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At least 1,495 records · Page 83

Updated Stagnation-Point Aeroheating Correlations for Mars Entry

The objective of this work was to develop new stagnation-point aeroheating engineering correlations for Mars entry vehicles. New convective and radiative heating relations were formulated over a wide range of entry conditions. These relations were based on computational fluid dynamics simulations informed by recent experimental testing and modeling enhancements. For convective heating, a relation similar to the Sutton-Graves relation was developed that is accurate to within ±25% across the domain of relevant Mars entry conditions. For radiative heating, two different functional forms were developed: exponential and polynomial relations. Each of these relation, which represents two different levels of complexity for implementation, were able to predict the radiative heating within about ±25%. The correlations were tested by applying them to the Mars Pathfinder entry trajectory to demonstrate their applicability. These new correlations are significant improvement over existing relations in terms of the accuracy, domain of applicability, and the captured physics, including CO2 inferred radiation and thermochemical nonequilibrium.

Thomas K West, IV↗

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↗

TPSAS-NF1676L-34528-DND

Since 2006, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, has provided a unique vertical perspective of Earth's atmosphere. These measurements have furthered our understanding of the role aerosols and clouds play in the climate system and have been leveraged for atmospheric modeling and air quality studies. In this seminar, the basics of LIDAR remote sensing will first be presented, including its operating principles, setup and geometry, the LIDAR equation, and different LIDAR types and techniques. Next, an overview of the LIDAR systems at NASA Langley Research Center will be provided, with an emphasis on the CALIPSO satellite mission, including available data products and examples of browse images. Lastly, several CALIPSO-based science applications and research projects will be discussed, including cloud contamination in passive satellite aerosol retrievals, aerosol detection limits, trends in aerosol vertical distribution, and air quality (PM2.5 concentrations).

Travis Toth↗

TPSAS-NF1676L-34683-DND

The lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, makes robust measurements of dust and has generated a length of record that is significant both seasonally and inter-annually. We exploit this record to determine a multi-year climatology of the properties of Middle Eastern dust in the vicinity of Kuwait City. In particular seasonal optical depths of dust gridded in accordance with the Level 3 data products protocol between 2006 and 2015. The data are screened using standard CALIPSO quality assurance flags, cloud aerosol discrimination (CAD) scores, overlying features and layer properties. CALIPSO is collaboration between NASA and Centre National d’Études Spatiales (CNES), was launched in April 2006 to provide vertically resolved measurements of cloud and aerosol distributions. The primary instrument on the CALIPSO satellite is the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a near-nadir viewing two-wavelength polarization-sensitive instrument. In addition to CALIPSO, we use the AErosol RObotic NETwork (AERONET) sites in the region to identify extreme dust events such as Sand and Dust Storms (SDS). The lidar measurements of the vertical location of the layers along with predominant prevailing wind vectors will enable identification of dust sources and inform mitigation solutions for extreme SDS.

Ali H Omar↗

TPSAS-NF1676L-32014-DND

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), on-board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) is a satellite-borne polarization sensitive lidar. It has been providing the vertical distributions of clouds and aerosols along with their microphysical and optical properties since 2006. One of its important Level 2 products, feature classification, has been determined using the lidar information from 532 nm parallel and perpendicular channels, and 1064 nm channel measurements of layer integrated backscatter. Deep machine learning methods which combine both the channel and texture information to recognize feature patterns is uniquely beneficial when applied to this data. In this study, we will use Convolutional Neural Network (CNN), a deep machine learning method, to classify lidar aerosol subtypes by using the lidar profile observations. This method uses additional information from the vertical texture of the feature instead of using only the layer information. Note that in the integrated layer properties, the texture information has been masked due to averaging. Our results will show how the texture information plays a role in the classification. This preliminary work explores the benefits and potential of deep machine learning methods for lidar retrievals and focuses on the aerosol subtype classification. The broader application extends to the classification of other feature types. Future applications include the developing deep machine learning methods with neural networks to retrieve properties of the features, and studies of indirect effect of cloud-aerosol interaction from lidar measurements.

