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At least 145 records · Page 8

Investigation of serendipitious WFC sources

The serendipitious WFC sources under investigation, i.e., those which just happened to lie in the field of view while another object was being studied, were disappointing. The integration times were chosen to suit the primary target not the serendipitous targets. UX UMa, CZ Ori, BI Ori, WX Cet and AR And were not detected. A long (approximately 17 ksec) pointed observation of UX Uma (PI Wood) has since been carried out (February 1993) and the data is expected shortly. The other observations were much more successful. V471 Tau was observed with the WFC for 6.5 hrs with the S1 filter and 1.1 hrs with the S2b filter. It was easily detected with a count rate of 0.03 cps in the S1 filter and 0.15 cps in the S2b filter. The oscillations were seen, even before the data was folded, as was expected from preliminary results from the survey (Barstow et al. 1992). The pointed observations provide a much better phase coverage of the oscillations than did the survey data where the coverage was sparse. These data will be presented in a paper with the PSPC data (PI's Robinson and Shipman) and the pulse profiles in the different wavelengths will be compared.

Robinson, Edward L.↗

Recommendations for Using Noise Monitors to Estimate Noise Exposure During X-59 Community Tests

A low fidelity simulation approach is used to explore how to place and use noise monitors during X-59 QueSST community tests, where people’s annoyance to the noise produced by the X-59 aircraft will be gathered. Several recommendations are provided including: 1) the desired number of sparsely spaced noise monitor sites within the survey area, 2) whether to group and average measurements across multiple noise monitors located at a site, 3) what spacing should be used if grouped noise monitors are used, 4) an approach to mitigate ambient noise contamination at the measurement sites, 5) a method to combine empirical and predicted dose estimates to provide a single dose estimate for respondents, and 6) assessing how changes in turbulence intensity and array configuration affect dose uncertainty. To make these recommendations, the error that is expected when fitting contrived, smoothly varying sonic boom “reference exposure surfaces” is studied when a spatially sparse and scattered set of samples is used as responses for the fit. The reference exposure surfaces mimic the sonic boom exposure at ground level that might be expected in the X-59 survey area in the absence of atmospheric turbulence, ambient noise, and other localized effects. The spatial extent of these surfaces varies and is representative of the different survey area sizes that might be expected during future X-59 community overflight tests. These contrived reference surfaces are sampled, and those reference samples are then perturbed to mimic atmospheric turbulence, ambient noise and other localized effects that might affect noise monitor measurements within overflown communities. Two different surface fitting methods are investigated when fitting these perturbed samples to approximate the reference surface. The first method uses interpolation between the perturbed data at the scattered sites to compute the fit. The second method fits a polynomial surface model to the perturbed data using ordinary least squares regression analysis. For both fitting methods, the root mean square fit error is computed from the pointwise difference between the fit surface and the reference surface as the count and configuration of the sites is varied while also averaging the error across many different realizations of both the smooth variation of the reference exposure surface and the random, localized perturbations at the sample sites. Different site configurations are compared using this error statistic to make the recommendations noted above. Additionally, the two fitting approaches (interpolation vs linear regression) are compared based on the fit error observed in these simulations. These analyses, comparisons, and recommendations should inform future decisions on the noise monitor placement and the methods used to analyze the noise monitor data that is collected during X-59 community overflights.

sonic boom↗

Pluto-Charon stellar occultation candidates - 1990-1995

A search to identify stars that might be occulted by Pluto or Charon during the period 1990-1995 and part of 1996 is studied. This search was made with an unfiltered CCD camera operated in the strip scanning mode, and it reaches an R magnitude of approximately 17.5 - about 1.5 mag fainter than previous searches. Circumstances for each of the 162 potential occultations are given, including an approximate R magnitude of the star, which allows estimation of the signal-to-noise ratio (S/N) for observation of each occultation. The faintest stars in the list would yield an S/N of about 20 for a 1 s integration when observed with a CCD detector on an 8 m telescope under a dark sky. The astrometric precision (+/- 0.2 arcsec, with larger systematic errors possible for individual cases) is insufficient to serve as a final prediction for these potential occultations, but is sufficient to identify stars deserving of further, more accurate, astrometric observations. Statistically, about 32 of these events to be observable somewhere on earth are expected. The number of events actually observed will be substantially smaller because of clouds and the sparse distribution of large telescopes. Finder charts for each of the 91 stars involved are presented.

