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Remote Sensing of the Atmospheric Boundary Layer
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Remote Sensing of the Atmospheric Boundary Layer

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

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 38733

Special Issue Editors

Prof. Dr. Joachim Reuder

E-Mail Website
Guest Editor
Geophysical Institute & Bergen Offshore Wind Centre, University of Bergen, N-5007 Bergen, Norway
Interests: development and application of UAS for atmospheric measurements; boundary layer meteorology; turbulence; wind energy meteorology; renewable energy and energy transition; polar meteorology
Special Issues, Collections and Topics in MDPI journals
Prof. Phillip Chilson

E-Mail Website
Guest Editor
School of Meteorology & Atmospheric Radar Research Center, University of Oklahoma 120 David L. Boren Blvd, Norman, OK 73072-7307, USA
Interests: atmospheric boundary layer; aeroecology; unmanned aircraft systems; radar meteorology

Special Issue Information

Dear Colleagues,

Active and passive remote sensing methods (e.g., sodar, lidar, radar, scintillometry, radiometry, and spectroscopy) have a long history of being used to better understand and characterize the structure and dynamics of the atmospheric boundary layer (ABL). The spatial scales observed using remote sensors span from meso- and sub-meso-scale phenomena (fronts and severe storms and precipitation; over local scale effects (wind turbine wakes and urban and orographic forcings); down to the characterization of small-scale atmospheric turbulence. We aim to compile a Special Issue that highlights the latest development in active and passive remote sensing technology applied to ABL studies. The Special Issue should serve as a medium to present and discuss both potential and challenges for future research in this area. A representative but not exhaustive selection of topics to be covered is given below. If you doubt whether your intended manuscript will fit under this Special Issue, please contact us in advance:

  • ABL wind profiling by sodar, lidar, and radar
  • 3D wind field evaluation by multiple scanning lidar and radar systems
  • Characterization of BL clouds and precipitation by radar
  • ABL scintillometry
  • Temperature and humidity profiling by passive microwave radiometry and spectroscopy
  • Acoustic tomography of the ABL
  • Field campaigns using active and/or passive remote sensing
  • Validation of remote sensing (e.g., against masts, radiosoundings, manned or unmanned aircraft)
Prof. Dr. Joachim Reuder
Prof. Phillip Chilson
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

  • Boundary layer profiling
  • Boundary layer turbulence
  • Lidar
  • Sodar
  • Radar
  • Passive microwave radiometry
  • Acoustic tomography
  • Field campaigns
  • Validation of remote sensing data

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Published Papers (7 papers)

