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Atmosphere
Special Issues
Developing Algorithms and Software Tools to Retrieve Atmospheric Composition
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Developing Algorithms and Software Tools to Retrieve Atmospheric Composition

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

Deadline for manuscript submissions: closed (12 April 2021) | Viewed by 9946

Special Issue Editor

Dr. Anu Dudhia

E-Mail Website
Guest Editor
Department of Physics, University of Oxford, Parks Rd, Oxford OX1 3PU, UK
Interests: Atmospheric composition; remote sensing; retrieval algorithm

Special Issue Information

Dear Colleagues,

In the past two decades a large number satellite instruments have been flown with the aim of retrieving atmospheric composition. These have used a variety of viewing geometries and spectral ranges, each with their own particular characteristics, advantages and difficulties.

For this special issue we would like to compile descriptions of the retrieval algorithms used for these instruments, not at a detailed ATBD level but with sufficient information to allow different methods to be compared and to guide those designing future missions.

In particular we would like an emphasis on solutions adopted for particular problems, both anticipated and unanticipated, and lessons learned for instrument design.

The generally accepted equations for radiative transfer and inverse methods need not detailed. Specific examples of retrieved profiles may be included to illustrate retrieval characteristics but this special issue is not intended to include validation.  A length of 10 pages is suggested.

In addition we would welcome short papers addressing particular issues which may be have been confined to internal technical documents but could be of wider interest.

Dr. Anu Dudhia
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

  • atmospheric composition
  • remote sensing
  • retrieval algorithm

Published Papers (4 papers)

