FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1982103134> ?p ?o ?g. }

• W1982103134 endingPage "81" @default.
• W1982103134 startingPage "71" @default.
• W1982103134 abstract "CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 34:71-81 (2007) - doi:10.3354/cr034071 Utility of dynamical seasonal forecasts in predicting crop yield Mikhail A. Semenov1,*, Francisco J. Doblas-Reyes2 1Biomathematics & Bioinformatics, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK 2ECMWF (European Centre for Medium-range Weather Forecasting), Shinfield Park, Reading RG2 9AX, UK *Email: mikhail.semenov@bbsrc.ac.uk ABSTRACT: Advance predictions of crop yield using crop simulation models require daily weather input for the whole growing season. Seasonal forecasts, based on coupled ocean–atmosphere climate models, are now available up to 6 mo in advance from a number of operational meteorological centres around the world. Seasonal forecasts are not directly suitable for crop simulations, because of model biases and mismatch of spatial and temporal scales. However, it is possible to utilise seasonal forecasts for yield predictions by constructing site-specific daily weather using a stochastic weather generator linked to seasonal forecasts. In our study, we use the LARS-WG weather generator and a subset of predictions by DEMETER (Development of a European Multimodel Ensemble system for seasonal to inTERannual climate prediction), i.e. seasonal ensemble hindcasts from the general circulation model (GCM) of ECMWF (European Centre for Medium-range Weather Forecasting) for 1980–2001. To assess the value of seasonal forecasts, 2 sets of scenarios were created, one based on seasonal forecasts and the other on historical climatology. The Sirius wheat simulation model was used to compute distributions of wheat yield at 2 locations in Europe and New Zealand. The main conclusion is that the use of dynamical seasonal forecasts at selected sites has not improved yield predictions compared with the approach based on historical climatology. The likely reason is that for dynamic seasonal forecasts, the skill score for temperature and precipitation is generally low for latitudes higher than 30° for northern and southern hemispheres, and our test locations are at 47.6°N and 43.6°S. KEY WORDS: ECMWF GCM · General circulation model · Stochastic weather generator · LARS-WG · Wheat simulation model · Sirius · Probabilistic ensemble Full text in pdf format PreviousExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 34, No. 1. Online publication date: June 14, 2007 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2007 Inter-Research." @default.
• W1982103134 created "2016-06-24" @default.
• W1982103134 creator A5077181632 @default.
• W1982103134 creator A5091017953 @default.
• W1982103134 date "2007-06-14" @default.
• W1982103134 modified "2023-09-30" @default.
• W1982103134 title "Utility of dynamical seasonal forecasts in predicting crop yield" @default.
• W1982103134 cites W1580095257 @default.
• W1982103134 cites W1966807578 @default.
• W1982103134 cites W1977219044 @default.
• W1982103134 cites W1985114715 @default.
• W1982103134 cites W1986797382 @default.
• W1982103134 cites W1999733221 @default.
• W1982103134 cites W2019826292 @default.
• W1982103134 cites W2021470958 @default.
• W1982103134 cites W2024360954 @default.
• W1982103134 cites W2028671789 @default.
• W1982103134 cites W2029956817 @default.
• W1982103134 cites W2042260153 @default.
• W1982103134 cites W2045123123 @default.
• W1982103134 cites W2048855290 @default.
• W1982103134 cites W2055578622 @default.
• W1982103134 cites W2062252084 @default.
• W1982103134 cites W2063383699 @default.
• W1982103134 cites W2066130707 @default.
• W1982103134 cites W2073968193 @default.
• W1982103134 cites W2111115198 @default.
• W1982103134 cites W2121183894 @default.
• W1982103134 cites W2147087715 @default.
• W1982103134 cites W2147747979 @default.
• W1982103134 cites W2147983357 @default.
• W1982103134 cites W2150285422 @default.
• W1982103134 cites W2162509081 @default.
• W1982103134 doi "https://doi.org/10.3354/cr034071" @default.
