Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Sparse Data”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

774 records · Page 43

Assimilation of SMAP Products for Improving Streamflow Simulations over Tropical Climate Region—Is Spatial Information More Important Than Temporal Information?

Streamflow is one of the key variables in the hydrological cycle. Simulation and forecasting of streamflow are challenging tasks for hydrologists, especially in sparsely gauged areas. Coarse spatial resolution remote sensing soil moisture products (equal to or larger than 9 km) are often assimilated into hydrological models to improve streamflow simulation in large catchments. This study uses the Ensemble Kalman Filter (EnKF) technique to assimilate SMAP soil moisture products at the coarse spatial resolution of 9 km (SMAP 9 km), and downscaled SMAP soil moisture product at the higher spatial resolution of 1 km (SMAP 1 km), into the Soil and Water Assessment Tool (SWAT) to investigate the usefulness of different spatial and temporal resolutions of remotely sensed soil moisture products in streamflow simulation and forecasting. The experiment was set up for eight catchments across the tropical climate of Vietnam, with varying catchment areas from 267 to 6430 km^2 during the period 2017–2019. We comprehensively evaluated the EnKF-based SWAT model in simulating streamflow at low, average, and high flow. Our results indicated that high-spatial resolution of downscaled SMAP 1 km is more beneficial in the data assimilation framework in aiding the accuracy of streamflow simulation, as compared to that of SMAP 9 km, especially for the small catchments. Our analysis on the impact of observation resolution also indicates that the improvement in the streamflow simulation with data assimilation is more significant at catchments where downscaled SMAP 1 km has fewer missing observations. This study is helpful for adding more understanding of performances of soil moisture data assimilation based hydrological modelling over the tropical climate region, and exhibits the potential use of remote sensing data assimilation in hydrology.

soil moisture↗

Effectiveness of Redundant Communications Systems in Maintaining Operational Control of Small Unmanned Aircraft

NASA has been researching prototype technologies for an Unmanned Aircraft System (UAS) Traffic Management (UTM) system to facilitate enabling of safe and efficient civilian low-altitude airspace and UAS operations, in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for beyond visual line-of-sight (BVLOS) operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 will build on the earlier TCLs and focus on technologies and requirements for operations in higher-density urban areas for tasks such as news gathering, package delivery and for managing large-scale contingencies. This paper describes a communications test conducted in TCL3 and discusses insights gained from the test. In the test, operators were directed to equip UAS with redundant Command and Control (C2) communications systems, send a maneuver command to Unmanned Aircraft (UA) via the primary system, then verify execution of the sent command. This exercise was repeated with each redundant system. The test was designed to assess effectiveness of redundant C2 systems in maintaining operational control of UA. Several UAS were configured with varying arrangements to achieve redundancy, including two identical radio modems using the same frequency band, WiFi and Long-Term Evolution (LTE) cellular modems, etc. From the test, digital data such as time maneuver command sent, time maneuver verified, etc., were collected. Descriptions of methods to detect loss of C2 communications and contingency steps for such event were collected and assessed. The final paper will include a detailed analysis of the collected data leading to the following insights. First, effectiveness of redundant C2 systems depends on several factors, such as operational environment and communications service availability. For example, use of two identical point-to-point radio to connect operator and UA on the same frequency band can be effective in mitigating radio malfunction when operating in an environment where possibility of Radio Frequency (RF) interference is low, such as over open plains. However, the same arrangement may not be effective where high level of RF transmissions in broad spectrum ranges can be expected, such as over or near urban areas. For redundant systems that consist of external communications services, such as cellular and satellite communications network, redundancy is maintained only in the areas where more than one services are available. Therefore, UAS operators should have the means to plan for and monitor the performance of external communications services they are relying on to control UA. Second, communications performance needs, such as the minimum data transfer rate and the maximum tolerable latency, should be assessed to reflect the potential hazard that can come from loss of UA control. For example, UA operations over desolate area pose less hazard to people than operations over densely populated area and performance need for the former would be less than the latter.

