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David Winker

Publications and source records attributed to David Winker.

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 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 NTRS2019

MAIAC Thermal Technique for Smoke Injection Height from MODIS

We present a new algorithm to derive smoke plume height (Ha) using thermal contrast from the rising mixture of aerosol and emitted gases in the MODIS 11m channel. Validation shows good agreement with wind-corrected MISR-MINX values, with about 60% of the MODIS Terra thermal retrievals within 500m of MISR Ha, and 450m lower on average. The bias is expected because the thermal technique represents an effective rather than a top plume height from MISR MINX. Comparison of MODIS Aqua retrievals with CALIOP CALIPSO shows similar statistics, with standard deviation of 458m for the mean plume height and 216m lower on average. Ha is part of the MAIAC MODIS Collection 6 suite of products (MCD19), accessible via the Land Product Distributed Active Archive Center (LP DAAC). Aerosol injection height is reported in the daily MAIAC atmospheric product MCD19A2 along with the cloud mask, column water vapor, aerosol optical depth, AOD uncertainty and aerosol type, at 1km resolution on global Sinusoidal grid. Despite some limitations, the vastly increased coverage from MODIS observations makes it a valuable dataset complementing the established MISR and CALIOP products.

atmosphere↗
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-20101-DND

Aerosols influence climate through their direct and indirect effects. The aerosol indirect effect is based on the way they interact with surrounding clouds. During cloud formation and development, aerosols act as cloud nucleation nuclei (CCN) or ice nuclei, which modifies cloud micro-, macro-physical and radiative properties, and hence helps to shape the Earth's radiation budget. Dominant sources of ocean-derived aerosols that may serve as CCN include sea spray and biogenic aerosol. In this study, we used 10-years global observations from the A-Train satellites to show seasonal variations of cloud droplet number concentrations (CDNC), ocean chlorophyll concentrations, aerosol angstrom parameter, and rainfall. Potential cloud-aerosol interactions are further discussed based on seasonal and spatial correlations between microphysics of clouds and aerosols. Emphasis for this study is placed on the southern ocean and tropical Pacific.

Shan Zeng↗
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

Uncertainty in Observational Estimates of the Aerosol Direct Radiative Effect and Forcing

Aerosols continue to be responsible for the largest uncertainty in determining the anthropogenic radiative forcing of the climate. To both reconcile the large range in satellite-based estimates of the aerosol direct radiative effect (DRE, the direct interaction with solar radiation by all aerosols) and to optimize the design of future observing systems, we build a framework for assessing uncertainty in aerosol DRE and the aerosol direct radiative forcing (DRF, the radiative effect of just anthropogenic aerosols, RF_ari). Shortwave aerosol radiative kernels (Jacobians) were derived using the MERRA-2 reanalysis data. These radiative kernels are used to compute a lower-bound on the systematic uncertainty in observational estimates of the aerosol DRE/DRF by making the optimistic assumption that global aerosol observations can be made with the accuracy found in the Aerosol Robotic Network (AERONET) sun photometer retrievals. The total uncertainty is shown to be dominated by contributions from the aerosol single scattering albedo uncertainty. These uncertainty estimates were compared to a literature survey of mostly satellite-based aerosol DRE/DRF values. Comparisons to previous studies reveal that most have significantly underestimated the aerosol DRE uncertainty. Past estimates of the aerosol DRF uncertainty are smaller (on average) than our optimistic observational estimates, including the aerosol DRF uncertainty given in the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5).

Tyler James Thorsen↗