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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Airborne remote sensing of tropospheric water vapor using a near infrared DIAL system

Summarized here are the results of airborne water vapor measurements in the lower middle and upper troposphere using the Differential Absorption Lidar (DIAL) technique in the near infrared. The measurements were performed in July 1990 in Southern Bavaria between Allersberg and Straubing from 20 to 23 UTC taking advantage of night time conditions. The tropospheric H2O profiles were range investigated both horizontally and vertically. With the DIAL system that was used, water vapor measurements in the upper troposphere have been carried out for the first time. To calibrate the H2O-retrievals, effective absorption cross sections of selected H2O lines in terms of altitude around 724 nm were calculated using line parameter data from the literature (B. E. Grossmann et al). The frequency of the on-line measurements was adjusted by the spectra of a Polyacenic Semiconductor (PAS) cell filled with H2O. We found that the calibration error ranged between 0.005 and 0.015 cm(exp -1). The systematic errors of the H2O as a function of altitude were estimated below 7 km and 12 percent accuracy in the upper troposphere. The vertical H2O profile agrees well with in situ measurements in the investigated range between the top of the planetary boundary layer (PBL) up to near the tropopause. Horizontal and vertical H2O profiles are calculated by means of averaging single lidar returns. Typical horizontal resolutions range from 4 km in the lower to 11 km in the upper troposphere with vertical resolutions varying from 0.3 km up to 1 km, respectively, in order to satisfy a 5 - 10 percent accuracy in the statistical error. The measurement sensibility of the water vapor mixing ration in the upper troposphere is 0.01 g/kg.

Ehret, G.↗
NASA NTRS1991

Theory of CW lidar aerosol backscatter measurements and development of a 2.1 microns solid-state pulsed laser radar for aerosol backscatter profiling

The performance and calibration of a focused, continuous wave, coherent detection CO2 lidar operated for the measurement of atmospheric backscatter coefficient, B(m), was examined. This instrument functions by transmitting infrared (10 micron) light into the atmosphere and collecting the light which is scattered in the rearward direction. Two distinct modes of operation were considered. In volume mode, the scattered light energy from many aerosols is detected simultaneously, whereas in the single particle mode (SPM), the scattered light energy from a single aerosol is detected. The analysis considered possible sources of error for each of these two cases, and also considered the conditions where each technique would have superior performance. The analysis showed that, within reasonable assumptions, the value of B(m) could be accurately measured by either the VM or the SPM method. The understanding of the theory developed during the analysis was also applied to a pulsed CO2 lidar. Preliminary results of field testing of a solid state 2 micron lidar using a CW oscillator is included.

Kavaya, Michael J.↗
NASA NTRS2007

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

A physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

Zhou, Daniel K.↗
NASA NTRS1986

SAGE 2 satellite data set validation

The results of a validation study of data obtained by the Stratospheric Aerosol and Gas Experiment 2 satellite experiment (SAGE 2) are given. Preliminary SAGE 2 data have been available for the period October, 1984 to May, 1985. In addition, the results of two correlative experimental measurement series have been studied in detail, as well as climatological data obtained by other techniques, including ground-based and airborne lidar. The study shows the SAGE 2 data to be of great potential value to studies of the microphyiscs of stratospheric aerosols, the chemistry of trace gases and stratospheric dynamics. A small number of unidentified errors in the current preliminary data set are described. These will be removed from the next version of the data set which is anticipated to be of archival quality.

Kent, G. S.↗
NASA NTRS2013

Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 μm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.

cirrus correction↗
NASA NTRS2015

Advanced Intensity-Modulation Continuous-Wave Lidar Techniques for ASCENDS O2 Column Measurements

Global atmospheric carbon dioxide (CO2) measurements for the NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) space mission are critical for improving our understanding of global CO2 sources and sinks. Advanced Intensity- Modulated Continuous-Wave (IM-CW) lidar techniques are investigated as a means of facilitating CO2 measurements from space to meet the ASCENDS measurement requirements. In recent numerical, laboratory and flight experiments we have successfully used the Binary Phase Shift Keying (BPSK) modulation technique to uniquely discriminate surface lidar returns from intermediate aerosol and cloud contamination. We demonstrate the utility of BPSK to eliminate sidelobes in the range profile as a means of making Integrated Path Differential Absorption (IPDA) column CO2 measurements in the presence of optically thin clouds, thereby eliminating the need to correct for sidelobe bias errors caused by the clouds. Furthermore, high accuracy and precision ranging to the surface as well as to the top of intermediate cloud layers, which is a requirement for the inversion of column CO2 number density measurements to column CO2 mixing ratios, has been demonstrated using new hyperfine interpolation techniques that takes advantage of the periodicity of the modulation waveforms. This approach works well for both BPSK and linear swept-frequency modulation techniques. The BPSK technique under investigation has excellent auto-correlation properties while possessing a finite bandwidth. A comparison of BPSK and linear swept-frequency is also discussed in this paper. These results are extended to include Richardson-Lucy deconvolution techniques to extend the resolution of the lidar beyond that implied by limit of the bandwidth of the modulation, where it is shown useful for making tree canopy measurements.