Dunham, E. W.↗

Pluto-Charon Stellar Occultation Candidates: 1990-1995

We have carried out a search to identify stars that might be occulted by Pluto or Charon during the period 1990-1995 and part of 1996. This search was made with an unfiltered CCD camera operated in the strip scanning mode, and it reaches an R magnitude of approximately 17.5-about 1.5 mag fainter than previous searches. Circumstances for each of the 162 potential occultations are given, including an approximate R magnitude of the star, which allows estimation of the signal-to-noise ratio (S/N) for observation of each occultation. The faintest stars in our list would yield an S/N of about 20 for a 1 S integration when observed with a CCD detector on an 8 m telescope under a dark sky. Our astrometric precision (+/- 0.2 arcsec, with larger systematic errors possible for individual cases) is insufficient to serve as a final prediction for these potential occultations, but is sufficient to identify stars deserving of further, more accurate, astrometric observations. Statistically, we expect about 32 of these events to be observable somewhere on Earth. The number of events actually observed will be substantially smaller because of clouds and the sparse distribution of large telescopes. Finder charts for each of the 91 stars involved are presented.

Dunham, E. W.↗

Characteristics of the Variable Star P Cygni Determined from Cluster Membership

Empirical information on the luminosity, reddening, age, and mass of the variable B2 Oe supergiant P Cygni is derived from its assumed membership in the sparse anonymous cluster on which it is projected, as well as its association with the spatially adjacent cluster IC 4996, which forms a double cluster with the P Cyg cluster. Evidence for the high luminosity of P Cyg is confirmed by its derived absolute magnitude of M(sub V)= -8.46 +/- 0.03, which translates to log (L/L(sun)) = 5.54 +/- 0.02 for an effective temperature consistent with the star's derived space reddening (E(sub B-V) = 0.53 +/- 0.02). More surprising is an age for the associated clusters of 6 (+/- 1.5) x 10(exp 6) years, corresponding to a turnoff point mass of 25.1 (+/- 5.5) M(sun). By inference, P Cygni, as a post main-sequence object, should have a mass of no more than approximately 23-35 M(sun).

Turner, David G.↗

Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels

We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborneALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-daybaseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low(≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e.,<90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is<60% (or<100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.

NISAR↗

Central Valley Water Resources: Improving California Groundwater Assessments using GRACE and InSAR Datasets for Water Resource Management

California’s Central Valley is one of the most productive agricultural areas in the world, producing approximately $20 billion in crops annually. The recent California droughts of 2007-2010 and 2011-2017 resulted in increased groundwater pumping in the Central Valley to adequately irrigate farmland. Overdrafting of the Central Valley aquifer results in groundwater depletion, land subsidence, and permanent loss of groundwater storage. In 2014, depletion of groundwater led the state of California to enact the Sustainable Groundwater Management Act (SGMA), requiring critically overdrafted, high, and medium priority sub-basins to reach sustainable levels of groundwater pumping and recharge by 2042. SGMA allows local Groundwater Sustainability Agencies the authority to create Groundwater Sustainability Plans at the sub-basin level. To assist California’s Department of Water Resources, this project quantified groundwater change and land subsidence in Central Valley sub-basins with sparse or unreliable well and GPS data. This was done using NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GRACE-FO), and interferograms derived from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2). Time series of the GRACE and InSAR data were compared with well and GPS data in data-dense sub-basins to determine the feasibility of these datasets for groundwater storage and subsidence monitoring. We found thatGRACE and InSAR data are effective tools for determining groundwater change and land subsidence and can be used on their own to monitor sub-basins in the absence of well and GPS data.

Water Resources↗

A Case for Nebula Scale Mixing Between Non-Carbonaceous and Carbonaceous Chondrite Reservoirs: Testing the Grand Tack Model with Chromium Isotopic Composition of Almahata Sitta Stone 91A

