Matches in SemOpenAlex for { <https://semopenalex.org/work/W2100022531> ?p ?o ?g. }
- W2100022531 abstract "[1] Quantitative precipitation estimation based on meteorological radar data potentially provides continuous, high-resolution, large-coverage data that are essential for meteorological and hydrologic analyses. While intense scientific efforts have focused on precipitation estimation in temperate climatic regimes, relatively few studies examined radar-based estimates in dry climatic regions. The paper examines radar-based rain depth estimation for rainfall periods (a series of successive rainy days) in Israel, where the climate ranges between Mediterranean to dry. Three radar-gauge adjustment methods are compared: a one-coefficient bulk adjustment, which simply removes the mean bias; a two-coefficient range adjustment based on a weighted regression (WR); and a four-coefficient adjustment based on a weighted multiple regression (WMR), which assumes a locally varied, nonisotropic correction factor. The WMR technique has been previously applied in the Alps of Europe. Adjustment coefficients have been derived for 28 rainfall periods using 59 independent gauges of a quality-checked training data set. The validation was based on an independent data set composed of gauges located in eleven 20 × 20 km2 validation areas, which are representative of different climate, topography and radar distance conditions. The WR and WMR methods were found preferable with a slight better performance of the latter. Furthermore, a novel approach has been adopted in this study, whereby radar estimates are considered useable if they provide information that is better than gauge-only estimates. The latter was derived by spatial interpolation of the gauges belonging to the training data set. Note that these gauges are outside the validation areas. As for the radar-adjusted estimates, gauge-derived estimates were assessed against gauge data in the validation areas. It was found that radar-based estimates are better for the validation areas at the dry climate regime. At distances larger than 100 km, the radar underestimation becomes too large in the two northern validation areas, while in the southern one radar data are still better than gauge interpolation. It is concluded that in ungauged areas of Israel it is preferable to use WMR-adjusted (or alternatively, simply WR-adjusted) radar echoes rather than the standard bulk adjustment method and for dry ungauged areas it is preferable over the conventional gauge-interpolated values derived from point measurements, which are outside the areas themselves. The WR and WMR adjustment methods provide useful rain depth estimates for rainfall periods for the examined areas but within the limitation stated above." @default.
- W2100022531 created "2016-06-24" @default.
- W2100022531 creator A5000892152 @default.
- W2100022531 creator A5059792657 @default.
- W2100022531 date "2007-10-20" @default.
- W2100022531 modified "2023-09-25" @default.
- W2100022531 title "Radar-based quantitative precipitation estimation over Mediterranean and dry climate regimes" @default.
- W2100022531 cites W130184397 @default.
- W2100022531 cites W1966307270 @default.
- W2100022531 cites W1976880734 @default.
- W2100022531 cites W1982803224 @default.
- W2100022531 cites W2002757003 @default.
- W2100022531 cites W2008026438 @default.
- W2100022531 cites W2010438871 @default.
- W2100022531 cites W2015674580 @default.
- W2100022531 cites W2033904783 @default.
- W2100022531 cites W2041177182 @default.
- W2100022531 cites W2044939257 @default.
- W2100022531 cites W2052346171 @default.
- W2100022531 cites W2061436185 @default.
- W2100022531 cites W2069364619 @default.
- W2100022531 cites W2078329130 @default.
- W2100022531 cites W2079427681 @default.
- W2100022531 cites W2081556096 @default.
- W2100022531 cites W2104915231 @default.
- W2100022531 cites W2106826803 @default.
- W2100022531 cites W2120224786 @default.
- W2100022531 cites W2137023185 @default.
- W2100022531 cites W2142140026 @default.
- W2100022531 cites W2173031829 @default.
- W2100022531 cites W2173596050 @default.
- W2100022531 cites W2174998367 @default.
- W2100022531 cites W2178244408 @default.
- W2100022531 cites W2324837854 @default.
- W2100022531 cites W3160528504 @default.