Campbell, Joel F.↗
NASA NTRSDate not supplied

Improving Boundary Layer Data Assimilation in the NASA GEOS System

The Goddard Earth Observing System (GEOS) developed by the NASA Global Modeling and Assimilation Office assimilates a wide range of observations to support various NASA Earth Science missions. As Measurement of planetary boundary layer (PBL) was designated as an incubation program by the 2018 Decadal Survey, we have aimed to improve PBL thermodynamic structure using data from multiple observing systems. In particular, we have developed strategies and infrastructure to assimilate PBL height (PBLH) data derived from radiosondes, GNSS radio occultation, space-based lidar (CALIPSO, CATS, IceSat-2), ground-based lidar (MPLNET) and radar wind profilers to produce global PBL height analyses. We have also explored methods to better represent capping inversions by using PBLH data together with other observations in the GEOS to adjust background error covariance and enhance model PBL parameterization performance.

Y. Zhu↗
NASA NTRS2005

Raman Lidar Measurements During the International H2O Project: Instrument Comparisons and Case Studies - 2

The NASA/GSFC Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP) that occurred in May and June, 2002 in the midwestern part of the U. S. The SRL system configuration and methods of data analysis were described in part I of this paper. In this second part, comparisons of SRL water vapor measurements and those of chilled mirror radiosonde and LASE airborne water vapor lidar are performed. Two case studies are presented; one for daytime and one for nighttime. The daytime case study is of a convectively driven boundary layer event and is used to characterize the SRL water vapor random error characteristics. The nighttime case study is of a thunderstorm-generated cirrus cloud case that is studied in it s meteorological context. Upper tropospheric humidification due to precipitation from the cirrus cloud is quantified as is the cirrus cloud ice water content and particle depolarization ratio. These detailed cirrus cloud measurements are being used in a cirrus cloud modeling study.

Whiteman, D. N.↗
NASA NTRS2003

NASA/GSFC Scanning Raman Lidar Measurements of Water Vapor and Clouds during the International H2O Project (IHOP) Field Campaign

The NASA/GSFC Scanning Raman Lidar (SFL) acquired approximately 200 hours of water vapor, aerosol and cloud measurements during the IHOP field campaign. The detailed water vapor structure of events such as a dryline passage and internal bores were revealed. We discuss the error characteristics of the instrument as well as the water vapor and cirrus cloud structure during the 19-20 June bore event.

Whiteman, David↗
NASA NTRSDate not supplied

SO2 Plumes Observation with LMOL: Theory, Modeling, and Validation

LMOL, the NASA Langley Mobile Ozone Lidar, is located near NASA’s LaRC steam plant when not deployed in campaigns. The plant produces steam through the incineration of local trash, and its exhaust plume occasionally contains SO2 . SO2 is a known, regulated, pollutant that affects O3 observations in the UV, as is the case with LMOL. In this work, we show how we modified LMOL to detect the plant SO2 plumes and compute its density when the O3 background is stable; we observed densities compatible with what is expected from the typical plume exhaust. The selection of laser lines so that an O3 variation would not get confused with a SO2 detection is explained in details, and a model capable of simulating the Lidar signal with (notably) O3 and SO2 absorption for the validation of the retrieval resolution and uncertainty is presented. Finally, the comparison between the modeled and observed performances of the system is shown: the maximum altitude, resolution, and error in the modeled signal and the observed signals are the same within reasonable margins. This work demonstrates that LMOL is fully capable of working with SO2 . The next step being the addition of an additional laser channel, which is simplified by the tunable aspect of the LMOL laser, to address O3 and SO2 simultaneously, allowing the assessment of SO2 when O3 has variations. Note: This presentation is accompanied by an mp4 video of the given talk.

