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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 163 records · Page 9

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NASA NTRS2001

Aerosol Measurements by the Globally Distributed Micro Pulse Lidar Network

Full time measurements of the vertical distribution of aerosol are now being acquired at a number of globally distributed MP (micro pulse) lidar sites. The MP lidar systems provide full time profiling of all significant cloud and aerosol to the limit of signal attenuation from compact, eye safe instruments. There are currently eight sites in operation and over a dozen planned. At all sited there are also passive aerosol and radiation measurements supporting the lidar data. Four of the installations are at Atmospheric Radiation Measurement program sites. The network operation includes instrument operation and calibration and the processing of aerosol measurements with standard retrievals and data products from the network sites. Data products include optical thickness and extinction cross section profiles. Application of data is to supplement satellite aerosol measurements and to provide a climatology of the height distribution of aerosol. The height distribution of aerosol is important for aerosol transport and the direct scattering and absorption of shortwave radiation in the atmosphere. Current satellite and other data already provide a great amount of information on aerosol distribution, but no passive technique can adequately resolve the height profile of aerosol. The Geoscience Laser Altimeter System (GLAS) is an orbital lidar to be launched in early 2002. GLAS will provide global measurements of the height distribution of aerosol. The MP lidar network will provide ground truth and analysis support for GLAS and other NASA Earth Observing System data. The instruments, sites, calibration procedures and standard data product algorithms for the MPL network will be described.

Spinhirne, James↗

NASA NTRS2020

The GPM Ground Validation Program

We present a detailed overview of the structure and activities associated with the NASA-led ground-validation component of the NASA-JAXA Global Precipitation Measurement (GPM) mission. The overarching philosophy and approaches for NASA's GV program are presented with primary focus placed on aspects of direct validation and a summary of physical validation campaigns and results. We describe a spectrum of key instruments, methods, field campaigns and data products developed and used by NASA's GV team to verify GPM level-2 precipitation products in rain and snow. We describe the tools and analysis framework used to confirm that NASA's Level-I science requirements for GPM are met by the GPM Core Observatory. Examples of routine validation activities related to verification of Integrated MultisatellitE Retrievals for GPM (IMERG) products for two different regions of the globe (Korea and the US) are provided, and a brief analysis related to IMERG performance in the extreme rainfall event associated with Hurricane Florence is discussed.

precipitation↗

NASA NTRSDate not supplied

Improvements in CALIOP Smoke Optical Depth over Clouds

Smoke over marine stratocumulus is ubiquitous off the south west coast of Africa during biomass burning season. The vertical profile measurements provided by the CALIOP lidar are successfully able to distinguish between smoke and underlying clouds. With over 14 years of observations, the CALIOP data set is a valuable asset for quantifying the radiative impact of smoke over clouds in this region. However past studies have shown that CALIOP overestimates the base altitudes of strongly attenuating smoke layers. This is because CALIOP layer detection operates on the 532 nm attenuated backscatter signal. Smoke strongly attenuates light at this wavelength, so CALIOP feature detection at times assigns a base altitude that is higher than the true layer base for optically thick layers. This can be confirmed by the 1064 nm attenuated backscatter signal, also measured by CALIOP. In order to improve the AOD for smoke over clouds, a new algorithm has been implemented in for an upcoming CALIOP level 2 data release that will extend the base altitudes of smoke layers over clouds. Tunable restrictions are put in place to ensure that smoke bases are only extended within a reasonable smoke-to-cloud gap distance and only when there is strong reason to believe that smoke exists within the gap. This presentation will summarize the new smoke base extension algorithm and summarize its performance. We will demonstrate that base extension is primarily invoked off the south west coast of Africa as expected. We will also quantify the increase in smoke AOD that will be reported in the upcoming level 2 data release.

Jason L Tackett↗

NASA NTRS1971

Estimation of total ozone from satellite measurements of backscattered ultraviolet earth radiance.

Total ozone is estimated from Nimbus IV satellite measurements of the attenuation of backscattered radiances at wavelengths between 3100 and 3400 A. A measurement of the backscattered radiance at 3800 A, outside the ozone absorption band, is used to determine an equivalent Lambert albedo for the cloud-ground-haze surface viewed by the instrument. The measured relative attenuation at two wavelengths is compared with such values precomputed for a series of standard ozone profiles and corrected for the equivalent Lambert albedo. Total ozone is obtained by interpolation. Two alternative methods are used to assign an equivalent Lambert albedo at the absorbing wavelengths. Total ozone values estimated by these methods are compared with the Dobson (ground-truth) data by linear regression. The available evidence suggests that the true standard error of the satellite data may be 0.015 atm-cm or less for solar zenith angles smaller than 60 deg.

