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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

TRACER-CAT-LANL Aerosol Optics and Chemical Speciation - PASS

Aerosol size distribution, optical properties, and speciation data collected in La Port TX, during TRACER-CAT-LANL, July 2022, with basic trace gas measurements. All sampling was conducted with an identical aerosol inlet as the standard ARM-AOS systems. The TRacking Aerosol Convection interactions ExpeRiment Carbonaceous Aerosols Thrust by Los Alamos National Laboratory (TRACER-CAT-LANL, July 2022) was designed to complement the larger ARM TRACER science goals to understand convective cloud lifecycles and aerosol-convection interactions. TRACER-CAT-LANL is focused on understanding the relationship between particle composition and light absorption and the influence of water uptake on this relationship. This aerosol and trace gas data can be used to understand the relationship between particle composition and light absorption and the influence of water uptake on this relationship. Instruments Include: Picarro GHG Photoacoustic Soot Spectrometer (PASS-3) Humidified-cavity attenuated phase shift-single scattering albedo particulate matter monitor (H-CAPS-PMSSA) Soot Particle Aerosol Mass Spectrometer (SPAMS) Single-Particle Soot Photometer (SP2) Cloud Condensation Nuclei Counter (CCNc) Aerodynamic Particle Sizer (APS) Scanning Mobility Particle Sizer (SMPS)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER-CAT-LANL Aerosol Optics and Chemical Speciation - CCN

Aerosol size distribution, optical properties, and speciation data collected in La Port TX, during TRACER-CAT-LANL, July 2022, with basic trace gas measurements. All sampling was conducted with an identical aerosol inlet as the standard ARM-AOS systems. The TRacking Aerosol Convection interactions ExpeRiment Carbonaceous Aerosols Thrust by Los Alamos National Laboratory (TRACER-CAT-LANL, July 2022) was designed to complement the larger ARM TRACER science goals to understand convective cloud lifecycles and aerosol-convection interactions. TRACER-CAT-LANL is focused on understanding the relationship between particle composition and light absorption and the influence of water uptake on this relationship. This aerosol and trace gas data can be used to understand the relationship between particle composition and light absorption and the influence of water uptake on this relationship. Instruments Include: Picarro GHG Photoacoustic Soot Spectrometer (PASS-3) Humidified-cavity attenuated phase shift-single scattering albedo particulate matter monitor (H-CAPS-PMSSA) Soot Particle Aerosol Mass Spectrometer (SPAMS) Single-Particle Soot Photometer (SP2) Cloud Condensation Nuclei Counter (CCNc) Aerodynamic Particle Sizer (APS) Scanning Mobility Particle Sizer (SMPS)

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Advanced atmospheric sounder and imaging radiometer /AASIR/ for STORMSAT

The principal mission of the three-axis stabilized STORMSAT spacecraft is to provide the necessary meteorological data for tracking, studying the detailed structure, and modeling mesoscale weather phenomena. In the area of mesoscale events, the following meteorological objectives are indicated: high-quality imagery, visible and infrared; wind velocity from cloud tracers (1 m/sec), atmospheric temperature profiles (1 K), and atmospheric humidity sounding. These objectives are reflected in the functional characteristics of the AASIR, which is a second generation meteorological sensor based on the Visible Infrared Spin-Scan Radiometer (VISSR) and the Atmospheric Sounder (VAS). The AASIR design and interface constraints with the STORMSAT spacecraft is discussed.

