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At least 451 records · Page 25
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NASA NTRS2024

Retrievals of Aerosol Optical Depth Over the Western North Atlantic Ocean During ACTIVATE

Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the National Aeronautics and Space Administration (NASA) Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a long-standing issue in atmospheric field studies is that there is a lack of reference datasets for properly validating field measurements and estimating their uncertainties. Here we address this issue by using the triple collocation method, in which a third collocated satellite dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) is introduced for comparison. HSRL-2 is found to provide a more accurate retrieval than RSP over the study region. The error standard deviation of HSRL-2 with respect to the ground truth is 0.027. Moreover, this approach enables us to develop a simple, yet efficient, quality control criterion for RSP data. The physical reasons for the differences in two retrievals are determined to be cloud contamination, aerosols near the surface, multiple aerosol layers, absorbing aerosols, non-spherical aerosols, and simplified retrieval assumptions. These results demonstrate the pathway for optimal aerosol retrievals by combining information from both lidars and polarimeters for future airborne and satellite missions.

Aerosol optical depth↗
NASA NTRS2006

Merging IceSAT GLAS and Terra MODIS Data in Order to Derive Forest Type Specific Tree Heights in the Central Siberian Boreal Forest

Mapping of boreal forest's type, biomass, and other structural parameters are critical for understanding of the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. We believe the nature of the forest structure information available from MISR and GLAS can be used to help identify forest type, age class, and estimate above ground biomass levels beyond that now possible with MODIS alone. The ground measurements will be used to develop relationships between remote sensing observables and forest characteristics and provide new information for understanding forest changes with respect to environmental change. Lidar is a laser altimeter that determines the distance from the instrument to the physical surface by measuring the time elapsed between the pulse emission and the reflected return. Other studies have shown that the returned signal may identify multiple returns originating from trees, building and other objects and permits the calculation of their height. Studies using field data have shown that lidar data can provide estimates of structural parameters such as biomass, stand volume and leaf area index and allows remarkable differentiation between primary and secondary forest. NASA's IceSAT Geoscience Laser Altimeter System (GLAS) was launched in January 2003 and collected data during February and September of that year. This study used data acquired over our study sites in central Siberia to examine the GLAS signal as a source of forest height and other structural characteristics. The purpose of our Siberia project is to improve forest cover maps and produce above-ground biomass maps of the boreal forest in Northern Eurasia from MODIS by incorporating structural information inherent in the Terra MISR and ICESAT Geoscience Laser Altimeter System (GLAS) instruments. A number of forest cover classifications exist for the boreal forest. We believe the limiting factor in these products is the lack of structural information, particularly in the vertical dimension. The emphasis of this project is to improve upon satellite maps of boreal forest structure parameters (i.e. height and biomass) using temporal, multi-angle, and vertical profile information of GLAS data. The existing and near future lidar data is useful for demonstrating these techniques and pursuing current estimates. Future lidar missions may be several years in the future, so we will work other new data sets that may aide in biomass estimates such as ALOS PALSAR We will continue this work to produce an accurate map of current above ground forest phytomass/carbon storage possible for the study area. We plan to develop, test, and integrate remote sensing methods for extracting forest canopy structure measures. We are compiling our field measurements and will compare them with the remote sensing methods where possible. We also be able to produce a realistic error bound on the remotely sensed carbon estimates.

Ranson, K. Jon↗
NASA NTRS2014

Regional Characteristics of the Relationship Between Columnar AOD and Surface PM2.5: Application of Lidar Aerosol Extinction Profiles over Baltimore-Washington Corridor During DISCOVER-AQ

