Global evaluation of a semiempirical model for yield anomalies and application to within-season yield forecasting

Global Change Biology

Volumn 23, Issue 11, 2017, Pages 4750-4764

  Schauberger, Bernhard ^a,b   Gornott, Christoph ^a   Wechsung, Frank ^a  

^a POTSDAM INSTITUTE FOR CLIMATE IMPACT RESEARCH   (Germany)

^b INSTITUT PIERRE SIMON LAPLACE   (France)

Author keywords

forecast; global; maize; semiempirical model; soybeans; weather; wheat; yield anomaly

Indexed keywords

ANNUAL VARIATION; CLIMATE CHANGE; CROP YIELD; EMPIRICAL ANALYSIS; FORECASTING METHOD; GROWING SEASON; MAIZE; NUMERICAL MODEL; SOYBEAN; WEATHER; WHEAT;

UNITED STATES;

GLYCINE MAX; TRITICUM AESTIVUM; ZEA MAYS;

CLIMATE CHANGE; CROP PRODUCTION; GROWTH, DEVELOPMENT AND AGING; MAIZE; SEASON; SOYBEAN; STATISTICS AND NUMERICAL DATA; THEORETICAL MODEL; TRENDS; UNITED STATES; WEATHER; WHEAT;

CLIMATE CHANGE; CROP PRODUCTION; MODELS, THEORETICAL; SEASONS; SOYBEANS; TRITICUM; UNITED STATES; WEATHER; ZEA MAYS;

EID: 85020096044     PISSN: 13541013     EISSN: 13652486     Source Type: Journal    
DOI: 10.1111/gcb.13738     Document Type: Article

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