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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Cloud Edge Properties Measured by the ARM Shortwave Spectrometer Over Ocean and Land

In this paper, we use the spectrally invariant method to study the variability of cloud optical thickness (τ) and droplet effective radius (r eff ) in transition zones between the cloudy and clear-sky columns observed by Shortwave Array Spectroradiometer-Zenith at the Southern Great Plains Central Facility site (SGP C1) and during the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign. The spectrally invariant method approximates the spectra in the transition zone as a linear combination of definitely clear and definitely cloudy spectra. The slope and intercept of the linear relations characterize τ and r eff in the transition region, respectively. The radiative transfer model simulations show that that (i) the slope of the visible band is positively correlated with τ, while (ii) the intercept of the near-infrared band has a high negative correlation with r eff . We have analyzed 22 cloud edge cases from the SGP and MAGIC and found that from cloud to clear in the transitions, (a) the slopes of the visible band decrease, indicating the decrease of τ toward cloud edges, and (b) the intercepts of the near-infrared band show a much more significant increase at the SGP than from the MAGIC. The results from observed cases suggest that while τ decreases for all cases, the decrease in r eff is much more significant for cloud over land at the SGP site compared to the ocean counterpart during the MAGIC campaign.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

A Climatology of Surface Cloud Radiative Effects at the ARM Tropical Western Pacific Sites

Cloud radiative effects on surface downwelling fluxes are investigated using long-term datasets from the three Atmospheric Radiation Measurement (ARM) sites in the Tropical Western Pacific (TWP) region. The Nauru and Darwin sites show significant variability in sky cover, downwelling radiative fluxes, and surface cloud radiative effect (CRE) due to El Niño and the Australian monsoon, respectively, while the Manus site shows little intra-seasonal or interannual variability. Cloud radar measurement of cloud base and top heights are used to define cloud types so that the effect of cloud type on the surface CRE can be examined. Clouds with low bases contribute 71-75% of the surface shortwave (SW) CRE and 66-74% of the surface longwave (LW) CRE at the three TWP sites, while clouds with mid-level bases contribute 8-9% of the SW CRE and 12-14% of the LW CRE, and clouds with high bases contribute 16-19% of the SW CRE and 15-21% of the LW CRE.

ARM↗
DOE OSTI2016

Deployment of ARM Aerial Facility Scanning Mobility Particle Sizer Field Campaign Report

Atmospheric aerosols influence global climate by scattering and absorbing sunlight (direct effects) and by changing the microphysical structure, lifetime, and coverage of clouds (indirect effects). While it is widely accepted that aerosol indirect effects cool the Earth-atmosphere system by increasing cloud reflectivity and coverage, the magnitudes of the indirect effects are poorly quantified. One key aerosol property for understanding aerosol indirect effects is the ability of aerosol particles to form cloud droplets at atmospheric relevant supersaturations—i.e., cloud condensation Nuclei (CCN) activity. For particles consisting of typical atmospheric inorganic compounds, their CCN activity is well understood and can be effectively predicted using Köhler theory based on physicochemical properties of the solute, such as its mass, molar volume, and activity coefficient. However, atmospheric aerosols often consist of hundreds of organic species, which can contribute ~20-90% to the total fine aerosol mass. Depending on their properties, organic species can significantly influence the ability of aerosol particles to act as CCN and form cloud droplets. This project focuses on the CCN activity of secondary organic aerosol (SOA) compounds formed from key biogenic volatile organic compounds (VOCs) under representative conditions, and the relationship between the hygroscopicity and composition of organic aerosols. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Aerial Facility (AAF) scanning mobility particles sizer (SMPS) was deployed during a ~ 2-week intensive measurement campaign, taking place February 10-February 23, 2016 at the Pacific Northwest National Laboratory (PNNL) Environmental Simulation Chamber. The SMPS was operated with a CCN counter (CCNc). Aerosol particles were first classified by the differential mobility analyzer inside the SMPS; the classified aerosol will then be simultaneously characterized by a condensation particle counter (CPC) (part of the SMPS) and the CCNc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Deployment of ARM Aerial Facility Scanning Mobility Particle Sizer Field Campaign Report

Atmospheric aerosols influence global climate by scattering and absorbing sunlight (direct effects) and by changing the microphysical structure, lifetime, and coverage of clouds (indirect effects). While it is widely accepted that aerosol indirect effects cool the Earth-atmosphere system by increasing cloud reflectivity and coverage, the magnitudes of the indirect effects are poorly quantified. One key aerosol property for understanding aerosol indirect effects is the ability of aerosol particles to form cloud droplets at atmospheric relevant supersaturations—i.e., cloud condensation Nuclei (CCN) activity. For particles consisting of typical atmospheric inorganic compounds, their CCN activity is well understood and can be effectively predicted using Köhler theory based on physicochemical properties of the solute, such as its mass, molar volume, and activity coefficient. However, atmospheric aerosols often consist of hundreds of organic species, which can contribute ~20-90% to the total fine aerosol mass. Depending on their properties, organic species can significantly influence the ability of aerosol particles to act as CCN and form cloud droplets. This project focuses on the CCN activity of secondary organic aerosol (SOA) compounds formed from key biogenic volatile organic compounds (VOCs) under representative conditions, and the relationship between the hygroscopicity and composition of organic aerosols. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Aerial Facility (AAF) scanning mobility particles sizer (SMPS) was deployed during a ~ 2-week intensive measurement campaign, taking place February 10-February 23, 2016 at the Pacific Northwest National Laboratory (PNNL) Environmental Simulation Chamber. The SMPS was operated with a CCN counter (CCNc). Aerosol particles were first classified by the differential mobility analyzer inside the SMPS; the classified aerosol will then be simultaneously characterized by a condensation particle counter (CPC) (part of the SMPS) and the CCNc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Surface heat flux and its association with the MJO in the tropical western Pacific using ARM observations

