Browsing by Author "van den Heever, Susan C., committee member"
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Item Open Access A new post-processing paradigm? Improving high-impact weather forecasts with machine learning(Colorado State University. Libraries, 2018) Herman, Gregory Reid, author; Schumacher, Russ S., advisor; Barnes, Elizabeth A., committee member; van den Heever, Susan C., committee member; Cooley, Daniel S., committee member; Hamill, Thomas M., committee memberHigh-impact weather comes in many different shapes, sizes, environments, and storm types, but all pose threats to human life, property, and the economy. Because of the significant societal hazards inflicted by these events, having skillful forecasts of the risks with sufficient lead time to make appropriate precautions is critical. In order to occur, these extreme events require a special conglomeration of unusual meteorological conditions. Consequently, effective forecasting of such events often requires different perspectives and tools than routine forecasts. A number of other factors make advance forecasts of rare, high-impact weather events particularly challenging, including the lack of sufficient resolution to adequately simulate the phenomena dynamically in a forecast model; model biases in representing storms, and which often become increasingly pronounced in extreme scenarios; and even difficulty in defining and verifying the high-impact event. This dissertation systematically addresses these recurring challenges for several types of high-impact weather: flash flooding and extreme rainfall, tornadoes, severe hail, and strong convective winds. For each listed phenomenon, research to more concretely define the current state of the science in analyzing, verifying, and forecasting the phenomenon. From there, in order to address the aforementioned persistent limitations with forecasting extreme weather events, machine learning-based post-processing models are developed to generate skillful, calibrated probabilistic forecasts for high-impact weather risk across the United States. Flash flooding is a notoriously challenging forecast problem. But the challenge is rooted even more fundamentally with difficulties in assessing and verifying flash flooding from observations due to the complex combination of hydrometeorological factors affecting flash flood occurrence and intensity. The first study in this dissertation investigates the multi-faceted flash flood analysis problem from a simplified framework considering only quantitative precipitation estimates (QPEs) to assess flash flood risk. Many different QPE-to-flash flood potential frameworks and QPE sources are considered over a multi-year evaluation period and QPE exceedances are compared against flash flood observations and warnings. No conclusive "best" flash flood analysis framework is clearly identified, though specific strengths and weaknesses of different approaches and QPE sources are identified in addition to regional differences in optimal correspondence with observations. The next two-part study accompanies the flash flood analysis investigation by approaching forecasting challenges associated with extreme precipitation. In particular, more than a decade of forecasts from a convection-parameterized global ensemble, the National Oceanic and Atmospheric Administration's Second Generation Global Ensemble Forecast System Reforecast (GEFS/R) model, are used to develop machine learning (ML) models for probabilistic prediction of extreme rainfall across the conterminous United States (CONUS) at Days 2 and 3. Both random forests (RFs) and logistic regression models (LR) are developed, with separate models trained for each lead time and for eight different CONUS regions. Models use the spatiotemporal evolution of a host of different atmospheric fields as predictors in addition to select geographic and climatological predictors. The models are evaluated over four years of withheld forecasts. The models, and particularly the RFs, are found to compare very favorably with both raw GEFS/R ensemble forecasts and those from a superior global ensemble produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) both in terms of forecast skill and reliability. The trained models are also inspected to discern what statistical findings are identified through ML. Many of the findings quantify anecdotal knowledge that is already recognized regarding the forecast problem, such as the relative skill of simulated precipitation in areas where extreme precipitation events are associated with large-scale processes well resolved by the GEFS/R compared with areas where extreme precipitation predominantly occurs in association with convection in the warm-season. But more subtle spatiotemporal biases are also diagnosed, including a northern displacement bias in the placement of convective systems and a southern displacement bias in placing landfalling atmospheric rivers. The final extended study shifts weather phenomenon focus from extreme rainfall to severe weather: tornadoes, large hail, and severe convective winds. While both high-impact, the two classes of weather hazards share some commonalities and contrasts. While rainfall is directly forecast by dynamical weather models, most severe weather occurs on too small of spatial scales to be directly simulated by the same models. Consequently, unlike with extreme precipitation, when developing post-processed severe weather forecasts, there is no obvious benchmark for objectively determining whether and how much improvement the post-processing is yielding. A natural alternative, albeit much more stringent, benchmark is operational forecasts produced by human forecasters. Operational severe weather forecasts are produced by the Storm Prediction Center (SPC), but there is limited published verification of their outlooks quantifying their probabilistic skill. In the first part of this study, an extended record SPC severe weather outlooks were evaluated to quantitatively assess the state of operational severe weather forecasting, including strengths and weaknesses. SPC convective outlooks were found to decrease in skill with increased forecast lead time, and were most skillful for severe winds, with the worst performance for tornado outlooks. Many seasonal and regional variations were also observed, with performance generally best in the North and East and worst in the South and especially West. The second part of the study follows similar methodology to the extreme precipitation models, developing RF-based probabilistic forecast models forced from the GEFS/R for Days 1--3 across CONUS, analogous to the format in which SPC produces its convective outlooks. RF properties are inspected to investigate the statistical relationships identified between GEFS/R fields and severe weather occurrence. Like with the extreme precipitation model, RF severe weather forecasts are generated and evaluated from several years of withheld validation cases. These forecasts are compared alongside SPC outlooks and also blended with them to produce a combined forecast. Overall, by statistically quantifying relationships between the synoptic-scale environment and severe weather in a manner consistent with the community's physical understanding of the forecast problems, the RF models are able to demonstrate skill over SPC outlooks at Days 2 and 3, and can be blended with SPC outlooks to enhance skill at Day 1. Overall, multiple high-impact weather phenomena---extreme precipitation and severe weather---are investigated from verification, analysis, and forecasting standpoints. On verification and analysis, foundations have been laid both to improve existing operational products as well as better frame and contextualize future studies. ML post-processing models developed were highly successful in advancing forecast skill and reliability for these hazardous weather phenomena despite being developed from predictors of a coarse, dated dynamical model in the GEFS/R. The findings also suggest adaptability across a wide array of forecast problems, types of predictor inputs, and lead times, raising the possibility of broader applicability of these methods in operational numerical weather prediction.Item Open Access A triple-moment bulk hail microphysics scheme to investigate the sensitivities of hail to aerosols(Colorado State University. Libraries, 2012) Loftus, Adrian Matthew, author; Cotton, William R., advisor; Rutledge, Steven A., committee member; van den Heever, Susan C., committee member; Bringi, Viswanathan N., committee memberHail is a frequent occurrence in warm season deep convection in many mid-latitude regions and causes significant damage to property and agricultural interests every year. Hail can also have a substantial impact on the precipitation characteristics of deep convection as well as on the dynamic and thermodynamic properties of convective downdrafts and cold-pools, which in turn can affect storm evolution and propagation. In