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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Flight Wing Surface Pressure and Boundary-Layer Data Report from the F-111 Smooth Variable-Camber Supercritical Mission Adaptive Wing

Flight tests were conducted using the advanced fighter technology integration F-111 (AFTI/F-111) aircraft modified with a variable-sweep supercritical mission adaptive wing (MAW). The MAW leading- and trailing-edge variable-camber surfaces were deflected in flight to provide a near-ideal wing camber shape for the flight condition. The MAW features smooth, flexible upper surfaces and fully enclosed lower surfaces, which distinguishes it from conventional flaps that have discontinuous surfaces and exposed or semi-exposed mechanisms. Upper and lower surface wing pressure distributions were measured along four streamwise rows on the right wing for cruise, maneuvering, and landing configurations. Boundary-layer measurements were obtained near the trailing edge for one of the rows. Cruise and maneuvering wing leading-edge sweeps were 26 deg for Mach numbers less than 1 and 45 deg or 58 deg for Mach numbers greater than 1. The landing wing sweep was 9 deg or 16 deg. Mach numbers ranged from 0.27 to 1.41, angles of attack from 2 deg to 13 deg, and Reynolds number per unit foot from 1.4 x 10(exp 6) to 6.5 x 10(exp 6). Leading-edge cambers ranged from O deg to 20 deg down, and trailing-edge cambers ranged from 1 deg up to 19 deg down. Wing deflection data for a Mach number of 0.85 are shown for three cambers. Wing pressure and boundary-layer data are given. Selected data comparisons are shown. Measured wing coordinates are given for three streamwise semispan locations for cruise camber and one spanwise location for maneuver camber.

Powers, Sheryll Goecke↗
NASA NTRS2018

Variability of Disk Emission in Pre-Main-Sequence and Related Stars. IV. Investigating the Structural Changes in the Inner Disk Region of MWC 480

We present five epochs of near-IR observations of the protoplanetary disk around MWC 480 (HD 31648) obtained with the SpeX spectrograph on NASA’s Infrared Telescope Facility between 2007 and 2013, inclusive. Using the measured line fluxes in the Pa β and Br γ lines, we found the mass accretion rates to be (1.26–2.30) x 10(exp −7) Solar Mass/yr and (1.4–2.01) x 10(exp −7) Solar Mass/yr, respectively, but which varied by more than 50% from epoch to epoch. The spectral energy distribution reveals a variability of about 30% between 1.5 and 10 μm during this same period of time. We investigated the variability using of the continuum emission of the disk in using the Monte- Carlo Radiative Transfer Code HOCHUNK3D. We find that varying the height of the inner rim successfully produces a change in the NIR flux but lowers the far-IR emission to levels below all measured fluxes. Because the star exhibits bipolar flows, we utilized a structure that simulates an inner disk wind to model the variability in the near-IR, without producing flux levels in the far-IR that are inconsistent with existing data. For this object, variable near-IR emission due to such an outflow is more consistent with the data than changing the scale height of the inner rim of the disk.

Fernandes, Rachel B.↗
NASA NTRS2012

Climate Variability and Weather Extremes: Model-Simulated and Historical Data

Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).

Schubert, Siegfried D.↗
NASA NTRS2016

Successful Validation of Sample Processing and Quantitative Real-Time PCR Capabilities on the International Space Station