• W1982103134 hasPublicationYear "2007" @default.
• W1982103134 type Work @default.
• W1982103134 sameAs 1982103134 @default.
• W1982103134 citedByCount "62" @default.
• W1982103134 countsByYear W19821031342012 @default.
• W1982103134 countsByYear W19821031342013 @default.
• W1982103134 countsByYear W19821031342014 @default.
• W1982103134 countsByYear W19821031342015 @default.
• W1982103134 countsByYear W19821031342016 @default.
• W1982103134 countsByYear W19821031342017 @default.
• W1982103134 countsByYear W19821031342018 @default.
• W1982103134 countsByYear W19821031342019 @default.
• W1982103134 countsByYear W19821031342020 @default.
• W1982103134 countsByYear W19821031342021 @default.
• W1982103134 countsByYear W19821031342022 @default.
• W1982103134 countsByYear W19821031342023 @default.
• W1982103134 crossrefType "journal-article" @default.
• W1982103134 hasAuthorship W1982103134A5077181632 @default.
• W1982103134 hasAuthorship W1982103134A5091017953 @default.
• W1982103134 hasBestOaLocation W19821031341 @default.
• W1982103134 hasConcept C105795698 @default.
• W1982103134 hasConcept C125403950 @default.
• W1982103134 hasConcept C126343540 @default.
• W1982103134 hasConcept C127313418 @default.
• W1982103134 hasConcept C132651083 @default.
• W1982103134 hasConcept C134121241 @default.
• W1982103134 hasConcept C137580998 @default.
• W1982103134 hasConcept C153294291 @default.
• W1982103134 hasConcept C168754636 @default.
• W1982103134 hasConcept C18903297 @default.
• W1982103134 hasConcept C191897082 @default.
• W1982103134 hasConcept C192562407 @default.
• W1982103134 hasConcept C205649164 @default.
• W1982103134 hasConcept C24552861 @default.
• W1982103134 hasConcept C2777106113 @default.
• W1982103134 hasConcept C33923547 @default.
• W1982103134 hasConcept C39432304 @default.
• W1982103134 hasConcept C49204034 @default.
• W1982103134 hasConcept C86803240 @default.
• W1982103134 hasConcept C97137747 @default.
• W1982103134 hasConceptScore W1982103134C105795698 @default.
• W1982103134 hasConceptScore W1982103134C125403950 @default.
• W1982103134 hasConceptScore W1982103134C126343540 @default.
• W1982103134 hasConceptScore W1982103134C127313418 @default.
• W1982103134 hasConceptScore W1982103134C132651083 @default.
• W1982103134 hasConceptScore W1982103134C134121241 @default.
• W1982103134 hasConceptScore W1982103134C137580998 @default.
• W1982103134 hasConceptScore W1982103134C153294291 @default.
• W1982103134 hasConceptScore W1982103134C168754636 @default.
• W1982103134 hasConceptScore W1982103134C18903297 @default.
• W1982103134 hasConceptScore W1982103134C191897082 @default.
• W1982103134 hasConceptScore W1982103134C192562407 @default.
• W1982103134 hasConceptScore W1982103134C205649164 @default.
• W1982103134 hasConceptScore W1982103134C24552861 @default.
• W1982103134 hasConceptScore W1982103134C2777106113 @default.
• W1982103134 hasConceptScore W1982103134C33923547 @default.
• W1982103134 hasConceptScore W1982103134C39432304 @default.
• W1982103134 hasConceptScore W1982103134C49204034 @default.
• W1982103134 hasConceptScore W1982103134C86803240 @default.
• W1982103134 hasConceptScore W1982103134C97137747 @default.
• W1982103134 hasLocation W19821031341 @default.
• W1982103134 hasLocation W19821031342 @default.
• W1982103134 hasOpenAccess W1982103134 @default.
• W1982103134 hasPrimaryLocation W19821031341 @default.

• next