Aerosol–Cloud–Precipitation Interactions: From Weather to Climate

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

Deadline for manuscript submissions: closed (22 November 2021) | Viewed by 18459

Special Issue Editor

Department of Climate and Space Sciences and Engineering, University of Michigan, 2455 Hayward Street, Ann Arbor, MI, USA
Interests: cloud microphysics; precipitation; aerosol–cloud interaction; atmospheric radiation; atmospheric modelling

Special Issue Information

Dear Colleagues,

Aerosols are particles that suspend in the air and act as condensation nuclei on which cloud droplets/crystals are formed. Although aerosols are ubiquitous in the natural atmosphere of the Earth, human activities (e.g., fossil fuel burning) tend to inject extra aerosols or their predecessors to the atmosphere. The extra aerosols, with varying properties (e.g., loading, chemical composition, and size spectrum) and geographical locations, can remarkably alter the microphysical characteristics of clouds and their propensity to generate precipitation, which in turn affects not only the local weather characteristics such as rain intensity/frequency, but also the radiation budget and climate on larger scales.

However, great uncertainties still persist in the modelling of aerosol–cloud–precipitation interaction (ACPI) in both numerical weather prediction models and global climate models. Challenges arise largely from the broad span of scales: from sub-microns (aerosol chemistry and microphysics) to tens or hundreds of kilometers (weather/climate system). It therefore warrants more intensive cross-scale research efforts, from both the observational and modeling approaches, in order to disentangle the role of aerosols in affecting weather and climate.

This Special Issue is expected to focus on studies on ACPI on various spatial and temporal scales. We welcome research and review papers that represent the recent advances in the measuring and modelling of ACPI-associated processes. All studies that enhance our understanding of the mechanisms within, and the impacts from, ACPI are highly relevant to this Special Issue. Cross-scale studies that bridge the gap between the weather and climate effects of ACPI are especially welcome.

Dr. Xianwen Jing
Guest Editor

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Keywords

  • aerosol
  • aerosol–cloud–precipitation interaction
  • microphysics
  • weather and climate effects
  • observational investigation
  • model evaluation
  • model development

Published Papers (3 papers)

