Scanning ARM Cloud Radars Part II. Data Quality Control and Processing

Journal Article · Fri Oct 04 00:00:00 EDT 2013 · Journal of Atmospheric and Oceanic Technology, 31(3):583-598

DOI:https://doi.org/10.1175/JTECH-D-13-00045.1· OSTI ID:1158471

Kollias, Pavlos ^[1]; Jo, Ieng ^[1]; Borque, Paloma ^[1]; Tatarevic, Aleksandra ^[1]; Lamer, Katia ^[1]; Bharadwaj, Nitin ^[2]; Widener, Kevin B. ^[2]; Johnson, Karen ^[3]; Clothiaux, Eugene E. ^[4]

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1. McGill Univ., Montreal, QC (Canada)
2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
3. Brookhaven National Lab. (BNL), Upton, NY (United States)
4. Pennsylvania State Univ., State College, PA (United States)

The Scanning ARM Cloud Radars (SACR’s) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20-30 km radius from the ARM fixed and mobile sites. Here, the post-processing of the calibrated SACR measurements is discussed. First, a feature mask algorithm that objectively determines the presence of significant radar returns is described. The feature mask algorithm is based on the statistical properties of radar receiver noise. It accounts for atmospheric emission and is applicable even for SACR profiles with few or no signal-free range gates. Using the nearest-in-time atmospheric sounding, the SACR radar reflectivities are corrected for gaseous attenuation (water vapor and oxygen) using a line-by-line absorption model. Despite having a high pulse repetition frequency, the SACR has a narrow Nyquist velocity limit and thus Doppler velocity folding is commonly observed. An unfolding algorithm that makes use of a first guess for the true Doppler velocity using horizontal wind measurements from the nearest sounding is described. The retrieval of the horizontal wind profile from the Hemispherical Sky – Range Height Indicator SACR scan observations and/or nearest sounding is described. The retrieved horizontal wind profile can be used to adaptively configure SACR scan strategies that depend on wind direction. Several remaining challenges are discussed, including the removal of insect and second-trip echoes. The described algorithms significantly enhance SACR data quality and constitute an important step towards the utilization of SACR measurements for cloud research.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1158471
• Report Number(s): PNNL-SA-100005; 830403000
• Journal Information: Journal of Atmospheric and Oceanic Technology, 31(3):583-598, Vol. 31, Issue 3; ISSN ‎0739-0572
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
algorithms
could retrieval
cloud tracking/cloud motion winds
data processing
radars/radar observations