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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (15 November 2020) | Viewed by 36682

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Dr. Anwar Khan

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Atmospheric Chemistry Research Group, School of Chemistry, Cantock’s Close, University of Bristol, Bristol BS8 1TS, UK
Interests: monitoring of indoor and outdoor atmospheric pollutants; chemical scheme development for indoor and outdoor air quality modeling; refinement of atmospheric chemistry and transport air quality modelling; kinetic study of oxidants and the evaluation of their impact on air quality using atmospheric models; impact of aircraft emissions on air quality locally and globally
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The atmosphere is a complex mixture of physical and chemical processes. Ambient air measurements provide a snapshot of the atmosphere at a given space and time. Policymakers require more than measurements in order to address a variety of environmental issues such as air quality, climate change and human health. An alternative approach using an atmospheric model, which is a mathematical representation of the dynamical, physical, chemical and photolytic processes in the atmosphere, can give a necessary framework for integrating our understanding of atmospheric processes with ambient measurements. In order to improve our understanding of the Earth system, a combination of ambient measurements and modelling is required. Atmospheric modelling results can be used to gain and develop insights into what trace species are present at what concentrations in the atmosphere, how these concentrations are changing over time, where and in what quantities they are being emitted, what the impacts are for these changes and if the policymakers need to introduce legislation or change policies in response to these answers.

Articles are invited on all aspects of the development and use of atmospheric models in atmospheric chemistry and transport of the trace species across a range of space from local to regional and global scales and a range of time from seconds, hours, days to seasonal, decadal and centuries.

Dr. Anwar Khan
Guest Editor

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

global atmospheric model
regional atmospheric model
model evaluation
air quality
indoor and outdoor pollutants
climate change

Published Papers (11 papers)

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Research

18 pages, 2700 KiB

Open AccessArticle

Ensemble Forecasting Experiments Using the Breeding of Growing Modes with Perturbed Land Variables

by Xin-Min Zeng, Yong-Jing Liang, Yang Wang and Yi-Qun Zheng

Atmosphere 2021, 12(12), 1578; https://doi.org/10.3390/atmos12121578 - 27 Nov 2021

Viewed by 1372

Abstract

Although land surface influences atmospheric processes significantly, insufficient studies have been conducted on the ensemble forecasts using the breeding of growing modes (BGM) with perturbed land surface variables. To investigate the practicability of perturbed land variables for ensemble forecasting, we used the ARWv3 mesoscale model to generate ensembles for an event of 24 h heavy rainfall with perturbed atmospheric and land variables by the BGM method. Results show that both atmospheric and land variables can generate initial perturbations with BGM, except that they differ in time and saturation characteristics, e.g., saturation is generally achieved in approximately 30 h with a growth rate of ~1.30 for atmospheric variables versus 102 h and growth rate of 1.02 for land variables. With the increase in precipitation, the importance of the perturbations of land variables also increases as compared to those of atmospheric variables. Moreover, the influence of the perturbations of land variables on simulated precipitation is still relatively large, although smaller than that of atmospheric variables, e.g., the spreads of perturbed atmospheric and land subsets were 7.3 and 3.8 mm, respectively. The benefits of perturbed initialisation can also be observed in terms of probability forecast. All findings indicate that the BGM method with perturbed land variables has the potential to ensemble forecasts for precipitation. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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13 pages, 2249 KiB

Open AccessArticle

Abundance of NO₃ Derived Organo-Nitrates and Their Importance in the Atmosphere

by Amy Foulds, M. Anwar H. Khan, Thomas J. Bannan, Carl J. Percival, Mark H. Lowenberg and Dudley E. Shallcross

Atmosphere 2021, 12(11), 1381; https://doi.org/10.3390/atmos12111381 - 22 Oct 2021

Cited by 4 | Viewed by 1947

Abstract

The chemistry of the nitrate radical and its contribution to organo-nitrate formation in the troposphere has been investigated using a mesoscale 3-D chemistry and transport model, WRF-Chem-CRI. The model-measurement comparisons of NO₂, ozone and night-time N₂O₅ mixing ratios show good agreement supporting the model’s ability to represent nitrate (NO₃) chemistry reasonably. Thirty-nine organo-nitrates in the model are formed exclusively either from the reaction of RO₂ with NO or by the reaction of NO₃ with alkenes. Temporal analysis highlighted a significant contribution of NO₃-derived organo-nitrates, even during daylight hours. Night-time NO₃-derived organo-nitrates were found to be 3-fold higher than that in the daytime. The reactivity of daytime NO₃ could be more competitive than previously thought, with losses due to reaction with VOCs (and subsequent organo-nitrate formation) likely to be just as important as photolysis. This has highlighted the significance of NO₃ in daytime organo-nitrate formation, with potential implications for air quality, climate and human health. Estimated atmospheric lifetimes of organo-nitrates showed that the organo-nitrates act as NO_x reservoirs, with particularly short-lived species impacting on air quality as contributors to downwind ozone formation. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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13 pages, 2736 KiB

