Influences of increasing temperature on Indian wheat: quantifying limits to predictability

cg.contributor.crpClimate Change, Agriculture and Food Security
cg.coverage.countryIndia
cg.coverage.iso3166-alpha2IN
cg.coverage.regionSouthern Asia
cg.creator.identifierSenthold Asseng: 0000-0002-7583-3811
cg.identifier.doihttps://doi.org/10.1088/1748-9326/8/3/034016en
cg.issn1748-9326en
cg.issue3en
cg.journalEnvironmental Research Lettersen
cg.subject.ccafsCLIMATE-SMART TECHNOLOGIES AND PRACTICESen
cg.volume8en
dc.contributor.authorKöhler, Ann-Kristinen
dc.contributor.authorChallinor, Andrew J.en
dc.contributor.authorHawkins, E.en
dc.contributor.authorAsseng, Sentholden
dc.date.accessioned2013-08-14T11:02:48Zen
dc.date.available2013-08-14T11:02:48Zen
dc.identifier.urihttps://hdl.handle.net/10568/33462
dc.titleInfluences of increasing temperature on Indian wheat: quantifying limits to predictabilityen
dcterms.abstractAs climate changes, temperatures will play an increasing role in determining crop yield. Both climate model error and lack of constrained physiological thresholds limit the predictability of yield. We used a perturbed-parameter climate model ensemble with two methods of bias-correction as input to a regional-scale wheat simulation model over India to examine future yields. This model configuration accounted for uncertainty in climate, planting date, optimization, temperature-induced changes in development rate and reproduction. It also accounts for lethal temperatures, which have been somewhat neglected to date. Using uncertainty decomposition, we found that fractional uncertainty due to temperature-driven processes in the crop model was on average larger than climate model uncertainty (0.56 versus 0.44), and that the crop model uncertainty is dominated by crop development. Simulations with the raw compared to the bias-corrected climate data did not agree on the impact on future wheat yield, nor its geographical distribution. However the method of bias-correction was not an important source of uncertainty. We conclude that bias-correction of climate model data and improved constraints on especially crop development are critical for robust impact predictions.en
dcterms.accessRightsOpen Access
dcterms.available2013-08-05
dcterms.bibliographicCitationKoehler AK, Challinor AJ, Hawkins E, Asseng S. 2013. Influences of increasing temperature on Indian wheat: quantifying limits to predictability. Environmental Research Letters 8(3).en
dcterms.issued2013-09-01
dcterms.languageen
dcterms.licenseCC-BY-3.0
dcterms.publisherIOP Publishingen
dcterms.subjectagricultureen
dcterms.subjectclimateen
dcterms.subjectyieldsen
dcterms.subjectmodelsen
dcterms.typeJournal Article

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