The first field campaign of DISCOVER-AQ (Deriving Information on Surface conditions from COlumn and VERtically resolved observations relevant to Air Quality) took place in July 2011 over Baltimore-Washington Corridor (BWC). A suite of airborne remote sensing and in-situ sensors was deployed along with ground networks for mapping vertical and horizontal distribution of aerosols. Previous researches were based on a single lidar station because of the lack of regional coverage. This study uses the unique airborne HSRL (High Spectral Resolution Lidar) data to baseline PM2.5 (particulate matter of aerodynamic diameter less than 2.5 μm) estimates and applies to regional air quality with satellite AOD (Aerosol Optical Depth) retrievals over BWC (∼6500 sq. km). The linear approximation takes into account aerosols aloft above AML (Aerosol Mixing Layer) by normalizing AOD with haze layer height (i.e., AOD/HLH). The estimated PM2.5 mass concentrations by HSRL AOD/HLH are shown within 2 RMSE (Root Mean Square Error ∼9.6 μg/cu. m) with correlation ∼0.88 with the observed over BWC. Similar statistics are shown when applying HLH data from a single location over the distance of 100 km. In other words, a single lidar is feasible to cover the range of 100 km with expected uncertainties. The employment of MPLNET-AERONET (MicroPulse Lidar NETwork - AErosol RObotic NETwork) measurements at NASA GSFC produces similar statistics of PM2.5 estimates as those derived by HSRL. The synergy of active and passive remote sensing aerosol measurements provides the foundation for satellite application of air quality on a daily basis. For the optimal range of 10 km, the MODIS-estimated PM2.5 values are found satisfactory at 27 (out of 36) sunphotometer locations with mean RMSE of 1.6-3.3 μg/cu. m relative to PM2.5 estimated by sunphotometers. The remaining 6 of 8 marginal sites are found in the coastal zone, for which associated large RMSE values ∼4.5-7.8 μg/cu. m are most likely due to overestimated AOD because of water-contaminated pixels.

DISCOVER-AQ↗
NASA NTRS2017

Lidar Observations Revealing Transport of O3 in the Presence of a Nocturnal Low-Level Jet: Regional Implications for "Next-Day" Pollution

Remotely sensed profiles of ozone (O3) and wind are presented continuously for the first time during anocturnal low-level jet (NLLJ) event occurring after a severe O3 episode in the Baltimore-Washington D.C.(BW) urban corridor throughout 11-12 June 2015. High-resolution O3 lidar observations indicate a well mixedand polluted daytime O3 reservoir, which decayed into a contaminated nocturnal residual layer(RL) with concentrations between 70 and 100 ppbv near 1 km above the surface. Observations indicatethe onset of the NLLJ was responsible for transporting polluted O3 away from the region, while simultaneouslyaffecting the height and location of the nocturnal residual layer. High-resolution modelinganalyses and next-day (12 June) lidar, surface, and balloon-borne observations indicate the trajectory ofthe NLLJ and polluted residual layer corresponds with ''next-day'' high O3 at sites throughout thesouthern New England region (New York, Connecticut, Massachusetts). The novel O3 lidar observationsare evidence of both nocturnal advection (via high NLLJ wind fields) and entrainment of the pollutedresidual layer in the presence of the ''next-day'' convectively growing boundary layer. In the greatercontext, the novel observational suite described in this work has shown that the chemical budget in areasdownwind of major urban centers can be altered significantly overnight during transport events such asthe NLLJ.

ozone↗
NASA NTRS2018

Fusion of Multiple Low-Resolution NASA Airborne Snow Observatory (ASO) Lidar Data for Forest Vegetation Structure Characterization

Airborne lidar provides timely updated maps for monitoring forest change at high resolution but it has been little used for that purpose due to the scarcity of long-term time-series over a common area. The NASA Jet Propulsion Laboratory Airborne Snow Observatory (ASO) is a landscape-level monitoring system that provides ongoing multi-year remote sensing measurements over mountainous ecosystems to primary quantify snow volume and dynamics. It collects low-resolution lidar data (~1.5 pt/m2) with a nominal weekly frequency up to 12 times a year with measurements that span 2013-2017 over 12 mountain watersheds across the western US that currently face ecological threads. In this work, we present a method to automatically register ASO weekly low-resolution lidar point clouds in order to calculate spatially consistent datasets (~12 pt/m2) adapted to fine scale forestry studies. We test the method using 12 lidar datasets acquired over the Tuolumne River Basin (Sierra Nevada, California) in the spring and summer of 2014. On average, the ASO lidar system provides accurate measurements in terms of geolocation (0.38m and 0.12m for the horizontal and vertical dimension, respectively) but some datasets are biased up to 1.38m and 0.53m, respectively. Our registration method successfully corrected for systematic bias improving the 3D geometry of forest point clouds.