Open AccessArticle

The Impact of the Observation Data Assimilation on Atmospheric Reanalyses over Tibetan Plateau and Western Yunnan-Guizhou Plateau

by Xinghua Bao, Fuqing Zhang, Yang Zhao and Yueli Chen

Atmosphere 2021, 12(1), 38; https://doi.org/10.3390/atmos12010038 - 30 Dec 2020

Viewed by 1567

Abstract

Three modern atmospheric reanalyses with different input observation data (NOAA–CIRES 20th Century Reanalysis (20CR), Japanese 55-year Reanalysis (JRA-55), and JRA-55C) were compared against the independent radiosonde observations over the Tibetan Plateau (TP) and the western Yunnan–Guizhou Plateau (YGP) from the China-Japan Meteorological Disaster Reduction Cooperation (JICA/Tibet) Center Project in the summer of 2018 to investigate the effects of the assimilation of the observation data on the quality and accuracy of the reanalyses in the troposphere. The results indicate that the mean biases and mean root-mean-square errors of horizontal wind, temperature, and specific humidity significantly decreased when comparing the 20CR reanalysis (assimilating only surface pressure) to the JRA-55C (assimilating conventional surface and upper-air observations) and the JRA-55 (assimilating conventional and satellite observations), and the bias spreads of these aboveground variables in JRA-55C and JRA-55 were cut to almost half of those observed in 20CR. However, the mean biases and uncertainties varied little from JRA-55C to JRA-55. This means that the assimilation of conventional observation data plays a vital role in the quality of reanalyses for the troposphere over these data-sparse plateaus. It was also found that the temperature and specific humidity near the ground over TP showed larger mean biases and bias spans than those over YGP, likely due to the sparser surface observation over TP. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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16 pages, 3545 KiB

Open AccessArticle

Annual Cycle of East Asian Precipitation Simulated by CMIP6 Models

by Yuhan Yan, Congwen Zhu, Boqi Liu and Song Jiang

Atmosphere 2021, 12(1), 24; https://doi.org/10.3390/atmos12010024 - 26 Dec 2020

Cited by 10 | Viewed by 2472

Abstract

Annual cycle is fundamental in the East Asian monsoon (EAM) systems, profoundly governing the spatiotemporal distribution of the East Asian rainfall. The present study identified the dominant modes of the annual cycle in the East Asian rainfall based on the Fourier harmonic analysis and the Empirical Orthogonal Function (EOF) decomposition. We evaluated the performance of the first two leading modes (i.e., EOF-1 and EOF-2) in historical experiments (1979–2014) of the 21 released climate models of phase six of the Coupled Model Intercomparison Project (CMIP6). Comparing with the observation, although the CMIP6 models yield the essential fidelity, they still show considerable systematic biases in the amplitude and phase of the annual cycle, especially in east and south China. Most models exhibit substantial phase delays in the EOF-2 mode of the annual cycle. Some specific models (BCC-ESM1, CanESM5, and GFDL-CM4) exhibiting better performance could capture the observed annual cycle and the underlying physics in climatology and interannual variability. The limited fidelity of the EOF-2 mode of the EAM annual cycle primarily hinders the monsoon variability simulation and thus the reliable future projection. Therefore, the dominant modes of the EAM annual cycle act as the evaluate benchmark in the EAM modelling framework. Their improvement could be one possible bias correction strategy for decreasing the uncertainty in the CMIP6 simulation of the EAM. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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26 pages, 1879 KiB

Open AccessArticle

Diurnal and Seasonal Variation of Area-Fugitive Methane Advective Flux from an Open-Pit Mining Facility in Northern Canada Using WRF

by Manoj K. Nambiar, Françoise R. Robe, Alison M. Seguin, Matthew Endsin and Amir A. Aliabadi

Atmosphere 2020, 11(11), 1227; https://doi.org/10.3390/atmos11111227 - 14 Nov 2020