Jung, Jaewoo↗

Cloud-Precipitation Hybrid Regimes and their Projection onto IMERG Precipitation Data

We extend and enhance the concept of the Cloud Regimes (CRs) developed from two-dimensional joint histograms of cloud optical thickness and cloud top pressure from the Moderate Resolution Imaging Spectroradiometer (MODIS), by adding precipitation information in order to better understand cloud-precipitation relationships. Taking advantage of the high-resolution Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation dataset, cloud-precipitation “hybrid” regimes are derived by implementing the k-means clustering algorithm with advanced initialization and objective measures to determine the most optimal clusters. By expressing precipitation rates within 1-degree grid cell as histograms and making choices on the relative weight of cloud and precipitation, we could obtain several editions of hybrid cloud-precipitation regimes (CPRs), and examine their characteristics. In the deep tropics, when precipitation is weighted weakly, the cloud part of the hybrid entroids resembles the centroid of cloud-only regimes, but still tightens the cloud-precipitation relationship by decreasing the precipitation variability of each regime. As precipitation weight progressively increases, the shape of the cloudy part of the hybrid centroids becomes blunter, while the precipitation part of the centroids sharpens. In the case where cloud and precipitation are weighted equally, the CPRs representing high clouds with intermediate to heavy precipitation exhibit distinct features in the precipitation parts of the centroids, which allows us to project them onto the 30-minly IMERG domain. Such a projection can be used to overcome the temporal sparseness of MODIS cloud observations, which leads to great application potential for various convection-focused studies, including diurnal cycle analysis.

cloud-precipitation↗

Investigation Into the Use of Satellite Data in Aiding Characterization of Particulate Air Quality in the Atlanta, Georgia Metropolitan Area

Poor air quality episodes occur often in metropolitan Atlanta, Georgia. The primary focus of this research is to assess the capability of satellites as a tool in characterizing air quality in Atlanta. Results indicate that intra-city PM2.5 concentrations show similar patterns as other U.S. urban areas, with the highest concentrations occurring within the city. Both PM2.5 and MODIS AOD show more increases in the summer than spring, yet MODIS AOD doubles in the summer unlike PM2.5. A majority of OMI AI is below 0.5. Using this value as an ambient measure of carbonaceous aerosols in the urban area, aerosol transport events can be identified. Our results indicate that MODIS AOD is well correlated with PM2.5 on a yearly and seasonal basis with correlation coefficients as high as 0.8 for Terra and 0.7 for Aqua. A possible alternative view of the PM2.5 and AOD relationship is seen through the use of AOD thresholds. These probabilistic thresholds provide a means to describe the AQI through the use of past AOD for a specific area. We use the NAAQS to classify the AOD into different AQI codes, and probabilistically determine thresholds of AOD that represent the majority of a specific AQI category. For example, the majority 80% of moderate AQI days have AOD values between 0.5 - 0.6. The development of thresholds could be a tool used to evaluate air quality from the use of satellites in regions where there are sparse ground-based measurements of PM2.5.

Alston, Erica J.↗

Classification of the LCVF AVIRIS test site with a Kohonen artificial neural network

We present a classification of an AVIRIS spectral image of the Lunar Crater Volcanic Field (LCVF). Geologic mapping from such data is made possible by distinctive mineral signatures: absorption features and the shape of the spectral continuum. The subtle spectral shape differences between some of the geological units in this scene along with the high dimensionality of the spectral presents a challenging pattern recognition task. We found an artificial neural network powerful in separating 13 geological units based on the full spectral resolution. The LCVF, in northern Nye County, Nevada, was the primary focus of the NASA-sponsored Geologic Remote Sensing Field Experiment in the summer of 1989. It consists of over 100 square miles of Quaternary basaltic pyroclastic and flow deposits. These deposits lie atop ignimbrites and silicic lava flows of Tertiary age and in turn are overlain by Quaternary alluvial and playa deposits. This AVIRIS image was collected on September 29, 1989 at 11:44 at 11:44 PDT. The 256-by-256 pixel subsection in this study contains oxidized basaltic cinder deposits, the southern half of the Lunar Lake playa, and outcrops of the Rhyollite of Big Sand Spring Valley. Vegetation in LCVF is sparse, but locally abundant within washes and near springs.