addition, large and often destructive hail commonly occurs in severe convection, yet most one- (1M) and two-moment (2M) bulk microphysics schemes in cloud-resolving numerical models are incapable of producing large hail (diameter D ≥ 2 cm). The limits imposed by fixing one or two of the distribution parameters in these schemes often lead to particularly poor representations of particles within the tails of size distribution spectra; an especially important consideration for hail, which covers a broad range of sizes in nature. In order to improve the representation of hail distributions in simulations of deep moist convection in a cloud-resolving numerical model, a new triple-moment bulk hail microphysics scheme (3MHAIL) is presented and evaluated. The 3MHAIL scheme predicts the relative dispersion parameter for a gamma distribution function via the prediction of the sixth moment (related to the reflectivity factor) of the distribution in addition to the mass mixing ratio and number concentration (third and zeroeth moments, respectively) thereby allowing for a fully prognostic distribution function. Initial testing of this scheme reveals significant improvement in the representation of sedimentation, melting, and formation processes of hail compared to lower-order moment schemes. The 3MHAIL scheme is verified in simulations of a well-observed supercell storm that occurred over northwest Kansas on 29 June 2000 during the Severe Thunderstorm and Electrification and Precipitation Study (STEPS). Comparisons of the simulation results with the observations for this case, as well as with results of simulations using two different 2M microphysics schemes, suggest a significant improvement of the simulated storm structure and evolution is achieved with the 3MHAIL scheme. The generation of large hail and subsequent fallout in the simulation using 3MHAIL microphysics show particularly good agreement with surface hail reports for this storm as well as with previous studies of hail in supercell storms. On the other hand, the simulation with 2M microphysics produces only small hail aloft and virtually no hail at the surface, whereas a two-moment version of the 3MHAIL scheme (with a fixed relative dispersion parameter) produces unrealistically high amounts of large hail at low levels as a result of artificial shifts in the hail size spectra towards larger diameter hail during the melting process. The 3MHAIL scheme is also used to investigate the impact of changing the concentrations of aerosols that act as cloud condensation nuclei (CCN) on hail for the 29 June 2000 supercell case. For the simulated supercells in the particular environment examined, an increase in CCN from 100 to 3000 cm-3 leads to an increase in the numbers and a decrease in the sizes of cloud droplets, as expected, yet the overall storm dynamics and evolution are largely unaffected. Increases in CCN lead to non-monotonic responses in the bulk characteristics of nearly all hydrometeor fields, surface precipitation, and cold-pool strength. However, higher concentrations of CCN also result in larger hail sizes and greater amounts of large diameter (≥ 2 cm) hail both aloft as well as at the surface. Analyses of the hail formation and growth mechanisms for these simulations suggest that the combination of increased sizes of new hail particles and localized reductions in numbers of new hailstones forming near maximum growth regions with increasing CCN tends to promote conditions that lead to increased hail sizes and amounts of large hail.Item Open Access Building the foundations for a physically based passive microwave precipitation retrieval algorithm over the US Southern Great Plains(Colorado State University. Libraries, 2015) Ringerud, Sarah, author; Kummerow, Christian D., advisor; Peters-Lidard, Christa D., advisor; Reising, Steven C., committee member; van den Heever, Susan C., committee member; Vonder Haar, Thomas H., committee memberThe recently launched NASA Global Precipitation Measurement Mission (GPM) offers the opportunity for a greatly increased understanding of global rainfall and the hydrologic cycle. The GPM algorithm team has made improvements in passive microwave remote sensing of precipitation over land a priority for this mission, and implemented a framework allowing for algorithm advancement for individual land surface types as new techniques are developed. In contrast to the radiometrically cold ocean surface, land emissivity in the microwave is large with highly dynamic variability. An accurate understanding of the instantaneous, dynamic emissivity in terms of the associated surface properties is necessary for a physically based retrieval scheme over land, along with realistic profiles of frozen and liquid hydrometeors. In an effort to better simulate land surface microwave emissivity, a combined modeling technique is developed and tested over the US Southern Great Plains (SGP) area. The National Centers for Environmental Prediction (NCEP) Noah land surface model is utilized for surface information, with inputs optimized for SGP. A physical emissivity model, using land surface model data as input, is used to calculate emissivity at the 10 GHz frequency, combining contributions from the underlying soil and vegetation layers, including the dielectric and roughness effects of each medium. An empirical technique is then applied, based upon a robust set of observed channel covariances, extending the emissivity calculations to all channels. The resulting emissivities can then be implemented in calculation of upwelling microwave radiance, and combined with ancillary datasets to compute brightness temperatures (Tbs) at the top of the atmosphere (TOA). For calculation of the hydrometeor contribution, reflectivity profiles from the Tropical Rainfall Measurement Mission Precipitation Radar (TRMM-PR) are utilized along with coincident Tbs from the TRMM radiometer (TMI), and cloud resolving model data from NASA-Goddard's MMF model. Ice profiles are modified to be consistent with the higher frequency microwave Tbs. Resulting modeled TOA Tbs show correlations to observations of 0.9 along with biases 1K or less and small RMS error and show improved agreement over the use of climatological emissivity values. The synthesis of the emissivity and cloud resolving model input with satellite and ancillary datasets leads to creation of a unique Tb database for SGP that includes both dynamic surface and atmospheric information physically consistent with the LSM, emissivity model, and atmospheric information, for use in a Bayesian-type precipitation retrieval scheme utilizing a technique that can easily be applied to GPM as data becomes available.Item Open Access Impacts of assimilating vertical velocity, latent heating, or hydrometeor water contents retrieved from a single reflectivity data set(Colorado State University. Libraries, 2017) Lee, Yoonjin, author; Kummerow, Christian D., advisor; Zupanski, Milija, advisor; Reising, Steven C., committee member; van den Heever, Susan C., committee memberAssimilation of observation data in cloudy regions has been challenging due to the unknown properties of clouds such as cloud depth, cloud vertical profiles, or cloud drop size distributions. Attempts to assimilate data in cloudy regions generally assume a drop size distribution, but most assimilation systems fail to maintain consistency between models and the observation data, as each has its own set of assumptions. This study tries to retain the consistency between the forecast model and the retrieved data by developing a Bayesian retrieval scheme that uses the forecast model itself for the a-priori database. Through the retrieval algorithm, vertical profiles of three variables related to the development of tropical cyclones, including vertical velocity, latent heating, and hydrometeor water contents are derived from the same reflectivity observation. Vertical velocity and latent heating are variables related to dynamical processes of tropical cyclones, whereas hydrometeors are byproducts of those processes. Each retrieved variable is assimilated in the data assimilation system using a flow dependent forecast error covariance matrix. The simulations are compared to evaluate the respective impact of each variable in the assimilation system. In this study, the three assimilation experiments were conducted for two hurricane cases captured by the Global Precipitation Measurement (GPM) satellite: Hurricane Pali and Hurricane Jimena. Analyses from these two hurricane cases suggest that assimilating latent heating and hydrometeor water contents have similar impacts on the assimilation system while vertical velocity has less of an impact than the other two variables. Using these analyses as an initial condition for the forecast model reveals that the assimilations of retrieved latent heating and hydrometeor water contents were also able to improve the track forecast of Hurricane Jimena.Item Open Access Insights into extreme