Cited by 6 | Viewed by 2224

Abstract

Greenhouse Gas (GHG) emissions pose a global climate challenge and the mining sector is a large contributor. Diurnal and seasonal variations of area-fugitive methane advective flux, released from an open-pit mine and a tailings pond, from a facility in northern Canada, were simulated in spring 2018 and winter 2019, using the Weather Research and Forecasting (WRF) model. The methane mixing ratio boundary conditions for the WRF model were obtained from the in-situ field measurements, using Los Gatos Research Ultra-Portable Greenhouse Gas Analyzers (LGRs), placed in various locations surrounding the mine pit and a tailings pond. The simulated advective flux was influenced by local and synoptic weather conditions in spring and winter, respectively. Overall, the average total advective flux in the spring was greater than that in the winter by 36% and 75%, for the mine and pond, respectively. Diurnal variations of flux were notable in the spring, characterized by low flux during thermally stable (nighttime) and high flux during thermally unstable (daytime) conditions. The model predictions of the methane mixing ratio were in reasonable agreement with limited aircraft observations (

R^{2} = 0.68

). The findings shed new light in understanding the area-fugitive advective flux from complex terrains and call for more rigorous observations in support of the findings. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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26 pages, 4625 KiB

Open AccessArticle

Assessing the Horizontal Homogeneity of the Atmospheric Boundary Layer (HHABL) Profile Using Different CFD Software

by Islam Abohela, Elsa Aristodemou, Abas Hadawey and Raveendran Sundararajan

Atmosphere 2020, 11(10), 1138; https://doi.org/10.3390/atmos11101138 - 21 Oct 2020

Cited by 5 | Viewed by 2897

Abstract

One of the main factors affecting the reliability of computational fluid dynamics (CFD) simulations for the urban environment is the Horizontal Homogeneity of the Atmospheric Boundary Layer (HHABL) profile—meaning the vertical profiles of the mean streamwise velocity, the turbulent kinetic energy, and dissipation rate are maintained throughout the streamwise direction of the computational domain. This paper investigates the preservation of the HHABL profile using three different commercial CFD codes—the ANSYS Fluent, the ANSYS CFD, and the Siemens STAR-CCM+ software. Three different cases were considered, identified by their different inlet conditions for the inlet velocity, turbulent kinetic energy, and dissipation rate profiles. Simulations were carried out using the RANS k-ε turbulence model. Slight variations in the eddy viscosity models, as well as in the wall boundary conditions, were identified in the different software, with the standard wall function with roughness being implemented in the Fluent applications, the scalable wall function with roughness in the CFX applications, and the blended wall function option in the STAR-CCM+ simulations. There was a slight difference in the meshing approach in the three different software, with a prism-layer option in the STAR-CCM+ software, which allowed a finer mesh near the wall/ground boundary. The results show all three software are able to preserve the horizontal homogeneity of the ABL—less than 0.5% difference between the software—indicating very similar degrees of accuracy. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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Graphical abstract

36 pages, 12227 KiB

Open AccessArticle

Atmospheric Simulations of Total Column CO₂ Mole Fractions from Global to Mesoscale within the Carbon Monitoring System Flux Inversion Framework

by Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman and Kenneth J. Davis

Atmosphere 2020, 11(8), 787; https://doi.org/10.3390/atmos11080787 - 26 Jul 2020

Cited by 10 | Viewed by 3299

Abstract

Quantifying the uncertainty of inversion-derived

{CO}_{2}

surface fluxes and attributing the uncertainty to errors in either flux or atmospheric transport simulations continue to be challenges in the characterization of surface sources and sinks of carbon dioxide (

{CO}_{2}

). Despite recent [...] Read more.

Quantifying the uncertainty of inversion-derived

{CO}_{2}

{CO}_{2}

). Despite recent studies inferring fluxes while using higher-resolution modeling systems, the utility of regional-scale models remains unclear when compared to existing coarse-resolution global systems. Here, we present an off-line coupling of the mesoscale Weather Research and Forecasting (WRF) model to optimized biogenic

{CO}_{2}

fluxes and mole fractions from the global Carbon Monitoring System inversion system (CMS-Flux). The coupling framework consists of methods to constrain the mass of

{CO}_{2}

introduced into WRF, effectively nesting our regional domain covering most of North America (except the northern half of Canada) within the CMS global model. We test the coupling by simulating Greenhouse gases Observing SATellite (GOSAT) column-averaged dry-air mole fractions (