Merenyi, Erzsebet↗

Controls/CFD Interdisciplinary Research Software Generates Low-Order Linear Models for Control Design From Steady-State CFD Results

The NASA Lewis Research Center is developing analytical methods and software tools to create a bridge between the controls and computational fluid dynamics (CFD) disciplines. Traditionally, control design engineers have used coarse nonlinear simulations to generate information for the design of new propulsion system controls. However, such traditional methods are not adequate for modeling the propulsion systems of complex, high-speed vehicles like the High Speed Civil Transport. To properly model the relevant flow physics of high-speed propulsion systems, one must use simulations based on CFD methods. Such CFD simulations have become useful tools for engineers that are designing propulsion system components. The analysis techniques and software being developed as part of this effort are an attempt to evolve CFD into a useful tool for control design as well. One major aspect of this research is the generation of linear models from steady-state CFD results. CFD simulations, often used during the design of high-speed inlets, yield high resolution operating point data. Under a NASA grant, the University of Akron has developed analytical techniques and software tools that use these data to generate linear models for control design. The resulting linear models have the same number of states as the original CFD simulation, so they are still very large and computationally cumbersome. Model reduction techniques have been successfully applied to reduce these large linear models by several orders of magnitude without significantly changing the dynamic response. The result is an accurate, easy to use, low-order linear model that takes less time to generate than those generated by traditional means. The development of methods for generating low-order linear models from steady-state CFD is most complete at the one-dimensional level, where software is available to generate models with different kinds of input and output variables. One-dimensional methods have been extended somewhat so that linear models can also be generated from two- and three-dimensional steady-state results. Standard techniques are adequate for reducing the order of one-dimensional CFD-based linear models. However, reduction of linear models based on two- and three-dimensional CFD results is complicated by very sparse, ill-conditioned matrices. Some novel approaches are being investigated to solve this problem.

Melcher, Kevin J.↗

Coherence Analysis of the Space Launch System using Unsteady Pressure Sensitive Paint

Transonic buffet during atmospheric ascent is a major source of unsteady loading on launch vehicles that, in the past, has led to structural failures. Thus, determining accurate buffet forcing functions (BFFs) to properly predict the vehicle response to buffet is of vital importance in launch vehicle design. The state of the art for obtaining the BFFs relies on wind-tunnel tests where the fluctuating pressures are measured by pressure transducers (PTs) at sparse locations on a rigid, geometrically-scaled buffet model. To compute the BFFs, the outer mold line (OML) of the vehicle is mapped onto contiguous panels centered at the location of the PTs and the measured fluctuating pressures are integrated over the panels’ areas. To mitigate conservatism due to the assumption that the measured buffet pressures act in phase across each panel, coherence factors are applied, effectively reducing the integration areas and, therefore, the buffet forces. For coherence factors to provide the proper level of BFF attenuation, accurate knowledge of the spatial and temporal correlation of the buffet pressures is paramount. Unfortunately, even with hundreds of unsteady pressure transducers instrumenting the models, compromises must be made on the spatial resolution of the PTs. Typically, the PT layout aims at resolving the pressure correlation along the longitudinal axis of the vehicle, assuming that coherent structures propagate mostly in the longitudinal direction. As a result, the distribution of azimuthal/cross-stream correlation is not well known and its impact on the estimated BFFs is often neglected. To fill this and other knowledge gaps, extremely high spatial-resolution uPSP data were collected for three different production-design configurations of the Space Launch System in the NASA Ames Research Center Unitary Plan Wind Tunnel 11-Foot Transonic Wind Tunnel. Specifically, two cargo configurations, the Block 1 and Block 1B, and one crew configuration, the Block 1B crew, were surveyed at resolutions ranging from 600,000 to over 1 million uPSP measurement locations. To shed light on the temporal and spectral behavior of are presented. Several OML regions and flow features of interest are investigated, from theexpansion/shock on the Orion Multi-Purpose Crew Vehicle, to the terminal shock environment on the core stage, and the Strouhal shedding behind the boosters forward attach. The sensitivity of these environments to the vehicle attitude is examined. Furthermore, for selected panels,coherence factors that accurately capture the azimuthal coherence distribution of the buffetpressures are derived and their impact on the estimated BFFs is discussed. Finally, distributions of the local convection velocity and cross spectrum phase are presented.