There is an increasing number of Cr-O-Ti isotope studies that show solar system materials are divided into two main populations, one carbonaceous chondrite (CC)-like and the other is non-carbonaceous (NC)-like, with minimal mixing attributed to a gap opened in the protoplanetary disk due to Jupiter's formation. The Grand Tack model suggests there should be large-scale mixing between S- and C-type asteroids, an idea supported by our recent work on chondrule (Delta)17O-ε54Cr isotope systematics. The Almahata Sitta (AhS) meteorite provides a unique opportunity to test the Grand Tack model. The meteorite fell to Earth in October 2008 and has been linked to the asteroid 2008 TC3 which was discovered just prior to the fall of the AhS stones. The AhS meteorite is composed of up to 700 individual pieces with approx.140 of those pieces having some geochemical and/or petrologic studies. Almahata Sitta is an anomalous polymict ureilite with other meteorite components, including enstatite, ordinary, and carbonaceous chondrites with an approximate abundance of 70% ureilites and 30% chondrites. This observation has lead to the suggestion that TC3 2008 was a loosely aggregated rubble pile-like asteroid with the non-ureilite sample clasts within the rubble-pile. Due to the loosely-aggregated nature of AhS, the object disintegrated during atmospheric entry resulting in the weakly held clasts falling predominantly as individual stones in the AhS collection area. However, recent work has identified one sample of AhS, sample 91A, which may represent two different lithologies coexisting within a single stone. The predominate lithology type in 91A appears to be that of a C2 chondrite based on mineralogy but also contains olivine, pyroxene, and albite that have ureilite-like compositions. Previous Cr isotope investigations into AhS stones are sparse and what data is available show nearly uniform isotopic composition similar to that of typical ureilites with negative ε54Cr values.

Sanborn, M. E.↗

Central Valley Water Resources: Improving California Groundwater Assessments using GRACE and InSAR Datasets for Water Resource Management

California’s Central Valley is one of the most productive agricultural areas in the world, producing approximately $20 billion in crops annually. The recent California droughts of 2007-2010 and 2012-2019 resulted in increased groundwater pumping in the Central Valley to adequately irrigate farmland. Overdrafting of the Central Valley aquifer results in groundwater depletion, land subsidence, and permanent loss of groundwater storage. In 2014, depletion of groundwater led the state of California to enact the Sustainable Groundwater Management Act (SGMA),requiring critically overdrafted, high, and medium priority sub-basins to reach sustainable levels of groundwater pumping and recharge by 2042. SGMA allows local Groundwater Sustainability Agencies (GSAs) the authority to create Groundwater Sustainability Plans (GSPs) at the sub-basin level. To assist California’s Department of Water Resources (DWR), this project quantified groundwater change and land subsidence in Central Valley sub-basins with sparse or unreliable well and Geographic Positioning Systems (GPS) data. This was done using NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE FollowOn (GRACE-FO), and interferograms derived from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Advanced Land Observing Satellite 2 (ALOS-2)Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2). Time series of the GRACE and InSAR data were compared with well and GPS data in data-dense sub-basins to determine the feasibility of these datasets for groundwater storage and subsidence monitoring. We found that GRACE and InSAR data are effective tools for determining groundwater change and land subsidence and can be used on their own to monitor sub-basins in the absence of well and GPS data

Water Resources↗

High-Resolution N-Band Observations of the Nova RS Ophiuchi with the Keck Interferometer Nuller

We report new observations of the nova RS Ophiuchi (RS Oph) using the Keck Interferometer Nulling Instrument, approximately 3.8 days following the most recent outburst that occurred on 2006 February 12. The Keck Interferometer Nuller (KIN) operates in K-band from 8 to 12.5 pm in a nulling mode, which means that the central broad-band interference fringe is a dark fringe - with an angular width of 25 mas at mid band - rather than the bright fringe used ill a conventional optical interferometer. In this mode the stellar light itself is suppressed by the destructive fringe, effectively enhancing the contrast of the circumstellar material located near the star. By subsequently shifting the neighboring bright fringe onto the center of the source brightness distribution and integrating, a second spatial regime dominated by light from the central portion of the source is almost simultaneously sampled. The nulling technique is the sparse aperture equivalent of the conventional corongraphic technique used in filled aperture telescopes. By fitting the unique KIK inner and outer spatial regime data, we have obtained an angular size of the mid-infrared continuum of 6.2, 4.0. or 5.4 mas for a disk profile, gaussian profile (fwhm), and shell profile respectively. The data show evidence of enhanced neutral atomic hydrogen emission located in the inner spatial regime relative to the outer regime. There is also evidence of a 9.7 micron silicate feature seen outside of this region. Importantly, we see spectral lines excited by the nova flash in the outer region before the blast wave reaches these regions. These lines are from neutral, weakly excited atoms which support the following interpretation. We discuss the present results in terms of a unifying model of the system that includes an increase in density in the plane of the orbit of the two stars created by a spiral shock wave caused by the motion of the stars through the cool wind of the red giant star. These data show the power and potential of the nulling technique which has been developed for the detection of Earth-like planets around nearby stars for the Terrestrial Planet Finder Mission and Darwin missions.

