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Advanced Technologies in Satellite Observations

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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 (15 June 2022) | Viewed by 12618

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Special Issue Editors

Dr. Banghua Yan

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Guest Editor

Center for Satellite Applications and Research (STAR) in National Oceanic and Atmospheric Administration (NOAA), College Park, MD 20740, USA
Interests: satellite sensor data record (SDR) data calibration/validation; advanced microwave sounding unit-a (AMSU-A); ozone mapping and profiler suite (OMPS); inter-sensor calibration methodology; satellite data assimilation and applications; microwave surface emissivity modeling development

Prof. Dr. Knut Stamnes

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Guest Editor

School of Engineering and Science, Stevens Institute of Technology, Hoboken, NJ 07030, USA
Interests: radiative transfer theory and modeling; satellite remote sensing of the environment; algorithm development, machine learning, aerosol–cloud–radiation–climate interactions and feedbacks; atmospheric radiative energy balance and climate; numerical modeling of geophysical phenomena and comparison with measurements

Prof. Dr. Xiaobing Zhou

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Guest Editor

Department of Geological Engineering, Montana Technological University, Butte, MT 59701, USA
Interests: remote sensing theory; applied geophysics; instrumentation; algorithm development; image processing; applications in hydrology; ecology; snow and ice; environmental monitoring; geophysical mineral exploration
Special Issues, Collections and Topics in MDPI journals

Dr. Xiaozhen Xiong

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Guest Editor

Chemistry and Dynamics Branch, NASA Langley Research Center, Hampton, VA 23666, USA
Interests: radiative transfer modeling; retrieval algorithm development; sensor calibration; atmospheric sounding; trace gases; application of remote sensing products for weather, air quality and climate change studies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since the launch of the world's first meteorological satellite, Television Infrared Observation Satellite (TIROS), on April 1, 1960, meteorological satellites have experienced incredible improvements over the past 60 years. To date, hundreds of meteorological satellite instruments have been successfully launched into either Low Earth Orbit (LEO) or Geosynchronous Equatorial Orbit (GEO) to provide research or operational observations of the Earth’s atmospheric and surface properties. Sensor data records (SDR) from many satellite observations have been widely applied to various Environmental Data Record (EDR) product systems for retrievals of the Earth’s atmospheric and related surface parameters, the Numerical Weather Prediction (NWP) satellite data assimilation systems for weather and climate forecast, and for weather and climate studies, significantly improving NWP weather forecast skills and our understanding of the Earth’s atmosphere–surface system. Simultaneously, many advanced technologies have been developed for satellite observations. They have played and will continue to play a critical role in the success of satellite observation driven meteorology, weather forecasts, climate studies, and atmosphere–surface interaction studies.

Manuscripts solicited for this Special Issue are in research areas including, but not limited to, the following topics: 1) satellite instrumentation technologies (e.g., precipitation radars, microwave radiometers, infrared sounders, UV/VIS sounders, optical spectrometers, lighting sensors, or a hybrid of multi-sensor packages); 2) fundamental calibration technologies in relation to a specific sensor within the meteorological satellites; 3) satellite data inter-sensor calibration technogologies; 4) satellite instrument and observation data monitoring systems in near-real time mode; 5) satellite observation data record analysis for weather, environmental, or climate studies; 6) developments in radiative transfer modeling for satellite observations; 7) advanced retrieval algorithm development of atmospheric composition, meteorological parameters, or surface (land/ocean) properties from single or hybrid sensors of single or multiple satellites; 8) satellite data assimilation development in NWP. We also encourage review articles on new meteorological satellite missions in the LEO and/or GEO systems from the past through the future satellite observation technologies and on long-term satellite instrument and data (SDR and EDR) monitoring systems from multiple meteorological satellite platforms and instruments.

The scientific results and conclusions, as well as any views or opinions expressed herein, are those of the author(s) and do not necessarily reflect those of NOAA or the Department of Commerce.

Dr. Banghua Yan
Prof. Dr. Knut Stamnes
Dr. Xiaobing Zhou
Dr. Xiaozhen Xiong
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

satellite instrumention technologies
fundamental calibration technologies
satellite data inter-sensor calibration techogologies
satellite instrument and observation data monitoring systems in near-real time mode
satellite observation data record analysis for weather, environmental, or climate studies
developments in radiative transfer modeling for satellite observations
advanced retrieval algorithm development
satellite data assimilation development in NWP

Published Papers (7 papers)

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Research

26 pages, 11841 KiB

Open AccessArticle

Towards Space Deployment of the NDSA Concept for Tropospheric Water Vapour Measurements

by Luca Facheris, Andrea Antonini, Fabrizio Argenti, Flavio Barbara, Ugo Cortesi, Fabrizio Cuccoli, Samuele Del Bianco, Federico Dogo, Arjan Feta, Marco Gai, Anna Gregorio, Giovanni Macelloni, Agnese Mazzinghi, Samantha Melani, Francesco Montomoli, Alberto Ortolani, Luca Rovai, Luca Severin and Tiziana Scopa

