Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 1157-1174, 2017
http://www.geosci-model-dev.net/10/1157/2017/
doi:10.5194/gmd-10-1157-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Development and technical paper
17 Mar 2017
A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 1: Offline forward and adjoint transport models
Yosuke Niwa1, Hirofumi Tomita2, Masaki Satoh3,4, Ryoichi Imasu3, Yousuke Sawa1, Kazuhiro Tsuboi1, Hidekazu Matsueda1, Toshinobu Machida5, Motoki Sasakawa5, Boris Belan6, and Nobuko Saigusa5 1Oceanography and Geochemistry Research Department, Meteorological Research Institute, Tsukuba, Japan
2RIKEN Advanced Institute for Computational Science, Kobe, Japan
3Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan
4Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
5Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
6V. E. Zuev Institute of Atmospheric Optics, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia
Abstract. A four-dimensional variational (4D-Var) method is a popular algorithm for inverting atmospheric greenhouse gas (GHG) measurements. In order to meet the computationally intense 4D-Var iterative calculation, offline forward and adjoint transport models are developed based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). By introducing flexibility into the temporal resolution of the input meteorological data, the forward model developed in this study is not only computationally efficient, it is also found to nearly match the transport performance of the online model. In a transport simulation of atmospheric carbon dioxide (CO2), the data-thinning error (error resulting from reduction in the time resolution of the meteorological data used to drive the offline transport model) is minimized by employing high temporal resolution data of the vertical diffusion coefficient; with a low 6-hourly temporal resolution, significant concentration biases near the surface are introduced. The new adjoint model can be run in discrete or continuous adjoint mode for the advection process. The discrete adjoint is characterized by perfect adjoint relationship with the forward model that switches off the flux limiter, while the continuous adjoint is characterized by an imperfect but reasonable adjoint relationship with its corresponding forward model. In the latter case, both the forward and adjoint models use the flux limiter to ensure the monotonicity of tracer concentrations and sensitivities. Trajectory analysis for high CO2 concentration events are performed to test adjoint sensitivities. We also demonstrate the potential usefulness of our adjoint model for diagnosing tracer transport. Both the offline forward and adjoint models have computational efficiency about 10 times higher than the online model. A description of our new 4D-Var system that includes an optimization method, along with its application in an atmospheric CO2 inversion and the effects of using either the discrete or continuous adjoint method, is presented in an accompanying paper Niwa et al.(2016).

Citation: Niwa, Y., Tomita, H., Satoh, M., Imasu, R., Sawa, Y., Tsuboi, K., Matsueda, H., Machida, T., Sasakawa, M., Belan, B., and Saigusa, N.: A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 1: Offline forward and adjoint transport models, Geosci. Model Dev., 10, 1157-1174, doi:10.5194/gmd-10-1157-2017, 2017.
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We have developed forward and adjoint models based on NICAM-TM, as part of the 4D-Var system for atmospheric GHGs inversions. The models are computationally efficient enough to make the 4D-Var iterative calculation feasible. Trajectory analysis for high-CO2 concentration events are performed to test adjoint sensitivities; we also demonstrate the potential usefulness of our adjoint model for diagnosing tracer transport.
We have developed forward and adjoint models based on NICAM-TM, as part of the 4D-Var system for...
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