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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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At least 577 records · Page 32
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NASA NTRS1996

Radioactive Transfer Models for Saturn and Titan

The infrared spectra of the earth's atmosphere and planetary atmospheres contains information about atmospheric physical and chemical processes. Atmospheric molecular constituents absorb and emit infrared radiation by rotational and vibrational transition. Observed spectra exhibit characteristic features in the electromagnetic spectrum region. Observation of the absorption or thermal emission spectra may be obtained with space-borne high resolution infrared spectrometers in the 10-5000 cm(exp -1) (2-1000 micro-m) spectral region. Information about the atmospheric thermal structure, composition, and the chemical and physical processes of the observed spectral was accomplished. A preliminary version of a P-T retrieval algorithm for Saturn using all three modes for temperature inversion, e.g., CH4-limb, and H2-nadir spectra was completed and tested for accuracy. Radiative transfer and inversion programs were studied and analyzed for applications to infrared limb thermal emission observations of Saturn and Titan from the Cassini Orbiter, as well as Earth's atmosphere. Analysis and modification of the existing radiative transfer and inversion programs for Earth and planetary atmospheres are being made. Data analysis and retrieval of information form the observations by digital calculations were carried out at UAH and MSFC computer. The working program for generating and reading g-k arrays for using the c-k arrays via the c-k method for radiative transfer calculations for desired atmospheric and instrumental parameters was completed, tested for accuracy and resides at the MSFC computer.

Wu, S. T.↗
NASA NTRS2017

Effective Assimilation of SMAP Observations Using Statistical Techniques

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

Kolassa, J.↗
NASA NTRSDate not supplied

Synthetic Hyperspectral Data for Global Water Quality Algorithm Development

Eutrophication and increasing prevalence of potentially toxic algal blooms (cyanoHABs) among global inland water bodies have become a major ecological concern and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local aquatic processes, to spatially resolved global products. Planned aquatic biogeochemistry remote sensing data products from hyperspectral imagers such as NASA’s Surface Biology and Geology (SBG) mission and relevant aquatic sensor sensitivity precursor airborne imaging spectrometer data provide unprecedented radiometric resolution and sensor sensitivity for characterizing complex aquatic ecosystems. However, scarcity of high-quality freshwater in-situ optical data hinders our capability to develop and validate robust retrieval algorithms. A state-of-the-art synthetic dataset of paired top-of-atmosphere, bottom-of-atmosphere, and optical and biogeophysical data was developed through radiative transfer modeling to simulate natural freshwater ecosystems. A synthetic or precursor dataset for SBG is being used to train robust machine learning models to derive water quality products pertinent to SBG mission objectives. The dataset is also used to show the potential of performing vigorous aquatic sensitivity studies and explored pathways for how best to optimize hyperspectral data for machine learning development. A processing pipeline and resultant global synthetic/precursor dataset for inland waters is presented to establish the innovation for water quality studies of inland waters globally. Optical Society of America Imaging and Applied Optics Congress, Hyperspectral Imaging and Sounding of the Environment (OSA HISE) Meeting, 19-23 July 2021, Virtual Meeting, https://www.osa.org/enus/meetings/osa_meetings/optical_sensors_and_sensing_congress/program/hyperspectral_imaging_and_sounding_of_the_environm/

Synthetic↗
NASA NTRS2009

NASA Global Precipitation Mission Ground Validation Implementation

The Global Precipitation Mission (GPM; core-satellite launch 2013) will provide Ka/Ku-band dual-frequency precipitation radar (DPR) and accompanying passive microwave radiometer-diagnosed precipitation estimates over a latitude range of 65 N to 65 S. The extended latitudinal domain of GPM coverage combined with requirements to detect (and in the case of liquid, estimate) liquid and frozen precipitation rates for values ranging from several hundred to just a few tenths of a millimeter per hour present new challenges to the development of physically-based satellite precipitation retrieval algorithms. On regional scales select national and international resources such as existing calibrated radar and rain gauge networks can provide basic datasets that enable direct statistical validation of GPM core-satellite reflectivitys and core/constellation rain rate measurements. Near-term planned field campaign involvements include Finland/Baltic Sea (fall 2010; joint CloudSat,GPM, and European study of precipitation in low-altitude melting layers and snowfall in the vicinity of the Helsinki testbed), central Oklahoma (spring 2011; joint with DOE ARM- precipitation retrievals over a mid-latitude continental land surface), and the Great Lakes region (winter 2011-12, snowfall retrieval).

