Topical Collection "Feature Papers for Section Atmosphere Remote Sensing"
Topical Collection Information
Changing of the atmosphere drives processes in weather, climate, and even oceans. The measurements, detection and predictions in atmospheric areas is of great importance for humans. Remote sensing is a key tool to monitor and analyze the atmosphere. Atmospheric remote sensing uses modern satellite instruments, as well as ground-based LIDAR, ceilometer and radar to study important processes.
We invite you to submit reviews and outstanding articles to this Special Issue in order to improve the current knowledge on remote sensing of the atmosphere. Papers addressing retrieval methods, validation of remote sensing data, calibration and applications based on remote sensing data in atmospheric areas, such as air quality, clouds, aerosols, water vapor, precipitation, wind, as well as chemical components, etc., are welcome.
The applications or technologies in your work should be novel and should bring new information to this area.
Dr. Richard Müller
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 papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection 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.
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- Atmosphere remote sensing
- Renewable Energy
- Air quality
- UV index
- Solar and wind energy systems
- Ground-based LIDAR
Published Papers (6 papers)
Improved Empirical Coefficients for Estimating Water Vapor Weighted Mean Temperature over Europe for GNSS Applications
Development of the so-called global navigation satellite system (GNSS) meteorology is based on the possibility of determining a precipitable water vapor (PWV) from a GNSS zenith wet delay (ZWD). Conversion of ZWD to the PWV requires application of water vapor weighted mean temperature
[...] Read more.
Development of the so-called global navigation satellite system (GNSS) meteorology is based on the possibility of determining a precipitable water vapor (PWV) from a GNSS zenith wet delay (ZWD). Conversion of ZWD to the PWV requires application of water vapor weighted mean temperature (
) measurements, which can be done using a surface temperature (
) and its linear dependency to the
. In this study we analyzed up to 24 years (1994–2018) of data from 49 radio-sounding (RS) stations over Europe to determine reliable coefficients of the
relationship. Their accuracy was verified using 109 RS stations. The analysis showed that for most of the stations, there are visible differences between coefficients estimated for the time of day and night. Consequently, the ETm4 model containing coefficients determined four times a day is presented. For hours other than the primary synoptic hours, linear interpolation was used. However, since this approach was not enough in some cases, we applied the dependence of
coefficients on the time of day using a polynomial (ETmPoly model). This resulted in accuracy at the level of 2.8 ± 0.3 K. We also conducted an analysis of the impact of this model on the PWV GNSS. Analysis showed that differences in PWV reached 0.8 mm compared to other commonly used models.
Comparison of Tropospheric Path Delay Estimates from GNSS and Space-Borne SAR Interferometry in Alpine Conditions
We compare tropospheric delays from Global Navigation Satellite Systems (GNSS) and Synthetic Aperture Radar (SAR) Interferometry (InSAR) in a challenging mountainous environment in the Swiss Alps, where strong spatial variations of the local tropospheric conditions are often observed. Tropospheric delays are usually considered
[...] Read more.
We compare tropospheric delays from Global Navigation Satellite Systems (GNSS) and Synthetic Aperture Radar (SAR) Interferometry (InSAR) in a challenging mountainous environment in the Swiss Alps, where strong spatial variations of the local tropospheric conditions are often observed. Tropospheric delays are usually considered to be an error for both GNSS and InSAR, and are typically removed. However, recently these delays are also recognized as a signal of interest, for example for assimilation into numerical weather models or climate studies. The GNSS and InSAR are techniques of complementary nature, as one has sparse spatial but high temporal resolution, and the other very dense spatial coverage but repeat pass of only a few days. This raises expectations for a combination of these techniques. For this purpose, a comprehensive comparison between the techniques must be first performed. Due to the relative nature of InSAR estimates, we compare the difference slant tropospheric delays (
) retrieved from GNSS with the
s estimated using Persistent Scatterer Interferometry (PSI) of 32 COSMO-SkyMed SAR images taken in a snow-free period from June to October between 2008 and 2013. The GNSS estimates calculated at permanent geodetic stations are interpolated to the locations of persistent scatterers using an in-house developed least-squares collocation software COMEDIE. The Pearson’s correlation coefficient between InSAR and GNSS estimates averaged over all acquisitions is equal to 0.64 and larger than 0.8 for approximately half of the layers. Better agreement is obtained mainly for days with high variability of the troposphere (relative to the tropospheric conditions at the time of the reference acquisition), expressed as standard deviations of the GNSS-based
s. On the other hand, the most common feature for the days with poor agreement is represented by very stable, almost constant GNSS estimates. In addition, there is a weak correlation between the agreement and the water vapor values in the area, as well as with the number of stations in the closest vicinity of the study area. Adding low-cost L-1 only GPS stations located within the area of the study increases the biases for most of the dates, but the standard deviations between InSAR and GNSS decrease for the limited area with low-cost stations.
