.png){kind=icon}
返回
A multiphase CMAQ version 5.0 adjoint
.png){kind=icon}
OA
AI
DOI：10.5194/gmd-13-2925-2020.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present the development of a multiphase ad-joint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint model provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation, and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosol dynamics and thermodynamics, cloud chemistry and dynamics, diffusion, and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with algorithmic differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or finite-difference method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the complex variable method (CVM) is adopted where necessary. The ad-joint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM and CVM. In an example application of the full multiphase adjoint model, we provide the first estimates of how emissions of particulate matter (PM2.5) affect public health across the US.
Keyword:
FINE PARTICULATE MATTER
VARIATIONAL DATA ASSIMILATION
UNITED-STATES IMPLICATIONS
DECOUPLED DIRECT METHOD
CANADIAN CENSUS HEALTH
AIR-QUALITY MODEL
SENSITIVITY-ANALYSIS
SOURCE APPORTIONMENT
GOVERNING EQUATIONS
MORTALITY
期刊
IF:
4.9
论文数:
4.1K
被引数:
2.4W
机构
查看更多机构
引用论文
.png){kind=icon}
分享收藏 查看更多内容