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Research

Jump to: Review, Other

18 pages, 8441 KiB  
Article
Random Sample Fitting Method to Determine the Planetary Boundary Layer Height Using Satellite-Based Lidar Backscatter Profiles
by Lin Du, Ya’ni Pan and Wei Wang
Remote Sens. 2020, 12(23), 4006; https://doi.org/10.3390/rs12234006 - 7 Dec 2020
Cited by 5 | Viewed by 3037
Abstract
The planetary boundary layer height (PBLH) is the atmospheric region closest to the earth’s surface and has important implications on weather forecasting, air quality, and climate research. However, lidar-based methods traditionally used to determine PBLH—such as the ideal profile fitting method (IPF), maximum [...] Read more.
The planetary boundary layer height (PBLH) is the atmospheric region closest to the earth’s surface and has important implications on weather forecasting, air quality, and climate research. However, lidar-based methods traditionally used to determine PBLH—such as the ideal profile fitting method (IPF), maximum gradient method, and wavelet covariance transform—are not only heavily influenced by cloud layers, but also rely heavily on a low signal-to-noise ratio (SNR). Therefore, a random sample fitting (RANSAF) method was proposed for PBLH detection based on combining the random sampling consensus and IPF methods. According to radiosonde measurements, the testing of simulated and satellite-based signals shows that the proposed RANSAF method can reduce the effects of the cloud layer and significantly fluctuating noise on lidar-based PBLH detection better than traditional algorithms. The low PBLH bias derived by the RANSAF method indicates that the improved algorithm has a superior performance in measuring PBLH under a low SNR or when a cloud layer exists where the traditional methods are mostly ineffective. The RANSAF method has the potential to determine regional PBLH on the basis of satellite-based lidar backscatter profiles. Full article
(This article belongs to the Special Issue Remote Sensing of the Atmospheric Boundary Layer)
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23 pages, 4012 KiB  
Article
Tailored Algorithms for the Detection of the Atmospheric Boundary Layer Height from Common Automatic Lidars and Ceilometers (ALC)
by Simone Kotthaus, Martial Haeffelin, Marc-Antoine Drouin, Jean-Charles Dupont, Sue Grimmond, Alexander Haefele, Maxime Hervo, Yann Poltera and Matthias Wiegner
Remote Sens. 2020, 12(19), 3259; https://doi.org/10.3390/rs12193259 - 7 Oct 2020
Cited by 32 | Viewed by 4818
Abstract
A detailed understanding of atmospheric boundary layer (ABL) processes is key to improve forecasting of pollution dispersion and cloud dynamics in the context of future climate scenarios. International networks of automatic lidars and ceilometers (ALC) are gathering valuable data that allow for the [...] Read more.
A detailed understanding of atmospheric boundary layer (ABL) processes is key to improve forecasting of pollution dispersion and cloud dynamics in the context of future climate scenarios. International networks of automatic lidars and ceilometers (ALC) are gathering valuable data that allow for the height of the ABL and its sublayers to be derived in near real time. A new generation of advanced methods to automatically detect the ABL heights now exist. However, diversity in ALC models means these algorithms need to be tailored to instrument-specific capabilities. Here, the advanced algorithm STRATfinder is presented for application to high signal-to-noise ratio (SNR) ALC observations, and results are compared to an automatic algorithm designed for low-SNR measurements (CABAM). The two algorithms are evaluated for application in an operational network setting. Results indicate that the ABL heights derived from low-SNR ALC have increased uncertainty during daytime deep convection, while high-SNR observations can have slightly reduced capabilities in detecting shallow nocturnal layers. Agreement between the ALC-based methods is similar when either is compared to the ABL heights derived from temperature profile data. The two independent methods describe very similar average diurnal and seasonal variations. Hence, high-quality products of ABL heights may soon become possible at national and continental scales. Full article
(This article belongs to the Special Issue Remote Sensing of the Atmospheric Boundary Layer)
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23 pages, 6000 KiB  
Article
Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar
by Ruijun Dang, Yi Yang, Hong Li, Xiao-Ming Hu, Zhiting Wang, Zhongwei Huang, Tian Zhou and Tiejun Zhang
Remote Sens. 2019, 11(3), 263; https://doi.org/10.3390/rs11030263 - 29 Jan 2019
Cited by 32 | Viewed by 6714
Abstract
Accurate estimation of the atmospheric boundary layer height (ABLH) is critically important and it mainly relies on the detection of the vertical profiles of atmosphere variables (temperature, humidity,’ and horizontal wind speed) or aerosols. Aerosol Lidar is a powerful remote sensing instrument frequently [...] Read more.
Accurate estimation of the atmospheric boundary layer height (ABLH) is critically important and it mainly relies on the detection of the vertical profiles of atmosphere variables (temperature, humidity,’ and horizontal wind speed) or aerosols. Aerosol Lidar is a powerful remote sensing instrument frequently used to retrieve ABLH through the detection of the vertical distribution of aerosol concentration. A challenge is that cloud, residual layer (RL), and local signal structure seriously interfere with the lidar measurement of ABLH. A new objective technique presenting as giving a top limiter altitude is introduced to reduce the interference of RL and cloud layer on ABLH determination. Cloud layers are identified by looking for the rapid increase and sharp attenuation of the signal combined with the relative increase in the signal. The cloud layers whether they overlay the ABL are classified or are decoupled from the ABL are classified by analyzing the continuity of the signal below the cloud base. For cloud layer capping of the ABL, the limiter is determined to be the altitude where a positive signal gradient first occurs above the cloud upper edge. For a cloud that is decoupled from the ABL, the cloud base is considered to be the altitude limiter. For RL in the morning, the altitude limiter is the greatest positive gradient altitude below the RL top. The ABLH will be determined below the top limiter altitude using Haar wavelet (HM) and the curve fitting method (CFM). Besides, the interference of local signal noise is eliminated through consideration of the temporal continuity. While comparing the lidar-determined ABLH by HM (or CFM) and nearby radiosonde measurements of the ABLH, a reasonable concordance is found with a correlation coefficient of 0.94 (or 0.96) and 0.79 (or 0.74), presenting a mean of the relative absolute differences with respect to radiosonde measurements of 10.5% (or 12.3%) and 22.3% (or 17.2%) for cloud-free and cloudy situations, respectively. The diurnal variations in the ABLH determined from HM and CFM on four selected cases show good agreement with a mean correlation coefficient higher than 0.99 and a mean absolute bias of 0.22 km. Also, the determined diurnal ABLH are consistent with surface turbulent kinetic energy (TKE) combined with the time-height distribution of the equivalent potential temperature. Full article
(This article belongs to the Special Issue Remote Sensing of the Atmospheric Boundary Layer)
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12 pages, 4697 KiB  
Article
Measurement of Planetary Boundary Layer Winds with Scanning Doppler Lidar
by Soojin Park, Sang-Woo Kim, Moon-Soo Park and Chang-Keun Song
Remote Sens. 2018, 10(8), 1261; https://doi.org/10.3390/rs10081261 - 10 Aug 2018
Cited by 14 | Viewed by 7099
Abstract
The accurate measurement of wind profiles in the planetary boundary layer (PBL) is important not only for numerical weather prediction, but also for air quality modeling. Two wind retrieval methods using scanning Doppler light detection and ranging (lidar) measurements were compared and validated [...] Read more.
The accurate measurement of wind profiles in the planetary boundary layer (PBL) is important not only for numerical weather prediction, but also for air quality modeling. Two wind retrieval methods using scanning Doppler light detection and ranging (lidar) measurements were compared and validated with simultaneous radiosonde soundings. A comparison with 17 radiosonde sounding profiles showed that the sine-fitting method was able to retrieve a larger number of data points, but the singular value decomposition method showed significantly smaller bias (0.57 m s−1) and root-mean-square error (1.75 m s−1) with radiosonde soundings. Increasing the averaging time interval of radial velocity for obtaining velocity azimuth display scans to 15 min resulted in better agreement with radiosonde soundings due to the signal averaging effect on noise. Simultaneous measurements from collocated wind Doppler lidar and aerosol Mie-scattering lidar revealed the temporal evolution of PBL winds and the vertical distribution of aerosols within the PBL. Full article
(This article belongs to the Special Issue Remote Sensing of the Atmospheric Boundary Layer)
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Review