Shan Zeng Kowalski↗

TPSAS-NF1676L-17243-DND

This presentation captures ERA Project's effort in using integrated cost-schedule-risk analysis tool, identifying and capturing explicit relationships between program funds, schedule, and discrete risks. The project team merged a myriad of cost and schedule data for timely, objective, uncertainty analysis of the ITD's budget and schedule. The project team conducted detailed schedule uncertainty analysis showing schedule activities and how their interrelationships were impacted, representing an impressive advance beyond routine Gantt charts. Furthermore, the ERA Project collected discrete risk events including their impacts to costs and/or schedule and interwove these risks into cost and schedule logic networks, providing the foundation to conduct cost and schedule analyses. The team integrated this data into the analysis model, providing probabilistic results that were then used by the ERA Project's senior management for decision-making purposes. The ERA Project management team, through technical and pathfinder expertise in integrating cost, schedule, risk, and technical content, consistently provided risk-informed recommendations to Implementing Centers and ISRP senior management which ultimately ensured the successful ARMD Key Decision Point (KDP) review of the ERA Phase 2 ITD Portfolio and increased the likelihood of achieving technical objectives within cost and schedule constraints.

Gaudy M Bezos-O'Connor↗

TPSAS-NF1676L-20076-DND

Polar stratospheric clouds (PSCs) play a crucial role in the springtime chemical depletion of ozone at high latitudes. PSC particles (primarily supercooled ternary solution, or STS droplets) provide sites for heterogeneous chemical reactions that transform stable chlorine and bromine reservoir species into highly reactive ozone-destructive forms. Furthermore, large nitric acid trihydrate (NAT) PSC particles can irreversibly redistribute odd nitrogen through gravitational sedimentation (a process commonly known as denitrification), which prolongs the ozone depletion process by slowing the reformation of the stable chlorine reservoirs. Spaceborne observations from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite are providing a rich new dataset for studying PSCs. CALIPSO is an excellent platform for studying polar processes with CALIOP acquiring, on average, over 300,000 backscatter profiles daily at latitudes between 55o and 82o in both hemispheres. PSCs are detected in the CALIOP backscatter profiles using a successive horizontal averaging scheme that enables detection of strongly scattering PSCs (e.g., ice) at the finest possible spatial resolution (5 km), while enhancing the detection of very tenuous PSCs (e.g., low number density NAT) at larger spatial scales (up to 135 km). CALIOP PSCs are separated into composition classes (STS; liquid/NAT mixtures; and ice) based on the ensemble 532-nm scattering ratio (the ratio of total-to-molecular backscatter) and 532-nm particulate depolarization ratio (which is sensitive to the presence of non-spherical, i.e. NAT and ice particles). In this paper, we will provide an overview of the CALIOP PSC detection and composition classification algorithm and then examine the vertical and spatial distribution of PSCs in the Arctic and Antarctic on vortex-wide scales for entire PSC seasons over the more than eight-year data record.

Michael C Pitts↗

A Synopsis of the 8+ Year CALIOP Polar Stratospheric Cloud Data Record

Polar stratospheric clouds (PSCs) play a crucial role in the springtime chemical depletion of ozone at high latitudes. PSC particles (primarily supercooled ternary solution, or STS droplets) provide sites for heterogeneous chemical reactions that transform stable chlorine and bromine reservoir species into highly reactive ozone-destructive forms. Furthermore, large nitric acid trihydrate (NAT) PSC particles can irreversibly redistribute odd nitrogen through gravitational sedimentation (a process commonly known as denitrification), which prolongs the ozone depletion process by slowing the reformation of the stable chlorine reservoirs. Spaceborne observations from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite are providing a rich new dataset for studying PSCs. CALIPSO is an excellent platform for studying polar processes with CALIOP acquiring, on average, over 300,000 backscatter profiles daily at latitudes between 55o and 82o in both hemispheres. PSCs are detected in the CALIOP backscatter profiles using a successive horizontal averaging scheme that enables detection of strongly scattering PSCs (e.g., ice) at the finest possible spatial resolution (5 km), while enhancing the detection of very tenuous PSCs (e.g., low number density NAT) at larger spatial scales (up to 135 km). CALIOP PSCs are separated into composition classes (STS; liquid/NAT mixtures; and ice) based on the ensemble 532-nm scattering ratio (the ratio of total-to-molecular backscatter) and 532-nm particulate depolarization ratio (which is sensitive to the presence of non-spherical, i.e. NAT and ice particles). In this paper, we will provide an overview of the CALIOP PSC detection and composition classification algorithm and then examine the vertical and spatial distribution of PSCs in the Arctic and Antarctic on vortex-wide scales for entire PSC seasons over the more than eight-year data record.

