GSTDTAP  > 气候变化
DOI10.1029/2020GL087516
Potential for Early Forecast of Moroccan Wheat Yields Based on Climatic Drivers
Lehmann, J.1; Kretschmer, M.2; Schauberger, B.1; Wechsung, F.1
2020-05-16
发表期刊GEOPHYSICAL RESEARCH LETTERS
ISSN0094-8276
EISSN1944-8007
出版年2020
卷号47期号:12
文章类型Article
语种英语
国家Germany; England
英文摘要

Wheat production plays an important role in Morocco. Current wheat forecast systems use weather and vegetation data during the crop growing phase, thus limiting the earliest possible release date to early spring. However, Morocco's wheat production is mostly rainfed and thus strongly tied to fluctuations in rainfall, which in turn depend on slowly evolving climate dynamics. This offers a source of predictability at longer time scales. Using physically guided causal discovery algorithms, we extract climate precursors for wheat yield variability from gridded fields of geopotential height and sea surface temperatures which show potential for accurate yield forecasts already in December, with around 50% explained variance in an out-of-sample cross validation. The detected interactions are physically meaningful and consistent with documented ocean-atmosphere feedbacks. Reliable yield forecasts at such long lead times could provide farmers and policy makers with necessary information for early action and strategic adaptation measurements to support food security.


Plain Language Summary The per capita consumption of cereals in Morocco is one of the highest in the world, placing a significant role to wheat production in the framework of national food security. Early wheat forecasts are crucial to increase the resilience of the agricultural sector to climate risks. So far, operational forecast systems provide first yield estimates in March-April and hence around 1 month before harvest starts in May. These systems use weather and vegetation data during the crop growing phase, thus limiting the earliest possible release date to this very time period. Here, we present a different approach based on causal interactions in the climate system to provide accurate forecasts of year-to-year wheat yield changes already in December. We make use of the fact that wheat production is mostly rainfed and thus strongly coupled to prevailing rain conditions which, in turn, are influenced by slowly evolving circulation patterns and sea surface temperatures in the Atlantic and Pacific Ocean. These links between far-away regions, also known as teleconnections, can last for several months and thus provide predictability at seasonal time scales relevant for strategic adaptation decisions, for example, regarding crop import planning or the choice and intensity of agronomic practices.


英文关键词causal discovery algorithms teleconnections seasonal forecast machine learning wheat forecast climate precursors
领域气候变化
收录类别SCI-E
WOS记录号WOS:000551464800031
WOS关键词JULIAN OSCILLATION ; EARLY PREDICTION ; TELECONNECTIONS ; VARIABILITY ; LINKAGES ; RAINFALL ; MADDEN
WOS类目Geosciences, Multidisciplinary
WOS研究方向Geology
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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/267614
专题气候变化
作者单位1.Leibniz Assoc, Potsdam Inst Climate Impact Res PIK, Potsdam, Germany;
2.Univ Reading, Dept Meteorol, Reading, Berks, England
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Lehmann, J.,Kretschmer, M.,Schauberger, B.,et al. Potential for Early Forecast of Moroccan Wheat Yields Based on Climatic Drivers[J]. GEOPHYSICAL RESEARCH LETTERS,2020,47(12).
APA Lehmann, J.,Kretschmer, M.,Schauberger, B.,&Wechsung, F..(2020).Potential for Early Forecast of Moroccan Wheat Yields Based on Climatic Drivers.GEOPHYSICAL RESEARCH LETTERS,47(12).
MLA Lehmann, J.,et al."Potential for Early Forecast of Moroccan Wheat Yields Based on Climatic Drivers".GEOPHYSICAL RESEARCH LETTERS 47.12(2020).
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