Atmosphere 2023, 14(3), 550; https://doi.org/10.3390/atmos14030550 - 14 Mar 2023

Viewed by 1286

Abstract

A novel measurement concept specifically tuned to monitoring tropospheric water vapour’s vertical distribution has been demonstrated on a theoretical basis and is currently under development for space deployment. The NDSA (Normalised Differential Spectral Attenuation) technique derives the integrated water vapour (IWV) along the radio link between a transmitter and a receiver carried by two LEO satellites, using the linear correlation between the IWV and a parameter called spectral sensitivity. This is the normalised incremental ratio of the spectral attenuation at two frequencies in the Ku and K bands, with the slope of the water vapour absorption line at 22.235 GHz. Vertical profiles of WV can be retrieved by inverting a set of IWV measurements acquired in limb geometry at different tangent altitudes. This paper provides a comprehensive insight into the NDSA approach for sounding lower tropospheric WV, from the theoretical investigations in previous ESA studies, to the first experimental developments and testing, and to the latest advancements achieved with the SATCROSS project of the Italian Space Agency. The focus is on the new results from SATCROSS activities; primarily, on the upgrading of the instrument prototype, with improved performance in terms of its power stability and the time resolution of the measurements. Special emphasis is also placed on discussing tomographic inversion methods capable of retrieving tropospheric WV content from IWV measurements, i.e., the least squares and the external reconstruction approaches, showing results with different spatial features when applied to a given atmospheric scenario. The ultimate goal of deploying the NDSA measurement technique from space is thoroughly examined and conclusions are drawn after presenting the results of an Observing System Simulation Experiment conducted to assess the impact of NDSA data assimilation on environmental model simulations. Full article

(This article belongs to the Special Issue Advanced Technologies in Satellite Observations)

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16 pages, 6399 KiB

Open AccessArticle

Forecasting Maximum Mechanism Temperature in Advanced Technology Microwave Sounder (ATMS) Data Using a Long Short-Term Memory (LSTM) Neural Network

by Warren Dean Porter, Banghua Yan and Ninghai Sun

Atmosphere 2023, 14(3), 503; https://doi.org/10.3390/atmos14030503 - 04 Mar 2023

Viewed by 1333

Abstract

Among the monitored telemetry raw data record (RDR) parameters with the STAR Integrated/Validation System (ICVS), the Advanced Technology Microwave Sounder (ATMS) scan motor mechanism temperature is especially important because the instrument might be unavoidably damaged if the mechanism temperature exceeds 50 °C. In the current operational flight processing software, the instrument automatically enters safe mode and stops collecting scientific data whenever the mechanism temperature exceeds 40 °C. This approach inevitably leads to the instrument entering safe mode unnecessarily at a premature time, causing the loss of scientific data before the mechanism temperature reaches 50 °C. This study seeks to leverage the influence the main motor current, compensation motor current, and main motor loop integral error have on mechanism temperature to forecast the maximum mechanism temperature over the upcoming 6 min. A long short-term memory (LSTM) neural network predicts maximum mechanism temperature using ATMS RDR telemetry data as the input. The performance of the LSTM is compared with observed maximum mechanism temperatures by applying the LSTM coefficients to several cases. In all cases studied, the mean average error (MAE) of the forecast remained under 1.1 °C, and the correlation between forecasts and measurements remained above 0.96. These forecasts of maximum mechanism temperature are expected to be able to provide information on when the ATMS instrument should enter safe mode without needlessly losing valuable data for the ATMS flight operational team. Full article

(This article belongs to the Special Issue Advanced Technologies in Satellite Observations)

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15 pages, 7388 KiB

Open AccessArticle

Observed Atmospheric Features for the 2022 Hunga Tonga Volcanic Eruption from Joint Polar Satellite System Science Data Products

by Lihang Zhou, Banghua Yan, Ninghai Sun, Jingfeng Huang, Quanhua Liu, Christopher Grassotti, Yong-Keun Lee, William Straka III, Jianguo Niu, Amy Huff, Satya Kalluri and Mitch Goldberg