Michael C Pitts↗

TPSAS-NF1676L-26925-DND

Observationally-based atmospheric energy balance is analyzed using Clouds and the Earth's Radiant Energy System (CERES)-derived TOA and surface irradiance, Global Precipitation Climatology Project (GPCP)-derived precipitation, dry static and kinetic energy tendency and divergence estimated from ERA-Interim, and surface sensible heat flux from SeaFlux. The residual tends to be negative over tropics and positive over mid-latitudes. A negative residual implies that precipitation rate is too small, divergence is too large, or radiative cooling is too large. The residual of atmospheric energy is spatially and temporally correlated with cloud objects to identify cloud types associated with the residual. Spatially, shallow cumulus, cirrostratus, and deep convective cloud object occurrence are positively correlated with the absolute value of the residual. The temporal correlation coefficient between the number of deep convective cloud objects and individual energy components, net atmospheric irradiance, precipitation rate, and the sum of dry static and kinetic energy divergence and their tendency over western Pacific are, respectively, 0.84, 0.95, and 0.93. However, when all energy components are added, the atmospheric energy residual over tropical Pacific temporally correlates well with the number of shallow cumulus cloud objects over tropical Pacific. Because shallow cumulus does not alter enough atmospheric energy compared to the residual, these suggest 1) if retrieval errors associated with deep convective clouds are causing the column integrated atmospheric energy residual, the errors vary among individual deep convective clouds, 2) it is possible that the residual is associated with processes in which shallow cumulus clouds affect deep convective clouds and hence atmospheric energy budget over tropical western Pacific, and 3) it is also possible that cumulus congestus present cirrostratus that missed in massive sensor retrieval contribute the residual. Cloud objects used in the study that leads to the above conclusions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS). In this investigation, we use Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat data to evaluate and verify above findings. Specifically, we focus on 3) above and analyze frequency of occurrence of cumulus congestus present under cirrostratus and correlation to the energy balance residual.

Seiji Kato↗

TPSAS-NF1676L-26965-DND

A comprehensive understanding of the spatial and temporal distributions of clouds on a global scale can be best achieved when the vertical distributions and multi-layer occurrence frequencies obtained from active remote sensors are fully integrated with the horizontal distributions currently provided by passive sensors. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft was specially designed to acquire aerosol and cloud profiles with unprecedented high vertical resolution and accuracy. As a part of the A-Train satellite constellation, CALIPSO has been operating routinely for more than 10 years and continues to provide a wealth of cloud observations to describe the mean state and inter-annual variability. Recently a suite of level 3 (L3) cloud products has been under development by the CALIPSO lidar science working group at the NASA Langley Research Center. These products describe 3-dimensional (3D) cloud occurrence and 3D ice cloud extinction coefficients and ice water content. Future evolution of the products will add observations from the Imaging Infrared Radiometer onboard CALIPSO. Here we present a brief introduction and provide results from a product prototype. We will characterize the inter-annual vertical variability of zonal cloud occurrence and ice water content during the last 10 years. Suggestions and comments are welcome to help us design and provide better cloud climatology products using CALIOP observations for our cloud community.

Xia Cai↗

TPSAS-NF1676L-29044-DND

In Langley NASA, Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. The capability of viewing C3M product on browsers will be available on CERES ordering tool web site in the future, https://ceres.larc.nasa.gov

David R Doelling↗

Using Open Innovation in Reducing Risk to Crews

In the exploration of destinations outside of Earth's neighborhood, specifically Mars, scientific and engineering inquiries have occurred by two means; observations from satellites and observations by landed spacecraft. Satellite observations (Mariner, MRO, Mars Odyssey, provide global-scale spatial and temporal data while landed spacecraft (Viking, Mars Pathfinder, Spirit, Opportunity, Phoenix Mars Lander) investigate highly localized areas of the surface of the planet. In preparation for human exploration, extensive knowledge of the surface and atmospheric environments should be known before the first human leaves Earth. The primary goal of performing reconnaissance on Mars on a sub-global scale is to know as much as possible about the environment to which crews will be subjected. At the current rate of launching and landing probes to Mars, it will take a very long time to understand the surface and atmospheric conditions associated with the regions where prospective crews may land. Meanwhile electronics and electrical systems are rapidly getting smaller. One can argue that to acquire the knowledge of the region, one must take hundreds, maybe thousands of measurements simultaneously. One means to perform such a task is to deploy a swarm of sensors. Such a swarm would perform an in-situ assessment of the region. Imagine a close flyby mission to Mars for example, where mini- to micro-sensors are deposited into the atmosphere over half an orbit or more. The sensors, captured by the atmospheric drag and Martian gravity slowly descend buffeted about by Martian winds and weather until they settle on the surface a great time later (think of how long dust takes to settle). As they descend they communicate a vast array of data; temperature, chemistry, pressure, radiation dose, electric or magnetic properties from a region of the planet and an individual sensor need not measure the same quantity as its neighbors. Initially, they could move at the whim of the environment but later versions could have locomotion or propulsion mechanisms. Humans wouldn't need to decide where the sensors go, the sensors do that for themselves. This is a key strength of a sensor swarm. The intelligence relies on the group not on a decision maker on earth. Real time sensor inputs direct what the swarm considers most interesting to investigate resulting in emergent behavior. We issued a $20,000 challenge to the global innovators to provide solutions as to how such a swarm could be initialized and by what protocols and methodologies by which they operate. Over 400 innovators from 49 countries took a look at the problem, with three receiving partial awards for solutions.

