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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Cloud Properties Derived From GOES-7 for Spring 1994 ARM Intensive Observing Period Using Version 1.0.0 of ARM Satellite Data Analysis Program

This document describes the initial formulation (Version 1.0.0) of the Atmospheric Radiation Measurement (ARM) program satellite data analysis procedures. Techniques are presented for calibrating geostationary satellite data with Sun synchronous satellite radiances and for converting narrowband radiances to top-of-the-atmosphere fluxes and albedos. A methodology is documented for combining geostationary visible and infrared radiances with surface-based temperature observations to derive cloud amount, optical depth, height, thickness, temperature, and albedo. The analysis is limited to two grids centered over the ARM Southern Great Plains central facility in north-central Oklahoma. Daytime data taken during 5 Apr. - 1 May 1994, were analyzed on the 0.3 deg and 0.5 deg latitude-longitude grids that cover areas of 0.9 deg x 0.9 deg and 10 deg x 14 deg, respectively. Conditions ranging from scattered low cumulus to thin cirrus and thick cumulonimbus occurred during the study period. Detailed comparisons with hourly surface observations indicate that the mean cloudiness is within a few percent of the surface-derived sky cover. Formats of the results are also provided. The data can be accessed through the World Wide Web computer network.

Minnis, Patrick↗
NASA NTRS2016

Satellite-Surface Perspectives of Air Quality and Aerosol-Cloud Effects on the Environment: An Overview of 7-SEAS BASELInE

The objectives of 7-SEASBASELInE (Seven SouthEast Asian Studies Biomass-burning Aerosols and Stratocumulus Environment: Lifecycles and Interactions Experiment) campaigns in spring 2013-2015 were to synergize measurements from uniquely distributed ground-based networks (e.g., AERONET (AErosol RObotic NETwork)), MPLNET ( NASA Micro-Pulse Lidar Network)) and sophisticated platforms (e.g.,SMARTLabs (Surface-based Mobile Atmospheric Research and Testbed Laboratories), regional contributing instruments), along with satellite observations retrievals and regional atmospheric transport chemical models to establish a critically needed database, and to advance our understanding of biomass-burning aerosols and trace gases in Southeast Asia (SEA). We present a satellite-surface perspective of 7-SEASBASELInE and highlight scientific findings concerning: (1) regional meteorology of moisture fields conducive to the production and maintenance of low-level stratiform clouds over land; (2) atmospheric composition in a biomass-burning environment, particularly tracers-markers to serve as important indicators for assessing the state and evolution of atmospheric constituents; (3) applications of remote sensing to air quality and impact on radiative energetics, examining the effect of diurnal variability of boundary-layer height on aerosol loading; (4) aerosol hygroscopicity and ground-based cloud radar measurements in aerosol-cloud processes by advanced cloud ensemble models; and (5) implications of air quality, in terms of toxicity of nanoparticles and trace gases, to human health. This volume is the third 7-SEAS special issue (after Atmospheric Research, vol. 122, 2013; and Atmospheric Environment, vol. 78, 2013) and includes 27 papers published, with emphasis on air quality and aerosol-cloud effects on the environment. BASELInE observations of stratiform clouds over SEA are unique, such clouds are embedded in a heavy aerosol-laden environment and feature characteristically greater stability over land than over ocean, with minimal radar surface clutter at a high vertical spatial resolution. To facilitate an improved understanding of regional aerosol-cloud effects, we envision that future BASELInE-like measurement modeling needs fall into two categories: (1) efficient yet critical in-situ profiling of the boundary layer for validating remote-sensing retrievals and for initializing regional transport chemical and cloud ensemble models; and (2) fully utilizing the high observing frequencies of geostationary satellites for resolving the diurnal cycle of the boundary layerheight as it affects the loading of biomass-burning aerosols, air quality and radiative energetics.

AERONET↗
NASA NTRS2004

The Cloud Detection and Ultraviolet Monitoring Experiment (CLUE)

In this paper we describe a new balloon instrument - CLUE - which is designed to monitor ultraviolet (uv) nightglow levels and determine cloud cover and cloud heights with a CO2 slicing technique. The CO2 slicing technique is based on the MODIS instrument on NASA's Aqua and Terra spacecraft. CLUE will provide higher spatial resolution (0.5 km) and correlations between the uv and the cloud cover.