The WetLab-2 system was developed by NASA Ames Research Center to offer new capabilities to researchers. The system can lyse cells and extract RNA (Ribonucleic Acid) on-orbit from different sample types ranging from microbial cultures to animal tissues. The purified RNA can then either be stabilized for return to Earth or can be used to conduct on-orbit quantitative Reverse Transcriptase PCR (Polymerase Chain Reaction) (qRT-PCR) analysis without the need for sample return. The qRT-PCR results can be downlinked to the ground a few hours after the completion of the run. The validation flight of the WetLab-2 system launched on SpaceX-8 on April 8, 2016. On orbit operations started on April 15th with system setup and was followed by three quantitative PCR runs using an E. coli genomic DNA template pre-loaded at three different concentrations. These runs were designed to discern if quantitative PCR functions correctly in microgravity and if the data is comparable to that from the ground control runs. The flight data showed no significant differences compared to the ground data though there was more variability in the values, this was likely due to the numerous small bubbles observed. The capability of the system to process samples and purify RNA was then validated using frozen samples prepared on the ground. The flight data for both E. coli and mouse liver clearly shows that RNA was successfully purified by our system. The E. coli qRT-PCR run showed successful singleplex, duplex and triplex capability. Data showed high variability in the resulting Cts (Cycle Thresholds [for the PCR]) likely due to bubble formation and insufficient mixing during the procedure run. The mouse liver qRT-PCR run had successful singleplex and duplex reactions and the variability was slightly better as the mixing operation was improved. The ability to purify and stabilize RNA and to conduct qRT-PCR on-orbit is an important step towards utilizing the ISS as a National Laboratory facility. The ability to get on-orbit data will provide investigators with the opportunity to adjust experimental parameters in real time without the need for sample return and re-flight. The WetLab-2 Project is supported by the Research Integration Office in the ISS Program.

gene expression↗
NASA NTRS2016

Successful Validation of Sample Processing and Quantitative Real-Time PCR Capabilities on the International Space Station

The WetLab-2 system was developed by NASA Ames Research Center to offer new capabilities to researchers. The system can lyse cells and extract RNA (Ribonucleic Acid) on-orbit from different sample types ranging from microbial cultures to animal tissues. The purified RNA can then either be stabilized for return to Earth or can be used to conduct on-orbit quantitative Reverse Transcriptase PCR (Polymerase Chain Reaction) (qRT-PCR) analysis without the need for sample return. The qRT-PCR results can be downlinked to the ground a few hours after the completion of the run. The validation flight of the WetLab-2 system launched on SpaceX-8 on April 8, 2016. On orbit operations started on April 15th with system setup and was followed by three quantitative PCR runs using an E. coli genomic DNA template pre-loaded at three different concentrations. These runs were designed to discern if quantitative PCR functions correctly in microgravity and if the data is comparable to that from the ground control runs. The flight data showed no significant differences compared to the ground data though there was more variability in the values, this was likely due to the numerous small bubbles observed. The capability of the system to process samples and purify RNA was then validated using frozen samples prepared on the ground. The flight data for both E. coli and mouse liver clearly shows that RNA was successfully purified by our system. The E. coli qRT-PCR run showed successful singleplex, duplex and triplex capability. Data showed high variability in the resulting Cts (Cycle Thresholds [for the PCR]) likely due to bubble formation and insufficient mixing during the procedure run. The mouse liver qRT-PCR run had successful singleplex and duplex reactions and the variability was slightly better as the mixing operation was improved. The ability to purify and stabilize RNA and to conduct qRT-PCR on-orbit is an important step towards utilizing the ISS as a National Laboratory facility. The ability to get on-orbit data will provide investigators with the opportunity to adjust experimental parameters in real time without the need for sample return and re-flight. The WetLab-2 Project is supported by the Research Integration Office in the ISS Program.

quantitative PCR↗
NASA NTRS2012

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Roberts, Yolanda↗
NASA NTRSDate not supplied

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗
NASA NTRS1988

Moisture and latent heat flux variabilities in the tropical Pacific derived from satellite data

This paper describes a method of determining latent heat flux and the ocean-atmosphere moisture from sea surface temperature, precipitable water, and surface wind speed data derived from 1980-1983 observations of SMMR aboard Nimbus 7 above tropical Pacific. The observation period included a very intense El Nino-Southern Oscillation (ENSO) episode. It was found that, during the early phase of the 1982-1983 ENSO, a surface convergence center moved east leading the anomalous equatorial westerlies. At this center, the low wind and high humidity caused negative (low) latent heat flux anomalies, despite anomalously high sea surface temperatures. Latent heat flux was found to play an important role in the seasonal cooling of the upper ocean, except in areas covered by major surface convergence zones and in areas of ocean upwelling.