Petersen, Walter A.↗
NASA NTRS2019

Two Decades Observing Smoke Above Clouds in the South-Eastern Atlantic Ocean: Deep Blue Algorithm Updates and Validation with ORACLES Field Campaign Data

This study presents and evaluates an updated algorithmfor quantification of absorbing aerosols above clouds(AACs) from passive satellite measurements. The focus isbiomass burning in the south-eastern Atlantic Ocean duringthe 2016 and 2017 ObseRvations of Aerosols above CLoudsand their intEractionS (ORACLES) field campaign deployments.The algorithm retrieves the above-cloud aerosoloptical depth (AOD) and underlying liquid cloud opticaldepth and is applied to measurements from the Sea-viewingWide Field-of-view Sensor (SeaWiFS), Moderate ResolutionImaging Spectroradiometer (MODIS), and Visible InfraredImaging Radiometer Suite (VIIRS) from 1997 to 2017. AirborneNASA Ames Spectrometers for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) and NASA LangleyHigh Spectral Resolution Lidar 2 (HSRL2) data collectedduring ORACLES provide important validation for spectralAOD for MODIS and VIIRS; as the SeaWiFS missionended in 2010, it cannot be evaluated directly. The 4STARand HSRL2 comparisons are complementary and reveal performancegenerally in line with uncertainty estimates providedby the optimal estimation retrieval framework used. Atpresent the two MODIS-based data records seem the mostreliable, although there are differences between the deployments,which may indicate that the available data are not yetsufficient to provide a robust regional validation. Spatiotemporalpatterns in the data sets are similar, and the time seriesare very strongly correlated with each other (correlationcoefficients from 0.95 to 0.99). Offsets between the satellitedata sets are thought to be chiefly due to differences in absolutecalibration between the sensors. The available validationdata for this type of algorithm are limited to a small numberof field campaigns, and it is strongly recommended that suchairborne measurements continue to be made, both over thesouthern Atlantic Ocean and elsewhere.

Sayer, Andrew M.↗
NASA NTRS2006

Ozone Profiles in the High-latitude Stratosphere and Lower Mesosphere Measured by the Improved Limb Atmospheric Spectrometer (ILAS)-II: Comparison with other Satellite Sensors and Ozonesondes

A solar occultation sensor, the Improved Limb Atmospheric Spectrometer (ILAS)-II, measured 5890 vertical profiles of ozone concentrations in the stratosphere and lower mesosphere and of other species from January to October 2003. The measurement latitude coverage was 54-71degN and 64-88degS, which is similar to the coverage of ILAS (November 1996 to June 1997). One purpose of the ILAS-II measurements was to continue such high-latitude measurements of ozone and its related chemical species in order to help accurately determine their trends. The present paper assesses the quality of ozone data in the version 1.4 retrieval algorithm, through comparisons with results obtained from comprehensive ozonesonde measurements and four satellite-borne solar occultation sensors. In the Northern Hemisphere (NH), the ILAS-II ozone data agree with the other data within +/-10% (in terms of the absolute difference divided by its mean value) at altitudes between 11 and 40 km, with the median coincident ILAS-II profiles being systematically up to 10% higher below 20 km and up to 10% lower between 21 and 40 km after screening possible suspicious retrievals. Above 41 km, the negative bias between the NH ILAS-II ozone data and the other data increases with increasing altitude and reaches 30% at 61-65 km. In the Southern Hemisphere, the ILAS-II ozone data agree with the other data within 10% in the altitude range of 11-60 km, with the median coincident profiles being on average up to 10% higher below 20 km and up to 10% lower above 20 km.

Sugita, T.↗
NASA NTRS1991

Analysis of error in TOMS total ozone as a function of orbit and attitude parameters

