1 resultado para HLRF-BASED ALGORITHMS
em DigitalCommons - The University of Maine Research
Filtro por publicador
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (2)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (29)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (15)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (4)
- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (1)
- Aston University Research Archive (30)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (10)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (128)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (33)
- Brock University, Canada (5)
- Bulgarian Digital Mathematics Library at IMI-BAS (19)
- CaltechTHESIS (1)
- CentAUR: Central Archive University of Reading - UK (58)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (2)
- Cochin University of Science & Technology (CUSAT), India (7)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (39)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- CUNY Academic Works (2)
- Dalarna University College Electronic Archive (3)
- Department of Computer Science E-Repository - King's College London, Strand, London (1)
- Digital Commons - Michigan Tech (11)
- Digital Commons at Florida International University (18)
- Digital Peer Publishing (3)
- DigitalCommons - The University of Maine Research (1)
- DigitalCommons@The Texas Medical Center (7)
- DigitalCommons@University of Nebraska - Lincoln (4)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (19)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (1)
- FUNDAJ - Fundação Joaquim Nabuco (1)
- Glasgow Theses Service (1)
- Greenwich Academic Literature Archive - UK (2)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (4)
- Institutional Repository of Leibniz University Hannover (2)
- INSTITUTO DE PESQUISAS ENERGÉTICAS E NUCLEARES (IPEN) - Repositório Digital da Produção Técnico Científica - BibliotecaTerezine Arantes Ferra (2)
- Instituto Politécnico de Bragança (1)
- Instituto Politécnico de Leiria (1)
- Instituto Politécnico do Porto, Portugal (38)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (1)
- Martin Luther Universitat Halle Wittenberg, Germany (1)
- Massachusetts Institute of Technology (6)
- Memorial University Research Repository (2)
- National Center for Biotechnology Information - NCBI (1)
- Nottingham eTheses (6)
- Publishing Network for Geoscientific & Environmental Data (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (7)
- RCAAP - Repositório Científico de Acesso Aberto de Portugal (1)
- Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa) (1)
- Repositório Científico da Universidade de Évora - Portugal (2)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (5)
- Repositório da Produção Científica e Intelectual da Unicamp (33)
- Repositório da Universidade Federal do Espírito Santo (UFES), Brazil (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (2)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional da Universidade Federal do Rio Grande - FURG (1)
- Repositorio Institucional de la Universidad de Málaga (3)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (40)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (15)
- Scielo Saúde Pública - SP (1)
- Universidad de Alicante (13)
- Universidad del Rosario, Colombia (1)
- Universidad Politécnica de Madrid (49)
- Universidade Complutense de Madrid (2)
- Universidade do Minho (11)
- Universidade Federal de Uberlândia (1)
- Universidade Federal do Pará (1)
- Universitat de Girona, Spain (15)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (4)
- Université de Lausanne, Switzerland (54)
- Université de Montréal (1)
- Université de Montréal, Canada (9)
- Université Laval Mémoires et thèses électroniques (1)
- University of Canberra Research Repository - Australia (2)
- University of Michigan (2)
- University of Queensland eSpace - Australia (34)
- University of Washington (1)
- WestminsterResearch - UK (3)
Resumo:
Efforts to understand and model the dynamics of the upper ocean would be significantly advanced given the ability to rapidly determine mixed layer depths (MLDs) over large regions. Remote sensing technologies are an ideal choice for achieving this goal. This study addresses the feasibility of estimating MLDs from optical properties. These properties are strongly influenced by suspended particle concentrations, which generally reach a maximum at pycnoclines. The premise therefore is to use a gradient in beam attenuation at 660 nm (c660) as a proxy for the depth of a particle-scattering layer. Using a global data set collected during World Ocean Circulation Experiment cruises from 1988-1997, six algorithms were employed to compute MLDs from either density or temperature profiles. Given the absence of published optically based MLD algorithms, two new methods were developed that use c660 profiles to estimate the MLD. Intercomparison of the six hydrographically based algorithms revealed some significant disparities among the resulting MLD values. Comparisons between the hydrographical and optical approaches indicated a first-order agreement between the MLDs based on the depths of gradient maxima for density and c660. When comparing various hydrographically based algorithms, other investigators reported that inherent fluctuations of the mixed layer depth limit the accuracy of its determination to 20 m. Using this benchmark, we found a similar to 70% agreement between the best hydrographical-optical algorithm pairings.