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NASA NTRS1996

Estimating the Thickness of Sea Ice Snow Cover in the Weddell Sea from Passive Microwave Brightness Temperatures

Passive microwave satellite observations have frequently been used to observe changes in sea ice cover and concentration. Comiso et al. showed that there may also be a direct relationship between the thickness of snow cover (h(sub s)) on ice and microwave emissivity at 90 GHz. Because the in situ experiment of experiment of Comiso et al. was limited to a single station, the relationship is re-examined in this paper in a more general context and using more extensive in situ microwave observations and measurements of h from the Weddell Sea 1986 and 1989 winter cruises. Good relationships were found to exist between h(sub s) sand the emissivity at 90 GHz - 10 GHz and the emissivity at 90 GHz - 18.7 GHz when the standard deviation of h(sub s) was less than 50% of the mean and when h(sub s) was less than 0.25 m. The reliance of these relationships on h(sub s) is most likely caused by the limited penetration through the snow of radiation at 90 GHz. When the algorithm was applied to the Special Sensor Microwave/Imager (SSM/I) satellite data from the Weddell Sea, the resulting mean h(sub s) agreed within 5% of the mean calculated from greater than 1400 in situ observations.

Arrigo, K. R.↗
NASA NTRS2001

Combining TOPEX and SeaWinds Data to Refine Models for Ocean Surface Emissivity: Wind Vector Signatures at 18, 21 and 37 GHz

TOPEX Microwave Radiometer (TMR) brightness temperature observations at 18, 21, and 37 GHz have been collocated with near-simultaneous SeaWinds wind vector data as well as with a monthly SST climatological product. The combined data set allows us to study the dependence of ocean surface emissivity (at each frequency) upon both wind speed. Results show clear two-branch wind speed dependence; weak and linear below 6 m/s with an abrupt increase in sensitivity above that point. The analysis also shows that the zenith-directed ocean surface emissivity is polarization dependent above wind speeds of 5-6 m/s with an azimuthal variation related to the wind direction. This last result accords with recent polarimetric radiometer observations collected from aircraft. Implications of these observations to water vapor retrieval algorithms, nadir-viewing polarimetry, and ocean emission modeling will be discussed.

Vandemark, D.↗
NASA NTRS2002

A Method to Retrieve Rainfall Rate Over Land from TRMM Microwave Imager Observations

Over tropical land regions, rain rate maxima in mesoscale convective systems revealed by the Precipitation Radar (PR) flown on the Tropical Rainfall Measuring Mission (TRMM) satellite are found to correspond to thunderstorms, i.e., Cbs. These Cbs are reflected as minima in the 85 GHz brightness temperature, T85, observed by the TRMM Microwave Imager (TMI) radiometer. Because the magnitude of TMI observations do not discriminate satisfactorily convective and stratiform rain, we developed here a different TMI discrimination method. In this method, two types of Cbs, strong and weak, are inferred from the Laplacian of T85 at minima. Then, to retrieve rain rate, where T85 is less than 270 K, a weak (background) rain rate is deduced using T85 observations. Furthermore, over a circular area of 10 km radius centered at the location of each T85 minimum, an additional Cb component of rain rate is added to the background rain rate. This Cb component of rain rate is estimated with the help of (T19-T37) and T85 observations. Initially, our algorithm is calibrated with the PR rain rate measurements from 20 MCS rain events. After calibration, this method is applied to TMI data taken from several tropical land regions. With the help of the PR observations, we show that the spatial distribution and intensity of rain rate over land estimated from our algorithm are better than those given by the current TMI-Version-5 Algorithm. For this reason, our algorithm may be used to improve the current state of rain retrievals on land.