Mateer, C. L.↗

NASA NTRS2013

Preliminary Experiments for the Assessment of V/W-band Links for Space-Earth Communications

Since September 2012, NASA Glenn Research Center has deployed a microwave profiling radiometer at White Sands, NM, to estimate atmospheric propagation effects on communications links in the V and W bands (71-86GHz). Estimates of attenuation statistics in the millimeter wave due to gaseous and cloud components of the atmosphere show good agreement with current ITU-R models, but fail to predict link performance in the presence of moderate to heavy rain rates, due to the inherent limitations of passive radiometry. Herein, we discuss the preliminary results of these measurements and describe a design for a terrestrial link experiment to validate/refine existing rain attenuation models in the V/Wbands.

propagation↗

NASA NTRS2013

Preliminary Experiments for the Assessment of VW-Band Links for Space-Earth Communications

Since September 2012, NASA Glenn Research Center has deployed a microwave profiling radiometer at White Sands, NM, to estimate atmospheric propagation effects on communications links in the V and W bands (71-86GHz). Estimates of attenuation statistics in the millimeter wave due to gaseous and cloud components of the atmosphere show good agreement with current ITU-R models, but fail to predict link performance in the presence of moderate to heavy rain rates, due to the inherent limitations of passive radiometry. Herein, we discuss the preliminary results of these measurements and describe a design for a terrestrial link experiment to validaterefine existing rain attenuation models in the VW-bands.

terrestrial milimeterwave experiments↗

NASA NTRS1996

Correction of WindScat Scatterometric Measurements by Combining with AMSR Radiometric Data

The Seawinds scatterometer on the advanced Earth observing satellite-2 (ADEOS-2) will determine surface wind vectors by measuring the radar cross section. Multiple measurements will be made at different points in a wind-vector cell. When dense clouds and rain are present, the signal will be attenuated, thereby giving erroneous results for the wind. This report describes algorithms to use with the advanced mechanically scanned radiometer (AMSR) scanning radiometer on ADEOS-2 to correct for the attenuation. One can determine attenuation from a radiometer measurement based on the excess brightness temperature measured. This is the difference between the total measured brightness temperature and the contribution from surface emission. A major problem that the algorithm must address is determining the surface contribution. Two basic approaches were developed for this, one using the scattering coefficient measured along with the brightness temperature, and the other using the brightness temperature alone. For both methods, best results will occur if the wind from the preceding wind-vector cell can be used as an input to the algorithm. In the method based on the scattering coefficient, we need the wind direction from the preceding cell. In the method using brightness temperature alone, we need the wind speed from the preceding cell. If neither is available, the algorithm can work, but the corrections will be less accurate. Both correction methods require iterative solutions. Simulations show that the algorithms make significant improvements in the measured scattering coefficient and thus is the retrieved wind vector. For stratiform rains, the errors without correction can be quite large, so the correction makes a major improvement. For systems of separated convective cells, the initial error is smaller and the correction, although about the same percentage, has a smaller effect.

Song, S.↗

NASA NTRS1988

The photodissociation and chemistry of interstellar CO

Recent work on the vacuum UV absorption spectrum of CO to the description of the photodissociation of interstellar CO and its principal isotopic varieties is discussed. The effects of line broadening, self-shielding, shielding by H and H2, and isotope-selective shielding are examined as functions of depth into interstellar clouds. The photodissociation rates of the isotopic species are larger than that of (C-12)O inside the clouds by up to one to two orders of magnitude. A simple approximation to the attenuation by line absorption is given in tabular form. Computed abundances of CO and related species C and C+ are presented for a variety of interstellar clouds ranging from diffuse clouds to dense photodissociation regions. Several series of models of translucent clouds are presented which illustrate how the CO abundance increases rapidly with total cloud thickness. The variations of the isotopic abundances with depth and their sensitivity to temperature and total cloud thickness are explored in detail.

