Global pollution aerosol monitoring (GPAM) in the atmospheric boundary layer using future earth observing satellite remote sensing

2003 ◽  
Author(s):  
Jianhe Qu ◽  
Menas Kafatos ◽  
Ruixin Yang ◽  
Long S. Chiu ◽  
Allen R. Riebau
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Satellite Remote Sensing ◽  
Global Pollution ◽  
Aerosol Monitoring

scholarly journals Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship‐based and satellite remote sensing observations

2017 ◽  
Vol 122 (4) ◽  
pp. 2403-2418 ◽  
Author(s):  
David Painemal ◽  
J.‐Y. Christine Chiu ◽  
Patrick Minnis ◽  
Christopher Yost ◽  
Xiaoli Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Satellite Remote Sensing ◽  
Cloud Microphysics ◽  
Northeast Pacific

Internal gravity-shear waves in the atmospheric boundary layer from acoustic remote sensing data

2015 ◽  
Vol 51 (2) ◽  
pp. 193-202 ◽  
Author(s):  
V. S. Lyulyukin ◽  
M. A. Kallistratova ◽  
R. D. Kouznetsov ◽  
D. D. Kuznetsov ◽  
I. P. Chunchuzov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Shear Waves ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Acoustic Remote Sensing

scholarly journals Design of Meteorological Element Detection Platform for Atmospheric Boundary Layer Based on UAV

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yonghong Zhang ◽  
Tiantian Dong ◽  
Yunping Liu
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Detection System ◽  
Structure Design ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Meteorological Element ◽  
Local Storage ◽  
And Control

Among current detection methods of the atmospheric boundary layer, sounding balloon has disadvantages such as low recovery and low reuse rate, anemometer tower has disadvantages such as fixed location and high cost, and remote sensing detection has disadvantages such as low data accuracy. In this paper, a meteorological element sensor was carried on a six-rotor UAV platform to achieve detection of meteorological elements of the atmospheric boundary layer, and the influence of different installation positions of the meteorological element sensor on the detection accuracy of the meteorological element sensor was analyzed through many experiments. Firstly, a six-rotor UAV platform was built through mechanical structure design and control system design. Secondly, data such as temperature, relative humidity, pressure, elevation, and latitude and longitude were collected by designing a meteorological element detection system. Thirdly, data management of the collected data was conducted, including local storage and real-time display on ground host computer. Finally, combined with the comprehensive analysis of the data of automatic weather station, the validity of the data was verified. This six-rotor UAV platform carrying a meteorological element sensor can effectively realize the direct measurement of the atmospheric boundary layer and in some cases can make up for the deficiency of sounding balloon, anemometer tower, and remote sensing detection.

scholarly journals Remote Sensing And Surface Observations Of The Response Of The Atmospheric Boundary Layer To A Solar Eclipse

2003 ◽  
Vol 106 (1) ◽  
pp. 93-115 ◽  
Author(s):  
Fanny Girard-Ardhuin ◽  
B. Bénech ◽  
B. Campistron ◽  
J. Dessens ◽  
S. Jacoby-Koaly
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Solar Eclipse ◽  
Surface Observations

scholarly journals Estimating the urban atmospheric boundary layer height from remote sensing applying machine learning techniques

2021 ◽  
pp. 105962
Author(s):  
Gregori de Arruda Moreira ◽  
Guadalupe Sánchez-Hernández ◽  
Juan Luis Guerrero-Rascado ◽  
Alberto Cazorla ◽  
Lucas Alados-Arboledas
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Machine Learning Techniques ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Learning Techniques ◽  
Atmospheric Boundary Layer Height

scholarly journals The COTUR project: Remote sensing of offshore turbulence for wind energy application

2021 ◽  
Author(s):  
Etienne Cheynet ◽  
Martin Flügge ◽  
Joachim Reuder ◽  
Jasna B. Jakobsen ◽  
Yngve Heggelund ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Surface Layer ◽  
Atmospheric Boundary Layer ◽  
Wind Turbines ◽  
Microwave Radiometer ◽  
Wind Load ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Sensing Technology

Abstract. The paper presents the measurement strategy and dataset collected during the COTUR (COherence of TURbulence with lidars) campaign. This field experiment took place from February 2019 to April 2020 on the southwestern coast of Norway. The coherence quantifies the spatial correlation of eddies and is little known in the marine atmospheric boundary layer. The study was motivated by the need to better characterize the lateral coherence, which partly governs the dynamic wind load on multi-megawatt offshore wind turbines. During the COTUR campaign, the coherence was studied using land-based remote sensing technology. The instrument setup consisted of three long-range scanning Doppler wind lidars, one Doppler wind lidar profiler and one passive microwave radiometer. Both the WindScanner software and Lidar Planner software were used jointly to simultaneously orient the three scanner heads into the mean wind direction, which was provided by the lidar wind profiler. The radiometer instrument complemented these measurements by providing temperature and humidity profiles in the atmospheric boundary layer. The preliminary results show an undocumented variation of the lateral coherence with the distance from the coast. The scanning beams were pointed slightly upwards to record turbulence characteristics both within and above the surface layer, providing further insight on the applicability of surface-layer scaling to model the turbulent wind load on offshore wind turbines.

Integrated monitoring of the atmospheric boundary layer dynamics by remote sensing methods in June 2015 in Tomsk

2016 ◽  
Author(s):  
Grigorii P. Kokhanenko ◽  
Yurii S. Balin ◽  
Sergei V. Nasonov ◽  
Ioganes E. Penner ◽  
Svetlana V. Samoilova ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Integrated Monitoring ◽  
Boundary Layer Dynamics ◽  
Remote Sensing Methods
Sign in / Sign up

Export Citation Format

Share Document