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For years Georgia's HOPE Scholarship program provided full tuition scholarships to high-achieving students. State budgetary shortfalls reduced its generosity in 2011. Under the new rules, only students meeting more rigorous merit-based criteria would retain the original scholarship covering full tuition, now called the Zell Miller Scholarship, with other students seeing aid reductions of approximately 15 percent. We exploit the fact that two of the criteria were high school grade point average and SAT/ACT score, which students could not manipulate when the change took place. We compare already-enrolled students just above and below these cutoffs, making use of advances in multi-dimensional regression discontinuity, to estimate effects of partial aid loss. We show that, after the changes, aid flowed disproportionately to wealthier students and find no evidence that the financial aid reduction affected persistence or graduation for these students. The results suggest that high-achieving students, particularly those already in college, may be less price-sensitive than their peers.

The normalized distributions of thermodynamic and dynamical variables both within and outside shallow clouds are investigated through a composite algorithm using large eddy simulations of oceanic and continental cases. The normalized magnitude is maximum near cloud center and decreases outwards. While relative humidity (RH) and cloud liquid water ($q_l$) decrease smoothly to match the environment, the vertical velocity, virtual potential temperature ($\theta_v$) and potential temperature ($\theta$) perturbations have more complicated behaviour towards the cloud boundary. Below the inversion layer, $\theta_v^{'}$ becomes negative before the vertical velocity has turned from updraft to subsiding shell outside the cloud, indicating the presence of a transition zone where the updraft is negatively buoyant. Due to the downdraft outside the cloud and the enhanced horizontal turbulent mixing across the edge, the normalized turbulence kinetic energy (TKE) and horizontal turbulence kinetic energy (HTKE) decrease more slowly from the cloud center outwards than the thermodynamic variables. The distributions all present asymmetric structures in response to the vertical wind shear, with more negatively buoyant air, stronger downdrafts and larger TKE on the downshear side. We discuss several implications of the distributions for theoretical models and parameterizations. Positive buoyancy near cloud base is mostly due to the virtual effect of water vapor, emphasising the role of moisture in triggering. The mean vertical velocity is found to be approximately half the maximum vertical velocity within each cloud, providing a constraint to achieve possible power law distributions for some models. Finally, the normalized distributions for different variables are used to estimate the vertical heat and moisture fluxes within clouds. The results suggest the distributions near cloud edge and the variability of maximum perturbations need careful treatment. The fluxes are underestimated in the inversion layer because the cloud top downdrafts can not be well captured.

We have investigated the predictability of precipitation using a new configuration of the superparameterized Community Atmosphere Model, SP-CAM. The new configuration, called the multiple-instance superparameterized-CAM, or MP-CAM, uses the average heating and drying rates from 10 independent two-dimensional cloud-permitting models (CPMs) in each grid column of the global model, instead of a single CPM. The 10 CPMs start from slightly different initial conditions, and simulate alternative realizations of the convective cloud systems. By analyzing the ensemble of possible realizations, we can study the predictability of the cloud systems, and identify the weather regimes and physical mechanisms associated with chaotic convection. We explore alternative methods for quantifying the predictability of precipitation. Our results show that unpredictable precipitation occurs when the simulated atmospheric state is close to critical points as defined by Peters and Neelin (2006, https://doi.org/10.1038/nphys314). The predictability of precipitation is also influenced by the convective available potential energy (CAPE) and the degree of mesoscale organization. It is strongly controlled by the large-scale circulation. A companion paper compares the global atmospheric circulations simulated by SP-CAM and MP-CAM.