short-term precipitation associated with supercells and mesovortices(Colorado State University. Libraries, 2019) Nielsen, Erik R., author; Schumacher, Russ S., advisor; van den Heever, Susan C., committee member; Bell, Michael M., committee member; Niemann, Jeffrey D., committee memberOverall, this manuscript aims to holistically evaluate the relationship between rotation and extreme precipitation processes, since radar and rain-gauge observations in several flash flooding events have suggested that the heaviest short-term rainfall accumulations were associated with supercells or mesovortices embedded within larger convective systems. A specific subclass of these events, when tornadoes and flash floods are both concurrent and collocated (referred to here at TORFF events), present a unique set of concerns, since the recommended life-saving actions for each threat are contradictory. Given this, Chapter 2 aims to evaluate the climatological and meteorological characteristics associated with TORFF events over the United States. Two separate datasets, one based on overlapping tornado and flash flood warnings and the other based on observations, were used to arrive at estimations of the instances when a TORFF event was deemed imminent and verified to have occurred, respectively. These datasets, combined with field project data, were then used to discern the geographical and meteorological characteristics of recent TORFF events. The results show that TORFF scenarios commonly occur, are not easily distinguishable from tornadic events that fail to produce collocated flash flooding, and present difficult challenges both from the perspective of forecasting and public communication. The research in Chapter 3 strives to identify the influence that rotation has on the storm-scale processes associated with heavy precipitation. Five total idealized simulations of a TORFF event, where the magnitude of the 0-1 km shear was varied, were performed to test the sensitivity of precipitation processes to rotation. In the simulations with greater environmental low-level shear and associated rotation, more precipitation fell, both in a point maximum and area-averaged sense. Intense, rotationally induced low-level vertical accelerations associated with the dynamic nonlinear perturbation vertical pressure gradient force were found to enhance the low-to-mid level updraft strength, total vertical mass flux, and allowed access to otherwise inhibited sources of moisture and CAPE in the higher shear simulations. The dynamical accelerations, which increased with the intensity of the low-level shear, dominated over buoyant accelerations in the low levels and were responsible for inducing more intense, low-level updrafts that were sustained despite a stable boundary layer. Chapter 4 aims to explore how often extreme short-term rain rates in the United States are associated with storm-scale or mesoscale vortices, since significant low-level rotation does not always yield a tornado (i.e., not all extreme rainfall events are TORFFs). Five years of METAR observations and three years of Stage-IV analyses were obtained and filtered for hourly accumulations over 75 and 100 mm, respectively. Local dual-pol radar data was then obtained for the remaining events for the hour leading up to the METAR observation. Nearly 50% of the cases were associated with low-level rotation in high-precipitation supercells and/or mesoscale vortices embedded in more organized storm modes. These results support recent modeling results, presented in Chapter 3, suggesting that rotationally induced dynamic vertical pressure accelerations are important to the precipitation formation mechanisms that lead to extreme short-term rainfall rates. The upper Texas Coast, in and around the Houston, TX area, has experienced many intense TORFF events over the recent years. The research in Chapter 5 focuses on examining the horizontally heterogeneous environmental characteristics associated with one of those events, the Tax Day flood of 2016, which was identified as a "verified" TORFF event in Chapter 2. Radar and local mesonet rain gauge observations were used to examine the storm scale characteristics to identify the locations and structures of extreme rain rate producing cells. To supplement the observational based analysis above, a WRF-ARW simulation of the Tax Day flood in 2016, based upon a real-time forecast from the HRRR, was examined. Convective cells that produced the most intense short-term (i.e., sub-hourly to hourly) accumulations within the MCS were examined for the influence of any attendant rotation on both the dynamics and microphysics of the precipitation processes. Results show that the most intense rainfall accumulations, as in the observations analysis, are associated with rotating convective elements, and the results of this chapter confirm that the processes described in Chapter 3 apply outside of the idealized framework.Item Embargo Marine ice nucleating particles: sources, composition, emissions, and model parameterizations(Colorado State University. Libraries, 2023) Moore, Kathryn A., author; Kreidenweis, Sonia M., advisor; DeMott, Paul J., advisor; Farmer, Delphine K., committee member; Pierce, Jeffrey R., committee member; van den Heever, Susan C., committee memberSea spray aerosol has received increasing attention over the last decade as a source of ice nucleating particles (INPs) to the atmosphere. Sparse measurements in remote marine regions indicate both marine INP concentrations and ice nucleating efficiency are several orders of magnitude lower than those of mineral or soil dusts, which dominate the INP budget on a global scale. The Southern Ocean (SO) surrounding Antarctica is thought to be the only region where marine INPs are the predominant INP type due to its remoteness from continental and anthropogenic aerosol sources and persistent strong westerlies, although several recent studies have suggested this may also be true of the high Arctic seasonally or intermittently. INPs are critical for initiating cloud glaciation at temperatures warmer than ~-36 °C and can thus have an outsize effect on cloud phase and related climate feedbacks due to their relative scarcity. This is particularly true over the polar oceans, where low and mid-level mixed phase and supercooled clouds are ubiquitous and especially sensitive to aerosols due to the generally low background particle concentrations. The research presented here aimed to improve our understanding of the factors influencing marine INP emissions and the sources and composition of INPs in remote marine regions, as well as to evaluate and improve current INP model parameterizations. This was accomplished using observations made in the Southern Ocean, one of the few remaining pristine aerosol environments, during the Southern Ocean Cloud Radiation Aerosol Transport Experimental Study (SOCRATES) aircraft campaign on the NSF/NCAR G-V, and the second Clouds, Aerosols, Precipitation, Radiation and atmospherIc Composition Over the southeRN ocean (CAPRICORN-2) ship campaign on the R/V Investigator in 2018. Ambient observations were supplemented by measurements from the CHaracterizing Atmosphere-Ocean parameters in SOARS (CHAOS) mesocosm experiment in the new Scripps Ocean-Atmosphere Research Simulator (SOARS) wind-wave channel. CHAOS measurements allowed for isolation of the role of wind speed in marine INP production, which had not previously been characterized through controlled experiments. SOCRATES and CAPRICORN-2 are notable for collecting the first vertically resolved INP measurements over the Southern Ocean, including the first in situ observations in and above cloud in the region. Both aerosol and INP concentrations showed excellent agreement between G-V and R/V Investigator observations during overflights of the ship, supporting the use of such a multi-platform measurement approach for future campaigns interested in aerosol and INP vertical profiles. New techniques for estimating marine aerosol surface area and the number of particles >0.5 μm, key quantities often used in INP parameterizations, were developed based on lidar and nephelometer measurements. An additional parameterization for marine INPs is proposed, which uses both wind speed and activation temperature, and reduces bias compared to the existing parameterization based solely on temperature. Marine boundary layer (MBL) and above cloud INP concentrations from the same SOCRATES flight support the hypothesis suggested by several modeling studies that marine INPs dominate at low altitudes, and mineral dust becomes increasingly important with height. Unexpectedly, enhanced INP and aerosol iron concentrations, but low iron solubilities, were observed for samples collected south of 60 °S during CAPRICORN-2. Antarctica is suggested as a potential source of both biological and inorganic INPs to the Southern Ocean marine boundary layer through the emission of mineral and soil dusts from ice-free areas. Similar