Adele L. Igel

Momentum equations of hydrometeors and air variously forced by gravity and frictional dissipation are considered. Limiting cases are shown to reveal important behavior. The case of hydrometeors accelerating to the velocity of a constant horizontal wind reveals extremely long equilibration times due to friction alone. Velocity traces for the case of accelerating hydrometeors falling through air and the case of accelerating hydrometeors and air under the influence of gravity are found. They reveal that acceleration occurs for about twice as long as naive scaling would suggest. When the laden system can accelerate both horizontally and vertically, the solution to the momentum equations is complicated by the unique vector nature of the problem. Numerical solutions illustrate how drops act as a damper on the motion of air. A particular focus throughout is on the modification of terminal hydrometeor fall speeds due to multiple effects. Among these are enervation due to accounting for hydrometeor momentum, invigoration from viscous effects for the very smallest drops, and enervation from relative horizontal motion of particles during settling.

The overarching objective of this project was to use observations to evaluate hypotheses related to aerosol-induced invigoration or enervation of deep convective storms. We did so by tracking isolated, developing deep convective storms around SGP with GOES and pairing each storm with environmental conditions and aerosol measurements taken at SGP. The analysis was subject to numerous uncertainties and we could not draw strong conclusions about the magnitude of invigoration or enervation. That said, we could not disprove the hypothesis that aerosol-induced invigoration and enervation exist. Encouragingly, the results we found were largely consistent with existing hypotheses and previous modeling studies. Specifically, we found evidence that large concentrations of small aerosol particles promotes storms that develop more quickly while large concentrations of moderately sized particles are associated with less quickly developing storms. These signals are strengthened under some meteorological conditions and suggest convective environments to target for future study to study this phenomenon.

Previous modeling studies have shown a connection between higher aerosol concentrations and heightened updraft speeds in convective clouds, an effect known as aerosol‐induced invigoration. Observational evidence of this phenomenon, however, is inconclusive. We seek to provide a statistically robust, observational assessment of the effects of aerosol invigoration on isolated, developing, midlatitude, deep convective updraft speeds. This study uses geostationary satellite data to track approximately 225 storms over the Southern Great Plains. We show using cloud resolving model simulations that convective updraft speeds are proportional to the cloud top rise rate. After controlling for meteorology, the results suggest that high concentrations of small aerosol particles can invigorate convection, whereas accumulation mode particles may enervate updrafts at mid to upper levels of the storms. The statistical significance of an invigoration effect increases under environmental conditions that promote high supersaturation (strong updrafts, extensive warm phase regions), while the significance of an enervation response is enhanced under conditions that promote entrainment (high wind shear, lower cloud bases). These results are largely in agreement with many past modeling studies but have not been seen previously in observations. Our findings suggest that future efforts in the field should reject the framework of invigoration or enervation and instead focus on the specific conditions under which each response is expected.

We present an analysis of an adaptive time‐stepping scheme for the super‐droplet method (SDM), a Monte Carlo algorithm for simulating particle collision‐coalescence. SDM represents cloud droplets as weighted superdroplets, enabling high‐fidelity representations of microphysical processes such as collision‐coalescence. However, the algorithm can undercount collisions when the expected number of events is not realizable given the superdroplet configuration, introducing a systematic underestimation of collision events referred here as the collision deficit. This error can be addressed with adaptive time‐stepping, dynamically adjusting simulation timesteps to eliminate this deficit. We analyze the behavior of the deficit across a wide range of timesteps, superdroplet counts, and initialization strategies, and explore trade‐offs between accuracy and efficiency with adaptive time‐stepping. Using the classical Safranov‐Golovin test case, we show that the deficit increases with timestep and superdroplet count, and that adaptive time‐stepping effectively removes the associated error without significant cost. We test a smooth continuum of attribute initialization methods, and find that while the deficit is sensitive to the choice of sampling strategies, adaptive time‐stepping substantially reduces the difference. In 2‐D flow‐coupled simulations, we find the deficit can have a stronger effect on convergence than previously shown, with uncorrected deficit delaying precipitation onset. We also propose a method of visualization, capturing both the attribute sampling, droplet interactions over multiple timesteps, and the deficit using network connectivity graphs. We recommend implementation of adaptive time‐stepping, as it efficiently eliminates biased coalescence errors, increases robustness to initialization choices, and can have a noticeable impact in bulk properties.

The discussion of radiative cooling in cloud dynamics rarely considers quantities aside from the total radiative cooling over a cloud layer, which is constant for blackbody clouds in a given environment. However, here we demonstrate using idealized radiative transfer calculations that the total cooling in the upper part of the cloud increases with liquid water path up to ~100 g m ^{− 2} , well beyond the threshold liquid water path needed for a cloud to be a blackbody. Moreover, the maximum local cooling rate increases with LWP indefinitely. We then show using high-resolution simulations that the modulation of longwave radiative cooling profiles in blackbody clouds alters the dynamics, free tropospheric entrainment rates, liquid water path, and organization of closed cell stratocumulus clouds. We suggest that the role of longwave radiation in blackbody clouds, particularly in the context of aerosol-cloud interactions, should be given more consideration.

This study examines how different structural choices in bulk microphysics schemes impact the simulation of warm rain initiation. A single liquid category (SLC) approach prognosing up to four moments of a single drop size distribution (DSD) is compared to the traditional two‐category, two‐moment approach with separate DSDs for cloud and rain (four total prognostic variables). Different methods for calculating tendencies of the prognostic variables from drop collision‐coalescence are also tested: a discretized numerical‐integration approach, machine learning via neural networks, lookup tables, and traditional power law fits. Relative to simulations using a bin microphysics model, SLC gives smaller error overall than the two‐category approach when numerical integration is used to calculate the collision‐coalescence tendencies for both. Replacing the numerical integration with a pre‐computed lookup table reduces computational cost with little loss of accuracy. However, using fitted power laws with SLC to represent the collision‐coalescence tendencies substantially reduces accuracy and leads to an order of magnitude increase in error. It is also demonstrated that with SLC, reasonably accurate solutions are obtained using only three prognostic moments, while a two‐moment SLC scheme leads to substantial error. Overall, both the choice of prognostic moments (e.g., SLC vs. two‐category) and method to calculate the collision‐coalescence tendencies are important to consider for minimizing errors in bulk schemes. SLC with a sufficiently detailed calculation of the collision‐coalescence tendencies provides accurate solutions for a reasonable computational cost, providing a viable alternative to the traditional two‐category, two‐moment approach for bulk microphysics.

One common process for marine fog formation is cloud base lowering (CBL), which is frequently observed, for example, off the coast of California and in Canada's Grand Banks, as well as other foggy ocean regions. While previous studies have extensively examined the meteorological controls on CBL fog, its microphysical characteristics have received comparatively less attention. We employ a single-column model to investigate the interplay among aerosols, microphysics, and CBL fog evolution under diverse meteorological conditions. We find that lower aerosol concentrations make fog formation more probable but that if fog does form, fog water concentrations are lower. Lower aerosol concentrations lead to earlier fog formation due to faster gravitational settling of larger droplets, which serves to flux moisture downward. Faster gravitational settling (among other mechanisms at low aerosol concentration) also suppresses entrainment at cloud top, which aids in keeping the liquid water path high. However, faster gravitational settling also limits the fog water concentration through faster liquid deposition to the surface. It is these counteracting influences of gravitational settling that appear to cause both prolonged fog duration and suppressed fog water concentration. The relative strength of these counteracting influences depends on the environmental conditions.