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At least 991 records · Page 55

SGP Precipitation 2017-2019 Best Estimate

The Atmospheric Radiation Measurement user facility (ARM) Southern Great Plains observatory (SGP) houses over 50 precipitation instruments, using approximately 10 different methods for measurement. Nine different types of sensors are deployed at the SGP Central Facility with duplicates of the video disdrometer, impact disdrometer, and laser disdrometer. These instruments are deployed relatively close to one another in the “Central Cluster” of the SGP Central Facility. This effort employed simple clustering techniques on these data to calculate a precipitation best estimate, which in turn was used to develop a weighting scheme for each instrument type across rain rates that can be reused in the future for different configurations of instrument deployments. Product should be considered as an evaluation data set.

54 ENVIRONMENTAL SCIENCES↗

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Gas Adsorption Analyzer

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

3Flex,BET specific surface area and pore volume, A↗

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) X-Ray Diffraction

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Cryogenic Refrigerator Applied to Freezing Test

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Aerodynamic Particle Sizer, Condensation Particle Counter, and Meteorological Instrument Data Analysis

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

hsrlcfad

The ARM lidar simulator is developed to facilitate direct comparison of climate model output with the ARM ground-based lidar measurements. The ARM user facility provides lidar SR-height joint histograms (CFADs) to compare with outputs from lidar simulators (e.g., EMC2 and COSP2.0). The CFADs were generated from the lidar measurements (hsrlM1.a1). The dataset contains vertical calculated profiles of lidar scattering ratio (SR) and SR-height joint histograms.

54 ENVIRONMENTAL SCIENCES↗

Doppler spectra from ARM Doppler Lidar during ARMing the Edge

There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site at Lamont, Oklahoma, hosts five ARM Doppler lidars that can measure cloud and aerosol properties. In particular, the ARM Doppler lidars record Doppler spectra that contain information about the fall speeds of cloud and precipitation particles. In this dataset, we provide the Doppler spectra from the ARM Doppler lidar at C1 recorded in April 2022 during ARMing the Edge.

54 ENVIRONMENTAL SCIENCES↗

Warm boundary-layer cloud properties and cloud susceptibilities product at the ARM ENA observatory

Cloud liquid water path, albedo, and cloud fraction susceptibilities for marine warm boundary-layer clouds are quantified using the Meteosat retrieved cloud microphysical properties at the ARM Eastern North Atlantic (ENA) observatory in the Azores. The Meteosat cloud retrievals are based on the methods applied by the Clouds and the Earth’s Radiant Energy System (CERES) project, which are specifically tailored to support the ARM user facility over the ARM ground-based observation sites (enavisstpx2dm11minnisX1.c1). Cloud susceptibility is quantified as the slope between cloud properties and Nd within a 1-degree-by-1-degree grid box at each satellite time step using a least-square regression. To reduce uncertainties associated with the adiabatic assumption in the Nd retrieval, for each cloud object, we exclude cloudy pixels at the cloud edge, defined as those adjacent to cloud-free pixels. To minimize influence of cloud heterogeneity and co-variability on the retrieved cloud susceptibility, cloud properties are averaged to 0.25-degree resolution using the 3-km pixel-level retrieval, and the 1-degree cloud susceptibilities are estimated using the smoothed data. Cloud type classification is applied to distinct cloud object, labeling all contiguous cloudy pixels. Marine warm boundary-layer clouds are defined as clouds with 90% of cloud tops below 3km, and Meteosat retrieved cloud phase as liquid.

54 ENVIRONMENTAL SCIENCES↗

TRACER Soil Moisture Data, Guy TX

The purpose of this study was to collect and distribute ground-truth soil water content and meteorological data in the Houston, TX, area, supporting the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility, and the 2022 field campaign for the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). The files herein contain soil water content and meteorological data for the Guy, Texas station that the Bureau of Economic Geology at UT Austin installed in the area of study during period of performance. This station produces two data files. First, the file ending with “_Soil_flagged.dat” contains mean hourly volumetric soil water content and temperature measured at 5, 10, 20 and 50 cm depths. The file ending with “_Meteoro_flagged.dat” contains mean hourly measured precipitation, air temperature and humidity, wind speed and direction, and solar radiation. All data have undergone QA/QC procedures that are described by Caldwell et al. (2019) and Dorigo et al. (2013) for the soil-specific data, and EPA (2008) for the meteorological data.

precipitation↗

Soil Moisture Data for TRACER project (Houston, TX)

The purpose of this study was to collect and distribute ground-truth soil water content and meteorological data in the Houston, TX, area, supporting the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility, and the 2022 field campaign for the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). The files herein contain soil water content and meteorological data for three stations that the Bureau of Economic Geology at UT Austin installed in the Houston, TX, area during the period of performance. The data includes soil moisture, volumetric water content, electrical conductivity of soil, soil temperature, rain precipitation, air temperature and other parameters. Data files within this data set contain measurements at both sub-hourly and 1-hour resolution measurements. The sub-hourly meteorological data file names end with “TRACER_SubHourly_met.dat”, and the sub-hourly soil data files end with “TRACER_SubHourly_soil.dat”. For the 1-hour resolution data, the files ending with "_Soil_flagged.dat” contain mean hourly volumetric soil water content and temperature measured at 5, 10, 20 and 50 cm depths. The files ending with “_Meteoro_flagged.dat” contain mean hourly measured precipitation, air temperature and humidity, wind speed and direction, and solar radiation. All data have undergone QA/QC procedures that are described by Caldwell et al. (2019) and Dorigo et al. (2013) for the soil-specific data, and EPA (2008) for the meteorological data.