Prabhakara, C.↗
NASA NTRS2003

Reliable Transport over SpaceWire for James Webb Space Telescope (JWST) Focal Plane Electronics (FPE) Network

NASA's James Webb Space Telescope (JWST) faces difficult technical and budgetary challenges to overcome before it is scheduled launch in 2010. The Integrated Science Instrument Module (ISIM), shares these challenges. The major challenge addressed in this paper is the data network used to collect, process, compresses and store Infrared data. A total of 114 Mbps of raw information must be collected from 19 sources and delivered to the two redundant data processing units across a twenty meter deployed thermally restricted interface. Further data must be transferred to the solid-state recorder and the spacecraft. The JWST detectors are kept at cryogenic temperatures to obtain the sensitivity necessary to measure faint energy sources. The Focal Plane Electronics (FPE) that sample the detector, generate packets from the samples, and transmit these packets to the processing electronics must dissipate little power in order to help keep the detectors at these cold temperatures. Separating the low powered front-end electronics from the higher-powered processing electronics, and using a simple high-speed protocol to transmit the detector data minimize the power dissipation near the detectors. Low Voltage Differential Signaling (LVDS) drivers were considered an obvious choice for physical layer because of their high speed and low power. The mechanical restriction on the number cables across the thermal interface force the Image packets to be concentrated upon two high-speed links. These links connect the many image packet sources, Focal Plane Electronics (FPE), located near the cryogenic detectors to the processing electronics on the spacecraft structure. From 12 to 10,000 seconds of raw data are processed to make up an image, various algorithms integrate the pixel data Loss of commands to configure the detectors as well as the loss of science data itself may cause inefficiency in the use of the telescope that are unacceptable given the high cost of the observatory. This combination of requirements necessitates a redundant, fault tolerant, high- speed, low mass, low power network with a low Bit error Rate(1E-9- 1E-12). The ISIM systems team performed many studies of the various network architectures that meeting these requirements. The architecture selected uses the Spacewire protocol, with the addition of a new transport and network layer added to implement end-to-end reliable transport. The network and reliable transport mechanism must be implemented in hardware because of the high average information rate and the restriction on the ability of the detectors to buffer data due to power and size restrictions. This network and transport mechanism was designed to be compatible with existing Spacewire links and routers so that existing equipment and designs may be leveraged upon. The transport layer specification is being coordinated with European Space Agency (ESA), Spacewire Working Group and the Consultative Committee for Space Data System (CCSDS) PlK Standard Onboard Interface (SOIF) panel, with the intent of developing a standard for reliable transport for Spacewire. Changes to the protocol presented are likely since negotiations are ongoing with these groups. A block of RTL VHDL that implements a multi-port Spacewire router with an external user interface will be developed and integrated with an existing Spacewire Link design. The external user interface will be the local interface that sources and sinks packets onto and off of the network (Figure 3). The external user interface implements the network and transport layer and handles acknowledgements and re-tries of packets for reliable transport over the network. Because the design is written in RTL, it may be ported to any technology but will initially be targeted to the new Actel Accelerator series (AX) part. Each link will run at 160 Mbps and the power will be about 0.165 Watt per link worst case in the Actel AX.

Rakow, Glenn↗
NASA NTRS2011

Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap was undertaken preparatory to extending the 1979-2007 NASA Goddard Space Flight Center (GSFC) NASA Team algorithm time series of global sea ice extents and areas. The 1979- 2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in Northern Hemisphere sea ice extents is -0.0156%, with a standard deviation of the differences of 0.6204%, and the yearly mean difference in Northern Hemisphere sea ice areas is 0.5433%, with a standard deviation of 0.3519%. For the Southern Hemisphere, the yearly mean difference in sea ice extents is 0.0304% +/- 0.4880%, and the mean difference in sea ice areas is 0.1550% +/- 0.3753%. This F13/F17 intercalibration enables the extension of the 28-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available.

Cavalieri, Donald J.↗
NASA NTRS2012

Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap was undertaken preparatory to extending the 1979-2007 NASA Goddard Space Flight Center (GSFC) NASA Team algorithm time series of global sea ice extents and areas. The 1979- 2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in Northern Hemisphere sea ice extents is -0.0156%, with a standard deviation of the differences of 0.6204%, and the yearly mean difference in Northern Hemisphere sea ice areas is 0.5433%, with a standard deviation of 0.3519%. For the Southern Hemisphere, the yearly mean difference in sea ice extents is 0.0304% 0.4880%, and the mean difference in sea ice areas is 0.1550% 0.3753%. This F13/F17 intercalibration enables the extension of the 28-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available.