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28 pages, 3347 KiB  
Review
A Review of Techniques for Diagnosing the Atmospheric Boundary Layer Height (ABLH) Using Aerosol Lidar Data
by Ruijun Dang, Yi Yang, Xiao-Ming Hu, Zhiting Wang and Shuwen Zhang
Remote Sens. 2019, 11(13), 1590; https://doi.org/10.3390/rs11131590 - 4 Jul 2019
Cited by 89 | Viewed by 9515
Abstract
The height of the atmospheric boundary layer (ABLH) or the mixing layer height (MLH) is a key parameter characterizing the planetary boundary layer, and the accurate estimation of that is critically important for boundary layer related studies, which include air quality forecasts and [...] Read more.
The height of the atmospheric boundary layer (ABLH) or the mixing layer height (MLH) is a key parameter characterizing the planetary boundary layer, and the accurate estimation of that is critically important for boundary layer related studies, which include air quality forecasts and numerical weather prediction. Aerosol lidar is a powerful remote sensing instrument frequently used to retrieve the ABLH through detecting the vertical distributions of aerosol concentration. Presently available methods for ABLH determination from aerosol lidar are summarized in this review, including a lot of classical methodologies as well as some improved versions of them. Some new recently developed methods applying advanced techniques such as image edge detection, as well as some new methods based on multi-wavelength lidar systems, are also summarized. Although a lot of techniques have been proposed and have already given reasonable results in several studies, it is impossible to recommend a technique which is suitable in all atmospheric scenarios. More accurate instantaneous ABLH from robust techniques is required, which can be used to estimate or improve the boundary layer parameterization in the numerical model, or maybe possible to be assimilated into the weather and environment models to improve the simulation or forecast of weather and air quality in the future. Full article
(This article belongs to the Special Issue Remote Sensing of the Atmospheric Boundary Layer)
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Other

