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Atmosphere
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Atmospheric Ice Nucleating Particles, Cloud and Precipitation
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Atmospheric Ice Nucleating Particles, Cloud and Precipitation

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 5168

Special Issue Editor

Dr. Kui Chen

E-Mail Website
Guest Editor
Emergency Management College, Nanjing University of Information Science & Technology, Nanjing 211544, China
Interests: ice nucleating particles; aerosol component; cloud; precipitation

Special Issue Information

Dear Colleagues,

This Special Issue aims to present the current advances in the field of atmospheric ice nucleating particles (INPs), cloud and precipitation observation, and modeling. Atmospheric ice nucleation plays a vital role in ice crystal formation in clouds, changing the microphysical properties of clouds, precipitation, and atmospheric radiative transfer and affecting the climate system and hydrological cycle. Heterogeneous nucleation of atmospheric ice nuclei has become a hot research topic due to its activation characteristics for improving the accuracy of regional and global weather, climate, and Earth system models. However, little is known about how INPs affect clouds and precipitation. Here, we call for contributions related to the properties of ice nucleating particles, clouds, and precipitation. This topic encompasses observations (INPs, cloud, and precipitation), simulations (process, regional and global), as well as weather extremes (droughts, floods, and storm surges), etc.

Dr. Kui Chen
Guest Editor

Manuscript Submission Information

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

  • ice nucleating particles
  • cloud
  • precipitation
  • observational study
  • modeling research

Published Papers (4 papers)

