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NASA NTRSDate not supplied

A SATELLITE AGNOSTIC APPROACH TO QUANTIFYING HAIL DAMAGE SWATHS ACROSS THE CENTRAL UNITED STATES AND OTHER AGRICULTURAL REGIONS

Intense thunderstorms can bring damaging winds and large hail to agricultural regions during the prime growing season. In certain cases, large swaths of damage from the wind and hail are left behind and visible to satellite remote sensing instruments. Often times, Earth observing optical remote sensing from low to high spatial resolutions are able to view these damaged swaths. With the large number of moderate to high-resolution instruments in orbit, these damaged areas have potential to be viewed daily. However, during the prime growing season, clouds frequently block the viewing of the land surface by these optical instruments. Space-borne synthetic aperture radar (SAR) instruments allow for the viewing of the land surface in most weather conditions, but instead measure backscatter as opposed to optical sensors measuring reflected or emitted radiation. Additionally, the number of SAR instruments with free and open data lags behind the number of optical sensors. This paper describes the development of a methodology that attempts to characterize hail damaged swaths, through independent use of multiple optical and SAR platforms. This satellite-agnostic approach will focus statistical analysis by comparing undamaged areas to suspected damaged areas by using commonly derived indices from optical instruments and SAR backscatter from multiple polarizations.

Jordan R Bell↗
DOE OSTI2021

Rahasak—Scalable blockchain architecture for enterprise applications

Blockchain-based decentralized infrastructure has been adapted in various industries to handle the sensitive data in a privacy-preserving manner without trusting third parties. However, integrating state-of-the-art blockchain platforms with the scalable, enterprise-level applications result in several challenges. Current blockchain platforms do not support high transaction throughput, lack high scalability, and cannot provide real-time transaction processing and back-pressure operation handling in high transaction throughput applications(e.g Big data, IoT). In this paper, we propose a novel permissioned blockchain platform “Rahasak” for highly scalable, enterprise applications. Rahasak blockchain adopts the Apache Kafka-based consensus on top of a “Validate-Execute-Group” blockchain architecture to handle realtime transaction execution on the blockchain. The architecture is equipped with a functional programming and actor-based smart contract platform that enables concurrent execution of transactions in the blockchain. Rahasak supports high transaction throughput, high scalability, concurrent transaction execution, data analytics features. Finally, with Rahasak, we make blockchain more scalable, secure, structured and meaningful for further data analytics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

HIRIS, the instrument and its science

The High Resolution Imaging Spectrometer (HIRIS) is a facility instrument slated for flight on the second EOS series AM platforms. HIRIS is designed to acquire 24 km wide, 30 m pixel images in 192 spectral bands simultaneously in the 0.4-2.45 micron wavelength region. With pointing mirrors it can sample any place on Earth, except the poles, every 2 days. HIRIS operates at the intermediate scale between the human and the global and therefore links studies of Earth surface processes to global monitoring carried out by lower resolution instruments. So far, over 50 science data products from HIRIS images have been identified in the fields of atmospheric gases, clouds, snow and ice, water, vegetation, and rocks and soils. The key attribute of imaging spectrometry that makes it possible to derive quantitative information from the data is the large number of contiguous, spectral bands. Therefore, spectrum-matching techniques can be applied. Such techniques are not possible with present-day, multispectral scanner data.

Goetz, Alexander F. H.↗
NASA NTRS2010

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

Several multisensor simulator packages are being developed by different research groups across the world. Such simulator packages [e.g., COSP , CRTM, ECSIM, RTTO, ISSARS (under development), and SDSU (this article), among others] share overall aims, although some are targeted more on particular satellite programs or specific applications (for research purposes or for operational use) than others. The SDSU or Satellite Data Simulator Unit is a general-purpose simulator composed of Fortran 90 codes and applicable to spaceborne microwave radiometer, radar, and visible/infrared imagers including, but not limited to, the sensors listed in a table. That shows satellite programs particularly suitable for multisensor data analysis: some are single satellite missions carrying two or more instruments, while others are constellations of satellites flying in formation. The TRMM and A-Train are ongoing satellite missions carrying diverse sensors that observe clouds and precipitation, and will be continued or augmented within the decade to come by future multisensor missions such as the GPM and Earth-CARE. The ultimate goals of these present and proposed satellite programs are not restricted to clouds and precipitation but are to better understand their interactions with atmospheric dynamics/chemistry and feedback to climate. The SDSU's applicability is not technically limited to hydrometeor measurements either, but may be extended to air temperature and humidity observations by tuning the SDSU to sounding channels. As such, the SDSU and other multisensor simulators would potentially contribute to a broad area of climate and atmospheric sciences. The SDSU is not optimized to any particular orbital geometry of satellites. The SDSU is applicable not only to low-Earth orbiting platforms as listed in Table 1, but also to geostationary meteorological satellites. Although no geosynchronous satellite carries microwave instruments at present or in the near future, the SDSU would be useful for future geostationary satellites with a microwave radiometer and/or a radar aboard, which could become more feasible as engineering challenges are met. In this short article, the SDSU algorithm architecture and potential applications are reviewed in brief.

