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In-season performance of European Union wheat forecasts during extreme impacts
- Source :
- Scientific Reports 1 (8), 10 p.. (2018), Scientific Reports, Scientific Reports, Nature Publishing Group, 2018, 8 (1), 10 p. ⟨10.1038/s41598-018-33688-1⟩, Scientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- Here we assess the quality and in-season development of European wheat (Triticum spp.) yield forecasts during low, medium, and high-yielding years. 440 forecasts were evaluated for 75 wheat forecast years from 1993–2013 for 25 European Union (EU) Member States. By July, years with median yields were accurately forecast with errors below ~2%. Yield forecasts in years with low yields were overestimated by ~10%, while yield forecasts in high-yielding years were underestimated by ~8%. Four-fifths of the lowest yields had a drought or hot driver, a third a wet driver, while a quarter had both. Forecast accuracy of high-yielding years improved gradually during the season, and drought-driven yield reductions were anticipated with lead times of ~2 months. Single, contrasting successive in-season, as well as spatially distant dry and wet extreme synoptic weather systems affected multiple-countries in 2003, ’06, ’07, ’11 and 12’, leading to wheat losses up to 8.1 Mt (>40% of total EU loss). In these years, June forecasts (~ 1-month lead-time) underestimated these impacts by 10.4 to 78.4%. To cope with increasingly unprecedented impacts, near-real-time information fusion needs to underpin operational crop yield forecasting to benefit from improved crop modelling, more detailed and frequent earth observations, and faster computation.
- Subjects :
- Crops, Agricultural
010504 meteorology & atmospheric sciences
Rain
[SDV]Life Sciences [q-bio]
rendement des cultures
Yield (finance)
lcsh:Medicine
surface cultivée
01 natural sciences
Article
Crop
prévision de rendement
Predictive Value of Tests
prédiction de rendement
Humans
culture saisonnière
media_common.cataloged_instance
European Union
European union
Extreme Hot Weather
lcsh:Science
Weather
Triticum
modélisation
0105 earth and related environmental sciences
media_common
2. Zero hunger
Models, Statistical
Multidisciplinary
Member states
Crop yield
lcsh:R
04 agricultural and veterinary sciences
Droughts
Information fusion
Triticum spp
13. Climate action
Climatology
[SDE]Environmental Sciences
union européenne
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
Environmental science
lcsh:Q
Seasons
condition météorologique
Forecasting
Subjects
Details
- ISSN :
- 20452322
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....86e7bb5f3b4c16b2eca5511311688d65
- Full Text :
- https://doi.org/10.1038/s41598-018-33688-1