Chase, S. C.↗
NASA NTRS2005

Channel alignment and radiometry in hyperspectral atmospheric infrared sounders

The Atmospheric Infrared Sounder (AIRS) is a hyper-spectral infrared sounder which covers the 3.7 to 15,4 micron region with 2378 spectral channels. The AIRS instrument specification called for spatial co-registration of all channels to better than 2% of the field of view. Pre-launch testing confirmed that this requirement was met, since the standard deviations in the centroids was about 1% of the 13.5 km IFOV in scan and 3% in track. Detailed analysis of global AIRS data show that the typical scene gradient in 10 micron window channels is about I .3K/km rms. The way these gradients, which are predominantly caused by clouds, manifest themselves in the data depends on the details of the instrument design and the way the spectral channels are used in the data analysis, AIRS temperature and moisture retrievals use 328 of the 2378 channels from 17 independent arrays. As a result, the effect of the boresight misalignment averages to zero mean. Any increase in the effective noise is less than 0.2K. Also, there is no discernable performance degradation of products at the 45 km spatial resolution in the presence of partially cloudy scenes with up to 80% cloudiness. Single pixel radiometric differences between channels with boresight alignment differences can be appreciable and can affect scientific investigations on a single 15km footprint scale, particularly near coastlines, thunderstorms and surface emissivity inhomogeneities.

sounders↗
NASA NTRS2019

Radiometric Model and Inter-Comparison Results of the SGLI-VNR On-Board Calibration

The Second Generation Global Imager (SGLI) on Global Change Observation Mission– Climate (GCOM-C) satellite empowers surface and atmospheric measurements related to the carbon cycle and radiation budget, with two radiometers of Visible and Near Infrared Radiometer (SGLI-VNR) and Infrared Scanning Radiometer (SGLI-IRS) that perform a wide-band (380 nm–12 µm) optical observation not only with as wide as a 1150–1400 km field of view (FOV), but also with as high as 0.25–0.5 km resolution. Additionally, polarization and along-track slant view observations are quite characteristic of SGLI. It is important to calibrate radiometers to provide the sensor data records for more than 28 standard products and 23 research products including clouds, aerosols, ocean color, vegetation, snow and ice, and other applications. In this paper, the radiometric model and the first results of on-board calibrations on the SGLI-VNR, which include weekly solar and light-emitting diode (LED) calibration and monthly lunar calibration, will be described. Each calibration data was obtained with corrections, where beta angle correction and avoidance of reflection from multilayer insulation (MLI) were applied for solar calibration; LED temperature correction was performed for LED calibration; and the GIRO (GSICS (Global Space-based Inter-Calibration System) Implementation of the ROLO (RObotic Lunar Observatory) model) model was used for lunar calibration. Results show that the inter-comparison of the relative degradation amount between these three calibrations agreed to within 1% or less.

Urabe, Tomoyuki↗
DOE OSTI2025

Optical Particle Measurements during EPCAPE Field Campaign Report

This campaign requested the deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility optical particle counter (OPC) at the first ARM Mobile Facility (AMF1) located at the Scripps Pier in La Jolla, California during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE). The addition of the OPC was requested for two reasons. (1) Close the gap between the scanning mobility particle sizer (SMPS) and aerodynamic particle sizer (APS) size distribution from the Aerosol Observing System (AOS) measurements. (2) Principal investigator Petters has been working with Tracking Aerosol Convection Interaction Experiment (TRACER) data to compute particle fluxes from Doppler lidar (Petters et al. 2024). Briefly, backscatter flux is obtained using the eddy covariance technique using the Doppler vertical velocity and attenuated backscatter. Building upon prior studies, we were able to relate backscatter to particle number concentration by calibrating the lidar retrievals against optical particle counter-measured ground-based aerosol size distribution and radiosonde-interpolated relative humidity at lidar sample height. Performing similar analysis was of interest to EPCAPE to better understand the emissions and vertical transport of large particles into the overlying stratus clouds. However, as stated above, this analysis requires an optical size distribution that covers the 0.3-30-μm-diameter size range. The OPC was deployed between 2023-04-14 and 2024-02-14. The deployment, data quality analysis, and data archiving was handled by the DOE ARM instrument mentor team without additional involvement by the principal investigator. Data quality was marked as “routine” for the majority of the campaign.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Development of an Extended Reality (XR) Tool for Earth Science Visualization

