المؤلفون: Abhiru Aryal, Ajay Kalra

المصدر: River, Vol 2, Iss 3, Pp 371-383 (2023)

مصطلحات موضوعية: 1D‐flood modeling, flood risk map, LID, NEXRAD, PCSWMM, Oceanography, GC1-1581, River, lake, and water-supply engineering (General), TC401-506

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2750-4867Test

الوصول الحر: https://doaj.org/article/3be373e15b654ee4a42240148bfd7c83Test

المؤلفون: P. E. Saide, M. Krishna, X. Ye, L. H. Thapa, F. Turney, C. Howes, C. C. Schmidt

المصدر: Geophysical Research Letters, Vol 50, Iss 21, Pp n/a-n/a (2023)

مصطلحات موضوعية: weather radar, NEXRAD, wildfire, fire radiative power, fire radiative energy, biomass burning emissions, Geophysics. Cosmic physics, QC801-809

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/0094-8276Test; https://doaj.org/toc/1944-8007Test

الوصول الحر: https://doaj.org/article/94727f28dca7458595991bafdba35549Test

المؤلفون: Junkai Liu, Zhaoxia Pu, Wen-Chau Lee, Zhiqiu Gao

المصدر: Remote Sensing, Vol 16, Iss 8, p 1351 (2024)

مصطلحات موضوعية: NEXRAD observations, radar data assimilation, hurricane landfall, WRF model, Science

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/2072-4292/16/8/1351Test; https://doaj.org/toc/2072-4292Test

الوصول الحر: https://doaj.org/article/907e389f35ec42869cfc9c251d513101Test

المؤلفون: Antía Paz, Ramon Padullés, Estel Cardellach

المصدر: Remote Sensing, Vol 16, Iss 7, p 1118 (2024)

مصطلحات موضوعية: Global Navigation Satellite Systems (GNSS), Polarimetric Radio Occultations (PRO), Next Generation Weather Radars (NEXRAD), Science

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/2072-4292/16/7/1118Test; https://doaj.org/toc/2072-4292Test

الوصول الحر: https://doaj.org/article/ab6368bc93744fd9b9862680277afab9Test

المؤلفون: Kasra Shamsaei, Timothy W. Juliano, Matthew Roberts, Hamed Ebrahimian, Neil P. Lareau, Eric Rowell, Branko Kosovic

المصدر: Fire; Volume 6; Issue 7; Pages: 264

مصطلحات موضوعية: WRF-fire, canopy, crown fire, coupled fire-atmosphere simulation, mass loss, burning rate, Caldor Fire, Camp Fire, heat distribution, NEXRAD

جغرافية الموضوع: agris

وصف الملف: application/pdf

العلاقة: https://dx.doi.org/10.3390/fire6070264Test

الإتاحة: https://doi.org/10.3390/fire6070264Test

المؤلفون: Jungho Kim, Evelyn Shu, Kelvin Lai, Mike Amodeo, Jeremy Porter, Ed Kearns

المصدر: Journal of Hydrology: Regional Studies, Vol 44, Iss , Pp 101276- (2022)

مصطلحات موضوعية: Flood, Extreme precipitation, Precipitation frequency estimate, NOAA Atlas, NEXRAD Stage-IV, Radar-based IDF curve, Physical geography, GB3-5030, Geology, QE1-996.5

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S2214581822002890Test; https://doaj.org/toc/2214-5818Test

الوصول الحر: https://doaj.org/article/97c7ac167f50478985704df4f83bae70Test

المؤلفون: Colin, Aurélien, Peureux, Charles, Husson, Romain, Fablet, Ronan, Tandeo, Pierre

المساهمون: Equipe Observations Signal & Environnement (Lab-STICC_OSE), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT), Département Mathematical and Electrical Engineering (IMT Atlantique - MEE), IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Collecte Localisation Satellites (CLS), ANR-19-CHIA-0016,OceaniX,Physics-Informed AI for Observation-driven Ocean AnalytiX(2019)

المصدر: IGARSS 2022: IEEE International Geoscience and Remote Sensing Symposium ; IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium ; https://imt-atlantique.hal.science/hal-03874778Test ; IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 2022, Kuala Lumpur, Malaysia. pp.307-309, ⟨10.1109/IGARSS46834.2022.9884881⟩

مصطلحات موضوعية: SAR, Sentinel-1, NEXRAD, ocean, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [SDE]Environmental Sciences

جغرافية الموضوع: Kuala Lumpur, Malaysia

العلاقة: hal-03874778; https://imt-atlantique.hal.science/hal-03874778Test; https://imt-atlantique.hal.science/hal-03874778/documentTest; https://imt-atlantique.hal.science/hal-03874778/file/IGARSS2022_acolin.pdfTest

الإتاحة: https://doi.org/10.1109/IGARSS46834.2022.9884881Test
https://imt-atlantique.hal.science/hal-03874778Test
https://imt-atlantique.hal.science/hal-03874778/documentTest
https://imt-atlantique.hal.science/hal-03874778/file/IGARSS2022_acolin.pdfTest

المؤلفون: Acosta-Coll, Melisa, Morales, Abel, Zamora-Musa, Ronald, Butt, Shariq Aziz

المصدر: https://www-webofscience-com.ezproxy.cuc.edu.co/wos/woscc/full-record/WOS:000839716900001Test.