Guillaume Gronoff↗
NASA NTRS2014

Deciphering the Precision of Stereo IKONOS Canopy Height Models for U.S. Forests with G-LiHT Airborne LiDAR

Few studies have evaluated the precision of IKONOS stereo data for measuring forest canopy height. The high cost of airborne light detection and ranging (LiDAR) data collection for large area studies and the present lack of a spaceborne instrument lead to the need to explore other low cost options. The US Government currently has access to a large archive of commercial high-resolution imagery, which could be quite valuable to forest structure studies. At 1 m resolution, we here compared canopy height models (CHMs) and height data derived from Goddard's airborne LiDAR Hyper-spectral and Thermal Imager (G-LiHT) with three types of IKONOS stereo derived digital surface models (DSMs) that estimate CHMs by subtracting National Elevation Data (NED) digital terrain models (DTMs). We found the following in three different forested regions of the US after excluding heterogeneous and disturbed forest samples: (1) G-LiHT DTMs were highly correlated with NED DTMs with R (sup 2) greater than 0.98 and root mean square errors (RMSEs) less than 2.96 m; (2) when using one visually identifiable ground control point (GCP) from NED, G-LiHT DSMs and IKONOS DSMs had R (sup 2) greater than 0.84 and RMSEs of 2.7 to 4.1 m; and (3) one GCP CHMs for two study sites had R (sup 2) greater than 0.7 and RMSEs of 2.6 to 3 m where data were collected less than four years apart. Our results suggest that IKONOS stereo data are a useful LiDAR alternative where high-quality DTMs are available.

IKONOS↗
NASA NTRS1981

Absolute tracer dye concentration using airborne laser-induced water Raman backscatter

The use of simultaneous airborne-laser-induced dye fluorescence and water Raman backscatter to measure the absolute concentration of an ocean-dispersed tracer dye is discussed. Theoretical considerations of the calculation of dye concentration by the numerical comparison of airborne laser-induced fluorescence spectra with laboratory spectra for known dye concentrations using the 3400/cm OH-stretch water Raman scatter as a calibration signal are presented which show that minimum errors are obtained and no data concerning water mass transmission properties are required when the laser wavelength is chosen to yield a Raman signal near the dye emission band. Results of field experiments conducted with an airborne conical scan lidar over a site in New York Bight into which rhodamine dye had been injected in a study of oil spill dispersion are then indicated which resulted in a contour map of dye concentrations, with a minimum detectable dye concentration of approximately 2 ppb by weight.

Hoge, F. E.↗
NASA NTRS2014

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Planetary Boundary Layer↗
NASA NTRSDate not supplied

Navigation Sensor Technology Assessment Capability for Data-Driven Systems Analysis

The capability to assess the mission performance of novel navigation technologies from a systems-level approach and to provide quantitative results is crucial. With growing interest and innovations from NASA’s commercial partners, data-driven results that quantify the technological impact will guide research developments and facilitate stakeholder decision-making while requiring less time and resources. This paper presents a method to evaluate various sensor combinations and their impact on the overall system performance using an existing six degrees-of-freedom, physics-based engineering simulation for a government reference lunar lander as a testbed. Selected navigation technologies over various technology readiness levels, including Inertial Measurement Units, Navigation Doppler Lidar, and radar altimeter-radar velocimeter, were studied in this paper. Results using this testbed to perform sensitivity studies and to provide quantitative assessments are reported. One key finding is that there are diminishing returns for reducing sensor errors. The most influential sensor parameter to landing success are vehicle configuration and mission dependent. Results from this method could be used by stakeholders to make data-driven systems-based decisions and by technology developers as guidance for the specific parameter improvements that will have the most significant impact on mission success. This capability could be further used to assess alternative scenarios should one type of technology become unavailable or to re-assess initial assumptions and identify appropriate requirements from a system perspective.

Esther Lee↗
NASA NTRSDate not supplied

Improving Boundary Layer Data Assimilation Using Observation Data from Multiple Observing Systems in the NASA GEOS System

The Planetary Boundary Layer (PBL) is a complex interface that mediates energy and moisture exchanges between the Earth’s surface and atmosphere. Accurate simulation and observation of PBL characteristics, such as PBL height and thermodynamic structure, have proven to be a challenge. In our latest efforts, we have focused on improving PBL thermodynamic structure using data from multiple observing systems in the Goddard Earth Observing System (GEOS), developed by the NASA Global Modeling and Assimilation Office (GMAO). We present strategies and results from assimilating PBL height data derived from radiosondes, GNSS radio occultation, space-based lidar (CALIPSO, CATS, IceSat-2), ground-based lidar (MPLNET), and radar wind profilers, including a novel global PBL height analysis dataset. We also discuss the impacts of better representing capping inversions by using PBL height data together with other observations in GEOS through adjustments to the background error covariance. Long-term statistics of the impact of assimilating and utilizing PBL height data in GEOS are presented. In addition, we explore an innovative approach to assimilate GNSS-RO refractivity data in the lower troposphere.