high latitude dust sources in Iceland and Svalbard have been observed to contribute to INPs in the Arctic atmosphere, and are anticipated to increase in importance as the climate warms.Item Open Access Microphysical and macrophysical responses of marine stratocumulus polluted by underlying ships(Colorado State University. Libraries, 2012) Christensen, Matthew Wells, author; Stephens, Graeme, advisor; Kummerow, Christian, committee member; van den Heever, Susan C., committee member; Reising, Steven, committee memberMultiple sensors flying in the A-train constellation of satellites were used to determine the extent to which aerosol plumes from ships passing below marine stratocumulus alter the microphysical and macrophysical properties of the clouds. Aerosol plumes generated by ships sometimes influence cloud microphysical properties (effective radius) and, to a largely undetermined extent, cloud macrophysical properties (liquid water path, coverage, depth, precipitation, and longevity). Aerosol indirect effects were brought into focus, using observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the 94-GHZ radar onboard CloudSat. To assess local cloud scale responses to aerosol, the locations of over one thousand ship tracks coinciding with the radar were meticulously logged by hand from the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. MODIS imagery was used to distinguish ship tracks that were embedded in closed, open, and unclassifiable mesoscale cellular cloud structures. The impact of aerosol on the microphysical cloud properties in both the closed and open cell regimes were consistent with the changes predicted by the Twomey hypothesis. For the macrophysical changes, differences in the sign and magnitude of these properties were observed between cloud regimes. The results demonstrate that the spatial extent of rainfall (rain cover fraction) and intensity decrease in the clouds contaminated by the ship plume compared to the ambient pristine clouds. Although reductions of precipitation were common amongst the clouds with detectable rainfall (72% of cases), a substantial fraction of ship tracks (28% of cases) exhibited the opposite response. The sign and strength of the response was tied to the type of stratocumulus (e.g., closed vs open cells), depth of the boundary layer, and humidity in the free-troposphere. When closed cellular clouds were identified, liquid water path, drizzle rate, and rain cover fraction (an average relative decrease of 61%) was significantly smaller in the ship-contaminated clouds. Differences in drizzle rate resulted primarily from the reductions in rain cover fraction (i.e., fewer pixels were identified with rain in the clouds polluted by the ship). The opposite occurred in the open cell regime. Ship plumes ingested into this regime resulted in significantly deeper and brighter clouds with higher liquid water amounts and rain rates. Enhanced rain rates (average relative increase of 89%) were primarily due to the changes in intensity (i.e., rain rates on the 1.1 km pixel scale were higher in the ship contaminated clouds) and, to a lesser extent, rain cover fraction. One implication for these differences is that the local aerosol indirect radiative forcing was more than five times larger for ship tracks observed in the open cell regime (-59 W m-2) compared to those identified in the closed cell regime (-12 W m-2). The results presented here underline the need to consider the mesoscale structure of stratocumulus when examining the cloud dynamic response to changes in aerosol concentration. In the final part of the dissertation, the focus shifted to the climate scale to examine the impact of shipping on the Earth's radiation budget. Two studies were employed, in the first; changes to the radiative properties of boundary layer clouds (i.e., cloud top heights less than 3 km) were examined in response to the substantial decreases in ship traffic that resulted from the recent world economic recession in 2008. Differences in the annually averaged droplet effective radius and top of atmosphere outgoing shortwave radiative flux between 2007 and 2009 did not manifest as a clear response in the climate system and, was probably masked either due to competing aerosol cloud feedbacks or by interannual climate variability. In the second study, a method was developed to estimate the radiative forcing from shipping by convolving lanes of densely populated ships onto the global distributions of closed and open cell stratocumulus clouds. Closed cells were observed more than twice as often as open cells. Despite the smaller abundance of open cells, a significant portion of the radiative forcing from shipping was claimed by this regime. On the whole, the global radiative forcing from ship tracks was small (approximately -0.45 mW m-2) compared to the radiative forcing associated with the atmospheric buildup of anthropogenic CO2.Item Open Access Observations of atmospheric reactive nitrogen species and nitrogen deposition in the Rocky Mountains(Colorado State University. Libraries, 2012) Benedict, Katherine B., author; Collett, Jeffrey L., advisor; Kreidenweis, Sonia M., committee member; van den Heever, Susan C., committee member; Hamm, Jay, committee memberTo view the abstract, please see the full text of the document.Item Open Access On the environments and dynamics of nocturnal mesoscale convective systems(Colorado State University. Libraries, 2018) Hitchcock, Stacey, author; Schumacher, Russ S., advisor; Randall, David A., committee member; van den Heever, Susan C., committee member; Eykholt, Richard, committee memberThe 2015 Plains Elevated Convection at Night (PECAN) field campaign was motivated by unanswered questions about key processes in elevated mesoscale convective systems (MCSs) and the difficulty in accurately forecasting them. During the campaign, 15 MCS environments were sampled by an array of instruments including radiosondes launched by fixed and mobile sounding teams. Cluster analysis of observed vertical profiles established three primary pre-convective categories. Only one of these groups fits well with the common conceptual model of nocturnal MCS environments where equivalent potential temperature increases in an elevated layer with the onset of the low-level jet (LLJ). Post-convective soundings demonstrate substantial variability, but cold pools were observed in nearly every PECAN MCS case. However, stronger, deeper stable layers appear to lead to structures where the largest cooling is observed above the surface. On 24-25 June 2015, a 'bow-and-arrow' MCS structure was observed in an environment with strong low-level stability. Previous work on the mechanisms that support the structure in the arrow region (also sometimes referred to as rearward off-boundary development or ROD) has relied on a combination of a surface cold pool and large scale ascent provided by the interaction of a LLJ with a baroclinic zone. A horizontally homogeneous simulation initialized with a near-storm pre-convective PECAN sounding from the 24-25 June 2015 produces nearly the same MCS structure in the absence of a surface cold pool. Instead, outflow takes on several different forms in different regions of the MCS. Ultimately, the ROD (or arrow) is most likely supported by gravity wave amplified by vertical wind shear over the same layer, and maintained by persistent downdrafts. The success of both MCS initiation and development of ROD despite the strong stable layer and idealized horizontally homogeneous initial conditions suggests that the interactions between convective outflow and a stable layer in a sheared environment are important in both of these processes. Very few studies to date have explored these interactions, and even less in 3D. A series of 2D and 3D experiments were designed to explore 1) What happens when a downdraft impacts a stable layer with and without shear? 