首页> 外文会议>International conference on computational science;ICCS 2009 >Improving GEOS-Chem Model Tropospheric Ozone through Assimilation of Pseudo Tropospheric Emission Spectrometer Profile Retrievals
【24h】

Improving GEOS-Chem Model Tropospheric Ozone through Assimilation of Pseudo Tropospheric Emission Spectrometer Profile Retrievals

机译:通过同化对流层发射光谱仪剖面反演改进GEOS-Chem模型对流层臭氧

获取原文

摘要

4D-variational or adjoint-based data assimilation provides a powerful means for integrating observations with models to estimate an optimal atmospheric state and to characterize the sensitivity of that state to the processes controlling it. In this paper we present the improvement of 2006 summer time distribution of global tropospheric ozone through assimilation of pseudo profile retrievals from the Tropospheric Emission Spectrometer (TES) into the GEOS-Chem global chemical transport model based on a recently-developed adjoint model of GEOS-Chem v7. We are the first to construct an adjoint of the linearized ozone parameterization (linoz) scheme that can be of very high importance in quantifying the amount of tropospheric ozone due to upper boundary exchanges. Tests conducted at various geographical levels show that the mismatch between adjoint values and their finite difference approximations could be up to 87% if linoz module adjoint is not used, leading to a divergence in the quasi-Newton approximation algorithm (L-BFGS) during data assimilation. We also present performance improvements in this adjoint model in terms of memory usage and speed. With the parallelization of each science process adjoint subroutine and sub-optimal combination of checkpoints and recalculations, the improved adjoint model is as efficient as the forward GEOS-Chem model.
机译:4D变量或基于伴随的数据同化为将观测值与模型集成在一起以估算最佳大气状态并表征该状态对控制它的过程的敏感性提供了强大的手段。在本文中,我们通过将对流层排放光谱仪(TES)的伪轮廓检索同化到基于最近开发的GEOS-伴随模型的GEOS-Chem全球化学迁移模型中,来改善2006年夏季全球对流层臭氧的分布化学v7。我们是第一个构建线性化臭氧参数化(linoz)方案的伴随者,该方案在量化对流层臭氧量(由于上限交换)方面具有非常重要的意义。在不同地理级别上进行的测试表明,如果不使用linoz模块伴随,则伴随值与其有限差分近似之间的不匹配可能高达87%,从而导致数据期间的拟牛顿近似算法(L-BFGS)出现差异。同化。在内存使用和速度方面,我们还介绍了该伴随模型的性能改进。通过并行处理每个科学过程的伴随子例程以及检查点和重新计算的次优组合,改进的伴随模型与正向GEOS-Chem模型一样有效。

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