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Clouds, Circulation and Climate Sensitivity Supported by Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (25 March 2022) | Viewed by 2616

Special Issue Editors


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Guest Editor
NOAA/AOML Hurricane Research Division, Miami, FL 33149, USA
Interests: cloud microphysics; hurricanes; tropical meteorology
Special Issues, Collections and Topics in MDPI journals
School of Meteorology, The University of Oklahoma, Norman, OK, USA
Interests: aerosol and cloud remote sensing; atmospheric radiation; light scattering by small particles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Atmospheric remote sensing has been used for decades, first with Radar, then with IR sensors, profilers, LIDAR, etc. Drones are also being used to measure environmental parameters where aircraft cannot easily go. Cloud microphysical properties are a particularly difficult problem for remote observations. Some advances have been made using differential radar reflectivity and polarization diversity measurements, and limb measurements from satellites can now make inferences about the water and ice content of clouds. All of these techniques have shown promise, but the schemes still need to be calibrated against in-situ measurements, which are often scarce. Still, efforts continue to make use of these techniques to probe clouds, many of which will appear in the pages of this Journal. To that end, we invite researchers to send manuscripts that touch on any of these topics to be considered in Journal of Remote Sensing.

Dr. Robert A. Black
Dr. Feng Xu
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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

  • radar
  • Lidar
  • Satellite methods
  • profiler
  • cloud circulation
  • climate change

Published Papers (1 paper)

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Research

11 pages, 4040 KiB  
Communication
Application of M5 Model Tree in Passive Remote Sensing of Thin Ice Cloud Microphysical Properties in Terahertz Region
by Pingyi Dong, Lei Liu, Shulei Li, Shuai Hu and Lingbing Bu
Remote Sens. 2021, 13(13), 2569; https://doi.org/10.3390/rs13132569 - 30 Jun 2021
Cited by 3 | Viewed by 1860
Abstract
This article presents a new method for retrieving the Ice Water Path (IWP), the median volume equivalent sphere diameter (Dme) of thin ice clouds (IWP < 100 g/m2, Dme < 80 μm) in the Terahertz band. The upwelling [...] Read more.
This article presents a new method for retrieving the Ice Water Path (IWP), the median volume equivalent sphere diameter (Dme) of thin ice clouds (IWP < 100 g/m2, Dme < 80 μm) in the Terahertz band. The upwelling brightness temperature depressions caused by the ice clouds at 325.15, 448.0, 664.0 and 874.0 GHz channels are simulated by the Atmospheric Radiative Transfer Simulator (ARTS). The simulated forward radiative transfer models are taken as historical data for the M5 model tree algorithm to construct a set of piecewise functions which represent the relation of simulated brightness temperature depressions and IWP. The inversion results are optimized by an empirical relation of the IWP and the Dme for thin ice clouds which is summarized by previous studies. We inverse IWP and Dme with the simulated brightness temperature and analyze the inversion performance of selected channels. The 874.4 ± 6.0 GHz channel provides the most accurate results, because of the strong brightness temperature response to the change of IWP in the forward radiative transfer model. In order to improve the thin ice clouds IWP and Dme retrieval accuracy at the middle-high frequency channels in Terahertz band, a dual-channel inversion method was proposed that combines the 448.0± 3.0 GHz and 664.0 ± 4.2 GHz channel. The error analysis shows that the results of the 874.4 ± 6.0 GHz channel and the dual-channel inversion are reliable, and the IWP inversion results meet the error requirement range proposed by previous studies. Full article
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