Computer simulations of orbital scenarios were performed to examine the effects of orbital altitude, equator crossing time, attitude uncertainty, and orbital eccentricity on ozone observations by future satellites. These effects were assessed by determining changes in solar and viewing geometry and earth daytime coverage loss. The importance of these changes on ozone retrieval was determined by simulating uncertainties in the TOMS ozone retrieval algorithm. The major findings are as follows: (1) Drift of equator crossing time from local noon would have the largest effect on the quality of ozone derived from TOMS. The most significant effect of this drift is the loss of earth daytime coverage in the winter hemisphere. The loss in coverage increases from 1 degree latitude for + or - 1 hour from noon, 6 degrees for + or - 3 hours from noon, to 53 degrees for + or - 6 hours from noon. An additional effect is the increase in ozone retrieval errors due to high solar zenith angles. (2) To maintain contiguous earth coverage, the maximum scan angle of the sensor must be increased with decreasing orbital altitude. The maximum scan angle required for full coverage at the equator varies from 60 degrees at 600 km altitude to 45 degrees at 1200 km. This produces an increase in spacecraft zenith angle, theta, which decreases the ozone retrieval accuracy. The range in theta was approximately 72 degrees for 600 km to approximately 57 degrees at 1200 km. (3) The effect of elliptical orbits is to create gaps in coverage along the subsatellite track. An elliptical orbit with a 200 km perigee and 1200 km apogee produced a maximum earth coverage gap of about 45 km at the perigee at nadir. (4) An attitude uncertainty of 0.1 degree in each axis (pitch, roll, yaw) produced a maximum scan angle to view the pole, and maximum solar zenith angle).

Gregg, W. W.↗
NASA NTRS2017

The Effects of Different Footprint Sizes and Cloud Algorithms on the Top-Of-Atmosphere Radiative Flux Calculation from the Clouds and Earth’s Radiant Energy System (CERES) Instrument on Suomi National Polar-Orbiting Partnership (NPP)

Only one Clouds and Earth’s Radiant Energy System (CERES) instrument is onboard the Suomi National Polar-orbiting Partnership (NPP) and it has been placed in cross-track mode since launch; it is thus not possible to construct a set of angular distribution models (ADMs) specific for CERES on NPP. Edition 4 Aqua ADMs are used for flux inversions for NPP CERES measurements. However, the footprint size of NPP CERES is greater than that of Aqua CERES, as the altitude of the NPP orbit is higher than that of the Aqua orbit. Furthermore, cloud retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), which are the imagers sharing the spacecraft with NPP CERES and Aqua CERES, are also different. To quantify the flux uncertainties due to the footprint size difference between Aqua CERES and NPP CERES, and due to both the footprint size difference and cloud property difference, a simulation is designed using the MODIS pixel-level data, which are convolved with the Aqua CERES and NPP CERES point spread functions (PSFs) into their respective footprints. The simulation is designed to isolate the effects of footprint size and cloud property differences on flux uncertainty from calibration and orbital differences between NPP CERES and Aqua CERES. The footprint size difference between Aqua CERES and NPP CERES introduces instantaneous flux uncertainties in monthly gridded NPP CERES measurements of less than 4.0 W/sq. m for SW (shortwave) and less than 1.0 W/sq. m for both daytime and nighttime LW (longwave). The global monthly mean instantaneous SW flux from simulated NPP CERES has a low bias of 0.4 W/sq. m when compared to simulated Aqua CERES, and the root-mean-square (RMS) error is 2.2 W/sq. m between them; the biases of daytime and night- time LW flux are close to zero with RMS errors of 0.8 and 0.2 W/sq. m. These uncertainties are within the uncertainties of CERES ADMs. When both footprint size and cloud property (cloud fraction and optical depth) differences are considered, the uncertainties of monthly gridded NPP CERES SW flux can be up to 20 W/sq. m in the Arctic regions where cloud optical depth retrievals from VIIRS differ significantly from MODIS. The global monthly mean instantaneous SW flux from simulated NPP CERES has a high bias of 1.1 W/sq. m and the RMS error increases to 5.2 W/sq. m. LW flux shows less sensitivity to cloud property differences than SW flux, with uncertainties of about 2 W/sq. m in the monthly gridded LW flux, and the RMS errors of global monthly mean daytime and nighttime fluxes increase only slightly. These results highlight the importance of consistent cloud retrieval algorithms to maintain the accuracy and stability of the CERES climate data record.

