FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4322004917> ?p ?o ?g. }

• W4322004917 abstract "Quantitative estimation of precipitation (QPE) of high resolution, accurate and in real-time, increases the potential of weather radars for many applications, such as flash flood forecasting and hydropower production and distribution management. Using polarimetric variables from dual-polarization weather radars has already shown significant improvements in quantitative precipitation estimation in many countries with diverse weather. In Brazil, in the past ten years, we have seen an increase in dual-polarization weather radar coverage, mostly S-Band and some X-Band, concentrated in the southern parts of the country, an area prone to severe weather with high precipitation and lightning due to mesoscale convective systems. This region's significant economic activity is agriculture and energy production, accounting for more than 33% of the hydro energy generation used in the country. Therefore, the improvement of precipitation estimation is a necessary goal. However, the use of weather radar's QPE depends on calibration, good fit with rain gauges and distrometers, good data filtering, target&#8217;s distance from the radar, orography (i.e., relative to the topography), and signal propagation, as well as other factors.&#160; A multi-sensor integration approach of remotely sensed precipitation estimation using weather satellites and weather radar with rain gauges improves the accuracy of hydrological models compared to a model using only rain gauge data. A quantitative precipitation estimation algorithm called SIPREC (System for Integrated PRECipitation) has been used operationally for more than 15 years, combining data from different sources, such as weather radar, rain gauge, and satellite. Precipitation estimates are obtained through an automated precipitation classification scheme based on reflectivity structures. This approach aggregates data from rain gauges by interpolation while maintaining the spatial distribution of the radar or satellite measurement. Statistical results indicate that the method can reduce radar and satellite data errors. This method is an essential advantage in an operational environment since it does not require frequent processing to update the weights as in other known schemes. However, this approach does not solve problems such as uncertainties related to Z-R estimation, spatial variability, and the one-hour temporal resolution. To improve the SIPREC algorithm, we used machine learning classification and regression methods to address the problem of precipitation estimation using dual polarization variables and rain gauge. An enhanced satellite precipitation estimation using GOES-16 data also replaced the previous dataset, and a new quality control algorithm for the network of weather radars was also applied to the dataset. A performance evaluation study shows improvements in precipitation estimation, primarily when used in real-time in an operational environment. This paper presents the results of this evaluation, with applications in severe weather events with high precipitation in the area." @default.
• W4322004917 created "2023-02-26" @default.
• W4322004917 creator A5041890207 @default.
• W4322004917 creator A5044695347 @default.
• W4322004917 creator A5060058692 @default.
• W4322004917 creator A5062362560 @default.
• W4322004917 creator A5075463968 @default.
• W4322004917 creator A5091436123 @default.
• W4322004917 date "2023-05-15" @default.
• W4322004917 modified "2023-10-18" @default.
• W4322004917 title "Operational Quantitative Precipitation Estimation Algorithm in Southern Brazil - An Update Blending Dual Polarization Weather Radar Network with Raingauges and Satellite Data" @default.
• W4322004917 doi "https://doi.org/10.5194/egusphere-egu23-8456" @default.
• W4322004917 hasPublicationYear "2023" @default.
• W4322004917 type Work @default.
• W4322004917 citedByCount "0" @default.
• W4322004917 crossrefType "posted-content" @default.
• W4322004917 hasAuthorship W4322004917A5041890207 @default.
• W4322004917 hasAuthorship W4322004917A5044695347 @default.
• W4322004917 hasAuthorship W4322004917A5060058692 @default.
• W4322004917 hasAuthorship W4322004917A5062362560 @default.
• W4322004917 hasAuthorship W4322004917A5075463968 @default.
• W4322004917 hasAuthorship W4322004917A5091436123 @default.
• W4322004917 hasConcept C107054158 @default.
• W4322004917 hasConcept C120417685 @default.
• W4322004917 hasConcept C120961793 @default.
• W4322004917 hasConcept C127413603 @default.
• W4322004917 hasConcept C133204551 @default.
• W4322004917 hasConcept C140178040 @default.
• W4322004917 hasConcept C146978453 @default.
• W4322004917 hasConcept C147947694 @default.
• W4322004917 hasConcept C153294291 @default.
• W4322004917 hasConcept C166957645 @default.
• W4322004917 hasConcept C19269812 @default.
• W4322004917 hasConcept C194507410 @default.
• W4322004917 hasConcept C205649164 @default.
• W4322004917 hasConcept C39432304 @default.
• W4322004917 hasConcept C40382383 @default.
• W4322004917 hasConcept C41008148 @default.
• W4322004917 hasConcept C554190296 @default.
• W4322004917 hasConcept C62649853 @default.
• W4322004917 hasConcept C74256435 @default.
• W4322004917 hasConcept C75398719 @default.
• W4322004917 hasConcept C76155785 @default.
• W4322004917 hasConcept C92237259 @default.
• W4322004917 hasConceptScore W4322004917C107054158 @default.
• W4322004917 hasConceptScore W4322004917C120417685 @default.
• W4322004917 hasConceptScore W4322004917C120961793 @default.
• W4322004917 hasConceptScore W4322004917C127413603 @default.
• W4322004917 hasConceptScore W4322004917C133204551 @default.
• W4322004917 hasConceptScore W4322004917C140178040 @default.
• W4322004917 hasConceptScore W4322004917C146978453 @default.
• W4322004917 hasConceptScore W4322004917C147947694 @default.
• W4322004917 hasConceptScore W4322004917C153294291 @default.
• W4322004917 hasConceptScore W4322004917C166957645 @default.
• W4322004917 hasConceptScore W4322004917C19269812 @default.
• W4322004917 hasConceptScore W4322004917C194507410 @default.
• W4322004917 hasConceptScore W4322004917C205649164 @default.
• W4322004917 hasConceptScore W4322004917C39432304 @default.
• W4322004917 hasConceptScore W4322004917C40382383 @default.
• W4322004917 hasConceptScore W4322004917C41008148 @default.
• W4322004917 hasConceptScore W4322004917C554190296 @default.
• W4322004917 hasConceptScore W4322004917C62649853 @default.
• W4322004917 hasConceptScore W4322004917C74256435 @default.
• W4322004917 hasConceptScore W4322004917C75398719 @default.
• W4322004917 hasConceptScore W4322004917C76155785 @default.
• W4322004917 hasConceptScore W4322004917C92237259 @default.
• W4322004917 hasLocation W43220049171 @default.
• W4322004917 hasOpenAccess W4322004917 @default.
• W4322004917 hasPrimaryLocation W43220049171 @default.
• W4322004917 hasRelatedWork W188653796 @default.
• W4322004917 hasRelatedWork W2056439781 @default.
• W4322004917 hasRelatedWork W2077630572 @default.
• W4322004917 hasRelatedWork W2085731157 @default.
• W4322004917 hasRelatedWork W2146207877 @default.
• W4322004917 hasRelatedWork W2311407058 @default.
• W4322004917 hasRelatedWork W2891615880 @default.
• W4322004917 hasRelatedWork W2949655323 @default.
• W4322004917 hasRelatedWork W4313431925 @default.
• W4322004917 hasRelatedWork W4322004917 @default.
• W4322004917 isParatext "false" @default.
• W4322004917 isRetracted "false" @default.
• W4322004917 workType "article" @default.