{XCO}_{2}

) over North America for 2010. We find mean model-model differences in summer of ∼0.12 ppm, significantly lower than the original coupling scheme (from 0.5 to 1.5 ppm, depending on the boundary). While 85% of the

{XCO}_{2}

values are due to long-range transport from outside our North American domain, most of the model-model differences appear to be due to transport differences in the fraction of the troposphere below 850 hPa. Satellite data from GOSAT and tower and aircraft data are used to show that vertical transport above the Planetary Boundary Layer is responsible for significant model-model differences in the horizontal distribution of column

{XCO}_{2}

across North America. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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23 pages, 1121 KiB

Open AccessArticle

SSH-Aerosol v1.1: A Modular Box Model to Simulate the Evolution of Primary and Secondary Aerosols

by Karine Sartelet, Florian Couvidat, Zhizhao Wang, Cédric Flageul and Youngseob Kim

Atmosphere 2020, 11(5), 525; https://doi.org/10.3390/atmos11050525 - 20 May 2020

Cited by 18 | Viewed by 4624

Abstract

Particles are emitted by different sources and are also formed in the atmosphere. Despite the large impact of atmospheric particles on health and climate, large uncertainties remain concerning their representation in models. To reduce these uncertainties as much as possible, a representation of the main processes involved in aerosol dynamics and chemistry is necessary. For that purpose, SSH-aerosol was developed to represent the evolution of the mass and number concentrations of primary and secondary particles, across different scales, using state-of-the-art modules, taking into account processes that are usually not considered in air-quality or climate modelling. For example, the particle mixing state and the growth of ultra-fine particles are taken into account in the aerosol dynamics, the affinity of semi-volatile organic compounds with water and viscosity are taken into account in the partitioning between the gas and particle phases of organics and the formation of extremely low-volatility organic compounds from biogenic precursors is represented. SSH-aerosol is modular and can be used with different levels of complexity. It may be used as standalone to analyse chamber measurements. It is also designed to be easily coupled to 3D models, adapting the level of complexity to the spatial scale studied. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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15 pages, 855 KiB

Open AccessArticle

Global Warming Potential (GWP) for Methane: Monte Carlo Analysis of the Uncertainties in Global Tropospheric Model Predictions

by Richard G. Derwent

Atmosphere 2020, 11(5), 486; https://doi.org/10.3390/atmos11050486 - 09 May 2020

Cited by 24 | Viewed by 8093

Abstract

Estimates of the global warming potential (GWP) of methane rely on the predictions from global chemistry-transport models. These models employ many uncertain input parameters representing the sources and sinks for methane and those for the tropospheric ozone, which is formed as a by-product of the methane sink process. Five thousand quasi-randomly Monte Carlo sampled model runs employing a zonally averaged global model were completed, each with a base case and a pulse case that differed from the base case only in having an additional 149 Tg (1Tg = 10⁹ kg) emission pulse of methane. Each of the five thousand pulse case experiments had a small excess of methane that decayed away throughout the twenty-year model experiment. The radiative forcing consequences of this excess methane, and the excess tropospheric ozone formed from it, were integrated over a 100-year time horizon. The GWP was calculated in each of the five thousand model experiments from the sum of the radiative forcing consequences of methane and tropospheric ozone, by expressing them relative to the radiative forcing consequences of an identical emission pulse of carbon dioxide. The 2-sigma confidence range surrounding the methane atmospheric lifetime estimated in the Monte Carlo analysis was considerably wider than that derived from observations, suggesting that some of the input parameter combinations may have been unrealistic. The rejection of the unrealistic Monte Carlo replicates increased the mean methane GWP and narrowed its 2-sigma confidence interval to 37 ± 10 over a 100-year time horizon for emission pulses of the order of 1 Tg. Multiple linear regression was used to attribute the uncertainty in the output GWPs to each of the 183 uncertain input parameters, which represented emission source sectors, chemical kinetic rate coefficients, dry deposition velocities and biases in temperature and water vapour concentrations. Overall, the only significant contributions to the uncertainty in the methane GWP came from the chemical kinetic parameters representing the CH₄ + OH, CH₃O₂ + HO₂, CH₃O₂ + NO and the terpene + O₃ reaction rate coefficients. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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13 pages, 1592 KiB

Open AccessArticle

Investigating the Atmospheric Sources and Sinks of Perfluorooctanoic Acid Using a Global Chemistry Transport Model

by Rayne Holland, M. Anwar H. Khan, Rabi Chhantyal-Pun, Andrew J. Orr-Ewing, Carl J. Percival, Craig A. Taatjes and Dudley E. Shallcross

