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NASA NTRS1994

Aerosol-associated changes in tropical stratospheric ozone following the eruption of Mount Pinatubo

The large amount of sulfuric acid aerosol formed in the stratosphere by conversion of sulfur dioxide emitted by the eruption of Mount Pinatubo (15.14 deg N, 120.35 deg E) in the Philippines around June 15, 1991, has had a pronounced effect on lower stratospheric ozone in the tropics. Measurements of stratospheric ozone in the tropics using electrochemical concentration cell (ECC) sondes before and after the eruption and the airborne UV differential absorption lidar (DIAL) system after the eruption are compared with Stratospheric Aerosol and Gas Experiment II (SAGE II) measurements from several years before the eruption and ECC sonde measurements from the year prior to the eruption to determine the resulting changes. Ozone decreases of up to 33 % compared with SAGE II climatological values were found to be directly correlated with altitude regions of enhanced aerosol loading in the 16- to 28-km range. A maximum partial-column decrease of 29 +/- Dobson units (DU) was found over the 16- to 28-km range in September 1991 along with small increases (to 5.9 +/- 2 DU) from 28 to 31.5 km. A large decrease of ozone was also found at 4 deg to 8 deg S from May to August 1992, with a maximum decrease of 33 +/- 7 DU found above Brazzaville in July. Aerosol data form the visible channel of the advanced very high resolution radiometer (AVHRR) and the visible wavelength of the UV DIAL system were used to examine the relationship between aerosol (surface area) densities and ozone changes. The tropical stratospheric ozone changes we observed in 1991 and 1992 are likely be explained by a combination of dynamical (vertical transport) perturbations, radiative perturbations on ozone photochemistry, and heterogeneous chemistry.

Grant, William B.↗

NASA NTRS2003

Atmospheric Measurements by the Geoscience Laser Altimeter System: Initial Results

The Geoscience Laser Altimeter System launched in early 2003 is the first satellite instrument in space to globally observe the distribution of clouds and aerosol through laser remote sensing. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data is expected to significantly enhance knowledge in several areas of atmospheric science, in particular the distribution, transport and influence of atmospheric aerosol. Measurements of the coverage and height of polar and cirrus cloud should be significantly more accurate than previous global measurement. Initial result from the first several months of operation will be presented.

Spinhirne, J. D.↗

NASA NTRS2003

Aerosol Measurements by the GLAS Space Borne Lidar

Beginning in February 2003, the Geoscience Laser Altimeter System (GLAS) provides global coverage lidar measurement of the height distribution of aerosol in the atmosphere. The characteristic and value of the unique data will be presented. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data is expected to significantly enhance knowledge of the distribution, transport and influence of atmospheric aerosol and thin clouds. Initial results from the 1064 nm channel show strong aerosol loading in many regions of the world. From the initial performance and verification experiments, aerosol backscatter cross sections down to sever times 10(exp -6)I/m-sr are detected. In August the 532 nm channel will also provide aerosol profiles but with a projected order of magnitude more sensitivity, and full data products including aerosol optical depths will be generated. Results from these first several months of operation will be presented.

Spinhirne, James D.↗

NASA NTRS2003

Space Borne Cloud and Aerosol Measurements by the Geoscience Laser Altimeter System: Initial Results

In January 2003 the Geoscience Laser Altimeter System (GLAS) was successfully launched into orbit. Beginning in March 2003 GLAS will provide global coverage lidar measurement of the height distribution of clouds and aerosol in the atmosphere for up to five years. The characteristic and value of the unique data will be presented. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data is expected to significantly enhance knowledge in several areas of atmospheric science, in particular the distribution, transport and influence of atmospheric aerosol and thin clouds. Measurements of the coverage and height of polar and cirrus cloud should be significantly more accurate than previous global observations. In March and April 2003, airborne and ground based data verification experiments will be carried out. Initial results from the verification experiments and the first several months of operation will be presented.