- W2100022531 doi "https://doi.org/10.1029/2006jd008206" @default.
- W2100022531 hasPublicationYear "2007" @default.
- W2100022531 type Work @default.
- W2100022531 sameAs 2100022531 @default.
- W2100022531 citedByCount "62" @default.
- W2100022531 countsByYear W21000225312012 @default.
- W2100022531 countsByYear W21000225312013 @default.
- W2100022531 countsByYear W21000225312014 @default.
- W2100022531 countsByYear W21000225312015 @default.
- W2100022531 countsByYear W21000225312017 @default.
- W2100022531 countsByYear W21000225312018 @default.
- W2100022531 countsByYear W21000225312019 @default.
- W2100022531 countsByYear W21000225312020 @default.
- W2100022531 countsByYear W21000225312021 @default.
- W2100022531 countsByYear W21000225312022 @default.
- W2100022531 countsByYear W21000225312023 @default.
- W2100022531 crossrefType "journal-article" @default.
- W2100022531 hasAuthorship W2100022531A5000892152 @default.
- W2100022531 hasAuthorship W2100022531A5059792657 @default.
- W2100022531 hasBestOaLocation W21000225311 @default.
- W2100022531 hasConcept C105795698 @default.
- W2100022531 hasConcept C107054158 @default.
- W2100022531 hasConcept C120961793 @default.
- W2100022531 hasConcept C121684516 @default.
- W2100022531 hasConcept C127313418 @default.
- W2100022531 hasConcept C137800194 @default.
- W2100022531 hasConcept C153294291 @default.
- W2100022531 hasConcept C18903297 @default.
- W2100022531 hasConcept C203332170 @default.
- W2100022531 hasConcept C205203396 @default.
- W2100022531 hasConcept C205649164 @default.
- W2100022531 hasConcept C2780092901 @default.
- W2100022531 hasConcept C33923547 @default.
- W2100022531 hasConcept C39432304 @default.
- W2100022531 hasConcept C41008148 @default.
- W2100022531 hasConcept C48921125 @default.
- W2100022531 hasConcept C49204034 @default.
- W2100022531 hasConcept C502989409 @default.
- W2100022531 hasConcept C554190296 @default.
- W2100022531 hasConcept C58489278 @default.
- W2100022531 hasConcept C75398719 @default.
- W2100022531 hasConcept C76155785 @default.
- W2100022531 hasConcept C81461190 @default.
- W2100022531 hasConcept C83546350 @default.
- W2100022531 hasConcept C86803240 @default.
- W2100022531 hasConceptScore W2100022531C105795698 @default.
- W2100022531 hasConceptScore W2100022531C107054158 @default.
- W2100022531 hasConceptScore W2100022531C120961793 @default.
- W2100022531 hasConceptScore W2100022531C121684516 @default.
- W2100022531 hasConceptScore W2100022531C127313418 @default.
- W2100022531 hasConceptScore W2100022531C137800194 @default.
- W2100022531 hasConceptScore W2100022531C153294291 @default.
- W2100022531 hasConceptScore W2100022531C18903297 @default.
- W2100022531 hasConceptScore W2100022531C203332170 @default.
- W2100022531 hasConceptScore W2100022531C205203396 @default.
- W2100022531 hasConceptScore W2100022531C205649164 @default.
- W2100022531 hasConceptScore W2100022531C2780092901 @default.
- W2100022531 hasConceptScore W2100022531C33923547 @default.
- W2100022531 hasConceptScore W2100022531C39432304 @default.
- W2100022531 hasConceptScore W2100022531C41008148 @default.
- W2100022531 hasConceptScore W2100022531C48921125 @default.
- W2100022531 hasConceptScore W2100022531C49204034 @default.
- W2100022531 hasConceptScore W2100022531C502989409 @default.
- W2100022531 hasConceptScore W2100022531C554190296 @default.
- W2100022531 hasConceptScore W2100022531C58489278 @default.