FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2034630107> ?p ?o ?g. }

• W2034630107 endingPage "7434" @default.
• W2034630107 startingPage "7418" @default.
• W2034630107 abstract "We have developed a neural network technique for retrieving accurate 12.5-km resolution wind speeds from Ku-band scatterometer measurements in tropical cyclone conditions including typical rain events in such storms. The method was shown to retrieve accurate wind speeds up to 40 m/s when compared with aircraft reconnaissance data, including GPS dropwindsondes and Stepped-Frequency Microwave Radiometer surface wind speed measurements, and when compared to global best track maximum wind speeds. Wind directions were unchanged from the current (version 3) Jet Propulsion Laboratory (JPL) global wind vector product. The technique removes positive biases with respect to best track winds in the developing phase of tropical cyclones that occurred in the nominal (version 2) JPL QuikSCAT product. The new technique also reduces negative biases with respect to best track wind speeds that occurred in the nominal product (both versions 2 and 3) during the most extreme period of the lifetime of intense storms. The wind regime with the most notable improvement is 20-40 m/s (40-80 kn), with more modest improvement for higher winds and the improvement at lower winds comparable to that achieved previously by the version 3 JPL global rain-corrected product. The net effect of all the wind speed improvements is a much better measurement of storm intensity over time in the new product than what has been previously available. When compared with speed data from aircraft flights in Atlantic hurricanes, the new product exhibited a 1-2-m/s positive overall bias and a 3-m/s mean absolute error. The random error and systematic positive bias in the new scatterometer wind product is similar to that of the Hurricane Research Division H*WIND analyses when aircraft data are available for assimilation. This similarity may be explained by the fact that H*WIND data are used as ground truth to fit the coefficients used by the new technique to map radar measurements to wind speed. The fact that H*WIND was designed to match maximum winds while preserving radial symmetry may explain the overall positive biases that we observe in both H*WIND and the new scatterometer wind product which compared to aircraft reconnaissance data. The new scatterometer product could also be inheriting systematic biases in the presence of rain from H*WIND. Under the most extreme rain conditions, the radar signal from the surface can be lost. In such cases, the technique makes use of measurements in the 87.5-km region comprising the 7 $times$ 7 neighboring cells around the target 12.5-km wind vector cell. In so doing, we sacrifice resolution in cases where the highest resolution region has no useful measurements. Even so, the most extreme rain conditions can result in reduced accuracy. The new technique has been used to retrieve wind fields for every tropical cyclone of tropical storm force or above that has been observed by QuikSCAT during the period of time from October 1999 to November 2009. The resulting data set has been made available online for use by the tropical cyclone research community." @default.
• W2034630107 created "2016-06-24" @default.
• W2034630107 creator A5023884656 @default.
• W2034630107 creator A5032987607 @default.
• W2034630107 creator A5038281243 @default.
• W2034630107 creator A5055524341 @default.
• W2034630107 creator A5061867139 @default.
• W2034630107 creator A5070284190 @default.
• W2034630107 creator A5088635952 @default.
• W2034630107 date "2014-11-01" @default.
• W2034630107 modified "2023-10-16" @default.
• W2034630107 title "Optimized Tropical Cyclone Winds From QuikSCAT: A Neural Network Approach" @default.
• W2034630107 cites W1491237211 @default.
• W2034630107 cites W1498436455 @default.
• W2034630107 cites W1542533195 @default.
• W2034630107 cites W1968710492 @default.
• W2034630107 cites W1968783543 @default.
• W2034630107 cites W1982639428 @default.
• W2034630107 cites W1982803992 @default.
• W2034630107 cites W1984701266 @default.
• W2034630107 cites W1985041453 @default.
• W2034630107 cites W1986278258 @default.
• W2034630107 cites W1998099504 @default.
• W2034630107 cites W1998672188 @default.
• W2034630107 cites W1998824063 @default.
• W2034630107 cites W2012392621 @default.