Su, Wenying↗
NASA NTRS1993

AVHRR Surface Temperature and Narrow-Band Albedo Comparison with Ground Measurements for the Greenland Ice Sheet

An ice-surface temperature retrieval algorithm for the Greenland ice sheet was developed using NOAA 11 thermal radiances from channels 4 and 5. Temperature, pressure and humidity profiles, cloud observations and skin temperatures from the Swiss Federal Institute of Technology (ETH) camp, located at the equilibrium line altitude at 49 deg17 min W, 69 deg 34 min N, were used in the LOWTRAN 7 model. Through a statistical analysis of daily clear sky profiles, the coefficients that correct for the atmospheric effects were determined for the ETH-Camp field season (May to August). Surface temperatures retrieved by this method were then compared against the in situ observations with a maximum difference of 0.6 K. The NOAA 11 narrow-band planetary albedo values for channels 1 and 2 were calculated using pre-launch calibration coefficients. Scattering and absorption by the atmosphere were modelled with LOWTRAN 7. Then, narrow-band albedo values for the AVHRR visible and near infrared channels were compared with in situ high resolution spectral reflectance measurements. In the visible band (580-680 nm), AVHRR-derived narrow-band albedo and the in situ measurements corrected with radiative transfer model LOWTRAN 7 showed a difference of less than 2%. For the near infrared channel (725-1100 nm) the difference between the measured and modelled narrow-band albedo was 14%. These discrepancies could be either the result of inaccurate aerosol scattering modelling (lack of the in situ observation), or the result of sensor drift due to degradation.

Haefliger, M.↗
NASA NTRS2012

Evaluations of Thin Cirrus Contamination and Screening in Ground Aerosol Observations Using Collocated Lidar Systems

Cirrus clouds, particularly sub visual high thin cirrus with low optical thickness, are difficult to be screened in operational aerosol retrieval algorithms. Collocated aerosol and cirrus observations from ground measurements, such as the Aerosol Robotic Network (AERONET) and the Micro-Pulse Lidar Network (MPLNET), provide us with an unprecedented opportunity to examine the susceptibility of operational aerosol products to thin cirrus contamination. Quality assured aerosol optical thickness (AOT) measurements were also tested against the CALIPSO vertical feature mask (VFM) and the MODIS-derived thin cirrus screening parameters for the purpose of evaluating thin cirrus contamination. Key results of this study include: (1) Quantitative evaluations of data uncertainties in AERONET AOT retrievals are conducted. Although AERONET cirrus screening schemes are successful in removing most cirrus contamination, strong residuals displaying strong spatial and seasonal variability still exist, particularly over thin cirrus prevalent regions during cirrus peak seasons, (2) Challenges in matching up different data for analysis are highlighted and corresponding solutions proposed, and (3) Estimation of the relative contributions from cirrus contamination to aerosol retrievals are discussed. The results are valuable for better understanding and further improving ground aerosol measurements that are critical for aerosol-related climate research.

Huang, Jingfeng↗
NASA NTRS2001

Columnar Aerosol Single-Scattering Albedo and Phase Function Retrieved from Sky Radiance Over the Ocean: Measurements of African Dust

The single-scattering albedo and phase function of African mineral dust are retrieved from ground-based measurements of sky radiance collected in the Florida Keys. The retrieval algorithm employs the radiative transfer equation to solve by iteration for these two properties which best reproduce the observed sky radiance using an assumed aerosol vertical structure and measured aerosol optical depth. Thus, no assumptions regarding particle size, shape, or composition are required. The single-scattering albedo, presented at fourteen wavelengths between 380 and 870 nm, displays a spectral shape expected of iron-bearing minerals but is much higher than current dust models allow. This indicates the absorption of light by mineral dust is significantly overestimated in climate studies. Uncertainty in the retrieved albedo is less than 0.02 due to the small uncertainty in the solar-reflectance-based calibration (12.2%) method employed. The phase function retrieved at 860 nm is very robust under simulations of expected experimental errors, indicating retrieved phase functions at this wavelength may be confidently used to describe aerosol scattering characteristics. The phase function retrieved at 443 nm is very sensitive to expected experimental errors and should not be used to describe aerosol scattering. Radiative forcing by aerosol is the greatest source of uncertainty in current climate models. These results will help reduce uncertainty in the absorption of light by mineral dust. Assessment of the radiative impact of aerosol species is a key component to NASA's Earth System Enterprise.

