The Impact of Parameterized Convection on the Simulation of Crop Processes
Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by d...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
American Meteorological Society
2015
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/76570 |
| _version_ | 1855520296407138304 |
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| author | García Carreras, L. Challinor, Andrew J. Parkes BJ Birch, C.E. Nicklin KJ Parker DJ |
| author_browse | Birch, C.E. Challinor, Andrew J. García Carreras, L. Nicklin KJ Parker DJ Parkes BJ |
| author_facet | García Carreras, L. Challinor, Andrew J. Parkes BJ Birch, C.E. Nicklin KJ Parker DJ |
| author_sort | García Carreras, L. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty. |
| format | Journal Article |
| id | CGSpace76570 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | American Meteorological Society |
| publisherStr | American Meteorological Society |
| record_format | dspace |
| spelling | CGSpace765702024-10-17T10:13:27Z The Impact of Parameterized Convection on the Simulation of Crop Processes García Carreras, L. Challinor, Andrew J. Parkes BJ Birch, C.E. Nicklin KJ Parker DJ climate change agriculture food security climate prediction convective parameterization model errors Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty. 2015-06-01 2016-08-25T11:51:03Z 2016-08-25T11:51:03Z Journal Article https://hdl.handle.net/10568/76570 en Open Access American Meteorological Society Garcia-Carreras L, Challinor AJ, Parkes BJ, Birch CE, Nicklin KJ, Parker DJ. 2015. The Impact of Parameterized Convection on the Simulation of Crop Processes. Journal of Applied Meteorology and Climatology 54:1283–1296. |
| spellingShingle | climate change agriculture food security climate prediction convective parameterization model errors García Carreras, L. Challinor, Andrew J. Parkes BJ Birch, C.E. Nicklin KJ Parker DJ The Impact of Parameterized Convection on the Simulation of Crop Processes |
| title | The Impact of Parameterized Convection on the Simulation of Crop Processes |
| title_full | The Impact of Parameterized Convection on the Simulation of Crop Processes |
| title_fullStr | The Impact of Parameterized Convection on the Simulation of Crop Processes |
| title_full_unstemmed | The Impact of Parameterized Convection on the Simulation of Crop Processes |
| title_short | The Impact of Parameterized Convection on the Simulation of Crop Processes |
| title_sort | impact of parameterized convection on the simulation of crop processes |
| topic | climate change agriculture food security climate prediction convective parameterization model errors |
| url | https://hdl.handle.net/10568/76570 |
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