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Atmosphere
Special Issues
Cloud Remote Sensing: Current Status and Perspective
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Cloud Remote Sensing: Current Status and Perspective

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

Deadline for manuscript submissions: 31 January 2025 | Viewed by 4557

Special Issue Editors

Dr. Alexander Kokhanovsky

E-Mail Website
Guest Editor
Max Planck Institute for Chemistry, 55128 Mainz, Germany
Interests: cloud remote sensing; aerosol remote sensing; trace gas remote sensing; snow remote sensing; radiative transfer
Special Issues, Collections and Topics in MDPI journals
Dr. Luca Lelli

E-Mail Website
Guest Editor
1. Remote Sensing Technology Institute, Atmospheric Processors, German Aerospace Centre (DLR), Oberpfaffenhofen, 82234 Wessling, Germany
2. Department of Physics, Institute of Environmental Physics, University Bremen, 28359 Bremen, Germany
Interests: clouds; aerosols; atmospheric composition; radiative transfer; time series analysis; trend detection; climate data records; climate networks
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Daniel Rosenfeld

E-Mail Website
Guest Editor
Program of Atmospheric Sciences, Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
Interests: cloud remote sensing; atmospheric radiative transfer; climatic effects of cloudiness
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Clouds are composed of liquid water droplets, ice crystals or a mixture of the two. Clouds with mixtures of ice particles and cloud droplets also occur. Clouds are inherently inhomogeneous media with inhomogeneity both in the vertical and horizontal directions. Therefore, theoretical studies on radiation transport in clouds (e.g., clouds of various shapes) are performed using the 3D radiative transfer theory. Accounting for 3D effects and cloud vertical inhomogeneity is critical in modern cloud remote sensing. In addition, the modelling of light-scattering properties of irregular ice crystals and effects of possible cloud pollution via various impurities (e.g., dust, smoke, volcanic eruptions) is at the frontier of modern cloud research and remote sensing.

Because clouds play an important role in the water cycle, atmospheric radiative transfer, weather prediction and climate change, they have been thoroughly studied using ground-based, shipborne, airborne and satellite instrumentation operating from the optical to thermal and microwave spectral ranges.

This Special Issue is focused on the latest developments in cloud remote sensing. We therefore invite papers on the following areas:

  • Ground-based cloud remote sensing;
  • Satellite cloud remote sensing;
  • Airborne cloud remote sensing;
  • Remote sensing of clouds using optical and thermal infrared techniques;
  • Microwave remote sensing of clouds;
  • Multi-angular cloud polarimetry;
  • Radiative transfer in clouds;
  • Light scattering by ice crystals and mixed-phase clouds;
  • Radiative properties of polluted and mixed phase clouds;
  • Radiative properties of hurricanes.

You may choose our Joint Special Issue in Remote Sensing.

Dr. Alexander Kokhanovsky
Dr. Luca Lelli
Prof. Dr. Daniel Rosenfeld
Guest Editors

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

  • clouds
  • hurricanes
  • precipitation
  • cloud pollution
  • remote sensing
  • radiative transfer
  • light scattering
  • atmospheric ice crystals