Liu, W. Timothy↗
NASA NTRS1989

Cross correlations between the radiation and atmospheric variables in a general circulation model and satellite data

The classical picture of the influence of midlatitude troughs on cloud patterns is studied in a GCM and in satellite and NMC data, by comparing the cross correlation of the poleward component of the wind and the outgoing longwave radiation (OLR). Over storm tracks, the variance of the OLR is explained by a correlation with the poleward component of the horizontal wind, forced by stronger correlations with the vertical velocity through the cloud and humidity fields. It is found that stratiform clouds have a dominant impact on the model OLR fluctuations, even over much of the tropics.

Charlock, Thomas P.↗
NASA NTRS1991

Mean flow and variability in the Kuroshio Extension from Geosat altimetry data

The mean flow and temporal and spatial variations of the Kuroshio Extension in the region of 140-180 deg E and 30-40 deg N are investigated using altimeter data from the Geosat Exact Repeat Mission (ERM). Mean surface height profiles are estimated along individual tracks by assuming the velocity profile of the Kuroshio Extension to be Gaussian-shaped and by successively fitting this synthetic current's height profile to the residual height data. The mean profiles from ascending and descending tracks are used to derive the mean surface height by an inverse method and to obtain the absolute surface height fields for the first 2.5 yr of the Geosat ERM. Both the mean and the instantaneous height fields thus derived compare well with the available hydrographic data and the SST patterns from the NOAA satellites. Effects of deep mean flow and baroclinic shear are found to be important in explaining the observed propagation speeds.

Qiu, BO↗
NASA NTRS2001

Sea Ice and Ice Temperature Variability as Observed by Microwave and Infrared Satellite Data

Recent reports of a retreating and thinning sea ice cover in the Arctic have pointed to a strong suggestion of significant warming in the polar regions. It is especially important to understand what these reports mean in light of the observed global warning and because the polar regions are expected to be most sensitive to changes in climate. To gain insight into this phenomenon, co-registered ice concentrations and surface temperatures derived from two decades of satellite microwave and infrared data have been processed and analyzed. While observations from meteorological stations indicate consistent surface warming in both regions during the last fifty years, the last 20 years of the same data set show warming in the Arctic but a slight cooling in the Antarctic. These results are consistent with the retreat in the Arctic ice cover and the advance in the Antarctic ice cover as revealed by historical satellite passive microwave data. Surface temperatures derived from satellite infrared data are shown to be consistent within 3 K with surface temperature data from the limited number of stations. While not as accurate, the former provides spatially detailed changes over the twenty year period. In the Arctic, for example, much of the warming occurred in the Beaufort Sea and the North American region in 1998 while slight cooling actually happened in parts of the Laptev Sea and Northern Siberia during the same time period. Big warming anomalies are also observed during the last five years but a periodic cycle of about ten years is apparent suggesting a possible influence of the North Atlantic Oscillation. In the Antarctic, large interannual and seasonal changes are also observed in the circumpolar ice cover with regional changes showing good coherence with surface temperature anomalies. However, a mode 3 is observed to be more dominant than the mode 2 wave reported in the literature. Some of these spatial and temporal changes appear to be influenced by the Antarctic Circumpolar Wave (ACW) and changes in coastal polynya activities.

Comiso, Josefino C.↗
NASA NTRS2002

Algorithms for Autonomous GPS Orbit Determination and Formation Flying: Investigation of Initialization Approaches and Orbit Determination for HEO

This report summarizes the efforts to date in processing GPS measurements in High Earth Orbit (HEO) applications by the Colorado Center for Astrodynamics Research (CCAR). Two specific projects were conducted; initialization of the orbit propagation software, GEODE, using nominal orbital elements for the IMEX orbit, and processing of actual and simulated GPS data from the AMSAT satellite using a Doppler-only batch filter. CCAR has investigated a number of approaches for initialization of the GEODE orbit estimator with little a priori information. This document describes a batch solution approach that uses pseudorange or Doppler measurements collected over an orbital arc to compute an epoch state estimate. The algorithm is based on limited orbital element knowledge from which a coarse estimate of satellite position and velocity can be determined and used to initialize GEODE. This algorithm assumes knowledge of nominal orbital elements, (a, e, i, omega, omega) and uses a search on time of perigee passage (tau(sub p)) to estimate the host satellite position within the orbit and the approximate receiver clock bias. Results of the method are shown for a simulation including large orbital uncertainties and measurement errors. In addition, CCAR has attempted to process GPS data from the AMSAT satellite to obtain an initial estimation of the orbit. Limited GPS data have been received to date, with few satellites tracked and no computed point solutions. Unknown variables in the received data have made computations of a precise orbit using the recovered pseudorange difficult. This document describes the Doppler-only batch approach used to compute the AMSAT orbit. Both actual flight data from AMSAT, and simulated data generated using the Satellite Tool Kit and Goddard Space Flight Center's Flight Simulator, were processed. Results for each case and conclusion are presented.

