• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Ocean Dynamics >Correcting circulation biases in a lower-resolution global general circulation model with data assimilation
【24h】

Correcting circulation biases in a lower-resolution global general circulation model with data assimilation

机译：通过数据同化来校正较低分辨率的全局总环流模型中的环流偏差

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this study, we aim at developing a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias by directly adding an additional source term into the model equations. This method is presented and tested first with a twin experiment on a fully controlled Lorenz '96 model. It is then applied to the lower-resolution global circulation NEMO-LIM2 model, with both a twin experiment and a real case experiment. Sea surface height observations are used to create a forcing to correct the poorly located and estimated currents. Validation is then performed throughout the use of other variables such as sea surface temperature and salinity. Results show that the method is able to consistently correct part of the model bias. The bias correction term is presented and is consistent with the limitations of the global circulation model causing bias on the oceanic currents.
机译：在这项研究中，我们旨在开发一种使用数据同化的偏差校正的新方法。该方法基于对模型的随机强迫，可通过将额外的源项直接添加到模型方程中来校正偏差。首先通过在完全受控的Lorenz '96模型上进行的双实验对这种方法进行了介绍和测试。然后通过双生实验和真实案例实验将​​其应用于较低分辨率的全球环流NEMO-LIM2模型。利用海面高度观测值来创建强迫，以更正定位不良和估算的洋流。然后，在使用其他变量（例如海面温度和盐度）的整个过程中进行验证。结果表明，该方法能够一致地校正模型偏差的一部分。提出了偏差校正项，它与引起洋流偏差的全球环流模型的局限性一致。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号