Cavalieri, Donald J.↗
NASA NTRS2019

Negative extreme events in gross primary productivity and their drivers in China during the past three decades

Climate extremes have remarkable impacts on ecosystems and are expected to increase with future global warming. However, only few studies have focused on the ecological extreme events and their drivers in China. In this study, we carried out an analysis of negative extreme events in gross primary productivity (GPP) in China and the sub-regions during 1982–2015, using monthly GPP simulated by 12 process-based models (TRENDYv6) and an observation-based model (Yao-GPP). Extremes were defined as the negative 5th percentile of GPP anomalies, which were further merged into individual extreme events using a three-dimensional contiguous algorithm. Spatio-temporal patterns of negative GPP anomalies were analyzed by taking the 1000 largest extreme events into consideration. Results showed that the effects of extreme events decreased annual GPP by 2.8% (i.e. 208 TgC/year) in TRENDY models and 2.3% (i.e. 151 TgC/year) in Yao-GPP. Hotspots of extreme GPP deficits were mainly observed in North China (−53 gC/sq.m year) in TRENDY models and Northeast China (−42 gC/sq.m year) in Yao-GPP. For China as a whole, attribution analyses suggested that extreme low precipitation was associated with 40%–50% of extreme negative GPP events. Most events in northern and western China could be explained by meteorological droughts (i.e. low precipitation) while GPP extreme events in southern China were more associated with temperature extremes, in particular with cold spells. GPP was revealed to be much more sensitive to heat/drought than to cold/wet extreme events. Combined with projected changes in climate extremes in China, GPP negative anomalies caused by drought events in northern China and by temperature extremes in southern China might be more prominent in the future.

Climate change↗
NASA NTRS2022

On the Stability and Phase Behavior of Titan's Subsurface Liquid Columns

On Titan, liquid hydrocarbon may stay in the subsurface porous permeable crust known as the alkanofer, analogous to water in Earth’s aquifer. In addition to pressure gradient, the subsurface liquid in alkanofers is subject to vertical compositional grading due to the gravity and temperature gradient. The common wisdom is that the liquid would normally stay underground in a stability established by the pressure that increases with depth as observed in aquifers on Earth. However, Titan’s liquids consist of nitrogen and hydrocarbons, mainly methane and ethane, the behavior of which is very sensitive to temperature and pressure. Consequently, the liquid density does not always increase with depth, thus may introduce a reverse density profile that leads to vertical convective instability of the liquid column. If reverse density profiles are present, capillary pressures arising from liquid trapped within small pores in the crust can help with the column stability. The liquid held in the capillaries can seal the space below it thus helping with the stability, unless the overpressure built from underneath becomes larger than the capillary pressure, which causes leakage to allow the liquids to seep upward from the deep. This situation is analogous to hydrocarbon seeps on Earth, where oil and natural gas escape the reservoir and flow slowly through network of cracks to the surface. An algorithm based on an extended Gibbs equation commonly used in petroleum reservoir engineering is employed in this work to produce pressure, density, and compositional profiles for evaluating the stability and phase behavior of Titan’s subsurface fluids.

Sugata Tan↗
NASA NTRSDate not supplied

Web-based Visualization and Analytics of Petascale Data: Equity as a Tide that Lifts All Boats

Scientists generate petabytes of data daily to help uncover environmental trends or behaviors that are hard to predict. For example, understanding climate simulations based on the long-term average of temperature, precipitation, and other environmental variables is essential to predicting and establishing root causes of future undesirable scenarios and assessing possible mitigation strategies. While supercomputer centers provide a powerful infrastructure for generating petabytes of simulation output, accessing and analyzing these datasets interactively remains challenging on multiple fronts. This paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hid-ing the complexities of dealing with file systems or cloud services.We also optimize network utilization while streaming from petas-cale repositories through state-of-the-art progressive compression algorithms. Based on this abstraction, we provide customizable dashboards that can be accessed from any device with any inter-net connection, enabling interactive visual analysis of vast amounts of data to a wide range of users - from top scientists with access to leadership-class computing environments to undergraduate students of disadvantaged backgrounds from minority-serving institutions. We focus on NASA’s use of petascale climate datasets as an example of particular societal impact and, therefore, a case where achieving equity in science participation is critical. We validate our approach by improving the ability of climate scientists to visually explore their data via two fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution.These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Data visualization↗
NASA NTRS2008