Painter, Thomas H.↗
NASA NTRS2000

Comparison of Aerosol Optical Properties and Water Vapor Among Ground and Airborne Lidars and Sun Photometers During TARFOX

We compare aerosol optical thickness (AOT) and precipitable water vapor (PWV) measurements derived from ground and airborne lidars and Sun photometers during TARFOX (Tropospheric Aerosol Radiative Forcing Observational Experiment). Such comparisons are important to verify the consistency between various remote sensing measurements before employing them in any assessment of the impact of aerosols on the global radiation balance. Total scattering ratio and extinction profiles measured by the ground-based NASA/GSFC Scanning Raman Lidar (SRL) system, which operated from Wallops Island, Virginia (37.86 deg N, 75.51 deg W), are compared with those measured by the Lidar Atmospheric Sensing Experiment (LASE) airborne lidar system aboard the NASA ER-2 aircraft. Bias and rms differences indicate that these measurements generally agreed within about 10%. Aerosol extinction profiles and estimates of AOT are derived from both lidar measurements using a value for the aerosol extinction/backscattering ratio S(sub a)=60 sr for the aerosol extinction/backscattering ratio, which was determined from the Raman lidar measurements.

Ferrare, R.↗
NASA NTRS2003

Remote Sensing of Vertical Distributions of Smoke Aerosol Off the Coast of Africa

In 2004 NASA plans to launch the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations- CALIPSO mission, with a two-wavelength lidar aboard. CALIPSO will fly in formation with the Moderate Resolution Imaging Spectro-Radiometer (MODIS) on the Aqua satellite. Here we present inversions of combined aircraft lidar and MODIS data to study the properties of smoke off the southwest coast of Southern Africa. The inversion derives profiles of the aerosol extinction due to fine and coarse particles. Comparisons with three sets of airborne in situ measurements show excellent agreement of the aerosol extinction profiles; however the inversion derives smaller spectral dependence of the extinction than the in situ measurements. The inversion is sensitive to the aerosol backscattering-to-extinction ratio (BER). Due to nonsphericity of the coarse aerosols, the range of BERs of the smoke aerosol is 0.014 to 0.021 sr(sup -l) for the fine and coarse particles at 0.53 and 1.06 pm wavelengths, which do not differ much from the value for dust (0.016 sr(sup -1)) at these wavelengths.

Kaufman, Y. J.↗
NASA NTRS2001

Semiconductor Reference Oscillator Development for Coherent Detection Optical Remote Sensing Applications

The NASA Earth Science Enterprise Advanced Technology Initiatives Program is supporting a program for the development of semiconductor laser reference oscillators for application to coherent optical remote sensing from Earth orbit. Local oscillators provide the frequency reference required for active spaceborne optical remote sensing concepts that involve heterodyne (coherent) detection. Two recent examples of such schemes are Doppler wind lidar and tropospheric carbon dioxide measurement by laser absorption spectrometry, both of which are being proposed at a wavelength of 2.05 microns. Frequency-agile local oscillator technology is important to such applications because of the need to compensate for large platform-induced Doppler components that would otherwise interfere with data interpretation. Development of frequency-agile local oscillator approaches has heretofore utilized the same laser material as the transmitter laser (Tm,Ho:YLF in the case of the 2.05-micron wavelength mentioned above). However, a semiconductor laser-based frequency-agile local oscillator offers considerable scope for reduced mechanical complexity and improved frequency agility over equivalent crystal laser devices, while their potentially faster tuning capability suggest the potential for greater scanning versatility. The program we report on here is specifically tasked with the development of prototype novel architecture semiconductor lasers with the power, tunability, and spectral characteristics required for coherent Doppler lidar. The baseline approach for this work is the distributed feedback (DFB) laser, in which gratings are etched into the semiconductor waveguide structures along the entire length of the laser cavity. However, typical DFB lasers at the wavelength of interest have linewidths that exhibit unacceptable growth when driven at the high currents and powers that are required for the Doppler lidar application. Suppression of this behavior by means of corrugation pitch-modulation (using a detuned central section to prevent intensity peaking in the center of the cavity) is currently under investigation to achieve the required performance goals.

distributed feedback (DFB) laser↗
DOE OSTI2020

Improving Land Cover Classification Using Extended Multi-Attribute Profiles (EMAP) Enhanced Color, Near Infrared, and LiDAR Data