مصطلحات موضوعية: Cross-evaluation, Reflectivity, NEXRAD, GPM, Hurricane, Ground validation system, Ground radar

وصف الملف: 21 páginas; application/pdf

العلاقة: Sensors; 1. de Beurs, K.M.; McThompson, N.S.; Owsley, B.C.; Henebry, G.M. Hurricane damage detection on four major Caribbean islands. Remote Sens. Environ. 2019, 229, 1–13. [CrossRef]; 2. NSF and The University of Rhode Island. Rainfall and Inland Flooding. 2010. Available online: http://hurricanescience.orgTest/ society/impacts/rainfallandinlandflooding/ (accessed on 20 October 2021).; 3. Ortega-Gonzalez, L.; Acosta-Coll, M.; Piñeres-Espitia, G.; Butt, S.A. Communication protocols evaluation for a wireless rainfall monitoring network in an urban area. Heliyon 2021, 18, 7. [CrossRef] [PubMed]; 4. Ren, Y.; Zhang, J.; Guimond, S.; Wang, X. Hurricane Boundary Layer Height Relative to Storm Motion from GPS Dropsonde Composites. Atmposphere 2019, 10, 339. [CrossRef]; 5. Trepanier, J. North Atlantic Hurricane Winds in Warmer than Normal Seas. Atmposphere 2020, 11, 293. [CrossRef]; 6. Yang, K.; Davidson, R.A.; Blanton, B.; Colle, B.; Dresback, K.; Kolar, R.; Nozick, L.K.; Trivedi, J.; Wachtendorf, T. Hurricane evacuations in the face of uncertainty: Use of integrated models to support robust, adaptive, and repeated decision-making. Int. J. Disaster Risk Reduct. 2019, 36, 101093. [CrossRef]; 7. Luitel, B.; Villarini, G.; Vecchi, G. Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones. J. Hydrol. 2018, 556, 1026–1037. [CrossRef]; 8. Ramirez-Cerpa, E.; Acosta-Coll, M.; Velez-Zapata, J. Analysis of the climatic conditions for short-term precipitation in urban areas: A case study Barranquilla, Colombia. Idesia 2017, 35, 2. [CrossRef]; 9. Neeck, S.P.; Kakar, R.K.; Azarbarzin, A.A.; Hou, A.Y. Global Precipitation Measurement (GPM) launch, commissioning, and early operations. Sens. Syst. Next-Gener. Satell. XVIII 2014, 9241, 31–44. [CrossRef]; 11. Furukawa, K.; Yamamoto, K.; Kubota, T.; Oki, R.; Iguchi, T. Current status of the Dual-frequency precipitation Radar on the Global Precipitation Measurement core spacecraft and scan pattern change test operations results. Remote Sens. Atmos. Clouds Precip. VII 2018, 10776, 1077602. [CrossRef]; 12. Hou, A.Y.; Kakar, R.K.; Neeck, S.; Azarbarzin, A.A.; Kummerow, C.D.; Kojima, M.; Oki, R.; Nakamura, K.; Iguchi, T. The Global Precipitation Measurement Mission; American Metereological Society: Boston, MA, USA, 2014. Available online: https: //pdfs.semanticscholar.org/c2c9/e1aca77adaf560d24f08ca72e58b4484e66d.pdf (accessed on 9 August 2021).; 13. Skofronick-Jackson, G.; Petersen, W.A.; Berg, W.; Kidd, C.; Stocker, E.F.; Kirschbaum, D.B.; Kakar, R.; Braun, S.A.; Huffman, G.J.; Iguchi, T.; et al. The Global Precipitation Measurement (GPM) Mission for Science and Society. Bull. Am. Meteorol. Soc. 2017, 98, 1679–1695. [CrossRef] [PubMed]; 14. Baldini, L.; Roberto, N.; Montopoli, M.; Adirosi, E. Ground-Based Weather Radar to Investigate Thunderstorms. In Remote Sensing of Clouds and Precipitation; Springer: Cham, Switzerland, 2018; pp. 113–135. [CrossRef]; 15. Acosta-Coll, M.; Ballester-Merelo, F.; de la Hoz-Franco, E.; Martinez-Peiró, M. Real-time early warning system design for pluvial flash floods—A review. Sensors 2018, 18, 2255. [CrossRef] [PubMed]; 16. Keem, M.; Seo, B.C.; Krajewski, W.F.; Morris, K.R. Intercomparison of Reflectivity Measurements between GPM DPR and NEXRAD Radars. Atmos. Res. 2019, 226, 49–65. [CrossRef]; 17. Biswas, S.; Chandrasekar, V. Cross-Validation of Observations between the GPM Dual-Frequency Precipitation Radar and Ground Based Dual-Polarization Radars. Remote Sens. 2018, 10, 1773. [CrossRef]; 18. Kim, K.; Bui, L. Learning from Hurricane Maria: Island ports and supply chain resilience. Int. J. Disaster Risk Reduct. 