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NASA NTRS2000

Factors Controlling Upper-Troposphere Water Vapor

The seasonal changes of the upper-tropospheric humidity are studied with the water vapor data from the Microwave Limb Sounder on the National Aeronautics and Space Administration's Upper Atmosphere Research Satellite and the winds and vertical velocity data obtained from the European Centre for Medium-Range Weather Forecasts. Using the same algorithm for vertical transport as that used for horizontal transport (by Zhu and Newell), the authors find that the moisture in the tropical upper troposphere may be increased mainly by intensified local convection in a small portion, less than 10%, of the whole area between 40 degrees S and 40 degrees N. The contribution of large-scale background circulations and divergence of horizontal transport is relatively small in these regions. These dynamic processes cannot be revealed by the traditional analyses of moisture fluxes. The negative response suggested by Lindzen, with enhanced convection in the Tropics being accompanied by subsidence drying in the subtropics, also exists, but the latter does not apparently dominate in the moisture budget.

Zhu, Yong↗

NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

Harrivel, Angela↗

NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Harrivel, Angela↗

NASA NTRS2013

Faster Array Training and Rapid Analysis for a Sensor Array Intended for an Event Monitor in Air

Environmental monitoring, in particular, air monitoring, is a critical need for human space flight. Both monitoring and life support systems have needs for closed loop process feedback and quality control for environmental factors. Monitoring protects the air environment and water supply for the astronaut crew and different sensors help ensure that the habitat falls within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the farther the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. There is an acknowledged need for an event monitor which samples the air continuously and provides near real-time information on changes in the air. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. We are working on a sensor array and new algorithms that will incorporate transient sensor responses in the analysis. Preliminary work has already showed more rapid quantification and identification of analytes and the potential for faster training time of the array. We will look at some of the factors that contribute to demonstrating faster training time for the array. Faster training will decrease the integrated sensor exposure to training analytes, which will also help extend sensor lifetime.

sensing array↗

NASA NTRS2000

KDD Services at the Goddard Earth Sciences Distributed Active Archive Center

NASA's Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) processes, stores and distributes earth science data from a variety of remote sensing satellites. End users of the data range from instrument scientists to global change and climate researchers to federal agencies and foreign governments. Many of these users apply data mining techniques to large volumes of data (up to 1 TB) received from the GES DAAC. However, rapid advances in processing power are enabling increases in data processing that are outpacing tape drive performance and network capacity. As a result, the proportion of data that can be distributed to users continues to decrease. As mitigation, we are migrating more data mining and mining preparation activities into the data center in order to reduce the data volume that needs to be distributed and to offer the users a more useful and manageable product. This migration of activities faces a number of technical and human-factor challenges. As data reduction and mining algorithms are normally quite specific to the user's research needs, the user's algorithm must be integrated virtually unchanged into the archive environment. Also, the archive itself is busy with everyday data archive and distribution activities and cannot be dedicated to, or even impacted by, the mining activities. Therefore, we schedule KDD 'campaigns' (similar to reprocessing campaigns), during which we schedule a wholesale retrieval of specific data products, offering users the opportunity to extract information from the data being retrieved during the campaign.

