• Title/Summary/Keyword: Raman LIDAR

Search Result 48, Processing Time 0.044 seconds

Daytime Temperature Measuring LIDAR System by Using Rotational Raman Signal (회전 라만 신호를 이용한 낮 시간 온도측정 라이다)

  • Yoon, Moonsang;Kim, Dukhyeon;Park, Sunho;Sin, MyeongJae;Kim, Yonggi;Jung, Haedoo
    • Korean Journal of Optics and Photonics
    • /
    • v.23 no.4
    • /
    • pp.159-166
    • /
    • 2012
  • We have developed a daytime measuring rotational Raman LIDAR system for temperature measurement. To decrease the background signal from sunlight, we have designed and installed narrow band (0.5 nm) and high rejection ($10^{-6}$) rate band pass filter system using a grating and an interference filter. We calibrated our system by comparing our horizontal temperature profile and KMA (Korea Meteorological Administration) data. We have found that our temperature profile has a good correlation with KMA data within our theoretically expected variance. And we have used these calibration values in obtaining a vertical temperature distribution. To check our system, we also have compared our vertical temperature data with US standard atmospheric temperature profile. We also have compared our temperature profile with sonde data.

Designing of Rotational Raman Lidar system measuring Atmospheric Temperature (대기 온도 측정용 회전 라만 라이다 시스템의 설계)

  • ;;;Serguei Bobronikov
    • Proceedings of the Optical Society of Korea Conference
    • /
    • 2000.08a
    • /
    • pp.208-209
    • /
    • 2000
  • 라이다 방법을 이용한 대기의 온도 측정은 크게 1) DIAL 방법을 이용하는 방법 2) 공기분자의 밀도를 측정하는 진동 라만 산란을 이용하는 방법 3)공기분자의 회전 라만 산란을 이용하는 방법 4) Rayleigh 산란의 선폭을 이용하는 방법 등으로 나누어진다. 이 중에서 대류권의 온도 측정에 적용가능한 방법은 3 번째의 방법으로 질소나 산소의 회전 라만 산란(RRS:Rotational Raman Scattering)이 가장 흔히 사용되는 기술이다. 질소와 산소의 회전 라만 신호를 이용한 온도 측정 기술은 Cohen$^1$ 등에 의하여 처음 시도되었으며, 그 후 많은 사람들에 의하여 검증되었다.$^2$ (중략)

  • PDF

Calculation of Multiple Scattering in Water Cloud and Application in Remote Measurement of Cloud Physical Properties (구름에서의 다중산란효과 계산 및 이를 이용한 구름 물리변수 원격 추출 방법 연구)

  • Kim, Dukhyeon;Park, Sunho;Choi, Sungcheol
    • Korean Journal of Optics and Photonics
    • /
    • v.25 no.1
    • /
    • pp.1-7
    • /
    • 2014
  • Multiple scattering effects in cloud are important error sources of the Mie scattering Lidar inversion method, which should be measured to correct the Lidar equation in single wavelength Mie Lidar. We have calculated the multiple scattering effects in liquid water clouds by using a Monte Carlo method, and we have applied these multiple scattering effects in measuring water cloud effective size and LWC (Liquid Water Content). When cloud effective size is less than $2.5{\mu}m$, we can easily extract cloud effective size and LWC by using two wavelength Lidar such as extinction coefficients measured at 355nm and 1064nm. For a larger size cloud, we can find that saturated degree of linear polarization is strongly correlated with cloud effective size, LWC, and extinction coefficients. From these correlations we know that we can measure LWC and cloud effective size if we use single wavelength Rotational Raman Lidar and Mie scattering polarization Lidar.

Depolarization Ratio Retrievals Using AERONET Sun Photometer Data

  • Lee, Kyung-Hwa;Muller, Detlef;Noh, Young-Min;Shin, Sung-Kyun;Shin, Dong-Ho
    • Journal of the Optical Society of Korea
    • /
    • v.14 no.3
    • /
    • pp.178-184
    • /
    • 2010
  • We present linear particle depolarization ratios (LPDRs) retrieved from measurements with an AERONET Sun photometer at the Gwangju Institute of Science and Technology (GIST), Korea ($35.10^{/circ}N$, $126.53^{\circ}E$) between 19 October and 3 November 2009. The Sun photometer data were classified into three categories according to ${\AA}$ngstr$\ddot{o}$ exponent and size distribution: 1) pure Asian dust (19 October 2009), 2) Asian dust mixed with urban pollution observed in the period from 20-26 October 2009, and 3) clean conditions (3 November). We show that the LPDRs can be used to distinguish among Asian dust, mixed aerosol, and non-Asian dust in the atmosphere. The mean LPDR of the pure Asian dust case is 23 %. Mean LPDRs are 13 % for the mixed case. The lowest mean LPDR is 6 % in the clean case. We compare our results to vertically resolved LPDRs (at 532 nm) measured by a Raman LIDAR system at the same site. In most cases, we find good agreement between LPDRs derived with Sun photometer and measured by LIDAR.