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Research

23 pages, 5541 KiB  
Article
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific
by Alexandre L. Correia, Marina M. Mendonça, Thiago F. Nobrega, Andre C. Pugliesi and Micael A. Cecchini
Atmosphere 2022, 13(1), 77; https://doi.org/10.3390/atmos13010077 - 02 Jan 2022
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Abstract
Geostationary satellites can retrieve the cloud droplet effective radius (re) but suffer biases from cloud inhomogeneities, internal retrieval nonlinearities, and 3-D scattering/shadowing from neighboring clouds, among others. A 1-D retrieval method was applied to Geostationary Operational Environmental Satellite 13 (GOES-13) [...] Read more.
Geostationary satellites can retrieve the cloud droplet effective radius (re) but suffer biases from cloud inhomogeneities, internal retrieval nonlinearities, and 3-D scattering/shadowing from neighboring clouds, among others. A 1-D retrieval method was applied to Geostationary Operational Environmental Satellite 13 (GOES-13) imagery, over large areas in South America (5 N–30 S; 2070 W), the Southeast Pacific (5 N–30 S; 70120 W), and the Amazon (2 N–7 S; 5473 W), for four months in each year from 2014–2017. Results were compared against in situ aircraft measurements and the Moderate Resolution Imaging Spectroradiometer cloud product for Terra and Aqua satellites. Monthly regression parameters approximately followed a seasonal pattern. With up to 108,009 of matchups, slope, intercept, and correlation for Terra (Aqua) ranged from about 0.71 to 1.17, −2.8 to 2.5 μm, and 0.61 to 0.91 (0.54 to 0.78, −1.5 to 1.8 μm, 0.63 to 0.89), respectively. We identified evidence for re overestimation (underestimation) correlated with shadowing (enhanced reflectance) in the forward (backscattering) hemisphere, and limitations to illumination and viewing configurations accessible by GOES-13, depending on the time of day and season. A proposition is hypothesized to ameliorate 3-D biases by studying relative illumination and cloud spatial inhomogeneity. Full article
(This article belongs to the Special Issue Aerosol–Cloud–Precipitation Interactions: From Weather to Climate)
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17 pages, 6101 KiB  
Article
The UAE Cloud Seeding Program: A Statistical and Physical Evaluation
by Taha Al Hosari, Abdulla Al Mandous, Youssef Wehbe, Abdeltawab Shalaby, Noor Al Shamsi, Hajer Al Naqbi, Omar Al Yazeedi, Alya Al Mazroui and Sufian Farrah
Atmosphere 2021, 12(8), 1013; https://doi.org/10.3390/atmos12081013 - 07 Aug 2021
Cited by 28 | Viewed by 13625
Abstract
Operational cloud seeding programs have been increasingly deployed in several countries to augment natural rainfall amounts, particularly over water-scarce and arid regions. However, evaluating operational programs by quantifying seeding impacts remains a challenging task subject to complex uncertainties. In this study, we investigate [...] Read more.
Operational cloud seeding programs have been increasingly deployed in several countries to augment natural rainfall amounts, particularly over water-scarce and arid regions. However, evaluating operational programs by quantifying seeding impacts remains a challenging task subject to complex uncertainties. In this study, we investigate seeding impacts using both long-term rain gauge records and event-based weather radar retrievals within the framework of the United Arab Emirates (UAE) National Center of Meteorology’s operational cloud seeding program. First, seasonal rain gauge records are inter-compared between unseeded (1981–2002) and seeded (2003–2019) periods, after which a posteriori target/control regression is developed to decouple natural and seeded rainfall time series. Next, trend analyses and change point detection are carried out over the July-October seeding periods using the modified Mann-Kendall (mMK) test and the Cumulative Sum (CUSUM) method, respectively. Results indicate an average increase of 23% in annual surface rainfall over the seeded target area, along with statistically significant change points detected during 2011 with decreasing/increasing rainfall trends for pre-/post-change point periods, respectively. Alternatively, rain gauge records over the control (non-seeded) area show non-significant change points. In line with the gauge-based statistical findings, a physical analysis using an archive of seeded (65) and unseeded (87) storms shows enhancements in radar-based storm properties within 15–25 min of seeding. The largest increases are recorded in storm volume (159%), area cover (72%), and lifetime (65%). The work provides new insights for assessing long-term seeding impacts and has significant implications for policy- and decision-making related to cloud seeding research and operational programs in arid regions. Full article
(This article belongs to the Special Issue Aerosol–Cloud–Precipitation Interactions: From Weather to Climate)
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18 pages, 3922 KiB  
Article
The Impact of Aerosol Vertical Distribution on a Deep Convective Cloud
by Minzhong Zhang, Xin Deng, Ruihao Zhu, Yangze Ren and Huiwen Xue
Atmosphere 2021, 12(6), 675; https://doi.org/10.3390/atmos12060675 - 25 May 2021
Cited by 8 | Viewed by 2063
Abstract
This study investigates the effects of aerosol vertical distribution on a deep convective cloud system. We intend to elucidate the mechanisms for aerosols entering the cloud from different heights, and how they affect cloud microphysics and precipitation. A thermal bubble is released at [...] Read more.
This study investigates the effects of aerosol vertical distribution on a deep convective cloud system. We intend to elucidate the mechanisms for aerosols entering the cloud from different heights, and how they affect cloud microphysics and precipitation. A thermal bubble is released at 1.5 km initially to run an idealized case using the Weather Research and Forecast (WRF) model. The aerosol layer with high concentration was initially put at different altitudes in the model to study the mechanisms and the number of aerosols entering the cloud. It was found that there are three mechanisms for aerosols from different heights to enter the cloud, depending on their relative height with the thermal bubble. Aerosols from lower altitudes (below 1 km) enter the cloud through pumping, while aerosols from higher altitudes (2–3 km, 3–5 km) enter the cloud through entrainment. Both mechanisms lead to low cloud condensation nuclei (CCN) concentration in the cloud. Only aerosols from intermediate altitudes (1–2 km), which is the same as the initial height of the thermal bubble, enter the cloud mainly by ascending with the bubble and lead to high CCN concentration in the cloud. The differences in activated CCN concentration affect the microphysical processes and precipitation remarkably. For the simulations with an initial aerosol layer at 1–2 km and 0–5 km, aerosols can enter the cloud more efficiently than the other four simulations. More activated CCNs in these two simulations lead to more graupels with smaller sizes at higher altitudes, which delays the precipitation but makes the precipitation last longer. However, the accumulated precipitation is similar in all six simulations, no matter what aerosol vertical distribution is like. The results in this study indicate that the altitude of aerosol layers determines the mechanisms for aerosols entering clouds, CCN concentration in the cloud, and to what extent the cloud microphysical processes and precipitation are affected. Full article
(This article belongs to the Special Issue Aerosol–Cloud–Precipitation Interactions: From Weather to Climate)
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