In this presentation, we will discuss our work in adapting the NASA open source XR software, the Mixed Reality Exploration Toolkit (MRET), to an earth science domain. MRET is a NASA open source XR software for rapidly building extended reality (XR) environments for NASA domain problems, e.g., pulling in CAD models of thermal vac chamber and Roman Space Telescope to do fit checks. Primarily used for hardware integration & test, we have been adapting and extending MRET for science problems. Traditionally, scientists view and analyze the result of calculated or measured observables with static 1-D, 2-D or 3-D plots. It can be difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. Additionally, numerical models, such as the NASA GEOS climate model, are almost exclusively formulated and analyzed on Eulerian grids with points fixed in space and time. However, atmospheric phenomena such as convective clouds, hurricanes and wildfire smoke plumes move with the 3-D flow field, and it is often difficult and unnatural to understand these phenomena in an Eulerian reference frame as opposed to the Lagrangian reference frame in which nature operates. As part of an Earth Science Technology Office (ESTO) proposal, we have been adapting MRET to be a scientific exploration and analysis XR tool with integrated Lagrangian Dynamics (LD) for the Goddard Earth Observing System (GEOS) numerical weather prediction model. We believe this will help scientists identify, track, and understand the evolution of Earth Science phenomena. This presentation will discuss current results in our work in developing this XR tool for Earth Science.

Thomas G Grubb↗
NASA NTRSDate not supplied

Development of an Extended Reality (XR) Tool for Earth Science Visualization

In this presentation, we will discuss our work in adapting the NASA open source XR software, the Mixed Reality Exploration Toolkit (MRET), to an earth science domain. MRET is a NASA open source XR software for rapidly building extended reality (XR) environments for NASA domain problems, e.g., pulling in CAD models of thermal vac chamber and Roman Space Telescope to do fit checks. Primarily used for hardware integration & test, we have been adapting and extending MRET for science problems. Traditionally, scientists view and analyze the result of calculated or measured observables with static 1-D, 2-D or 3-D plots. It can be difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. Additionally, numerical models, such as the NASA GEOS climate model, are almost exclusively formulated and analyzed on Eulerian grids with points fixed in space and time. However, atmospheric phenomena such as convective clouds, hurricanes and wildfire smoke plumes move with the 3-D flow field, and it is often difficult and unnatural to understand these phenomena in an Eulerian reference frame as opposed to the Lagrangian reference frame in which nature operates. As part of an Earth Science Technology Office (ESTO) proposal, we have been adapting MRET to be a scientific exploration and analysis XR tool with integrated Lagrangian Dynamics (LD) for the Goddard Earth Observing System (GEOS) numerical weather prediction model. We believe this will help scientists identify, track, and understand the evolution of Earth Science phenomena. This presentation will discuss current results in our work in developing this XR tool for Earth Science.

Thomas Grubb↗
DOE OSTI2020

The Amazonian Low-Level Jet and Its Connection to Convective Cloud Propagation and Evolution

In this work, we describe the existence of an Amazonian low-level jet (ALLJ) that can affect the propagation and life cycle of convective systems from the northeast coast of South America into central Amazonia. Horizontal winds from reanalysis were analyzed during March–April–May (MAM) of the two years (2014–15) of the GoAmazon2014/5 field campaign. Convective system tracking was performed using GOES-13 infrared imagery and classified into days with high and weak convective activity. The MAM average winds show a nocturnal enhancement of low-level winds starting near the coast in the early evening and reaching 1600 km inland by late morning. Mean 3-hourly wind speeds maximize at 9–10 m s -1 near 900 hPa, but individual days can have nighttime low-level winds exceeding 12 m s -1 . Based on objective low-level wind criteria, the ALLJ is present 10%–40% of the time over the Amazon during MAM depending on the location and time of day. The evolution of the ALLJ across the Amazon impacts the frequency of occurrence of cloud clusters and the intensity of the moisture flux. In addition, the ALLJ is associated with the enhancement of northeasterly flow in the midtroposphere during active convective days, when vertical momentum transport may be occurring in the organized cloud clusters. During the weakly active convective period, the ALLJ is weaker near the coast but stronger across the central Amazon and appears to be linked more directly with the South American low-level jet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Nonparametric, data-based kernel interpolation for particle-tracking simulations and kernel density estimation