Air temperature↗

ARM SGP PBLH and MLH datasets from Raman lidar and Doppler lidar

The planetary boundary layer (PBL) plays a critical role in the atmosphere by transferring heat, moisture, and momentum. The warm PBL has a distinct diurnal cycle including the daytime convective mixing layer (ML) and nighttime residual layer developments. Thus, simultaneous determinations of PBL height (PBLH) and ML height (MLH) are necessary for studying PBL characterization and processes. Here, new approaches are developed to provide reliable PBLH and MLH estimates to characterize warm PBL evolution. The approaches use Raman lidar (RL) water vapor mixing ratio (WVMR) and Doppler lidar (DL) vertical velocity measurements at the Southern Great Plains (SGP) atmospheric observatory, which was established by the Atmospheric Radiation Measurement (ARM) User Facility. Compared to widely used lidar aerosol measurements for PBLH, WVMR is a better tracer for PBL vertical mixing. For PBLH, the approach classifies PBL water vapor structures into a few general patterns, then uses a slope method and dynamic threshold method to determine PBLH. For MLH, wavelet analysis is used to reconstruct 2D variance from DL vertical wind velocity measurements according to the turbulence eddy size to minimize the impacts of gravity wave and eddy size on variance calculations; then, a dynamic threshold method is used to determine MLH. Remotely-sensed PBLHs and MLHs are compared with radiosonde measurements based on the Richardson number method. Good agreements between them confirm that the proposed new algorithms are reliable for PBLH and MLH characterization. The algorithms are applied to warm-season RL and ML measurements at the SGP site for five years to study warm-season PBL structure and processes. The weekly composited diurnal evolutions of PBLHs and MLHs in a warm climate were provided to illustrate diurnal and seasonal PBL evolutions. This reliable data set of PBLH and MLH values will be valuable for studying PBL processes, model evolution, and PBL parameterization improvements. The MLH dataset includes the MLH in values of km above ground level. The PBLH dataset includes the PBLH in values of km above ground level, along with a flag ("situation_PBLH") to determine the state of the PBL (1 = Cloudy Condition, 2 = Stable Layer, 3 = Multi-layer WVMR structure, 4 = Well-Mixed PBL, 5 = A de-coupled layer, 6 = Other).

mixing layer height↗

NWB Sensors Infrared Cloud Imager Data Products from SGP

NWB Sensors is a company which has developed a commercially available Infrared Cloud Imager (ICI). For more information, consult the company's webpage, https://www.nwbsensors.com/infrared-cloud-imager. To validate the radiometric accuracy of the ICI, NWB Sensors deployed it to the ARM SGP User Facility in 2023. The primary motivation of this deployment was to perform an intercomparison between the ICI and the Atmospheric Emitted Radiance Interferometer (AERI). The AERI spectral radiance data product can be integrated across the response function of the ICI and directly compared to the zenith radiance observed by the ICI. In addition, the ICI uses proprietary models of the downwelling clear-sky radiance in its cloud processing algorithms. They are based on surface meteorology and precipitable water vapor (PWV). These models were validated by comparing their predicted radiances to those derived from radiative transfer models of the ARM radiosondes. Finally, PWV observations derived from the ICI's onboard GNSS-based PWV retrieval system were compared against those from the microwave radiometer. This dataset contains the ICI radiance and cloud data products.

Atmosphere↗

Automatic cartography techniques for earth resources research

Progress in developing instrumentation and software for the EROS user facilities is reported. Significant progress has been made in developing the USGS binary-mode scanning digitizer which is described in detail. Other instrumentation and processes discussed include profile-generating techniques, a manual digitizer, image correlation systems, and some new photomechanical data processing techniques.

Edson, D. T.↗

Lear jet telescope system

The telescope system was designed as a multi-user facility for observations of celestial objects at infrared wavelengths, where ground-based observations are difficult or impossible due to the effects of telluric atmospheric absorption. The telescope is mounted in a Lear jet model 24B which typically permits 70 min. of observing per flight at altitudes in excess of 45,000 ft (13 km). Telescope system installation is discussed, along with appropriate setup and adjustment procedures. Operation of the guidance system is also explained, and checklists are provided which pertain to the recommended safe operating and in-flight trouble-shooting procedures for the equipment.

Erickson, E. F.↗

An infrared foreoptics adaptor for the Learjet Telescope

A foreoptics adapter has been built for the Learjet telescope which permits simultaneous viewing of the visible star field in the image plane and acquisition of astronomical data at infrared wavelengths (less than 1 micrometer). The device uses an adjustable dichroic beamsplitter to transmit visible wavelengths to an eyepiece (or television camera), and to reflect infrared wavelengths to a port where an infrared detector system can be mounted. The instrument is intended as a multiple user facility for the Learjet telescope. This report describes the adapter and its use.

Erickson, E. F.↗

Space science on the Space Shuttle - Plans and prospects

The paper gives an overview of current planning for the use of the Space Shuttle and Spacelab for carrying out NASA's program in Space Science. Attention is given to the major categories of use: (1) as a launch and service vehicle; (2) as an experiment platform for carrying out passive observations; (3) as a component in active and controlled experiments in space; and (4) as a manned orbiting laboratory for carrying out investigations requiring hands-on access to equipment and samples. Examples of each type of use are given. Also discussed are some of the multi-user facility instruments which are planned for early development. Finally, payloads to be carried on the early missions are discussed with particular emphasis on the capabilities of the Shuttle/Spacelab.

Rosendhal, J. F.↗

Conceptual design study for an advanced cab and visual system, volume 2

The performance, design, construction and testing requirements are defined for developing an advanced cab and visual system. The rotorcraft system integration simulator is composed of the advanced cab and visual system and the rotorcraft system motion generator, and is part of an existing simulation facility. User's applications for the simulator include rotorcraft design development, product improvement, threat assessment, and accident investigation.

Rue, R. J.↗