Relevant bibliographies by topics / Weather radar networks

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Weather radar networks'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Weather radar networks"

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Junyent, Francesc, and V. Chandrasekar. "Theory and Characterization of Weather Radar Networks." Journal of Atmospheric and Oceanic Technology 26, no. 3 (2009): 474–91. http://dx.doi.org/10.1175/2008jtecha1099.1.

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Abstract A dense weather radar network is an emerging concept advanced by the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). In a weather radar environment, the specific radar units employed and the network topology will influence the characteristics of the data obtained. To define this, a general framework is developed to describe the radar network space, and formulations are obtained that can be used for weather radar network characterization. The models developed are useful for quantifying and comparing the performance of different weather radar net
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Lengfeld, K., M. Clemens, H. Münster, and F. Ament. "Performance of high-resolution X-band weather radar networks – the PATTERN example." Atmospheric Measurement Techniques 7, no. 12 (2014): 4151–66. http://dx.doi.org/10.5194/amt-7-4151-2014.

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Abstract. This publication intends to prove that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) project observing precipitation with a temporal resolution of 30 s, a range resolution of 60 m and a sampling resolution of 1° in the azimuthal direction. The network covers an area of 60 km × 80 km. In this paper, algorithms u
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Lengfeld, K., M. Clemens, H. Münster, and F. Ament. "Performance of high-resolution X-band weather radar networks – the PATTERN example." Atmospheric Measurement Techniques Discussions 7, no. 8 (2014): 8233–70. http://dx.doi.org/10.5194/amtd-7-8233-2014.

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Abstract. This publication intends to proof that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the project Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) observing precipitation with temporal resolution of 30 s, azimuthal resolution of 1° and spatial resolution of 60 m. The network covers an area of 60 km × 80 km. In this paper algorithms used to obtain undisturbed preci
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Overeem, Aart, Iwan Holleman, and Adri Buishand. "Derivation of a 10-Year Radar-Based Climatology of Rainfall." Journal of Applied Meteorology and Climatology 48, no. 7 (2009): 1448–63. http://dx.doi.org/10.1175/2009jamc1954.1.

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Abstract Weather radars give quantitative precipitation estimates over large areas with high spatial and temporal resolutions not achieved by conventional rain gauge networks. Therefore, the derivation and analysis of a radar-based precipitation “climatology” are highly relevant. For that purpose, radar reflectivity data were obtained from two C-band Doppler weather radars covering the land surface of the Netherlands (≈3.55 × 104 km2). From these reflectivities, 10 yr of radar rainfall depths were constructed for durations D of 1, 2, 4, 8, 12, and 24 h with a spatial resolution of 2.4 km and a
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Kurdzo, James M., and Robert D. Palmer. "Objective Optimization of Weather Radar Networks for Low-Level Coverage Using a Genetic Algorithm." Journal of Atmospheric and Oceanic Technology 29, no. 6 (2012): 807–21. http://dx.doi.org/10.1175/jtech-d-11-00076.1.

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Abstract The current Weather Surveillance Radar-1988 Doppler (WSR-88D) radar network is approaching 20 years of age, leading researchers to begin exploring new opportunities for a next-generation network in the United States. With a vast list of requirements for a new weather radar network, research has provided various approaches to the design and fabrication of such a network. Additionally, new weather radar networks in other countries, as well as networks on smaller scales, must balance a large number of variables in order to operate in the most effective way possible. To offer network desi
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Cho, John Y. N., and James M. Kurdzo. "Weather Radar Network Benefit Model for Flash Flood Casualty Reduction." Journal of Applied Meteorology and Climatology 59, no. 4 (2020): 589–604. http://dx.doi.org/10.1175/jamc-d-19-0176.1.

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ABSTRACTA monetized flash flood casualty reduction benefit model is constructed for application to meteorological radar networks. Geospatial regression analyses show that better radar coverage of the causative rainfall improves flash flood warning performance. Enhanced flash flood warning performance is shown to decrease casualty rates. Consequently, these two effects in combination allow a model to be formed that links radar coverage to flash flood casualty rates. When this model is applied to the present-day contiguous U.S. weather radar network, results yield a flash flood–based benefit of
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Cerda Villafaña, Gustavo, Sergio Ledesma, and Dawei Han. "Weather Radar Estimations Feeding an Artificial Neural Network Model." Acta Universitaria 18, no. 2 (2008): 11–17. http://dx.doi.org/10.15174/au.2008.142.

