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Mark Vaughan

Publications and source records attributed to Mark Vaughan.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Tropical Three-dimensional Cloud Climatology during El Niño Events with CALIPSO Level-3 Cloud Products

A previous case study showed opposite cloud anomalies at high, middle and low altitude regions during a weak 2006/2007 El Niño and a moderate 2009/2010 El Niño. In this work, we use CALIPSO Level 3 (L3) Cloud Products to provide a comprehensive picture of cloud anomalies during all recent five El Niño events since 2006, with a particular focus on thin cirrus clouds at high altitudes, which are challenging for passive sensor detection algorithms. Specifically, the vertical cloud anomalies are calculated with the L3 Cloud Occurrence Product, the horizontal cloud anomalies are from the L3 GEWEX product, and the ice cloud extinction profiles and ice water content are obtained from the L3 Ice Cloud product. The cloud anomalies are further analyzed with the magnitude and pattern of sea surface temperature (SST) anomalies. These findings will improve current knowledge of ENSO from a new perspective.

El Nino↗
NASA NTRS2023

Tropical Three-dimensional Cloud Climatology during El Niño Events with CALIPSO Level-3 Cloud Products

The El Niño–Southern Oscillation (ENSO) is a large-scale climatic phenomenon that originates in the tropical Pacific Ocean but affects global climate patterns. Its warm phase El Niño occurs irregularly every two to seven years and peaks in winter. A previous case study showed opposite cloud anomalies at high, middle and low altitude regions during a weak 2006/2007 El Niño and a moderate 2009/2010 El Niño, suggesting a non-linear response of tropical clouds to El Niño sea surface temperature (SST) forcing. To further understand the cloud response to SST, we examine the three-dimensional (3-D) cloud anomalies during all recent five El Niño events since 2006 using level-3 (L3) cloud products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission. During its 17+ years operation, CALIPSO delivered near-global measurements of cloud and aerosol profiles at unprecedented high resolution and sensitivity. In this work, we provide a comprehensive picture of cloud anomalies during El Niño, with a particular focus on thin cirrus clouds at high altitudes, which are challenging for passive sensor detection algorithms. Specifically, the vertical cloud anomalies are calculated with the L3 3-D Cloud Occurrence Product, the horizontal cloud anomalies are from the L3 Global Energy and Water Exchanges (GEWEX) product, and the ice cloud extinction profiles and ice water content are obtained from the L3 Ice Cloud product. These findings will improve current knowledge of ENSO from a new perspective.

El Nino↗
NASA NTRS2023

Cloud - Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) - Data Management System: Data Products Catalog V4.95

The CALIPSO V4.51 Lidar Level 1 and Level 2 data product is an updated version of an already order-able dataset. The changes were signed off by the CALIPSO Configuration Control Board, versioned, and the code uploaded to a code repository. There is no ITAR/SBU data or code associated with this product. Data will be publicly order-able at the NASA LaRC Atmospheric Sciences Data Center (ASDC). All documentation and web sites will be made public once the data product is released. The data is in HDF4 format and will be generated for majority of the mission (June 2006 - August 2023). The attached Data Products Catalog (v4.95) describes the content of these new data products.

Mark Vaughan↗
NASA NTRS2023

Polarization Calibration Using Solar Radiation Background Signal Scattered from Dense Cirrus Clouds in the Visible and Ultraviolet Wavelength Regimes

In this presentation we describe the application of a previously developed technique that is now being used to correct the daytime polarization calibration of the CALIPSO lidar. The technique leverages the fact that the solar radiation background signals from dense cirrus clouds are largely unpolarized due to the internal multiple reflections within the non-spherical ice particles and the multiple scattering that occurs among these particles. Therefore, the ratio of polarization components of the cirrus background signals provides a good estimate for the polarization gain ratio (PGR) of the lidar. Using airborne backscatter lidar measurements, this technique was demonstrated to work well in the infrared regime. However, in the visible and ultraviolet regime, the molecular contribution is too large to be ignored, and thus corrections must be applied to account for the highly polarizing characteristics of the molecular scattering. Ignoring molecular scattering contributions can cause PGR errors of 2-3% at 532 nm, where the CALIPSO lidar makes its depolarization measurement. Because of the wavelength dependence of -4 of the molecular scattering, the PGR error can be even larger at the 355 nm wavelength that will be used by ESA’s EarthCARE lidar. To correct the molecular scattering contributions to the lidar received solar background signal, a look-up table has been created using a polarization-sensitive radiative transfer model. This presentation describes the theory and implementation of the molecular scattering correction.