• W2034630107 cites W2016437149 @default.
• W2034630107 cites W2019999822 @default.
• W2034630107 cites W2026943567 @default.
• W2034630107 cites W2054601869 @default.
• W2034630107 cites W2056478327 @default.
• W2034630107 cites W2056743318 @default.
• W2034630107 cites W2061320736 @default.
• W2034630107 cites W2061419471 @default.
• W2034630107 cites W2066495170 @default.
• W2034630107 cites W2067854543 @default.
• W2034630107 cites W2070850297 @default.
• W2034630107 cites W2076977109 @default.
• W2034630107 cites W2077635557 @default.
• W2034630107 cites W2087060808 @default.
• W2034630107 cites W2098981773 @default.
• W2034630107 cites W2103496339 @default.
• W2034630107 cites W2105434047 @default.
• W2034630107 cites W2107982224 @default.
• W2034630107 cites W2112278239 @default.
• W2034630107 cites W2118253779 @default.
• W2034630107 cites W2122950446 @default.
• W2034630107 cites W2123337604 @default.
• W2034630107 cites W2125767514 @default.
• W2034630107 cites W2126231593 @default.
• W2034630107 cites W2126692291 @default.
• W2034630107 cites W2128574079 @default.
• W2034630107 cites W2135064467 @default.
• W2034630107 cites W2138836373 @default.
• W2034630107 cites W2142247079 @default.
• W2034630107 cites W2158340651 @default.
• W2034630107 cites W2166135556 @default.
• W2034630107 cites W2167905626 @default.
• W2034630107 cites W4248656856 @default.
• W2034630107 doi "https://doi.org/10.1109/tgrs.2014.2312333" @default.
• W2034630107 hasPublicationYear "2014" @default.
• W2034630107 type Work @default.
• W2034630107 sameAs 2034630107 @default.
• W2034630107 citedByCount "48" @default.
• W2034630107 countsByYear W20346301072014 @default.
• W2034630107 countsByYear W20346301072016 @default.
• W2034630107 countsByYear W20346301072017 @default.
• W2034630107 countsByYear W20346301072018 @default.
• W2034630107 countsByYear W20346301072019 @default.
• W2034630107 countsByYear W20346301072020 @default.
• W2034630107 countsByYear W20346301072021 @default.
• W2034630107 countsByYear W20346301072022 @default.
• W2034630107 countsByYear W20346301072023 @default.
• W2034630107 crossrefType "journal-article" @default.
• W2034630107 hasAuthorship W2034630107A5023884656 @default.
• W2034630107 hasAuthorship W2034630107A5032987607 @default.
• W2034630107 hasAuthorship W2034630107A5038281243 @default.
• W2034630107 hasAuthorship W2034630107A5055524341 @default.
• W2034630107 hasAuthorship W2034630107A5061867139 @default.
• W2034630107 hasAuthorship W2034630107A5070284190 @default.
• W2034630107 hasAuthorship W2034630107A5088635952 @default.
• W2034630107 hasConcept C105306849 @default.
• W2034630107 hasConcept C118536763 @default.
• W2034630107 hasConcept C121332964 @default.
• W2034630107 hasConcept C127313418 @default.
• W2034630107 hasConcept C135558025 @default.
• W2034630107 hasConcept C153294291 @default.
• W2034630107 hasConcept C161067210 @default.
• W2034630107 hasConcept C2776212561 @default.
• W2034630107 hasConcept C2777864850 @default.
• W2034630107 hasConcept C29141058 @default.
• W2034630107 hasConcept C39432304 @default.
• W2034630107 hasConcept C41008148 @default.
• W2034630107 hasConcept C42935608 @default.
• W2034630107 hasConcept C62649853 @default.
• W2034630107 hasConcept C82313973 @default.
• W2034630107 hasConcept C9390403 @default.
• W2034630107 hasConceptScore W2034630107C105306849 @default.

• next