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The Cloud Absorption Radiometer (CAR) was flown aboard the University of Washington Convair 580 (CV-580) research aircraft during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) field campaign and obtained measurements of bidirectional reflectance distribution function (BRDF) of the ocean in July and August 2001 under different illumination conditions with solar zenith angles ranging from 15° to 46°. The BRDF measurements were accompanied by concurrent measurements of atmospheric aerosol optical thickness and column water vapor above the airplane. The method of spherical harmonics with Cox–Munk wave-slope distribution is used in a new algorithm developed for this study to solve the atmosphere–ocean radiative transfer problem and to remove the effects of the atmosphere from airborne measurements. The algorithm retrieves simultaneously the wind speed and full ocean BRDF (sun’s glitter and water-leaving radiance) from CAR measurements and evaluates total albedo and equivalent albedo for the water-leaving radiance outside the glitter. Results show good overall agreement with other measurements and theoretical simulations, with the anisotropy of the water-leaving radiance clearly seen. However, the water-leaving radiance does not show a strong dependence on solar zenith angle as suggested by some theoretical studies. The spectral albedo was found to vary from 4.1%–5.1% at λ = 0.472 μm to 2.4%–3.5% for λ ≥ 0.682 μm. The equivalent water-leaving albedo ranges from 1.0%–2.4% at λ = 0.472 μm to 0.1%–0.6% for λ = 0.682 μm and 0.1%–0.3% for λ = 0.870 μm. Results of the validation of the Cox–Munk model under the conditions measured show that although the model reproduces the shape of sun’s glitter on average with an accuracy of better than 30%, it underestimates the center of the sun’s glitter reflectance by about 30% for low wind speeds (<2–3 m s−1). In cases of high wind speed, the model with Gram–Charlier expansion seems to provide the best fit.

In light of mixed findings regarding the valence of outcomes associated with acculturation gaps in mixed-generation immigrant families, this research adopted a qualitative methodology to explore the rich complexity of acculturation gaps and their navigation. Through multiple individual, dyadic, and family semistructured interviews with 2 mixed-generation Salvadoran immigrant families living in the United States, this study explored the ways in which families (a) described and understood their acculturation gaps, (b) determined whether gaps were benign, potentially problematic, or useful for the family, and (c) navigated gaps depending on their determined valence. The individual and family narratives were analyzed through constructivist grounded theory, guided by the theories of acculturation gap-distress (Lau et al., 2005;Portes & Rumbaut, 1996) and family resilience (Walsh, 2003). This research revealed that acculturation gaps can exist among all family members and that although families described gaps in terms of differences in overt behavioral practices, only those discrepant practices that were related to underlying value or identification differences were considered potentially problematic. The families were seen to use their belief systems, organizational patterns, communication and problem-solving strategies, and methods of escape to effectively navigate these gaps in 18 diverse ways depending upon the gaps' valences. This study suggests that (a) a family resilience model can be applied to the study of acculturation gaps, (b) expansion of such model as applied to acculturation gaps may be indicated, and (c) such model may provide insight into why some families with acculturation gaps experience negative outcomes whereas others flourish.

Most cloud radiation models and conventional data processing techniques assume that the mean number of drops of a given radius is proportional to volume. The analysis of microphysical data on liquid water drop sizes shows that, for sufficiently small volumes, this proportionality breaks down; the number of cloud drops of a given radius is instead proportional to the volume raised to a drop size-dependent nonunit power. The coefficient of proportionality, a generalized drop concentration, is a function of the drop size. For abundant small drops the power is unity as assumed in the conventional approach. However, for rarer large drops, it falls increasingly below unity. This empirical fact leads to drop clustering, with the larger drops exhibiting a greater degree of clustering. The generalized drop concentration shows the mean number of drops per cluster, while the power characterizes the occurrence frequency of clusters. With a fixed total number of drops in a cloud, a decrease in frequency of clusters is accompanied by a corresponding increase in the generalized concentration. This initiates a competing process missed in the conventional models: an increase in the number of drops per cluster enhances the impact of rarer large drops on cloud radiation while a decrease in the frequency suppresses it. Because of the nonlinear relationship between the number of clustered drops and the volume, these two opposite tendencies do not necessarily compensate each other. The data analysis suggests that clustered drops likely have a stronger radiative impact compared to their unclustered counterpart; ignoring it results in underestimation of the contribution from large drops to cloud horizontal optical path.