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William L Smith

Publications and source records attributed to William L Smith.

17 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Improving the CERES SYN Cloud and Flux Products by Identifying GOES-17 Scan Anomalies Using a Convolutional Neural Network

The NASA Clouds and the Earth’s Radiant Energy System (CERES) project relies on top-of-atmosphere (TOA) broadband fluxes derived from geostationary (GEO) satellite imagery to account for the diurnal flux variations between the CERES observation intervals, and thereby produce a synoptic gridded (SYN1deg) product based on continuous temporal observations. Consistent broadband flux derivation depends on accurate radiative property measurements and cloud retrievals, which largely determine the radiance-to-flux conversion process. Therefore, it is important to ensure a high quality of cloud property input in order to maintain a reliable broadband flux record. In Edition 4 of the CERES SYN1deg product, a robust automated image anomaly detection algorithm based on inter-line and inter-pixel differences, spatial variance, and 2-D Fourier analysis has been successful in identifying imagery with linear artifacts, but the line-by-line inspection and cleaning process must still be performed by a human. Therefore, further automation of this quality assurance process is warranted, especially considering the excessive amount of additional cleaning necessitated by the GOES-17 Advance Baseline Imager (ABI) cooling system anomaly. As such, this article highlights advancement of the CERES GEO image artifact cleaning approach based on a convolutional neural network (CNN) for classification of bad scanlines. Once trained, the CNN approach is a computationally inexpensive means to ensure greater consistency in cloud retrievals, and therefore broadband flux derivation, based on GOES-17 measurements.

Benjamin Scarino↗
NASA NTRS2021

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast – Part 2: Circulation, Boundary Layer, and Clouds

The Western North Atlantic Ocean (WNAO) is a complex land-ocean-atmosphere system that experiences a broad range of atmospheric phenomena, which in turn drive unique aerosol transport pathways, cloud morphologies, and boundary layer variability. This work, Part 2 of a 2-part paper series, provides an overview of the atmospheric circulation, boundary layer variability, three-dimensional cloud structure, and precipitation over the WNAO; the companion paper (Part 1) focused on chemical characterization of aerosols, gases, and wet deposition.Seasonal changes in atmospheric circulation and sea surface temperature explain a clear transition in cloud morphologies from small shallow cumulus clouds, convective clouds, and tropical storms in summer, to stratus/stratocumulus and multi-layer cloud systems associated with winter storms. Synoptic variability in cloud fields is estimated using satellite-based weather states, and the role of postfrontal conditions (cold-air outbreaks) in the development of stratiform clouds is further analyzed. Precipitation is persistent over the ocean, with a regional peak over the Gulf Stream path, where offshore sea surface temperature gradients are large and surface fluxes reach a regional peak. Satellite data show a clear annual cycle in cloud droplet number concentration with maxima (minima) along the coast in winter (summer), suggesting a marked annual cycle in aerosol-cloud interactions. Compared with satellite cloud retrievals, four climate models qualitatively reproduce the annual cycle in cloud cover and liquid water path, but with large discrepancies across models, especially in the extra-tropics. The paper concludes with a summary of outstanding issues and recommendations for future work.

David Painemal↗
NASA NTRS2020

Toward a Consistent Definition between Satellite and Model Clear-Sky Radiative Fluxes

A new method of determining clear-sky radiative fluxes from satellite observations for climate model evaluation is presented. The method consists of applying adjustment factors to existing satellite clear-sky broadband radiative fluxes that make the observed and simulated clear-sky flux definitions more consistent. The adjustment factors are determined from the difference between observation-based radiative transfer model calculations of monthly mean clear-sky fluxes obtained by ignoring clouds in the atmospheric column and by weighting hourly mean clear-sky fluxes with imager-based clear-area fractions. The global mean longwave (LW) adjustment factor is −2.2 W m−2 at the top of the atmosphere and 2.7 W m−2 at the surface. The LW adjustment factors are pronounced at high latitudes during winter and in regions with high upper-tropospheric humidity and cirrus cloud cover, such as over the west tropical Pacific, and the South Pacific and intertropical convergence zones. In the shortwave (SW), global mean adjustment is 0.5 W m−2 at TOA and −1.9 W m−2 at the surface. It is most pronounced over sea ice off of Antarctica and over heavy aerosol regions, such as eastern China. However, interannual variations in the regional SW and LW adjustment factors are small compared to those in cloud radiative effect. After applying the LW adjustment factors, differences in zonal mean cloud radiative effect between observations and climate models decrease markedly between 60°S and 60°N and poleward of 65°N. The largest regional improvements occur over the west tropical Pacific and Indian Oceans. In contrast, the impact of the SW adjustment factors is much smaller.

