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Hailong Wang, William C. Skamarock, and Graham Feingold

Abstract

In the Advanced Research Weather Research and Forecasting Model (ARW), versions 3.0 and earlier, advection of scalars was performed using the Runge–Kutta time-integration scheme with an option of using a positive-definite (PD) flux limiter. Large-eddy simulations of aerosol–cloud interactions using the ARW model are performed to evaluate the advection schemes. The basic Runge–Kutta scheme alone produces spurious oscillations and negative values in scalar mixing ratios because of numerical dispersion errors. The PD flux limiter assures positive definiteness but retains the oscillations with an amplification of local maxima by up to 20% in the tests. These numerical dispersion errors contaminate active scalars directly through the advection process and indirectly through physical and dynamical feedbacks, leading to a misrepresentation of cloud physical and dynamical processes. A monotonic flux limiter is introduced to correct the generally accurate but dispersive solutions given by high-order Runge–Kutta scheme. The monotonic limiter effectively minimizes the dispersion errors with little significant enhancement of numerical diffusion errors. The improvement in scalar advection using the monotonic limiter is discussed in the context of how the different advection schemes impact the quantification of aerosol–cloud interactions. The PD limiter results in 20% (10%) fewer cloud droplets and 22% (5%) smaller cloud albedo than the monotonic limiter under clean (polluted) conditions. Underprediction of cloud droplet number concentration by the PD limiter tends to trigger the early formation of precipitation in the clean case, leading to a potentially large impact on cloud albedo change.

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Jerry Y. Harrington, Graham Feingold, and William R. Cotton

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The impact of solar heating and infrared cooling on the growth of a population of drops is studied with two numerical modeling frameworks. An eddy-resolving model (ERM) simulation of Arctic stratus clouds is used to generate a dataset of 500 parcel trajectories that follow the mean dynamic motions of the simulated cloud. The 500-parcel dataset is used to drive a trajectory ensemble model (TEM) coupled to an explicit microphysical model that includes the radiative term in the vapor growth equation. The second framework is that of the ERM itself.

Results from the TEM show that the production of drizzle-sized drops is strongly dependent upon parcel cloud-top residence time for both radiative- and nonradiative-influenced growth. Drizzle-sized drops can be produced between 20 and 50 min earlier through the inclusion of the radiative term, which corroborates earlier results. The radiative effect may also cause drops with r < 10 μm to evaporate, producing a bimodal size spectrum. Parcel cloud-top residence times as short as 12 min can initiate this bimodal spectrum. TEM results show that the radiative effect increases drizzle drop mass predominately in parcels that tend to contribute to drizzle even in the absence of the radiative term. Activation of large cloud condensation nuclei appears to have a larger effect on drizzle production than does the radiative term. ERM simulations show a weak overall influence of the radiative term. Drizzle onset occurs earlier when the radiative term is included (about 20 min), but there is no strong change in the overall structure or evolution of the cloud.

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Bjorn Stevens, Graham Feingold, William R. Cotton, and Robert L. Walko

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A set of 500 simulated trajectories and a simple parcel model are used to (i) evaluate the performance of a large eddy simulation model coupled to a detailed representation of the droplet spectrum (the LES-BM model) and (ii) gain insight into the microphysical structure of numerically simulated nonprecipitating stratocumulus. The LES-BM model reasonably reproduces many observed features of stratocumulus. The largest sources of error appear to be associated with limited vertical resolution, the neglect of gas kinetic effects and the inability of the model to properly represent mixing across cloud interfacial boundaries. The first two problems have simple remedies; for instance, a condensation–nucleation scheme is derived that includes gas–kinetic effects thus obviating the second problem. The third source of error poses a more vexing, and as yet unsolved, problem for models of the class described herein.

Trajectories timescales are analyzed and in-cloud residence times are found to be, in the mean, on the order of the large eddy turnover time. In addition, it is shown that the length of time trajectories spend near cloud top may be an important factor in the droplet growth equation for a certain favored subset of trajectories. An analysis of the adiabatic trajectory data also indicates that (i) values of diameter dispersion are a factor of 2 to 5 smaller than commonly observed; (ii) simulated values of the dispersion in number concentration are found to be explainable solely on the basis of trajectories having different updraft velocities; (iii) diameter dispersions are not found to be equal to a third of number dispersions, nor did they relate simply to the dispersion in the cloud-base updraft velocity.

Problems with coupling one- and two-dimensional models to detailed representations of the droplet spectrum are discussed. In the case of the former, the lack of an explicit representation of turbulent eddies requires that the coupling between the microphysics and the dynamics be parameterized. In the case of the latter, boundary layer eddies are represented, thus allowing for a more reasonable coupling between turbulence and microphysics. However, the resolved eddies have a different structure than their three-dimensional counterparts, one consequence of which is that timescales of in-cloud circulations are found to be shorter and have less variability.

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Bjorn Stevens, Robert L. Walko, William R. Cotton, and Graham Feingold

Abstract

The production of anomalous supersaturations at cloud edges other than cloud base has presented a vexing challenge for modelers attempting to represent the evolution of a droplet spectrum across an Eulerian grid. Although the problem manifests itself most dramatically for models that explicitly predict on the supersaturation field, it is also present in models with bulk condensation schemes in which condensation happens implicitly. Although the problem has been discussed in the context of truncation errors associated with finite difference approximations to advection, this note demonstrates more generally that the cloud-edge supersaturation problem is a fundamental problem associated with the ubiquitous assumption that the forcings on the droplet spectra are well represented by the mean thermodynamic fields. In certain respects, this assumption is equivalent to failing to represent fractional cloudiness within a grid. Although well-known consequences of this problem are the underprediction of temperature and the erroneous representation of the mean buoyancy flux within a grid box, we also demonstrate that the spurious production of droplets can arise in response to the spurious production of supersaturations in models with detailed microphysical representations.

