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Editorial

Lower Atmosphere Meteorology

by
M. Ángeles García
* and
Isidro A. Pérez
*
Department of Applied Physics, Universidad de Valladolid, Valladolid 47011, Spain
*
Authors to whom correspondence should be addressed.
Atmosphere 2019, 10(10), 609; https://doi.org/10.3390/atmos10100609
Submission received: 30 September 2019 / Revised: 8 October 2019 / Accepted: 9 October 2019 / Published: 10 October 2019
(This article belongs to the Special Issue Lower Atmosphere Meteorology)
The Atmosphere Special Issue “Lower Atmosphere Meteorology” comprises thirteen original papers dealing with different meteorological processes that occur in the layer of the atmosphere close to the surface and which can greatly affect living beings and materials. This issue was conceived because of the key role that the lower atmosphere plays in that intensive interaction.
This special issue is made up of three groups of papers. The first group focuses on three meteorological variables. One is the mixing layer height, which is an important parameter vis-à-vis gaining a better understanding of the processes involved in air pollution, climate, and weather. This layer is not usually measured and must be calculated and compared with experimental values. The second variable is wind speed, which is one of the most important parameters used as an indicator of changes in atmospheric circulation. The third variable is the air parcel trajectory for estimating atmospheric transport pathways. This is an important tool for obtaining a better understanding of processes within the lower atmosphere.
The mixing layer height’s influence on pollutant dispersion is noticeable in urban areas. In this issue, Danchovski [1] evaluated the algorithms used to calculate this variable based on radiosonde and ceilometer data, and a comparison between the procedures was made. The atmospheric boundary layer plays an important role in the study of meteorology and when modelling the weather. Turbulence mixing in the atmosphere near the surface is determined by the height of the atmospheric boundary layer and data remains scarce in hurricane conditions. Under such extreme conditions, Ren et al. [2] investigated the asymmetric distribution of atmospheric boundary layer height scales using dropsondes.
Meteorological parameters are subject to variations as a consequence of atmospheric turbulence. Daily evolution in the surface wind was analysed by Zhao et al. [3], considering observation data from a noticeable spatial and temporal extension. They found large diurnal variations in surface wind and significant regional features. Maruhaashi et al. [4] addressed the topic of mountain waves caused by disturbance in the air flow around a topographic obstacle. They categorized the severity of the wind shear into classes based on airborne observations from two flights and forecasts of a model considering the Froude number and turbulent indicators.
The dispersion and transport of gases and particles in the atmosphere is characterised by important parameters, such as temperature, precipitation, and wind direction and speed. Transport may have a major impact on living beings and materials when toxic substances are released. Analysis of air mass trajectories improves the response so as to minimize the environmental impact of harmful releases into the atmosphere. Air parcel trajectory models prove particularly useful in these situations. This issue presents one study carried out by Hernández-Ceballos et al. [5], who investigated areas probably affected by air masses of hazardous materials released into the atmosphere. Long-term forward trajectories, with the corresponding end-point positions and density maps, were used to show the influence of orography and height release on the dispersion and transport of materials in the atmosphere.
The content in this group is expanded taking into account that meteorological variables together with additional factors can be used to establish suitable environments for human settlements. This object was quantitatively evaluated and analysed in this issue by Song et al. [6]. The superposition of six key natural factors, including temperature–humidity index and land surface–temperature index, was considered. Results were expressed in levels as a function of the most suitable pattern. Topography and vegetation were the dominant factors while for the perspective of time the dominant factors were temperature and water resource.
Characterizing vegetation also plays an important role in modelling the atmospheric processes involved in climate simulations. The research carried out by Jiménez et al. [7] contributes further in this matter. Remote sensing was used to obtain the nearest different vegetation index database which represents vegetation in land surface models. Three methods were considered to derive the fractional vegetation cover assessing the impact of this parameter on near-surface temperature.
The second group of papers considers aerosols, clouds, and precipitation. Intensive research has been devoted in recent years to aerosols due to their influence on radiative processes and on human health. Moreover, aerosols may be cloud condensation nuclei. Atmospheric optics is represented by the analysis carried out by Zhang et al. [8], where aerosol optical depth evolution was investigated together with the determination of the volume size distribution. In this issue, the paper by Wang et al. [9] presents the seasonal and interannual variation of low-cloud fraction and some of its meteorological controlling factors such as the estimated inversion strength and sea surface temperature by means of a long-term database.
Precipitation is represented by the analysis made by Gao et al. [10], where several cycles were determined in a temporal analysis and two patterns in spatial analysis. The relationship between the diurnal variations of clouds and precipitation was also considered.
Persistent rain in a subtropical monsoon region is a complex process that demands in-depth research. The results obtained by Zhu et al. [11] are included in this issue. These authors studied the spatiotemporal variations of the Plum Rains and the influencing factors on different time scales that have thus far scarcely been considered in this perspective.
The final set of papers addresses fundamental features of gases in the atmosphere and anthropogenic greenhouse emission estimates whose concentration and evolution are measured worldwide. Trace gases retrieved using ground-based remote sensing instruments are presented in Javed et al. [12], who discuss the relationship between NO2 and CHOCHO with different meteorological parameters and show the significant decreasing trend of these trace gases in the afternoon. Huang et al. [13] analysed a correlation “top-down” procedure to estimate anthropogenic CH4 emission using long-term atmospheric CH4 and CO2 concentration data. Moreover, the results were compared with the frequent “bottom-up” IPCC inventory procedure.

