Matches in SemOpenAlex for { <https://semopenalex.org/work/W3141310273> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W3141310273 abstract "Quantile regression(QR) is proposed to examine the relationships between large-scale atmospheric variables and all parts of the distribution of daily precipitation amount at Beijing Station from 1960 to 2008. QR is also applied to evaluate the relationship between large-scale predictors and extreme precipitation(90th quantile) at 238 stations in northern China.Finally, QR is used to fit observed daily precipitation amounts for wet days at four sample stations. Results show that meridional wind and specific humidity at both 850 h Pa and 500 h Pa(V850, SH850, V500, and SH500) strongly affect all parts of the Beijing precipitation distribution during the wet season(April–September). Meridional wind, zonal wind, and specific humidity at only 850 h Pa(V850, U850, SH850) are significantly related to the precipitation distribution in the dry season(October–March). Impacts of these large-scale predictors on the daily precipitation amount with higher quantile become stronger, whereas their impact on light precipitation is negligible. In addition, SH850 has a strong relationship with wet-season extreme precipitation across the entire region, whereas the impacts of V850, V500, and SH500 are mainly in semi-arid and semi-humid areas. For the dry season, both SH850 and V850 are the major predictors of extreme precipitation in the entire region. Moreover, QR can satisfactorily simulate the daily precipitation amount at each station and for each season, if an optimum distribution family is selected. Therefore, QR is valuable for detecting the relationship between the large-scale predictors and the daily precipitation amount." @default.
- W3141310273 created "2021-04-13" @default.
- W3141310273 creator A5036497050 @default.
- W3141310273 date "2015-01-01" @default.
- W3141310273 modified "2023-09-23" @default.
- W3141310273 title "Using Quantile Regression to Detect Relationships between Large-scale Predictors and Local Precipitation over Northern China" @default.
- W3141310273 hasPublicationYear "2015" @default.
- W3141310273 type Work @default.
- W3141310273 sameAs 3141310273 @default.
- W3141310273 citedByCount "0" @default.
- W3141310273 crossrefType "journal-article" @default.
- W3141310273 hasAuthorship W3141310273A5036497050 @default.
- W3141310273 hasConcept C105795698 @default.
- W3141310273 hasConcept C107054158 @default.
- W3141310273 hasConcept C118671147 @default.
- W3141310273 hasConcept C127313418 @default.
- W3141310273 hasConcept C151420433 @default.
- W3141310273 hasConcept C153294291 @default.
- W3141310273 hasConcept C161067210 @default.
- W3141310273 hasConcept C166957645 @default.
- W3141310273 hasConcept C191935318 @default.
- W3141310273 hasConcept C205649164 @default.
- W3141310273 hasConcept C2778304055 @default.
- W3141310273 hasConcept C2778755073 @default.
- W3141310273 hasConcept C33923547 @default.
- W3141310273 hasConcept C39432304 @default.
- W3141310273 hasConcept C49204034 @default.
- W3141310273 hasConcept C58640448 @default.
- W3141310273 hasConcept C63817138 @default.
- W3141310273 hasConcept C91586092 @default.
- W3141310273 hasConceptScore W3141310273C105795698 @default.
- W3141310273 hasConceptScore W3141310273C107054158 @default.
- W3141310273 hasConceptScore W3141310273C118671147 @default.
- W3141310273 hasConceptScore W3141310273C127313418 @default.
- W3141310273 hasConceptScore W3141310273C151420433 @default.
- W3141310273 hasConceptScore W3141310273C153294291 @default.
- W3141310273 hasConceptScore W3141310273C161067210 @default.
- W3141310273 hasConceptScore W3141310273C166957645 @default.
- W3141310273 hasConceptScore W3141310273C191935318 @default.
- W3141310273 hasConceptScore W3141310273C205649164 @default.
- W3141310273 hasConceptScore W3141310273C2778304055 @default.
- W3141310273 hasConceptScore W3141310273C2778755073 @default.
- W3141310273 hasConceptScore W3141310273C33923547 @default.
- W3141310273 hasConceptScore W3141310273C39432304 @default.
- W3141310273 hasConceptScore W3141310273C49204034 @default.
- W3141310273 hasConceptScore W3141310273C58640448 @default.
- W3141310273 hasConceptScore W3141310273C63817138 @default.
- W3141310273 hasConceptScore W3141310273C91586092 @default.
- W3141310273 hasLocation W31413102731 @default.
- W3141310273 hasOpenAccess W3141310273 @default.
- W3141310273 hasPrimaryLocation W31413102731 @default.
- W3141310273 hasRelatedWork W1964095279 @default.
- W3141310273 hasRelatedWork W2012807120 @default.
- W3141310273 hasRelatedWork W2076173023 @default.
- W3141310273 hasRelatedWork W2098381406 @default.
- W3141310273 hasRelatedWork W2348780318 @default.
- W3141310273 hasRelatedWork W2352997535 @default.
- W3141310273 hasRelatedWork W2361168702 @default.
- W3141310273 hasRelatedWork W2362105407 @default.
- W3141310273 hasRelatedWork W2380258649 @default.
- W3141310273 hasRelatedWork W2391774453 @default.
- W3141310273 hasRelatedWork W2562329935 @default.
- W3141310273 hasRelatedWork W2625858012 @default.
- W3141310273 hasRelatedWork W2724657170 @default.
- W3141310273 hasRelatedWork W2859786338 @default.
- W3141310273 hasRelatedWork W2938174964 @default.
- W3141310273 hasRelatedWork W3007793824 @default.
- W3141310273 hasRelatedWork W3041307048 @default.
- W3141310273 hasRelatedWork W3130141382 @default.
- W3141310273 hasRelatedWork W3144599533 @default.
- W3141310273 hasRelatedWork W3200248700 @default.
- W3141310273 isParatext "false" @default.
- W3141310273 isRetracted "false" @default.
- W3141310273 magId "3141310273" @default.
- W3141310273 workType "article" @default.