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Bjorn Stevens, William R. Cotton, Graham Feingold, and Chin-Hoh Moeng

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Large-eddy simulations that incorporate a size-resolving representation of cloud water are used to study the effect of heavy drizzle on PBL structure. Simulated surface precipitation rates average about 1 mm day−1. Heavily drizzling simulations are compared to nondrizzling simulations under two nocturnal PBL regimes—one primarily driven by buoyancy and the other driven equally by buoyancy and shear. Drizzle implies a net latent heating in the cloud that leads to sharp reductions in both entrainment and the production of turbulent kinetic energy by buoyancy (particularly in downdrafts). Drizzle, which evaporates below cloud base, promotes a cooler and moister subcloud layer that further inhibits deep mixing. The cooling and moistening is in quantitative agreement with some observations and is shown to favor the formation of cumuli rising out of the subcloud layer. The cumuli, which are local in space and time, are responsible for most of the heat and moisture transport. They also appear to generate a larger-scale circulation that differs dramatically from the regularity typically found in nonprecipitating stratocumulus. Time-averaged turbulent fluxes of heat and moisture increase in the presence of precipitation, suggesting that drizzle (and drizzle-induced stratification) should not necessarily be taken as a sign of decoupling. Because drizzle primarily affects the vertical distribution of buoyancy, shear production of turbulent kinetic energy mitigates some of the effects described above. Based on large-eddy simulation the authors hypothesize that shallow, well-mixed, radiatively driven stratocumulus cannot persist in the presence of heavy drizzle. In accord with some simpler models, the simulated case with heavy precipitation promotes a reduction in both liquid-water path and entrainment. However, the simulations suggest that time-integrated cloud fraction may increase as a result of drizzle because thinner precipitating clouds may persist longer if the boundary layer does not deepen as rapidly. These somewhat more complicated dynamics have important implications for a number of hypotheses suggesting that changes in aerosol concentrations, when metabolized by stratocumulus, have a significant effect on climate.

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Graham Feingold, William R. Cotton, Sonia M. Kreidenweis, and Janel T. Davis

Abstract

The impact of giant and ultragiant cloud condensation nuclei (>5-μm radius) on drizzle formation in stratocumuli is investigated within a number of modeling frameworks. These include a simple box model of collection, a trajectory ensemble model (comprising an ensemble of Lagrangian parcel models), a 2D eddy-resolving model, and a 3D large-eddy simulation model. Observed concentrations of giant cloud condensation nuclei (GCCN) over the ocean at ambient conditions indicate that 20-μm radius haze particles exist in concentrations of between 10−4 and 10−2 cm−3, depending on ambient wind speed and seastate. It is shown that these concentrations are sufficient to move a nonprecipitating stratocumulus into a precipitating state at typical cloud condensation nucleus (CCN) concentrations of 50 to 250 cm−3, with higher concentrations of GCCN being required at higher CCN concentrations. However, at lower CCN concentrations, drizzle is often active anyway and the addition of GCCN has little impact. At high CCN concentrations, drizzle development is slow and GCCN have the greatest potential for enhancing the collection process. Thus, although drizzle production decreases with increasing CCN concentration, the relative impact of GCCN increases with increasing CCN concentration. It is also shown that in the absence of GCCN, a shift in the modal radius of the CCN distribution to larger sizes suppresses drizzle because larger modal radii enable the activation of larger droplet number concentrations. Finally, calculations of the impact of GCCN on cloud optical properties are performed over a range of parameter space. Results indicate that the presence of GCCN moderates the effect of CCN on optical properties quite significantly. In the absence of GCCN, an increase in CCN from 50 to 150 cm−3 results in a threefold increase in albedo; when GCCN exist at a concentration of 10−3 cm−3, the increase in albedo is only twofold. Thus the variable presence of GCCN represents yet another uncertainty in estimating the influence of anthropogenic activity on climate.

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Cynthia Rosenzweig, Radley M. Horton, Daniel A. Bader, Molly E. Brown, Russell DeYoung, Olga Dominguez, Merrilee Fellows, Lawrence Friedl, William Graham, Carlton Hall, Sam Higuchi, Laura Iraci, Gary Jedlovec, Jack Kaye, Max Loewenstein, Thomas Mace, Cristina Milesi, William Patzert, Paul W. Stackhouse Jr., and Kim Toufectis

A partnership between Earth scientists and institutional stewards is helping the National Aeronautics and Space Administration (NASA) prepare for a changing climate and growing climate-related vulnerabilities. An important part of this partnership is an agency-wide Climate Adaptation Science Investigator (CASI) Workgroup. CASI has thus far initiated 1) local workshops to introduce and improve planning for climate risks, 2) analysis of climate data and projections for each NASA Center, 3) climate impact and adaptation toolsets, and 4) Center-specific research and engagement.

Partnering scientists with managers aligns climate expertise with operations, leveraging research capabilities to improve decision-making and to tailor risk assessment at the local level. NASA has begun to institutionalize this ongoing process for climate risk management across the entire agency, and specific adaptation strategies are already being implemented.

A case study from Kennedy Space Center illustrates the CASI and workshop process, highlighting the need to protect launch infrastructure of strategic importance to the United States, as well as critical natural habitat. Unique research capabilities and a culture of risk management at NASA may offer a pathway for other organizations facing climate risks, promoting their resilience as part of community, regional, and national strategies.

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