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The application of ANNs (Artifi cial Neural Networks) has been studied by many researchers in modelling rainfall runoff processes. However, the work so far has been focused on the rainfall data from traditional raingauges. Weather radar is a modern technology which could provide high resolution rainfall in time and space. In this study, a comparison in rainfall runoff modelling between the raingauge and weather radar has been carried out. The data were collected from Brue catchment in Southwest of England, with 49 raingauges covering 136 km2 and two C-band weather radars. This raingauge networ
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Holleman, Iwan, Asko Huuskonen, Mikko Kurri, and Hans Beekhuis. "Operational Monitoring of Weather Radar Receiving Chain Using the Sun." Journal of Atmospheric and Oceanic Technology 27, no. 1 (2010): 159–66. http://dx.doi.org/10.1175/2009jtecha1213.1.

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Abstract A method for operational monitoring of a weather radar receiving chain, including the antenna gain and the receiver, is presented. The “online” method is entirely based on the analysis of sun signals in the polar volume data produced during operational scanning of weather radars. The method is an extension of that for determining the weather radar antenna pointing at low elevations using sun signals, and it is suited for routine application. The solar flux from the online method agrees very well with that obtained from “offline” sun tracking experiments at two weather radar sites. Fur
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Bendix, Jörg, Andreas Fries, Jorge Zárate, et al. "RadarNet-Sur First Weather Radar Network in Tropical High Mountains." Bulletin of the American Meteorological Society 98, no. 6 (2017): 1235–54. http://dx.doi.org/10.1175/bams-d-15-00178.1.

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Abstract Weather radar networks are indispensable tools for forecasting and disaster prevention in industrialized countries. However, they are far less common in the countries of South America, which frequently suffer from an underdeveloped network of meteorological stations. To address this problem in southern Ecuador, this article presents a novel radar network using cost-effective, single-polarization, X-band technology: the RadarNet-Sur. The RadarNet-Sur network is based on three scanning X-band weather radar units that cover approximately 87,000 km2 of southern Ecuador. Several instrument
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Kurdzo, James M., Emily F. Joback, Pierre-Emmanuel Kirstetter, and John Y. N. Cho. "Geospatial QPE Accuracy Dependence on Weather Radar Network Configurations." Journal of Applied Meteorology and Climatology 59, no. 11 (2020): 1773–92. http://dx.doi.org/10.1175/jamc-d-19-0164.1.

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AbstractThe relatively low density of weather radar networks can lead to low-altitude coverage gaps. As existing networks are evaluated for gap fillers and new networks are designed, the benefits of low-altitude coverage must be assessed quantitatively. This study takes a regression approach to modeling quantitative precipitation estimation (QPE) differences based on network density, antenna aperture, and polarimetric bias. Thousands of cases from the warm-season months of May–August 2015–17 are processed using both the specific attenuation [R(A)] and reflectivity–differential reflectivity [R(
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Dissertations / Theses on the topic "Weather radar networks"

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Abes, Brahim. "Real-time control of urban drainage systems using weather radar." Thesis, University of Salford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262685.

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Zarookian, Ruffy. "Feasibility of Spectrum Sharing Between Airborne Weather Radar and Wireless Local Area Networks." Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/35841.

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Emerging technologies such as wireless local area networks and cellular telephones have dramatically increased the use of wireless communications services within the last 10 years. The shortage of available spectrum exists due to increasing demand for wireless services and current spectrum allocation regulations. To alleviate this shortage, Research aims to improve spectral efficiency and to allow spectrum sharing between separately managed and non-coordinating communications systems. This thesis explores the feasibility of spectrum sharing between airborne weather radar and wireless local
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Da, Silveira Reinaldo Bomfim. "Recognition of clutter in weather radars using polarization diversity information and artificial neural networks." Thesis, University of Essex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265022.

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Esterhuyse, Daniel Johannes. "Establishment of the South African baseline surface radiation network station at De Aar." Pretoria : [s.n.], 2004. http://upetd.up.ac.za/thesis/available/etd-01182005-115035.

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Boon, Dirk Francois. "The link between daily rainfall and satellite radar backscatter data from the ERS-2 scatterometer in the Free State Province, South Africa." Diss., Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-10272008-132211.

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Mandapaka, Venkata Pradeep. "Role of rainfall variability in the statistical structure of peak flows." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/403.

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This thesis examines the role of rainfall variability and uncertainties on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas, and Iowa River basin in Iowa as illustrations. We illustrate why considering individual hydrographs at the outlet of a basin can lead to misleading interpretations of the effects of rainfall variability. The variability of rainfall is characterized in terms of storm intensity, duration, advection velocity, zero-rain intermittency, variance and spatial correlation structure. We begin with the simple scenario of a basin receiving spati
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Kattekola, Sravanthi. "Weather Radar image Based Forecasting using Joint Series Prediction." ScholarWorks@UNO, 2010. http://scholarworks.uno.edu/td/1238.