Infrared Hyperspectral and Ultraviolet Remote Measurements of Volcanic Gas Plume at MT Etna during IMAGETNA Campaign
Quantification of gaseous emission fluxes from volcanoes can yield valuable insights on processes occurring in the Earth’s interior as part of hazard monitoring. It is also an important task in the framework of climate change, in order to refine estimates of natural emissions.
[...] Read more.
Quantification of gaseous emission fluxes from volcanoes can yield valuable insights on processes occurring in the Earth’s interior as part of hazard monitoring. It is also an important task in the framework of climate change, in order to refine estimates of natural emissions. Passive open-path UltraViolet (UV) scattered observation by UV camera allows the imaging of volcanic plumes and evaluation of sulfur dioxide (SO2
) fluxes at high temporal resolution during daytime. Another technique of imaging is now available in the InfraRed (IR) spectral domain. Infrared hyperspectral imagers have the potential to overcome the boundary of daytime sampling of the UV, providing measurements also during the night and giving access simultaneously to additional relevant gas species. In this context the IMAGETNA campaign of measurements took place at Mt Etna (Italy) in June 2015. Three different IR imagers (commercial and under developments) were deployed, together with a Fourier Transform InfraRed spectrometer (FTIR) instrument, a UV camera, a Long Wavelength InfraRed (LWIR) camera and a radiometer. We present preliminary results obtained by the two IR cameras under development, and then the IR hyperspectral imager results, coming from full physics retrieval, are compared to those of the UV camera. The comparison points out an underestimation of the SO2
Slant Column Densities (SCD) of the UV camera by a factor of 3.6. The detailed study of the retrieved SO2
SCD highlights the promising application of IR imaging in volcanology for remotely volcanic plume gas measurements. It also provides a way to investigate uncertainties in the SO2
SCD imaging in the UV and the IR.
Satellite-based Cloudiness and Solar Energy Potential in Texas and Surrounding Regions
Global horizontal irradiance (i.e., shortwave downward solar radiation received by a horizontal surface on the ground) is an important geophysical variable for climate and energy research. Since solar radiation is attenuated by clouds, its variability is intimately associated with the variability of cloud
[...] Read more.
Global horizontal irradiance (i.e., shortwave downward solar radiation received by a horizontal surface on the ground) is an important geophysical variable for climate and energy research. Since solar radiation is attenuated by clouds, its variability is intimately associated with the variability of cloud properties. The spatial distribution of clouds and the daily, monthly, seasonal, and annual solar energy potential (i.e., the solar energy available to be converted into electricity) derived from satellite estimates of global horizontal irradiance are explored over the state of Texas, USA and surrounding regions, including northern Mexico and the western Gulf of Mexico. The maximum (minimum) monthly solar energy potential in the study area is 151–247 kWhm−2
) in July (December). The maximum (minimum) seasonal solar energy potential is 457–706 kWhm−2
) in summer (winter). The available annual solar energy in 2015 was 1295–2324 kWhm−2
. The solar energy potential is significantly higher over the Gulf of Mexico than over land despite the ocean waters having typically more cloudy skies. Cirrus is the dominant cloud type over the Gulf which attenuates less solar irradiance compared to other cloud types. As expected from our previous work, there is good agreement between satellite and ground estimates of solar energy potential in San Antonio, Texas, and we assume this agreement applies to the surrounding larger region discussed in this paper. The study underscores the relevance of geostationary satellites for cloud/solar energy mapping and provides useful estimates on solar energy in Texas and surrounding regions that could potentially be harnessed and incorporated into the electrical grid.