Barbier, Louis M.↗
NASA NTRS2019

Assessment of ICESat-2 Ice Sheet Surface Heights, Based on Comparisons over the Interior of the Antarctic Ice Sheet

We collected kinematic Global Navigation Satellite Systems (GNSS) surface height data, on a 750‐km ground‐based traverse of the flat interior of the Antarctic ice sheet, for comparison with Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) surface heights. Vertical errors in the GNSS data are estimated to be 5.6 cm, comparable to results from a previous traverse and with year‐to‐year comparisons. Comparisons of the GNSS heights and 6 months of ICESat‐2 ATL03 photon‐based heights and ATL06 segment‐based heights indicate that the accuracy and precision of ICESat‐2 data are comparable to that of results from the ICESat mission: ATL03 is currently accurate to better than 5 cm with better than 13 cm of surface measurement precision, while ATL06 is currently accurate to better than 3 cm with better than 9 cm of surface measurement precision.

Brunt, K. M.↗
NASA NTRS2000

BOREAS TF-8 NSA-OJP and SSA-OBS Ceilometer Data

The BOREAS TF-8 team used ceilometers to collect data on the fraction of the sky covered with clouds and the cloud height. Included with these data is the surface-based lifting condensation level, derived from temperature and humidity values acquired at the flux tower at the NSA-OJP site. Ceilo-meter data were collected at the NSA-OJP site in 1994 and at the NSA-OJP and SSA-OBS sites in 1996. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884).

Moore, Kathleen E.↗
NASA NTRS2021

Development and Analysis of a Thick Cloud Layers Database for Lightning Launch Commit Criteria Improvement

Lightning can pose a potential threat to space launch vehicles. In response to this, rules were created called the Lightning Launch Commit Criteria (LLCC) that help weather personnel evaluate the potential for natural and rocket-triggered lightning. One of the ten LLCC with the least research is called the Thick Cloud Layers rule. To further understand electrification of thick cloud layers and potentially improve the Thick Cloud Layers rule, a database of thick cloud layers that occurred over the Eastern Range was created. This database is then used to create an algorithm for identifying and differentiating thick cloud layers from other cloud types based on radar characteristics, temperature levels in reference to cloud height, and the surface electric field. By analyzing and identifying thick cloud events, this project could help narrow down when thick clouds are occurring and potentially minimize unnecessary launch delays. Events that caused LLCC violations involving the Thick Cloud Layers rule were analyzed by hand using Level-2 NEXRAD radar data from the National Weather Service WSR-88D radar in Melbourne with the program GR2Analyst. Cases that were found to be isolated and not involved with convection were recorded (date, start/end time, location) in a database. Radar data associated with these cases was collected and gridded using Python radar packages. Once gridded, I calculated and recorded for each radar scan the following radar reflectivity driven parameters within an 11x11 km bin centered on each 1 square km grid point: the mean reflectivity colder than 0 degrees Celsius, Maximum Radar Reflectivity (MRR) colder than 0 degrees Celsius, Volume Averaged Height Integrated Radar Reflectivity (VAHIRR), Hydrometeor Identification (HID), the difference between the maximum and mean reflectivity, the cloud depth colder than 0 degrees Celsius, the overall cloud depth, the cloud top, and the cloud bottom. Soundings for each event were used to determine cloud temperature levels, and where the cloud is in relation to the freezing level. Electric field mill data collected over the Eastern Range was used to determine surface electric fields below each cloud. All parameters were analyzed in depth for several thick cloud cases to gain an understanding of typical thick cloud characteristics. Cases of thick clouds and other isolated cloud types were also recorded for training purposes to see if enough differences exist between cloud types to differentiate them with an algorithm. Each case along with its corresponding characteristics was recorded in a database, and this database was used to compare differing cloud types, as well as train the algorithm to detect thick clouds.

Lightning↗
NASA NTRS1997

Development of a prototype algorithm for the operational retrieval of height-resolved products from GOME

Global ozone monitoring experiment (GOME) level 2 products of total ozone column amounts have been generated on a routine operational basis since July 1996. These products and the level 1 radiance products are the major outputs from the ERS-2 ground segment GOME data processor (GDP) at DLR in Germany. Off-line scientific work has already shown the feasibility of ozone profile retrieval from GOME. It is demonstrated how the retrievals can be performed in an operational context. Height-resolved retrieval is based on the optimal estimation technique, #and cloud-contaminated scenes are treated in an equivalent reflecting surface approximation. The prototype must be able to handle GOME measurements routinely on a global basis. Requirements for the major components of the algorithm are described: this incorporates an overall strategy for operational height-resolved retrieval from GOME.

