Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
<p>Farmers around the world time the planting of their crops to optimize growing season conditions and choose varieties that grow slowly enough to take advantage of the entire growing season while minimizing the risk of late-season kill. As climate changes, these strategies will be an importan...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-12-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/16/7253/2023/gmd-16-7253-2023.pdf |
| _version_ | 1797387671320920064 |
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| author | S. S. Rabin S. S. Rabin W. J. Sacks D. L. Lombardozzi L. Xia A. Robock |
| author_facet | S. S. Rabin S. S. Rabin W. J. Sacks D. L. Lombardozzi L. Xia A. Robock |
| author_sort | S. S. Rabin |
| collection | DOAJ |
| description | <p>Farmers around the world time the planting of their crops to optimize growing season conditions and choose varieties that grow slowly enough to take advantage of the entire growing season while minimizing the risk of late-season kill. As climate changes, these strategies will be an important component of agricultural adaptation. Thus, it is critical that the global models used to project crop productivity under future conditions are able to realistically simulate growing season timing. This is especially important for climate- and hydrosphere-coupled crop models, where the intra-annual timing of crop growth and management affects regional weather and water availability. We have improved the crop module of the Community Land Model (CLM) to allow the use of externally specified crop planting dates and maturity requirements. In this way, CLM can use alternative algorithms for future crop calendars that are potentially more accurate and/or flexible than the built-in methods.</p>
<p>Using observation-derived planting and maturity inputs reduces bias in the mean simulated global yield of sugarcane and cotton but increases bias for corn, spring wheat, and especially rice. These inputs also reduce simulated global irrigation demand by 15 %, much of which is associated with particular regions of corn and rice cultivation. Finally, we discuss how our results suggest areas for improvement in CLM and, potentially, similar crop models.</p> |
| first_indexed | 2024-03-08T22:28:22Z |
| format | Article |
| id | doaj.art-74d4849210a3426790f43659ff20a1f2 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-03-08T22:28:22Z |
| publishDate | 2023-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-74d4849210a3426790f43659ff20a1f22023-12-18T08:05:12ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032023-12-01167253727310.5194/gmd-16-7253-2023Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)S. S. Rabin0S. S. Rabin1W. J. Sacks2D. L. Lombardozzi3L. Xia4A. Robock5Department of Environmental Sciences, Rutgers University. 14 College Farm Rd., New Brunswick, New Jersey 08901-8551, USAClimate and Global Dynamics Laboratory, National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, Colorado 80305, USAClimate and Global Dynamics Laboratory, National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, Colorado 80305, USAClimate and Global Dynamics Laboratory, National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, Colorado 80305, USADepartment of Environmental Sciences, Rutgers University. 14 College Farm Rd., New Brunswick, New Jersey 08901-8551, USADepartment of Environmental Sciences, Rutgers University. 14 College Farm Rd., New Brunswick, New Jersey 08901-8551, USA<p>Farmers around the world time the planting of their crops to optimize growing season conditions and choose varieties that grow slowly enough to take advantage of the entire growing season while minimizing the risk of late-season kill. As climate changes, these strategies will be an important component of agricultural adaptation. Thus, it is critical that the global models used to project crop productivity under future conditions are able to realistically simulate growing season timing. This is especially important for climate- and hydrosphere-coupled crop models, where the intra-annual timing of crop growth and management affects regional weather and water availability. We have improved the crop module of the Community Land Model (CLM) to allow the use of externally specified crop planting dates and maturity requirements. In this way, CLM can use alternative algorithms for future crop calendars that are potentially more accurate and/or flexible than the built-in methods.</p> <p>Using observation-derived planting and maturity inputs reduces bias in the mean simulated global yield of sugarcane and cotton but increases bias for corn, spring wheat, and especially rice. These inputs also reduce simulated global irrigation demand by 15 %, much of which is associated with particular regions of corn and rice cultivation. Finally, we discuss how our results suggest areas for improvement in CLM and, potentially, similar crop models.</p>https://gmd.copernicus.org/articles/16/7253/2023/gmd-16-7253-2023.pdf |
| spellingShingle | S. S. Rabin S. S. Rabin W. J. Sacks D. L. Lombardozzi L. Xia A. Robock Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5) Geoscientific Model Development |
| title | Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5) |
| title_full | Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5) |
| title_fullStr | Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5) |
| title_full_unstemmed | Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5) |
| title_short | Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5) |
| title_sort | observation based sowing dates and cultivars significantly affect yield and irrigation for some crops in the community land model clm5 |
| url | https://gmd.copernicus.org/articles/16/7253/2023/gmd-16-7253-2023.pdf |
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