Barry, R. K.↗

An Observation-Based, Reduced-Form Model for Oxidation in the Remote Marine Troposphere

The hydroxyl radical (OH) fuels atmospheric chemical cycling as the main sink for methane and a driver of the formation and loss of many air pollutants, but direct OH observations are sparse. We develop and evaluate an observation-based proxy for short term, spatial variations in OH (Proxy OH ) in the remote marine troposphere using unprecedented and comprehensive measurements from the NASA Atmospheric Tomography (ATom) airborne campaign. Proxy OH is a reduced form of the OH steady-state equation representing the dominant OH production and loss pathways in the remote marine troposphere, according to box model simulations of OH constrained with ATom observations. Proxy OH comprises only eight variables that are generally observed by routine ground- or satellite-based instruments. ProxyOH scales linearly with in situ [OH] spatial variations along the ATom flight tracks (median r 2 = 0.90, interquartile range = 0.80 – 0.94 across 2 km altitude by 20° latitudinal regions). We deconstruct spatial variations in Proxy OH as a first-order approximation of the sensitivity of OH variations to individual terms. Two terms modulate within-region Proxy OH variations—water vapor (H 2 O) and, to a lesser extent, nitric oxide (NO). This implies that a limited set of observations could offer a novel avenue for observation-based mapping of OH spatial variations over much of the remote marine troposphere. Both H 2 O and NO are expected to change with climate, while NO also varies strongly with human activities. We also illustrate the utility of Proxy OH as a process-based approach for evaluating inter-model differences in remote marine tropospheric OH.

Colleen B. Baublitz↗

The Influence of Correlated Crustal Signals in Modelling the Main Geomagnetic Field

Algorithms used in geomagnetic main-field modelling have for the most part treated the noise in the field measurements as if it were white. A major component of the noise consists of the field due to magnetization in the crust and it has been realized for some time that such signals are highly correlated at satellite altitude. Hence approximation by white noise, while of undoubted utility, is of unknown validity. In this paper we study two plausible statistical models for the crustal magnetization, in which the magnetization is a realization of a stationary, isotropic, random process. At a typical satellite altitude the associated fields exhibit significant correlation over ranges as great as 15 deg. or more, which introduces off-diagonal elements into the covariance matrix, elements that have usually been neglected in modelling procedures. Dealing with a full covariance matrix for a large data set would present a formidable computational challenge, but fortunately most of the entries in the covariance matrix are so small that they can be replaced by zeros. The resultant matrix comprises only about 3 per cent non-zero entries and thus we can take advantage of efficient sparse matrix techniques to solve the numerical system. We construct several main-field models based on vertical-component data from a selected 5 deg. by 5 deg. data set derived from the Magsat mission. Models with and without off-diagonal terms are compared.