Spinhirne, James D.↗

NASA NTRS2009

The Effects of Synthetic and Enhanced Vision Technologies for Lunar Landings

Eight pilots participated as test subjects in a fixed-based simulation experiment to evaluate advanced vision display technologies such as Enhanced Vision (EV) and Synthetic Vision (SV) for providing terrain imagery on flight displays in a Lunar Lander Vehicle. Subjects were asked to fly 20 approaches to the Apollo 15 lunar landing site with four different display concepts - Baseline (symbology only with no terrain imagery), EV only (terrain imagery from Forward Looking Infra Red, or FLIR, and LIght Detection and Ranging, or LIDAR, sensors), SV only (terrain imagery from onboard database), and Fused EV and SV concepts. As expected, manual landing performance was excellent (within a meter of landing site center) and not affected by the inclusion of EV or SV terrain imagery on the Lunar Lander flight displays. Subjective ratings revealed significant situation awareness improvements with the concepts employing EV and/or SV terrain imagery compared to the Baseline condition that had no terrain imagery. In addition, display concepts employing EV imagery (compared to the SV and Baseline concepts which had none) were significantly better for pilot detection of intentional but unannounced navigation failures since this imagery provided an intuitive and obvious visual methodology to monitor the validity of the navigation solution.

Kramer, Lynda J.↗

NASA NTRS2020

NASA’s High-Resolution GEOS Forecasting and Reanalysis Products: Impact of Stratospheric Intrusions on Surface Ozone Air Quality

A new approach to the study of stratospheric intrusions (SIs)? the introduction of ozone-rich lower stratospheric air into the troposphere ? uses NASA's Goddard Earth Observing System Model (GEOS) model and assimilation products with an objective feature tracking algorithm to investigate the atmospheric dynamics in the UTLS region that generate SIs and the different mechanisms through which SIs may influence tropospheric chemistry and surface air quality. In particular, SIs have been linked with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime. However, the impact of SIs in the remaining seasons and over the rest of the USA is less clear. Improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of SI events. While the spring over the western USA does exhibit the largest number of SIs affecting the lower troposphere, we demonstrate that the number of intrusions in the remaining seasons and over the eastern USA is sizable. Using a multitude of observational datasets, including lidar data, ozonesondes and air quality monitoring surface sites, in combination with GEOS forecast and reanalysis products, the transport of ozone from the stratosphere toward the surface is assessed. By focusing on recent reports of high ozone at monitoring station sites likely associated with SIs, we aim to provide the public with tools which are available in near-real time to enhance their capability to identify the impact of stratospheric air on surface ozone concentrations separate from anthropogenic sources.

Knowland, K. Emma↗

NASA NTRSDate not supplied

Extending CF Conventions to Enhance Data FAIRness for Atmospheric Composition Observations

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global, group, or variable attributes and are popular with the modeling community. HDF and NetCDF files are widely used with atmospheric remote sensing data and have been used to support measurements from numerous field campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of their metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. Recently, the Measurements of Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a CF-based template for the HDF and NetCDF files for field studies, with the aim of making the data products more interoperable and usable. This template seeks to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. The template would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. The draft template has been applied to recent field studies for various instruments and their merge files in support of the Atmosphere Observing System (AOS) project. The details of the revised template are to be presented, as well as examples of the implementation of these requirements for merge files and lidar observation data files and issues revealed during the implementation process.

Sean Leavor↗

NASA NTRS2018

CALIPSO Lidar Calibration at 532 nm: Version 4 Nighttime Algorithm

Data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP’s other radiometric calibration procedures – i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime – depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30-34 km to 36-39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. As well, an enhanced strategy for filtering the radiation-induced noise from high energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved MERRA-2 model. An aerosol scattering ratio of 1.01 ± 0.01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2-3% lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne high spectral resolution lidar (HSRL) are reduced from 3.6% ± 2.2% in the version 3 data set to 1.6% ± 2.4 % in the version 4 release.

Jayanta Kar↗

DOE OSTI2026

IPC-Fusion (Infrastructure Perception and Control (IPC): Multisensor Data Fusion Software) [SWR-25-153]

As part of the National Laboratory of the Rockies' (NLR’s) Infrastructure Perception and Control Laboratory, the IPC-Fusion toolkit provides a probabilistic, scalable, multi-sensor fusion framework that integrates (late-stage fusion) heterogeneous object detection data from traffic sensors to enable robust, real-time tracking of roadway occupants. The algorithmic design of the toolkit is motivated by the need for creating a digital twin of traffic at the edge in a scalable and affordable manner. The software operates by combining object-level measurements (such as position and velocity) from a suite of sensors (such as radar, lidar, camera) using Kalman filtering and probabilistic data association techniques to overcome individual sensor limitations and achieve superior tracking performance in complex traffic zones. The framework addresses key challenges including heterogeneous measurement uncertainties, asynchronous data streams, varying spatiotemporal data resolutions, robust data association, and adaptive object lifecycle management. Validated on real-world traffic intersection data including vehicles and pedestrians, IPC-Fusion demonstrates enhanced tracking reliability across scenarios involving occlusions, sensor failures, and varying traffic densities, supporting the broader IPC initiative's goal of transforming transportation infrastructure through advanced perception capabilities for intelligent transportation systems, traffic safety applications, and autonomous vehicle support.