2) What low-level shear profiles support MCS development in an idealized simulation with strong stability and why? 3) What shear characteristics are favorable for ROD development? Results indicate that strong low level shear is critical for sustaining convection, that low-level shear may be as important as stability in determining the effective inflow layer, and that upper level winds play a critical role in the development of ROD.Item Open Access Potential indirect effects of aerosol on tropical cyclone development(Colorado State University. Libraries, 2010) Krall, Geoffrey Michael, author; Cotton, William R., advisor; van den Heever, Susan C., committee member; Eykholt, Richard Eric, 1956-, committee memberObservational and model evidence suggest that a 2008 Western Pacific typhoon (NURI) came into contact with and ingested elevated concentrations of aerosol as it neared the Chinese coast. This study uses a regional model with two-moment bin emulating microphysics to simulate the typhoon as it enters the field of elevated aerosol concentration. A continental field of cloud condensation nuclei (CCN) was prescribed based on satellite and global aerosol model output, then increased for further sensitivity tests. The typhoon was simulated for 96 hours beginning 17 August 2008, the final 60 of which were under varying CCN concentrations as it neared the Philippines and coastal China. The model was initialized with both global reanalysis model data and irregularly spaced dropsonde data from a 2008 observational campaign using an objective analysis routine. At 36 hours, the internal nudging of the model was switched off and allowed to evolve on its own. As the typhoon entered the field of elevated CCN in the sensitivity tests, the presence of additional CCN resulted in a significant perturbation of windspeed, convective fluxes, and hydrometeor species behavior. Initially ingested in the outer rainbands of the storm, the additional CCN resulted in an initial damping and subsequent invigoration of convection. The increase in convective fluxes strongly lag-correlates with increased amounts of supercooled liquid water within the storm domain. As the convection intensified in the outer rainbands the storm drifted over the developing cold-pools, affecting the inflow of air into the convective towers of the typhoon. Changes in the timing and amount of rain produced in each simulation resulted in differing cold-pool strengths and size. The presence of additional CCN increased resulted in an amplification of convection within the storm, except for the extremely high CCN concentration simulation, which showed a damped convection due to the advection of pristine ice away from the storm. This study examines the physical mechanisms that could potentially alter a tropical cyclone (TC) in intensity and dynamics upon ingesting elevated levels of CCN.Item Open Access Reconciling TRMM precipitation estimates related to El Niño Southern Oscillation variability(Colorado State University. Libraries, 2017) Henderson, David S., author; Kummerow, Christian D., advisor; van den Heever, Susan C., committee member; Rutledge, Steven, committee member; Notaros, Branislav, committee memberOver the tropical oceans, large discrepancies in TRMM passive and active microwave rainfall retrievals become apparent during El Niño-Southern Oscillation (ENSO) events, where TMI retrievals exhibit a systematic shift in precipitation seemingly correlated with ENSO phase, while the PR does not. To investigate the causality of this relationship, this dissertation focuses, both spatially and temporally, on the evolution of precipitation organization between El Niño and La Niña conditions and their impacts on TRMM TMI and PR retrieved precipitation through the use of ground validation (GV) and satellite-based sources. The precipitation validation is performed as a function of convective organization through implementation of defined precipitation regimes, which have physical characteristics consistent across meteorological regimes. Before a full evaluation of TRMM retrieved rain rates is completed, an assessment of TRMM ground validation (GV) oceanic rain rate estimates is necessary. The robustness of radar-based GV rainfall estimates from the Kwajalein S-band KPOL radar are examined through comparisons with the Kwajalein rain gauge network. The TRMM-GV 2A53 rainfall product is found to heavily underestimate convective rain types, where prominent biases occur as precipitation becomes more organized. To further examine these rainfall biases, GV and polarimetrically-tuned rain rates are compared, where GV biases in both the 2A53 product and convective and stratiform Z-R relationships are minimized when the rain rate relationships are developed specifically as a function of precipitation regime. The results demonstrate that exploration into precipitation regimes should be considered when deriving and evaluating rain relationships to establish the source and range of uncertainties existing within different precipitating systems. TRMM radar (PR) and radiometer (TMI) rain rates are then evaluated though multiple case studies of collocated TRMM and KPOL rain rates at the 1°x1° and TMI footprint scale. The results of this study indicate that TRMM TMI and PR rainfall biases are best explained when derived as a function of organization and convective fraction. Large underestimates in both TMI and PR rain rates are associated with predominately convective rainfall across all regimes, where TMI rainfall underestimates both PR and GV rain rates. While PR rain rate estimates typically underestimate GV rainfall, TMI rain rates are heavily overestimated in rainfall regimes containing predominantly stratiform precipitation. Over the Kwajalein region, differences in TMI and PR rain rates seem to be driven by the occurrence of organized precipitation, where TMI-PR differences during El Niño conditions largely derive from MCS-like precipitating systems containing large stratiform precipitating regions. Application of the resultant biases helps mitigate the TMI-PR differences occurring between the ENSO phases and explain uncertainties introduced by the TMI Bayesian retrieval. Expanding the analysis tropics-wide, TRMM discrepancies directly relate to a shift from isolated deep convection during La Niña events toward organized precipitation during El Niño events with the largest variability occurring in the Pacific basins. During El Niño conditions, an increase in stratiform raining fraction leads to an increase in TMI rain rates that is less prevalent in PR rain rate retrievals. Reanalysis and AIRS data indicate that higher occurrences in organized systems are aided by increased mid- and upper-tropospheric moisture accompanied by more frequent deep convection. During La Niña events tropical rainfall is dominated by isolated deep convective regimes associated with drier mid-tropospheric conditions and strong mid- and upper level zonal wind shear. Application of the known TMI and PR biases yields increased consistency in PR rainfall with the radiometer-based TMI and GPCP rainfall estimates. The resultant satellite-based rainfall estimates are in general agreement when describing the response of tropical precipitation to ENSO induced variability in tropical SSTs.Item Open Access Remote continental aerosol characteristics in the Rocky Mountains of Colorado and Wyoming(Colorado State University. Libraries, 2013) Levin, Ezra JT, author; Kreidenweis, Sonia M., advisor; Collett, Jeffrey L., committee member; van den Heever, Susan C., committee member; Ham, Jay, committee memberThe Rocky Mountains of Colorado and Wyoming enjoy some of the cleanest air in the United States, with few local sources of particulate matter or its precursors apart from fire emissions, windblown dust, and biogenic emissions. However, anthropogenic influences are also present with sources as diverse as the populated Front Range, large isolated power plants, agricultural emissions, and more recently emissions from increased oil and gas exploration and production. While long-term data exist on the bulk composition of background fine particulate matter at remote sites in the region, few long-term observations exist of aerosol size distributions, number concentrations and size resolved composition, although these characteristics are closely tied to important water resource issues through the potential aerosol impacts on clouds and precipitation. Recent modeling work suggests sensitivity of precipitation-producing systems to the availability of aerosols capable of serving as cloud condensation nuclei (CCN); however, model inputs for these aerosols are not well constrained due to the scarcity of data. In this work I present aerosol number and volume concentrations, size distributions, chemical composition and hygroscopicity measurements from long-term field campaigns. I also explore the volatility of organic material from biomass burning and the potential impacts on aerosol loading. Relevant aerosol observations were obtained in several long-term field studies: the Rocky Mountain Atmospheric Nitrogen and Sulfur study (RoMANS, Colorado), the Grand Tetons Reactive Nitrogen Deposition Study (GrandTReNDS, Wyoming) and as part of the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen project (BEACHON, Colorado). Average number concentrations (0.04 < Dp < 20 μm) measured during the field studies ranged between 1000 - 2000 cm-3 during the summer months and decreased to 200 - 500 cm-3 during the winter. These seasonal changes in aerosol number concentrations were correlated with the frequency of events typical of new particle formation. Measured sub-micron organic mass fractions were between 70 - 90% during the summer months, when new particle formation events were most frequent, suggesting the importance of organic species in the nucleation or growth process, or both. Aerosol composition derived from hygroscopicity measurements indicate organic mass fractions of 50 - 60% for particles with diameters larger than 0.15 μm during the winter. The