scholarly journals Exploring Atmospheric Aerosols by Twilight Photometry

2008 ◽  
Vol 25 (9) ◽  
pp. 1600-1607 ◽  
Author(s):  
B. Padma Kumari ◽  
S. H. Kulkarni ◽  
D. B. Jadhav ◽  
A. L. Londhe ◽  
H. K. Trimbake
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosols ◽  
Integrated Circuit ◽  
Tropical Meteorology ◽  
Indian Institute ◽  
Experimental Setup ◽  
Vertical Profiles ◽  
Remote Sensing Technique ◽  
Passive Remote Sensing ◽  
The Vertical Distribution

Abstract The instrument twilight photometer was designed, developed, and installed at the Indian Institute of Tropical Meteorology (IITM), Pune, India (18°43′N, 73°51′E), to monitor the vertical distribution of atmospheric aerosols. The instrument, based on passive remote sensing technique, is simple and inexpensive. It is operated only during twilights, and the method of retrieval of aerosol profile is based on a simple twilight technique. It functions at a single wavelength (660 nm), and a photomultiplier tube is used as a detector. The amplifier, an important component of the system, was designed and developed by connecting 10 single integrated-circuit (IC) amplifiers in parallel so that the noise at the output is drastically reduced and the sensitivity of the system has been increased. As a result, the vertical profiles are retrieved to a maximum of 120 km. A brief description of the basic principle of twilight technique, the experimental setup, and the method of retrieval of aerosol profiles using the above photometer are detailed in this paper.

scholarly journals To examine the association between oscillations of the stratospheric aerosol layer peaks and different types of clouds

2014 ◽  
Vol II-8 ◽  
pp. 13-19
Author(s):  
P. B. Mane
Keyword(s):  
Remote Sensing ◽  
Annual Variation ◽  
Stratospheric Aerosol ◽  
Aerosol Layer ◽  
Vertical Profiles ◽  
Remote Sensing Technique ◽  
Passive Remote Sensing ◽  
Peak Point ◽  
Different Types ◽  
Layer Peak

Aerosol measurements have been carried out at Kolhapur (16°42′N, 74°14′E) by using newly designed Semiautomatic Twilight Photometer. The system is a ground based simple and inexpensive but very sensitive passive remote sensing technique. The altitudes of the Junge layer peaks on measurement days were derived from the aerosol vertical profiles. One attempt is made to examine the association between oscillations of the stratospheric aerosol layer peaks and different types of clouds. The values of AND for the Junge layer peaks for each observational day were also calculated. The graph between AND at peak point of Junge layer and day numbers was also studied in comparison with High, Medium and Low level clouds. There is an annual variation in the altitude of the peak of Junge layer also. Its maximum is observed during January. The annual variation of the altitude of the peak of Junge layer and the AND of Junge layer peak showed opposite phase relation.

scholarly journals Measurements of Aerosols and Trace Gases in Southern Romania

2017 ◽  
Vol 68 (4) ◽  
pp. 873-878
Author(s):  
Alexandru Dandocsi ◽  
Anca Nemuc ◽  
Cristina Marin ◽  
Simona Andrei
Keyword(s):  
Remote Sensing ◽  
Vertical Profiles ◽  
Aerosol Mass Spectrometer ◽  
Boundary Layer Height ◽  
Passive Remote Sensing ◽  
Aerosol Mass ◽  
Scanning Lidar ◽  
532 Nm

An intensive measurement campaign was performed during September 2014 in southern Romania in two different locations: Magurele, Ilfov County and Turceni, Gorj County. This paper presents one case study with analysis of the aerosol properties from in-situ, passive remote sensing and active remote sensing measurements. A Multiwavelength Raman Lidar (RALI) provided one hour averaged vertical profiles of extinction and backscatter from the 532 nm and 1064 nm channels in Magurele. The UV scanning Lidar (MILI) provided one hour averaged backscattered and extinction vertical profiles for Turceni. Planetary Boundary Layer Height (PBLH) was calculated using the altitude of the maximum negative gradient of the range corrected signal. Mass concentrations for different aerosol species (organics, nitrate, sulphate, ammonium and chloride) were obtained from in-situ measurements using Aerosol Mass Spectrometer located in M�gurele and Aerosol Chemical Speciation Monitor (ACSM) located in Turceni.

scholarly journals Vertical profiles of aerosol mass concentrations observed during dust events by unmanned airborne in-situ and remote sensing instruments

2018 ◽  
Author(s):  
Dimitra Mamali ◽  
Eleni Marinou ◽  
Jean Sciare ◽  
Michael Pikridas ◽  
Panagiotis Kokkalis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosols ◽  
Climate Models ◽  
In Situ Measurements ◽  
Saharan Dust ◽  
Dust Particles ◽  
Vertical Profiles ◽  
Aerosol Mass ◽  
Aerosol Mass Concentration

Abstract. In-situ measurements using Unmanned Aerial Vehicles (UAVs) and remote sensing observations can independently provide dense vertically-resolved measurements of atmospheric aerosols; information which is highly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from Light Detection And Ranging (lidar) observations and in-situ measurements using an Optical Particle Counter (OPC) onboard a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse-mode (i.e., particles having radii > 0.5 μm) where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of the aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models.

scholarly journals An Improved Adaptive Subsurface Phytoplankton Layer Detection Method for Ocean Lidar Data

2021 ◽  
Vol 13 (19) ◽  
pp. 3875
Author(s):  
Chunyi Zhong ◽  
Peng Chen ◽  
Delu Pan
Keyword(s):  
Remote Sensing ◽  
Detection Method ◽  
Estimation Method ◽  
Absolute Difference ◽  
Lidar Data ◽  
Improved Method ◽  
Passive Remote Sensing ◽  
Layer Extraction ◽  
The Vertical Distribution

Phytoplankton, as the foundation of primary production, is of great significant for the marine ecosystem. The vertical distribution of phytoplankton contains key information about marine ecology and the optical properties of water bodies related to remote sensing.The common methods to detect subsurface phytoplankton biomass are often in situ measurements and passive remote sensing; however, the bio-argo measurement is discrete and costly, and the passive remote sensing measurement is limited to obtain the vertical information. As a component of active remote sensing, lidar technology has been proved as an effective method for mapping the vertical distribution of phytoplankton. In the past years, there have been few studies on the phytoplankton layer extraction method for lidar data. The existing subsurface layer extraction algorithms are often non-automatic, which need manual intervention or empirical parameters to set the layer extraction threshold. Hence, an improved adaptive subsurface phytoplankton layer detection method was proposed, which incorporates a curve fitting method and a robust estimation method to determine the depth and thickness of subsurface phytoplankton scattering layer. The combination of robust estimation method can realize automatic calculation of layer detection threshold according to the characteristic of each lidar signal, instead of an empirical fixed value used in previous works. In addition, the noise jamming signal can also be effectively detected and removed. Lidar data and in situ spatio-temporal matching Chlorophyll-a profile data obtained in Sanya Bay in 2018 was used for algorithm verification. The example result of step-by-step process illustrates that the improved method is available for adaptive threshold determination for layer detection and redundant noise signals elimination. Correlation analysis and statistical hypothesis testing shows the retrieved subsurface phytoplankton maximum depth by the improved method and in situ measurement is highly relevant. The absolute difference of layer maximum depth between lidar data and in situ data for all stations is less than 0.75 m, and mean absolute difference of layer thickness difference is about 1.74 m. At last, the improved method was also applied to the lidar data obtained near Wuzhizhou Island seawater, which proves that the method is feasiable and robust for various sea areas.

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