Masunaga, Hirohiko↗
NASA NTRS2013

Radar Range Sidelobe Reduction Using Adaptive Pulse Compression Technique

Pulse compression has been widely used in radars so that low-power, long RF pulses can be transmitted, rather than a highpower short pulse. Pulse compression radars offer a number of advantages over high-power short pulsed radars, such as no need of high-power RF circuitry, no need of high-voltage electronics, compact size and light weight, better range resolution, and better reliability. However, range sidelobe associated with pulse compression has prevented the use of this technique on spaceborne radars since surface returns detected by range sidelobes may mask the returns from a nearby weak cloud or precipitation particles. Research on adaptive pulse compression was carried out utilizing a field-programmable gate array (FPGA) waveform generation board and a radar transceiver simulator. The results have shown significant improvements in pulse compression sidelobe performance. Microwave and millimeter-wave radars present many technological challenges for Earth and planetary science applications. The traditional tube-based radars use high-voltage power supply/modulators and high-power RF transmitters; therefore, these radars usually have large size, heavy weight, and reliability issues for space and airborne platforms. Pulse compression technology has provided a path toward meeting many of these radar challenges. Recent advances in digital waveform generation, digital receivers, and solid-state power amplifiers have opened a new era for applying pulse compression to the development of compact and high-performance airborne and spaceborne remote sensing radars. The primary objective of this innovative effort is to develop and test a new pulse compression technique to achieve ultrarange sidelobes so that this technique can be applied to spaceborne, airborne, and ground-based remote sensing radars to meet future science requirements. By using digital waveform generation, digital receiver, and solid-state power amplifier technologies, this improved pulse compression technique could bring significant impact on future radar development. The novel feature of this innovation is the non-linear FM (NLFM) waveform design. The traditional linear FM has the limit (-20 log BT -3 dB) for achieving ultra-low-range sidelobe in pulse compression. For this study, a different combination of 20- or 40-microsecond chirp pulse width and 2- or 4-MHz chirp bandwidth was used. These are typical operational parameters for airborne or spaceborne weather radars. The NLFM waveform design was then implemented on a FPGA board to generate a real chirp signal, which was then sent to the radar transceiver simulator. The final results have shown significant improvement on sidelobe performance compared to that obtained using a traditional linear FM chirp.

Li, Lihua↗
DOE OSTI2021

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the atmosphere boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement Southern Great Plains site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential-absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to obtain a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near the boundary-layer top. Furthermore, we also explore how differences in retrievals may affect results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval shows some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A cell-based Papain-like Protease (PLpro) activity assay for rapid detection of active SARS-CoV-2 infections and antivirals

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants are a continuous threat to human life. An urgent need remains for simple and fast tests that reliably detect active infections with SARS-CoV-2 and its variants in the early stage of infection. Here we introduce a simple and rapid activity-based diagnostic (ABDx) test that identifies SARS-CoV-2 infections by measuring the activity of a viral enzyme, Papain-Like protease (PLpro). The test system consists of a peptide that fluoresces when cleaved by SARS PLpro that is active in crude, unprocessed lysates from human tongue scrapes and saliva. Test results are obtained in 30 minutes or less using widely available fluorescence plate readers, or a battery-operated portable instrument for on-site testing. Proof-of-concept was obtained in a study on clinical specimens collected from patients with COVID-19 like symptoms who tested positive (n = 10) or negative (n = 10) with LIAT RT-PCR using nasal mid turbinate swabs. When saliva from these patients was tested with in-house endpoint RT-PCR, 17 were positive and only 5 specimens were negative, of which 2 became positive when tested 5 days later. PLpro activity correlated in 17 of these cases (3 out of 3 negatives and 14 out of 16 positives, with one invalid specimen). Despite the small number of samples, the agreement was significant (p value = 0.01). Two false negatives were detected, one from a sample with a late Ct value of 35 in diagnostic RT-PCR, indicating that an active infection was no longer present. The PLpro assay is easily scalable and expected to detect all viable SARS-CoV-2 variants, making it attractive as a screening and surveillance tool. Additionally, we show feasibility of the platform as a new homogeneous phenotypic assay for rapid screening of SARS-CoV-2 antiviral drugs and neutralizing antibodies.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1991

