Cloud properties derived from two lidars over the ARM SGP site

Journal Article · Wed Feb 16 04:00:00 EST 2011 · Geophysical Research Letters, 38:Article No. L08814

DOI:https://doi.org/10.1029/2010GL046274· OSTI ID:1013284

Dupont, Jean-Charles; Haeffelin, Martial; Morille, Y; Comstock, Jennifer M; Flynn, Connor J; Long, Charles N; Sivaraman, Chitra; Newsom, Rob K

[1] Active remote sensors such as lidars or radars can be used with other data to quantify the cloud properties at regional scale and at global scale (Dupont et al., 2009). Relative to radar, lidar remote sensing is sensitive to very thin and high clouds but has a significant limitation due to signal attenuation in the ability to precisely quantify the properties of clouds with a 20 cloud optical thickness larger than 3. In this study, 10-years of backscatter lidar signal data are analysed by a unique algorithm called STRucture of ATmosphere (STRAT, Morille et al., 2007). We apply the STRAT algorithm to data from both the collocated Micropulse lidar (MPL) and a Raman lidar (RL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site between 1998 and 2009. Raw backscatter lidar signal is processed and 25 corrections for detector deadtime, afterpulse, and overlap are applied. (Campbell et al.) The cloud properties for all levels of clouds are derived and distributions of cloud base height (CBH), top height (CTH), physical cloud thickness (CT), and optical thickness (COT) from local statistics are compared. The goal of this study is (1) to establish a climatology of macrophysical and optical properties for all levels of clouds observed over the ARM SGP site 30 and (2) to estimate the discrepancies induced by the two remote sensing systems (pulse energy, sampling, resolution, etc.). Our first results tend to show that the MPLs, which are the primary ARM lidars, have a distinctly limited range where all of these cloud properties are detectable, especially cloud top and cloud thickness, but even actual cloud base especially during summer daytime period. According to the comparisons between RL and MPL, almost 50% of situations show a signal to noise ratio too low (smaller than 3) for the MPL in order to detect clouds higher than 7km during daytime period in summer. Consequently, the MPLderived annual cycle of cirrus cloud base (top) altitude is biased low, especially for daylight periods, compared with those derived from the RL data, which detects 5 cloud base ranging from 7.5 km in winter to 9.5 km in summer (and tops ranging from 8.6 to 10.5 km). The optically thickest cirrus clouds (COT>0.3) reach 50% of the total population for the Raman lidar and only 20% for the Micropulse lidar due to the difference of pulse energy and the effect of solar irradiance contamination. A complementary study using the cloud fraction 10 derived from the Micropulse lidar for clouds below 5 km and from the Raman lidar for cloud above 5 km allows for better estimation of the total cloud fraction between the ground and the top of the atmosphere. This study presents the diurnal cycle of cloud fraction for each season in comparisons with the Long et al. (2006) cloud fraction calculation derived from radiative flux analysis.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1013284
• Report Number(s): PNNL-SA-76764; KP1701000
• Journal Information: Geophysical Research Letters, 38:Article No. L08814, Journal Name: Geophysical Research Letters, 38:Article No. L08814 Vol. 38; ISSN GPRLAJ; ISSN 0094-8276
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
ALGORITHMS
CLOUDS
DATA ANALYSIS
OPTICAL PROPERTIES
OPTICAL RADAR
REMOTE SENSING