Rygaard-Hjalsted, C.↗

Ocular Counter-Rolling During Centrifugation and Static Tilt

Activation of the gravity sensors in the inner ear-the otoliths-generates reflexes that act to maintain posture and gaze. Ocular counter-rolling (OCR) is an example of such a reflex. When the head is tilted to the side, the eyes rotate around the line of sight in the opposite direction (i.e., counter-rolling). While turning comers, undergoing centrifugation, or making side-to-side tilting head movements, the OCR reflex orients the eyes towards the sum of the accelerations from body movements and gravity. Deconditioning of otolith-mediated reflexes following adaptation to microgravity has been proposed as the basis of many of the postural, locomotor, and gaze control problems experienced by returning astronauts. Evidence suggests that OCR is reduced postflight in about 75% of astronauts tested; but the data are sparse, primarily due to difficulties in recording rotational eye movements. During the Neurolab mission, a short-arm human centrifuge was flown that generated sustained sideways accelerations of 0.5-G and one-G to the head and upper body. This produces OCR; and so for the first time, the responses to sustained centrifugation could be studied without the influence of Earth's gravity on the results. This allowed us to determine the relative importance of sideways and vertical acceleration in the generation of OCR. This also provided the first test of the effects of exposure to artificial gravity in space on postflight otolith-ocular reflexes. There was little difference between the responses to centrifugation in microgravity and on Earth. In both conditions, the induced OCR was roughly proportional to the applied acceleration, with the OCR magnitude during 0.5-G centrifugation approximately 60% of that generated during one-G centrifugation. The overall mean OCR from the four payload crewmembers in response to one-G of sideways acceleration was 5.7 plus or minus 1.1 degree (mean and SD) on Earth. Inflight one-G centrifugation generated 5.7 plus or minus 1.1 degree of OCR, which was a small but significant decrease in OCR magnitude. The postflight OCR was 5.9 plus or minus 1.4 degree, which was not significantly different from preflight values. During both 0.5-G and one-G centrifugation in microgravity, where the head vertical gravitational component was absent, the OCR magnitude was not significantly different from that produced by an equivalent acceleration during static tilt on Earth. This suggests that the larger OCR magnitude observed during centrifugation on Earth was due to the larger body vertical linear acceleration component, which may have activated either the otoliths or the body tilt receptors. In contrast to previous studies, there was no decrease in OCR gain postflight. Our findings raise the possibility that inflight exposure to artificial gravity, in the form of intermittent one-G and 0.5-G centripetal acceleration, may have been a countermeasure to deconditioning of otolith-based orientation reflexes.

Cohen, Bernard↗

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗

Driving a car with custom-designed fuzzy inferencing VLSI chips and boards

Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human-like reasoning schemes which may include as little as six elemental behaviors embodied in fourteen qualitative rules.

Pin, Francois G.↗

Validation of the Pulmonary Function System for Use on the International Space Station

Aerobic deconditioning occurs during long duration space flight despite the use of exercise countermeasures (Convertino, 1996). As a part of International Space Station (ISS) medical operations, periodic tests designed to estimate aerobic capacity are performed to track changes in aerobic fitness and to determine the effectiveness of exercise countermeasures. These tests are performed prior to, during, and after missions of greater than 30 days in duration. Crewmembers selected for missions aboard the ISS perform a graded exercise test on a cycle ergometer approximately 270 days prior to their scheduled launch date in order to measure peak oxygen consumption (VO2PK) and peak heart rate (HRpk). Approximately 30 to 45 days prior to launch, crewmembers perform a submaximal cycle ergometer test at work rates set to elicit 25, 50 and 75% of their pre-flight VO2PK. This test, known as the Periodic Fitness Evaluation (PFE), serves as a baseline measure to which subsequent in-and post-flight exercise tests are compared. While onboard the ISS, crewmembers are normally scheduled to perform the PFE beginning with flight day (FD) 14 and every 30 days thereafter. The PFE is also conducted 5 and 30 days following flight. Using PFE data, aerobic fitness is estimated by quantifying the VO2 vs. HR relationship using linear regression and calculating the VO2 that would occur at the crewmember s previously measured HRpk. Currently, for data collected during flight, this technique assumes that the pre- vs. in-flight oxygen consumption per given cycle workload is similar. However, the validity of this assumption is based upon a sparse amount of data collected during the Skylab era (Michel, et al. 1977). The method of using heart rate and cycle ergometer work rates has been used to estimate aerobic fitness in normal gravity (Astrand and Ryhming, 1954; Lee, 1993). Due to spaceflight induced physiological alterations, such as shifts in extracellular fluid (e.g. plasma) volume, this method may not be valid during space flight. In addition, the ergometer onboard ISS is vibration-isolated and moves with the astronaut s application of force into the pedals. The effect of this movement on the VO2 of cycle exercise on ISS has not been quantified.

McCleary, Frank A.↗

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by the light and heavy rain rates. This is useful in estimating the fraction of rainfall contributed by the rain rates that go undetected by the radar. The results at high rain rates provide a cross-check on the usual attenuation correction methods that are applied at the highest resolution of the instrument.

Meneghini, R.↗

Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm

While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world's oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25% uncertainty that cannot be detected by a radiometer alone. Of this value, 20% is attributed to changes in cloud morphology and microphysics, while 5% is a result of changes in the rain/no-rain thresholds. All but 2%-3% of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy for these errors is outlined.

Kummerow, Christian↗