High Resolution Imaging Spectrometer (HIRIS): Science and Instrument

The High Resolution Imaging Spectrometer (HIRIS) is a facility instrument slated for flight on the second of the EOS-A series of platforms. HIRIS is designed to acquire 24-km wide, 30-m pixel images in 192 spectral bands simultaneously in the 0.4-2.45-micrometer wavelength region. With pointing mirrors it can sample any place on Earth, except the poles, every two days. HIRIS operates at the intermediate scale between the human and the global and therefore links studies of Earth surface processes to global monitoring carried out by lower-resolution instruments. So far, over 50 science data products from HIRIS images have been identified in the fields of atmospheric gases, clouds, snow and ice, water, vegetation, and rocks and soils. The key attribute of imaging spectrometry that makes it possible to derive quantitative information from the data is the large number of contiguous spectral bands. Therefore spectrum matching techniques can be applied. Such techniques are not possible with present-day, multispectral scanner data.

Goetz, Alexander F. H.↗
NASA NTRS2007

An EOF Iteration Approach for Obtaining Homogeneous Radiative Fluxes from Satellites Observations

Conventional observations of climate parameters are sparse in space and/or in time and the representativeness of such information needs to be optimized. Observations from satellites provide improved spatial coverage than point observations however they pose new challenges for obtaining homogeneous coverage. Surface radiative fluxes, the forcing functions of the hydrologic cycle and biogeophysical processes, are now becoming available from global scale satellite observations. They are derived from independent satellite platforms and sensors that differ in temporal and spatial resolution and in the size of the footprint from which information is derived. Data gaps, degraded spatial resolution near boundaries of geostationary satellites, and different viewing geometries in areas of satellite overlap, could result in biased estimates of radiative fluxes. In this study, discussed will be issues related to the sources of inhomogeneity in surface radiative fluxes as derived from satellites; development of an approach to obtain homogeneous data sets; and application of the methodology to the widely used International Satellite Cloud Climatology Project (ISCCP) data that currently serve as a source of information for deriving estimates of surface and top of the atmosphere radiative fluxes. Introduced is an Empirical Orthogonal Function (EOF) iteration scheme for homogenizing the fluxes. The scheme is evaluated in several ways including comparison of the inferred radiative fluxes against ground observations, both before and after the EOF approach is applied. On the average, the latter reduces the rms error by about 2-3 W/m2.

Zhang, Banglin↗
DOE OSTI2024

Modeling diurnal and annual ethylene generation from solar-driven electrochemical CO 2 reduction devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards reducing carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimentally-determined CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. Here we simulated gaseous diurnal product outputs with and without the effects of ambient temperature. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne per year at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

14 SOLAR ENERGY↗
DOE OSTI2021

University of Colorado and Black Swift Technologies RPAS-based measurements of the lower atmosphere during LAPSE-RATE

Abstract. Between 14 and 20 July 2018, small remotely piloted aircraft systems (RPASs) were deployed to the San Luis Valley of Colorado (USA) together with a variety of surface-based remote and in situ sensors as well as radiosonde systems as part of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). The observations from LAPSE-RATE were aimed at improving our understanding of boundary layer structure, cloud and aerosol properties, and surface–atmosphere exchange and provide detailed information to support model evaluation and improvement work. The current paper describes the observations obtained using four different types of RPASs deployed by the University of Colorado Boulder and Black Swift Technologies. These included the DataHawk2, the Talon and the TTwistor (University of Colorado), and the S1 (Black Swift Technologies). Together, these aircraft collected over 30 h of data throughout the northern half of the San Luis Valley, sampling altitudes between the surface and 914 m a.g.l. Data from these platforms are publicly available through the Zenodo archive and are co-located with other LAPSE-RATE data as part of the Zenodo LAPSE-RATE community (https://zenodo.org/communities/lapse-rate/, last access: 27 May 2021). The primary DOIs for these datasets are https://doi.org/10.5281/zenodo.3891620 (DataHawk2, de Boer et al., 2020a, e), https://doi.org/10.5281/zenodo.4096451 (Talon, de Boer et al., 2020d), https://doi.org/10.5281/zenodo.4110626 (TTwistor, de Boer et al., 2020b), and https://doi.org/10.5281/zenodo.3861831 (S1, Elston and Stachura, 2020).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1974

Preliminary results of fisheries investigation associated with Skylab-3

The author has identified the following significant results. This investigation is to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. Data from the test area in the northeastern Gulf of Mexico has made possible the identification of fisheries significant environmental parameters for white marlin. Predictive models based on catch data and surface truth information have been developed and have demonstrated potential for reducing search significantly by identifying areas which have a high probability of being productive. Three of the parameters utilized by the model, chlorophyll-a, sea surface temperature, and turbidity have been inferred from aircraft sensor data. Cloud cover and delayed receipt have inhibited the use of Skylab data. The first step toward establishing the feasibility of utilizing remotely sensed data to assess amd monitor the distribution of ocean gamefish has been taken with the successful identification of fisheries significant oceanographic parameters and the demonstration of the capability of measuring most of these parameters remotely.