The Madden-Julian oscillation (MJO) is a major atmospheric phenomenon in the tropics that moves eastward every 20 to 100 days. It brings heavy rain and strong winds, influencing extreme weather events far beyond the tropics – including flooding, hurricanes, tornadoes and heavy snow in the United States. Therefore, an improved understanding of the MJO is critical for enhancing weather forecasts and supporting better decision-making for communities, emergency managers, and the private sector. Past studies, based on short-term observations or long-term model data, have emphasized the dominant role of atmospheric humidity in driving the MJO. Our research, using long-term observations (2000-2014) from three U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) sites in the tropical western Pacific (Manus, Nauru, and Darwin) confirms those past findings. However, we also show that atmospheric temperature, especially in the mid and upper troposphere, also plays a key role in the MJO’s evolution from its quiet (suppressed) to convective (active) phase. These findings provide valuable insights into how the MJO evolves and may help evaluate and improve weather and climate models. Our study also examined how the exchange of heat between the Earth's surface and the atmosphere, called surface heat flux, interacts with the MJO. This flux includes components such as latent heat (related to evaporation), sensible heat (related to temperature difference between surface and atmosphere), and radiation. We found that modulation in MJO convection is well connected to surface heat flux over the tropical western Pacific. One surface heat flux component often overlooked is the sensible heat flux due to precipitation (Q P ). Since falling raindrops are typically cooler than the land or ocean surface, they can cool the surface and affect local weather. To test the impact of Q P on convection during MJO, we incorporated it into a weather model, and ran simulations for two periods: April 2009 (when the MJO was active) and June 2006 (when it was not). Including Q P reduced errors in simulating the daily peak of rainfall—by 83% during the strong MJO and 23% during the inactive phase. It also improved the timing of peak daily rainfall and reduced the overall precipitation error by about 10%. These improvements were especially noticeable during periods of heavy rainfall. Our results suggest that even small heat exchanges from rainfall can play a significant role in shaping local weather. Accounting for these effects, particularly in regions like the tropical islands, can lead to more accurate simulations of the MJO-associated precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scm_forcing)

The constrained variational objective analysis approach described in Zhang and Lin [1997] and Zhang et al. [2001]was used to derive the large-scale single-column/cloud resolving model forcing and evaluation data set from the observational data collected during Midlatitude Continental Convective Clouds Experiment (MC3E), which was conducted during April to June 2011 near the ARM Southern Great Plains (SGP) site. The analysis data cover the period from 00Z 22 April - 21Z 6 June 2011. The forcing data represent an average over the 3 different analysis domains centered at central facility with a diameter of 300 km (standard SGP forcing domain size), 150 km and 75 km, as shown in Figure 1. This is to support modeling studies on various-scale convective systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, S-band Radar (williams-s_band)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, 449 MHz Profiler(williams-449_prof)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Surface Meteorology (williams-surfmet)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Vertical Air Motion (williams-vertair)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Scanning ARM Cloud Radar Corrections (SACRCOR)

This dataset contains moments from the Scanning ARM Cloud Radars (SACRs) which have been filtered and corrected in order to provide a product for non-radar meteorologists which contains fewer measurement artifacts and effects from signal propagation. Corrections have been applied to selected moments. The 'reflectivity_corrected' variable has been corrected for gaseous attenuation effects. Dealiasing of Doppler velocities is performed using two algorithms, with the results stored in the variables 'mean_doppler_velocity_corrected' and 'mean_doppler_velocity_corrected2.' This product removes returns from non-atmospheric source, such as insects, ground clutter, and second trip echoes, leaving only meaningful returns from clouds and precipitation. Users should note that the filter mask in this product is not perfect. A small amount of clutter, insects and second trip echo artifacts may still be present in the filtered data, especially near the radar where classification is particularly challenging. Additionally, due to the instrument configuration, no filtering of insects was performed on data from the X-band SACR. Improvements to these algorithms are planned as further testing is performed and additional data becomes available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

ARM AAF G1 Video files for ACE-ENA

Forward and Nadir (downward) facing video recording during the ACE-ENA research flights aboard the ARM Aerial Facility G-1 from June to July in 2017. The video is recorded at 1 fps. It can be viewed in QuickTime. The camera time is synched daily with the aircraft NTP server.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Scanning ARM Precipitation Radar (SAPR) Velocity Azimuth Display (VAD)

The Velocity Azimuth Display (VAD, historical term) product contains retrievals of the zonal (north/south) and meridional (east/west) wind speed components, in precipitating systems, as a function of time and height. This product, which uses azimuthal variations in radial air velocity, allows quick insight into wind speed and wind direction in the vicinity of the radar when rainfall or snowfall is present. VAD data are derived from Corrected Moments in Antenna Coordinates Version 2 (CMAC2) using code within the Python ARM Radar Toolkit (Py-ART), an open-source architecture for interacting with radar data in the Python programming language.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Scanning ARM Precipitation Radar (SAPR) Quasi-Vertical Profile (QVP)

The Quasi-Vertical Profiles (QVP) VAP averages quality-controlled radar measurements along the axis of the azimuth. QVP allows quick insight into domain mean hydrometeor (e.g., snow, rain, melting layer) location and polarimetric data. QVP data are derived from Corrected Moments in Antenna Coordinates Version 2 (CMAC2) using code within the Python ARM Radar Toolkit (Py-ART), an open-source architecture for interacting with radar data in the Python programming language.

54 ENVIRONMENTAL SCIENCES↗