Estimating sowing and harvest dates based on the Asian summer monsoon
作者： Camilla Mathison , Chetan Deva , Pete Falloon , Andrew J. Challinor
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摘要: Abstract. Sowing and harvest dates are a significant source of uncertainty within crop models, especially for regions where high-resolution data are unavailable or, as is the case in future climate runs, no are available at all. Global datasets not always able to distinguish when wheat grown tropical subtropical regions, they also often coarse resolution. South Asia one such region large spatial variation means higher-resolution needed, together with greater clarity timing main wheat growing season. Agriculture South Asia closely associated dominating climatological phenomenon, the Asian summer monsoon (ASM). Rice two highly important crops for the region, rice being mainly cultivated wet season during summer monsoon months dry winter. We present method for estimating sowing using the ASM onset retreat. The aim this provide more accurate alternative global cropping calendars than currently available generate representative inputs impact assessments. first demonstrate that there skill model prediction monsoon onset retreat downscaled general circulation models (GCMs) by comparing modelled precipitation observations. then calculate and apply rules each simulation to climatological estimates day period. show reproduces day and harvest most parts India. application two future simulations demonstrates estimated dates are successfully modified ensure remains consistent internal climate. study therefore provides a useful way modelling potential adaptations changes in future
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