Cattrall, Christopher↗
NASA NTRS1994

The design and development of signal-processing algorithms for an airborne x-band Doppler weather radar

Improved measurements of precipitation will aid our understanding of the role of latent heating on global circulations. Spaceborne meteorological sensors such as the planned precipitation radar and microwave radiometers on the Tropical Rainfall Measurement Mission (TRMM) provide for the first time a comprehensive means of making these global measurements. Pre-TRMM activities include development of precipitation algorithms using existing satellite data, computer simulations, and measurements from limited aircraft campaigns. Since the TRMM radar will be the first spaceborne precipitation radar, there is limited experience with such measurements, and only recently have airborne radars become available that can attempt to address the issue of the limitations of a spaceborne radar. There are many questions regarding how much attenuation occurs in various cloud types and the effect of cloud vertical motions on the estimation of precipitation rates. The EDOP program being developed by NASA GSFC will provide data useful for testing both rain-retrieval algorithms and the importance of vertical motions on the rain measurements. The purpose of this report is to describe the design and development of real-time embedded parallel algorithms used by EDOP to extract reflectivity and Doppler products (velocity, spectrum width, and signal-to-noise ratio) as the first step in the aforementioned goals.

Nicholson, Shaun R.↗
NASA NTRSDate not supplied

Defining Pupil Knowledge Requirements for Roman Space Telescope Integrated Payload Assembly Testing

This thesis examines the use of phase retrieval to characterize an optical system under testing conditions with pupil knowledge error. The purpose of this investigation is to define pupil knowledge requirements for the integrated payload testing of the Roman Space Telescope. We have conducted a Monte Carlo study to determine how location uncertainty of the ground support equipment relative to the payload caused by the temperature deformation in the Space Environment Simulator will affect our ability to use image-based wavefront sensing during the test to characterize system alignment. This test will be conducted with significant wavefront error (WFE) present due to gravity sag on the primary mirror. The study incrementally decenters two pieces of ground support equipment and evaluates how the phase retrieval algorithm attempts to fit the wavefront. We conducted this investigation in two steps. First, we used an ideal optical model of the test configuration without the gravity sag on the primary mirror to see the fitting effects related only to pupil knowledge error introduced by the decentering. Then, we used perturbed and gravity sag models to investigate the effects of decentering dependent wavefront effects in addition to pupil knowledge error. The results from the ideal model provided a clear limit of the amount of pupil knowledge error that can be present before seeing significant WFE in the phase retrieval. For the second study, we used the decentering tolerances from the ideal model results to determine the WFE effects of decentering in the presence of gravity sag and system misalignments. The second part of this study will be factored into the overall integrated payload assembly testing WFE budget.

Roman Space Telescope↗
NASA NTRS2017

AIRS-Only Product in Giovanni for Exploring Up-to-Date AIRS Observation and Comparing with AIRS+AMSU Product

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of processing, archiving, and distribution services for the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002 for global observations of the atmospheric state. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important AIRS variables, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases, are available in Giovanni. AIRS is an instrument suite comprised of a hyperspectral infrared instrument (AIRS) and two multichannel microwave instruments, the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB). As HSB ceased operation in the very early stages of the AIRS mission, the AIRS project operates two parallel retrieval algorithms: one using both IR and MW measurements (AIRS+AMSU) and the other using only IR measurements (AIRS-only), which covers most of the mission duration. The AIRS+AMSU product is better quality, and the variables in Giovanni are from this product. However, generation of the AIRS+AMSU product has been suspended since the AMSU instrument anomaly occurred in late September 2016. To continue exploring up-to-date AIRS observations, the same set of variables from the AIRS-only product have been added to Giovanni by the GES DSIC. This will also support comparison of AIRS-only with AIRS+AMSU retrievals. In this presentation, we demonstrate the visualization of the AIRS-only product and plots/statistics of comparison with AIRS+AMSU product using Giovanni.

AIRS↗
NASA NTRS2004

Implications of Version 8 TOMS and SBUV Data for Long-Term Trend Analysis

Total ozone data from the Total Ozone Mapping Spectrometer (TOMS) and profile/total ozone data from the Solar Backscatter Ultraviolet (SBUV; SBW/2) series of instruments have recently been reprocessed using new retrieval algorithms (referred to as Version 8 for both) and updated calibrations. In this paper, we incorporate the Version 8 data into a TOMS/SBW merged total ozone data set and an S B W merged profile ozone data set. The Total Merged Ozone Data (Total MOD) combines data from multiple TOMS and SBW instruments to form an internally consistent global data set with virtually complete time coverage from October 1978 through December 2003. Calibration differences between instruments are accounted for using external adjustments based on instrument intercomparisons during overlap periods. Previous results showed errors due to aerosol loading and sea glint are significantly reduced in the V8 TOMS retrievals. Using SBW as a transfer standard, calibration differences between V8 Nimbus 7 and Earth Probe TOMS data are approx. 1.3%, suggesting small errors in calibration remain. We will present updated total ozone long-term trends based on the Version 8 data. The Profile Merged Ozone Data (Profile MOD) data set is constructed using data from the SBUV series of instruments. In previous versions, SAGE data were used to establish the long-term external calibration of the combined data set. The SBW Version 8 we assess the V8 profile data through comparisons with SAGE and between SBW instruments in overlap periods. We then construct a consistently-calibrated long term time series. Updated zonal mean trends as a function of altitude and season from the new profile data set will be shown, and uncertainties in determining the best long-term calibration will be discussed.