composition of smaller diameter particles appeared to be organic dominated year-round. High organic mass fractions led to low values of aerosol hygroscopicity, described using the κ parameter. Over the entire year-long BEACHON study, κ had an average value of 0.16 ± 0.08, similar to values determined during biologically active periods in tropical and boreal forests, and lower than the commonly assumed value of κcontinental = 0.3. There was also an observed increase in κ with size, due to external mixing of the fine mode aerosol. Incorrect representations of κ or its size dependence led to erroneous values of calculated CCN concentrations, especially for supersaturation values less than 0.3%. At higher supersaturations, most of the measured variability in CCN concentrations was captured by changes in total measured aerosol number concentrations. While data from the three measurement sites were generally well correlated, indicating similarities in seasonal cycles and in total number concentrations, there were some variations between measurements made at different sites and during different years that may be partly due to the effects of local emissions. The averaged data provide reasonable, observationally-based parameters for modeling of aerosol number size distributions and corresponding CCN concentrations. Field observations clearly indicated the episodic influence of wildfire smoke on particle number concentrations and compositions. However, the semi-volatile nature of the organic carbon species emitted makes it difficult to predict how much of the emitted organic mass will remain in the condensed phase downwind. To better constrain the volatility of organic species in smoke, emissions from laboratory biomass combustion experiments were subjected to quantified dilution, resulting in reduction of aerosol mass concentrations over several orders of magnitude and a corresponding volatilization response of the organic particles that was fit to the commonly-applied Volatility Basis Set. Organic emissions from all burns with initial organic aerosol concentrations greater than 1000 μg m-3 contained material with saturation concentration values ranging between 1 and 10,000 μg m-3, with most of the organic mass falling at the two extremes of this range. For most burns, a single distribution was able to capture the volatility behavior of the organic material, within experimental uncertainty, despite the considerable variability in fuel and fire characteristics, suggesting that a simplified two-product model of gas-aerosol partitioning may be adequate to describe the evolution of biomass burning organic aerosol in models.Item Open Access Seasonal, synoptic, and intraseasonal variability of the West African monsoon(Colorado State University. Libraries, 2012) McCrary, Rachel Rose, author; Randall, David A., advisor; Denning, A. Scott, committee member; van den Heever, Susan C., committee member; Betsill, Michele, committee memberThe simulation of the West African monsoon is examined in two coupled general circulation models (CGCMs). The first model is the standard Community Climate System Model (CCSM) which uses traditional parameterizations to represent convective processes. The second model is the superparameterized-CCSM (SP-CCSM), in which convective parameterizations have been replaced by embedding a two-dimensional cloud resolving model into each gridbox. Superparameterization is intended to improve simulation of the complex multiscale interactions that occur between the large-scale environment and clouds. Key features of West African climate are analyzed in both models including: the mean annual cycle of the monsoon, African easterly wave (AEW) activity and dynamics, and the intraseasonal modulation of precipitation. Adding superparameterization improves the position and intensity of the summer maximum in precipitation which is shifted from over the Gulf of Guinea in CCSM (not realistic), to over the continent in SP-CCSM which is in keeping with the observations. AEWs and their relationship with convection are also improved in the SP-CCSM: In the standard model, little to no easterly wave activity occurs over West Africa, and the relationship with convection is tenuous at best. SP-CCSM on the other hand produces strong AEWs over the region that exhibit similar horizontal and vertical structures to observations. AEWs in SP-CCSM are strongly coupled to convection, more so than is supported by observations. An examination of the energetics of the simulated AEWs suggests that convection drives the generation and propagation the waves in SP- CCSM. Consistent with observations, intraseasonal variations in West African precipitation in SP-CCSM appear to be linked to variations in convection in the Indo-Pacific region corresponding with the MJO and the Indian monsoon. Because of these physically-realistic relationships, SP-CCSM has potential to deepen our understanding of the teleconnections between the MJO and West Africa, helping to improve seasonal rainfall forecasts.Item Open Access Source apportionment of aerosol measured in the northern South China Sea during springtime(Colorado State University. Libraries, 2012) Atwood, Samuel A., author; Kreidenweis, Sonia M., advisor; van den Heever, Susan C., committee member; Peel, Jennifer L., committee memberLarge sources of aerosol are known to exist in Asia, but the nature of these sources and their impacts on surface particulate matter concentrations are presently not well understood, due in part to the complex meteorology in the region and the lack of speciated aerosol observations. This work presents findings from a pilot study that was aimed at improving knowledge in these areas. Aerosol was collected at a sea-level surface site using an 8-stage DRUM cascade impactor during an approximately six week study at Dongsha Island in the northern South China Sea in the Spring of 2010. The samples were analyzed by X-ray fluorescence (XRF) for selected elemental concentrations, and factor analysis was performed on the results using principal component analysis (PCA). The six factors extracted by PCA were identified as various dust, pollution, and sea salt aerosol types. A refined coarse mode only factor analysis yielded three coarse factors identified as dust, pollution laden dust, and sea salt. Backtrajectory analysis with the HYSPLIT trajectory model indicated likely source regions for dust factors to be in western and northern China and Mongolia, consistent with the known dust sources in the Gobi and Taklimakan Deserts. Pollution factors tended to be associated with transport from coastal China where large population and industrial centers exist, while sea salt sources indicated more diffuse marine regions. The results were generally consistent with observations from a co-located three-wavelength nephelometer and AERONET radiometer, along with model predictions from the Navy Aerosol Analysis and Prediction System (NAAPS). Backtrajectories indicated that transport of aerosol to the surface at Dongsha was occurring primarily within the boundary layer from regions generally to the north; an observation consistent with the dominance of pollution and dust aerosol in the ground-based data set. In contrast, more westerly flow aloft transported air from regions to the south and west, where biomass burning was a more significant aerosol source; however, this particle type was not clearly identified in the surface aerosol composition, consistent with it remaining primarily aloft and not mixing strongly to the surface during the study. Significant vertical wind shear and temperature inversions in the region support this conceptual understanding and suggest the potential for considerable vertical inhomogeneity in the SCS aerosol environment.Item Open Access The influence of cloud radiative effects on hydrologic sensitivity and variability(Colorado State University. Libraries, 2021) Naegele, Alexandra Claire, author; Randall, David A., advisor; Betsill, Michele M., committee member; Rasmussen, Kristen L., committee member; van den Heever, Susan C., committee memberThe global-mean precipitation change in response to CO2-forced warming, normalized by global-mean surface warming, is referred to as the hydrologic sensitivity. It is estimated at 1-3% K-1, much lower than the rate of increasing atmospheric moisture availability. Here, we study the role of cloud radiative effects (CREs) in constraining the hydrologic sensitivity. Often, the change in clear-sky atmospheric radiative cooling (ARC) is used to constrain the change in precipitation, but this constraint is incomplete. CMIP5 model data are analyzed to show that although the all-sky ARC increases at a lower rate than the clear-sky ARC, the smaller change in ARC due to CREs is balanced by the change in the surface sensible heat flux. Together, the change in the all-sky ARC with the change in the surface sensible heat flux provide a more accurate and complete energetic constraint on hydrologic