Centre and the Nevada Geodetic Laboratory (NGL) for processing and making available the GPS trend global record. Finally, we acknowledge CPSM for funding the “Vento da Satellite+” project on the development of satellite data in storm surge forecasting; ESA who funded the “HYDROCOASTAL” project (ESA contract No. 4000129872/20/I-DT), and the “SL_CCI Bridging Phase” project (ESA contract No. 4000109872/13/I-NB), from which some of the images in this chapter were adapted.
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Pereira, Maria J. Martins, Isabel Azevedo and Rosário Monteiro",authors:[{id:"74789",title:"Prof.",name:"Rosário",middleName:null,surname:"Monteiro",slug:"rosario-monteiro",fullName:"Rosário Monteiro"},{id:"74796",title:"Dr.",name:"Cidália",middleName:null,surname:"Pereira",slug:"cidalia-pereira",fullName:"Cidália Pereira"},{id:"74800",title:"Prof.",name:"Isabel",middleName:null,surname:"Azevedo",slug:"isabel-azevedo",fullName:"Isabel Azevedo"},{id:"160587",title:"Prof.",name:"Maria João",middleName:null,surname:"Martins",slug:"maria-joao-martins",fullName:"Maria João Martins"}]},{id:"27067",title:"Telocytes in Human Fallopian Tube and Uterus Express Estrogen and Progesterone Receptors",slug:"telocytes-in-human-fallopian-tube-and-uterus-express-estrogen-and-progesterone-receptors",totalDownloads:2272,totalCrossrefCites:0,totalDimensionsCites:22,abstract:null,book:{id:"805",slug:"sex-steroids",title:"Sex Steroids",fullTitle:"Sex Steroids"},signatures:"Sanda M. Cretoiu, Dragos Cretoiu Anca Simionescu and Laurentiu M. Popescu",authors:[{id:"65176",title:"Dr.",name:"Dragos",middleName:null,surname:"Cretoiu",slug:"dragos-cretoiu",fullName:"Dragos Cretoiu"},{id:"71558",title:"Dr.",name:"Sanda",middleName:"Maria",surname:"Cretoiu",slug:"sanda-cretoiu",fullName:"Sanda Cretoiu"},{id:"71561",title:"Dr.",name:"Anca",middleName:null,surname:"Simionescu",slug:"anca-simionescu",fullName:"Anca Simionescu"},{id:"71562",title:"Prof.",name:"Laurentiu M.",middleName:null,surname:"Popescu",slug:"laurentiu-m.-popescu",fullName:"Laurentiu M. Popescu"}]},{id:"27793",title:"Sex Steroids in Insects and the Role of the Endosymbiont Wolbachia:A New Perspective",slug:"sex-steroids-in-insects-and-the-role-of-the-endosymbiont-wolbachia-a-new-perspective",totalDownloads:3646,totalCrossrefCites:5,totalDimensionsCites:12,abstract:null,book:{id:"804",slug:"sex-hormones",title:"Sex Hormones",fullTitle:"Sex Hormones"},signatures:"Ilaria Negri and Marco Pellecchia",authors:[{id:"68168",title:"Dr.",name:"Ilaria",middleName:null,surname:"Negri",slug:"ilaria-negri",fullName:"Ilaria Negri"},{id:"74147",title:"Dr",name:"Marco",middleName:null,surname:"Pellecchia",slug:"marco-pellecchia",fullName:"Marco Pellecchia"}]},{id:"60756",title:"The Biological Role of Androgen Receptor in Prostate Cancer Progression",slug:"the-biological-role-of-androgen-receptor-in-prostate-cancer-progression",totalDownloads:1876,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"Prostate cancer is the most commonly diagnosed cancer in men all over the world. Localized cancers in the early stages can be well managed by surgical or radiation therapy. Metastatic prostate cancer is treated with androgen deprivation therapy because androgen signaling is essential to the prostate tumor growth and anti-apoptotic ability. However, resistance develops quickly in the clinical course and leads to castration-resistant prostate cancer (CRPC). Androgen receptor (AR) functions as a nuclear receptor to facilitate ligand-dependent transcriptional activation in the nucleus. AR interacts with several tissue-specific transcription factors such as forkhead box protein A1 (FOXA1) and regulates epigenetic status by recruiting epigenetic factors. In addition, AR transcriptional activity is modulated by interacting directly or indirectly with non-coding RNAs such as long non-coding RNAs (lncRNAs) and micro RNAs (miRNAs). Notably, enhanced AR signaling in CRPC has been documented in several studies; however, which of these factors are important for the biological function it remains poorly understood. Here, I review our current knowledge of the mechanistic roles of AR involved in prostate cancer progression and discuss the importance of the prostate cancer-associated signals.",book:{id:"6762",slug:"advances-in-testosterone-action",title:"Advances in Testosterone Action",fullTitle:"Advances in Testosterone Action"},signatures:"Ken-ichi Takayama",authors:[{id:"239221",title:"Dr.",name:"Ken-Ichi",middleName:null,surname:"Takayama",slug:"ken-ichi-takayama",fullName:"Ken-Ichi Takayama"}]},{id:"75047",title:"Role of Sex Hormones in Human Body",slug:"role-of-sex-hormones-in-human-body",totalDownloads:566,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"Gonadal Steroids hormones play an important role in the reproductive and non-reproductive systems. Estrogen has important rule in cardiovascular system as it has vasodilator effect and reduces or prevents platelet activation. In addition, it improves the profile of circulating lipoproteins. All of which may explain why women at premenopausal age are less likely to have heart disease than menopause women or men. E2 play a grate effect on the skeletal system as it is one of the strongest regulators of osteoblast and osteoclast function, and it is responsible for the reduction of adipose tissue and regulation of the body weight, and also has dermatological effect,hence it stimulates the proliferation of keratinocytes and prevents their apoptosis, in addition to the progesterone which increases collagen synthesis. Estrogen is necessary for the functioning and integrity of the tissues of the urinary system specially of the lower urinary tract. Sex steroid are crucial for nervous system, as progesterone is important for production of neurosteroid, and estrogen is currently used in Parkinson’s and Alzheimer’s disease because of its effects on mental health. The androgens also have a crucial biological effects on neural, muscle, bone, adipose tissue,prostate, cardiovascular, haemopoietic, and the reproductive systems. The gonadal steroid hormones play an important role in immune system and regulating the immune response against different viral or bacterial infections.",book:{id:"10313",slug:"reproductive-hormones",title:"Reproductive Hormones",fullTitle:"Reproductive Hormones"},signatures:"Nassrin Malik Aubead",authors:[{id:"329956",title:"Dr.",name:"Nassrin",middleName:null,surname:"Malik Aubead",slug:"nassrin-malik-aubead",fullName:"Nassrin Malik Aubead"}]}],onlineFirstChaptersFilter:{topicId:"1014",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:31,numberOfPublishedChapters:314,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:18,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:14,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,annualVolume:11418,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,annualVolume:11419,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,annualVolume:11420,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,annualVolume:11421,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,annualVolume:11422,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. 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