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NASA NTRS1993

Asteroid approach covariance analysis for the Clementine mission

The Clementine mission is designed to test Strategic Defense Initiative Organization (SDIO) technology, the Brilliant Pebbles and Brilliant Eyes sensors, by mapping the moon surface and flying by the asteroid Geographos. The capability of two of the instruments available on board the spacecraft, the lidar (laser radar) and the UV/Visible camera is used in the covariance analysis to obtain the spacecraft delivery uncertainties at the asteroid. These uncertainties are due primarily to asteroid ephemeris uncertainties. On board optical navigation reduces the uncertainty in the knowledge of the spacecraft position in the direction perpendicular to the incoming asymptote to a one-sigma value of under 1 km, at the closest approach distance of 100 km. The uncertainty in the knowledge of the encounter time is about 0.1 seconds for a flyby velocity of 10.85 km/s. The magnitude of these uncertainties is due largely to Center Finding Errors (CFE). These systematic errors represent the accuracy expected in locating the center of the asteroid in the optical navigation images, in the absence of a topographic model for the asteroid. The direction of the incoming asymptote cannot be estimated accurately until minutes before the asteroid flyby, and correcting for it would require autonomous navigation. Orbit determination errors dominate over maneuver execution errors, and the final delivery accuracy attained is basically the orbit determination uncertainty before the final maneuver.

Ionasescu, Rodica↗

NASA NTRS2010

Mission Simulation of Space Lidar Measurements for Seasonal and Regional CO2 Variations

Results of mission simulation studies are presented for a laser-based atmospheric [82 sounder. The simulations are based on real-time carbon cycle process modeling and data analysis. The mission concept corresponds to the Active Sensing of [82 over Nights, Days, and Seasons (ASCENDS) recommended by the US National Academy of Sciences Decadal Survey of Earth Science and Applications from Space. One prerequisite for meaningful quantitative sensor evaluation is realistic CO2 process modeling across a wide range of scales, i.e., does the model have representative spatial and temporal gradients? Examples of model comparison with data will be shown. Another requirement is a relatively complete description of the atmospheric and surface state, which we have obtained from meteorological data assimilation and satellite measurements from MODIS and [ALIPS0. We use radiative transfer model calculations, an instrument model with representative errors ' and a simple retrieval approach to complete the cycle from "nature" run to "pseudo-data" CO2, Several mission and instrument configuration options are examined/ and the sensitivity to key design variables is shown. We use the simulation framework to demonstrate that within reasonable technological assumptions for the system performance, relatively high measurement precision can be obtained, but errors depend strongly on environmental conditions as well as instrument specifications. Examples are also shown of how the resulting pseudo - measurements might be used to address key carbon cycle science questions.

Kawa, Stephan↗

NASA NTRS2022

GEDI Launches a New Era of Biomass Inference from Space

Accurate estimation of aboveground forest biomass stocks is required to assess the impacts of land use changes such as deforestation and subsequent regrowth on concentrations of atmospheric CO 2 . The Global Ecosystem Dynamics Investigation (GEDI) is a lidar mission launched by NASA to the International Space Station in 2018. GEDI was specifically designed to retrieve vegetation structure within a novel, theoretical sampling design that explicitly quantifies biomass and its uncertainty across a variety of spatial scales. In this paper we provide the estimates of pan-tropical and temperate biomass derived from two years of GEDI observations. We present estimates of mean biomass densities at 1 km resolution, as well as estimates aggregated to the national level for every country GEDI observes, and at the sub-national level for the United States. For all estimates we provide the standard error of the mean biomass. These data serve as a baseline for current biomass stocks and their future changes, and the mission’s integrated use of formal statistical inference points the way towards the possibility of a new generation of powerful monitoring tools from space.