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Accurate rainfall forecasting using weather radar imagery has always been a crucial and predominant task in the field of meteorology [1], [2], [3] and [4]. Competitive Radial Basis Function Neural Networks (CRBFNN) [5] is one of the methods used for weather radar image based forecasting. Recently, an alternative CRBFNN based approach [6] was introduced to model the precipitation events. The difference between the techniques presented in [5] and [6] is in the approach used to model the rainfall image. Overall, it was shown that the modified CRBFNN approach [6] is more computationally efficient
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Paduru, Anirudh. "Fast Algorithm for Modeling of Rain Events in Weather Radar Imagery." ScholarWorks@UNO, 2009. http://scholarworks.uno.edu/td/1097.

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Weather radar imagery is important for several remote sensing applications including tracking of storm fronts and radar echo classification. In particular, tracking of precipitation events is useful for both forecasting and classification of rain/non-rain events since non-rain events usually appear to be static compared to rain events. Recent weather radar imaging-based forecasting approaches [3] consider that precipitation events can be modeled as a combination of localized functions using Radial Basis Function Neural Networks (RBFNNs). Tracking of rain events can be performed by tracking th
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Filho, Kleber Lopes da Rocha. "Modelagem Hidrológica da Bacia do Rio Pirajuçara com TOPMODEL, Telemetria e Radar Meteorológico." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/14/14133/tde-21062013-124917/.

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A Bacia do Alto Tiete abriga cerca de 50% dos habitantes do Estado de São Paulo e é afetada freqüentemente por eventos de inundações. Uma das principais fontes de problemas é a alta impermeabilização devida à ocupação da superfície nas últimas décadas. Um dos seus tributários secundários, a bacia do Rio Pirajuçara se insere neste contexto e sofre com problemas da mesma natureza. A modelagem hidrológica permite uma análise do escoamento superficial nestes ambientes e é útil na previsão de vazões por meio de redes telemétricas e sensoriamento remoto. Entretanto, redes telemétricas apresentam pr
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Yen-Ming, Chiang. "Artificial Neural Networks in Hydrometeorology-Flood Forecasting from Radar and Numerical Weather Prediction Information." 2007. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-1801200717585100.

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Books on the topic "Weather radar networks"

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COST 73 Project. Management Committee. Weather radar networking: COST 73 Project : final report. Kluwer Academic Publishers, 1992.

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Hollinger, S. E. Illinois Climate Network: Site descriptions, instrumentation, and data management. Illinois State Water Survey, 1994.

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Panel, National Research Council (U S. ). NEXRAD. Toward a new National Weather Service: Assessment of NEXRAD coverage and associated weather services. National Academy Press, 1995.

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E, Gordon William, National Academy of Sciences (U.S.), and United States. National Oceanic and Atmospheric Administration., eds. Toward a new National Weather Service: Assessment of NEXRAD coverage and associated weather services. National Academy Press, 1995.

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United States. Interdepartmental Committee for Meteorological Services and Supporting Research. Joint Action Group for Phased Array Radar Project. Federal research and development needs and priorities for phased array radar. Office of the Federal Coordinator for Meteorological Services and Supporting Research, 2006.

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Seminar on COST Project 73 (1991 Ljubljana, Slovenia). International weather radar networking: Final seminar of the COST Project 73. Kluwer Academic Publishers, 1992.

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Seminar, on COST Project 73 (1989 Brussels Belgium). Weather radar networking: Seminar on COST Project 73. Kluwer Academic Publishers, 1990.

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Chai, Xiumei, and Jinhong Yang. Xin yi dai tian qi lei da chan pin ying yong ji shu lun wen ji: 2005-2010. 8th ed. Qi xiang chu ban she, 2011.

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Seliga, Thomas A. The NEXRAD radar system as a tool in highway traffic management. Washington State Dept. of Transportation, 1997.

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Environment, United States Congress House Committee on Science Subcommittee on Energy and. Next Generation Weather Radar (NEXRAD): Are we covered? : hearing before the Subcommittee on Energy and Environment of the Committee on Science, U.S. House of Representatives, One Hundred Fourth Congress, first session, October 17, 1995. U.S. G.P.O., 1996.

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Book chapters on the topic "Weather radar networks"

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Gekat, Frank, Peter Meischner, Katja Friedrich, et al. "The State of Weather Radar Operations, Networks and Products." In Weather Radar. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-05202-0_1.