buffet↗

Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

Pittman, Jasna↗

A Synthesis of Light Absorption Properties of the Arctic Ocean: Application to Semi-analytical Estimates of Dissolved Organic Carbon Concentrations from Space

The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean [e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012], the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher 74 than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained 75 by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian 76 side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off 77 North America. In contrast, the relationship between the phytoplankton absorption (a()) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific a() values [Matsuoka et al., 2013], this result indirectly suggests that CDOM absorption can be appropriately erived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

Pan-Arctic↗

Radio Occultation Studies of Venus' Atmosphere with Magellan

We have been conducting a systematic study of the middle and lower atmosphere of Venus through analysis of 20 radio occultation experiments conducted with the Magellan spacecraft between October, 1991, and August, 1994. These studies have revealed a rich but sparsely sampled trove of information regarding the structure, composition and dynamics of the Venus atmosphere. The five sets of experiments sampled a variety of latitudes. Basic results include vertical profiles of: (1) electron density in the ionosphere, (2) pressure, temperature, density, and static stability in the neutral atmosphere (from 33 km to 98 km), and (3) sulfuric acid vapor (H2SO4) abundance below the main cloud deck. Further analysis of the temperature profiles led to the discovery of small vertical-scale gravity waves in the neutral atmosphere. The retrieved profiles show intriguing zonal variations that might be due to planetary- scale waves. During the performance period of this grant, we have concentrated on reanalyzing the 15 experiments conducted in 1994 using improved trajectory files for Magellan provided by JPL, obtaining more reliable results, and on conducting an error analysis of the derived profiles. In addition, we have begun an analysis of microwave emission maps of Venus obtained at the Very Large Array (VLA) in April, 1996. This report is organized as follows: A summary of results is presented, giving representative examples of the various physical profiles retrieved from all the Magellan radio occultation studies, emphasizing latitudinal variations evident in the data. Next, a preliminary analysis of the VLA maps is given. A summary of activities follows the scientific results, detailing papers published and presented at various conferences. This report concludes with a "Conclusions and Suggestions for Future Work" section.

Jenkins, Jon M.↗

Observing System Simulations for Small Satellite Formations Estimating Bidirectional Reflectance

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.

small satellite↗

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Hurricanes↗

Quantitative remote sensing of ammonium minerals, Cedar Mountains, Esmeralda County, Nevada

Mineral-bound ammonium (NH4+) was discovered by the U.S. Geological Survey in the southern Cedar Mountains of Esmeralda County, Nevada in 1989. At 10 km in length, this site is 100 times larger than any previously known occurrence in volcanic rocks. The ammonium occurs in two hydrothermally altered, crystal-rich rhyolitic tuff units of Oligocene age, and is both structurally and stratigraphically controlled. This research uses Advanced Visible/Infrared Imaging Spectrometer (AVIRIS) data to quantitatively map the mineral-bound ammonium (buddingtonite) concentration in the altered volcanic rocks. Naturally occurring mineral-bound ammonium is fairly rare; however, it has been found to occur in gold-bearing hydrothermal deposits. Because of this association, it is thought that ammonium may be a useful too in exploration for gold and other metal deposits. Mineral-bound ammonium is produced when an ammonium ion (NH4+) replaces the alkali cation site (usually K+) in the crystal structure of silicate minerals such as feldspars, micas and clays. Buddingtonite is an ammonium feldspar. The ammonium originates in buried organic plant matter and is transported to the host rock by hydrothermal fluids. Ammonium alteration does not produce visible changes in the rock, and it is barely detectable with standard x-ray diffraction methods. It is clearly identified, however, by absorption features in short wave-infrared (SWIR) wavelengths (2.0 - 2.5 micrometers). The ammonium absorption features are believed to be caused by N-H vibrational modes and are analogous to hydroxyl (O-H) vibrational modes, only shifted slightly in wavelength. Buddingtonite absorption features in the near- and SWIR lie at 1.56, 2.02 and 2.12 micrometers. The feature at 2.12 micrometer is the strongest of the three and is the only one used in this study. The southern Cedar Mountains are sparsely vegetated and are an ideal site for a remote sensing study.