New Developments for Physically-based Falling Snow Retrievals over Land in Preparation for GPM

The NASA Global Precipitation Measurement mission (GPM) concept centers on deploying a Core spacecraft carrying a dual-frequency precipitation radar and a microwave radiometric imager with channels from 10 to 183 GHz to serve as a precipitation physics observatory and a calibration reference to unify a constellation of dedicated and operational passive microwave sensors. Because of the extended orbit of the Core (plus or minus 65 deg) and the enhanced dual frequency radar and high frequency radiometer, GPM will be able to sense falling snow precipitation and light rain over land. Accordingly, GPM has partnered with the Canadian CloudSat/CALIPSO Validation Project (C3VP) to obtain observations to provide one of several important ground-based validation data sets around which the falling snow models and retrieval algorithms can be further developed and tested. In this work we compare and correlate the long time series (Nov.'06 - March '07) measurements of precipitation rate from parsivels to the passive (89, 150, 183 plus or minus 1, plus or minus 3, plus or minus 7 GHz) observations of NOAA's AMSU-B radiometer. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that by computing brightness temperatures based on CARE radiosonde data and a rough estimate of surface emissivity show that the cloud ice scattering signal in the AMSU-B data is detected. That is the differences in computed TB and AMSU-B TB for precipitating and non-precipitating cases are unique such that the precipitating and non-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data. Forest fraction, snow cover, and measured emissivities were combined to calculate the surface emissivities.

Jackson, Gail S.↗
NASA NTRS2012

Aquarius Radiometer RFI Detection, Mitigation, and Impact Assessment

The Aquarius/SAC-D satellite was launched on 10 June 2011 into a sun-synchronous polar orbit and the Aquarius microwave radiometers [1] became operational on 25 August 2011. Since that time, it has been measuring brightness temperatures at 1.4 GHz with vertical, horizontal and 3rd Stokes polarizations . Beginning well before the launch, there has been the concern that Radio Frequency Interference (RFI) could have an appreciable presence. This concern was initiated by, among other things, its prevalence in both early [2] and more recent [3,4] aircraft field experiments using 1.4 GHz radiometers, as well as by the strong RFI environment encountered during the recent ESA SMOS mission, also at 1.4 GHz [5]. As a result, a number of methods for RFI detection and mitigation have been developed and tested. One in particular, "glitch detection" and "pulse blanking" mitigation has been adapted for use by Aquarius [6, 7]. The early on-orbit performance of the Aquarius RFI detection and mitigation algorithm is presented here, together with an assessment of the global RFI environment at 1.4 GHz which can be derived from the Aquarius results.

Ruf, Christopher↗
NASA NTRS2022

An Evaluation of NOAA-20 ATMS Instrument Pre-Launch and On-Orbit Performance Characterization

Passive microwave sounders provide the highest-impact observations ingested by major numerical weather prediction (NWP) forecast models. The Advanced Technology Microwave Sounder (ATMS), built by Northrop Grumman, Azusa, CA, USA, is the latest operational microwave sounder series being launched by the United States to provide both temperature and water vapor soundings of the atmosphere. The first ATMS was launched on the Suomi National Polarorbiting Partnership (SNPP) satellite in 2011. This article focuses on the details of the on-orbit performance characterization of the second ATMS, which launched on November 18, 2017, on the Joint Polar Satellite System-1 (JPSS-1) satellite. After successful commissioning, JPSS-1 was renamed National Oceanic and Atmospheric Administration (NOAA)-20 (N-20). We present performance characterizations from prelaunch and postlaunch tests, including the thermal vacuum (TVAC) campaign, and postlaunch activities that contribute to the radiance data products. Significant improvements were found for reflector emissivity, 1/ f noise performance, antenna beam efficiency, inter-channel noise correlation, and scan drive bearing design. New geolocation and pointing algorithms were evaluated. The N-20 ATMS has the same channel set, polarizations, scan geometry, and calibration approach as the SNPP ATMS. The N-20 ATMS meets all performance requirements with margin.

