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At least 145 records · Page 8

Processing Near-Infrared Imagery of the Orion Heatshield During EFT-1 Hypersonic Reentry

The Scientifically Calibrated In-Flight Imagery (SCIFLI) team captured high-resolution, calibrated, near-infrared imagery of the Orion capsule during atmospheric reentry of the EFT-1 mission. A US Navy NP-3D aircraft equipped with a multi-band optical sensor package, referred to as Cast Glance, acquired imagery of the Orion capsule's heatshield during a period when Orion was slowing from approximately Mach 10 to Mach 7. The line-of-sight distance ranged from approximately 65 to 40 nmi. Global surface temperatures of the capsule's thermal heatshield derived from the near-infrared intensity measurements complemented the in-depth (embedded) thermocouple measurements. Moreover, these derived surface temperatures are essential to the assessment of the thermocouples' reliance on inverse heat transfer methods and material response codes to infer the surface temperature from the in-depth measurements. The paper describes the image processing challenges associated with a manually-tracked, high-angular rate air-to-air observation. Issues included management of significant frame-to-frame motions due to both tracking jerk and jitter as well as distortions due to atmospheric effects. Corrections for changing sky backgrounds (including some cirrus clouds), atmospheric attenuation, and target orientations and ranges also had to be made. The image processing goal is to reduce the detrimental effects due to motion (both sensor and capsule), vibration (jitter), and atmospherics for image quality improvement, without compromising the quantitative integrity of the data, especially local intensity (temperature) variations. The paper will detail the approach of selecting and utilizing only the highest quality images, registering several co-temporal image frames to a single image frame to the extent frame-to-frame distortions would allow, and then co-adding the registered frames to improve image quality and reduce noise. Using preflight calibration data, the registered and averaged infrared intensity images were converted to surface temperatures on the Orion capsule's heatshield. Temperature uncertainties will be discussed relative to uncertainties of surface emissivity and atmospheric transmission loss. Comparison of limited onboard surface thermocouple data to the image derived surface temperature will be presented.

Spisz, Thomas S.↗

Measurements and Modeling of Aerosol Absorption and Single Scattering Albedo at Ambient Relative Hum

Uncertainties in the aerosol single scattering albedo have been identified to be an important source of errors in current large-scale model estimates of the direct aerosol radiative forcing of climate. A number of investigators have obtained estimates of the single scattering albedo from a variety of remote sensing and in situ measurements during aerosol field experiments. During the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX, 1996) for example, estimates of the aerosol single scattering albedo were obtained (1) as a best-fit parameter in comparing radiative flux changes measured by airborne pyranometer to those computed from independently measured aerosol properties; (2) from estimates of the aerosol complex index of refraction derived using a combination of airborne sunphotometer, lidar backscatter and in situ size distribution measurements; and (3) from airborne measurements of aerosol scattering and absorption using nephelometers and absorption photometers. In this paper, we briefly compare the results of the latter two methods for two TARFOX case studies, since those techniques provide height-resolved information about the aerosol single scattering albedo. Estimates of the aerosol single scattering albedo from nephelometer and absorption photometer measurements require knowledge of the scattering and absorption humidification (i.e., the increase in these properties in response to an increase in ambient relative humidity), since both measurements are usually carried out at a relative humidity different from the ambient atmosphere. In principle, the scattering humidification factor can be measured, but there is currently no technique widely available to measure the absorption of an aerosol sample as a function of relative humidity. Frequently, for lack of better knowledge, the absorption humidification is assumed to be unity (meaning that there is no change in aerosol absorption due to an increase in ambient relative humidity). This assumption then enters the estimate of the single scattering albedo at ambient relative humidity. To investigate the validity of this assumption we have carried out modeling studies of the absorption humidification factor, assuming that the aerosols contain an insoluble soot core and a coating which determines its hygroscopic growth behavior. The aerosol optical properties are then computed on the basis of the shell/core particle morphology using a Mie-code for concentric shells. From basic physical principles, it is conceivable that aerosol absorption increases when an atmospheric aerosol particle collects a non-absorbing shell, since the soot core is then exposed to an increased (focused) electric field strength. Indeed, our preliminary modeling studies show that the absorption of an atmospheric aerosol particle composed of a soot core and an aqueous sulfuric acid shell may increase by a factor of 50% due to a change in ambient relative humidity from 30 to 95%. We will show how this increased absorption is a function of the initial particle size and soot mass fraction.