sensitivity than by using the clear-sky radiative cooling alone. Idealized aquaplanet simulations using SP-CAM are analyzed to assess the temperature dependence of the hydrologic cycle and the large-scale circulation responses to CREs. We examine the response of the hydrologic cycle and the large-scale circulation to CREs at a range of sea surface temperatures (SSTs), including a cool (280 K) SST that is representative of the mid-latitudes; typically, the extratropics have been less studied than the tropics in similar idealized simulations. We use simulations with uniform SSTs to test the hypothesis that CREs enhance precipitation variability at cool temperatures, and reduce precipitation variability at warm temperatures. In these simulations, our hypothesis is confirmed. In less idealized simulations with a more realistic SST pattern, the influence of CREs on precipitation variability is obscured by other circulation changes. Can the hydrologic response to CREs be explained by the large-scale circulation response to CREs? Using the same idealized simulations, the vertical velocity —used here as an indicator of the circulation response to CREs—is compared to precipitation. We find that the influence of CREs on vertical velocity variability is very similar to the influence of CREs on precipitation variability.Item Open Access The simultaneous influence of thermodynamics and aerosols on deep convection and lightning(Colorado State University. Libraries, 2016) Stolz, Douglas C., author; Rutledge, Steven A., advisor; Pierce, Jeffrey R., committee member; van den Heever, Susan C., committee member; Reising, Steven C., committee memberThe dissertation consists of a multi-scale investigation of the relative contributions of thermodynamics and aerosols to the observed variability of deep convective clouds in the Tropics. First, estimates of thermodynamic quantities and cloud-condensation nuclei (CCN) in the environment are attributed to convective features (CFs) observed by the Tropical Rainfall Measuring Mission (TRMM) satellite for eight years (2004-2011) between 36⁰S-36⁰N across all longitudes. The collection of simultaneous observations was analyzed in order to assess the relevance of thermodynamic and aerosol hypotheses for explaining the spatial and temporal variability of the characteristics of deep convective clouds. Specifically, the impacts of normalized convective available potential energy (NCAPE) and warm cloud depth (WCD) as well as CCN concentrations (D ≥ 40 nm) on total lightning density (TLD), average height of 30 dBZ echoes (AVGHT30), and vertical profiles of radar reflectivity (VPRR) within individual CFs are the subject of initial curiosity. The results show that TLD increased by up to 600% and AVGHT30 increased by up to 2-3 km with increasing NCAPE and CCN for fixed WCD on the global scale. The partial sensitivity of TLD/AVGHT30 to NCAPE and CCN individually are found to be comparable in magnitude, but each independent variable accounts for a fraction of the total range of variability observed in the response (i.e., when the influences of NCAPE and CCN are considered simultaneously). Both TLD and AVGHT30 vary inversely with WCD such that maxima of TLD and AVGHT30 are found for the combination of high NCAPE, high CCN, and shallower WCD. The relationship between lightning and radar reflectivity is shown to vary as a function of CCN for a fixed thermodynamic environment. Analysis of VPRRs shows that reflectivity in the mixed phase region (altitudes where temperatures are between 0⁰C and -40⁰C) is up to 5.0-5.6 dB greater for CFs in polluted environments compared to CFs in pristine environments (holding thermodynamics fixed). A statistical decomposition of the relative contributions of NCAPE, CCN, and WCD to the variability of convective intensity proxies is undertaken. Simple linear models of TLD/AVGHT30 based on the predictor set composed of NCAPE, CCN, and WCD account for appreciable portions of the variability in convective intensity (R2 ≈ 0.3-0.8) over the global domain, continents, oceans, and select regions. Furthermore, the results from the statistical analysis suggest that the simultaneous contributions from NCAPE, CCN, and WCD to the variability of convective intensity are often comparable in magnitude. There was evidence for similar relationships over even finer-scale regions [O(106 km2)], but differences in the relative prognostic ability and stability of individual regression parameters between regions/seasons were apparent. These results highlight the need to investigate the connection between statistical behavior and local meteorological variability within individual regions. Following the global and regional analyses, data from Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign (2011-2012; central equatorial Indian Ocean (CIO)) and other sources was used to assess the relative impact of aerosols on deep convective clouds within a fine-scale environment with spatially homogeneous thermodynamics and variable aerosols in a pristine background over the CIO (CCN ~50-100 cm-3, on average; NCAPE and WCD are hypothesized to be approximately constant, spatially). The experiment was designed to compare differences in the convective cloud population developing in more-polluted and pristine regions, north and south of the equator, respectively. Analysis of the covariability of rainfall, cold cloud frequency, CCN, NCAPE, and lightning/radar reflectivity in deep convective clouds over multiple (> 20) episodes of the Madden-Julian Oscillation (MJO) leads to a hypothesis for a potential bi-directional interaction between aerosols and convective clouds that develop in association with the MJO. Close scrutiny of the results from climatology leads to the conclusion that thermodynamics and aerosols both influence deep convective cloud behavior over the CIO in a manner similar to that observed on the global scale, but the possibility that other factors are required to reproduce the full range of variability of deep convective clouds on fine-scales is acknowledged. The research presented in this dissertation constitutes one of the first efforts to link the documented variability of radar reflectivity and lightning within convective features observed by the TRMM satellite to their environment using novel representations of thermodynamic and aerosol quantities from reanalysis and a chemical transport model, respectively. The independent variables studied here (i.e., NCAPE, CCN, and WCD) were chosen specifically to address preeminent hypotheses in the literature and the results from this investigation suggest that NCAPE, CCN, and WCD each contribute significantly to the variability of deep convective clouds throughout the Tropics and Subtropics (and perhaps seasonally). Implications of the findings from the current investigations and the relevance of these results to future studies are discussed.Item Open Access Using laboratory and airborne measurements to investigate the role of ice nucleating particles in ice and mixed-phase clouds(Colorado State University. Libraries, 2023) Patnaude, Ryan John, author; Kreidenweis, Sonia M., advisor; DeMott, Paul J., advisor; van den Heever, Susan C., committee member; Chui, J. Christine, committee member; Willis, Megan D., committee memberIce may be present in the atmosphere either in cirrus or mixed-phase cloud regions, each with their own distinctly different characteristics and formation mechanisms. The former is characterized by the presence of only ice crystals at temperatures < -38 °C, while the latter includes the coexistence of both supercooled liquid cloud droplets and ice crystals between temperatures of 0 °C and -38 °C. Cirrus clouds represent an important cloud type as they are ubiquitous in the atmosphere and their radiative effects depend upon their microphysical properties. Their formation mechanisms may proceed via homogeneous or heterogeneous nucleation, and whether one or the other or both occur determines the size and number of ice crystals. The ocean represents one of the largest sources of aerosols into the atmosphere, and sea spray aerosols (SSA), if they are lofted to the upper troposphere, may act as ice nucleating particles (INPs) to initiate heterogeneous nucleation under cirrus conditions. Although a number of previous studies have investigated the ice nucleating behavior of SSA proxies such as sodium chloride (NaCl), or SSA generated from commercially-available artificial seawater products, ice nucleation under cirrus conditions of SSA generated from natural seawater had not been examined at the inception of this research program. Additionally, whether secondary marine aerosols (SMA), which form via the gas-to-particle conversion of ocean-emitted gas-phase species, may act as an INP in cirrus clouds is currently unknown. The first half of this dissertation highlights two laboratory studies that investigated the role and characteristics of SSA and SMA to act as INPs at cirrus cloud