2019, 39, 101244. [CrossRef]; 19. López-Marrero, T.; Castro-Rivera, A. Let’s not forget about non-land-falling cyclones: Tendencies and impacts in Puerto Rico. Nat. Hazards 2019, 98, 809–815. [CrossRef]; 20. Bacopoulos, P. Extreme low and high waters due to a large and powerful tropical cyclone: Hurricane Irma (2017). Nat. Hazards 2019, 98, 3. [CrossRef]; 21. Benach, J.; Diaz, M.R.; Muñoz, N.J.; Martinez-Herera, E.; Pericas, J.M. What the Puerto Rican hurricanes make visible: Chronicle of a public health disaster foretold. Soc. Sci. Med. 2019, 238, 112367. [CrossRef] [PubMed]; 22. Colom, J.G.; Cruz-Pol, S.; Pablos, G.; Córdoba, M.F.; Castellanos, W.; Acosta, M.; Ortiz, J.A.; de Jesús, B.; Trabal, J. Uprm Weather Radars at the Central American and Caribbean Games at Mayagüez 2010. IEEE Geosci. Remote Sens. Lett. 2010, 156, 34–39.; 23. Zhong, L.; Yang, R.; Wen, Y.; Chen, L.; Gou, Y.; Li, R.; Zhou, Q.; Hong, Y. Cross-evaluation of reflectivity from the space-borne precipitation radar and multi-type ground-based weather radar network in China. Atmos. Res. 2017, 196, 200–210. [CrossRef]; 24. Morris, K.R.; Greenbelt, S.; Schwaller, M.R. Sensitivity of Spaceborne and Ground Radar Comparison Results to Data Analysis Methods and Constraints. In Proceedings of the 35th Conference on Radar Meteorology, Pittsburgh, PA, USA, 26–30 September 2011. Available online: https://ams.confex.com/ams/35Radar/webprogram/Paper191729.htmlTest (accessed on 5 July 2021).; 25. Biswas, S.K.; Chandrasekar, V. Cross validation of observations from GPM dual-frequnecy precipitation radar with S-band ground radar measurents over the Dallas—Fort worth region. In Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 23–28 July 2017; pp. 2085–2088. [CrossRef]; 26. Arias, I.; Chandrasekar, V. Cross Validation of GPM and Ground-Based Radar in Latin America and the Caribbean. In Proceedings of the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22–27 July 2018; pp. 3891–3893. [CrossRef]; 27. Goddard Space Flight Center. Global Precipitation Mission (GPM) Ground Validation System Validation Network Data Product User’s Guide. 2013. Available online: https://gpm.nasa.gov/sites/default/files/document_files/Val_Network_Users_Guide_v4Test .1.pdf (accessed on 9 June 2021).; 28. National Hurricane Center. Hurrican Beryl. Available online: https://www.nhc.noaa.gov/data/tcr/AL022018_Beryl.pdfTest (accessed on 6 June 2021).; 29. National Weather Service. Hurricane Dorian. 2019. Available online: https://www.weather.gov/mhx/Dorian2019Test (accessed on 6 June 2021).; 30. National Weather Service. Tropical Storm Karen. 2019. Available online: https://www.weather.gov/sju/karen2019Test (accessed on 6 June 2021).; 21; 15; 22; Acosta-Coll, M.; Morales, A.; Zamora-Musa, R.; Butt, S.A. Cross-Evaluation of Reflectivity from NEXRAD and Global Precipitation Mission during Extreme Weather Events. Sensors 2022, 22, 5773. https://doi.org/10.3390/s22155773Test; https://hdl.handle.net/11323/10887Test; Corporación Universidad de la Costa; REDICUC - Repositorio CUC; https://repositorio.cuc.edu.coTest

الإتاحة: https://doi.org/10.3390/s22155773Test
https://hdl.handle.net/11323/10887Test
https://repositorio.cuc.edu.coTest

المؤلفون: Melisa Acosta-Coll, Abel Morales, Ronald Zamora-Musa, Shariq Aziz Butt

المصدر: Sensors; Volume 22; Issue 15; Pages: 5773

مصطلحات موضوعية: cross-evaluation, reflectivity, NEXRAD, GPM, hurricane, ground validation system, ground radar

وصف الملف: application/pdf

العلاقة: Remote Sensors; https://dx.doi.org/10.3390/s22155773Test

الإتاحة: https://doi.org/10.3390/s22155773Test

المؤلفون: Xiaohe Yu, David J. Lary, Christopher S. Simmons, Lakitha O. H. Wijeratne

المصدر: Remote Sensing; Volume 14; Issue 3; Pages: 495

مصطلحات موضوعية: PM 2.5, machine learning, ensemble method, weather radar, NEXRAD, GOES-16 AOD, ECMWF

جغرافية الموضوع: agris

وصف الملف: application/pdf

العلاقة: https://dx.doi.org/10.3390/rs14030495Test

الإتاحة: https://doi.org/10.3390/rs14030495Test