Overview of preparation for the American WAKE ExperimeNt (AWAKEN)
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54 ENVIRONMENTAL SCIENCES↗
Engineering topics
Morris, Victor R.
Publications and source records attributed to Morris, Victor R..
Shallow Cumulus Macrophysical Properties at Midcontinental US Site: Integrated Multiyear Active and Passive Observations
Substantial difference between cloud amounts obtained from active and passive remote sensing has been documented by previous studies. The difference is typically attributed to two main factors: the different field-of-view (FOV) (first factor) and different sensitivity to cloud properties (second factor) of the active and passive ground-based instruments. The relative impact of these two main factors on shallow cumuli cloud amount is demonstrated in this study. The demonstration involves a new multi-year (2000-2017) product, which integrates both the active and passive remote sensing data collected at the mid-continental Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility. Cloud fraction (CF) obtained from the narrow-FOV lidar-radar observations and wide-FOV fractional sky cover (FSC) acquired from sky images are key components of the integrated product. Results of this study indicate that (1) CF tends to overestimate FSC and this overestimation can be large (~40% on average) even at extended temporal scales (several years) and (2) the observed overestimate is primarily due to different sensitivity of the active and passive remote sensing instruments to shallow cumuli, while the limited FOV of active remote sensing instruments plays a minor role in such overestimation.
ARM Active Remotely Sensed Clouds Locations (ARSCL↗
Cloud Area Distributions of Shallow Cumuli: A New Method for Ground-Based Images
We develop a new approach that resolves cloud area distributions of single-layer shallow cumuli from ground-based observations. Our simple and computationally inexpensive approach uses images obtained from a Total Sky Imager (TSI) and complementary information on cloud base height provided by lidar measurements to estimate cloud equivalent diameter (CED) over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30 s). We illustrate the feasibility of our approach by comparing the estimated CEDs with those derived from collocated and coincident high-resolution (0.03 km) Landsat cloud masks with different spatial and temporal patterns of cloud cover collected over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. We demonstrate that (1) good (~7%) agreement between TSI and Landsat characteristic cloud size can be obtained for clouds that fall within the region of the sky observable by the TSI and (2) large clouds that extend beyond this region are responsible for noticeable (~16%) underestimation of the TSI characteristic cloud size. Our approach provides a previously unavailable dataset for process studies in the convective boundary layer and evaluation of shallow cumuli in cloud-resolving models.
14 SOLAR ENERGY↗
Infrared Thermometer (IRT) Instrument Handbook
The Infrared Thermometer (IRT) is a ground-based radiation pyrometer that provides measurements of the equivalent blackbody brightness temperature of the scene in its field of view. The downwelling version has a narrow field of view for measuring sky temperature and for detecting clouds. The upwelling version has a wide field of view for measuring the narrowband radiating temperature of the ground surface.
47 OTHER INSTRUMENTATION↗
Ceilometer Instrument Handbook
The Vaisala Laser Ceilometer (CEIL) is a self-contained, ground-based, active, remote-sensing device designed to measure cloud-base height, vertical visibility, and potential backscatter signals by aerosols. It detects up to three cloud layers simultaneously. Model CL31 has a maximum vertical range of 7700 meters (m). The laser ceilometer transmits near-infrared pulses of light, and the receiver detects the light scattered back by clouds and precipitation.
47 OTHER INSTRUMENTATION↗
Ceilometer (CEIL) Instrument Handbook
The Vaisala Laser Ceilometer (CEIL) is a self-contained, ground-based, active, remote-sensing device designed to measure cloud-base height, vertical visibility, and potential backscatter signals by aerosols. It detects up to three cloud layers simultaneously. Model CL31 has a maximum vertical range of 7700 meters (m). The laser ceilometer transmits near-infrared pulses of light, and the receiver detects the light scattered back by clouds and precipitation.
47 OTHER INSTRUMENTATION↗
Infrared Sky Imager (IRSI) Instrument Handbook
The Infrared Sky Imager (IRSI) deployed at the Atmospheric Radiation Measurement (ARM) Climate Research Facility is a Solmirus Corp. All Sky Infrared Visible Analyzer. The IRSI is an automatic, continuously operating, digital imaging and software system designed to capture hemispheric sky images and provide time series retrievals of fractional sky cover during both the day and night. The instrument provides diurnal, radiometrically calibrated sky imagery in the mid-infrared atmospheric window and imagery in the visible wavelengths for cloud retrievals during daylight hours. The software automatically identifies cloudy and clear regions at user-defined intervals and calculates fractional sky cover, providing a real-time display of sky conditions.
54 ENVIRONMENTAL SCIENCES↗
Installation and Initial Operation of DOE's 449-MHz Wind Profiling Radars on the U.S. West Coast
The U.S. Department of Energy (DOE), in collaboration with the National Oceanic and Atmospheric Administration (NOAA), has recently completed the installation of three new wind profiling radars on the Washington and Oregon coasts. These systems operate at a frequency of 449 MHz and provide mean wind profiles to a height of roughly 8 km, with the maximum measurement height depending on time-varying atmospheric conditions. This is roughly half the depth of the troposphere at these latitudes. Each system is also equipped with a radio acoustic sounding system (RASS), which provides a measure of the temperature profile to heights of approximately 2 km. Other equipment deployed alongside the radar includes a surface meteorological station and GPS for column water vapor. This project began in fiscal year 2014, starting with equipment procurements and site selection. In addition, environmental reviews, equipment assembly and testing, site access agreements, and infrastructure preparations have been performed. Finally, with equipment deployment with data collection and dissemination, the primary tasks of this project have been completed. The three new wind profiling radars have been deployed at airports near Coos Bay, OR, and Astoria, OR, and at an industrial park near Forks, WA. Data are available through the NOAA Earth Systems Research Laboratory Data Display website, and will soon be made available through the DOE Atmosphere to Electrons data archive and portal as well.
17 WIND ENERGY↗
A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer
For better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two-step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear-sky Tb obtained by an empirical formula as a function of surface air temperature and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of clear-sky conditions. It is designated as cloud-free data only when both the spectral and temporal tests confirm cloud-free data. Overall, most of the thick and uniform clouds are successfully detected by the spectral test, while the broken and fast-varying clouds are detected by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for six months, from January to June 2013. The overall proportion of correctness is about 88.3% and the probability of detection is 90.8%, which are comparable with or better than those of previous similar approaches. Two thirds of discrepancies occur when the new algorithm detects clouds while the ceilometer does not, resulting in different values of the probability of detection with different cloud-base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.
14 SOLAR ENERGY↗
Ground-based All-sky Mid-infrared and Visible Imagery for Purposes of Characterizing Cloud Properties
This paper describes the All Sky Infrared Visible Analyzer (ASIVA), a multi-purpose visible and infrared sky imaging and analysis instrument whose primary functionality is to provide radiometrically calibrated imagery in the mid-infrared (mid-IR) atmospheric window. This functionality enables the determination of diurnal hemispherical cloud fraction (HCF) and estimates of sky/cloud temperature from which one can derive estimates of cloud emissivity and cloud height. This paper describes the calibration methods and performance of the ASIVA instrument with particular emphasis on data products being developed for the meteorological community. Data presented here were collected during a field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Climate Research Facility from May 21 to July 27, 2009. The purpose of this campaign was to determine the efficacy of IR technology in providing reliable nighttime HCF data. Significant progress has been made in the analysis of the campaign data over the past several years and the ASIVA has proven to be an excellent instrument for determining HCF as well as several other important cloud properties.
analyzer↗