Lynnes, Christopher↗

NASA NTRS2022

Optimized Umkehr Profile Algorithm for Ozone Trend Analyses

The long-term record of Umkehr measurements from four NOAA Dobson spectrophotometers was reprocessed after updates to the instrument calibration procedures. In addition, a new data quality-control tool was developed for the Dobson automation software (WinDobson). This paper presents a comparison of Dobson Umkehr ozone profiles from NOAA ozone network stations (Boulder, OHP, MLO, Lauder) against several satellite records, including Aura Microwave Limb Sounder (MLS; ver. 4.2), and combined SBUV and OMPS records (NASA AGG and NOAA COH). A subset of satellite data is selected to match Dobson Umkehr observations at each station spatially (distance less than 200 km) and temporally (within 24 hours). Umkehr Averaging Kernels (AKs) are applied to vertically smooth all overpass satellite profiles prior to comparisons. The station Umkehr record consists of several instrumental records, which have different optical characterizations, and thus instrument-specific stray light contributes to the data processing errors and creates step changes in the record. This work evaluates the overall quality of Umkehr long-term measurements at NOAA ground-based stations and assesses the impact of the instrumental changes on the stability of the Umkehr ozone profile record. This paper describes a method designed to correct biases and discontinuities in the retrieved Umkehr profile that originate from the Dobson calibration process, repair, or optical realignment of the instrument. The M2GMI and GMI CTM ozone profile model output matched to station location and date of observation is used to evaluate instrumental step changes in the Umkehr record. Homogenization of the Umkehr record and discussion of the apparent stray light error in retrieved ozone profiles are the focus of this paper. Homogenization of ground-based records is of great importance for studies of long-term ozone trends and climate change.

Umkehr↗

DOE OSTI2026

Data‐Efficient Generation of Synthetic Microstructures of Polymer‐Bonded Energetic Material With Fine‐Tuned Stable Diffusion

Among current deep learning approaches for synthetic image generation, diffusion-based models stand out in terms of algorithmic stability and ability to retain high-fidelity image features with detailed resolution. Here, in this work, we employ Dreambooth, a method for fine-tuning Stable Diffusion, on X-ray CT images of microstructure of the polymer-bonded form (PBX) of a commonly used high explosive, Pentaerythritol tetranitrate (PETN), which yields generative models for creating synthetic PBX images. The models developed here represent five classes (or ‘lots’) of microstructures and demonstrate successful generation of images of each class with high fidelity, as verified by computed classification accuracy of ∼ 94% or higher. Data augmentation afforded by such image synthesis can be used to more reliably decipher underlying statistics, build processing-structure correlations, recognize off-normal structural anomalies, and identify age-related changes. Ideas related to converting image data into appropriate density mapping and performing mesoscale simulation or surrogate modeling of detonation are also discussed.

Dreambooth↗

NASA NTRS2013

Orion MPCV GN and C End-to-End Phasing Tests

End-to-end integration tests are critical risk reduction efforts for any complex vehicle. Phasing tests are an end-to-end integrated test that validates system directional phasing (polarity) from sensor measurement through software algorithms to end effector response. Phasing tests are typically performed on a fully integrated and assembled flight vehicle where sensors are stimulated by moving the vehicle and the effectors are observed for proper polarity. Orion Multi-Purpose Crew Vehicle (MPCV) Pad Abort 1 (PA-1) Phasing Test was conducted from inertial measurement to Launch Abort System (LAS). Orion Exploration Flight Test 1 (EFT-1) has two end-to-end phasing tests planned. The first test from inertial measurement to Crew Module (CM) reaction control system thrusters uses navigation and flight control system software algorithms to process commands. The second test from inertial measurement to CM S-Band Phased Array Antenna (PAA) uses navigation and communication system software algorithms to process commands. Future Orion flights include Ascent Abort Flight Test 2 (AA-2) and Exploration Mission 1 (EM-1). These flights will include additional or updated sensors, software algorithms and effectors. This paper will explore the implementation of end-to-end phasing tests on a flight vehicle which has many constraints, trade-offs and compromises. Orion PA-1 Phasing Test was conducted at White Sands Missile Range (WSMR) from March 4-6, 2010. This test decreased the risk of mission failure by demonstrating proper flight control system polarity. Demonstration was achieved by stimulating the primary navigation sensor, processing sensor data to commands and viewing propulsion response. PA-1 primary navigation sensor was a Space Integrated Inertial Navigation System (INS) and Global Positioning System (GPS) (SIGI) which has onboard processing, INS (3 accelerometers and 3 rate gyros) and no GPS receiver. SIGI data was processed by GN&C software into thrust magnitude and direction commands. The processing changes through three phases of powered flight: pitchover, downrange and reorientation. The primary inputs to GN&C are attitude position, attitude rates, angle of attack (AOA) and angle of sideslip (AOS). Pitch and yaw attitude and attitude rate responses were verified by using a flight spare SIGI mounted to a 2-axis rate table. AOA and AOS responses were verified by using a data recorded from SIGI movements on a robotic arm located at NASA Johnson Space Center. The data was consolidated and used in an open-loop data input to the SIGI. Propulsion was the Launch Abort System (LAS) Attitude Control Motor (ACM) which consisted of a solid motor with 8 nozzles. Each nozzle has active thrust control by varying throat area with a pintle. LAS ACM pintles are observable through optically transparent nozzle covers. SIGI movements on robot arm, SIGI rate table movements and LAS ACM pintle responses were video recorded as test artifacts for analysis and evaluation. The PA-1 Phasing Test design was determined based on test performance requirements, operational restrictions and EGSE capabilities. This development progressed during different stages. For convenience these development stages are initial, working group, tiger team, Engineering Review Team (ERT) and final.