Advanced Technology Microwave Sounder (ATMS)↗
NASA NTRS2008

High Vertically Resolved Atmospheric and Surface/Cloud Parameters Retrieved with Infrared Atmospheric Sounding Interferometer (IASI)

The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated indicating a high vertical structure of atmosphere is retrieved.

Zhou, Daniel K.↗
NASA NTRS2003

Interannual Variability of the Tropical Water Cycle: Capabilities in the TRMM Era and Challenges for GPM

Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30" NE) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Although it is well documented that El Nino-Southern Oscillation (ENSO) events with marked SST changes over the tropical oceans, produce significant regional changes in precipitation, water vapor, and radiative fluxes in the tropics, we still cannot yet adequately quantify the associated net integrated changes to water and heat balance over the entire tropical oceanic or land sectors. Robertson et al., [2001 GRL] for example, showed that substantial disagreement exists among contemporary satellite estimates of interannual variations in tropical rainfall that are associated with SST changes. Berg et al., [2002 J. Climate] have documented the distinct differences between precipitation structure over the eastern and western Pacific ITCZ and noted how various satellite precipitation algorithms may respond quite differently to ENSO modulations of these precipitation regimes. Resolving this uncertainty is important since precipitation and latent heat release variations over land and ocean sectors are key components of the tropical heat balance in its most aggregated form. Rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) averaged over the tropical oceans have not solved this issue and, in fact, show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. In this paper we will focus on findings that uncertainties in microphysical assumptions necessitated by the single-frequency PR measurement pose difficulties for detecting climate-related precipitation signals. Recent work has shown that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series, yet the PR rainfall interannual variability (and attenuation derived predominantly from reflectivity) differs even in sign. We will explore these apparent inconsistencies and detail their impact on estimates of how ENSO events perturb the tropical rainfall. We will place these results in perspective by considering requirements for precipitation accuracy for global climate variability and change studies involving ENSO, monsoon dynamics and variations, and climate model improvement and validation. The discussion will conclude with an assessment of the implications of these findings for Global Precipitation Mission (GPM) requirements.

Robertson, Franklin R.↗
NASA NTRS2005

View angle dependence of cloud optical thicknesses retrieved by MODIS

This study examines whether cloud inhomogeneity influences the view angle dependence of MODIS cloud optical thickness (tau) retrieval results. The degree of cloud inhomogeneity is characterized through the local gradient in 11 microns brightness temperature. The analysis of liquid phase clouds in a one year long global dataset of Collection 4 MODIS data reveals that while optical thickness retrievals give remarkably consistent results for all view directions if clouds are homogeneous, they give much higher tau-values for oblique views than for overhead views if clouds are inhomogeneous and the sun is fairly oblique. For solar zenith angles larger than 55deg, the mean optical thickness retrieved for the most inhomogeneous third of cloudy pixels is more than 30% higher for oblique views than for overhead views. After considering a variety of possible scenarios, the paper concludes that the most likely reason for the increase lies in three-dimensional radiative interactions that are not considered in current, one-dimensional retrieval algorithms. Namely, the radiative effect of cloud sides viewed at oblique angles seems to contribute most to the enhanced tau-values. The results presented here will help understand cloud retrieval uncertainties related to cloud inhomogeneity. They complement the uncertainty estimates that will start accompanying MODIS cloud products in Collection 5 and may eventually help correct for the observed view angle dependent biases.

Marshak, Alexander↗
NASA NTRS1992

Recognition of partially occluded threat objects using the annealed Hopefield network