Redemann, J.↗

Effects of Nuclear Interactions on Accuracy of Space Radiation Transport

Space radiation risk to astronauts and electronic equipments is one major obstacle in long term human space explorations. Space radiation transport codes have been developed to calculate radiation effects behind materials in human missions to the Moon, Mars or beyond. We study how nuclear fragmentation processes affect the accuracy of predictions from such radiation transport. In particular, we investigate the effects of fragmentation cross sections at different energies on fluxes, dose and dose-equivalent from galactic cosmic rays behind typical shielding materials. These results tell us at what energies nuclear cross sections are the most important for radiation risk evaluations, and how uncertainties in our knowledge about nuclear fragmentations relate to uncertainties in space transport predictions.

Lin, Zi-Wei↗

Northern Winter Climate Change: Assessment of Uncertainty in CMIP5 Projections Related to Stratosphere-Troposphere Coupling

Future changes in the stratospheric circulation could have an important impact on northern winter tropospheric climate change, given that sea level pressure (SLP) responds not only to tropospheric circulation variations but also to vertically coherent variations in troposphere-stratosphere circulation. Here we assess northern winter stratospheric change and its potential to influence surface climate change in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) multimodel ensemble. In the stratosphere at high latitudes, an easterly change in zonally averaged zonal wind is found for the majority of the CMIP5 models, under the Representative Concentration Pathway 8.5 scenario. Comparable results are also found in the 1% CO2 increase per year projections, indicating that the stratospheric easterly change is common feature in future climate projections. This stratospheric wind change, however, shows a significant spread among the models. By using linear regression, we quantify the impact of tropical upper troposphere warming, polar amplification, and the stratospheric wind change on SLP. We find that the intermodel spread in stratospheric wind change contributes substantially to the intermodel spread in Arctic SLP change. The role of the stratosphere in determining part of the spread in SLP change is supported by the fact that the SLP change lags the stratospheric zonally averaged wind change. Taken together, these findings provide further support for the importance of simulating the coupling between the stratosphere and the troposphere, to narrow the uncertainty in the future projection of tropospheric circulation changes.

climate change↗

Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Hall, Dorothy K.↗

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations: 2. Retrieval Evaluation

An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (tau) and effective radius (r(sub eff)) retrievals perform best for ice clouds having 0.5 < tau< 7 and r(sub eff) < 50microns. For global ice clouds, the averaged retrieval uncertainties of tau and r(sub eff) are 19% and 33%, respectively. For optically thick ice clouds with tau larger than 10, however, the tau and r(sub eff) retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48km. Relatively large h uncertainty (e.g., > 1km) occurs for tau < 0.5. Analysis of 1month of the OE-IR retrievals shows large tau and r(sub eff) uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent tau and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 r(sub eff) are found.

cloud optics↗

Simulating the Benesov Bolide Flowfield and Spectrum at Altitudes of 47 and 57 km

This paper develops a computational fluid dynamics capability for simulating the radiative emission from a meteor shock-layer and wake to an external observer. The developed capability includes the impact of radiation and ablation on the meteor flowfield, where coupled radiation accounts for the impact of radiation on the flowfield energy equations and coupled ablation accounts for the injection of ablation species from the meteoroid surface into the ow. This capability includes updated flowfield chemistry and nonequilibrium radiation models, which are compiled from the literature. To provide a level of validation for this capability, the Benesov spectral measurements are considered. Although the meteoroid was likely fragmented at the 47 and 57 km altitudes considered, and the measurement uncertainty is roughly ±50%, these measurements represent the best available spectral measurements for a relatively large (meter-class) bolide. To determine the equivalent meteoroid diameter to simulate, the continuum component of the spectrum in the 570 to 610 nm range is considered. This range is dominated by air emission from the high pressure and temperature shock-layer in front of the meteoroid, which is simulated with a relatively small uncertainty (because of the abundance of relevant shock tube measurements) and sensitive to the equivalent meteoroid diameter. This allows an equivalent diameter between 0.62 to 0.9 m to be determined, based on comparisons between measurements and simulations in the 570 to 610 nm range. The range of equivalent diameters is due to the various meteoroid geometries considered, where increasing the bluntness decreases the required diameter. Applying these diameters to simulations at 47 and 57 km results in simulated spectra that compare within 30% of the measured values, considering the wavelength integrated values between 400 and 650 nm. This agreement is well within the estimated measurement uncertainty of ±50%. All major spectral features are captured by the simulations. This agreement provides a level of validation for the developed model that has not been previously available.