Neumann, Brian C.↗

NASA NTRS2016

Mapping of Spacecraft Atmosphere Monitor Signal to Major Constituent Abundances

The Spacecraft Atmosphere Monitor (S.A.M.) follows the JPL’s commitment to introduce and develop next-generation instrumentation concepts for sensing the air quality on manned space flights via continuous sampling, measuring, and reporting in 2s intervals on all gaseous pollutants. The S.A.M. will have two modes of operation: the Major Constituent Analysis (MCA) mode and the Trace Gas Analysis (TGA) mode. The MCA mode will report on molecular analytes such as CH4, H2O, N2, O2, Ar, and CO2 while the TGA mode will acquire minute amounts of volatile organic compounds. Both modes assess the composition of the ambient air with twenty full mass spectra per second giving rise to a substantial amount of data to be processed by a set of small footprint software stacks hosted by an on-board computer. Mass spectra will be accumulated as the number of counts recorded in a given mass-to-charge channel and converted into the absolute abundances of detected species using an efficient algorithm. The decomposition algorithm contains four units: peak identification, mass calibration, background and dead time correction, and an abundance analysis unit. The abundance analysis module identifies target species through their characteristic fragmentation patterns in the presence of molecular isobars, such as CO and N2. For example, in order to identify N2 analyte, the code will simultaneously monitor abundance ratios of the 14, 28 and 29 Th signals and will adapt to any instability caused by a decrease in ambient pressure or changes in humidity. This requirement becomes critical for instruments designed to monitor the near real-time quality of cabin air and promptly provide accurate feedbacks.

Nikolic, D.↗

NASA NTRS2018

Dynamic Shared Computing Resources for Multi-Robot Mars Exploration

The NASA roadmap for 2020 and beyond includes several key technologies which will have a game-changing impact on planetary exploration. The ﬁrst of these is High Performance Spaceﬂight Computing (HPSC), which will provide orders of magnitude increases in processing power for next-generation rovers and orbiters (Doyle et al. 2013). The second is Delay Tolerant Networking, which overlays the Deep Space Network, providing internet-like abstractions and store-forward to route data through intermittent delays in connectivity. The third is a trend toward small, co-dependent robots included in ﬂagship missions (MarCO, PUFFER, and Mars Heli). Taken together, these imply an increasing amount of communication and computing heterogeneity on Mars in coming decades. Motivated by these technological trends, we study the concept of Mars on-site shared analysis, information, and communication (MOSAIC) for Mars exploration. The key algorithmic problem associated with MOSAIC networks is simultaneous scheduling of computation, communication, and caching of data, which we illustrate using the three scenarios. We present models, preliminary solutions, and simulation results for two scenarios, showing how mission efﬁciency relates to communication bandwidth, processing power, geography of the environment, and optimal scheduling of computation, communication, and data caching. The third scenario illustrates future directions of this work.

