Uncertainties : limitations of Martian granular material remote sensing
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Engineering and economic considerations are typical driving forces behind the selection of specific chemicals used in the manufacture of consumer products. Only recently has post-consumer environmental impact become part of the major considerations during the initial phases of product design. Therefore, reactive, rather than proactive strategies have dominated the consideration of environmental and health issues in product design.
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My presentation will begin with the discussion of the Intercomparison of three-dimensional (3D) Radiative Codes (13RC) project that has been started in 1997. I will highlight the question of how well the atmospheric science community can solve the 3D radiative transfer equation. Initially I3RC was focused only on algorithm intercomparison; now it has acquired a broader identity providing new insights and creating new community resources for 3D radiative transfer calculations. Then I will switch to satellite remote sensing. Almost all radiative transfer calculations for satellite remote sensing are one-dimensional (1D) assuming (i) no variability inside a satellite pixel and (ii) no radiative interactions between pixels. The assumptions behind the 1D approach will be checked using cloud and aerosol data measured by the MODerate Resolution Imaging Spectroradiometer (MODIS) on board of two NASA satellites TERRA and AQUA. In the discussion, I will use both analysis technique: statistical analysis over large areas and time intervals, and single scene analysis to validate how well the 1D radiative transfer equation describes radiative regime in cloudy atmospheres.
A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5 -resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%-80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5deg resolution is relatively small (less than 6% at 5 mm day.1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%-35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%-15% at 5 mm day.1, with proportionate reductions in latent heating sampling errors.
When averaged over the tropical oceans (30deg N/S), latent heat flux anomalies derived from passive microwave satellite measurements as well as reanalyses and climate models driven with specified seal-surface temperatures show considerable disagreement in their decadal trends. These estimates range from virtually no trend to values over 8.4 W/sq m decade. Satellite estimates also tend to have a larger interannual signal related to El Nino/Southern Oscillation (ENSO) events than do reanalyses or model simulations. An analysis of wind speed and humidity going into bulk aerodynamic calculations used to derive these fluxes reveals several error sources. Among these are apparent remaining intercalibration issues affecting passive microwave satellite 10 m wind speeds and systematic biases in retrieval of near-surface humidity. Likewise, reanalyses suffer from discontinuities in availability of assimilated data that affect near surface meteorological variables. The results strongly suggest that current latent heat flux trends are overestimated.
A simplified schematic diagram of a tilt-sensing unequal-path interferometer set up to measure the orientation of the normal vector of one surface of a cube mounted on a structure under test is described herein. This interferometer has been named a "theoferometer" to express both its interferometric nature and the intention to use it instead of an autocollimating theodolite. The theoferometer optics are mounted on a plate, which is in turn mounted on orthogonal air bearings for near-360 rotation in azimuth and elevation. Rough alignment of the theoferometer to the test cube is done by hand, with fine position adjustment provided by a tangent arm drive using linear inchwormlike motors.
Human exploration of space requires the ability to understand and mitigate risks to crews exposed to the conditions associated with such missions. This becomes a greater imperative as we prepare for interplanetary expeditions involving humans who will be subjected to long transit periods in microgravity as they travel to a distant planet such as Mars, embark and live on the planet's surface for an extended time, and finally, return to the 1 g environment of Earth. We need to know, more definitively, what the human health, safety, and performance risks are, and how to prevent or counteract them throughout all phases of a long duration mission. The Johnson Space Center's Space and Life Sciences Directorate along with the National Space Biomedical Research Institute (NSBRI) have been engaged in a strategic planning effort that identifies the most critical risks confronting humans who will venture forth on such missions and the types of research and technology efforts required to mitigate and otherwise reduce the probability and/or severity of those risks. This paper describes the unique approach used to define, assess and prioritize the risks and presents the results of the assessment with an emphasis on the research and technology priorities that will help us to meet the challenge of long duration human spaceflight missions.
Not long after the discovery of the Antarctic ozone hole, it was established that halogen compounds, supplied to the atmosphere mainly by anthropogenic activities, are the primary driver of polar ozone loss. We will briefly review the chemical mechanisms that cause polar ozone loss and the early evidence showing the key role played by anthropogenic halogens. Recently, stratospheric halogen loading has leveled off, due to adherence to the Montreal Protocol and its amendments that has essentially banned CFCs (chlorofluorocarbons) and other halocarbons. We will describe recent reports of the first stage of recovery of the Antarctic ozone hole (e.g., a statistically significant slowing of the downward trend), associated with the leveling off of stratospheric halogens. Despite this degree of understanding, we will discuss the tendency of photochemical models to underestimate the observed rate of polar ozone loss and a hypothesis that has recently been put forth that might resolve this discrepancy. Finally, we will briefly discuss chemical loss of Arctic ozone, which
Berth scheduling is a critical function at marine container terminals and determining the best berth schedule depends on several factors including the type and function of the port, size of the port, location, nearby competition, and type of contractual agreement between the terminal and the carriers. In this paper we formulate the berth scheduling problem as a bi-objective mixed-integer problem with the objective to maximize customer satisfaction and reliability of the berth schedule under the assumption that vessel handling times are stochastic parameters following a discrete and known probability distribution. A combination of an exact algorithm, a Genetic Algorithms based heuristic and a simulation post-Pareto analysis is proposed as the solution approach to the resulting problem. Based on a number of experiments it is concluded that the proposed berth scheduling policy outperforms the berth scheduling policy where reliability is not considered.