Atmosphere 2020, 11(4), 407; https://doi.org/10.3390/atmos11040407 - 19 Apr 2020

Cited by 7 | Viewed by 3524

Abstract

Perfluorooctanoic acid, PFOA, is one of the many concerning pollutants in our atmosphere; it is highly resistant to environmental degradation processes, which enables it to accumulate biologically. With direct routes of this chemical to the environment decreasing, as a consequence of the industrial phase out of PFOA, it has become more important to accurately model the effects of indirect production routes, such as environmental degradation of precursors; e.g., fluorotelomer alcohols (FTOHs). The study reported here investigates the chemistry, physical loss and transport of PFOA and its precursors, FTOHs, throughout the troposphere using a 3D global chemical transport model, STOCHEM-CRI. Moreover, this investigation includes an important loss process of PFOA in the atmosphere via the addition of the stabilised Criegee intermediates, hereby referred to as the “Criegee Field.” Whilst reaction with Criegee intermediates is a significant atmospheric loss process of PFOA, it does not result in its permanent removal from the atmosphere. The atmospheric fate of the resultant hydroperoxide product from the reaction of PFOA and Criegee intermediates resulted in a ≈0.04 Gg year⁻¹ increase in the production flux of PFOA. Furthermore, the physical loss of the hydroperoxide product from the atmosphere (i.e., deposition), whilst decreasing the atmospheric concentration, is also likely to result in the reformation of PFOA in environmental aqueous phases, such as clouds, precipitation, oceans and lakes. As such, removal facilitated by the “Criegee Field” is likely to simply result in the acceleration of PFOA transfer to the surface (with an expected decrease in PFOA atmospheric lifetime of ≈10 h, on average from ca. 80 h without Criegee loss to 70 h with Criegee loss). Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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18 pages, 3937 KiB

Open AccessArticle

Density Correction of NRLMSISE-00 in the Middle Atmosphere (20–100 km) Based on TIMED/SABER Density Data

by Xuan Cheng, Junfeng Yang, Cunying Xiao and Xiong Hu

Atmosphere 2020, 11(4), 341; https://doi.org/10.3390/atmos11040341 - 30 Mar 2020

Cited by 7 | Viewed by 3463

Abstract

This paper describes the density correction of the NRLMSISE-00 using more than 15 years (2002–2016) of TIMED/SABER satellite atmospheric density data from the middle atmosphere (20–100 km). A bias correction factor dataset is established based on the density differences between the TIMED/SABER data and NRLMSISE-00. Seven height nodes are set in the range between 20 and 100 km. The different scale oscillations of the correction factor are separated at each height node, and the spherical harmonic function is used to fit the coefficients of the different timescale oscillations to obtain a spatiotemporal function at each height node. Cubic spline interpolation is used to obtain the correction factor at other non-node heights. The spatiotemporal correction function depends on six key parameters, including height, latitude, longitude, local time, day, and year. The evaluation results show that the spatiotemporal correction function proposed in this paper achieves a good correction effect on the atmospheric density of NRLMSISE-00. The correction effect becomes more pronounced as the height increases. After correction, the relative error of the model decreased by 40%–50% in July, especially at ±40° N in the 80–100 km region. The correction effect of the spatiotemporal correction function under different geomagnetic activity may have some potential relationships with geomagnetic activities. During geomagnetic storms, the relative errors in atmospheric density at 100, 70, and 32 km decrease from 41.21%, 22.09%, and 3.03% to −9.65%, 2.60%, and 1.44%, respectively, after correction. The relative errors in atmospheric density at 100, 70, and 32 km decrease from 68.95%, 21.02%, and 3.56% to 3.49%, 2.20%, and 1.77%, respectively, during the geomagnetic quiet period. The correction effect during the geomagnetic quiet period is better than that during geomagnetic storms at a height of 100 km. The subsequent effects of geomagnetic activity will be considered, and the atmospheric density during magnetic storms and quiet periods will be corrected separately near 100 km. The ability of the model to characterize the mid-atmosphere (20–100 km) is significantly improved compared with the pre-correction performance. As a result, the corrected NRLMSISE-00 can provide more reliable atmospheric density data for scientific researches and engineering fields, such as data analysis, instrument design, and aerospace vehicles. Full article

(This article belongs to the Special Issue Atmospheric Modeling Study)

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