Luminous efficiency↗

Non-Parametric Collision Probability for Low-Velocity Encounters

An implicit, but not necessarily obvious, assumption in all of the current techniques for assessing satellite collision probability is that the relative position uncertainty is perfectly correlated in time. If there is any mis-modeling of the dynamics in the propagation of the relative position error covariance matrix, time-wise de-correlation of the uncertainty will increase the probability of collision over a given time interval. The paper gives some examples that illustrate this point. This paper argues that, for the present, Monte Carlo analysis is the best available tool for handling low-velocity encounters, and suggests some techniques for addressing the issues just described. One proposal is for the use of a non-parametric technique that is widely used in actuarial and medical studies. The other suggestion is that accurate process noise models be used in the Monte Carlo trials to which the non-parametric estimate is applied. A further contribution of this paper is a description of how the time-wise decorrelation of uncertainty increases the probability of collision.

Carpenter, J. Russell↗

The effect of wind and moisture gradients on the arbitrary assignment of cloud motions to a vertical coordinate system in two Sesame cases

Satellite-derived cloud motion 'wind' vectors (CMV) are increasingly used in mesoscale and in global analyses, and questions have been raised regarding the uncertainty of the level assignment for the CMV. One of two major problems in selecting a level for the CMV is related to uncertainties in assigning the motion vector to either the cloud top or base. The second problem is related to the inability to transfer the 'wind' derived from the CMV at individually specified heights to a standard coordinated surface. The present investigation has the objective to determine if the arbitrary level assignment represents a serious obstacle to the use of cloud motion wind vectors in the mesoscale analysis of a severe storm environment.

Peslen, C. A.↗

Satellite and correlative measurements of the stratospheric aerosol. III - Comparison of measurements by SAM II, SAGE, dustsondes, filters, impactors and lidar

The SAM II and SAGE satellite sensors, dustsondes, impactors, a filter collector and an airborne lidar were used in a large satellite validation experiment on July 16-19, 1979, at Poker Flat, Alaska. Independent measurements of extinction profiles by SAM II and SAGE are noted to agree with each other and with those derived from the other instruments (within combined uncertainties). The wire impactor-derived results, while also consistent with the others, are coarse due to the relatively large uncertainties in impactor-derived mass, extinction, and number of particles/unit volume whose radius is greater than x microns.

Russell, P. B.↗

Estimating Uncertainties in the Multi-Instrument SBUV Profile Ozone Merged Data Set

The MOD data set is uniquely qualified for use in long-term ozone analysis because of its long record, high spatial coverage, and consistent instrument design and algorithm. The estimated MOD uncertainty term significantly increases the uncertainty over the statistical error alone. Trends in the post-2000 period are generally positive in the upper stratosphere, but only significant at 1-1.6 hPa. Remaining uncertainties not yet included in the Monte Carlo model are Smoothing Error ( 1 from 10 to 1 hPa) Relative calibration uncertainty between N11 and N17Seasonal cycle differences between SBUV records.

Uncertainties↗

Non-Causal Controller Approximation Methodology Augmented with Model Reference Control – Robust Design

This paper describes the development of a new control design methodology based on a non-causal controller structure and its approximation. The non-causal controller design is based on a loop shaping approach. Partial fraction decomposition is used, along with derivative approximations, to derive a proper transfer function design for a causal control structure. The premise for this non-causal control methodology is that the phase delay as a function of frequency ideally remains within approximately -90o, which tends to make the system robustly stable to uncertainties in the plant dynamics. To have a predictable control system response in lieu of the tolerance of this methodology to relatively large uncertainty in the plant dynamics, the approach is augmented with model reference control. The addition of model reference control can potentially further enhance the robustness of the design. A control system design example is presented in this paper, along with simulation results, to demonstrate the high degree of robustness of this non-causal methodology and its augmentation.

Control Systems↗

Airborne Sun Photometer Measurements of Aerosol Optical Depth during SOLVE II: Comparison with SAGE III and POAM III Measurements

The 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was operated aboard the NASA DC-8 during the Second SAGE III Ozone Loss and Validation Experiment (SOLVE II) and obtained successful measurements during the sunlit segments of eight science flights. These included six flights out of Kiruna, Sweden, one flight out of NASA Dryden Flight Research Center (DFRC), and the Kiruna-DFRC return transit flight. Values of spectral aerosol optical depth (AOD), columnar ozone and columnar water vapor have been derived from the AATS-14 measurements. In this paper, we focus on AATS-14 AOD data. In particular, we compare AATS-14 AOD spectra with temporally and spatially near-coincident measurements by the Stratospheric Aerosol and Gas Experiment III (SAGE III) and the Polar Ozone and Aerosol Measurement III (POAM III) satellite sensors. We examine the effect on retrieved AOD of uncertainties in relative optical airmass (the ratio of AOD along the instrument-to-sun slant path to that along the vertical path) at large solar zenith angles. Airmass uncertainties result fiom uncertainties in requisite assumed vertical profiles of aerosol extinction due to inhomogeneity along the viewing path or simply to lack of available data. We also compare AATS-14 slant path solar transmission measurements with coincident measurements acquired from the DC-8 by the NASA Langley Research Center Gas and Aerosol Measurement Sensor (GAMS).

Russell, P.↗

Polar Motion Constraints on Models of the Fortnightly Tide

Estimates of the near-fortnightly Mf ocean tide from Topex/Poseidon satellite altimetry and from numerical solutions to the shallow water equations agree reasonably well, at least in their basin-scale features. For example, both show that the Pacific Ocean tide lags the Atlantic tide by roughly 30 degrees. There are hints of finer scale agreements in the elevation fields, but noise levels are high. In contrast, estimates of Mf currents are only weakly constrained by the TP data, because high-wavenumber Rossby waves (with intense currents) are associated with relatively small perturbations in surface elevation. As a result, a wide range of Mf current fields are consistent with both the TP data and the hydrodynamic equations within a priori plausible misfit bounds. We find that a useful constraint on the Mf currents is provided by independent estimates of the Earth's polar motion. At the Mf period polar motion shows a weak signal (both prograde and retrograde) which must be almost entirely caused by the ocean tide. We have estimated this signal from the SPACE2000 time series, after applying a broad-band correction for atmospheric angular momentum. Although the polar motion estimates have relatively large uncertainties, they are sufficiently precise to fix optimum data weights in a global ocean inverse model of Mf. These weights control the tradeoff between fitting a prior hydrodynamic model of Mf and fitting the relatively noisy T/P measurements of Mf. The predicted polar motion from the final inverse model agrees remarkably well with the Mf polar motion observations. The preferred model is also consistent with noise levels suggested by island gauges, and it is marginally consistent with differences observed by subsetting the altimetry (to the small extent that this is possible). In turn, this new model of the Mf ocean tide allows the ocean component to be removed from Mf estimates of length of day, thus yielding estimates of complex Love numbers less contaminated by oceanic effects than has hitherto been possible.

Ray, Richard D.↗

Self diffusion of alkaline-Earth in Ca-Mg-aluminosilicate melts: Experimental improvements on the determination of the self-diffusion coefficients

Experimental studies of self-diffusion isotopes in silicate melts often have quite large uncertainties when comparing one study to another. We designed an experiment in order to improve the precision of the results by simultaneously studying several elements (Mg, Ca, Sr, Ba) during the same experiment thereby greatly reducing the relative experimental uncertainties. Results show that the uncertainties on the diffusion coefficients can be reduced to 10 percent, allowing a more reliable comparison of differences of self-diffusion coefficients of the elements. This type of experiment permits us to study precisely and simultaneously several elements with no restriction on any element. We also designed an experiment to investigate the possible effects of multicomponent diffusion during Mg self-diffusion experiments by comparing cases where the concentrations of the elements and the isotopic compositions are different. The results suggest that there are differences between the effective means of transport. This approach should allow us to investigate the importance of multicomponent diffusion in silicate melts.

Paillat, O.↗

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

climate projection↗

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km by 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

general circulation model (GCM)↗