Hyperspectral (HS) data have found a wide range of applications in recent years. Researchers observed that more spectral information helps land cover classification performance in many cases. However, in some practical applications, HS data may not be available, due to cost, data storage, or bandwidth issues. Instead, users may only have RGB and near infrared (NIR) bands available for land cover classification. Sometimes, light detection and ranging (LiDAR) data may also be available to assist land cover classification. A natural research problem is to investigate how well land cover classification can be achieved under the aforementioned data constraints. In this paper, we investigate the performance of land cover classification while only using four bands (RGB+NIR) or five bands (RGB+NIR+LiDAR). A number of algorithms have been applied to a well-known dataset (2013 IEEE Geoscience and Remote Sensing Society Data Fusion Contest). One key observation is that some algorithms can achieve better land cover classification performance by using only four bands as compared to that of using all 144 bands in the original hyperspectral data with the help of synthetic bands generated by Extended Multi-attribute Profiles (EMAP). Moreover, LiDAR data do improve the land cover classification performance even further.

58 GEOSCIENCES↗
DOE OSTI2025

LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory’s (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller Road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDAR System was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, and lidar data and imagery can be found in NGA281 (https://doi.org/10.5440/1671794).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Forest Structure Characterization Using Jpl's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

This paper concerns forest remote sensing using JPL's multi-baseline polarimetric interferometric UAVSAR data. It presents exemplary results and analyzes the possibilities and limitations of using SAR Tomography and Polarimetric SAR Interferometry (PolInSAR) techniques for the estimation of forest structure. Performance and error indicators for the applicability and reliability of the used multi-baseline (MB) multi-temporal (MT) PolInSAR random volume over ground (RVoG) model are discussed. Experimental results are presented based on JPL's L-band repeat-pass polarimetric interferometric UAVSAR data over temperate and tropical forest biomes in the Harvard Forest, Massachusetts, and in the La Amistad Park, Panama and Costa Rica. The results are partially compared with ground field measurements and with air-borne LVIS lidar data.

remote sensing↗
NASA NTRS1991

Lidar windshear detection for commercial aircraft

As part of the NASA/FAA National Integrated Windshear Program, a measurable windshear hazard index that can be remotely sensed from an aircraft is presented. This will provide a pilot information about the wind conditions he will experience at some later time if he continues along the present flight path. The technology analysis and end-to-end performance simulation, which measured S/N and resulting wind velocity errors for competing lidar systems, demonstrated that a Ho:YAG lidar at a wavelength of 2.1 microns and a CO2 lidar at 10.6 microns can give the pilot data about the line-of-sight component of a windshear threat in an area extending from his present position to two to four km in front of the aircraft.

Targ, Russell↗
DOE OSTI2026

CHESS 2025: Field-collected vegetation attributes and site photos

This dataset represents field observations of vegetation samples collected as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Samples were collected in the field using tablet computers and digital forms, with target data differing by sample type (individual trees, individual shrubs, or 1-meter square plots of meadow and subshrub vegetation). Field samples were collected within 72 hours of airborne data collection using the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. Remote sensing data for the project is available on ESS-DIVE (DOI and citation to be added upon publication). Field data collected included canopy height and per-species horizontal proportional cover for meadow plots, species identity and height information for shrubs, as well as species identity, height, diameter at breast height, and health assessment information for trees. Photos of the focal site and surrounding landscape were taken for all sampling sites and are included in this archive. Green leaves or needles were collected for plant trait and foliar chemistry analysis. This data is archived separately (DOI and citation to be added upon publication). High-precision geospatial data for each sample (crown perimeter polygons for trees and shrubs, plot boundaries for meadow plots) is available here (Henderson et al., 2026). Field and remote sensing protocols largely followed those of a previous field and airborne imaging campaign performed in 2018 (described in Chadwick et al. 2020). Field data from the 2018 campaign can be found here (Chadwick et al., 2020 doi:10.15485/1618130). Because different field measurements were taken for meadow, shrub, and tree sites, data from these three sample types are archived as separate tables (chess_meadow_site_cleaned.csv, chess_shrub_site_cleaned.csv, chess_tree_site_cleaned.csv). Meadow proportional cover data is stored in a separate table (chess_meadow_cover_cleaned.csv). Taxonomy was treated identically between sample types, and the dataset shares a common set of voucher specimens (chess_voucher_IDs_cleaned.csv), as well as a single species list (chess_species_list_cleaned.csv). All taxonomic determinations were performed to the species level, and adhere to the Global Biodiversity Information Facility (GBIF) backbone taxonomy as of January 10th, 2026 (GBIF Secretariat 2023). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRS1988