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

13 pages, 3786 KiB  
Article
Characteristics of the Evolution of Precipitation Particles during a Stratiform Precipitation Event in Liupan Mountains
by Yujun Qiu, Nansong Feng, Ying He, Rui Xu and Danning Zhao
Atmosphere 2024, 15(6), 732; https://doi.org/10.3390/atmos15060732 - 19 Jun 2024
Viewed by 616
Abstract
This study utilizes comprehensive observational data from a stratiform mixed-cloud precipitation event in Liupan Mountains, combined with ground-based millimeter-wave cloud radar (CR), micro rain radar (MRR), and microwave radiometer (MR) data, to study the evolution characteristics and conversion efficiency of precipitation particles in [...] Read more.
This study utilizes comprehensive observational data from a stratiform mixed-cloud precipitation event in Liupan Mountains, combined with ground-based millimeter-wave cloud radar (CR), micro rain radar (MRR), and microwave radiometer (MR) data, to study the evolution characteristics and conversion efficiency of precipitation particles in the ice–water mixed layer, melting layer, and below these layers during the formation and dissipation of precipitation. The results show the following: (1) When precipitation particles occupy more than 20% of cloud layers detected by cloud radar, the ice–water mixed cloud layer descends and evolves into a precipitating cloud. (2) During surface precipitation periods, the proportion of raindrops forming precipitation was equivalent to that of small-scale precipitation particles in the cloud layers. The proportion of precipitation particles in the cloud layers with temperatures below 0 °C averaged 25%. Ice-phase particles within the bright band (BB) melted, coalesced, and grew into larger precipitation particles, increasing their proportion to 55%. (3) After surface precipitation ended, the water content and precipitation rate of the cloud layer were 60% and 52% of those during the precipitation process, respectively. The proportion of small-scale precipitation particles in the cloud layers was approximately half of that during the precipitation period. A large number of evaporated small-scale precipitation particles floated in the air layer below the clouds, occupying less than 6.0% of the cloud layers. Full article
(This article belongs to the Special Issue Cloud Remote Sensing: Current Status and Perspective)
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16 pages, 7952 KiB  
Article
Cloud Characteristics in South China Using Ka-Band Millimeter Cloud Radar Datasets
by Haowen Li, Chengyan Mao, Huaiyu Li, Jieyi Li, Binghong Chen, Lin Zeng, Jiawen Zheng and Mingtuan Liu
Atmosphere 2024, 15(4), 486; https://doi.org/10.3390/atmos15040486 - 15 Apr 2024
Viewed by 1244
Abstract
In this study, we investigate the seasonal and diurnal variations in cloud occurrence frequency, as well as cloud vertical structure (CVS) characteristics under different seasons and precipitation intensities over the Guangzhou region in South China, based on the analysis of millimeter-wave cloud radar [...] Read more.
In this study, we investigate the seasonal and diurnal variations in cloud occurrence frequency, as well as cloud vertical structure (CVS) characteristics under different seasons and precipitation intensities over the Guangzhou region in South China, based on the analysis of millimeter-wave cloud radar (MMCR) and ground automatic weather station rainfall observations from May 2019 to August 2021. The results showed that the occurrence frequency of clouds exhibits a bimodal distribution throughout the year, with peaks in March to June and October, reaching its highest occurrence in May at approximately 80% and its lowest from December to February at around 40%. Additionally, there are distinct diurnal variations in occurrence frequency, with the lowest rates occurring around 0005 LST, rapidly increasing after 0006 LST, and peaking during the afternoon to evening hours. Cloud top height (CTH) shows bimodal distributions during the pre-flood and post-flood seasons. The most frequently occurring range of CTH during the pre-flood season is below 3 km, accounting for approximately 43%, while during the post-flood season, it ranges from 11 to 14 km, constituting about 37%. For precipitation clouds, CTH can extend beyond 12 km, with the radar reflectivity decreasing gradually with increasing height. The highest frequencies of radar echoes are observed below 2 km and between 4 and 7 km, exhibiting clear diurnal variations, with echoes mainly below 2 km and between 4 to 6 km during the early morning, intensifying and shifting to higher altitudes during the day and reaching their maximum below 4 km during the afternoon to nighttime hours, while both the frequency and intensity increase in the height range of 4 to 12 km. Vertical profiles of radar reflectivity and cloud ice/liquid water content (IWC/LWC) exhibit similar trends under different precipitation intensities. The main differences are observed below 4 km, where both radar reflectivity and IWC/LWC generally increase with increasing precipitation intensity. These findings contribute to a better understanding of cloud characteristics in the South China region, enhance the accuracy of model simulations, and provide a scientific basis for accurate forecasting and warning of meteorological disasters. Full article
(This article belongs to the Special Issue Cloud Remote Sensing: Current Status and Perspective)
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21 pages, 4985 KiB  
Article
The Spatio-Temporal Cloud Frequency Distribution in the Galapagos Archipelago as Seen from MODIS Cloud Mask Data
by Samira Zander, Nazli Turini, Daniela Ballari, Steve Darwin Bayas López, Rolando Celleri, Byron Delgado Maldonado, Johanna Orellana-Alvear, Benjamin Schmidt, Dieter Scherer and Jörg Bendix
Atmosphere 2023, 14(8), 1225; https://doi.org/10.3390/atmos14081225 - 29 Jul 2023
Viewed by 1651
Abstract
Clouds play an important role in the climate system; nonetheless, the relationship between climate change in general and regional cloud occurrence is not yet well understood. This particularly holds for remote areas such as the iconic Galapagos archipelago in Ecuador. As a first [...] Read more.
Clouds play an important role in the climate system; nonetheless, the relationship between climate change in general and regional cloud occurrence is not yet well understood. This particularly holds for remote areas such as the iconic Galapagos archipelago in Ecuador. As a first step towards a better understanding, we analyzed the spatio-temporal patterns of cloud cover over Galapagos. We found that cloud frequency and distribution exhibit large inter- and intra-annual variability due to the changing influence of climatic drivers (trade winds, sea surface temperature, El Niño/La Niña events) and spatial variations due to terrain characteristics and location within the archipelago. The highest cloud frequencies occur in mid-elevations on the slopes exposed to the southerly trade winds (south-east slopes). Towards the highlands ( >900 m a.s.l), cloud frequency decreases, with a sharp leap towards high-level crater areas mainly on Isabela Island that frequently immerse into the trade inversion layer. With respect to the diurnal cycle, we found a lower cloud frequency over the islands in the evening than in the morning. Seasonally, cloud frequency is higher during the hot season (January–May) than in the cool season (June–December). However, spatial differences in cloudiness were more pronounced during the cool season months. We further analyzed two periods beyond average atmospheric forcing. During El Niño 2015, the cloud frequency was higher than usual, and differences between altitudes and aspects were less pronounced. La Niña 2007 led to negative anomalies in cloud frequency over the islands, with intensified differences between altitude and aspect. Full article
(This article belongs to the Special Issue Cloud Remote Sensing: Current Status and Perspective)
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