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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

STS-72 Flight Day 3

On this third day of the STS-72 mission, the flight crew, Cmdr. Brian Duffy, Pilot Brent W. Jett, and Mission Specialists Leroy Chiao, Daniel T. Barry, Winston E. Scott, and Koichi Wakata (NASDA), awakened to a traditional Japanese song, 'Sea in Springtime.' Wakata, using the shuttle's robot arm, successfully retrieved the Japanese Space Flyer Unit (SFU) satellite and berthed it in the shuttle's cargo bay. Duffy and Wakata were interviewed, via satellite, by Japanese journalists and reporters in Houston, Texas. Earth views include cloud cover, storm systems, Africa and several other land masses.

Source record↗
NASA NTRS1999

Comparison of Ground-Based 3-Dimensional Lightning Mapping Observations with Satellite-Based LIS Observations in Oklahoma: Comparison of LMS and LIS Lightning Mapping

3-dimensional lightning mapping observations obtained during the MEaPRS program in central Oklahoma during June, 1998 have been compared with observations of the discharges from space, obtained by NASA's Lightning Imaging Sensor (LIS) on the TRMM satellite. Excellent spatial and temporal correlations were observed between the two sets of observations. Most of the detected optical events were associated with intracloud discharges that developed into the upper part of the storm. Cloud-to-ground discharges that were confined to mid- and lower-altitudes tended not to be detected by LIS. Extensive illumination tended to occur in impulsive bursts toward the end or part way through intracloud flashes and appeared to be produced by energetic K-changes that typically occur at these times.

Thomas, Ronald J.↗
NASA NTRS1999

Comparison of Ground-Based 3-Dimensional Lightning Mapping Observation with Satellite-Based LIS Observations in Oklahoma

3-dimensional lightning mapping observations were obtained in central Oklahoma during June 1998, using New Mexico Tech's Lightning Mapping Array (LMA). The results have been compared with observations of the discharges from space obtained by NASA's Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) spacecraft. Excellent spatial and temporal correlations were obtained between the two sets of observations. All discharges seen by LIS were mapped by the LMA. Most of the detected optical events were associated with lightning channels that extended into the upper part of the storm. Cloud-to-ground discharges that were confined to mid- and lower-altitudes tended to be detected by LIS at the time of late-stage return strokes. Extensive illumination tended to occur in impulsive bursts toward the end or part way through intracloud discharges and appeared to be produced by energetic K-changes that typically occur at these times.

Thomas, Ronald J.↗
NASA NTRS2000

Channel Selection for the Advanced Baseline Imager (ABI)

The GOES-R (Geostationary Operational Environmental Satellite-R) Imager will be the fourth generation imaging radiometer flown in 40 years that observes the western hemisphere from geosynchronous orbit. The Imager is an international resource for information about unpredictable short-term mesoscale phenomena such as severe storms, precipitation, clouds and fog, fires and volcanoes. As such, it must provide: (1) continuity of service, (2) valuable new capabilities, and (3) synergy with the companion fleet of imaging radiometers. This combination of requirements lead to a suite of channels evolved from the generations of LEO (low Earth orbit) and GEO- (geosynchronous Earth orbit) and -sounders. To maximize the science and applications payoff from its unique viewpoint, the next generation GOES Imager should concentrate upon regional measurements of the chaotic atmospheric phenomena involving water and the diurnal cycle -- energy potential, moisture transport, phase changes, precipitation, and cloud climatology.