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16 pages, 9575 KiB  
Letter
Low-Cost Ka-Band Cloud Radar System for Distributed Measurements within the Atmospheric Boundary Layer
by Roberto Aguirre, Felipe Toledo, Rafael Rodríguez, Roberto Rondanelli, Nicolas Reyes and Marcos Díaz
Remote Sens. 2020, 12(23), 3965; https://doi.org/10.3390/rs12233965 - 3 Dec 2020
Viewed by 3455
Abstract
Radars are used to retrieve physical parameters related to clouds and fog. With these measurements, models can be developed for several application fields such as climate, agriculture, aviation, energy, and astronomy. In Chile, coastal fog and low marine stratus intersect the coastal topography, [...] Read more.
Radars are used to retrieve physical parameters related to clouds and fog. With these measurements, models can be developed for several application fields such as climate, agriculture, aviation, energy, and astronomy. In Chile, coastal fog and low marine stratus intersect the coastal topography, forming a thick fog essential to sustain coastal ecosystems. This phenomenon motivates the development of cloud radars to boost scientific research. In this article, we present the design of a Ka-band cloud radar and the experiments that prove its operation. The radar uses a frequency-modulated continuous-wave with a carrier frequency of 38 GHz. By using a drone and a commercial Lidar, we were able to verify that the radar can measure reflectivities in the order of −60 dBZ at 500 m of distance, with a range resolution of 20 m. The lower needed range coverage imposed by our case of study enabled a significant reduction of the instrument cost compared to existent alternatives. The portability and low-cost of the designed instrument enable its implementation in a distributed manner along the coastal mountain range, as well as its use in medium-size aerial vehicles or balloons to study higher layers. The main features, limitations, and possible improvements to the current instrument are discussed. Full article
(This article belongs to the Special Issue Remote Sensing of the Atmospheric Boundary Layer)
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13 pages, 2206 KiB  
Letter
Lidar Estimates of the Anisotropy of Wind Turbulence in a Stable Atmospheric Boundary Layer
by Viktor A. Banakh and Igor N. Smalikho
Remote Sens. 2019, 11(18), 2115; https://doi.org/10.3390/rs11182115 - 11 Sep 2019
Cited by 12 | Viewed by 2866
Abstract
In this paper, a method is proposed to estimate wind turbulence parameters using measurements recorded by a conically scanning coherent Doppler lidar with two different elevation angles. This methodology helps determine the anisotropy of the spatial correlation of wind velocity turbulent fluctuations. The [...] Read more.
In this paper, a method is proposed to estimate wind turbulence parameters using measurements recorded by a conically scanning coherent Doppler lidar with two different elevation angles. This methodology helps determine the anisotropy of the spatial correlation of wind velocity turbulent fluctuations. The proposed method was tested in a field experiment with a Stream Line lidar (Halo Photonics, Brockamin, Worcester, United Kingdom) under stable temperature stratification conditions in the atmospheric boundary layer. The results show that the studied anisotropy coefficient in a stable boundary layer may be up to three or larger. Full article
(This article belongs to the Special Issue Remote Sensing of the Atmospheric Boundary Layer)
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