Atmosphere 2023, 14(2), 263; https://doi.org/10.3390/atmos14020263 - 28 Jan 2023

Cited by 2 | Viewed by 2104

Abstract

The Joint Polar Satellite System (JPSS) mission has provided over ten years of high-quality data products for environment forecasting and monitoring through the current Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites. Particularly, the sensor data record (SDR) and the derived environmental data record (EDR) products from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), the Advanced Technology Microwave Sounder (ATMS), and the Ozone Mapping and Profiler Suite (OMPS) offer an unprecedented opportunity to observe severe weather and environmental events over the Earth. This paper presents the observations about atmospheric features of the Hunga Tonga Volcanic eruption of January 2022, e.g., the gravity wave, volcanic cloud, and aerosol (sulfate) plume phenomena, by using the ATMS, CrIS, OMPS, and VIIRS SDR and EDR products. Powerful gravity waves ringing through the atmosphere after the eruption of the Hunga Tonga volcano are discovered at two CrIS upper sounding channels (670 cm⁻¹ and 2320 cm⁻¹) in the deviations of the observed brightness temperature (O) from the simulated baseline brightness temperature (B) using the Community Radiative Transfer Model (CRTM), i.e., O—B. A similar pattern is also observed in the ATMS global maps at channel 15, whose peak weighting function is around 40 km, showing the atmospheric disturbance caused by the eruption that reached 40 km above the surface. The Tonga volcanic cloud (plume) was also captured by the OMPS SO₂ EDR product. The gravity wave features were also captured in the native resolution image of the S-NPP VIIRS I-5 band nighttime observations. In addition, the VIIRS Aerosol Optical Depth (AOD) captured and tracked the volcanic aerosol (sulfate) plume successfully. These discoveries demonstrate the scientific potential of the JPSS SDR and EDR products in monitoring and tracking the eruption of the Hunga Tonga volcano and its severe environmental impacts. This paper presents the atmospheric features of the Hunga Tonga volcano eruption that is uniquely captured by all four advanced sensors onboard JPSS satellites, with different spectral coverages and spatial resolutions. Full article

(This article belongs to the Special Issue Advanced Technologies in Satellite Observations)

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11 pages, 2718 KiB

Open AccessArticle

Methodology and Case Study for Validation of Aircraft-Induced Clouds from Hyperspectral Imagery

by Amy Tal Rose, Lance Sherry and Donglian Sun

Atmosphere 2022, 13(8), 1257; https://doi.org/10.3390/atmos13081257 - 08 Aug 2022

Cited by 1 | Viewed by 1304

Abstract

Aircraft-Induced Clouds (AICs), colloquially called contrails, form from the emission of soot from jet engines during cruise flight in favorable atmospheric conditions. AICs absorb, scatter, and reflect shortwave and longwave radiation. This radiative transfer has a cooling effect during the day; however, the night experiences an overwhelming warming effect, which leads to an overall warming effect on Earth, contributing to anthropogenically propelled climate change. Reducing AICs significantly mitigates aviation’s contribution to climate change by reducing the disruption in Earth’s radiation budget. Researchers have proposed AIC Abatement Programs (AAPs) to increase cruise flight levels without additional fuel burn. In order to effectively implement AAPs, it is crucial to be able to accurately identify AICs from publicly available aerial and satellite imagery. This study aims at the identification of AICs from hyperspectral imagery to help the effective implementation of an AAP and to mitigate climate change. This paper describes a method for the hyperspectral analysis of aerial images in order to accurately identify AICs through a case study based in West Virginia. The results show that both the Adaptive Coherence Estimator and the Matched Filter algorithms based on unique in-scene spectra were successful in the isolation of the AICs from other cloud types and the background. It is found that AICs can be identified with 84% confidence in this case study. The method, a case study, and future works are provided. Full article

(This article belongs to the Special Issue Advanced Technologies in Satellite Observations)

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23 pages, 12565 KiB

Open AccessEditor’s ChoiceArticle

Impact of Stratosphere on Cold Air Outbreak: Observed Evidence by CrIS on SNPP and Its Comparison with Models

by Xiaozhen Xiong, Xu Liu, Wan Wu, K. Emma Knowland, Fanglin Yang, Qiguang Yang and Daniel K. Zhou

Atmosphere 2022, 13(6), 876; https://doi.org/10.3390/atmos13060876 - 28 May 2022

Cited by 5 | Viewed by 1826

Abstract

A cold air outbreak (CAO) is an extreme weather phenomenon that has significant social and economic impacts over a large region of the midlatitudes. However, the dynamical mechanism of the occurrence and evolution of CAO events, particularly the role of the stratosphere, is not well understood. Through an analysis of one extreme CAO episode that occurred on 27–31 January 2019 across much of the US Midwest, this study examined its thermodynamic structure and the impact of stratospheric downward transport using the single-field-view (SFOV) satellite products (with a spatial resolution of ~14 km at nadir) from the Cross-track Infrared Sounder (CrIS) onboard Suomi National Polar-Orbiting Partnership (SNPP) in conjunction with MERRA-2 and ERA-5 reanalysis products. It is found that along the path of cold air transport, particularly near the coldest surface center, there exists a large enhancement of O₃, deep tropopause folding, significant downward transport of stratospheric dry air, and a warm center above the tropopause. The upper warm center can be observed directly using the brightness temperature (BT) of CrIS stratospheric sounding channels. While similar large-scale patterns of temperature (T), relative humidity (RH), and ozone (O₃) are captured from CrIS, MERRA-2, and ERA-5 products, it is found that, in the regions impacted by CAO, MERRA-2 has a thicker dry layer under the tropopause (with the difference of RH up to ~10%) and the total column ozone (TCO) from ERA-5 has a relatively large positive bias of 2.8 ± 2.8% compared to that measured by Ozone Mapping and Profiler Suite (OMPS). This study provides some observational evidence from CrIS that confirm the impact of the stratosphere on CAO through downward transport and demonstrates the value of the SFOV retrieval products for CAO dynamic transport study and model evaluation. Full article