Chesters, Dennis↗
NASA NTRS2007

OMI Tropospheric NO2 from Lightning in Observed Convective Events

Lightning is responsible for an estimated 15 percent of total NO emissions, and is one of the most prominent sources in the upper troposphere. In this study, we present evidence of lightning-generated NO2 (LNO2) using data from the Ozone Monitoring Instrument (OMI), which has observed tropospheric NO2 since its launch in 2004. Although LNO2 has been also reported in previous satellite studies from the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY, OMI is better suited for such measurements by virtue of its higher spatial resolution and daily global coverage. We will present data clearly showing the LNO2 signal in the OMI tropospheric NO2 product on two days over and downwind of specific convective systems in the US Midwest. Gridded monthly mean tropospheric NO 2 data are subtracted from the daily gridded data to obtain the presumed LNO2 signal. Observed cloud-to-ground (CG) lightning flashes from the National Lightning Detection Network (NLDN) were counted along middle and upper tropospheric back trajectories that were run from the regions containing the LNO2 signal. A vertically-weighted average number of upwind CG flashes was obtained using a profile of LNO(x) mass obtained from a series of midlatitude cloud-resolved storm chemistry simulations. The number of CG flashes was scaled up to total flashes (intracloud (IC) flashes plus CG) using a climatological IC/CG ratio. The number of moles of LNO(x) in the region considered was estimated by assuming that LNO2 is 30 percent of LNO(x). This value was divided by the number of upwind flashes to obtain an average estimate of the number of moles produced per flash. Results yield values in the range obtained through other estimation techniques (e.g., aircraft measurements, models). We will also present a similar analysis over northern Australia during the SCOUT-O3/ACTIVE field campaigns in November and December 2005, in which we will compare the OMI LNOx signals with aircraft observations from the storm anvils.

Pickering, Kenneth↗
NASA NTRS2014

Terminal Area Simulation System User's Guide - Version 10.0

The Terminal Area Simulation System (TASS) is a three-dimensional, time-dependent, large eddy simulation model that has been developed for studies of wake vortex and weather hazards to aviation, along with other atmospheric turbulence, and cloud-scale weather phenomenology. This document describes the source code for TASS version 10.0 and provides users with needed documentation to run the model. The source code is programed in Fortran language and is formulated to take advantage of vector and efficient multi-processor scaling for execution on massively-parallel supercomputer clusters. The code contains different initialization modules allowing the study of aircraft wake vortex interaction with the atmosphere and ground, atmospheric turbulence, atmospheric boundary layers, precipitating convective clouds, hail storms, gust fronts, microburst windshear, supercell and mesoscale convective systems, tornadic storms, and ring vortices. The model is able to operate in either two- or three-dimensions with equations numerically formulated on a Cartesian grid. The primary output from the TASS is time-dependent domain fields generated by the prognostic equations and diagnosed variables. This document will enable a user to understand the general logic of TASS, and will show how to configure and initialize the model domain. Also described are the formats of the input and output files, as well as the parameters that control the input and output.

Switzer, George F.↗
NASA NTRS1992

Deuterium in North Atlantic storm tops

During the ERICA project in 1989, ice crystals were collected from the tops of two winter storms and one broad cirrus cloud. Deuterium concentration in the storm ice samples, together with a model of isotope fractionation, are used to determine the temperature where the ice was formed. Knowledge of the ice formation temperature allows us to determine whether the ice has fallen or been lofted to the altitude of collection. In both storms, the estimated fall distance decreases upward. In the 21 January storm, the fall distance decreases to zero at the cloud top. In the 23 January storm, the fall distance decreases to zero at a point 2 km below the cloud top and appears to become negative above, indicating lofted ice. Cloud particle data from the cloud tops show an ice-to-vapor ratio greater than one and indicate the presence of particles with small terminal velocities; both observations support the idea of ice lofting. The satellite-derived cloud tops lie well below the actual cloud top (e.g., 2.5 km below on 23 January), indicating that the lofted ice in winter storms may not be detectable from space using IR radiance techniques. A comparison of deuterium in cloud-top ice and clear-air vapor suggests that even in winter, when vertical air motions are relatively weak, lofted ice crystals are the dominant source of water vapor in the upper troposphere.

Smith, Ronald B.↗
NASA NTRS1982

Remote sensing of tornadic storms from space

By using infrared images obtained from GOES satellite, the digital count values of pixels representing blackbody temperatures of the cloud top, convective storms are observed throughout their life cycles. Clouds associated with a tornadic storm are compared with those without a tornadic storm to illustrate how the infrared and visible observations from a geosynchronous satellite can be used to study the differences in their life cycles.