Ultraviolet Lidar Would Measure Wind Velocity

Incoherent Doppler-shifted scattering from aerosols reveals important weather data. Remote-sensing system in early stage of development makes global measurements of wind velocities along probing beam of ultraviolet light. In aviation system promotes safety through detection of wind shears and clear-air turbulence. System includes range-gated ultraviolet-excimer laser operating at 308 or 353 nm.

Mcdermid, Iain Stuart↗
NASA NTRS2016

Development of an Airborne Triple-Pulse 2-Micron Integrated Path Differential Absorption Lidar (IPDA) for Simultaneous Airborne Column Measurements of Carbon Dioxide and Water Vapor in the Atmosphere

This presentation will provide status and details of an airborne 2-micron triple-pulse integrated path differential absorption (IPDA) lidar being developed at NASA Langley Research Center with support from NASA ESTO Instrument Incubator Program. The development of this active optical remote sensing IPDA instrument is targeted for measuring both atmospheric carbon dioxide and water vapor in the atmosphere from an airborne platform. This presentation will focus on the advancement of the 2-micron triple-pulse IPDA lidar development. Updates on the state-of-the-art triple-pulse laser transmitter will be presented including the status of seed laser locking, wavelength control, receiver and detector upgrades, laser packaging and lidar integration. Future plan for IPDA lidar system for ground integration, testing and flight validation will also be presented.

Singh, Upendra N.↗
DOE OSTI2024

LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Kougarok 64 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 64 along the Kougarok road (Nome-Taylor Highway) between Nome, Alaska and Taylor, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, raw LiDAR data, and RGB imagery can be found in NGA298.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Comparison of Aerosol Optical Properties and Water Vapor Among Ground and Airborne Lidars and Sun Photometers During TARFOX

We compare aerosol optical thickness (AOT) and precipitable water vapor (PWV) measurements derived from ground and airborne lidars and sun photometers during the Tropospheric Aerosol Radiative Forcing Observational Experiment. Such comparisons are important to verify the consistency between various remote sensing measurements before employing them in any assessment of the impact of aerosols on the global radiation balance. Total scattering ratio and extinction profiles measured by the ground-based NASA Goddard Space Flight Center scanning Raman lidar system, which operated from Wallops Island, Virginia (37.86 deg N, 75.51 deg W); are compared with those measured by the Lidar Atmospheric Sensing Experiment (LASE) airborne lidar system aboard the NASA ER-2 aircraft. Bias and root-mean-square differences indicate that these measurements generally agreed within about 10%. Aerosol extinction profiles and estimates of AOT are derived from both lidar measurements using a value for the aerosol extinction/backscattering ratio S(sub a) = 60 sr for the aerosol extinction/backscattering ratio, which was determined from the Raman lidar measurements. The lidar measurements of AOT are found to be generally within 25% of the AOT measured by the NASA Ames Airborne Tracking Sun Photometer (AATS-6). However, during certain periods the lidar and Sun photometer measurements of AOT differed significantly, possibly because of variations in the aerosol physical characteristics (e.g., size, composition) which affect S(sub a). Estimates of PWV, derived from water vapor mixing ratio profiles measured by LASE, are within 5-10% of PWV derived from the airborne Sun photometer. Aerosol extinction profiles measured by both lidars show that aerosols were generally concentrated in the lowest 2-3 km.

Ferrare, R.↗
NASA NTRS1992

Mechanical and Thermal Issues in the Development of a Spaceborne Lidar System

The Lidar In-space Technology Experiment (LITE) is being developed by NASA's Langley Research Center (LaRC) to conduct spaceborne remote sensing of the Earth's atmosphere from the Space Shuttle. LITE is currently manifested as the primary payload on STS-63 to be launched in February 1994. Addressed here are some of the key mechanical and thermal issues in the design and development of this spaceborne lidar system.

Delorme, Joseph F.↗