Acknowledgments

The editors would like to thank the authors for their contributions, the reviewers for their comments and the editorial office for the support in publishing this issue.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Danchovski, V. Summertime urban mixing layer height over Sofia, Bulgaria. Atmosphere 2019, 10, 36. [Google Scholar] [CrossRef]
  2. Ren, Y.; Zhang, J.A.; Guimond, S.R.; Wang, X. Hurricane boundary layer height relative to storm motion from GPS dropsonde composites. Atmosphere 2019, 10, 339. [Google Scholar] [CrossRef]
  3. Zhao, Y.; Li, J.; Zhang, Q.; Jiang, X.; Feng, A. Diurnal variations in surface wind over the Tibetan plateau. Atmosphere 2019, 10, 112. [Google Scholar] [CrossRef]
  4. Maruhashi, J.; Serrào, P.; Belo-Pereira, M. Analysis of mountain wave effects on a hard landing incident in Pico Aerodrome using the AEROME model and airborne observations. Atmosphere 2019, 10, 350. [Google Scholar] [CrossRef]
  5. Hernández-Ceballos, M.A.; De Felice, L. Air mass trajectories to estimate the “most likely” areas to be affected by the release of hazardous materials in the atmosphere-feasibility study. Atmosphere 2019, 10, 253. [Google Scholar] [CrossRef]
  6. Song, F.; Yang, X.; Wu, F. Suitable pattern of the natural environment of human settlements in the lower reaches of the Yangtze river. Atmosphere 2019, 10, 200. [Google Scholar] [CrossRef]
  7. Jiménez-Gutiérrez, J.M.; Valero, F.; Jerez, S.; Montávez, J.P. Impacts of green vegetation fraction derivation methods on regional climate simulations. Atmosphere 2019, 10, 281. [Google Scholar] [CrossRef]
  8. Zhang, C.H.; Zhang, Y.; Li, Z.; Wang, Y.; Xu, H.; Li, K.; Li, D.; Xie, Y.; Zhang, Y. Sub-mode aerosol volume size distribution and complex refractive index from the three-year ground-based measurements in Chengdu China. Atmosphere 2019, 10, 46. [Google Scholar] [CrossRef]
  9. Wang, Q.; Xu, H.; Zhang, L.; Deng, J. Seasonal and interannual variation characteristics of low-cloud fraction in different north pacific regions. Atmosphere 2019, 10, 126. [Google Scholar] [CrossRef]
  10. Gao, C.; Li, Y.; Chen, H. Diurnal variations of different cloud types and the relationship between the diurnal variations of clouds and precipitation in central and east China. Atmosphere 2019, 10, 304. [Google Scholar] [CrossRef]
  11. Zhu, N.; Xu, J.; Li, K.; Luo, Y.; Yang, D.; Zhou, C. Spatiotemporal change of plum rains in the Yangtze River Delta and its relation with EASM, ENSO, and PDO during the period of 1960-2012. Atmosphere 2019, 10, 258. [Google Scholar] [CrossRef]
  12. Javez, Z.; Lui, C.; Ullah, K.; Xing, C.H.; Lui, H. Investigating the effect of different meteorological conditions on MAX-DOAS observations of NO2 and CHOCHO in Hefei, China. Atmosphere 2019, 10, 353. [Google Scholar]
  13. Huang, W.; Xiao, H.; Zhang, M.; Wang, W.; Xu, J.; Hu, Y.; Hu, C.; Liu, S.; Lee, X. Anthropogenic CH4 emissions in the Yangtze River delta based on a “top-down” method. Atmosphere 2019, 10, 185. [Google Scholar] [CrossRef]

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MDPI and ACS Style

García, M.Á.; Pérez, I.A. Lower Atmosphere Meteorology. Atmosphere 2019, 10, 609. https://doi.org/10.3390/atmos10100609

AMA Style

García MÁ, Pérez IA. Lower Atmosphere Meteorology. Atmosphere. 2019; 10(10):609. https://doi.org/10.3390/atmos10100609

Chicago/Turabian Style

García, M. Ángeles, and Isidro A. Pérez. 2019. "Lower Atmosphere Meteorology" Atmosphere 10, no. 10: 609. https://doi.org/10.3390/atmos10100609

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