Mel Ferebee↗

Advancing Open Science Through Innovative Data System Solutions: The Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)'s Data Ecosystem

Collaborative open science practices are changing the way research is conducted. These changes affect how scientists work together on data, code and information. Data systems enhance open science by offering forward thinking technological solutions, such as providing data and computation on the cloud, to enable collaboration, sharing and analysis. In this paper, we present our vision for a conceptual data system on the cloud that enables open science. We also present our work on the Multi-Mission Algorithm and Analysis Platform (MAAP)which has served as a pathfinder data system for this conceptual approach.

Kaylin Bugbee↗

Compass Final Report: Venus Bridge Orbiter and Surface Study (V-BOSS)

The Venus Bridge Orbiter and Surface Study (V-BOSS) Compass concurrent engineering design team study shows that new, high-priority Venus science can be achieved using a linked Orbiter + Surface Element (Lander) mission concept within a $200M cost cap with assumptions. This is feasible through optimizing investment in early technologies and platforms, such as the Long-Lived In-Situ Solar System Explorer (LLISSE), leveraging known and flight-ready technology, and the overall use of simple, small, robust systems in innovative approaches to Venus exploration. This architecture allows a range of science investigations through modification of Orbiter-Lander platforms in this study through choice of other instruments (often sensors), science themes, or operational modes. In particular, a fundamental strength of this approach is to provide science not available in other ways by using simplified architectures including rugged systems operable in-situ on the Venus surface. Such investigations would be pathfinders for more complex, and more expensive, future missions. Additionally, the results of this study can be used to further champion the need, value and return of early investment technology programs for the hard problem of in-situ investigations at Venus.

Venus Bridge↗

The Origins Space Telescope Integration and Testing

This paper describes the plans, flows, key facilities, test beds, pathfinders, simulators and ground support equipment that could be used to fully integrate, functionally test and qualify the Origins Space Telescope (Origins). The Origins Observatory consists of the Spacecraft Bus Module (SBM) and the Cryogenic Payload Module (CPM), which comprises the telescope and three science instruments. The telescope is a Three Mirror Anastigmat (TMA) and is composed of four mirrors: three with optical power (the elliptical primary, hyperbolic secondary, and elliptical tertiary mirrors) and a flat field-steering mirror (FSM). The three science instruments spanning the wavelength range 2.8 to 588 μm provide the powerful new spectroscopic and imaging capabilities required to achieve the scientific objectives. The Origins Survey Spectrometer (OSS) uses six gratings in parallel to take multi-beam spectra simultaneously across the 25 to 588 μm window through long slits enabling deep 3D extra-galactic surveys. The Far-IR Imager/Polarimeter (FIP) provides imaging and polarimetric measurement capabilities at 50 and 250 μm. Its fast mapping enables rapid follow-up of transient or variable sources and efficient monitoring campaigns. The Mid-Infrared Spectrometer (MISC-T) provides spectroscopy simultaneously over 2.8 to 20 μm with exquisite stability and precision (<5 ppm between 2.8 to 10 μm, <20 ppm between 11 to 20 μm). All the instruments are delivered for Integration and Test fully qualified and calibrated. The Integration and Test program implemented at each level of assembly is discussed as well as the separation of thermal vacuum testing between the hot and cold zones of the Observatory. Portions of this manuscript appear in the Origins Study Final Report.

Origins↗

Exo-C: A Dedicated Probe-scale Space Mission for Coronagraphic Imaging and Spectroscopy of Exoplanetary Systems

