评估CRU-JRA格式气象数据集用于模拟伊朗的小麦生产系统
Alireza Araghi1, Christopher J Martinez2
1Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran. alireza_araghi@yahoo.com.
International journal of biometeorology
|April 7, 2024
概括
一个新的CRU-JRA格式气象数据集显示了作物建模的可接受准确性,与现有的数据集相似. 建议进行进一步校准,以提高其在农业模拟中的实用性.
科学领域:
- 农业科学 农业科学
- 气象学 天气学
- 气候科学 气候科学
背景情况:
- 气象数据对于农业模拟模型至关重要,但测量数据的稀缺性阻碍了许多地区的模型应用.
- 网格气象数据集为作物建模提供了测量数据的可行替代方案.
- CRU-JRA数据集是一个新开发的每6小时,0.5°×0.5°分辨率的数据集,旨在用于建模目的.
研究的目的:
- 为了评估CRU-JRA格式气象数据集用于作物建模应用程序.
- 评估CRU-JRA温度,太阳辐射和降水数据在模拟小麦生产中的准确性.
主要方法:
- 在农业技术转让决策支持系统 (DSSAT) 中使用CERES-小麦模型.
- 在伊朗模拟灌和雨水小麦生产系统,使用CRU-JRA数据集.
- 使用谷物产量的正常化根平均平方误差 (NRMSE) 量化数据集性能.
主要成果:
- 对于模拟的谷物产量,CRU-JRA最大和最小温度显示出良好的准确性 (NRMSE14%).
- 在产量模拟中,CRU-JRA太阳辐射也显示了相似的性能 (NRMSE 14.4%).
- CRU-JRA降水数据表现最弱,谷物产量NRMSE为18.9%.
结论:
- CRU-JRA数据集是研究区域作物建模的相对可接受的气象数据来源.
- 虽然CRU-JRA显示出前景,但需要进一步校准以提高未来版本的精度.
- 建议进行额外的研究,以探索CRU-JRA在各种气候条件下适用于农业建模的适用性.
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