Baugh, William M.↗

An IR Sounding-Based Analysis of the Saharan Air Layer in North Africa

Intense daytime surface heating over barren-to-sparsely vegetated surfaces results in dry convective mixing. In the absence of external forcing such as mountain waves, the dry convection can produce a deep, well-mixed, nearly isentropic boundary layer that becomes a well-mixed residual layer in the evening. These well-mixed layers (WML) retain their unique mid-tropospheric thermal and humidity structure for several days. To detect the SAL and characterize its properties, AIRS Level 2 Ver. 6 temperature and humidity products (2003-Present) are evaluated against rawinsondes and compared to model analysis at each of the 55 rawinsonde stations in northern Africa. To distinguish WML from Saharan air layers (WMLs of Saharan origin), the detection involved a two-step process: 1) algorithm-based detection of WMLs in dry environments (less than 7 g per kilogram mixing ratio) 2) identification of Sahara air layers (SAL) by applying Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back trajectories to determine the history of each WML. WML occurrence rates from AIRS closely resemble that from rawinsondes, yet rates from model analysis were up to 30% higher than observations in the Sahara due to model errors. Despite the overly frequent occurrence of WMLs from model analysis, HYSPLIT trajectory analysis showed that SAL occurrence rates (given a WML exists) from rawinsondes, AIRS, and model analysis were nearly identical. Although the number of WMLs varied among the data sources, the proportion of WMLs which were classified as SAL was nearly the same. The analysis of SAL bulk properties showed that AIRS and model analysis exhibited a slight warm and moist bias relative to rawinsondes in non-Saharan locations, but model analysis was notably warmer than rawinsondes and AIRS within the Sahara. The latter result is likely associated with the dearth of available data assimilated by model analysis in the Sahara. The variability of SAL thicknesses was reasonably captured by both AIRS and model analysis, but the former favor layers than are thinner than observations. Finally, further analysis of HYSPLIT trajectories revealed that fewer than 10% and 33% of all SAL back trajectories passed through regions with notable precipitation (>100 mm accumulated along the trajectory path) or Aerosol Optical Depth (AOD greater than 0.4, 75th percentile of AOD) on average, respectively. Trajectory analysis indicated that only 57% of Saharan and 24% of non-Saharan WMLs are definitively of Saharan origin (Saharan requirement: Two consecutive days in Sahara and 24 or more of those hours within 72 hours of detection). Non-SAL WMLs either originate from local-to-regionally generated residual layers or from mid-latitude air streams that do not linger over the Sahara for a sufficient time period. Initial analysis shows these non-SAL WMLs tend to be both notably cooler and slightly moister than their SAL counter parts. Continuing analysis will address what role Saharan and non-Saharan air masses characteristics may play on local and regional environmental conditions.

Nicholls, Stephen D.↗

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Hou, Arthur Y.↗

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.