Ralph Dubayah↗

NASA NTRS2000

Measurements and Modeling of Aerosol Absorption and Single Scattering Albedo at Ambient Relative Hum

Uncertainties in the aerosol single scattering albedo have been identified to be an important source of errors in current large-scale model estimates of the direct aerosol radiative forcing of climate. A number of investigators have obtained estimates of the single scattering albedo from a variety of remote sensing and in situ measurements during aerosol field experiments. During the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX, 1996) for example, estimates of the aerosol single scattering albedo were obtained (1) as a best-fit parameter in comparing radiative flux changes measured by airborne pyranometer to those computed from independently measured aerosol properties; (2) from estimates of the aerosol complex index of refraction derived using a combination of airborne sunphotometer, lidar backscatter and in situ size distribution measurements; and (3) from airborne measurements of aerosol scattering and absorption using nephelometers and absorption photometers. In this paper, we briefly compare the results of the latter two methods for two TARFOX case studies, since those techniques provide height-resolved information about the aerosol single scattering albedo. Estimates of the aerosol single scattering albedo from nephelometer and absorption photometer measurements require knowledge of the scattering and absorption humidification (i.e., the increase in these properties in response to an increase in ambient relative humidity), since both measurements are usually carried out at a relative humidity different from the ambient atmosphere. In principle, the scattering humidification factor can be measured, but there is currently no technique widely available to measure the absorption of an aerosol sample as a function of relative humidity. Frequently, for lack of better knowledge, the absorption humidification is assumed to be unity (meaning that there is no change in aerosol absorption due to an increase in ambient relative humidity). This assumption then enters the estimate of the single scattering albedo at ambient relative humidity. To investigate the validity of this assumption we have carried out modeling studies of the absorption humidification factor, assuming that the aerosols contain an insoluble soot core and a coating which determines its hygroscopic growth behavior. The aerosol optical properties are then computed on the basis of the shell/core particle morphology using a Mie-code for concentric shells. From basic physical principles, it is conceivable that aerosol absorption increases when an atmospheric aerosol particle collects a non-absorbing shell, since the soot core is then exposed to an increased (focused) electric field strength. Indeed, our preliminary modeling studies show that the absorption of an atmospheric aerosol particle composed of a soot core and an aqueous sulfuric acid shell may increase by a factor of 50% due to a change in ambient relative humidity from 30 to 95%. We will show how this increased absorption is a function of the initial particle size and soot mass fraction.

Redemann, J.↗

NASA NTRS2007

Performance of the Lidar Design and Data Algorithms for the GLAS Global Cloud and Aerosol Measurements

The Geoscience Laser Altimeter System (GLAS) launched in early 2003 is the first polar orbiting satellite lidar. The instrument design includes high performance observations of the distribution and optical scattering cross sections of atmospheric clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. For the atmospheric cloud and aerosol measurements, the 532 nm channel was designed for ultra high efficiency with solid state photon counting detectors and etalon filtering. Data processing algorithms were developed to calibrate and normalize the signals and produce global scale data products of the height distribution of cloud and aerosol layers and their optical depths and particulate scattering cross sections up to the limit of optical attenuation. The paper will concentrate on the effectiveness and limitations of the lidar channel design and data product algorithms. Both atmospheric receiver channels meet and exceed their design goals. Geiger Mode Avalanche Photodiode modules are used for the 532 nm signal. The operational experience is that some signal artifacts and non-linearity require correction in data processing. As with all photon counting detectors, a pulse-pile-up calibration is an important aspect of the measurement. Additional signal corrections were found to be necessary relating to correction of a saturation signal-run-on effect and also for daytime data, a small range dependent variation in the responsivity. It was possible to correct for these signal errors in data processing and achieve the requirement to accurately profile aerosol and cloud cross section down to 10-7 llm-sr. The analysis procedure employs a precise calibration against molecular scattering in the mid-stratosphere. The 1064 nm channel detection employs a high-speed analog APD for surface and atmospheric measurements where the detection sensitivity is limited by detector noise and is over an order of magnitude less than at 532 nm. A unique feature of the GLAS is a full acquisition of the surface return pulse, which has important application to the atmospheric transmission retrieval.