Van Dishoeck, Ewine F.↗

DOE OSTI2025

CROCUS Dual Polarization Ceilometer Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, CROCUS Urban Integrated Field Laboratory (https://crocus-urban.org/). The dual-polarization ceilometer (Vaisala CL61) is an autonomous lidar system operating at 910 nm wavelength, providing valuable measurements for understanding atmospheric boundary layer evolution, air quality, and cloud-aerosol interactions. The CL61 measures the backscattered signal intensity alternating between parallel- and cross-polarization signals. The unique depolarization measurement capability improves discrimination between different particle types, such as liquid droplets, ice crystals, and aerosols. The depolarization is highly dependent on the scatterer shape and orientation (spherical vs non-spherical particles), with the linear depolarization ratio providing a measure of dominant backscatter signal component from atmospheric particles at various heights, essentially allowing discrimination between liquid and solid particles. With its efficient optical system, CL61’s improved signal-to-noise ratio compared to traditional ceilometers allows studying detailed vertical profiles of aerosols and clouds up to 15 km height.Datasets are stored in a netCDF data format, and we we encourage users to make use of the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Remote Sensing of In-Flight Icing Conditions: Operational, Meteorological, and Technological Considerations

Remote-sensing systems that map aircraft icing conditions in the flight path from airports or aircraft would allow icing to be avoided and exited. Icing remote-sensing system development requires consideration of the operational environment, the meteorological environment, and the technology available. Operationally, pilots need unambiguous cockpit icing displays for risk management decision-making. Human factors, aircraft integration, integration of remotely sensed icing information into the weather system infrastructures, and avoid-and-exit issues need resolution. Cost, maintenance, power, weight, and space concern manufacturers, operators, and regulators. An icing remote-sensing system detects cloud and precipitation liquid water, drop size, and temperature. An algorithm is needed to convert these conditions into icing potential estimates for cockpit display. Specification development requires that magnitudes of cloud microphysical conditions and their spatial and temporal variability be understood at multiple scales. The core of an icing remote-sensing system is the technology that senses icing microphysical conditions. Radar and microwave radiometers penetrate clouds and can estimate liquid water and drop size. Retrieval development is needed; differential attenuation and neural network assessment of multiple-band radar returns are most promising to date. Airport-based radar or radiometers are the most viable near-term technologies. A radiometer that profiles cloud liquid water, and experimental techniques to use radiometers horizontally, are promising. The most critical operational research needs are to assess cockpit and aircraft system integration, develop avoid-and-exit protocols, assess human factors, and integrate remote-sensing information into weather and air traffic control infrastructures. Improved spatial characterization of cloud and precipitation liquid-water content, drop-size spectra, and temperature are needed, as well as an algorithm to convert sensed conditions into a measure of icing potential. Technology development also requires refinement of inversion techniques. These goals can be accomplished with collaboration among federal agencies including NASA, the FAA, the National Center for Atmospheric Research, NOAA, and the Department of Defense. This report reviews operational, meteorological, and technological considerations in developing the capability to remotely map in-flight icing conditions from the ground and from the air.

Ryerson, Charles C.↗

DOE OSTI2020

kasacrcfrcorppiv.c0

Attenuation Corrected reflectivity add to Ka-Band Scanning ARM Cloud Radar (KASACR) CF-Radial PPI scan

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

Validation of CALIPSO Lidar Observations Using Data From the NASA Langley Airborne High Spectral Resolution Lidar

This poster focuses on preliminary comparisons of data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft with data acquired by the NASA Langley Airborne High Spectral Resolution Lidar (HSRL). A series of 20 aircraft validation flights was conducted from 14 June through 27 September 2006, under both day and night lighting conditions and a variety of aerosol and cloud conditions. This poster presents comparisons of CALIOP measurements of attenuated backscatter at 532 and 1064 nm and depolarization at 532 nm with near coincident measurements from the Airborne HSRL as a preliminary assessment of CALIOP calibration accuracy. Note that the CALIOP data presented here are the pre-release version. These data have known artifacts in calibration which have been corrected in the December 8 CALIPSO data release which was not available at the time the comparisons were conducted for this poster. The HSRL data are also preliminary. No artifacts are known to exist; however, refinements in calibration and algorithms are likely to be implemented before validation comparisons are made final.