Chien, Steve↗

NASA NTRS2004

Toward a Global Map of Raindrop Size Distributions: Rain-Type Classification and Its Implications for Validating Global Rainfall Products - Part 1

Variability in the global distribution of precipitation is recognized as a key element in assessing the impact of climate change for life on earth. The response of precipitation to climate forcings is, however, poorly understood because of discrepancies in the magnitude and sign of climatic trends in satellite-based rainfall estimates. Quantifying and ultimately removing these biases is critical for studying the response of the hydrologic cycle to climate change. In addition, estimates of random errors owing to variability in algorithm assumptions on local spatial and temporal scales are critical for establishing how strongly their products should be weighted in data assimilation or model validation applications and for assigning a level of confidence to climate trends diagnosed from the data. This paper explores the potential for refining assumed drop size distributions (DSDs) in global radar rainfall algorithms by establishing a link between satellite observables and information gleaned from regional validation experiments where polarimetric radar, Doppler radar, and disdrometer measurements can be used to infer raindrop size distributions. By virtue of the limited information available in the satellite retrieval framework, the current method deviates from approaches adopted in the ground-based radar community that attempt to relate microphysical processes and resultant DSDs to local meteorological conditions. Instead, the technique exploits the fact that different microphysical pathways for rainfall production are likely to lead to differences in both the DSD of the resulting raindrops and the three-dimensional structure of associated radar reflectivity profiles. Objective rain-type classification based on the complete three-dimensional structure of observed reflectivity profiles is found to partially mitigate random and systematic errors in DSDs implied by differential reflectivity measurements. In particular, it is shown that vertical and horizontal reflectivity structure obtained from spaceborne radar can be used to reproduce significant differences in Z(sub dr) between the easterly and westerly climate regimes observed in the Tropical Rainfall Measuring Mission Large-scale Biosphere-Atmosphere (TRMM-LBA) field experiment as well as the even larger differences between Amazonian rainfall and that observed in eastern Colorado. As such, the technique offers a potential methodology for placing locally observed DSD information into a global framework.

L'Ecuyer, Tristan S.↗

NASA NTRS2008

Image Compression Algorithm Altered to Improve Stereo Ranging

A report discusses a modification of the ICER image-data-compression algorithm to increase the accuracy of ranging computations performed on compressed stereoscopic image pairs captured by cameras aboard the Mars Exploration Rovers. (ICER and variants thereof were discussed in several prior NASA Tech Briefs articles.) Like many image compressors, ICER was designed to minimize a mean-square-error measure of distortion in reconstructed images as a function of the compressed data volume. The present modification of ICER was preceded by formulation of an alternative error measure, an image-quality metric that focuses on stereoscopic-ranging quality and takes account of image-processing steps in the stereoscopic-ranging process. This metric was used in empirical evaluation of bit planes of wavelet-transform subbands that are generated in ICER. The present modification, which is a change in a bit-plane prioritization rule in ICER, was adopted on the basis of this evaluation. This modification changes the order in which image data are encoded, such that when ICER is used for lossy compression, better stereoscopic-ranging results are obtained as a function of the compressed data volume.

