The shortwave radiative forcing bias of liquid and ice clouds from MODIS observations

We present an assessment of the plane-parallel bias of the shortwave cloud radiative forcing (SWCRF) of liquid and ice clouds at 1 deg scales using global MODIS (Terra and Aqua) cloud optical property retrievals for four months of the year 2005 representative of the meteorological seasons. The (negative) bias is estimated as the difference of SWCRF calculated using the Plane-Parallel Homogeneous (PPH) approximation and the Independent Column Approximation (ICA). PPH calculations use MODIS-derived gridpoint means while ICA calculations use distributions of cloud optical thickness and effective radius. Assisted by a broadband solar radiative transfer algorithm, we find that the absolute value of global SWCRF bias of liquid clouds at the top of the atmosphere is about 6 W m<sup>−2</sup> for MODIS overpass times while the SWCRF bias for ice clouds is smaller in absolute terms by about 0.7 W m<sup>−2</sup>, but with stronger spatial variability. If effective radius variability is neglected and only optical thickness horizontal variations are accounted for, the absolute SWCRF biases increase by about 0.3–0.4 W m<sup>−2</sup> on average. Marine clouds of both phases exhibit greater (more negative) SWCRF biases than continental clouds. Finally, morning (Terra)–afternoon (Aqua) differences in SWCRF bias are much more pronounced for ice clouds, up to about 15% (Aqua producing stronger negative bias) on global scales, with virtually all contribution to the difference coming from land areas. The substantial magnitude of the global SWCRF bias, which for clouds of both phases is collectively about 4 W m<sup>−2</sup> for diurnal averages, should be considered a strong motivation for global climate modelers to accelerate efforts linking cloud schemes capable of subgrid condensate variability with appropriate radiative transfer schemes

Advancements in the Representation of Cloud-Aerosol Microphysics in the GEOS-5 AGCM

Despite numerous challenges, the physical parameterization of cloud-aerosol interactions in atmospheric GCMs has become a top priority for advancement because of our need to simulate and understand past, current, and future indirect effects of aerosols on clouds. The challenges stem from the involvement of wide range of cloud-scale dynamics and aerosol activation physical processes. Cloud dynamics modulate cloud areal extent and condensate, while aerosol activation depends on aerosol mass load, size distribution, internal mixing state, and nucleating properties, and ultimately determines cloud optical properties via particle sizes. Both macro- and micro-scale processes are obviously important for cloud-radiation interactions. We will present the main features of cloud microphysical properties in the GEOS- 5 Atmospheric GCM (AGCM) as simulated by the McRAS-AC (Microphysics of Clouds with Relaxed Arakawa-Schubert and Aerosol-Cloud interaction) scheme. McRAS-AC uses Fountoukis and Nenes (2005) aerosol activation for liquid clouds, and has an option for either Liu and Penner (2005) or Barahona and Nenes (2008, 2009) aerosol activation for ice clouds. Aerosol loading (on-line or climatological) comes from GOCART, with an assumed log-normal size distribution. Other features of McRAS-AC are level-by-level cloud-scale thermodynamics, and Seifert-Beheng (2001)-type precipitation microphysics, particularly from moist convection. Results from Single-Column Model simulations will be shown to demonstrate how cloud radiative properties, lifetimes, and precipitation are influenced by different parameterization assumptions. Corresponding fields from year-long simulations of the full AGCM will also be presented with geographical distributions of cloud effective particle sizes compared to satellite retrievals. While the primary emphasis will be on current climate, simulation results with perturbed aerosol loadings will also be shown to expose the radiative sensitivity of the microphysical parameterization

The Role of Simplification and Information in College Decisions: Results from the H&R Block FAFSA Experiment

Growing concerns about low awareness and take-up rates for government support programs like college financial aid have spurred calls to simplify the application process and enhance visibility. This project examines the effects of two experimental treatments designed to test of the importance of simplification and information using a random assignment research design. H&R Block tax professionals helped low- to moderate-income families complete the FAFSA, the federal application for financial aid. Families were then given an estimate of their eligibility for government aid as well as information about local postsecondary options. A second randomly-chosen group of individuals received only personalized aid eligibility information but did not receive help completing the FAFSA. Comparing the outcomes of participants in the treatment groups to a control group using multiple sources of administrative data, the analysis suggests that individuals who received assistance with the FAFSA and information about aid were substantially more likely to submit the aid application, enroll in college the following fall, and receive more financial aid. These results suggest that simplification and providing information could be effective ways to improve college access. However, only providing aid eligibility information without also giving assistance with the form had no significant effect on FAFSA submission rates.

The use of happiness research for public policy

Research on happiness tends to follow a "benevolent dictator" approach where politicians pursue people's happiness. This paper takes an antithetic approach based on the insights of public choice theory. First, we inquire how the results of happiness research may be used to improve the choice of institutions. Second, we show that the policy approach matters for the choice of research questions and the kind of knowledge happiness research aims to provide. Third, we emphasize that there is no shortcut to an optimal policy maximizing some happiness indicator or social welfare function since governments have an incentive to manipulate this indicator

