FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2016753622> ?p ?o ?g. }

• W2016753622 endingPage "495" @default.
• W2016753622 startingPage "495" @default.
• W2016753622 abstract "Aerosol radiative forcing over the industrial period has remained the largest forcing uncertainty through all IPCC assessments since 1996. Despite the importance of this uncertainty for our understanding of past and future climate change, very little attention is given to the problem of uncertainty reduction in its own right, mainly because most uncertainty analysis approaches are not appropriate to computationally expensive global models. Here we show how a comprehensive understanding of global aerosol model parametric uncertainty can be obtained by using emulators. The approach enables a Monte Carlo sampling of the model uncertainty space based on a manageable number of simulations. This allows full probability density functions of model outputs to be generated from which the uncertainty and its causes can be diagnosed using variance decomposition. We apply this approach to global concentrations of particles larger than 3 and 50 nm diameter (N3 and N50) to produce a ranked list of twenty-eight processes and emissions that control the uncertainty. The results show that the uncertainty in N50 is much more strongly affected by emissions and processes that control the availability of gas phase H2SO4 than by uncertainties in the nucleation rate itself, which cause generally less than 10% uncertainty in N50 in July. Secondary organic aerosol production is assumed to be very uncertain (5–360 Tg a−1 for biogenic emissions) but the effect on global N3 uncertainty is <3% except in a few hotspots, and generally <2% for N50. A complete understanding of the model uncertainty combined with global observations can be used to determine plausible and implausible parts of parameter space as well as to identify model structural weaknesses. In this direction, a preliminary comparison of the model ensemble with observations at Hyytiala, Finland, suggests that an organic-mediated boundary layer nucleation mechanism would help to optimise the behaviour of the model." @default.
• W2016753622 created "2016-06-24" @default.
• W2016753622 creator A5033471603 @default.
• W2016753622 creator A5058971309 @default.
• W2016753622 creator A5061310552 @default.
• W2016753622 creator A5076728700 @default.
• W2016753622 creator A5080126581 @default.
• W2016753622 date "2013-01-01" @default.
• W2016753622 modified "2023-09-23" @default.
• W2016753622 title "The magnitude and sources of uncertainty in global aerosol" @default.
• W2016753622 cites W1964406071 @default.
• W2016753622 cites W2011109821 @default.
• W2016753622 cites W2013350969 @default.
• W2016753622 cites W2029222580 @default.
• W2016753622 cites W2062075925 @default.
• W2016753622 cites W2078592413 @default.
• W2016753622 cites W2090755408 @default.
• W2016753622 cites W2108218364 @default.
• W2016753622 cites W2110123713 @default.
• W2016753622 cites W2114829375 @default.
• W2016753622 cites W2118276286 @default.
• W2016753622 cites W2125107816 @default.
• W2016753622 cites W2127722963 @default.
• W2016753622 cites W2128175515 @default.
• W2016753622 cites W2129433315 @default.
• W2016753622 cites W2143974588 @default.
• W2016753622 cites W2145318668 @default.
• W2016753622 cites W2149129262 @default.
• W2016753622 cites W2149761878 @default.
• W2016753622 cites W2152172226 @default.
• W2016753622 cites W2154836345 @default.
• W2016753622 cites W2156633761 @default.
• W2016753622 cites W2158718894 @default.
• W2016753622 cites W2165655513 @default.
• W2016753622 cites W2166882786 @default.
• W2016753622 cites W2318890869 @default.
• W2016753622 cites W4241793634 @default.
• W2016753622 cites W4245329459 @default.
• W2016753622 doi "https://doi.org/10.1039/c3fd00043e" @default.
• W2016753622 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/24601019" @default.
• W2016753622 hasPublicationYear "2013" @default.
• W2016753622 type Work @default.
• W2016753622 sameAs 2016753622 @default.
• W2016753622 citedByCount "23" @default.
• W2016753622 countsByYear W20167536222013 @default.
• W2016753622 countsByYear W20167536222014 @default.
• W2016753622 countsByYear W20167536222015 @default.
• W2016753622 countsByYear W20167536222016 @default.
• W2016753622 countsByYear W20167536222017 @default.
• W2016753622 countsByYear W20167536222018 @default.
• W2016753622 countsByYear W20167536222019 @default.
• W2016753622 countsByYear W20167536222020 @default.
• W2016753622 countsByYear W20167536222021 @default.
• W2016753622 countsByYear W20167536222023 @default.
• W2016753622 crossrefType "journal-article" @default.
• W2016753622 hasAuthorship W2016753622A5033471603 @default.
• W2016753622 hasAuthorship W2016753622A5058971309 @default.
• W2016753622 hasAuthorship W2016753622A5061310552 @default.
• W2016753622 hasAuthorship W2016753622A5076728700 @default.
• W2016753622 hasAuthorship W2016753622A5080126581 @default.
• W2016753622 hasConcept C105795698 @default.
• W2016753622 hasConcept C117251300 @default.
• W2016753622 hasConcept C121332964 @default.
• W2016753622 hasConcept C121955636 @default.
• W2016753622 hasConcept C123614077 @default.
• W2016753622 hasConcept C144133560 @default.
• W2016753622 hasConcept C153294291 @default.
• W2016753622 hasConcept C177803969 @default.
• W2016753622 hasConcept C19499675 @default.
• W2016753622 hasConcept C196083921 @default.
• W2016753622 hasConcept C197115733 @default.
• W2016753622 hasConcept C2779345167 @default.
• W2016753622 hasConcept C32230216 @default.
• W2016753622 hasConcept C33923547 @default.
• W2016753622 hasConcept C39432304 @default.
• W2016753622 hasConcept C91586092 @default.
• W2016753622 hasConcept C99578197 @default.
• W2016753622 hasConceptScore W2016753622C105795698 @default.
• W2016753622 hasConceptScore W2016753622C117251300 @default.
• W2016753622 hasConceptScore W2016753622C121332964 @default.
• W2016753622 hasConceptScore W2016753622C121955636 @default.
• W2016753622 hasConceptScore W2016753622C123614077 @default.
• W2016753622 hasConceptScore W2016753622C144133560 @default.
• W2016753622 hasConceptScore W2016753622C153294291 @default.
• W2016753622 hasConceptScore W2016753622C177803969 @default.
• W2016753622 hasConceptScore W2016753622C19499675 @default.
• W2016753622 hasConceptScore W2016753622C196083921 @default.
• W2016753622 hasConceptScore W2016753622C197115733 @default.
• W2016753622 hasConceptScore W2016753622C2779345167 @default.
• W2016753622 hasConceptScore W2016753622C32230216 @default.
• W2016753622 hasConceptScore W2016753622C33923547 @default.
• W2016753622 hasConceptScore W2016753622C39432304 @default.
• W2016753622 hasConceptScore W2016753622C91586092 @default.
• W2016753622 hasConceptScore W2016753622C99578197 @default.
• W2016753622 hasLocation W20167536221 @default.
• W2016753622 hasLocation W20167536222 @default.
• W2016753622 hasOpenAccess W2016753622 @default.
• W2016753622 hasPrimaryLocation W20167536221 @default.

• next