Hostetler, Chris↗

NASA NTRSDate not supplied

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

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

John Yorks↗

NASA NTRS1999

Global Mapping of Underwater UV Irradiances and DNA-Weighted Exposures using TOMS and SeaWiFS Data Products

The global stratospheric ozone-layer depletion results In an increase in biologically harmful ultraviolet (UV) radiation reaching the surface and penetrating to ecologically significant depths in natural waters. Such an increase can be estimated on a global scale by combining satellite estimates of UV irradiance at the ocean surface from the Total Ozone Mapping Spectrometer (TOMS) satellite instrument with the SeaWIFS satellite ocean-color measurements in the visible spectral region. In this paper we propose a model of seawater optical properties in the UV spectral region based on the Case I water model in the visible range. The inputs to the model are standard monthly SeaWiFS products: chlorophyll concentration and the diffuse attenuation coefficient at 490nm. Penetration of solar UV radiation to different depths in open ocean waters is calculated using the RT (radiative transfer) quasi-single scattering approximation (QSSA). The accuracy of the QSSA approximation in the water is tested using more accurate codes. The sensitivity study of the underwater UV irradiance to atmospheric and oceanic optical properties have shown that the main environmental parameters controlling the absolute levels of the UVB (280-320nm) and DNA-weighted irradiance underwater are: solar-zenith angle, cloud transmittance, water optical properties, and total ozone. Weekly maps of underwater UV irradiance and DNA-weighted exposure are calculated using monthly-mean SeaWiFS chlorophyll and diffuse attenuation coefficient products, daily SeaWiFS cloud fraction data, and the TOMS-derived surface UV irradiance daily maps. The final products include global maps of weekly-average UVB irradiance and DNA-weighted daily exposures at 3m and 10m, and depths where the UVB irradiance and DNA-weighted dose rate at local noon are equal to 10% of their surface values.

Vasilkov, Alexander↗

NASA NTRS2020

The NASA Micro Pulse Lidar Network (MPLNET): Introduction of the New Version 3 Release

The NASA Micro-Pulse Lidar Network (MPLNET) is a global federated network of polarized Micro-Pulse Lidar (MPL) systems running continuously. MPLNET began in 2000, and there have been over 70 sites deployed worldwide, with 24 sites currently active and a few more planned over the next year. Seven of the long-term sites have 10+ years of data, and many more have 5+ years. Most sites are co-located with AERONET providing joint data on column and vertically resolved aerosol and cloud information. This presentation will introduce our new Version 3 MPLNET data. All sites in the network now feature eye-safe polarized backscatter MPL instruments, providing information on attenuated backscatter and particle shape. In addition to change with our signal data, we have an enhanced cloud product suite, a new PBL height product, and inclusion of the new AERONET lunar aerosol optical depth into MPLNET aerosol retrievals. A new quality flag process will be used to better describe all data products. Finally, a new data portal will provide near-real-time (NRT) access to all data products, including new quality assured NRT L1.5 products. Custom products developed for model specific applications will also be provided.

Welton, Ellsworth J.↗

DOE OSTI2023

Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation

Abstract. Atmospheric aerosol has substantial impacts on climate, air quality and biogeochemical cycles, and its concentrations are highly variable in space and time. A key variability to evaluate within models that simulate aerosol is the vertical distribution, which influences atmospheric heating profiles and aerosol–cloud interactions, to help constrain aerosol residence time and to better represent the magnitude of simulated impacts. To ensure a consistent comparison between modeled and observed vertical distribution of aerosol, we implemented an aerosol lidar simulator within the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package version 2 (COSPv2). We assessed the attenuated total backscattered (ATB) signal and the backscatter ratios (SRs) at 532 nm in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1). The simulator performs the computations at the same vertical resolution as the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), making use of aerosol optics from the E3SMv1 model as inputs and assuming that aerosol is uniformly distributed horizontally within each model grid box. The simulator applies a cloud masking and an aerosol detection threshold to obtain the ATB and SR profiles that would be observed above clouds by CALIOP with its aerosol detection capability. Our analysis shows that the aerosol distribution simulated at a seasonal timescale is generally in good agreement with observations. Over the Southern Ocean, however, the model does not produce the SR maximum as observed in the real world. Comparison between clear-sky and all-sky SRs shows little differences, indicating that the cloud screening by potentially incorrect model clouds does not affect the mean aerosol signal averaged over a season. This indicates that the differences between observed and simulated SR values are due not to sampling errors, but to deficiencies in the representation of aerosol in models. Finally, we highlight the need for future applications of lidar observations at multiple wavelengths to provide insights into aerosol properties and distribution and their representation in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

kasacrcfrcorhsrhi.c1

Attenuation Corrected reflectivity add to calibrated Ka-Band Scanning ARM Cloud Radar (KASACR) CF-Radial RHI scan

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2019

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