Spinhirne, James D.↗

NASA NTRS1997

MIR Measurements of Atmospheric Water Vapor Profiles

Three subjects related to atmospheric water vapor profiling using the 183.3 GHz absorption line are discussed in this paper. First, data acquired by an airborne millimeter-wave imaging radiometer (MIR) over ocean surface in the western Pacific are used to estimate three-dimensional (3-D) distribution of atmospheric water vapor. The instrument's radiometric measurements with mixed vertical and horizontal polarizations require modifications to the retrieval algorithm used in the past. It is demonstrated that, after the modifications, the new algorithm can provide adequate retrieval of water vapor profiles, even though the measured data are of mixed polarizations. Next, the retrieved profiles, in terms of water vapor mixing ratio rho (g/kg), are compared with those measured in near concurrence by dropsondes from a research aircraft in the western Pacific and by a ground-based Raman lidar at Wallops Island, Virginia. The ratio of the standard deviation to the mean rho is found to be 0.12 at 0.25 km altitude and gradually degraded to 0.67 at the highest altitude of the retrieval of 10.25 km. Finally, the effect of the "initial guess" relative humidity profile on the final retrieved product is analyzed with respect to the condition for the convergent retrieval. It is found that the effect is minimal if the initial profile is not unrealistically different from the true one. If the initial profile is very different from the true one, the final retrieved product could be subject to a substantial error. Tightening of the convergent condition in the retrieval helped reduce magnitude of the error, but not remove it totally. It is concluded that an initial profile based on climatology is likely to provide most reliable retrieval results.

Wang, J. R.↗

NASA NTRS2015

Remote Sensing of Cloud Top Heights Using the Research Scanning Polarimeter

Clouds cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered clouds occur about half of the time and are predominantly two-layered. Changes in cloud top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at cloud altitude using a correlation function designed to identify the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the Cloud Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately identify cloud heights. Interestingly, the analysis reveals an ability for the approach to identify multiple cloud layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of identifying single and multiple cloud layers heights are explored. Special focus is given to sources of error in the method including optically thin clouds, physically thick clouds, multi-layered clouds as well as cloud phase. When determining multi-layered CTHs, limits on the upper clouds opacity are assessed.

Cloud height indicators↗

NASA NTRS2019

Deriving High-Resolution Reservoir Bathymetry from ICESat-2 Prototype Photon-Counting Lidar and Landsat Imagery

Knowledge of reservoir bathymetry is essential for many studies on terrestrial hydrological and biogeochemical processes. However, there are currently no cost-effective approaches to derive reservoir bathymetry at the global scale. This study explores the potential of generating high-resolution global bathymetry using elevation data collected by the 532-nm Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESat-2). The novel algorithm was developed and tested using the ICESat-2 airborne prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), with Landsat-based water classifications (from 1982 to 2017). MABEL photon elevations were paired with Landsat water occurrence percentiles to establish the elevation-area (E-A) relationship, which in turn was applied to the percentile image to obtain partial bathymetry over the historic dynamic range of reservoir area. The bathymetry for the central area was projected to achieve the full bathymetry. The bathymetry image was then embedded onto the digital elevation model (DEM). Results were validated over Lake Mead against survey data. Results over four transects show coefficient of determination (R²) values from 0.82 to 0.99 and root-mean-square error (RMSE) values from 1.18 to 2.36 m. In addition, the E-A and elevation-storage (E-S) curves have RMSEs of 1.56 m and 0.08 km³, respectively. Over the entire dynamic reservoir area, the derived bathymetry agrees very well with independent survey data, except for within the highest and lowest percentile bands. With abundant overpassing tracks and high spatial resolution, the newly launched ICESat-2 should enable the derivation of bathymetry over an unprecedented number of reservoirs.