Axelrad, Penina↗
NASA NTRS2010

Terrestrial Hydrological Data from NASA's Hydrology Data and Information Services Center (HDISC): Products, Services, and Applications

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. The North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) have been generating a series of land surface states (soil moisture, snow, and temperature) and fluxes (evapotranspiration, radiation, and heat flux) variables. These data, hosted at and available from NASA s Hydrology Data and Information Services Center (HDISC), include the NLDAS hourly 1/8 degree products and the GLDAS 3-hourly 0.25 and 1.0 degree products. HDISC provides easy access and visualization and analysis capabilities for these products, thus reducing the time and resources spent by scientists on data management and facilitating hydrological research. Users can perform spatial and parameter subsetting, data format transformation, and data analysis operations without needing to first download the data. HDISC is continually being developed as a data and services portal that supports weather and climate forecasts, and water and energy cycle research.

Fang, Hongliang↗
NASA NTRS1988

Observed variability of the solar luminosity

Data on solar luminosity variations are compiled in graphs and analyzed, with a focus on the SMM satellite bolometric measurements and other observations made since 1983. Consideration is given to total irradiance measurements in integrated light; emission-line variability in the visible, UV, and IR; mechanisms contributing to the solar variability (sunspots, faculae, rotation, oscillations, granulation, and active networks); the role of the solar magnetic cycle; and other observable parameters indicating variability. Also discussed are the effects of solar variations on the earth climate and the implications of the observations for theoretical models of convective-envelope processes (thermal diffusion near the surface and magnetic pressure in the interior).

Hudson, H. S.↗
NASA NTRS2000

The Sandmeier Field Goniometer: A Measurement Tool for Bi-Directional Reflectance

Recent activities at the Remote Sensing Program at Stennis Space Center have identified the need to properly verify and validate data provided by the remote sensing community. One important variable, which effects remote sensing data is bi-directional reflectance distribution (BRDF). In order to quantify the effects of BRDF on man-made and natural ground targets, the Stennis Verification & Validation (V&V) team commissioned the Systems Engineering Division at NASA Ames Research Center to develop a Field Goniometer for use at the V&V Large Target Range and for various ground truthing missions. The Swiss Field Goniometer (FIGOS) was used as a benchmark instrument to design the new state of the art Sandmeier Field Goniometer (SGF), named after Stefan Sandmeier, developer of FIGOS. After establishing requirements for the SFG, design efforts began in early May 1998. The design of the SFG was completed in September 1998. Manufacturing, construction, and testing was completed in May 1999. The SFG was shipped to NASA SSC and fully operational by June 1999.

Turner, Mark↗
NASA NTRS2014

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

aerosols↗
NASA NTRS1988

A flight-test methodology for identification of an aerodynamic model for a V/STOL aircraft

Described is a flight test methodology for developing a data base to be used to identify an aerodynamic model of a vertical and short takeoff and landing (V/STOL) fighter aircraft. The aircraft serves as a test bed at Ames for ongoing research in advanced V/STOL control and display concepts. The flight envelope to be modeled includes hover, transition to conventional flight, and back to hover, STOL operation, and normaL cruise. Although the aerodynamic model is highly nonlinear, it has been formulated to be linear in the parameters to be identified. Motivation for the flight test methodology advocated in this paper is based on the choice of a linear least-squares method for model identification. The paper covers elements of the methodology from maneuver design to the completed data base. Major emphasis is placed on the use of state estimation with tracking data to ensure consistency among maneuver variables prior to their entry into the data base. The design and processing of a typical maneuver is illustrated.

Bach, Ralph E., Jr.↗