Influences of increasing temperature on Indian wheat: quantifying limits to predictability
As 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...
| Autores principales: | , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
IOP Publishing
2013
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/33462 |
| _version_ | 1855513563934752768 |
|---|---|
| author | Köhler, Ann-Kristin Challinor, Andrew J. Hawkins, E. Asseng, Senthold |
| author_browse | Asseng, Senthold Challinor, Andrew J. Hawkins, E. Köhler, Ann-Kristin |
| author_facet | Köhler, Ann-Kristin Challinor, Andrew J. Hawkins, E. Asseng, Senthold |
| author_sort | Köhler, Ann-Kristin |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | As 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. |
| format | Journal Article |
| id | CGSpace33462 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | IOP Publishing |
| publisherStr | IOP Publishing |
| record_format | dspace |
| spelling | CGSpace334622025-02-19T13:41:57Z Influences of increasing temperature on Indian wheat: quantifying limits to predictability Köhler, Ann-Kristin Challinor, Andrew J. Hawkins, E. Asseng, Senthold agriculture climate yields models As 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. 2013-09-01 2013-08-14T11:02:48Z 2013-08-14T11:02:48Z Journal Article https://hdl.handle.net/10568/33462 en Open Access IOP Publishing Koehler AK, Challinor AJ, Hawkins E, Asseng S. 2013. Influences of increasing temperature on Indian wheat: quantifying limits to predictability. Environmental Research Letters 8(3). |
| spellingShingle | agriculture climate yields models Köhler, Ann-Kristin Challinor, Andrew J. Hawkins, E. Asseng, Senthold Influences of increasing temperature on Indian wheat: quantifying limits to predictability |
| title | Influences of increasing temperature on Indian wheat: quantifying limits to predictability |
| title_full | Influences of increasing temperature on Indian wheat: quantifying limits to predictability |
| title_fullStr | Influences of increasing temperature on Indian wheat: quantifying limits to predictability |
| title_full_unstemmed | Influences of increasing temperature on Indian wheat: quantifying limits to predictability |
| title_short | Influences of increasing temperature on Indian wheat: quantifying limits to predictability |
| title_sort | influences of increasing temperature on indian wheat quantifying limits to predictability |
| topic | agriculture climate yields models |
| url | https://hdl.handle.net/10568/33462 |
| work_keys_str_mv | AT kohlerannkristin influencesofincreasingtemperatureonindianwheatquantifyinglimitstopredictability AT challinorandrewj influencesofincreasingtemperatureonindianwheatquantifyinglimitstopredictability AT hawkinse influencesofincreasingtemperatureonindianwheatquantifyinglimitstopredictability AT assengsenthold influencesofincreasingtemperatureonindianwheatquantifyinglimitstopredictability |