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Wessels, H. R. A. "Estimation of the Areal Coverage of Radars and Radar Networks from Radar Site Horizon Data." In Weather Radar Networking. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_23.

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Singh, Sonam, Sudeshna Sarkar, and Pabitra Mitra. "Leveraging Convolutions in Recurrent Neural Networks for Doppler Weather Radar Echo Prediction." In Advances in Neural Networks - ISNN 2017. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59081-3_37.

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Shi, En, Qian Li, Daquan Gu, and Zhangming Zhao. "A Method of Weather Radar Echo Extrapolation Based on Convolutional Neural Networks." In MultiMedia Modeling. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73603-7_2.

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Overgaard, S. "A Nordic Weather Radar Network." In Weather Radar Networking. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_6.

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Fair, C. A., P. K. James, and P. Larke. "The United Kingdom Weather Radar Network." In Weather Radar Networking. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_16.

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Calheiros, R. V. "The São Paulo Weather Radar Network Program." In Weather Radar Networking. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_7.

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King, R. H. "Operational Experiences with the Finnish Weather Radar Network." In Weather Radar Networking. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_11.

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Calheiros, R. V., and M. A. de Antonio. "Nowcasting for Agriculture with the São Paulo Radar Network." In Weather Radar Networking. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_58.

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Riedl, J. "The Weather Radar Network of the Deutscher Wetterdienst Progress Report." In Weather Radar Networking. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_10.

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Conference papers on the topic "Weather radar networks"

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Yao, Guang, Zongxuan Liu, Xufeng Guo, Chaoshi Wei, Xinfeng Li, and Zhihao Chen. "Prediction of Weather Radar Images via a Deep LSTM for Nowcasting." In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9206889.

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Teschl, R., W. L. Randeu, and F. Teschl. "Weather Radar Estimates of Rainfall Adjusted to Rain Gauge Measurements Using Neural Networks." In The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE, 2006. http://dx.doi.org/10.1109/ijcnn.2006.247242.

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Salazar, Jorge L., Rafael Medina, Eric J. Knapp, and David J. McLaughlin. "Phase-Tilt Array Antenna Design for Dense Distributed Radar Networks for Weather Sensing." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4780092.

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Salazar, Jorge L., Anthony Hopf, Robert F. Contreras, et al. "Coverage comparison of short range radar networks vs. conventional weather radars: Case study in the northwestern United States." In 2009 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5418261.

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Murata, Ken T., Praphan Pavarangkoon, Kazunori Yamamoto, et al. "Improvement of real-time transfer of phased array weather radar data on long-distance networks." In 2016 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET). IEEE, 2016. http://dx.doi.org/10.1109/icramet.2016.7849575.

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Li, Tengwei, and Tao Wang. "The radial-based noise power estimation algorithm in the C-band dual-polarization Doppler weather radar." In 2016 8th IEEE International Conference on Communication Software and Networks (ICCSN). IEEE, 2016. http://dx.doi.org/10.1109/iccsn.2016.7586661.

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Hanuliaková, Radoslava, and Miriam Jarošová. "Meteorological radiolocator as a tool to improve meteorological information for aviation." In Práce a štúdie. University of Žilina, 2021. http://dx.doi.org/10.26552/pas.z.2021.1.08.

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The paper deals with meteorological radar as a tool to improve meteorological information for aviation. The first theoretical part is devoted to the history of weather forecasting and its gradual improvement. The part describes the current state of the problem in the Slovak Republic and in the world. The next part characterizes the meteorological radar, what it is used for and what is its essence. The following is the division of radars, characteristics of the radar network in Europe and the radar network in Slovakia. In the last theoretical part, attention was paid to the merged maps, their i
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Mak, Bart, and Bülent Düz. "Ship As a Wave Buoy: Estimating Relative Wave Direction From In-Service Ship Motion Measurements Using Machine Learning." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-96201.

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Abstract For operations at sea it is important to have a good estimate of the current local sea state. Often, sea state information comes from wave buoys or weather forecasts. Sometimes wave radars are used. These sources are not always available or reliable. Being able to reliably use ship motions to estimate sea state characteristics reduces the dependency on external and/or expensive sources. In this paper, we present a method to estimate sea state characteristics from time series of 6-DOF ship motions using machine learning. The available data consists of ship motion and wave scanning rada
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Junyent, Francesc, and V. Chandrasekar. "Weather Radar Network Design." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779899.

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Antonini, A., P. G. Dal Farra, F. Farruggio, S. Melani, and M. Pieri. "Improvements on the ARIES-C weather radar Tuscany network." In 2008 IEEE Radar Conference (RADAR). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4721094.

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