Zhaoyan Liu↗
NASA NTRS2022

Mitigation Strategies for the Impact of Low Energy Laser Pulses in CALIOP Calibration and Level 2 Retrievals

Since mid-2016, the frequency of low energy laser pulses emitted by the CALIPSO lidar has been slowly increasing due to pressure losses in the canister housing the laser. While originally confined primarily to the South Atlantic Anomaly (SAA) region, these low energy pulses now occur intermittently around the globe. Low energy pulses can cause calibration biases and degrade the science quality of level 2 retrievals. We describe a new low energy mitigation (LEM) algorithm that will be implemented incrementally in future versions of the CALIOP data processing to identify and reject affected profiles during calibration and feature detection. The LEM algorithm effectively eliminates low energy calibration biases, improves level 2 retrievals, and minimizes level 2 data loss.

Jason Tackett↗
NASA NTRS2022

Cloud Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) - Data Management - Data Products Catalog V4.94

The CALIPSO V2.00 Lidar Level 2 Polar Stratospheric Cloud data product is an updated version of an already order-able dat set. The changes were signed off by the CALIPSO Configuration Control Board, versioned, and the code uploaded to a code repository. There is no ITAR/SBU data or code associated with this product. Data will be publicly order-able at the NASA LaRC Atmospheric Sciences Data Center (ASDC). All documentation and web sites will be made public once the data product is released. The data is in HDF4 format and will be generated for majority of the mission (June 2006 - March 2021). The attached Data Products Catalog (v4.94) describes this new product in section 2.14, pp 115- 119.

Mark Vaughan↗
NASA NTRS2021

Detection and Height Measurement of Tenuous Clouds and Blowing Snow in ICESat-2 ATLAS Data

Tenuous atmospheric layers, such as high, thin cirrus clouds and blowing snow over Antarctica, play an important role in the climate system, affecting energy fluxes between the Earth and the atmosphere. Our knowledge of the structure of the atmosphere is largely derived from atmospheric satellite measurements. Yet tenuous layers can be hard to detect in satellite lidar data, especially in daylight data characterized by high solar background. In this study, we introduce an approach to detect tenuous atmospheric layers in the atmospheric lidar measurements of NASA's ICESat-2. The density-dimension algorithm for ICESat-2 atmospheric data (DDA-atmos) identifies atmospheric layers while automatically adapting to different background conditions of night, twilight, and daylight data. This capability, demonstrated for tenuous clouds and blowing snow, offers a data-based solution to an important climate modeling problem. Atmospheric layer boundaries, detection confidence, and density fields resultant from the DDA-atmos are reported in ICESat-2 atmospheric data product ATL09.

Ute Herzfeld↗
NASA NTRS2018

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↗
NASA NTRS2017

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↗
NASA NTRSDate not supplied

TPSAS-NF1676L-17926-DND

Validation of the CALIOP data products remains an ongoing task for the CALIPSO team. Validating the optical properties of aerosols located above clouds is especially difficult, because independent measurements are usually not available. In this presentation we analyze 532-nm aerosol optical depth (AOD) above clouds, comparing results from the standard CALIOP algorithm with two alternate algorithms applied to CALIOP data acquired along the transport pathways of African dust and biomass burning aerosols. Multiple years of the CALIPSO nighttime data (2007-2012) were examined. The analysis was limited to cases where there are opaque water clouds below aerosol layers that can be used as a reference to retrieve AOD of the overlying aerosol layer.

Zhaoyan Liu↗
NASA NTRSDate not supplied

TPSAS-NF1676L-18612-DND

Can a space-based elastic backscatter lidar and coincident infrared radiometer recognize the varied microphysical properties observed by aircraft-based cloud probes in cirrus clouds? If so, then the global and continuous coverage provided by the satellite instruments can extend the knowledge about cirrus cloud properties gained from intensive aircraft field campaigns. The recent Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) aircraft field mission that occurred during August and September, 2013 is an ideal data set to use to test whether this is possible. During SEAC4RS there was extensive sampling of cirrus clouds occurring in widely varied conditions, including the North American Monsoon, forest fires, midlatitude frontal convection and tropical convection. Aircraft cloud probe sampling (2D-S, FCDP or FSSP, CPI) was performed from three airplanes, often coordinated with remote sensing by an aircraft-based elastic backscatter lidar (CPL). During the mission the CALIPSO satellite also observed these clouds from space with a similar elastic backscatter lidar (CALIOP) and an infrared radiometer (IIR). There are several cases where the airplanes sampled directly along the satellite track, but also many overpasses of the region and these features that were not coincident with the aircraft-based sampling. This presentation seeks to address the question of whether relationships between the cloud particle size distribution measurements and habits observed by the SPEC cloud probes and CPL aircraft lidar parameters can be up-scaled to classify the CALIPSO satellite observations from this region and time period. The lidar can also provide cloud top information and evidence of whether there was irreversible transport of ice and aerosols into the UT/LS.