Traditional interpolation techniques for particle tracking include binning and convolutional formulas that use pre-determined (i.e., closed-form, parameteric) kernels. In many instances, the particles are introduced as point sources in time and space, so the cloud of particles (either in space or time) is a discrete representation of the Green’s function of an underlying PDE. As such, each particle is a sample from the Green’s function; therefore, each particle should be distributed according to the Green’s function. In short, the kernel of a convolutional interpolation of the particle sample “cloud” should be a replica of the cloud itself. This idea gives rise to an iterative method by which the form of the kernel may be discerned in the process of interpolating the Green’s function. When the Green’s function is a density, this method is broadly applicable to interpolating a kernel density estimate based on random data drawn from a single distribution. We formulate and construct the algorithm and demonstrate its ability to perform kernel density estimation of skewed and/or heavy-tailed data including breakthrough curves.

42 ENGINEERING↗
NASA NTRS1993

Cosmological gamma-ray burst model

A cosmological gamma-ray burst model that reproduces the observed gamma-ray spectra was developed. This model, which is an outgrowth of work on synchrotron emission from cosmological sources, creates the observed spectra from a power law spectrum through Compton attenuation in dense molecular clouds. It restricts the burst source to the centers of galaxies, and it is easily tested through comparisons with time dependent burst spectra. Dr. Brainerd continued development of a Monte Carlo code that tracks the random walk of a gamma-ray through a plasma in a strong magnetic field and used this code to show that a two temperature plasma in a strong magnetic field can suppress soft x-ray emission.

Brainerd, J. J.↗
NASA NTRS2002

Better Weather Prediction and Climate Diagnostics Using Rainfall Measurements from Space

Progress in understanding of the role of water in global weather and climate is currently limited by our knowledge of the spatial and temporal variability of primary hydrological fields such as precipitation and evaporation. The Tropical Rainfall Measuring Mission (TRMM) has recently demonstrated that use of microwave-based rainfall observations from space in data assimilation can provide better climate data sets and improve short-range weather forecasting. At NASA, we have been exploring non-traditional approaches to assimilating TRMM Microwave Imager (TMI) and Special Sensor Microwavehager (SSM/I) surface rain rate and latent heating profile information in global systems. In this talk we show that assimilating microwave rain rates using a continuous variational assimilation scheme based on moisture tendency corrections improves quantitative precipitation estimates (QPE) and related clouds, radiation energy fluxes, and large-scale circulations in the Goddard Earth Observing System (GEOS) reanalyses. Short-range forecasts initialized with these improved analyses also yield better QPE scores and storm track predictions for Hurricanes Bonnie and Floyd. We present a status report on current efforts to assimilate convective and stratiform latent heating profile information within the general variational framework of model parameter estimation to seek further improvements. Within the next 5 years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007/2008. Based on what has been learned from TRMM, there is a high degree of confidence that these observations can play a'major role in improving weather forecasts and producing better global datasets for understanding the Earth's water and energy cycle. The key to success is to adopt an integrated approach to retrieval, validation, modeling, and data assimilation in a coordinated end-to-end observation-application program.