Spurr, Robert J. D.↗
NASA NTRS1990

Turbulence measurements using tethered balloon instrumentation during FIRE 1987

As part of the surface-based observations conducted on San Nicolas Island, the U.K. Meteorological Office operated a set of turbulence probes attached to a balloon tether cable. Typically six probes were used, each capable of measuring momentum, heat, and humidity fluxes. Two probes were fitted with net radiometers, one positioned above cloud and the other below; a third probe carried a Lyman-alpha hygrometer fitted with a pre-heater for the measurement of total water content. Some preliminary results are presented from the 14th July describing the variation in structure of the cloudy boundary layer during the daytime. This day was characterized by a complete cloud cover, an inversion height of approximately 600 m. and north-westerly winds of approximately 6 m.s(-1). As an illustration the equivalent potential temperature derived from a profile ascent made between approximately 0830 and 0930 (PDT) is shown. The data has been smoothed to a height resolution of about 4 metres. At this time the cloud base was approximately 200 m. and very light drizzle was reaching the surface. The vertical velocity variance and potential temperature flux for two periods are shown; the first (shown by full lines) immediately follows the profile and the second (shown by dashed lines) is central around 1400 (PDT). The data have been normalized by their maximum values in the first period. Cloud base has now risen to approximately 300 m. There is a marked variation during the morning, particularly in sigma w. The net radiative flux above cloud top has by now reached its maximum value.

Hignett, Phillip↗
NASA NTRS2014

A Wrf-Chem Flash Rate Parameterization Scheme and LNO(x) Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were added to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Cloud physics↗
NASA NTRS2014

A WRF-Chem Flash Rate Parameterization Scheme and LNOx Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were applied to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Atmospheric chemistry↗
NASA NTRS1986

Retrieval of ammonia abundances and cloud opacities on Jupiter from Voyager IRIS spectra

Gaseous ammonia abundances and cloud opacities are retrieved from Voyager IRIS 5- and 45-micron data on the basis of a simplified atmospheric model and a two-stream radiative transfer approximation, assuming a single cloud layer with 680-mbar base pressure and 0.14 gas scale height. Brightness temperature measurements obtained as a function of emission angle from selected planetary locations are used to verify the model and constrain a number of its parameters.

Conrath, B. J.↗
NASA NTRS2018

Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion

The vast extent and inaccessibility of boreal forest ecosystems are barriers to routine monitoring of forest structure and composition. In this research, we bridge the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale using an unmanned aerial vehicle (UAV) and a structure from motion (SfM) approach. At 20 Forest Inventory and Analysis (FIA) subplots in interior Alaska, we acquired overlapping imagery and generated dense, 3D, RGB (red, green, blue) point clouds. We used these data to model forest type at the individual crown scale as well as subplot-scale tree density (TD), basal area (BA), and aboveground biomass (AGB). We achieved 85% cross-validation accuracy for five species at the crown level. Classification accuracy was maximized using three variables representing crown height, form, and color. Consistent with previous UAV-based studies, SfM point cloud data generated robust models of TD (r(sup 2) = 0.91), BA (r(sup 2) = 0.79), and AGB (r(sup 2) = 0.92), using a mix of plot- and crown-scale information. Precise estimation of TD required either segment counts or species information to differentiate black spruce from mixed white spruce plots. The accuracy of species-specific estimates of TD, BA, and AGB at the plot scale was somewhat variable, ranging from accurate estimates of black spruce TD (+/−1%) and aspen BA (−2%) to misallocation of aspen AGB (+118%) and white spruce AGB (−50%). These results convey the potential utility of SfM data for forest type discrimination in FIA plots and the remaining challenges to develop classification approaches for species-specific estimates at the plot scale that are more robust to segmentation error.

aboveground biomass↗
NASA NTRS2000

SMART Ground-based Radiation Measurements during PRIDE

We deployed a suite of ground-based remote sensing instruments - SMART (Surface Measurements for Atmospheric Radiative Transfer), at the Roosevelt Road Naval Station in Puerto Rico during the Puerto Rico Dust Experiment (PRIDE). The instruments include several solar and infrared broadband radiometers, a sunphotometer, a shadow-band radiometer, a micro-pulse lidar, a total-sky imager, a microwave radiometer, and two solar spectrometers. These radiometers were set up on a mobile platform and a solar tracker. During 27 June - 23 July, about 25 days of data were acquired under partially cloudy sky conditions. The diurnal air temperature was fluctuating around 28.6 C to within a few degrees. Daytime average of solar irradiance reaching at the surface was ranged from about 400 W/sq m on a rainy day to about 640 W/sq m on a cloud-free day. The infrared irradiance at the surface during the measurement period was averaged about 408 W/sq m. The heights of boundary layer, dusts and clouds were captured by lidar images. Based on sunphotometer and shadow-band radiometer retrievals, the aerosol optical thickness varied from below 0.1 to over 0.6. Combining with radiative transfer modeling and other in-situ and remote sensing measurements, our ground-based measurements provide vital information on understanding the long-range transport of African dust into the Caribbean.