Numerical models configured in radiative convective equilibrium (RCE) have shown that convection can self-aggregate, where initially randomly distributed convection becomes clustered despite homogeneous initial conditions and forcing. The degree of self-aggregation within a domain has important consequences for weather and climate, and varies considerably between models. Previous studies have shown that interactions between clouds and radiation are crucial drivers and maintainers of aggregation. This study investigates the direct radiative-convective feedbacks that are important to self-aggregation within elongated channel simulations of the UK Met Office Unified Model (UM) version 11.0. Our simulations are configured using three fixed sea surface temperatures (SSTs) following the radiative-convective equilibrium model intercomparison project (RCEMIP) protocol.Our analysis builds on the vertically-integrated frozen moist static energy (FMSE) variance budget framework that assumes that aggregation increases as FMSE variance increases. The budget shows how interactions between FMSE and radiation, surface fluxes and advection contribute to increasing FMSE variance. This variance is highly sensitive to SST, however, by normalising FMSE between theoretical upper and lower limits based on SST, this sensitivity can be eliminated. This allows the variance of normalised FMSE to be a consistent aggregation metric across all SSTs. By deriving a new budget equation for normalised FMSE, we can see which interactions are important for aggregation and how these interactions are sensitive to SST. By defining cloud types based on the vertical distribution of condensed water, we study the importance of radiative interactions with each cloud type to aggregation, and how they change with SST.We find that our simulations reach similar degrees of aggregation, despite the contributions of shortwave and longwave interactions decreasing with SST. Surface flux and advective feedbacks with FMSE become less negative with SST, accounting for the decreasing radiative feedback contribution. Longwave interactions with high-topped clouds are the main drivers and maintainers of aggregation, with their influence decreasing with SST as high clouds become less abundant. Longwave interactions in clear regions have significant positive effects in driving aggregation, however their contributions decrease once the convection becomes aggregated. Their longwave contributions to aggregation decrease with SST and can become negative at high SSTs once convection is aggregated. The shortwave interactions with water vapour are one of the key maintainers of aggregation, becoming more important as aggregation increases. Shortwave interactions are more important at cooler SSTs where there is a greater contrast in shortwave heating between moist and dry regions.Results presented here are not necessarily representative of real world convection, these are merely results of this model configuration. Applying this technique to other models may highlight key differences in their cloud-radiative feedbacks and may help to explain differences in the degree of aggregation within numerical models.

The normalized distributions of thermodynamic and dynamical variables both within and outside shallow clouds are investigated through a composite algorithm using large eddy simulation of the BOMEX case. The normalized magnitude is maximum near cloud center and decreases outwards. While relative humidity (RH) and cloud liquid water (ql ) decrease smoothly to match the environment, the vertical velocity, virtual potential temperature (θv ) and potential temperature (θ) perturbations have more complicated behaviour towards the cloud boundary. Below the inversion layer, θv becomes negative before the vertical velocity has turned from updraft to subsiding shell outside the cloud, indicating the presence of a transition zone where the updraft is negatively buoyant. Due to the downdraft outside the cloud and the enhanced horizontal turbulent mixing across the edge, the normalized turbulence kinetic energy (TKE) and horizontal turbulence kinetic energy (HTKE) decrease more slowly from the cloud center outwards than the thermodynamic variables. The distributions all present asymmetric structures in response to the vertical wind shear, with more negatively buoyant air, stronger downdrafts and larger TKE on the downshear side. We discuss several implications of the distributions for theoretical models and parameterizations. Positive buoyancy near cloud base is mostly due to the virtual effect of water vapor, emphasising the role of moisture in triggering. The mean vertical velocity is found to be approximately half the maximum vertical velocity within each cloud, providing a constraint on some models. Finally, products of normalized distributions for different variables are shown to be able to well represent the vertical heat and moisture fluxes, but they underestimate fluxes in the inversion layer because they do not capture cloud top downdrafts.

Millions of high school students who take an Advanced Placement (AP) course in one of over 30 subjects can earn college credit by performing well on the corresponding AP exam. Using data from four metro-Atlanta public school districts, we find that 15 percent of students’ AP courses do not result in an AP exam. We estimate that up to 32 percent of the AP courses that do not result in an AP exam would result in a score of 3 or higher, which generally commands college credit at colleges and universities across the United States. We then examine disparities in AP exam-taking rates and have three main takeaways. First, we find evidence consistent with the positive impact of school district exam subsidies on AP exam-taking rates. In fact, students on free and reduced-price lunch (FRL) in the districts that provide a higher subsidy to FRL students than non-FRL students are more likely to take an AP exam than their non-FRL counterparts, after controlling for demographic and academic covariates. Second, Black students are 4 percentage points less likely to take an AP exam than their White peers, even among those with the same academic credentials and from the same high school. Third, we find no evidence that a female student paired with a female AP course teacher takes the AP exam at a higher rate as compared to being paired with a male teacher, even in courses that are underrepresented by females.

The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations., Key Points Temperature, humidity, and clouds in radiative‐convective equilibrium vary substantially across modelsModels agree that self‐aggregation dries the atmosphere and reduces high cloudinessThere is no consistency in how self‐aggregation depends on warming

In this study, bulk mass flux formulations for turbulent fluxes are evaluated for shallow and deep convection using large-eddy simulation data. The bulk mass flux approximation neglects two sources of variability: the interobject variability due to differences between the average properties of different cloud objects, and the intraobject variability due to perturbations within each cloud object. Using a simple cloud–environment decomposition, the interobject and intraobject contributions to the heat flux are comparable in magnitude with that from the bulk mass flux approximation, but do not share a similar vertical distribution, and so cannot be parameterized with a rescaling method. A downgradient assumption is also not appropriate to parameterize the neglected flux contributions because a nonnegligible part is associated with nonlocal buoyant structures. A spectral analysis further suggests the presence of fine structures within the clouds. These points motivate investigations in which the vertical transports are decomposed based on the distribution of vertical velocity. As a result, a “core-cloak” conceptual model is proposed to improve the representation of total vertical fluxes, composed of a strong and a weak draft for both the updrafts and downdrafts. It is shown that the core-cloak representation can well capture the magnitude and vertical distribution of heat and moisture fluxes for both shallow and deep convection.