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Research

16 pages, 14429 KiB  
Article
Spatial Downscaling of GPM Satellite Precipitation Data Using Extreme Random Trees
by Shaonan Zhu, Xiangyuan Wang, Donglai Jiao, Yiding Zhang and Jiaxin Liu
Atmosphere 2023, 14(10), 1489; https://doi.org/10.3390/atmos14101489 - 26 Sep 2023
Viewed by 884
Abstract
Obtaining precise and detailed precipitation data is crucial for analyzing watershed hydrology, ensuring sustainable water resource management, and monitoring events such as floods and droughts. Due to the complex relationship between precipitation and geographic factors, this study divides the entire country of China [...] Read more.
Obtaining precise and detailed precipitation data is crucial for analyzing watershed hydrology, ensuring sustainable water resource management, and monitoring events such as floods and droughts. Due to the complex relationship between precipitation and geographic factors, this study divides the entire country of China into eight vegetation zones based on different vegetation types. Within each vegetation zone, we employ a seasonally adjusted Extreme Random Trees approach to spatially downscale GPM (Global Precipitation Measurement) satellite monthly precipitation data. To validate the effectiveness of this method, we compare it with kriging interpolation and traditional global downscaling methods. By increasing the spatial resolution of the GPM monthly precipitation dataset from 0.1° to 0.01°, we evaluate the downscaled results and validate them against ground-level rain gauge data and GPM satellite precipitation data. The results indicate that the partitioned area prediction method outperforms other approaches, resulting in a precipitation dataset that not only achieves high accuracy but also offers finer spatial resolution compared to the original GPM precipitation dataset. Overall, this approach enhances the model’s capability to capture complex spatial features and demonstrates excellent generalization. The resulting higher-resolution precipitation dataset enables the creation of more accurate precipitation distribution maps, providing data support for regions lacking hydrological information. These data can be used to analyze seasonal precipitation patterns and reveal differences in precipitation across different seasons and geographic regions. Full article
(This article belongs to the Special Issue Atmospheric Ice Nucleating Particles, Cloud and Precipitation)
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16 pages, 5337 KiB  
Article
Evaluation of Cloud Water Resources in the Huaihe River Basin Based on ERA5 Data
by Jinlan Gao, Jingjing Feng, Yanan Cao and Xiaoyi Zheng
Atmosphere 2023, 14(8), 1253; https://doi.org/10.3390/atmos14081253 - 07 Aug 2023
Viewed by 833
Abstract
High-resolution reanalysis data are an effective way to evaluate cloud water resources (CWRs). Based on ERA5 reanalysis data and gridded observed precipitation data, combined with the diagnostic quantification method of cloud water resource (CWR-DQ), we analyze and evaluate the CWRs and their distribution [...] Read more.
High-resolution reanalysis data are an effective way to evaluate cloud water resources (CWRs). Based on ERA5 reanalysis data and gridded observed precipitation data, combined with the diagnostic quantification method of cloud water resource (CWR-DQ), we analyze and evaluate the CWRs and their distribution characteristics in the Huaihe River Basin from 2011 to 2021. Moreover, we compare and evaluate the CWRs of two typical precipitation processes in summer and winter. The results show that the annual total amount of atmospheric hydrometeor (GMh) in the Huaihe River Basin is approximately 1537.3 mm. The precipitation (Ps) is 963.5 mm, the cloud water resource (CWR) is 573.8 mm, and the precipitation efficiency of hydrometeor (PEh) is 62.4%. The CWR in the Huaihe River Basin shows a slow increasing trend from 2011 to 2021.The monthly variations in Ps, CWR, and PEh show a single peak distribution. The spatial horizontal distributions of the gross mass of water vapor (GMv), GMh, and Ps in the Huaihe River Basin are zonal, and the values decrease with increasing latitude. In summer, the hydrometeors are mainly distributed in the middle layer (between 600 and 350 hPa). The hydrometeors in spring, autumn, and winter are mainly below 500 hPa. Two cases reveal that GMv, the condensation from water vapor to hydrometeors (Cvh), GMh, Ps, and PEh in the summer case are significantly higher compared to those in the winter case, while the CWRs are similar. The results are helpful for proposing rational suggestions for the Huaihe River Basin and to provide some beneficial reference for the development of CWRs. Full article
(This article belongs to the Special Issue Atmospheric Ice Nucleating Particles, Cloud and Precipitation)
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12 pages, 3465 KiB  
Article
Comprehensive Efficiency Evaluation of Aircraft Artificial Cloud Seeding in Hunan Province, China, Based on Numerical Simulation Catalytic Method
by Xiecheng Wan, Sheng Zhou and Zhichao Fan
Atmosphere 2023, 14(7), 1187; https://doi.org/10.3390/atmos14071187 - 23 Jul 2023
Viewed by 1718
Abstract
Aircraft cloud seeding refers to the use of equipment on aircraft to release chemicals into clouds, changing their physical and chemical properties to increase rainfall or snowfall. The purpose of precipitation enhancement is to alleviate drought and water scarcity issues. Due to the [...] Read more.
Aircraft cloud seeding refers to the use of equipment on aircraft to release chemicals into clouds, changing their physical and chemical properties to increase rainfall or snowfall. The purpose of precipitation enhancement is to alleviate drought and water scarcity issues. Due to the complexity of the technology, the precise control of factors such as cloud characteristics and chemical release amounts is necessary. Therefore, a scientific evaluation of the potential of aircraft cloud seeding can help to improve the effectiveness of the process, and is currently a technical challenge in weather modification. This study used the mesoscale numerical model WRF coupled with a catalytic process to simulate and evaluate the seven aircraft cloud seeding operations conducted in Hunan Province in 2021. The results show that WRF can effectively evaluate the effectiveness of cloud seeding. When the water vapor conditions are suitable, the airborne dispersion of silver iodide (AgI) can significantly increase the content of large particles of high-altitude ice crystals, snow, and graupel, resulting in an increase in low-level rainwater content and, correspondingly, an increase in ground precipitation. When the water vapor conditions are insufficient, the dispersion of AgI does not trigger effective precipitation, consistent with the results of station observations and actual flight evaluations. This study provides an effective method for scientifically evaluating the potential and effectiveness of aircraft cloud seeding operations. Full article
(This article belongs to the Special Issue Atmospheric Ice Nucleating Particles, Cloud and Precipitation)
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14 pages, 6529 KiB  
Article
Effects of Aerosol Number Concentration and Updraft Velocity on Relative Dispersion during the Collision–Coalescence Growth Stage of Warm Clouds
by Suying Yang, Yanzhe Zhang, Xinyang Yu, Chunsong Lu and Yiyu Li
Atmosphere 2023, 14(5), 828; https://doi.org/10.3390/atmos14050828 - 04 May 2023
Viewed by 1092
Abstract
Relative dispersion (ɛ) is a key expression used to parameterize various cloud processes in global circulation models (GCMs) and meteorological mesoscale models. Aerosols, updraft velocity (w), and different growth stages of warm clouds are known to affect relative dispersion. A two-dimensional [...] Read more.
Relative dispersion (ɛ) is a key expression used to parameterize various cloud processes in global circulation models (GCMs) and meteorological mesoscale models. Aerosols, updraft velocity (w), and different growth stages of warm clouds are known to affect relative dispersion. A two-dimensional detailed bin microphysical cloud model is used to investigate the combined impacts of aerosol number concentration (Na) and updraft velocity on relative dispersion in the collision–coalescence stage. In addition, the causes potentially controlling the changes in ɛ with updraft velocity are explored. There are three main influence regimes: the updraft velocity main influence regime, the aerosol main influence regime, and the joint influence regime. The cause of the variations in ɛ with updraft velocity is found to be different in the three main influence regimes. In the updraft velocity main influence regime, vigorous collision–coalescence due to stronger w results in a shift in the cloud droplet number concentration spectrum toward larger droplets, and the average cloud droplet radius increases, but the spectral width is less variable, so ε decreases. In the joint influence regime, stronger cloud droplet evaporation due to the stronger dragging effect of large cloud droplets widens the spectrum, mainly by reducing the cloud droplet number concentration (Nc) of 4–30 μm, and ε increases with the reduction in w. In the aerosol main influence regime, the strongest dragging effect reduces Nc at all radii with decreasing w, and the cloud droplet number concentration spectrum (CDNCS) narrows, which becomes the formation mechanism of the positive correlation between ε and w. Evaporation mainly causes a negative correlation between ε and Nc, but weak evaporation causes the correlation to become positive under the background of high aerosol concentration. At low aerosol concentrations, a strong collision–coalescence effect leads to a negative correlation between Nc and ε, but at high aerosol concentrations, the correlation is the opposite due to a weak collision–coalescence effect. Full article
(This article belongs to the Special Issue Atmospheric Ice Nucleating Particles, Cloud and Precipitation)
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