Kiely, Aaron↗

NASA NTRS2011

Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields

Lighter-than-air vehicles such as hot-air balloons have been proposed for exploring Saturn s moon Titan, as well as other bodies with significant atmospheres. For these vehicles to navigate effectively, it is critical to incorporate the effects of surrounding wind fields, especially as these winds will likely be strong relative to the control authority of the vehicle. Predictive models of these wind fields are available, and previous research has considered problems of planning paths subject to these predicted forces. However, such previous work has considered the wind fields as known a priori, whereas in practical applications, the actual wind vector field is not known exactly and may deviate significantly from the wind velocities estimated by the model. A probabilistic 3D path-planning algorithm was developed for balloons to use uncertain wind models to generate time-efficient paths. The nominal goal of the algorithm is to determine what altitude and what horizontal actuation, if any is available on the vehicle, to use to reach a particular goal location in the least expected time, utilizing advantageous winds. The solution also enables one to quickly evaluate the expected time-to-goal from any other location and to avoid regions of large uncertainty. This method is designed for balloons in wind fields but may be generalized for any buoyant vehicle operating in a vector field. To prepare the planning problem, the uncertainty in the wind field is modeled. Then, the problem of reaching a particular goal location is formulated as a Markov decision process (MDP) using a discretized space approach. Solving the MDP provides a policy of what actuation option (how much buoyancy change and, if applicable, horizontal actuation) should be selected at any given location to minimize the expected time-to-goal. The results provide expected time-to-goal values from any given location on the globe in addition to the action policy. This stochastic approach can also provide insights not accessible by deterministic methods; for example, one can evaluate variability and risk associated with different scenarios, rather than only viewing the expected outcome.

Wolf, Michael↗

DOE OSTI2024

Development of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) Value-Added Product Based on the lagtraj Framework

The Atmospheric Radiation Measurement (ARM) large-scale forcing data developed based on the constrained variational analysis (VARANAL) value-added product (VAP) (Zhang and Lin 1997, Zhang et al. 2001, Xie et al. 2004, Tang et al. 2019) has been widely used for single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LESs) to understand and improve physical processes in models. Recently, the U.S. Department of Energy (DOE) ARM user facility conducted several major field campaigns using ship-based moving observational platforms. For example, the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign focused on the role of subtropical marine-boundary layer (MBL) clouds, and the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign aimed to improve understanding of the coupled climate systems in the Arctic. Observations from moving platforms are critical to provide a comprehensive characterization of coupled-system processes associated with all stages of the cloud and/or sea-ice life cycle. Traditional ARM large-scale forcing data have been developed at fixed locations. They need to be extended to include these moving platforms to address data needs for ship-based field campaigns or to support LES modeling in a Lagrangian framework. With these considerations in mind, we develop ARM-type Lagrangian large-scale forcing data sets based on the lagtraj framework (Boeing et al. 2020) with notable enhancements in generating forcings that are more suitable for ARM field campaigns. The lagtraj is a novel tool that generates forcings for LES and SCM simulation in both Lagrangian and Eulerian perspective. This technical report focuses on the major changes we performed on the lagtraj algorithm and provides an overview of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) value-added products.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

GOME Calibration and Validation Using Backscatter UV Techniques

GOME radiance, irradiance, and ozone products were validated by NASA Goddard Space Flight Center through three tasks which included, pre-launch calibration comparisons with SBUV and TOMS radiometric standards, validation of GOME Level-1 irradiance and radiance and Level 2 total ozone data products using SBUV/2 and TOMS algorithms and data, and studies of GOME data using the Goddard radiative transfer code. The prelaunch calibration using the NASA large aperture integrating sphere was checked against that provided by TPD. Agreement in the calibration constants, derived in air, between the Goddard and TPD system were better than 3%. Validation of Level-1 irradiance data included comparison of GOME and SSBUV and the UARS solar irradiances measurements. Large wavelength dependent differences, as high as 10%, were noted between GOME and the US instruments. This discrepancy has now been attributed to radiometric sensitivity changes experienced by GOME when operating in a vacuum. GOME Earth radiance data were then compared to the NOAA-14 SBUV/2 radiances. These results show that between 340 and 400 nm the differences in GOME and SBUV/2 data are less than 5% with some wavelength dependence. At wavelengths shorter than 300 nm, differences are of the order of 10% or more where the GOME radiances are larger. To test GOME DOAS retrieved total ozone values, these values were compared with ozone amounts retrieved using GOME radiances in the TOMS version-7 algorithm. The differences showed a solar zenith angle dependence ranging from 0 to 10% where the TOMS algorithm values were higher. GOME radiances below 300 nm were further validated by selecting radiances at wavelengths normally used by SBUV and processing them through the SBUV ozone profile algorithm and then compared to climatological values. The GOME ozone profiles ranged from 10-30% lower over altitude compared to climatological values. This is consistent with the offsets detected in the SBUV/2 radiance comparisons at wavelengths shorter than 300 nm.