Hou, Arthur↗
NASA NTRS2014

Aerosol, Cloud and Trace Gas Observations Derived from Airborne Hyperspectral Radiance and Direct Beam Measurements in Recent Field Campaigns

The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions. The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. Dunagan et al. [2013] present results establishing the performance of the instrument, along with calibration, engineering flight test, and preliminary scientific field data. The 4STAR instrument operated successfully in the SEAC4RS [Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys] experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE [Department of Energy]-sponsored TCAP [Two Column Aerosol Project, July 2012 & Feb. 2013] experiment aboard the DoE G-1 aircraft (Shinozuka et al., 2013), and acquired a wealth of data in support of mission objectives on all SEAC4RS and TCAP research flights. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2; Segal-Rosenheimer et al., 2014), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In addition, 4STAR measured zenith radiances underneath cloud decks for retrievals of cloud optical depth and effective diameter. In this presentation, we provide an overview of the new 4STAR capabilities for airborne field campaigns, with an emphasis on comparisons between 4STAR and AERONET sky radiances, and retrievals of aerosol microphysical properties based on sky radiance measurements, column trace gas amounts from spectral direct beam measurements and cloud property retrievals from zenith mode observations for a few select case studies in the SEAC4RS and TCAP experiments. We summarize the aerosol, trace gas, cloud and airmass characterization studies made possible by the combined 4STAR direct beam, and sky/zenith radiance observations.

Aerosol-Climate↗
NASA NTRSDate not supplied

Characterization of Large Drop Velocity in the NASA Icing Research Tunnel

This paper presents experimental work conducted in the Icing Research Tunnel at NASA Glenn Research Center to characterize the velocity of large drops in the test section. Some icing spray clouds with large drops were generated with Mod1 nozzles at low nozzle air pressure of 2 to 4 psig for various tunnel air speeds. Drop diameters and drop velocities were measured via high-resolution imaging with a Particle Imaging Particle Tracking Velocimetry probe developed by Artium Technologies. The probe was mounted at four different locations aligned with the centerline of the test section from near the end of the contraction to the constant height test section part of the tunnel. CFD analyses were performed. It showed that the probe head geometry affects the local air flow in the measurement area of the probe between the prongs and in front of the probe. Initial analysis of the air velocity data during the test also indicated that the probe mounting stand has blockage effect on the local tunnel air velocity measurement by a pitot-static probe affixed on the mounting plate next to the stand. Those findings were later verified in the Icing Research Tunnel using a new pitot-static probe design with a linear motion system to measure the local tunnel air velocity with and without the probe. As a result, additional drop trajectory simulations were performed with the airflow moving towards the probe head with a Langmuir-D 7-bin distribution cloud containing large drops. The simulation results helped identify a critical drop-size threshold of 300 μm above which the velocities of larger drops are negligibly affected by the adverse pressure gradient generated by the probe head due to their large drop inertia. From the dimensional analysis of the drop velocity measurement data obtained, it showed that at the tunnel test section reference location a generalized empirical correlation was developed for the non-dimensional drop velocity as a function of the non-dimensional corrected drop diameter independent of the actual spraybar pressure settings and the tunnel air speeds. The generalized curve-fit correlation showed that the drop velocity was universally asymptotic to about 86 percent of the corresponding tunnel air speed at the test section reference location for the largest drop diameter captured by the probe. Further evaluation of this correlation is recommended to assess its applicability for Supercooled Large Drop icing scaling applications in the Icing Research Tunnel.

SLD↗
NASA NTRS2013

Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and recent applications within the operational forecasting environment

Molthan, Andrew L.↗
DOE OSTI2025

Targeted Mobile Measurements to Isolate the Impacts of Aerosols and Meteorology on Deep Convection

One of the main goals of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign near Houston, TX was to improve understanding of meteorology and aerosol effects on deep convective storms. To help TRACER achieve its goals of disentangling aerosol-cloud interactions from meteorology, the Texas A&M University (TAMU) team deployed the new fully mobile Rapid Onsite Atmospheric Measurement Van (ROAM-V) carrying instruments to measure aerosol and atmospheric properties that was moved to multiple locations on a deployment day of isolated convection initiated by the sea breeze.

54 ENVIRONMENTAL SCIENCES↗