Wang, James S.↗

Implicit Formulation of Muscle Dynamics in OpenSim

Astronauts lose bone and muscle mass during spaceflight. Exercise countermeasure is the primary method for counteracting bone and muscle mass loss in space. New spacecraft exercise device concepts are currently being developed for the NASAs new crew exploration vehicle. The NASA Digital Astronaut Project (DAP) uses computational modeling to help determine if the new exercise devices will be effective as countermeasures. The NASA Digital Astronaut Project is developing the ability to utilize predictive simulation to provide insight into the change in kinematics and kinetics with a change in device and gravitational environment (1-g versus 0-g). For example, in space exercise the subject's body weight is applied in addition to the loads prescribed for musculoskeletal maintenance. How and where these loads are applied obviously directly impacts bone and tissue loads. Additionally, due to space vehicle structural requirements, exercise devices are often placed on vibration isolation systems. This changes the apparent impedance or stiffness of the device as seen by the user. Data collection under these conditions is often impractical and limited. Predictive modeling provides a means to have a virtual subject to test hypotheses. Predictive simulation provides a virtual subject for which we are able to perform studies such as sensitivity to device loading and vibration isolation without the need for laboratory kinematic or kinetic test data.Direct Collocation optimization provides an efficient means to perform task based optimization and predictive modeling. It is relatively straight forward to structure a physical exercise task in a Direct Collocation mathematical formulation: perform a motion such that you start at an initial pose, achieve a given amount of deflection i.e a squat, return to the initial pose, and minimize muscle activation cost. Direct Collocation is advantageous in that it does not require numerical integration to evaluate the objective function. Instead, the system dynamics are transformed to discrete time and the optimizer is constrained such that the solution is not considered to be a valid unless the dynamic equations are satisfied at all time points. The simulation and optimization are effectively done simultaneously. Due to the implicit integration, time steps can be more coarse than in a differential equation solver. In a gait scenario this means that that the model constraints and cost function are evaluated at 100 nodes in the gait cycle versus 10,000 integration steps in a variable-step forward dynamic simulation. Furthermore, no time is wasted on accurate simulations of movements that are far from the optimum. Constrained optimization algorithms require a Jacobian matrix that contains the partial derivatives of each of the dynamic constraints with respect to of each of the state and control variables at all time points. This is a large but sparse matrix. An implicit dynamics formulation requires computation of the dynamic residuals f as a function of the states x and their derivatives, and controls u:f(x, dxdt, u) 0If the dynamics of musculoskeletal system are formulated implicitly, the Jacobian elements are often available analytically, eliminating the need for numerical differentiation; this is obviously computationally advantageous. Additionally, implicit formulation of musculoskeletal dynamics do not suffer from singularities from low mass bodies, zero muscle activation, or other stiff system or

physical exercise↗

Determining Concentration of Nanoparticles from Ellipsometry

A method of using ellipsometry or polarization analysis of light in total internal reflection of a surface to determine the number density of gold nanoparticles on a smooth substrate has been developed. The method can be modified to enable determination of densities of sparse distributions of nanoparticles in general, and is expected to be especially useful for measuring gold-nanoparticle-labeled biomolecules on microarrays. The method is based on theoretical calculations of the ellipsometric responses of gold nanoparticles. Elements of the calculations include the following: For simplicity, the gold nanoparticles are assumed to be spherical and to have the same radius. The distribution of gold nanoparticles is assumed to be a sub-monolayer (that is, sparser than a monolayer). The optical response of the sub-monolayer is modeled by use of a thin-island-film theory, according to which the polarizabilities parallel and perpendicular to the substrate are functions of the wavelength of light, the dielectric functions (permittivities expressed as complex functions of frequency or wavelength) of the gold and the suspending medium (in this case, the suspending medium is air), the fraction of the substrate area covered by the nanoparticles, and the radius of the nanoparticles. For the purpose of the thin-island-film theory, the dielectric function of the gold nanoparticles is modeled as the known dielectric function of bulk gold plus a correction term that is necessitated by the fact that the mean free path length for electrons in gold decreases with decreasing radius, in such a manner as to cause the imaginary part of the dielectric function to increase with decreasing radius (see figure). The correction term is a function of the nanoparticle radius, the wavelength of light, the mean free path and the Fermi speed of electrons in bulk gold, the plasma frequency of gold, and the speed of light in a vacuum. These models are used to calculate ellipsometric responses for various concentrations of gold nanoparticles having an assumed radius. The modeled data indicates distinct spectral features for both the real and the imaginary part of the dielectric function. An ellipsometric measurement would determine this distinct feature and thus can be used to measure nanoparticle concentration. By "ellipsometric responses" is meant the intensities of light measured in various polarization states as functions of the angle of incidence and the polarization states of the incident light. These calculated ellipsometric responses are used as calibration curves: Data from subsequent ellipsometric measurements on real specimens are compared with the calibration curves. The concentration of the nanoparticles on a specimen is assumed to be that of the calibration curve that most closely matches the data pertaining to that specimen.

Venkatasubbarao, Srivatsa↗