A Framework for Estimating Clear-Sky Atmospheric Total Precipitable Water (TPW) from VIIRS/S-NPP
Atmospheric water vapor content or total precipitable water (TPW) is a highly variable atmospheric constituent, yet it remains one of the meteorological parameters that is most difficult to characterize accurately. We develop a framework for estimating atmospheric TPW from Visible Infrared Imaging Radiometer
[...] Read more.
Atmospheric water vapor content or total precipitable water (TPW) is a highly variable atmospheric constituent, yet it remains one of the meteorological parameters that is most difficult to characterize accurately. We develop a framework for estimating atmospheric TPW from Visible Infrared Imaging Radiometer Suite (VIIRS) data in this study. First, TPW is retrieved from VIIRS top-of-atmosphere (TOA) radiance of channels 15 and 16 using the refined split-window covariance-variance ratio (SWCVR) method. Then, the VIIRS TPW is blended with the microwave integrated retrieval system (MIRS) derived TPW via Bayesian model averaging (BMA) to improve the accuracy of VIIRS TPW. Three years (2014–2017) of ground measurements collected from SuomiNet sites over North America are used to validate the VIIRS TPW and blended TPW. The mean bias error (MBE) and root mean square error (RMSE) of the VIIRS TPW are 0.21 g/cm2
and 0.73 g/cm2
, respectively, and the accuracy of the VIIRS TPW in daytime is much better than at night time. The MBE and RMSE of BMA integrated TPW are 0.06 g/cm2
and 0.35 g/cm2
, and the accuracy difference between daytime and nighttime is also removed. The global radiosonde measurements are also collected to validate the BMA integrated VIIRS TPW. The MBE and RMSE of the BMA integrated TPW are 0.09 g/cm2
and 0.44 g/cm2
compared to the radiosonde measurements. This accuracy is also superior to the VIIRS TPW. Therefore, it is concluded that the developed framework can be used to derive accurate clear-sky TPW for VIIRS. This is the first time that we can obtain high accuracy TPW from VIIRS. This study will certainly benefit the study of atmospheric processes and climate change.
Measurement of the Earth Radiation Budget at the Top of the Atmosphere—A Review
Cited by 9
The Earth Radiation Budget at the top of the atmosphere quantifies how the Earth gains energy from the Sun and loses energy to space. It is of fundamental importance for climate and climate change. In this paper, the current state-of-the-art of the satellite
[...] Read more.
The Earth Radiation Budget at the top of the atmosphere quantifies how the Earth gains energy from the Sun and loses energy to space. It is of fundamental importance for climate and climate change. In this paper, the current state-of-the-art of the satellite measurements of the Earth Radiation Budget is reviewed. Combining all available measurements, the most likely value of the Total Solar Irradiance at a solar minimum is 1362 W/m
, the most likely Earth albedo is 29.8%, and the most likely annual mean Outgoing Longwave Radiation is 238 W/m
. We highlight the link between long-term changes of the Outgoing Longwave Radiation, the strengthening of El Nino in the period 1985–1997 and the strengthening of La Nina in the period 2000–2009.
The below list represents only planned manuscripts. Some of these
manuscripts have not been received by the Editorial Office yet. Papers
submitted to MDPI journals are subject to peer-review.
Type of Paper: Review
Tentative Title: Cloud detection in satellite imagery for analysis of global cloudiness and cloudiness trends–a review
Authors: Karl-Göran Karlsson
Affiliations: Swedish Meteorological and Hydrological Institute (SMHI)
Abstract: Clouds play a significant role for the Earth's climate and for the global and regional exchange of water and energy. Together with snow- and ice covered surfaces, clouds explain the relatively high planetary albedo of about 30 % considering that most Earth surfaces are otherwise relatively dark. Clouds are also tightly linked with atmospheric dynamics and precipitation processes meaning that they implicitly impact both radiation and circulation conditions. This means that clouds may be involved in several types of climate feedback processes despite of the fact that the clouds themselves may still be looked upon as just passive manifestations or effects of atmospheric circulation. Consequently, monitoring global cloud conditions is an important climate monitoring activity. To accomplish this and, especially, to achieve the needed global coverage, the use of satellite data is crucial. This paper presents an overview of the most common methods of detecting clouds in satellite imagery from both active and passive sensors and how to use this information for estimating global cloudiness. The paper also discusses the important and fundamental question "What is a cloud?" and how to validate global cloudiness data records.