Hung, R. J.↗
DOE OSTI2021

Utilizing a Storm-Generating Hotspot to Study Convective Cloud Transitions: The CACTI Experiment

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Mixed-phase orographic cloud microphysics during StormVEx and IFRACS

Wintertime mixed-phase orographic cloud (MPC) measurements were conducted at the Storm Peak Laboratory (SPL) during the Storm Peak Lab Cloud Property Validation Experiment (StormVEx) and Isotopic Fractionation in Snow (IFRACS) programs in 2011 and 2014, respectively. The data include 92 h of simultaneous measurements of supercooled liquid cloud droplet and ice particle size distributions (PSDs). Average cloud droplet number concentration (CDNC), droplet size (NMD), and liquid water content (LWC) were similar in both years, while ice particle concentration (Ni) and ice water content (IWC) were higher during IFRACS. The consistency of the liquid cloud suggests that SPL is essentially a cloud chamber that produces a consistent cloud under moist, westerly flow during the winter. A variable cloud condensation nuclei (CCN)-related inverse relationship between CDNC and NMD strengthened when the data were stratified by LWC. Some of this variation is due to changes in cloud base height below SPL. While there was a weak inverse correlation between LWC and IWC in the data as a whole, a stronger relationship was demonstrated for a case study on 9 February 2014 during IFRACS. A minimum LWC of 0.05 g m–3 showed that the cloud was not completely glaciated on this day. Erosion of the droplet distribution at high IWC was attributed to the Wegener–Bergeron–Findeisen process as the high IWC was accompanied by a 10-fold increase in Ni. A relationship between large cloud droplet concentration (25–35 µm) and small ice particles (75–200 µm) under cold (<–8 °C) but not warm (>–8 °C) conditions during IFRACS suggests primary ice particle production by contact or immersion freezing. The effect of blowing snow was evaluated from the relationship between wind speed and Ni and by comparing the relative (percent) ice particle PSDs at high and low wind speeds. These were similar, contrary to expectation for blowing snow. However, the correlation between wind speed and ice crystal concentration may support this explanation for high crystal concentrations at the surface. Secondary processes could have contributed to high crystal concentrations but there was no direct evidence to support this. Further experimental work is needed to resolve these issues.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Tiny Particles, Big Storms

Tiny particles have a lot of clout when it comes to powering large storms in the Amazon, scientists from PNNL and collaborators from around the globe show in a paper in the journal Science.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

CRYSTAL-FACE Polarization Lidar Research

The University of Alaska Fairbanks (UAF) Polarization Diversity Lidar (PDL, Sassen 1994) participated in the July 2002 CRYSTAL-FACE field campaign, shortly after the PI moved from the University of Utah to UAF. The truck-mounted PDL is an advanced dual wavelength (1.06 and 0.532 micron), high resolution (0.1-s by 1.5-m), scanning lidar system designed as a testbed for evaluating laser backscatter depolarization techniques for the study of clouds and aerosols in the atmosphere. The main goals identified in our proposal for the CRYSTAL-FACE experiment were, i) the characterization of Florida thunderstorm anvil macrophysical and microphysical properties from lidar backscattering and depolarization, ii) the study of thin to subvisual tropopause-topped subtropical cirrus, iii) the search for indirect cloud effects of trans- Atlantic advected Saharan dust storm aerosols on clouds, and iv) the investigation of melting layer effects on lidar and multi-wavelength Doppler radar measurements in precipitation. Although we experienced adversity in the field during the campaign, sufficient data was collected to begin addressing these topics, and several conference presentations, three journal articles, and one book chapter have resulted from the data analysis effort supported by this grant. (PDL operations were delayed by FAA concerns over the initial sighting at the Kendall-Tamiami Airport, and a brief but major laser breakdown was experienced during the re- setup at the remote Ochopee Everglades site that also supported the N-POL radar.) All lidar data collected by the PDL system were processed and quality checked, and submitted to the CRYSTAL-FACE data archive in a timely manner.