Savastano, K. J.↗
DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗
NASA NTRS1999

Science Writer's Guide to Landsat 7

The Earth Observing System (EOS), the centerpiece of NASA's Earth science program, is a suite of spacecraft and interdisciplinary science investigations dedicated to advancing our understanding of global change. The flagship EOS satellite, Terra (formerly EOS AM-1), scheduled for launch in July 1999, will provide key measurements of the physical and radiative properties of clouds; air-land and air-sea exchanges of energy, carbon, and water; trace gases; and volcanoes. Flying in formation with Terra, Landsat 7 will make global high spatial resolution measurements of land surface and surrounding coastal regions. Other upcoming EOS missions and instruments include QuikSCAT, to collect sea surface wind data; the Stratospheric Gas and Aerosol Experiment (SAGE III), to create global profiles of key atmospheric gases; and the Active Cavity Radiometer Irradiance Monitors (ACRIM) to measure the energy output of the Sun. The second of the major, multi-instrument EOS platforms, PM-1, is scheduled for launch in 2000. Interdisciplinary research projects sponsored by EOS use specific Earth science data sets for a broader investigation into the function of Earth systems. Current EOS research spans a wide range of sciences, including atmospheric chemistry, hydrology, land use, and marine ecosystems. The EOS program has been managed since 1990 by the Goddard Space Flight Center in Greenbelt, Md., for NASA's Office of Earth Science in Washington, D. C. Additional information on the program can be found on the EOS Project Science Office Web site (http://eospso.gsfc.nasa.gov).

Source record↗
NASA NTRS2004

Assessment of Clear Sky Radiative Forcing in the Caribbean Region Using an Aerosol Dispersion Model and Ground Radiometry During Puerto Rico Dust Experiment

This study investigates the surface and top of the atmosphere solar radiative forcing by long-range transport of Saharan dust. The calculations of radiative forcing are based on measurements collected in the Puerto Rico Dust Experiment (PRIDE) carried out during July, 2000. The purpose of the experiment was the characterization of the Saharan dust plume, which frequently reaches the Caribbean region during the summer. The experiment involved the use of three approaches to study the plume: space and ground based remote sensing, airborne and ground based in-situ measurements and aerosol dispersion modeling. The diversity of measuring platforms provides an excellent opportunity for determination of the direct effect of dust on the clear sky radiative forcing. Specifically, comparisons of heating rates, surface and TOA fluxes derived from the Navy global aerosol dispersion model NAAPS (NRL Aerosol Analysis and Prediction System) and actual measurements of fluxes from ground and space based platforms are shown. In addition, the direct effect of dust on the clear sky radiative forcing is modeled. The extent and time of evolution of the radiative properties of the plume are computed with the aerosol concentrations modeled by NAAPS. Standard aerosol parameterizations, as well as in-situ composition and size distributions measured during PRIDE, are utilized to compute the aerosol optical depth, single scattering albedo and asymmetry factor. Radiative transfer computations are done with an in-house modified spectral radiative transfer code (Fu-Liou). The code includes gas absorption and cloud particles (ice and liquid phase) and it allows the input of meteorological data. The code was modified to include modules for the aerosols contribution to the calculated fluxes. This comparison study helps to narrow the current uncertainty in the dust direct radiative forcing, as recently reported in the 2001 IPCC assessment.