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Research

21 pages, 6042 KiB  
Article
Line-of-Sight Winds and Doppler Effect Smearing in ACE-FTS Solar Occultation Measurements
by Chris D. Boone, Johnathan Steffen, Jeff Crouse and Peter F. Bernath
Atmosphere 2021, 12(6), 680; https://doi.org/10.3390/atmos12060680 - 26 May 2021
Cited by 4 | Viewed by 2630
Abstract
Line-of-sight wind profiles are derived from Doppler shifts in infrared solar occultation measurements from the Atmospheric Chemistry Experiment Fourier transform spectrometers (ACE-FTS), the primary instrument on SCISAT, a satellite-based mission for monitoring the Earth’s atmosphere. Comparisons suggest a possible eastward bias from 20 [...] Read more.
Line-of-sight wind profiles are derived from Doppler shifts in infrared solar occultation measurements from the Atmospheric Chemistry Experiment Fourier transform spectrometers (ACE-FTS), the primary instrument on SCISAT, a satellite-based mission for monitoring the Earth’s atmosphere. Comparisons suggest a possible eastward bias from 20 m/s to 30 m/s in ACE-FTS results above 80 km relative to some datasets but no persistent bias relative to other datasets. For instruments operating in a limb geometry, looking through a wide range of altitudes, smearing of the Doppler effect along the line of sight can impact the measured signal, particularly for saturated absorption lines. Implications of Doppler effect smearing are investigated for forward model calculations and volume mixing ratio retrievals. Effects are generally small enough to be safely ignored, except for molecules having a large overhang in their volume mixing ratio profile, such as carbon monoxide. Full article
(This article belongs to the Special Issue Developing Algorithms and Software Tools to Retrieve Atmospheric Composition)
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14 pages, 3394 KiB  
Article
Evaluation and Improvement of the Quality of Ground-Based Microwave Radiometer Clear-Sky Data
by Qing Li, Ming Wei, Zhenhui Wang and Yanli Chu
Atmosphere 2021, 12(4), 435; https://doi.org/10.3390/atmos12040435 - 28 Mar 2021
Cited by 3 | Viewed by 1953
Abstract
To assess the quality of the retrieved products from ground-based microwave radiometers, the “clear-sky” Level-2 data (LV2) products (profiles of atmospheric temperature and humidity) filtered through a radiometer in Beijing during the 24 months from January 2010 to December 2011 were compared with [...] Read more.
To assess the quality of the retrieved products from ground-based microwave radiometers, the “clear-sky” Level-2 data (LV2) products (profiles of atmospheric temperature and humidity) filtered through a radiometer in Beijing during the 24 months from January 2010 to December 2011 were compared with radiosonde data. Evident differences were revealed. Therefore, this paper investigated an approach to calibrate the observed brightness temperatures by using the model-simulated brightness temperatures as a reference under clear-sky conditions. The simulation was completed with a radiative transfer model and National Centers for Environmental Prediction final analysis (NCEP FNL) data that are independent of the radiometer system. Then, the least-squares method was used to invert the calibrated brightness temperatures to the atmospheric temperature and humidity profiles. A comparison between the retrievals and radiosonde data showed that the calibration of the brightness temperature observations is necessary, and can improve the inversion of temperature and humidity profiles compared with the original LV2 products. Specifically, the consistency with radiosonde was clearly improved: the correlation coefficients are increased, especially, the correlation coefficient for water vapor density increased from 0.2 to 0.9 around the 3 km height; the bias decreased to nearly zero at each height; the RMSE (root of mean squared error) for temperature profile was decreased by more than 1 degree at most heights; the RMSE for water vapor density was decreased from greater than 4 g/m3 to less than 1.5 g/m3 at 1 km height; and the decrease at all other heights were also noticeable. In this paper, the evolution of a temperature inversion process is given as an example, using the high-temporal-resolution brightness temperature after quality control to obtain a temperature and humidity profile every two minutes. Therefore, the characteristics of temperature inversion that cannot be seen by conventional radiosonde data (twice daily) were obtained by radiometer. This greatly compensates for the limited temporal coverage of radiosonde data. The approach presented by this paper is a valuable reference for the reprocessing of the historical observations, which have been accumulated for years by less-calibrated radiometers. Full article
(This article belongs to the Special Issue Developing Algorithms and Software Tools to Retrieve Atmospheric Composition)
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24 pages, 9174 KiB  
Article
The Significance of Fast Radiative Transfer for Hyperspectral SWIR XCO2 Retrievals
by Peter Somkuti, Hartmut Bösch and Robert J. Parker
Atmosphere 2020, 11(11), 1219; https://doi.org/10.3390/atmos11111219 - 12 Nov 2020
Cited by 1 | Viewed by 2434
Abstract
Fast radiative transfer (RT) methods are commonplace in most algorithms which retrieve the column-averaged dry-mole fraction of carbon dioxide (XCO2) in the Earth’s atmosphere. These methods are required to keep the computational effort at a manageable level and to allow for [...] Read more.
Fast radiative transfer (RT) methods are commonplace in most algorithms which retrieve the column-averaged dry-mole fraction of carbon dioxide (XCO2) in the Earth’s atmosphere. These methods are required to keep the computational effort at a manageable level and to allow for operational processing of tens of thousands of measurements per day. Without utilizing any fast RT method, the involved computation times would be one to two orders of magnitude larger. In this study, we investigate three established methods within the same retrieval algorithm, and for the first time, analyze the impact of the fast RT method while keeping every other aspect of the algorithm the same. We perform XCO2 retrievals on measurements from the OCO-2 instrument and apply quality filters and parametric bias correction. We find that the central 50% of scene-by-scene differences in XCO2 between retrieval sets, after threshold filtering and bias correction, that use different fast RT methods, are less than 0.40 ppm for land scenes, and less than 0.11 ppm for ocean scenes. Significant regional differences larger than 0.3 ppm are observed and further studies with larger samples and regional-scale subsets need to be undertaken to fully understand the impact on applications that utilize space-based XCO2. Full article
(This article belongs to the Special Issue Developing Algorithms and Software Tools to Retrieve Atmospheric Composition)
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19 pages, 7365 KiB  
Article
First Spaceborne Version of Velocity-Azimuth Display Technique for Wind Field Retrieval on Cloud and Precipitation Radar
by Yuexia Wang, Ming Wei and Quan Shi
Atmosphere 2020, 11(10), 1089; https://doi.org/10.3390/atmos11101089 - 13 Oct 2020
Cited by 2 | Viewed by 2233
Abstract
Cloud and precipitation radar mounted on a polar orbiting satellite opens up a new opportunity for global wind observation to improve numerical weather forecasting and prevent weather disasters. However, no related works have been done to retrieve the wind field for spaceborne cloud [...] Read more.
Cloud and precipitation radar mounted on a polar orbiting satellite opens up a new opportunity for global wind observation to improve numerical weather forecasting and prevent weather disasters. However, no related works have been done to retrieve the wind field for spaceborne cloud and precipitation radar. This is mainly because the high-speed motion of satellites makes wind field retrieval complex. This paper developed the first spaceborne version of the velocity–azimuth display (VAD) technique for wind field retrieval, which was originally created for ground-based radar. After derivation of VAD for spaceborne radar, we found that the product of the azimuth of the radar beam and its first harmonic was introduced into the Fourier series of radar radial velocity due to the motion of the satellites. The wind retrieval equations were developed by considering the effects of satellite motion and conical scanning strategy of radar. Numerical simulations of the spaceborne radar showed that the proposed VAD method provided a mean vertical profile of the horizontal wind with high vertical resolution over a large observation swath. Validations on airborne radar data with the same conical scan strategy as the spaceborne radar were carried out to capture the average wind structure in one hurricane event. The real data results demonstrated that the wind-retrieved results by the proposed method were consistent with the ground truth data, indicating the potential use of our proposal for spaceborne radar. Full article
(This article belongs to the Special Issue Developing Algorithms and Software Tools to Retrieve Atmospheric Composition)
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