Hilsenrath, E.↗

NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗

DOE OSTI2024

Microfabricated Ion Traps on Sapphire for Larger Trap Areas and Higher Qubit Count

Surface ion traps are a promising platform for quantum computing due to their potential to store large numbers of ions that can be addressed by electrical and optical control signals in order to implement quantum algorithms. Increasing the power of the quantum computer requires increasing the number of ions, but this poses a significant challenge in that it leads to a non-linear increase in on-chip power dissipation. The primary contributor to this power scaling in current devices is the capacitance between the radio frequency (RF) electrode and the metal plane that shields the silicon substrate from the RF signals applied to it. Silicon has traditionally been chosen for the substrate material for compatibility with the processing required for multi-metal-level traps. In this work, we address these capacitance and fabrication challenges by replacing the commonly used silicon substrate with an insulating sapphire substrate to fabricate a multi-metal-level ion trap, while still employing common semiconductor manufacturing techniques. This change in substrate allows the design to remove the metal shielding from the device design, reducing the capacitance of the RF electrode. The electrical characteristics of these traps were measured, specifically trap impedance, capacitance, and voltage breakdown, and compared to nearly identical silicon trap devices. Finally, we used laser cutting techniques to shape a sapphire wafer into bowtie shapes matching silicon traps previously fabricated at Sandia National Labs to explore solutions for integrating sapphire substrates into non-rectangular ion trap designs.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2000

TRMM Surface Backscatter Measurements - Temporal and Spatial Analysis: Inter-Comparison with NSCAT

Global rainfall is the primary redistributor of earth's energy by the process of latent heat release. This forms the main driving force for the tropical circulation, which in turn impacts the global circulation .through transient events-such as El Nino. Hence, more precise and long-term time series of the rainfall and its variability is crucial to the understanding and prediction of the global climate and climate change. The Precipitation Radar (PR) abroad the US/Japan Tropical Rainfall Measuring Mission (TRMM) is the first radar ever launched into space that measures detailed vertical profiles of rain intensity over the tropics. One of the challenges in estimating rainfall from spaceborne radars is the presence of attenuation at frequencies, such as 14 GHz of the TRMM PR and future planned systems at this and higher frequencies. A common approach in current rainfall retrieval algorithms is to employed the path integrated attenuation (PIA) as a constraint to the retrieval, and hence overcome errors in the radar calibration or in the assumed rainfall parameters. PIA can either be derived from a radiometer or from the surface reference technique, in which a clear air radar measurement is compared with the measurement in the raining area. The current TRMM 2A21 PIA data product makes use of both a temporal and spatial clear air database for comparison to rainy measurements. In this paper we present results from analysis of TRMM surface backscatter cross-section (sigmaO) measurements from Nov 97-Feb99, and a comparison with sigmaO measurements obtained by the NASA Scatterometer (NSCAT) between Sept96-June97. Measurements for a given month from both instruments are compiled on a 1 deg. (lat.) x 1 deg. (lon.) x 1 hr. grid. This enables TRMM--NSCAT comparison and the investigation of seasonal and diurnal trends in both data sets. From preliminary analysis of TRMM sigmaO's we have decided not to treat the ocean as a single homogeneous region but to select a number of ocean sub-regions and individually analyze their trends. Likewise, and in a similar approach to previous studies of Seasat over-land data, we have selected a number of over-land regions for study. From said sigmaO maps and regional trend analysis we investigate possible sources of trends and variability. In addition, we study the effects of TRMM PR sensitivity through the PR "possible rain" class. Given NSCAT's inability to flag rain contaminated measurements we are able to gauge the impact of rain contamination on NSCAT monthly sigmaO maps, using TRMM measurements. The research described in this paper was carried out by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA), U.S.A.

Im, Eastwood↗