Sandhu, Rimple [National Laboratory of the Rockies↗

NASA NTRS2005

Impact of CAMEX-4 Data Sets for Hurricane Forecasts using a Global Model

This study explores the impact on hurricane data assimilation and forecasts from the use of dropsondes and remote-sensed moisture profiles from the airborne Lidar Atmospheric Sensing Experiment (LASE) system. We show that the use of these additional data sets, above those from the conventional world weather watch, has a positive impact on hurricane predictions. The forecast tracks and intensity from the experiments show a marked improvement compared to the control experiment where such data sets were excluded. A study of the moisture budget in these hurricanes showed enhanced evaporation and precipitation over the storm area. This resulted in these data sets making a large impact on the estimate of mass convergence and moisture fluxes, which were much smaller in the control runs. Overall this study points to the importance of high vertical resolution humidity data sets for improved model results. We note that the forecast impact from the moisture profiling data sets for some of the storms is even larger than the impact from the use of dropwindsonde based winds.

Kamineni, Rupa↗

NASA NTRS2010

LASE Observations of Interactions Between African Easterly Waves and the Saharan Air Layer

The Lidar Atmospheric Sensing Experiment (LASE) participated in the NASA African Monsoon Multidisciplinary Analyses (NAMMA) field experiment in 2006 that was conducted from Sal, Cape Verde to study the Saharan Air Layer (SAL) and its influence on the African Easterly Waves (AEWs) and Tropical Cyclones (TCs). During NAMMA, LASE collected simultaneous water vapor and aerosol lidar measurements from 14 flights onboard the NASA DC- 8. In this paper we present three examples of the interaction of the SAL and AEWs regarding: moistening of the SAL and transfer of latent heat; injection of dust in an updraft; and influence of dry air intrusion on an AEW. A brief discussion is also given on activities related to the refurbishment of LASE to enhance its operational performance and plans to participate in the next NASA hurricane field experiment in the summer of 2010.

Ismail, Syed↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33993-DND

Large volcanic eruptions are the primary sources of aerosols in the stratosphere and play an important role in the global climate system. The transformation of sulfur dioxide emitted by volcanoes into sulfuric acid droplets leads to a global cooling effect at the surface by enhanced reflection of solar radiation to space and reduced the earth's radiative budget for months to years. In June 2019, the Raikoke volcano, Kuril Islands (153.24167 E, 48.29167 N) emitted 1.4 Tg of SO2 between June 21st and 22nd with plume injection height between 7 and 15 km based on several ultra-violet and infrared sensors as well as the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) space-based lidar. CALIPSO and the NASA Langley Trajectory Model (LaTM) with GEOS5 meteorological data are used to track dispersed volcanic ash plumes. The trajectory mapping technique will be used to re-construct the 3-dimension structure of volcanic ash and sulfate. Results will be compared with independent observations from the Stratospheric Aerosol and Gas Experiment and GEOS-Chem model outputs to understand the transport of the plume into the stratosphere and its lifetime.

Hyundeok Choi↗

NASA NTRS2012

Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4: Potential for Enhancing Nocturnal Ice Cloud Retrievals

Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 microns can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses tau < approx.6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of tau and ice particle size D(sub e) to optically thick clouds. Measurements from the Moderate Resolution Imaging Spectroradiometer Airborne Simulator--ASTER, the Scanning High-resolution Interferometer Sounder, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval capabilities of infrared radiances over optically thick ice clouds. Simulations based on coincident in-situ measurements and combined cloud tau from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to tau up to approx.20 and that for ice clouds having tau > 20, the 3.7 - 10.8 microns and 3.7 - 6.7 microns BTDs are the most sensitive to D(sub e). Satellite imagery appears consistent with these results. Keywords: clouds; optical depth; particle size; satellite; TC4; multispectral thermal infrared

Minnis, Patrick↗

NASA NTRS2012

Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4- Potential for Enhancing Nocturnal Ice Cloud Retrievals