Frith, Stacey M.↗
NASA NTRS2019

Retrieving Aerosol Characteristics From the PACE Mission, Part 2: Multi-Angle and Polarimetry

The Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission presents new opportunities and new challenges in applying observations of two complementary multi-angle polarimeters for the space-based retrieval of global aerosol properties.Aerosol remote sensing from multi-angle radiometric-only observations enables aerosol characterization to a greater degree than single-view radiometers, as demonstrated by nearly two decades of heritage instruments. Adding polarimetry to the multi-angle observations allows for the retrieval of aerosol optical depth, Angstrom exponent,parameters of size distribution, measures of aerosol absorption, complex refractive index and degree of non-sphericity of the particles, as demonstrated by two independent retrieval algorithms applied to the heritage POLarization and Directionality of the Earth's Reflectance (POLDER) instrument. The reason why this detailed particle characterization is possible is because a multi-angle polarimeter measurement contains twice the number of Degrees of Freedom of Signal (DFS) compared to an observation from a single-view radiometer. The challenges of making use of this information content involve separating surface signal from atmospheric signal, especially when the surface is optically complex and especially in the ultraviolet portion of the spectrum where we show the necessity of polarization in making that separation. The path forward is likely to involve joint retrievalsthat will simultaneously retrieve aerosol and surface properties, although advances will berequired in radiative transfer modeling and in representing optically complex constituents in those models. Another challenge is in having the processing capability that can keep pace with the output of these instruments in an operational environment. Yet, preliminaryalgorithms applied to airborne multi-angle polarimeter observations offer encouraging results that demonstrate the advantages of these instruments to retrieve aerosol layer height, particle single scattering albedo, size distribution and spectral optical depth, and also show the necessity of polarization measurements, not just multi-angle radiometricmeasurements, to achieve these results.

Remer, Lorraine A.↗
NASA NTRS2018

NASA's Black Marble Product Suite: Validation Strategy

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500m resolution since January 2012 with data fro the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-terrain, vegetation, snow, lunar and stray light corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Current and planned validation activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at difference geographic locations and time periods representing the full range of retrieval conditions.

GEO Human Planet↗
DOE OSTI2024

Refining Planetary Boundary Layer Height Retrievals From Micropulse‐Lidar at Multiple ARM Sites Around the World

Abstract Knowledge of the planetary boundary layer height (PBLH) is crucial for various applications in atmospheric and environmental sciences. Lidar measurements are frequently used to monitor the evolution of the PBLH, providing more frequent observations than traditional radiosonde‐based methods. However, lidar‐derived PBLH estimates have substantial uncertainties, contingent upon the retrieval algorithm used. In addressing this, we applied the Different Thermo‐Dynamic Stabilities (DTDS) algorithm to establish a PBLH data set at five separate Department of Energy's Atmospheric Radiation Measurement sites across the globe. Both the PBLH methodology and the products are subject to rigorous assessments in terms of their uncertainties and constraints, juxtaposing them with other products. The DTDS‐derived product consistently aligns with radiosonde PBLH estimates, with correlation coefficients exceeding 0.77 across all sites. This study delves into a detailed examination of the strengths and limitations of PBLH data sets with respect to both radiosonde‐derived and other lidar‐based estimates of the PBLH by exploring their respective errors and uncertainties. It is found that varying techniques and definitions can lead to diverse PBLH retrievals due to the inherent intricacy and variability of the boundary layer. Our DTDS‐derived PBLH data set outperforms existing products derived from ceilometer data, offering a more precise representation of the PBLH. This extensive data set paves the way for advanced studies and an improved understanding of boundary‐layer dynamics, with valuable applications in weather forecasting, climate modeling, and environmental studies.

54 ENVIRONMENTAL SCIENCES↗