Yao Li↗

NASA NTRS2013

Simultaneous Laser Ranging and Communication from an Earth-Based Satellite Laser Ranging Station to the Lunar Reconnaissance Orbiter in Lunar Orbit

We report a free space laser communication experiment from the satellite laser ranging (SLR) station at NASA Goddard Space Flight Center (GSFC) to the Lunar Reconnaissance Orbiter (LRO) in lunar orbit through the on board one-way Laser Ranging (LR) receiver. Pseudo random data and sample image files were transmitted to LRO using a 4096-ary pulse position modulation (PPM) signal format. Reed-Solomon forward error correction codes were used to achieve error free data transmission at a moderate coding overhead rate. The signal fading due to the atmosphere effect was measured and the coding gain could be estimated.

fee-space optical communication↗

NASA NTRS1989

Estimations of ABL fluxes and other turbulence parameters from Doppler lidar data

Techniques for extraction boundary layer parameters from measurements of a short-pulse CO2 Doppler lidar are described. The measurements are those collected during the First International Satellites Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE). By continuously operating the lidar for about an hour, stable statistics of the radial velocities can be extracted. Assuming that the turbulence is horizontally homogeneous, the mean wind, its standard deviations, and the momentum fluxes were estimated. Spectral analysis of the radial velocities is also performed from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. Finally, using the statistical form of the Navier-Stokes equations, the surface heat flux is derived as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation. Combining many measurements would normally reduce the error provided that, it is unbiased and uncorrelated. The nature of some of the algorithms however, is such that, biased and correlated errors may be generated even though the raw measurements are not. Data processing procedures were developed that eliminate bias and minimize error correlation. Once bias and error correlations are accounted for, the large sample size is shown to reduce the errors substantially. The principal features of the derived turbulence statistics for two case studied are presented.

Gal-Chen, Tzvi↗

NASA NTRS2012

Height and Biomass of Mangroves in Africa from ICEsat/GLAS and SRTM

The accurate quantification of forest 3-D structure is of great importance for studies of the global carbon cycle and biodiversity. These studies are especially relevant in Africa, where deforestation rates are high and the lack of background data is great. Mangrove forests are ecologically significant and it is important to measure mangrove canopy heights and biomass. The objectives of this study are to estimate: 1. The total area, 2. Canopy height distributions and 3. Aboveground biomass of mangrove forests in Africa. To derive mangrove 3-D structure and biomass maps, we used a combination of mangrove maps derived from Landsat ETM+, LiDAR canopy height estimates from ICEsat/GLAS (Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) and elevation data from SRTM (Shuttle Radar Topography Mission) for the African continent. More specifically, we extracted mangrove forest areas on the SRTM DEM using Landsat based landcover maps. The LiDAR (Light Detection and Ranging) measurements from the large footprint GLAS sensor were used to derive local estimates of canopy height and calibrate the Interferometric Synthetic Aperture Radar (InSAR) data from SRTM. We then applied allometric equations relating canopy height to biomass in order to estimate above ground biomass (AGB) from the canopy height product. The total mangrove area of Africa was estimated to be 25 960 square kilometers with 83% accuracy. The largest mangrove areas and greatest total biomass was 29 found in Nigeria covering 8 573 km2 with 132 x10(exp 6) Mg AGB. Canopy height across Africa was estimated with an overall root mean square error of 3.55 m. This error also includes the impact of using sensors with different resolutions and geolocation error which make comparison between measurements sensitive to canopy heterogeneities. This study provides the first systematic estimates of mangrove area, height and biomass in Africa. Our results showed that the combination of ICEsat/GLAS and SRTM data is well suited for vegetation 3-D mapping on a continental scale.