Recognition of partially occluded objects has been an important issue to airport security because occlusion causes significant problems in identifying and locating objects during baggage inspection. The neural network approach is suitable for the problems in the sense that the inherent parallelism of neural networks pursues many hypotheses in parallel resulting in high computation rates. Moreover, they provide a greater degree of robustness or fault tolerance than conventional computers. The annealed Hopfield network which is derived from the mean field annealing (MFA) has been developed to find global solutions of a nonlinear system. In the study, it has been proven that the system temperature of MFA is equivalent to the gain of the sigmoid function of a Hopfield network. In our early work, we developed the hybrid Hopfield network (HHN) for fast and reliable matching. However, HHN doesn't guarantee global solutions and yields false matching under heavily occluded conditions because HHN is dependent on initial states by its nature. In this paper, we present the annealed Hopfield network (AHN) for occluded object matching problems. In AHN, the mean field theory is applied to the hybird Hopfield network in order to improve computational complexity of the annealed Hopfield network and provide reliable matching under heavily occluded conditions. AHN is slower than HHN. However, AHN provides near global solutions without initial restrictions and provides less false matching than HHN. In conclusion, a new algorithm based upon a neural network approach was developed to demonstrate the feasibility of the automated inspection of threat objects from x-ray images. The robustness of the algorithm is proved by identifying occluded target objects with large tolerance of their features.

Kim, Jung H.↗
NASA NTRS1993

Computer program for analysis of high speed, single row, angular contact, spherical roller bearing, SASHBEAN. Volume 1: User's guide

The computer program SASHBEAN (Sikorsky Aircraft Spherical Roller High Speed Bearing Analysis) analyzes and predicts the operating characteristics of a Single Row, Angular Contact, Spherical Roller Bearing (SRACSRB). The program runs on an IBM or IBM compatible personal computer, and for a given set of input data analyzes the bearing design for it's ring deflections (axial and radial), roller deflections, contact areas and stresses, induced axial thrust, rolling element and cage rotation speeds, lubrication parameters, fatigue lives, and amount of heat generated in the bearing. The dynamic loading of rollers due to centrifugal forces and gyroscopic moments, which becomes quite significant at high speeds, is fully considered in this analysis. For a known application and it's parameters, the program is also capable of performing steady-state and time-transient thermal analyses of the bearing system. The steady-state analysis capability allows the user to estimate the expected steady-state temperature map in and around the bearing under normal operating conditions. On the other hand, the transient analysis feature provides the user a means to simulate the 'lost lubricant' condition and predict a time-temperature history of various critical points in the system. The bearing's 'time-to-failure' estimate may also be made from this (transient) analysis by considering the bearing as failed when a certain temperature limit is reached in the bearing components. The program is fully interactive and allows the user to get started and access most of its features with a minimal of training. For the most part, the program is menu driven, and adequate help messages were provided to guide a new user through various menu options and data input screens. All input data, both for mechanical and thermal analyses, are read through graphical input screens, thereby eliminating any need of a separate text editor/word processor to edit/create data files. Provision is also available to select and view the contents of output files on the monitor screen if no paper printouts are required. A separate volume (Volume-2) of this documentation describes, in detail, the underlying mathematical formulations, assumptions, and solution algorithms of this program.

Aggarwal, Arun K.↗
NASA NTRS2019

A Fast Vector Radiative Transfer Model for the Atmosphere-Ocean Coupled System

To infer atmospheric and oceanic constituent properties from polarimetric observations, an efficient and accurate retrieval algorithm is desirable. In-line radiative transfer calculations are indispensable if a large state vector, including both atmospheric profiles and surface properties, is used to improve retrieval accuracy. However, in-line radiative transfer calculations are usually not computationally efficient for remote sensing applications. Therefore, there is a pressing need to develop an accurate and fast vector radiative transfer model (RTM) to fully utilize satellite polarimetric observations. This paper reports on a fast vector RTM, referred to as TAMU-VRTM, in support of polarimetric remote sensing, which is capable of simulating the Stokes vector values observed at the top of the atmosphere and at the surface by fully considering absorption, scattering, and emission in the atmosphere and ocean. Gaseous absorption is parameterized with respect to gas concentration, temperature, and pressure, by using a regression method applicable to an inhomogeneous atmospheric path. An efficient two-component approach combining the small angle approximation and the adding-doubling method is utilized to solve the vector radiative transfer equation (RTE). The thermal emission component of the RTE solution is obtained by an efficient doubling process. The air-sea interface is treated as a wind-ruffled rough surface in the model to mimic a realistic ocean surface. Several oceanic optical property models are introduced to model ocean inherent optical properties. To demonstrate the applicability of the TAMUVRTM, simulations are compared with satellite observations, and results from other vector radiative transfer methods including benchmarks.

radiative transfer in coupled atmosphere-ocean sys↗