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In support of the Ice, Cloud, and land Elevation Satellite (ICESat)-II mission, this paper studies the bias in surface-elevation measurements caused by undetected thin clouds. The ICESat-II satellite may only have a 1064-nm single-channel lidar onboard. Less sensitive to clouds than the 532-nm channel, the 1064-nm channel tends to miss thin clouds. Previous studies have demonstrated that scattering by cloud particles increases the photon-path length, thus resulting in biases in ice-sheet-elevation measurements from spaceborne lidars. This effect is referred to as atmospheric path delay. This paper complements previous studies in the following ways: First, atmospheric path delay is estimated over the ice sheets based on cloud statistics from the Geoscience Laser Altimeter System onboard ICESat and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua. Second, the effect of cloud particle size and shape is studied with the state-of-the-art phase functions developed for MODIS cirrus- cloud microphysical model. Third, the contribution of various orders of scattering events to the path delay is studied, and an analytical model of the first-order scattering contribution is developed. This paper focuses on the path delay as a function of telescope field of view (FOV). The results show that reducing telescope FOV can significantly reduce the expected path delay. As an example, the average path delays for FOV = 167 microrad (a 100-m-diameter circle on the surface) caused by thin undetected clouds by the 1064-nm channel over Greenland and East Antarctica are illustrated.
Boundary layer stability was analyzed for the HIFiRE-1 flight vehicle geometry for ground tests conducted at the CUBRC LENS I hypersonic shock test facility and the Langley Research Center (LaRC) 20- inch Mach 6 Tunnel. Boundary layer stability results were compared to transition onset location obtained from discrete heat transfer measurements from thin film gauges during the CUBRC test and spatially continuous heat transfer measurements from thermal phosphor paint data during the LaRC test. The focus of this analysis was on conditions at non-zero angles of attack as stability analysis has already been performed at zero degrees angle of attack. Also, the transition onset data obtained during flight testing was at nonzero angles of attack, so this analysis could be expanded in the future to include the results of the flight test data. Stability analysis was performed using the 2D parabolized stability software suite STABL (Stability and Transition Analysis for Hypersonic Boundary Layers) developed at the University of Minnesota and the mean flow solutions were computed using the DPLR finite volume Navier-Stokes computational fluid dynamics (CFD) solver. A center line slice of the 3D mean flow solution was used for the stability analysis to incorporate the angle of attack effects while still taking advantage of the 2D STABL software suite. The N-factors at transition onset and the value of Re(sub theta)/M(sub e), commonly used to predict boundary layer transition onset, were compared for all conditions analyzed. Ground test data was analyzed at Mach 7.2 and Mach 6.0 and angles of attack of 1deg, 3deg and 5deg. At these conditions, the flow was found to be second mode dominant for the HIFiRE-1 slender cone geometry. On the leeward side of the vehicle, a strong trend of transition onset location with angle of attack was observed as the boundary layer on the leeward side of the vehicle developed inflection points at streamwise positions on the vehicle that correlated to angle of attack. Inflection points are a strong instability mechanism that lead to rapid breakdown and transition to turbulence. The transition onset location on the windward side of the vehicle displayed no trend with angle of attack or freestream Reynolds number and transition was observed farther down the vehicle than observed on the leeward side of the vehicle. In analysis of both windward and leeward sides of the vehicle, use of the N factor methodology to develop trends to predict boundary layer transition onset showed improvements over the Re(sub theta)/M(sub e) empirical correlation methodology. Stronger correlations and less scatter in the data were observed when using the N factor method for these cases.
Surface roughness variations are often assumed to be negligible for the retrieval of sol moisture. Although previous investigations have suggested that this assumption is reasonable for natural vegetation covers (i.e. Moran et al. 2002), in-situ measurements over plowed agricultural fields (i.e. Callens et al. 2006) have shown that the soil surface roughness can change considerably due to weathering induced by rain.
The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.
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