The Surface Inversion Problem in Trench Isolated CMOS

To investigate the evolution of the nocturnal boundary layer (NBL) and its impacts on the vertical distributions of pollutant particulates, a combination of in situ observations from a large tethered balloon, remote sensing instruments (aerosol lidar and Doppler wind lidar) and an atmospheric environment-monitoring vehicle were utilized. The observation site was approximately 100 km southwest of Beijing, the capital of China. Results show that a considerable proportion of pollutant particulates were still suspended in the residual layer (RL) (e.g., the nitrate concentration reached 30 μg m−3) after sunset. The NBL height calculated by the aerosol lidar was closer to the top of the RL before midnight because of the pollutants stored aloft in the RL and the shallow surface inversion layer; after midnight, the NBL height was more consistent with the top of the surface inversion layer. As the convective mixing layer gradually became established after sunrise the following day, the pollutants stored in the nocturnal RL of the preceding night were entrained downward into the mixing layer. The early morning PM2.5 concentration near 700 m in the RL on 20 December decreased by 83% compared with the concentration at 13:34 on 20 December at the same height. The nitrate concentration also decreased significantly in the RL, and the mixing down of nitrate from the RL could contribute about 37% to the nitrate in the mixing layer. Turbulence activities still existed in the RL with the bulk Richardson number (Rb) below the threshold value. The corresponding increase in PM2.5 was likely to be correlated with the weak turbulence in the RL in the early morning.

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On Galerkin Approximations of the Surface Active Quasigeostrophic Equations

Journal of Physical Oceanography ◽

10.1175/jpo-d-15-0073.1 ◽

2016 ◽

Vol 46 (1) ◽

pp. 125-139 ◽

Cited By ~ 6

Author(s):

Cesar B. Rocha ◽

William R. Young ◽

Ian Grooms

Keyword(s):

Galerkin Approximation ◽

Three Dimensional ◽

Active Surface ◽

Inversion Problem ◽

Conservation Of Energy ◽

Galerkin Approximations ◽

Representation Of Solutions ◽

Surface Active ◽

Surface Buoyancy ◽

Quasigeostrophic Equations

AbstractThis study investigates the representation of solutions of the three-dimensional quasigeostrophic (QG) equations using Galerkin series with standard vertical modes, with particular attention to the incorporation of active surface buoyancy dynamics. This study extends two existing Galerkin approaches (A and B) and develops a new Galerkin approximation (C). Approximation A, due to Flierl, represents the streamfunction as a truncated Galerkin series and defines the potential vorticity (PV) that satisfies the inversion problem exactly. Approximation B, due to Tulloch and Smith, represents the PV as a truncated Galerkin series and calculates the streamfunction that satisfies the inversion problem exactly. Approximation C, the true Galerkin approximation for the QG equations, represents both streamfunction and PV as truncated Galerkin series but does not satisfy the inversion equation exactly. The three approximations are fundamentally different unless the boundaries are isopycnal surfaces. The authors discuss the advantages and limitations of approximations A, B, and C in terms of mathematical rigor and conservation laws and illustrate their relative efficiency by solving linear stability problems with nonzero surface buoyancy. With moderate number of modes, B and C have superior accuracy than A at high wavenumbers. Because B lacks the conservation of energy, this study recommends approximation C for constructing solutions to the surface active QG equations using the Galerkin series with standard vertical modes.

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Particular solutions of the PDF-to-ODF inversion problem of texture analysis by large-scale mathematical programming

Journal of Applied Crystallography ◽

10.1107/s0021889893007782 ◽

1994 ◽

Vol 27 (2) ◽

pp. 177-189 ◽

Cited By ~ 2

Author(s):

H. Schaeben ◽

J. J. Fundenberger

Keyword(s):

Mathematical Programming ◽

Texture Analysis ◽

Large Scale ◽

Inversion Problem ◽

Particular Solutions

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Simultaneous Estimation of a System Matrix by Compressed Sensing and Finding Optimal Regularization Parameters for the Inversion Problem

2018 26th European Signal Processing Conference (EUSIPCO) ◽

10.23919/eusipco.2018.8553458 ◽

2018 ◽

Author(s):

Marco Maass ◽

Philipp Koch ◽

Fabrice Katzberg ◽

Alfred Mertins

Keyword(s):

Compressed Sensing ◽

Simultaneous Estimation ◽

Inversion Problem ◽

System Matrix ◽

Regularization Parameters

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A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric CO<sub>2</sub> inversion

Geoscientific Model Development ◽

10.5194/gmd-10-2201-2017 ◽

2017 ◽

Vol 10 (6) ◽

pp. 2201-2219 ◽

Cited By ~ 5

Author(s):

Yosuke Niwa ◽

Yosuke Fujii ◽

Yousuke Sawa ◽

Yosuke Iida ◽

Akihiko Ito ◽

...

Keyword(s):

Transport Model ◽

Surface Fluxes ◽

Identical Twin ◽

Inversion Problem ◽

Model Errors ◽

Optimization Scheme ◽

Error Covariance ◽

Optimal Setting ◽

Source Sink ◽

Quasi Newton

Abstract. A four-dimensional variational method (4D-Var) is a popular technique for source/sink inversions of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines offline forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. In this paper, the inversion problem is simplified by assuming the prior flux errors to be reasonably well known and by designing the prior error correlations with a simple function as a first step. It is found that a system of forward and adjoint models with smaller model errors but with nonlinearity has comparable optimization performance to that of another system that conserves linearity with an exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is demonstrated, as the global error is reduced by about 15 % by adding prior error correlations that are simply designed when 65 weekly flask sampling observations at ground-based stations are used. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to global scales. The optimization algorithm introduced in the new system does not require decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.

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