Tsay, Si-Chee↗
NASA NTRS1998

Atmospheric Depolarization Lidar Experimental Receiver: A Space Shuttle Hitchhiker Payload

Development work is underway at the Goddard Space Flight Center to construct a depolarization measuring atmospheric lidar receiver. The Atmospheric Lidar (AL) is tentatively scheduled to fly on the Space Shuttle in a late-1999 time frame. The AL will fly in conjunction with the Shuttle Laser Altimeter (SLA) and the Infrared Spectral Imaging Radiometer (ISIR) to provide a comprehensive package of atmospheric aerosol and cloud information. The AL operates in conjunction with the SLA laser transmitter and measures profiles of atmospheric backscatter at 532 nm. The receiver system discriminates between the parallel and perpendicular polarizations of the backscattered signal, thus providing depolarization ratios for scattering from clouds. The lidar receiver also provides cloud height and thickness measurements to complement the brightness temperature measurements generated by the ISIR thermal imager. The function of the AL is twofold. The primary function is to provide range-resolved measurements of atmospheric aerosol backscatter and depolarization ratio at 532 nm with 75 m vertical resolution. The scientific purpose of these measurements is to determine composition of clouds based on the depolarization ratio (i.e cloud content is water or ice), to determine cloud height and thickness, and to gain further understanding of the global distribution of aerosols. This information, when coupled with the cloud brightness measured by the ISIR thermal imager will provide a significant amount of information on cloud composition and radiative effects, particularly for cirrus and sub-visual cirrus clouds. A secondary function of the AL is to serve as an in-space test bed for lidar technology advancements, including a fully fiber-coupled receiver and photon counting from space. In addition, the data obtained by the AL will be used to develop software for the Geoscience Laser Altimeter System (GLAS) flight mission.

McGill, Matthew J.↗
NASA NTRS1993

Importance of aggregation and small ice crystals in cirrus clouds, based on observations and an ice particle growth model

The 1 November 1986 FIRE I case study was used to test an ice particle growth model which predicts bimodal size spectra in cirrus clouds. The model was developed from an analytically based model which predicts the height evolution of monomodal ice particle size spectra from the measured ice water content (IWC). Size spectra from the monomodal model are represented by a gamma distribution, N(D) = N(sub o)D(exp nu)exp(-lambda D), where D = ice particle maximum dimension. The slope parameter, lambda, and the parameter N(sub o) are predicted from the IWC through the growth processes of vapor diffusion and aggregation. The model formulation is analytical, computationally efficient, and well suited for incorporation into larger models. The monomodal model has been validated against two other cirrus cloud case studies. From the monomodal size spectra, the size distributions which determine concentrations of ice particles less than about 150 mu m are predicted.

Mitchell, David L.↗
NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗
NASA NTRS1994

Vertical distribution of clouds over Hampton, Virginia observed by lidar under the ECLIPS and FIRE ETO programs

Intensive cloud lidar observations have been made by NASA Langley Research Center during the two observation phases of the ECLIPS project. Less intensive but longer term observations have been conducted as part of the FIRE extended time observation (ETO) program since 1987. We present a preliminary analysis of the vertical distribution of clouds based on these observations. A mean cirrus thickness of just under 1 km has been observed with a mean altitude of about 80 percent of the tropopause height. Based on the lidar data, cirrus coverage was estimated to be just under 20 percent, representing roughly 50 percent of all clouds studied. Cirrus was observed to have less seasonal variation than lower clouds. Mid-level clouds are found to occur primarily in association with frontal activity.

Vaughan, M. A.↗
NASA NTRS1983

Atmospheric pressure and temperature profiling using near IR differential absorption lidar

The present investigation is concerned with differential absorption lidar techniques for remotely measuring the atmospheric temperature and pressure profile, surface pressure, and cloud top pressure-height. The procedure used in determining the pressure is based on the conduction of high-resolution measurements of absorption in the wings of lines in the oxygen A band. Absorption with respect to these areas is highly pressure sensitive in connection with the mechanism of collisional line broadening. The method of temperature measurement utilizes a determination of the absorption at the center of a selected line in the oxygen A band which originates from a quantum state with high ground state energy.

Korb, C. L.↗