Magnetic Field Intensity Modification to Force Free Model of Magnetic Clouds: Website of Wind Examples From Launch to July of 2015

We describe a new NASA website that shows normalized magnetic field (B) magnitude profiles within Wind magnetic clouds (MCs) (i.e., observations versus basic model versus modified model) for 209 MCs observed from launch in late 1994 to July of 2015, where model modification is based on the studies of Lepping et al. (Solar Phys, 2017, 292:27) and Lepping et al. (Solar Phys, 2018, 293:162); the basic force free magnetic cloud parameter fitting model employing Bessel functions (Lepping et al., J. Geophys. Res., 1990, 95:11957) is called the LJB model here. The fundamental principles should be applicable to the B-data from any spacecraft at 1 AU. Earlier (in the LJB study), we justified why the field magnitude can be thought of as decoupled from the field direction within an MC, and further, we justified this idea in terms of actual observations seen over a few decades with examples of MCs from Wind data. The model modification is achieved by adding a correction (“Quad”) value to the LJB model (Bessel function) value in the following manner: B (est)/B0 ≈ [LJB Model + Quad (CA,u)], where B0 is the LJB-estimated field magnitude value on the MC’s axis, CA is the relative closest approach (See Supplementary Appendix A), and u is the distance that the spacecraft travels through the MC from its entrance point. In an average sense, the Quad technique is shown to be successful for 82% of the past modeled MCs, when Quality (Q0) is good or excellent (see Supplementary Appendix A). The Quad technique is successful for 78% of MCs when all cases are considered. So Q0 of the MC LJB-fit is not a big factor when the success of the Quad scheme is considered. In addition, it is found that the Quad technique does not work better for MC events with higher solar wind speed. Yearly occurrence frequency of all MC events (NYearly) and those MC events with ΔσN/σN2 ≥ 0.5 (NΔσN/σN2≥0.5) are well correlated, but there is no solar cycle dependence for normalizing NΔσN/σN2≥0.5 with NYearly.

Model modification and feature study of Duffing oscillator

With the development of chaos theory, Duffing oscillator has been extensively studied in many fields, especially in electronic signal processing. As a nonlinear oscillator, Duffing oscillator is more complicated in terms of equations or circuit analysis. In order to facilitate the analysis of its characteristics, the study analyzes the circuit from the perspective of vibrational science and energetics. The classic Holmes-Duffing model is first modified to make it more popular and concise, and then the model feasibility is confirmed by a series of rigorous derivations. According to experiments, the influence of driving force amplitude, frequency, and initial value on the system is finally explained by the basic theories of physics. Through this work, people can understand the mechanisms and characteristics of Duffing oscillator more intuitively and comprehensively. It provides a new idea for the study of Duffing oscillators and more.

Process-based and Observation-constrained SOA Simulations in China: The Role of Semivolatile and Intermediate-Volatility Organic Compounds and OH Levels

Organic aerosol (OA) is a major component of tropospheric submicron aerosol that contributes to air pollution and causes adverse effects on human health. Chemical transport models have difficulties to reproduce the variability of OA concentrations in polluted areas, hindering understanding of the OA budget. Herein, we applied both process-based and observation-constrained schemes to simulate OA in GEOS-Chem. Comprehensive data sets of surface OA, OA components, secondary organic aerosol (SOA) precursors, and oxidants were used for model-observation comparisons. In the revised schemes, updates of the emissions, volatility distributions, and SOA yields of semivolatile and intermediate volatility organic compounds (S/IVOCs) were made. These updates are however insufficient to reproduce the SOA concentrations in observations. The addition of nitrous acid sources is an important model modification, which improves the simulation of surface concentrations of hydroxyl radical (OH) in winter in northern China. The increased surface OH concentrations enhance the SOA formation and lead to greater SOA mass concentrations by over 30 %, highlighting the importance of having good OH simulations in air quality models. There is a greater sensitivity of the SOA formation to the oxidant levels in winter than in summer in China. With all the model improvements, both the process-based and observation-constrained SOA schemes can reproduce the observed mass concentrations of SOA and show spatial and seasonal consistency with each other. Our best model simulations suggest that anthropogenic S/IVOCs are the dominant source of SOA in China with a contribution of over 50 %. The residential sector may be the predominant source of S/IVOCs in winter, despite large uncertainty remains in the emissions of IVOCs from the residential sector in northern China. The industry sector is also an important source of IVOCs, especially in summer. More S/IVOC measurements are needed to constrain their emissions.