(This article belongs to the Special Issue Advanced Technologies in Satellite Observations)

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16 pages, 8574 KiB

Open AccessArticle

Retrieval of Soil Moisture from FengYun-3D Microwave Radiation Imager Operational and Recalibrated Data Using Random Forest Regression

by Chuanwen Wei, Fuzhong Weng, Shengli Wu, Dongli Wu and Peng Zhang

Atmosphere 2022, 13(4), 637; https://doi.org/10.3390/atmos13040637 - 18 Apr 2022

Cited by 2 | Viewed by 1808

Abstract

Three Microwave Radiation Imagers (MWRI) were carried onboard the FengYun-3B/C/D satellites and have collected more than 10 years of data since 2010. To create a robust climate quality of data, MWRI level one data were reprocessed with new calibration. This study evaluates the performance of retrieving global soil moisture from recalibrated MWRI data (RCD) and quantifies the difference of retrieved soil moisture between operational calibration data (OCD) and RCD. Soil Moisture Operational Products System (SMOPS) products from NOAA on four days of different seasons were collocated with MWRI brightness temperatures, and then the collocated data were used for training an algorithm through machine learning. The retrieved soil moisture products using OCD and RCD were evaluated against the independent SMOPS products, in situ networks and SMAP soil moisture product. It is shown that the algorithm from the random forest is suitable for FY-3D recalibrated MWRI data, with a coefficient of determination (R²) of 0.7223, a mean bias of −0.0062 and an unbiased root mean square difference (ubRMSD) of 0.0476 m³ m⁻³ compared with SMOPS products over the period from 12 July 2018 to 31 December 2019. The difference of retrieved soil moisture using OCD and RCD is spatially heterogeneous. Both temporal and spatial coverage and accuracy of the existing FY-3D operational soil moisture products are significantly improved. Full article

(This article belongs to the Special Issue Advanced Technologies in Satellite Observations)

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18 pages, 3408 KiB

Open AccessEditor’s ChoiceArticle

Spectral Recalibration of NOAA HIRS Longwave CO₂ Channels toward a 40+ Year Time Series for Climate Studies

by Bin Zhang, Changyong Cao, Tung-Chang Liu and Xi Shao

Atmosphere 2021, 12(10), 1317; https://doi.org/10.3390/atmos12101317 - 09 Oct 2021

Cited by 4 | Viewed by 1616

Abstract

The High-Resolution Infrared Radiation Sounder (HIRS) on NOAA and MetOp A/B satellites has been observing the Earth continuously for over four decades, providing essential data for operational numerical weather prediction, retrieval of atmospheric vertical profile, and total column information on atmospheric temperature, moisture, water vapor, ozone, cloud climatology, and other geophysical parameters globally. Although the HIRS data meets the needs of the short-term weather forecast, there are inconsistencies when the long-term decadal time series is used for time series analysis. The discrepancies are caused by several factors, including spectral response differences between the HIRS models on the satellites and spectral response uncertainties and other calibration issues. Previous studies have demonstrated that significant improvements can be achieved by recalibrating some of the HIRS longwave CO₂ channels (Channels 4, 5, 6, and 7), which has helped make the time series more consistent. The current study aims to extend the previous study to the remaining longwave infrared sounding channels, including Channels 1, 2, 3, and 8, using a similar approach. Similar to previous findings, the spectral shift of the HIRS bands has helped improve the consistency in the time series from NOAA-06 to MetOp-A and B for these channels. We also found that HIRS channels on MetOp-B also have bias relative to Infrared Atmospheric Sounding Interferometer (IASI) on the same satellite, especially Channel 4, and a spectral shift significantly reduced the bias. To bridge the observation gap in time series in the mid-1980s between NOAA-07 and NOAA-09, the global mean method has been used since no transfer radiometers between them was available for this period, and the spectral response function corrections, therefore, can be applied to the earliest satellites (NOAA-06) for these channels. The recalibration parameters have been provided to other scientists at the University of Wisconsin for improving the time series in their long-term studies using historical HIRS data and are now made available to the science community. Full article

(This article belongs to the Special Issue Advanced Technologies in Satellite Observations)

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