Search

College has been hailed as a “great equalizer” that can substantially reduce the influence of parents' socioeconomic status on their children's subsequent life chances. Do the equalizing effects of college extend beyond the well-studied economic outcomes to other dimensions, in particular, marriage? When and whom one marries have important implications for economic and family stability, with marriage acting as a social safety net, encouraging joint long-term investments, and potentially producing dual-earner families. I focus on the marriage timing and assortative mating patterns of first- and continuing-generation college graduates to test whether college acts as an equalizer for marriage against alternative hypotheses. Using discrete-time event-history methods and data from the National Longitudinal Survey of Youth 1997, I find small differences between first- and continuing-generation graduates in marriage timing, but larger differences in assortative mating, particularly for women. First-generation women have a substantially lower likelihood of marrying another college graduate than do continuing-generation women, and a higher likelihood of marrying a noncollege graduate. These findings highlight the importance of examining noneconomic outcomes when studying social mobility and offer insight into how inequality may persist across generations, especially for women, despite apparent upward mobility.

The Cloud Absorption Radiometer (CAR) Science Team, and the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) recently released a unique dataset of bidirectional reflectance-distribution function (BRDF) of different surface types including clouds, snow/ice, vegetation, ocean, lakes, desert, city scape, smoke and other mixed surface types. The data were acquired during numerous field campaigns around the world, with measurements spanning 1991 to 2017. This presentation will address several uses of these data including developing new methods that define important surface and atmosphere radiative transfer functions, improve remote sensing retrievals of multiple geophysical parameters such as aerosols, clouds and surface albedo, and support satellite remote sensing activities. CAR data are archived at GES DISC: https://disc.gsfc.nasa.gov/datasets?keywords=car.

Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).

Liquids show their strength Dielectric elastomer actuators are electrically powered muscle mimetics that offer high actuation strain and high efficiency but are limited by failure caused by high electric fields and aging. Acome et al. used a liquid dielectric, rather than an elastomeric polymer, to solve a problem of catastrophic failure in dielectric elastomer actuators. The dielectric's liquid nature allowed it to self-heal—something that would not be possible with a solid dielectric. The approach allowed the authors to exploit electrostatic and hydraulic forces to achieve muscle-like contractions in a powerful but delicate gripper. Science , this issue p. 61

Ice particle morphology and microphysical properties of cirrus clouds are essential for assessing radiative forcing associated with these clouds. We develop an optimal estimation-based algorithm to infer cirrus cloud optical thickness (COT), cloud effective radius (CER), plate fraction including quasi-horizontally oriented plates (HOPs) and the degree of surface roughness from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Infrared Imaging Radiometer (IIR) on the CALIPSO platform. A simple but realistic ice particle model is used, and the relevant bulk optical properties are computed using state-of-the-art light-scattering computational capabilities. Rigorous estimation of uncertainties related to surface properties, atmospheric gases and cloud heterogeneity is performed. The results based on the present method show that COTs are quite consistent with other satellite products, and CERs essentially agree with the other counterparts. A one-month global analysis for April 2007, in which CALIPSO off-nadir angle is 0.3∘, shows that the HOP has significant temperature-dependence and is critical to the lidar ratio when cloud temperature is warmer than −40∘C. The lidar ratio is calculated from the bulk optical properties based on the inferred parameters, showing robust temperature dependence. The median lidar ratio of cirrus clouds is 27–31 sr over the globe.

The Moderate-Resolution Imaging Spectroradiometer (MODIS) level-2 (L2) cloud product (earth science data set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud top properties (day and night pressure, temperature, and height) and cloud optical properties (optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases—daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: 1) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach; 2) improvement in the skill of the shortwave-derived cloud thermodynamic phase; 3) separate cloud effective radius retrieval data sets for each spectral combination used in previous collections; 4) separate retrievals for partly cloudy pixels and those associated with cloud edges; 5) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space; and 6) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes can collectively result in significant changes relative to C5, though the magnitude depends on the data set and the pixel’s retrieval location in the cloud parameter space. Example L2 granule and level-3 gridded data set differences between the two collections are shown. While the emphasis is on the suite of cloud optical property data sets, other MODIS cloud data sets are discussed when relevant.

Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from space-borne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This entails the derivation of surface albedo from SSFR/BBR and camera imagery for heterogeneous surfaces in the marginal ice zone (MIZ), as well as subsequent measurement-model inter-comparisons in the presence of thin clouds. In addition to MODIS cloud retrievals and surface albedo from SSFR, we used temperature and humidity data from in-situ data and reanalysis (MERRA-2). The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based measurements, and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case studies, about 22 % of clouds remained undetected (cloud optical thickness less than 0.5). The radiative effect of clouds above the detection threshold was −40 W m−2 above cloud, and −39 W m−2 below the cloud layer, and the optical thickness from the MODIS "1621" cloud product was consistent with the reflected and transmitted irradiance observations. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach, that would make it more dependable in the Arctic. Regardless of the cloud retrieval method, there is a need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effect from space-borne remote sensing.

A regression-based gas absorption parameterization method is developed. The present method considers an inhomogeneous atmosphere as a whole to perform regression calculations. This method can be applied in fast hyperspectral shortwave radiative transfer computations because of its computational efficiency and accuracy. We incorporate this regression method into a fast small-angle approximation radiative transfer model that fully considers the polarization state of radiative transfer.

The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multi-directional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed that provides a more noise-resilient roughness estimate than the conventional best-fit approach. The improvements include the introduction of a quantitative roughness parameter based on empirical orthogonal function analysis and proper treatment of polarization due to atmospheric scattering above clouds. A global 1-month data sample supports the use of a severely roughened ice habit to simulate the polarized reflectivity associated with ice clouds over ocean. The density distribution of the roughness parameter inferred from the global 1-month data sample and further analyses of a few case studies demonstrate the significant variability of ice cloud single-scattering properties. However, the present theoretical results do not agree with observations in the tropics. In the extratropics, the roughness parameter is inferred but 74 % of the sample is out of the expected parameter range. Potential improvements are discussed to enhance the depiction of the natural variability on a global scale.

In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

The Earth Observing System is a US National Aeronautics and Space Administration (NASA) program consisting of a science segment, a data system, and a space segment made up of a series of polar-orbiting and mid-inclination satellites for long-term monitoring of the Earth as an integrated system, including observations of the land surface, biosphere, atmosphere, cryosphere, and oceans. Initially conceived in the mid-late 1980s, it was implemented as a series of large “flagship” missions and smaller focused satellites, often in partnership with instruments and sometimes spacecraft from other nations.

Similarity relations applied to ice cloud radiance calculations are theoretically analyzed and numerically validated. If τ(1-ϖ) and τ(1-ϖg) are conserved where τ is optical thickness, ϖ the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection 5 (C5) and Collection 6 (C6) cloud property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice cloud optical thickness values are multiplied by their respective (1-ϖg) factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice cloud effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice cloud phase function ratios. The MODIS C5 and C6 values of ice cloud similarity parameter, defined as [(1-ϖ)/(1-ϖg)](1/2), also tend to be similar.

To infer atmospheric and oceanic constituent properties from polarimetric observations, an efficient and accurate retrieval algorithm is desirable. In-line radiative transfer calculations are indispensable if a large state vector, including both atmospheric profiles and surface properties, is used to improve retrieval accuracy. However, in-line radiative transfer calculations are usually not computationally efficient for remote sensing applications. Therefore, there is a pressing need to develop an accurate and fast vector radiative transfer model (RTM) to fully utilize spaceborne polarimetric observations. This paper reports on a fast vector RTM, referred to as TAMU-VRTM, in support of polarimetric remote sensing, which is capable of simulating the Stokes vector values observed at the top of the atmosphere and at the surface by fully considering absorption, scattering, and emission in the atmosphere and ocean. Gaseous absorption is parameterized with respect to gas concentration, temperature, and pressure, by using a regression method applicable to an inhomogeneous atmospheric path. An efficient two-component approach combining the small-angle approximation and the adding-doubling method is utilized to solve the vector radiative transfer equation (RTE). The thermal emission component of the RTE solution is obtained by an efficient doubling process. The air-sea interface is treated as a wind-ruffled rough surface in the model to mimic a realistic ocean surface. Several oceanic optical property models are introduced to model ocean inherent optical properties. To demonstrate the applicability of the TAMU-VRTM, simulations are compared with satellite observations, and results from other vector radiative transfer methods including benchmarks.

Cloud properties have been retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) over 12 years of continuous observations from Terra and over nine years from Aqua. Results include the spatial and temporal distribution of cloud fraction, the cloud top pressure and cloud top temperature, and the cloud optical thickness and effective radius of both liquid water and ice clouds. Globally, the cloud fraction derived by the MODIS cloud mask is ~ 67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, the cloud fraction over land is ~ 55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics. The cloud effective particle radius of liquid water clouds is significantly larger over ocean (mode 12-13 μm) than land (mode 10-11 μm), consistent with the variation in hygroscopic aerosol concentrations that provide cloud condensation nuclei necessary for cloud formation. We also find the effective radius to be 2-3 μm larger in the southern hemisphere than in the northern hemisphere, likely reflecting differences in sources of cloud condensation nuclei.