"Exo-C", the Exoplanet Coronagraph, is a concept for a dedicated probe-scale (< $1B) space mission optimized for direct imaging of exoplanetary systems. It was the product of a detailed mission study carried in 2013-2015 under the sponsorship of the NASA Astrophysics Division. Exo-C was designed to be capable of spectrally characterizing 1-2 dozen nearby exoplanets in reflected visible light, discovering previously undetected planets, and imaging structure in hundreds of circumstellar disks. It would obtain unique science results on planets down to super-Earth size and serve as a technology pathfinder toward an eventual flagship-class mission to find and characterize habitable Earth-like exoplanets. Key design elements are an unobscured telescope aperture, an internal coronagraph with deformable mirrors for precise wavefront control, and an orbit and observatory design chosen for high thermal stability. ExoC’s telescope aperture, orbit, mission lifetime, and spacecraft bus are all comparable to those of the highly successful Kepler mission. Much of the needed technology development (precision pointing, wavefront sensing and correction, high contrast integral field spectroscopy, detector flight readiness) has been advanced by the WFIRST Coronagraph Instrument (CGI) project over the past several years. Mission performance, mass, power, and cost estimates have also benefited from detailed work by the WFIRST CGI team. A Cost and Technical Evaluation (CATE) was performed in 2015 by the Aerospace Corporation. Today Exo-C is a backup option to WFIRST CGI. It could nominally be implemented within seven years from project start. This white paper summarizes the study final report, with updates on performance and technical readiness as of spring 2019.

Karl R. Stapelfeldt↗

Solar Cruiser Technology Maturation Plans

The NASA Marshall Space Flight Center (MSFC) developed the Solar Cruiser mission concept to mature solar sail technology for use in future Heliophysics missions, as well as missions of interest across a broad user community (e.g., space weather and Earth polar observatories). Solar Cruiser will serve as a pathfinder for missions that observe the solar environment from unique vantage points such as a high inclination solar mission opening a fundamentally new range of observational capabilities for the Heliophysics Program and for space weather monitoring. Sustained observations away from the Sun-Earth line (SEL) present unique opportunities for answering the outstanding science questions of Heliophysics, improving space-weather monitoring and prediction, and revealing new information about our Sun and solar system. Propellantless solar sails can be used to create artificial equilibria and maintain indefinite station-keeping at locations sunward of L1 along the SEL, or at any desired offset from the SEL leading or trailing the Earth in its orbit. They can change the heliocentric inclination of a spacecraft from the ecliptic to as high as solar polar, stopping and remaining at any intermediate inclination orbit in between. Sails can be used to hover over the Earth’s poles, using solar photon pressure to offset the Earth’s gravitational attraction, creating functional equivalents of geostationary earth orbits. The Solar Cruiser mission would fly a small spacecraft with a large (>1,600 square meter) solar sail containing embedded reflectivity control devices (RCDs) and photovoltaic cells. The mission concept includes successful deployment of the solar sail, validation of all sail subsystems, controlled station-keeping inside of the Sun-Earth L1 point, attitude control of the sail with the RCDs (including spinning and de-spinning), demonstration of pointing performance for science imaging, and an increase in heliocentric inclination (out of the ecliptic). To demonstrate the requisite sail technology, the Solar Cruiser project will design, fabricate, deploy, and fly the Solar Sail Propulsion Element (SSPE). The SSPE incorporates the following three systems: • The Solar Sail System (SSS) provides the large propulsive surface required for acceleration and smaller reflectivity-changing surfaces for roll control. • The Active Mass Translator System (AMT) provides SSPE motion with respect to the sailcraft bus for pitch and yaw control. • The Solar Sail Attitude Determination and Control System (SSADCS) consists of embedded software to 1) provide autonomous sailcraft attitude estimation, attitude pointing control, and reaction wheel momentum management following sail deployment and 2) execute the uplinked inertial attitude pointing commands to maintain the desired sailcraft trajectory. The plans for maturing each of these technology systems to TRL 5 and beyond are described herein.

Solar Sail↗

Study of Antarctic Blowing Snow Storms Using MODIS and CALIOP Observations With a Machine Learning Model

As a common phenomenon over Antarctica, blowing snow (BLSN), especially the large BLSN storms, play an important role in the Antarctic surface mass balance, radiation budget, and planetary boundary layer processes. This study presents the work on BLSN storm identification and analysis with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. Spectral analysis shows that BLSN identification is feasible with MODIS daytime data. A random forest machine learning model is developed and observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization are used for training. Model performance results show that machine‐learning based classification can achieve over 90% overall accuracy when classifying MODIS pixels into cloud, clear, and BLSN categories. The machine learning model is applied to MODIS observations during the month of October 2009 for BLSN storm analysis. Results show that the size of BLSN storms has a large spectrum and can reach hundreds of thousands km2. The MODIS based BLSN storm frequency map extends the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations coverage limit from 82°S to the South Pole. A BLSN storm belt, which extends from the South Pole region to the coastal area between 130°E and 160°E along the Transantarctic Mountains, provides a potential pathway of snow transport. These results are important in improving the understanding of BLSN impact on Antarctic surface mass balance and boundary layer processes.

Antarctic↗