Sassen, Kenneth↗
NASA NTRS2021

Using Intelligent Targeting to increase the science return of a Smart Ice Storm Hunting Radar

Smart Ice Cloud Sensing (SMICES) is a small-sat concept in which a radar intelligently targets ice storms based on information collected by a lookahead radiometer. Often space observations are performed by continuously collecting data from an instrument aimed at nadir (e.g. directly below the space platform). However, if the platform has the ability to assess science utility of features being overflown, an intelligent measurement scheme can improve science return. This can be achieved by controlling the on/off state of the instrument if it is not able to continuously operate (e.g. due to energy or thermal constraints), and by allowing the instrument to view off nadir if it has pointing capabilities.In the case of SMICES, power constraints and the rarity of storms means that with blind nadir targeting SMICES would collect a limited amount of ice storm radar data. The algorithms proposed acquire measurements to maximize acquired high interest storms while concurrently collecting a background sampling of all features. We use a cloud classification system to identify five different cloud types. Six algorithms ranging from “blind” to more selective are described and results from evaluation on a dataset of 13 ground swaths covering 72,399,600 km2 of data are presented. This data is from high quality science simulations that contain all five cloud types and multiple storms. When utilizing the radiometer’s lookahead and the full range of the radar the results show a 23.7x and 1.9x increase over the base algorithm in the most and second most important cloud types respectively.

Cooke, Caitlyn↗
NASA NTRS1979

Oxides of nitrogen and the clouds of Venus

Nitric oxide may be produced in the atmosphere of Venus by lightning storms in the clouds. The paper suggests that the odd nitrogen thus formed may play an important part in the chemistry of the clouds. Specifically, production rates for NO2 in the limiting case of high NO concentrations are estimated. If the NO density is high, it is suggested that NO2 may catalyse the production of sulfuric acid aerosol from sulfur dioxide and water vapor, and may also form nitrogen-sulfur compounds such as nitrosyl sulfuric acid, NOHSO4. The large partricles seen by the Pioneer Venus sounder probe may contain considerable quantities of NOHSO4. If this is the case, odd nitrogen must be present in the atmosphere in at least a parts-per-million mixing ratio.

Watson, A. J.↗
NASA NTRS2001

Observed and Simulated Radiative and Microphysical Properties of Tropical Convective Storms

Increases in the ice content, albedo and cloud cover of tropical convective storms in a warmer climate produce a large negative contribution to cloud feedback in the GISS GCM. Unfortunately, the physics of convective upward water transport, detrainment, and ice sedimentation, and the relationship of microphysical to radiative properties, are all quite uncertain. We apply a clustering algorithm to TRMM satellite microwave rainfall retrievals to identify contiguous deep precipitating storms throughout the tropics. Each storm is characterized according to its size, albedo, OLR, rain rate, microphysical structure, and presence/absence of lightning. A similar analysis is applied to ISCCP data during the TOGA/COARE experiment to identify optically thick deep cloud systems and relate them to large-scale environmental conditions just before storm onset. We examine the statistics of these storms to understand the relative climatic roles of small and large storms and the factors that regulate convective storm size and albedo. The results are compared to GISS GCM simulated statistics of tropical convective storms to identify areas of agreement and disagreement.

DelGenio, Anthony D.↗
DOE OSTI2022

Three-Dimensional Convective–Stratiform Echo-Type Classification and Convectivity Retrieval from Radar Reflectivity

The Echo Classification from COnvectivity (ECCO) algorithm identifies convective and stratiform types of radar echo in three dimensions. It is based on the calculation of reflectivity texture—a combination of the intensity and the heterogeneity of the radar echoes on each horizontal plane in a 3D Cartesian volume. Reflectivity texture is translated into convectivity, which is designed to be a quantitative measure of the convective nature of each 3D radar grid point. It ranges from 0 (100% stratiform) to 1 (100% convective). By thresholding convectivity, a more traditional qualitative categorization is obtained, which classifies radar echoes as convective, mixed, or stratiform. In contrast to previous algorithms, these echo-type classifications are provided on the full 3D grid of the reflectivity field. The vertically resolved classifications, in combination with temperature data, allow for subclassifications into shallow, mid-, deep, and elevated convective features, and low, mid-, and high stratiform regions—again in three dimensions. The algorithm was validated using datasets collected over the U.S. Great Plains during the PECAN field campaign. An analysis of lightning counts shows ~90% of lightning occurring in regions classified as convective by ECCO. A statistical comparison of ECCO echo types with the well-established GPM radar precipitation-type categories show 84% (88%) of GPM stratiform (convective) echo being classified as stratiform (convective) or mixed by ECCO. ECCO was applied to radar grids for the continental United States, the United Arab Emirates, Australia, and Europe, illustrating its robustness and adaptability to different radar grid characteristics and climatic regions.

Radars/Radar observations↗