Ice clouds and dust aerosols are two important atmospheric constituents. To reliably assess the radiativeforcings and to accurately infer the microphysical and optical properties of these two atmospheric components, it is necessary to use appropriate optical properties of ice crystals and dust particles. In this talk we will discuss the use of remote sensing techniques based on observations by passive and active sensors to constrain the optical properties. Specifically, we will use the MODIS (Moderate Resolution Imaging Spectroradiometer), POLDER (POLarization and Directionality of the Earth's Reflectances), MISR (Multi-angle Imaging SpectroRadiometer), and CALIOP/CALIPSO (Cloud-Aerosol Lidar with Orthogonal Polarization on the Cloud-Aerosol Lidar with Orthogonal Polarization) measurements in combination of theoretical light scattering simulations to identify the optimal single-scattering properties (extinction coefficient, single-scattering albedo, and phase matrix) of nonspherical/inhomogeneous ice crystals and dust particles.

Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 mm can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses t < ~6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of t and ice particle size De to optically thick clouds. Measurements from an imager, an interferometer, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval potential of infrared radiances over optically thick ice clouds. Simulations based on coincident in situ measurements and combined cloud t from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to t up to ~20 and that for ice clouds having t > 20, the 3.7–10.8 µm and 3.7–6.7 µm BTDs are the most sensitive to De. Satellite imagery appears to be consistent with these results suggesting that t and De could be retrieved for greater optical thicknesses than previously assumed. But, because of sensitivity of the BTDs to uncertainties in the atmospheric profiles of temperature, humidity, and ice water content, and sensor noise, exploiting the small BTD signals in retrieval algorithms will be very challenging.

Large forest fires are a known natural and dominant disturbance factor in high northern latitudes, and form pyrocumulus (pyroCu), and occasionally pyrocumulonimbus (pyroCb) clouds. These clouds can transport emissions into the upper troposphere/lower stratosphere (UT/LS) and produce significant regional and even global climate effects, as is the case with some volcanoes. However, the lack of observational data within pyroCu or pyroCb complicates our ability to investigate pyro-convection and to understand the vertical and cross-isentropic transport mechanisms responsible for UT/LS injection. Here, we report detailed airborne radiation measurements within strong pyroCu taken over boreal forest fires in Saskatchewan, Canada during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) summer field campaign in 2008. We find a prominent smoke core within the pyroCu, which is defined by strong extinction in the UV, VIS and NIR, and high gas-particle concentrations. We also find that the angular distribution of radiance within the pyroCu is closely related to the diffusion domain in water clouds, which is dominated by multiple scattering processes. The radiation field of pyroCu can be described by diffusion approximations that are comprised of simple cosine functions, which can be used to calculate the spatial and temporal characteristics of the radiance field, and applied in cloud resolving models. We demonstrate with Monte Carlo simulations that radiation transport in pyroCu is inherently a 3D problem and must account for particle absorption.

Objective To describe outcome after transarticular facet screw stabilization and dorsal laminectomy for treatment of dynamic degenerative lumbosacral stenosis (DLS) in 26 dogs. Study Design Retrospective case series. Animals Dogs (n = 26) with dynamic DLS. Methods Medical records (2004–2009) of dogs treated with transarticular facet screw stabilization and dorsal laminectomy were reviewed. Dogs (n = 26) were available for immediate postoperative follow-up, 21 dogs at 6 weeks, and 15 at greater than 6 months. Dogs were evaluated by radiographic assessment and owner questionnaire. Lumbosacral (LS) intervertebral disc (IVD) spaces were measured on pre and postoperative 6-week and 6-month radiographs. Results In 23 dogs, improvement in clinical signs occurred within 7 days of surgery. Overall postsurgical complication rate directly related to the surgical procedure was 15.4%. LS IVD space measurements taken immediately postoperatively, at 6 weeks, and ≥ 6 months were all significantly increased compared with preoperative measurements. All working dogs (4) returned to full work within 14 months. Most owners (85%) reported their dog was ambulating normally at 6 months with no perceptible lameness during normal activity. All owners perceived their dog's ability to walk, run, and jump after surgery to be improved. Conclusions Transarticular facet screw stabilization and dorsal laminectomy maintains distraction of the LS IVD space for medium-to-large breed dogs with dynamic DLS with a high degree of owner satisfaction, and is comparable to other reported surgical techniques for DLS.

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94-μm methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases.