Ionospheric electron density profiling and modeling of COSMIC follow-on simulations

Tsai, Liang‐Miin; Su, S.‐Y.; Liu, C. H.; Ram, S. Tulasi

doi:10.1007/s00190-015-0861-x

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…The four stars used in this study provide high-quality observations 7000 times/day. We used GPS occultation data from the COSMIC 2 [31], Metop A [32], Metop B, a Metop C satellites [33]. The GPS signal is in the microwave range and is therefore un fected by clouds and precipitation [15].…”

Section: Datamentioning

confidence: 99%

Evaluation of the Planetary Boundary Layer Height in China Predicted by the CMA-GFS Global Model

et al. 2022

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The key role of the planetary boundary layer height (PBLH) in pollution, climate, and model forecasting has long been recognized. However, the observed PBLH has rarely been used to evaluate numerical weather prediction models in China. We compared the temporal and spatial characteristics of the bias in the PBLH in China predicted by the CMA-GFS model with vertical high-resolution sounding data and Global Positioning System occultation data from 2019 to 2020. We found that: (1) The PBLH in East China is systematically underestimated by the CMA-GFS model. The bias mainly results from the underestimation of the wind shear in the boundary layer, a smaller sensible heat flux near the surface, and a lower surface temperature. The combined effects of these factors inhibit the boundary layer from developing to a higher height, although the most important contributor is the small sensible heat flux. (2) There is a systematic overestimation of the PBLH over the Tibetan Plateau throughout the year. The bias is mainly a result of the smaller buoyancy, higher wind shear, and larger sensible heat flux forecast by the CMA-GFS model, which drive the boundary layer to develop to a significantly deeper height than the observations. This bias in the CMA-GFS model is mainly caused by the bias in the sensible heat flux and wind shear forecasts. In contrast, the CMA-GFS model underestimates the PBLH in the Tarim Basin. Our preliminary analysis shows that the boundary layer forecasted is unable to develop because the buoyancy effect of the model is too strong. Therefore, the bias of the predicted PBLH by the CMA-GFS model in China is mainly caused by inaccuracies in the sensible heat flux and wind shear forecasts.

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Section: Datamentioning

confidence: 99%

Evaluation of the Planetary Boundary Layer Height in China Predicted by the CMA-GFS Global Model

et al. 2022

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Ionospheric electron density modelling using B-splines and constraint optimization

Gopalakrishnan

Schmidt

2022

Earth Planets Space

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Many modern applications, such as precise point positioning, autonomous driving or precision agriculture would benefit significantly if a high-precision and high-resolution model of electron density in the ionosphere and the plasmasphere would be globally available. Since the development of such a model still relies on data with insufficient and uneven global coverage, the consideration of background information and the introduction of equality and inequality constraints on Chapman key parameters are essential. In this work, we develop a multi-layer Chapman model based on B-spline expansions of selected key parameters of the electron density. The unknown series coefficients of the key parameters are subject to equality and inequality constraints. Finally, the developed model is applied to a combination of real and semi-simulated input data; the results are validated through ionosonde measurements. Graphical Abstract

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Ionospheric electron density profiling and modeling of COSMIC follow-on simulations

Cited by 2 publications

References 26 publications

Evaluation of the Planetary Boundary Layer Height in China Predicted by the CMA-GFS Global Model

Evaluation of the Planetary Boundary Layer Height in China Predicted by the CMA-GFS Global Model

Ionospheric electron density modelling using B-splines and constraint optimization

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