Gasso, Santiago↗
NASA NTRS2019

Evolving HPC and Application Design Toward a Coupled Data Assimilation System at NASA Suitable for Emerging Exascale Platforms

The prediction capabilities of global models have continuously evolved from the traditional medium-range global weather prediction application to span scales in support of hourly prediction of convective scale storms to seasonal Earth system prediction. This evolution has increased the demands on the system infrastructure design and workflow to achieve the required performance on modern high-performance computing (HPC) platforms. The planned evolution of the Goddard Earth Observing System (GEOS) modeling and assimilation system will stress the capabilities of conventional HPC overwhelming the available compute cycles at the NASA Center for Climate Simulation (NCCS) at the NASA Goddard Space Flight Center in the coming 5-10 years. This has led to the re-design of key elements of the assimilation and modeling systems to achieve significant gains in performance on anticipated Exacale platforms. The transition of the assimilation system to the Joint Effort for Data assimilation Integration (JEDI) framework has positioned GEOS to exploit new efficient algorithms for data assimilation (DA) in a fully-coupled Earth system context. The suitability of the GEOS model to leverage a domain specific language (DSL) approach and artificial intelligence (AI) is being explored to accelerate computational performance and data exchange efficiency of the coupled Earth system model. The storage and processing of large data volumes produced by these advance systems is being redesigned with a data-centric cloud-based approach. We will highlight the recent efforts in these areas and emphasize the demand for further development and re-design to achieve the science objectives in support of NASA's Earth system modeling and assimilation missions.

Putman, Bill↗
NASA NTRS1998

Contributions of Nimbus 7 TOMS Data to Volcanic Study and Hazard Mitigation

Nimbus TOMS data have led to advancements among many volcano-related scientific disciplines, from the initial ability to quantify SO2 clouds leading to derivations of eruptive S budgets and fluxes, to tracking of individual clouds, assessing global volcanism and atmospheric impacts. Some of the major aspects of TOMS-related research, listed below, will be reviewed and updated: (1) Measurement of volcanic SO2 clouds: Nimbus TOMS observed over 100 individual SO2 clouds during its mission lifetime; large explosive eruptions are now routinely and reliably measured by satellite. (2) Eruption processes: quantification of SO2 emissions have allowed assessments of eruption sulfur budgets, the evaluation of "excess" sulfur, and inferences of H2S emissions. (3) Detection of ash: TOMS data are now used to detect volcanic particulates in the atmosphere, providing complementary analyses to infrared methods of detection. Paired TOMS and AVHRR studies have provided invaluable information on volcanic cloud compositions and processes. (4) Cloud tracking and hazard mitigation: volcanic clouds can be considered gigantic tracers in the atmosphere, and studies of the fates of these clouds have led to new knowledge of their physical and chemical dispersion in the atmosphere for predictive models. (5) Global trends: the long term data set has provided researchers an unparalleled record of explosive volcanism, and forms a key component in assessing annual to decadal trends in global S emissions. (6) Atmospheric impacts: TOMS data have been linked to independent records of atmospheric change, in order to compare cause and effect processes following a massive injection of SO2 into the atmosphere. (7) Future TOMS instruments and applications: Nimbus TOMS has given way to new satellite platforms, with several wavelength and resolution modifications. New efforts to launch a geostationary TOMS could provide unprecedented observations of volcanic activity.

Krueger, Arlin J.↗
NASA NTRS2002

Embedded Real-Time Linux for Instrument Control and Data Logging

When I moved to the west. coast to take a job at NASA's Ames Research Center in Mountain View, CA, I was impressed with the variety of equipment and software which scientists at the center use to conduct their research. was happy to find that I was just as likely to see a machine running Lenox as one running Windows in the offices and laboratories of NASA Ames (although many people seem to use Moos around here). I was especially happy to find that the particular group with whom I was going to work, the Atmospheric Physics Branch at Ames, relied almost entirely on Lenox machines for their day-to-day work. So it was no surprise that when it was time to construct a new control system for one of their most important pieces of hardware, a switch from an unpredictable DOS-based platform to an Embedded Linux-based one was a decision easily made. The system I am working on is called the Solar Spectral Flux Radiometer (SSFR), a PC-104 based system custom-built by Dr. Warren Gore at Ames. Dr. Gore, Dr. Peter Pilewskie, Dr. Maura Robberies and Larry Pezzolo use the SSFR in their research. The team working on the controller project consists of Dr. Gore, John Pommier, and myself. The SSFR is used by the ,cities Atmospheric Radiation Group to measure solar spectral irradiance at moderate resolution to determine the radiative effect of clouds, aerosols, and gases on climate, and also to infer the physical properties of aerosols and clouds. Two identical SSFR's have been built and successfully deployed in three field missions: 1) the Department of Energy Atmospheric Radiation Measurement (ARM) Enhanced Shortwave Experiment (ARESE) II in February/March, 2000; 2) the Puerto Rico Dust Experiment (PRIDE) in July, 2000; and 3) the South African Regional Science Initiative (SAFARI) in August/September, 2000. Additionally, the SSFR was used to acquire water vapor spectra using the Ames Diameter base-path multiple-reflection absorption cell in a laboratory experiment.

Clanton, Sam↗