Melody Avery↗
NASA NTRSDate not supplied

TPSAS-NF1676L-23557-DND

The Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) measures both parallel and perpendicular backscatter of linearly polarized 532 nm light from cloud particles in the atmosphere. The perpendicular component of the return signal allows differentiation between cloud layers consisting of spherical water droplets from those with non-spherical ice particles. A two-way distribution of layer-integrated 532 nm total backscatter and the layer-integrated 532 nm depolarization ratio further differentiates between water cloud layers with significant multiple scattering, horizontally-oriented ice particles that cause specular reflections, and randomly-oriented ice particles, as described in Hu et al., 2009. The cloud phase algorithm functions well for the majority of clouds, but there have been some recent changes and improvements that are described in this poster. The impact of the CALIOP viewing angle change from near-nadir (0.3 degrees) to slightly tilted (3.0 degrees) on the optical properties of the various CALIOP cloud particle phases is also shown. A major improvement to the phase algorithm is the limitation of a spatial coherence test for horizontally-oriented ice to cloud layers that have sufficient integrated attenuated backscatter to likely contain HOI. This change reduces a "striping" effect caused by noisiness in the spatial coherence test for thin cloud layers. Additional temperature tests are considered, and the regional and vertical distribution of cloud layers with the various CALIOP cloud phases is shown. Only one cloud particle phase is allowed for each 5 km portion of a cloud layer that is considered by the cloud phase algorithm, so we use in situ aircraft and CloudSat observations to determine how the CALIOP cloud phase algorithm is treating optically and thermally thick clouds, which may be mixed-phase.

Melody Avery↗
NASA NTRSDate not supplied

Airborne High Spectral Resolution Lidar-2 Measurements of Enhanced Depolarization in Marine Aerosols

Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA EVS-3 Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed enhanced particulate linear depolarization associated with aerosols within the marine boundary layer. These HSRL-2 observations were acquired off the east coast of the United States in February and March 2020 when this lidar was deployed on the NASA LaRC UC-12 aircraft. HSRL-2 measured profiles of aerosol backscattering, extinction,and depolarization at 355 and 532nm and aerosol backscattering and depolarization at 1064nm. Typically HSRL-2 measures low (<5%) linear particulate depolarization associated with marine sea salt aerosols. However, during several ACTIVATE flights, particularly those that occurred with outbreaks of cold, dry air, linear particulate depolarization exceeded 15-20% (532nm) for aerosols within a few hundred meters above the surface. These high values indicated that these particles were nonspherical. Elevated depolarization values were also observed at 355 and 1064 nm. HSRL-2 measured aerosol extinction/backscatter ratio (“lidar ratio”) values around 20-25 sr (355 and 532 nm) that are typically associated with sea salt particles. Coincident measurements of relative humidity from dropsondes released from the UC-12and in situ Diode Laser Hygrometer (DLH) measurements flown on the NASA HU-25 aircraft showed that highest depolarization values of these nonspherical particles were found when the relative humidity (RH)was below 50-60%.These lidar observations of elevated depolarization associated with sea salt aerosol are consistent with previous lidar measurements of sea salt aerosols in dry conditions. We discuss these HSRL-2 measurements also in the context of coincident airborne in situ measurements of particle size and composition acquired on the HU-25 aircraft. We also found that CALIOP satellite measurements observed elevated depolarization during some similar cold air outbreaks. In such cases, the operational CALIOP algorithms attributed the elevated depolarization to nonspherical dust particles rather than the more likely scenario of nonspherical sea salt particles associated with low RH.

aerosols↗
NASA NTRSDate not supplied

CALIOP Stratospheric Aerosol Typing Performance of Smoke from the 2019-2020 Australian Bushfire Event

A series of pyroCb events occurring in southeast Australia in late December 2019 and early January 2020 injected a large amount of smoke into the stratosphere. CALIOP observations provided critical measurements of the plume in the stratosphere which gave clues about its microphysical properties. An upcoming revised version of the CALIOP level 2 data products (V4.5) will feature improved aerosol typing in the stratosphere. Above the tropopause, the level 2 products discriminate between smoke, volcanic ash, and volcanic sulfate. Accuracy of aerosol typing is critical for automated surveys characterizing distributions of anthropogenic versus natural aerosol and is essential for accurate aerosol extinction retrievals from elastic backscatter lidars such as CALIOP. This poster assesses the performance of the prototype V4.5 CALIOP stratospheric aerosol typing algorithm for the Australian bushfire event.

Jason Tackett↗
NASA NTRSDate not supplied

Improvements in CALIOP Smoke Optical Depth over Clouds

Smoke over marine stratocumulus is ubiquitous off the southwest coast of Africa during biomass burning season. 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. 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. This poster summarizes the new smoke base extension algorithm and its performance.

Jason L. Tackett↗