Fatoyinbo, Temilola E.↗

DOE OSTI2023

Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection

Optimizing traffic control systems at traffic intersections can reduce the network-wide fuel consumption, as well as emissions of conventional fuel-powered vehicles. While traffic signals have been controlled based on predetermined schedules, various adaptive signal control systems have recently been developed using advanced sensors such as cameras, radars, and LiDARs. Among these sensors, cameras can provide a cost-effective way to determine the number, location, type, and speed of the vehicles for better-informed decision-making at traffic intersections. In this research, a new approach for accurately determining vehicle locations near traffic intersections using a single camera is presented. For that purpose, a well-known object detection algorithm called YOLO is used to determine vehicle locations in video images captured by a traffic camera. YOLO draws a bounding box around each detected vehicle, and the vehicle location in the image coordinates is converted to the world coordinates using camera calibration data. During this process, a significant error between the center of a vehicle’s bounding box and the real center of the vehicle in the world coordinates is generated due to the angled view of the vehicles by a camera installed on a traffic light pole. As a means of mitigating this vehicle localization error, two different types of regression models are trained and applied to the centers of the bounding boxes of the camera-detected vehicles. The accuracy of the proposed approach is validated using both static camera images and live-streamed traffic video. Based on the improved vehicle localization, it is expected that more accurate traffic signal control can be made to improve the overall network-wide energy efficiency and traffic flow at traffic intersections.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Demonstration of Algorithmic Quantum Speedup for an Abelian Hidden Subgroup Problem

Simon’s problem is to find a hidden period (a bitstring) encoded into an unknown 2-to-1 function. It is one of the earliest problems for which an exponential quantum speedup was proven for ideal, noiseless quantum computers, albeit in the oracle model. Here, using two different 127-qubit IBM Quantum superconducting processors, we demonstrate an algorithmic quantum speedup for a variant of Simon’s problem where the hidden period has a restricted Hamming weight 𝑤. For sufficiently small values of 𝑤 and for circuits involving up to 58 qubits, we demonstrate an exponential speedup, albeit of a lower quality than the speedup predicted for the noiseless algorithm. The speedup exponent and the range of 𝑤 values for which an exponential speedup exists are significantly enhanced when the computation is protected by dynamical decoupling. Further enhancement is achieved with measurement error mitigation. This case constitutes a demonstration of a bona fide quantum advantage for an Abelian hidden subgroup problem.

computation↗

NASA NTRS1992

A considerable effect of stratospheric aerosol on lidar-detected ozone profile and a three-wavelength inversion technique for both ozone and aerosol

As far as the Differential Absorption Lidar (DIAL) technique is concerned, it is important that the off-line wavelength is close to the on-line wavelength in order to avoid a messy computation of the atmospheric aerosol scattering. However, the two wavelengths of ozone-DIAL are usually considerably different. Usually, an excimer laser of 308nm (on-line) and Raman shifting of 353nm or the third harmonic of a Nd-YAG laser with 355nm (off-line) are selected for measurements of the stratospheric ozone, and there is a difference of 45nm or 47nm between them. Because of the difference there is a difference in the atmospheric scatterings of the two wavelengths. This can cause some error in the retrieved ozone profile if the aerosol scattering is neglected. This paper is devoted to a study of the effect of the stratospheric aerosol on the ozone solution, and a three-wavelength detection technique is proposed for obtaining the more exact ozone profile and the aerosol profile in the stratosphere.

Qiu, Jinhuan↗

NASA NTRS2010

Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation, this book chapter has 3 main objectives: a) To describe in detail the field methodologies used to derive accurate estimates of biomass in mangrove forests b) To explain how mangrove forest biomass can be measured using several remote sensing techniques and datasets c) To give a detailed explanation of the measurement challenges and errors that arise in each estimate of forest biomass

Fatoyinbo, Temilola E.↗

NASA NTRS2012

Tele-Operated Lunar Rover Navigation Using Lidar

Near real-time tele-operated driving on the lunar surface remains constrained by bandwidth and signal latency despite the Moon s relative proximity. As part of our work within NASA s Human-Robotic Systems Project (HRS), we have developed a stand-alone modular LIDAR based safeguarded tele-operation system of hardware, middleware, navigation software and user interface. The system has been installed and tested on two distinct NASA rovers-JSC s Centaur2 lunar rover prototype and ARC s KRex research rover- and tested over several kilometers of tele-operated driving at average sustained speeds of 0.15 - 0.25 m/s around rocks, slopes and simulated lunar craters using a deliberately constrained telemetry link. The navigation system builds onboard terrain and hazard maps, returning highest priority sections to the off-board operator as permitted by bandwidth availability. It also analyzes hazard maps onboard and can stop the vehicle prior to contacting hazards. It is robust to severe pose errors and uses a novel scan alignment algorithm to compensate for attitude and elevation errors.