Eun-Gyeong Yang↗
NASA NTRS2011

Modeling the Height of Young Forests Regenerating from Recent Disturbances in Mississippi using Landsat and ICESat data

Many forestry and earth science applications require spatially detailed forest height data sets. Among the various remote sensing technologies, lidar offers the most potential for obtaining reliable height measurement. However, existing and planned spaceborne lidar systems do not have the capability to produce spatially contiguous, fine resolution forest height maps over large areas. This paper describes a Landsat-lidar fusion approach for modeling the height of young forests by integrating historical Landsat observations with lidar data acquired by the Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation (ICESat) satellite. In this approach, "young" forests refer to forests reestablished following recent disturbances mapped using Landsat time-series stacks (LTSS) and a vegetation change tracker (VCT) algorithm. The GLAS lidar data is used to retrieve forest height at sample locations represented by the footprints of the lidar data. These samples are used to establish relationships between lidar-based forest height measurements and LTSS-VCT disturbance products. The height of "young" forest is then mapped based on the derived relationships and the LTSS-VCT disturbance products. This approach was developed and tested over the state of Mississippi. Of the various models evaluated, a regression tree model predicting forest height from age since disturbance and three cumulative indices produced by the LTSS-VCT method yielded the lowest cross validation error. The R(exp 2) and root mean square difference (RMSD) between predicted and GLAS-based height measurements were 0.91 and 1.97 m, respectively. Predictions of this model had much higher errors than indicated by cross validation analysis when evaluated using field plot data collected through the Forest Inventory and Analysis Program of USDA Forest Service. Much of these errors were due to a lack of separation between stand clearing and non-stand clearing disturbances in current LTSS-VCT products and difficulty in deriving reliable forest height measurements using GLAS samples when terrain relief was present within their footprints. In addition, a systematic underestimation of about 5 m by the developed model was also observed, half of which could be explained by forest growth that occurred between field measurement year and model target year. The remaining difference suggests that tree height measurements derived using waveform lidar data could be significantly underestimated, especially for young pine forests. Options for improving the height modeling approach developed in this study were discussed.

Li, Ainong↗
NASA NTRS2011

Airborne Polarimetric, Two-Color Laser Altimeter Measurements of Lake Ice Cover: A Pathfinder for NASA's ICESat-2 Spaceflight Mission

The ICESat-2 mission will continue NASA's spaceflight laser altimeter measurements of ice sheets, sea ice and vegetation using a new measurement approach: micropulse, single photon ranging at 532 nm. Differential penetration of green laser energy into snow, ice and water could introduce errors in sea ice freeboard determination used for estimation of ice thickness. Laser pulse scattering from these surface types, and resulting range biasing due to pulse broadening, is assessed using SIMPL airborne data acquired over icecovered Lake Erie. SIMPL acquires polarimetric lidar measurements at 1064 and 532 nm using the micropulse, single photon ranging measurement approach.

Harding, David↗
NASA NTRS2013

Airborne Measurements of CO2 Column Concentration and Range Using a Pulsed Direct-Detection IPDA Lidar

We have previously demonstrated a pulsed direct detection IPDA lidar to measure range and the column concentration of atmospheric CO2. The lidar measures the atmospheric backscatter profiles and samples the shape of the 1,572.33 nm CO2 absorption line. We participated in the ASCENDS science flights on the NASA DC-8 aircraft during August 2011 and report here lidar measurements made on four flights over a variety of surface and cloud conditions near the US. These included over a stratus cloud deck over the Pacific Ocean, to a dry lake bed surrounded by mountains in Nevada, to a desert area with a coal-fired power plant, and from the Rocky Mountains to Iowa, with segments with both cumulus and cirrus clouds. Most flights were to altitudes >12 km and had 5-6 altitude steps. Analyses show the retrievals of lidar range, CO2 column absorption, and CO2 mixing ratio worked well when measuring over topography with rapidly changing height and reflectivity, through thin clouds, between cumulus clouds, and to stratus cloud tops. The retrievals shows the decrease in column CO2 due to growing vegetation when flying over Iowa cropland as well as a sudden increase in CO2 concentration near a coal-fired power plant. For regions where the CO2 concentration was relatively constant, the measured CO2 absorption lineshape (averaged for 50 s) matched the predicted shapes to better than 1% RMS error. For 10 s averaging, the scatter in the retrievals was typically 2-3 ppm and was limited by the received signal photon count. Retrievals were made using atmospheric parameters from both an atmospheric model and from in situ temperature and pressure from the aircraft. The retrievals had no free parameters and did not use empirical adjustments, and >70% of the measurements passed screening and were used in analysis. The differences between the lidar-measured retrievals and in situ measured average CO2 column concentrations were <1.4 ppm for flight measurement altitudes >6 km.

Lidar↗