Despite large and growing student loan balances, there is relatively little evidence on the effects of access to student loans on borrowing and educational outcomes. We examine the effect of access to credit by using policy variation in the maximum federal student loan amounts available to U.S. college students. In particular, first-, second-, and third-year students have access to different amounts of federal student loans. Using a regression discontinuity and administrative data from a state higher education system, we find that access to higher loan limits increases borrowing for at least 26 percent of borrowers. Despite this increase in borrowing, we find no evidence that eligibility for additional loans affects student GPA, persistence, or graduation.

There is substantial variation across occupations in outcomes, such as earnings, job satisfaction, and health, yet little is known about how occupational preferences are shaped and evolve. This paper assesses a channel that may influence occupational preferences—peer effects—by exploiting unique institutional features and a natural experiment at West Point to document the way students' (i.e., cadets') occupational preferences evolve, and to test for peer effects. After graduation, cadets must enter the U.S. Army as an officer in one of 16 occupational branches, and are required to rank-order their preferences for the branches repeatedly over four years. West Point randomly assigns cadets to social groups, both at broad company and narrow roommate levels. We leverage the timing of the randomization and preference elicitations to test for peer effects at the company, roommate, and older-peer levels. With the possible exception of the first few weeks of exposure, we find little evidence of peer effects. We also use a survey of cadets to explore mechanisms and find evidence that peer information may not be credible in this case, but rather cadets rely on mentors and job characteristics when making this decision.

Observations made during the TWP-ICE campaign are used to drive and evaluate thirteen cloud-resolving model simulations with periodic lateral boundary conditions. The simulations employ 2D and 3D dynamics, one- and two-moment microphysics, several variations on large-scale forcing, and the use of observationally derived aerosol properties to prognose droplet numbers. When domain means are averaged over a 6-day active monsoon period, all simulations reproduce observed surface precipitation rate but not its structural distribution. Simulated fractional areas covered by convective and stratiform rain are uncorrelated with one another, and are both variably overpredicted by up to a factor of {approx}2. Stratiform area fractions are strongly anticorrelated with outgoing longwave radiation (OLR) but are negligibly correlated with ice water path (IWP), indicating that ice spatial distribution controls OLR more than mean IWP. Overpredictions of OLR tend to be accompanied by underpredictions of reflected shortwave radiation (RSR). When there are two simulations differing only in microphysics scheme or large-scale forcing, the one with smaller stratiform area tends to exhibit greater OLR and lesser RSR by similar amounts. After {approx}10 days, simulations reach a suppressed monsoon period with a wide range of mean precipitable water vapor, attributable in part to varying overprediction of cloud-modulated radiativemore » flux divergence compared with observationally derived values. Differences across the simulation ensemble arise from multiple sources, including dynamics, microphysics, and radiation treatments. Close agreement of spatial and temporal averages with observations may not be expected, but the wide spreads of predicted stratiform fraction and anticorrelated OLR indicate a need for more rigorous observation-based evaluation of the underlying micro- and macrophysical properties of convective and stratiform structures.« less

[1] Quasi-equilibrium (QE) closure is an approximation that is expected to apply to a large ensemble of clouds under slowly changing weather conditions. It breaks down under rapidly changing conditions or when the domain size is too small to provide an adequate sample of the cloud field. We explore fluctuations about an equilibrium state as simulated by a three-dimensional cloud-resolving model. An ensemble of simulations is used to determine how the response to prescribed periodic large-scale forcing changes with the period of the forcing and the size of the averaging domain. The vertical profile of the forcing is loosely based on GATE data. Results are compared with those from constant forcing simulations. In the constant forcing simulations, the noise-to-signal ratio is nearly independent of forcing magnitude. With time-varying forcing, a considerable range of responses is found. As expected, the more slowly the forcing varies, the better the response is approximated by QE. Errors become large when the period of the forcing is less than 30 h, suggesting that the diurnal cycle cannot be accurately simulated with a QE closure. Nondeterministic variability becomes more significant with smaller domain sizes. For the cases studied, a domain width of at least 180 km is needed to obtain an adequate sample of the cloud population.