Pedersen, Liam↗

NASA NTRS2002

Airborne Sunphotometer Measurements of Aerosol Optical Depth and Water Vapor in ACE-Asia and Their Comparisons to Correlative Measurements

In the Spring 2001 phase of the Asian Pacific Regional Aerosol Characterization Experiment (ACE-Asia), the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated on 15 of the 19 research flights of the NCAR C-130, while its 14-channel counterpart (AATS-14) flew successfully on all 19 research flights of the CIRPAS Twin Otter. ACE-Asia studied aerosol outflow from the Asian continent to the Pacific basin. It was designed to integrate suborbital and satellite measurements and models to reduce the uncertainty in calculations of the climate forcing due to aerosols. AATS-6 and AATS-14 measured solar beam transmission at six and 14 wavelengths (380-1021 and 354-1558 nm, respectively), yielding aerosol optical depth (AOD) spectra and columnar water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction spectra and water vapor concentration. In this paper, we plan to present examples of the following, preliminary findings that are based in part on our airborne sunphotometer measurements: (1) The wavelength dependence of sunphotometer-derived AOD and extinction indicates that supermicron dust was often a major component of the aerosol, frequently extending to high altitudes. The percentage of full-column AOD (525 nm) that Jay above 3 km was typically 34+/-13%. In contrast, the analogous percentage of columnar water vapor was only 10+/-4%; (2) Initial comparison studies between AOD data obtained by AATS-6 and AATS-14 during coordinated low-level flight legs show agreement well within the instruments' error bars; (3) Aerosol extinction has been derived from airborne in situ measurements of scattering (nephelometers) and absorption (particle soot/ absorption photometer, PSAP) or calculated from particle size distribution measurements (mobility analyzers and aerodynamic particle sizers). Comparison with corresponding extinction values derived from the Ames airborne sunphotometer measurements shows good agreement for the vertical distribution of aerosol layers. However, the level of agreement in absolute magnitude of the derived aerosol extinction/optical depth varied among the aerosol layers sampled; (4) Initial comparisons of sunphotometer and satellite-derived AOD using SeaWiFS, MISR and AVHRR show promising results. We also plan to include comparisons with MODIS and TOMS: (5) Initial comparisons of sunphotometer-derived AOD and aerosol extinction profiles with lidars in Tokyo and on a ship show reasonable agreement.

Schmid, B.↗

DOE OSTI2021

Afterpulse correction for micro-pulse lidar to improve middle and upper tropospheric aerosol measurements

Micro-pulse lidar (MPL) measurements have been widely used in atmospheric research over the past few decades. However, the MPL afterpulse noise has a large impact on the MPL aerosol measurement in the middle and upper troposphere, and an effective correction method is still lacking. Here, a new afterpulse correction approach is presented by using measurements with low-level optically thick clouds to act as the lids blocking atmospheric signals beyond the clouds completely. Examples are provided to illustrate the effectiveness of this correction method. Using one-year 2014 MPL measurements at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site, the impact of the correction on the aerosol measurements is quantified. The relative error (RE, %) of attenuated backscattering ratio (ABR) without the afterpulse correction is 30% and 190% at the height of 1.00 km and 9.00 km (AGL), and the RE is larger for weaker aerosol signals (ABR<2). The RE of linear depolarization ratio (LDR), which is significantly higher than that of ABR for a given aerosol layer, is highly non-linear above 3.00 km, with a value of 300%-900% for weak aerosols (ABR<2) above 3.00 km. Therefore, the afterpulse correction is critical for the middle and upper tropospheric aerosol observations. We demonstrated that our afterpulse correction can provide reasonable particle depolarization ratio (PDR) to properly identify dust aerosols. The newly developed method can be applied to long-term MPL measurements to support aerosol and mixed-phase/ice cloud interaction study at the NSA site.

54 ENVIRONMENTAL SCIENCES↗