Viewpoint: Estimating the causal effects of policies and programs

Estimation, inference and interpretation of the causal effects of programs and policies have all advanced dramatically over the past 25 years. We highlight three particularly important intellectual trends: an improved appreciation of the substantive importance of heterogeneous responses and of their methodological implications, a stronger focus on internal validity brought about by the “credibility revolution,” and the scientific value that follows from grounding estimation and interpretation in economic theory. We discuss a menu of commonly employed partial equilibrium approaches to the identification of causal effects, emphasizing that the researcher’s central intellectual contribution always consists of making an explicit case for a specific causal interpretation given the relevant economic theory, the data, the institutional context and the economic question of interest. We also touch on the importance of general equilibrium effects and full cost–benefit analyses.RésuméPoint de vue: Sur l’estimation des effets causatifs des politiques et programmes. Dans le monde de l’estimation, l’inférence et l’interprétation des effets causatifs des programmes et des politiques, il y a eu des progrès dramatiques au cours des derniers 25 ans. Les auteurs soulignent trois tendances intellectuelles particulièrement importantes : une appréciation améliorée de l’importance substantielle des réponses hétérogènes et de leur importance méthodologique, une focalisation plus robuste sur la validité interne engendrée par la « révolution de la crédibilité », et la valeur scientifique qui découle d’un ancrage de l’estimation et de l’interprétation dans la théorie économique. On discute un éventail d’approches d’équilibre partiel à l’identification des effets causatifs, mettant au premier plan que la contribution intellectuelle centrale du chercheur consiste à bâtir un argumentaire explicite pour une interprétation causale spécifique compte tenu de la théorie économique pertinente, des données, du contexte institutionnel, et de la question économique d’intérêt. On mentionne aussi l’importance des effets d’équilibre général et des analyses de tous les coûts et avantages.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134884/1/caje12217.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134884/2/caje12217_am.pd

How to Educate Entrepreneurs?

Entrepreneurship education has two purposes: To improve students’ entrepreneurial skills and to provide impetus to those suited to entrepreneurship while discouraging the rest. While entrepreneurship education helps students to make a vocational decision its effects may conflict for those not suited to entrepreneurship. This study shows that vocational and the skill formation effects of entrepreneurship education can be identified empirically by drawing on the Theory of Planned Behavior. This is embedded in a structural equation model which we estimate and test using a robust 2SLS estimator. We find that the attitudinal factors posited by the Theory of Planned Behavior are positively correlated with students’ entrepreneurial intentions. While conflicting effects of vocational and skill directed course content are observed in some individuals, overall these types of content are complements. This finding contradicts previous results in the literature. We reconcile the conflicting findings and discuss implications for the design of entrepreneurship courses

Towards causal benchmarking of bias in face analysis algorithms

Measuring algorithmic bias is crucial both to assess algorithmic fairness, and to guide the improvement of algorithms. Current methods to measure algorithmic bias in computer vision, which are based on observational datasets, are inadequate for this task because they conflate algorithmic bias with dataset bias. To address this problem we develop an experimental method for measuring algorithmic bias of face analysis algorithms, which manipulates directly the attributes of interest, e.g., gender and skin tone, in order to reveal causal links between attribute variation and performance change. Our proposed method is based on generating synthetic ``transects'' of matched sample images that are designed to differ along specific attributes while leaving other attributes constant. A crucial aspect of our approach is relying on the perception of human observers, both to guide manipulations, and to measure algorithmic bias. Besides allowing the measurement of algorithmic bias, synthetic transects have other advantages with respect to observational datasets: they sample attributes more evenly allowing for more straightforward bias analysis on minority and intersectional groups, they enable prediction of bias in new scenarios, they greatly reduce ethical and legal challenges, and they are economical and fast to obtain, helping make bias testing affordable and widely available. We validate our method by comparing it to a study that employs the traditional observational method for analyzing bias in gender classification algorithms. The two methods reach different conclusions. While the observational method reports gender and skin color biases, the experimental method reveals biases due to gender, hair length, age, and facial hair

The role of parental investments for cognitive and noncognitive skill formation : evidence for the first 11 years of life

This paper examines the impact of parental investments on the development of cognitive, mental and emotional skills during childhood using data from a longitudinal study, the Mannheim Study of Children at Risk, starting at birth. Our work offers three important innovations. First, we use reliable measures of the child’s cognitive, mental and emotional skills as well as accurate measures of parental investment. Second, we estimate latent factor models to account for unobserved characteristics of children. Third, we examine the skill development for girls and boys separately, as well as for children who were born with either organic or psychosocial risk. We find a decreasing impact of parental investments on cognitive and mental skills, while emotional skills seem to be unaffected by parental investment throughout childhood. Thus, initial inequality persists during childhood. Since families are the main sources of education during the first years of life, our results have important implications for the quality of the parent-child relationship

Intercomparison of shortwave radiative transfer schemes in global aerosol modeling: results from the AeroCom Radiative Transfer Experiment

In this study we examine the performance of 31 global model radiative transfer schemes in cloud-free conditions with prescribed gaseous absorbers and no aerosols (Rayleigh atmosphere), with prescribed scattering-only aerosols, and with more absorbing aerosols. Results are compared to benchmark results from high-resolution, multi-angular line-by-line radiation models. For purely scattering aerosols, model bias relative to the line-by-line models in the top-of-the atmosphere aerosol radiative forcing ranges from roughly −10 to 20%, with over- and underestimates of radiative cooling at lower and higher solar zenith angle, respectively. Inter-model diversity (relative standard deviation) increases from ~10 to 15% as solar zenith angle decreases. Inter-model diversity in atmospheric and surface forcing decreases with increased aerosol absorption, indicating that the treatment of multiple-scattering is more variable than aerosol absorption in the models considered. Aerosol radiative forcing results from multi-stream models are generally in better agreement with the line-by-line results than the simpler two-stream schemes. Considering radiative fluxes, model performance is generally the same or slightly better than results from previous radiation scheme intercomparisons. However, the inter-model diversity in aerosol radiative forcing remains large, primarily as a result of the treatment of multiple-scattering. Results indicate that global models that estimate aerosol radiative forcing with two-stream radiation schemes may be subject to persistent biases introduced by these schemes, particularly for regional aerosol forcing