Norman G Loeb↗
NASA NTRS1992

Projected NASA power requirements for space science and exploration missions

NASA's Office of Space Science and Applications has recently completed its long-range strategic plan which describes a number of exciting space science missions into the early 21st century. In parallel, NASA's new Office of Exploration has begun defining in more detail the architectures of the Space Exploration Initiative (SEI) for returning to the Moon and going to Mars. Both the space science missions and the SEI missions are dependent upon power sources and energy storage with strong requirements for reliability, long life, ease of assembly, autonomy, and light weight. This paper reviews the currently planned space science and SEI missions and focuses upon the power requirements with a view toward guiding technology developers and power designers.

Gary L Bennett↗
NASA NTRSDate not supplied

TPSAS-NF1676L-13135-DND

Aircraft Icing - Aircraft structures act as ice nuclei in supercooled clouds - ice collects, weight increases, plane falls - Pilots need to know where and when icing can occur - PIREPS are first order: sparse, aircraft dependent, location uncertain - Model analyses and forecasts: freezing levels, cloud expectations - radar => precipitation - All combined in NCAR/FAA/NOAA/NASA program to provide Current Icing Product (CIP) & Forecast Icing product (FIP) analyses to pilots (CONUS) - some inadequacies remain - NWP uncertainties, intensity, altitude of icing, etc. - Operational satellites can add valuable information - indirectly: input of cloud properties to CIP & NWP - directly: determination of icing threat from real time satellite data

William L Smith↗
NASA NTRSDate not supplied

TPSAS-NF1676L-18322-DND

MetOp-A satellite was launched on 19 October 2006 and MetOp-B was launched on 17 September 2013. Two satellites fly in complementary orbits and in a sun synchronous morning orbit passing over the Equator at the same local time 9:30 am. MetOp-B phased 50 minutes apart from MetOp-A. Presented here are the global surface IR emissivity spectra retrieved from IASI measurements observed from both MetOp-A and MetOp-B satellites. Inter-comparison of the emissivities obtained from MetOp-A and MetOp-B is performed to ensure the continuity of emissivity monitoring and its trend analysis. Effort on emissivity validation continues with available ground in-situ measurements and retrieval consistency check through radiative transfer model simulations. The spatial resolution of emissivity climatology atlas is now increased from 0.5 to 0.25 degrees latitude-longitude, and available to the community.

Daniel K Zhou↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10574-DND

The Infrared Atmospheric Sounding Interferometer (IASI) aboard of MetOP-A was successfully launched on 19 October 2006 and has been providing excellent data for more than 3 years. The IASI spectra can be converted into proxy data for the NPOESS Crosstrack Infrared Sounder (CrIS) through a rigorous mathematical transformation by taking into account of instrument characteristics of both the IASI and the CrIS. The 15-channel AMSU temperature sounder, and the 5-channel and Microwave Humidity Sounder (MHS) aboard of MetOP-A can be used to generate proxy data for the NPOESS Advanced Technology Mircrowave Sounder (ATMS). The CrIS and ATMS make up the Cross-track Infrared and Microwave Sounder Suite (CrIMSS). CrIMSS will primarily provide global temperature, moisture, and pressure profiles. We will describe the method used in generating the proxy data and show results of using the proxy data for evaluation of the NPOESS CrIMSS Environmental Data Record (EDR) retrieval algorithm.

Xu Liu↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10888-DND

Hyperspectrally-resolved surface emissivities are derived with an algorithm utilizes a combined fast radiative transfer model (RTM) with a molecular RTM and a cloud RTM accounting for both atmospheric absorption and cloud absorption/scattering. Clouds are automatically detected and cloud microphysical parameters are retrieved; and emissivity is retrieved under clear and optically thin cloud conditions. The retrieval technique separates surface emissivity from skin temperature by representing the emissivity spectrum with eigenvectors derived from a laboratory measured emissivity database. Global land emissivities retrieved under the optically thin clouds are investigated by means of their accuracy in comparison with that under cloud-free conditions. Here we present the emissivity derived under optically thin clouds, their accuracy, and the inter-comparison with that under clear conditions.

Daniel K Zhou↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10898-DND

The Infrared Atmospheric Sounding Interferometer (IASI) aboard of MetOP-A was successfully launched on 19 October 2006 and has been providing excellent data for more than 3 years. The IASI spectra can be converted into proxy data for the NPOESS Crosstrack Infrared Sounder (CrIS) through a rigorous mathematical transformation by taking into account of instrument characteristics of both the IASI and the CrIS. The 15-channel AMSU temperature sounder, and the 5-channel and Microwave Humidity Sounder (MHS) aboard of MetOP-A can be used to generate proxy data for the NPOESS Advanced Technology Mircrowave Sounder (ATMS). The CrIS and ATMS make up the Cross-track Infrared and Microwave Sounder Suite (CrIMSS). CrIMSS will primarily provide global temperature, moisture, and pressure profiles. We will describe the method used in generating the proxy data and show results of using the proxy data for evaluation of the NPOESS CrIMSS Environmental Data Record (EDR) retrieval algorithm.

Xu Liu↗
NASA NTRSDate not supplied

Impact of Air Traffic Reductions during the COVID-19 Pandemic on Aircraft-induced Clouds and their Radiative Effects

Air travel restrictions due to the novel coronavirus 2019 (COVID-19) pandemic drastically reduced air travel internationally during the spring of 2020. Such an extraordinary disruption of air traffic may have a profound effect on contrail formation that could allow for better quantification and scientific understanding of the radiative impacts of aviation-induced clouds on climate. This investigation synergizes MODIS, CrIS, and GOES-16 satellite analyses with weather analyses, including those from GEOS and MERRA, to compare contrail formation conditions and radiative forcings of linear contrails and thin cirrus detected over the contiguous United States (CONUS) and the North Atlantic for the 2020 air traffic slowdown period with parallel analyses conducted for a baseline period from a previous year with normal air traffic. A consistent analysis system for contrail detection and cloud property retrievals (e.g. optical depth, particle size, and altitude) from satellites, coupled with radiative transfer modeling are applied to characterize and contrast contrail cirrus properties and radiative effects estimated during the pandemic and baseline periods. Temperature and humidity profiles from numerical weather models and hyperspectral infrared measurements are used to estimate the contrail formation potential (CFP) over the study areas in order to help choose the most appropriate baseline period and to account for potential impacts of differences in meteorology on contrail formation and coverage. This study, using NASA satellite data and other assets, is expected to improve our understanding of the relationship between air traffic, contrail cirrus coverage and related impacts in order to better quantify the need for contrail formation mitigation strategies that could reduce aviation effects on climate.

William L Smith↗
NASA NTRSDate not supplied

Advancing NASA SatCORPS Global Data Products with Cloud Computing and Machine Learning

Operational satellite imager radiances are valuable for deriving many different physical parameters that can be used for a variety of weather, aviation, and energy applications. The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) applies a suite of algorithms to meteorological satellite data to provide cloud properties, radiative fluxes and other parameters on a global scale. The use of cloud computing has enabled recent enhancements to process a constellation of geostationary satellites at higher spatiotemporal resolutions than previously possible that meet low latency and near real-time needs. Data taken from Meteosat-8 and -11, Himawari, GOES-16, and -17 are processed and combined with operational polar orbiting satellite data and composited on a 3-km grid to provide global coverage. To improve the utility of the data products, machine learning and other innovative methods are applied in various ways to help minimize data product uncertainties under the most challenging conditions and to improve their consistency at all times of day. An update on recent SatCORPS enhancements is presented, highlighting the community benefits achieved with the use of cloud computing and machine learning.

William L Smith↗
NASA NTRSDate not supplied

Creating Satellite Data Products in the Cloud: SatCORPS Global Cloud Composites

Real time satellite observations and real time derived cloud products are becoming an important tool for both science as well as business ventures. The SatCORPS group leverages public and private cloud-based sources of satellite observations to create its Global Cloud Composite product in near real-time. This dataset allows others access to cloud information that can be accessed directly from the cloud. In this work, we describe the software algorithms and software infrastructure that we have created to create and distribute this product through our hybrid cloud and on-premises system that leverages the strengths and weaknesses of each platform. We will also describe the GCC product itself in terms of the scientific parameters available, resolution and temporal availability. Finally, we will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global cloud products with very low latency which we see that as filling a rapidly growing need in the research, modelling and business community. We present a detailed description of the SatCORPS GCC product in terms of the capabilities and research benefits as well as the delivery architecture in AWS. We take the discussion further and describe the web tools that the SatCORPS group has developed that allow users to access and use the GIS data that it creates.

Global Cloud Composite SatCORPS SMCE AWS↗