CRS and CPL↗

NASA NTRS2016

Using High-Resolution Airborne Remote Sensing to Study Aerosol Near Clouds

The horizontal space in between clear and cloudy air is very complex. This so-called twilight zone includes activated aerosols that are not quite clouds, thin cloud fragments that are not easily observable, and dying clouds that have not quite disappeared. This is a huge challenge for satellite remote sensing, specifically for retrieval of aerosol properties. Identifying what is cloud versus what is not cloud is critically important for attributing radiative effects and forcings to aerosols. At the same time, the radiative interactions between clouds and the surrounding media (molecules, surface and aerosols themselves) will contaminate retrieval of aerosol properties, even in clear skies. Most studies on aerosol cloud interactions are relevant to moderate resolution imagery (e.g. 500 m) from sensors such as MODIS. Since standard aerosol retrieval algorithms tend to keep a distance (e.g. 1 km) from the nearest detected cloud, it is impossible to evaluate what happens closer to the cloud. During Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), the NASA ER-2 flew with the enhanced MODIS Airborne Simulator (eMAS), providing MODIS-like spectral observations at high (50 m) spatial resolution. We have applied MODIS-like aerosol retrieval for the eMAS data, providing new detail to characterization of aerosol near clouds. Interpretation and evaluation of these eMAS aerosol retrievals is aided by independent MODIS-like cloud retrievals, as well as profiles from the co-flying Cloud Physics Lidar (CPL). Understanding aerosolcloud retrieval at high resolution will lead to better characterization and interpretation of long-term, global products from lower resolution (e.g.MODIS) satellite retrievals.

aerosols near clouds↗

NASA NTRSDate not supplied

The TOLNet 2.0 Website: How an API Can Promote Open Science and FAIR Principles

The Tropospheric Ozone Lidar Network (TOLNet) has generated over a decade of ozone vertical profile data products over North America. The science value of the TOLNet data has been demonstrated in numerous peer-reviewed publications on air quality and other ozone relevant research. To support the broad spectrum of data use, the TOLNet team launched a major effort to upgrade the web-based data repository aiming to enhance the data discoverability and to enable machine-to-machine data upload and download processes. Specifically, the TOLNet website included an application programming interface (API), which supports machine-to-machine data search and data download. The API also extracts selected variables from the files, which can be retrieved as JSON objects and used to create data displays without having to download or open the underlying files. The TOLNet science team members can also use the API for automated data upload, including a data file scanning feature to ensure data product integrity. To be presented will include a summary of key features of data repositories, an actual use case of machine-to-machine data access/use, as well as our journey to make TOLNet data more FAIR, i.e., more findable, accessible, interoperable, and (re)usable.

Crystal Gummo↗

DOE OSTI2024

Deep-Learning-derived Boundary Layer Height from Meteorological Data over the SGP, GOAMAZON, CACTI

The planetary boundary-layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, designed to estimate PBLH by integrating morning temperature profiles with surface meteorological observations. The DNN model is developed by leveraging a rich data set of PBLH derived from long-standing radiosonde records and augmented with high-resolution micropulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of 10 members, each featuring distinct hidden layer structures, which collectively yield a robust 27-year PBLH data set over the Southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote-sensing methodologies, including Doppler lidar, ceilometer, Raman lidar, and micropulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote-sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (tropical rainforest) and CACTI (middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary-layer dynamics with implications for enhancing the representation of PBL in weather forecasting and climate modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Determination of Ground Subsidence Around Snow Fences in the Arctic Region

In this study, we analyzed the effects of snow cover changes caused by snow fences (SFs) installed in 2017 in the Alaskan tundra to examine ground subsidence. Digital surface model data obtained through LiDAR-based remote sensing in 2019 and 2022, combined with a field survey in 2021, revealed approximately 0.2 m of ground subsidence around the SF. To investigate the relationship between SF-induced snow cover changes and ground subsidence, geophysical methods, electrical resistivity tomography (ERT) and ground-penetrating radar (GPR), were applied in 2023 to analyze subsurface characteristics. The increased snow cover due to the SF-enhanced insulation, delaying the penetration of winter cold into the subsurface. This delay caused subsurface temperatures to decrease more slowly, melting the upper permafrost and increasing the thickness of the active layer. ERT and GPR surveys well delineated the boundary between the active layer and permafrost, confirming that the increased snow cover thickened the active layer. This thickening led to the melting of pore ice, causing water runoff and ground compaction, which resulted in subsidence. The runoff also formed channels flowing eastward over the SF. This study highlights how changes in snow cover can influence active layer properties, leading to localized environmental changes and ground subsidence.

54 ENVIRONMENTAL SCIENCES↗