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ABSTRACT
The scanning Atmospheric Radiation Measurement (ARM) Program cloud radars (SACRs) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20-30-km radius of the ARM fixed and mobile sites. Here, the postprocessing 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 toward the utilization of SACR measurements for cloud research.
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1. Introduction
The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates scanning ARM cloud radars (SACRs) at all its fixed and mobile sites (Kollias et al. 2014). The acquisition and operation of these state-of-the-art systems constitutes the first network of continuously operating scanning cloud radars and is expected to address several observational shortcomings of ARM's profiling cloud radars (Kollias et al. 2014). Much of the future impact these systems will have on cloud and precipitation research depends on how they are used to sample the atmosphere to capture the three-dimensional structure of clouds and their temporal evolution.While a first set of generic scan strategies has been implemented (Kollias et al. 2014), it is adaptable and changes will be made to it as necessary in support of future cloud...