temperatures. The first study compared ice nucleation results for submicron SSA and NaCl particles and examined whether particle size affected the low temperature ice nucleation. Results showed that both SSA and NaCl initiated heterogeneous nucleation strongly at temperatures below 220 K, and that the size of the particles did not affect the ice nucleating ability of SSA. The similarities between the freezing behaviors of SSA and NaCl particles suggested the salt components were controlling heterogeneous ice nucleation. The second study used a more realistic aerosol generation method, utilizing a Marine Aerosol Reference Tank (MART) that was filled with natural seawater, and investigated the effects of atmospheric oxidation on SSA using an oxidation flow reactor (OFR), which was also used to generate SMA from gaseous emissions released in the MART. SMA alone were also examined for their ice nucleation behavior at cirrus temperatures. Results from this study indicated that atmospheric oxidation did not hinder low temperature ice nucleation of SSA, and that SMA are not efficient ice nucleating particles at cirrus temperatures, but could participate in homogeneous nucleation. Finally, the similarities between the findings from the two studies indicated that the generation method of SSA, and any impacts on SSA organic aerosol content, did not affect the ice nucleating behavior of SSA at cirrus temperatures. Ice in mixed-phase clouds (MPCs), on the other hand, forms initially via heterogeneous nucleation at a wide range of temperatures and relative humidity conditions, depending on the abundance and characteristics of available INPs. Secondary ice production (SIP) may follow heterogeneous nucleation in MPCs, where new ice crystals form either during the heterogeneous freezing event, or through subsequent interactions between the pre-existing liquid cloud droplets and ice crystals. SIP may lead to enhanced ice crystal number concentrations via a number of proposed mechanisms, especially in convective environments. Despite decades of study toward developing better understanding of ice formation in MPCs, the freezing pathways of ice crystals over the course of cloud lifetimes, and the conditions that favor the various proposed SIP pathways, are not fully resolved. The third study in this dissertation reports and interprets observations of INPs during an airborne campaign over the U.S. Central Great Plains during the Secondary Production of Ice in Cumulus Experiment (SPICULE) campaign that primarily sampled cumulus congestus clouds. Coincident measurements of INP and ice crystal number concentrations in cumulus congestus clouds were used to infer the ice formation pathway, either through heterogeneous nucleation or SIP. Warmer cloud base temperatures and faster updrafts were found to facilitate environmental conditions favorable for SIP. Further, the fragmentation of freezing droplets (FFD) SIP mechanism was found to be critical in the enhancement of observed ice crystal number concentrations during the earliest stages of the cloud lifetime. Numerical model simulations of an idealized, single congestus cloud, designed to mimic the clouds sampled during SPICULE, were conducted with newly-implemented SIP mechanisms, added to the existing Hallet-Mossop (HM) rime-splintering mechanism. The model results indicated that HM dominated the production of ice crystals, but without the FFD and ice-ice collisional breakup (BR) SIP mechanisms, the model could not accurately resolve ice crystal number concentrations compared to observations. Competing results in the dominant SIP mechanisms underscore the need for improved mechanistic understanding of these SIP processes, either through laboratory or observational studies, in order to close this gap between model prediction and observations. The final portion of this dissertation describes airborne observations of INPs during a field campaign along the U.S. Gulf Coast, also aimed at investigating the impacts of various aerosol-cloud interaction mechanisms on development of convective clouds. During this campaign, a widespread and prolonged Saharan Air Layer (SAL) event took place and INP characteristics during this event are reported and contrasted with INP characteristics prior to the arrival of the SAL. The INP concentrations at temperatures below -20 °C were enhanced by 1–2 orders of magnitude compared to the flights prior to the dust intrusion, and showed good agreement with one previous study of Saharan dust near Barbados, but lower INP concentrations than another study off the coast of western Africa. The INP concentrations in the SAL also generally overlapped with or exceeded INP concentrations during SPICULE, but only for INPs active temperatures < -25 °C. These observations were the first airborne measurements in nearly two decades tagging INP concentrations to North African dust that had been transported all the way to the United States. Further, they provide the most comprehensive description of these INPs yet recorded, and suggest a common natural INP perturbation in the southeastern U.S. and Gulf regions in early summer, with implications for cloud processes that warrant further study.Item Open Access Variability in observed remote marine aerosol populations and implications for haze and cloud formation(Colorado State University. Libraries, 2020) Atwood, Samuel A., author; Kreidenweis, Sonia M., advisor; van den Heever, Susan C., committee member; Pierce, Jeffrey R., committee member; Cooley, Daniel, committee memberIn many oceanic regions of the planet, once pristine environments are known to have a high degree of sensitivity to changing aerosol populations and perturbations from anthropogenic emissions. However, difficulties in modeling and remote sensing efforts in remote marine regions have led to continued uncertainties in aerosol-cloud-climate interactions. Numerous properties of the aerosol and environment affect these interactions in complex and often non-linear ways. In this work, I examine the variability in observed remote marine aerosol properties and its implications for classifying aerosol impacts on cloud development and radiative transfer in the atmosphere. The results from several field campaigns that measured aerosol and environmental properties relevant to these processes in marine and coastal regions are first presented. An unsupervised classification methodology was used to identify periods of impacts associated with distinct fine-mode aerosol population types and to quantify the observed range of variability associated with these types. A specific focus was placed on differentiating between internal variability in relevant properties within a given population type and external variability between the average values for each population type. The result was a set of aerosol population type models observed in marine regions that allowed for further investigation of the impact of different sources of variability on subsequent atmospheric processes. Next presented are the results of several observationally driven sensitivity studies using the aerosol models. First, initial cloud properties were investigated using a cloud parcel model driven by the observed aerosol population types to examine relative sensitivity to updraft velocity, extensive aerosol properties including number concentration, and a range of intensive aerosol properties. It was found that the parameter space across which initial cloud property sensitivity to variability in the observed aerosol dataset was investigated could be simplified to incorporate relevant intensive aerosol properties into a single population type parameter. Previous work using simpler mono-modal aerosol populations had identified several regimes of sensitivity of initial cloud properties to updraft velocity and total particle number concentration. When driven by the more complex and atmospherically relevant marine population types additional sensitivity to population type was identified through portions of these two regimes, and a new regime was identified that was more sensitive to population type than either of the other parameters. A Monte Carlo optical reconstruction model was then used to investigate sensitivity of atmospheric optical properties to observed variability in aerosol and environmental properties. As expected, aerosol dry mass concentrations were the largest contributors to overall sensitivity of extensive optical properties. However, in terms of intensive optical properties, the range of expected variability due to internal variability within a given population type was on the same order as impacts expected due to differences between population types. Specific aerosol population type models may therefore provide little advantage for further constraining expected optical property variability in this dataset. Additionally, the combined impacts of variability in environmental relative humidity (RH) and intensive aerosol properties within a nominally consistent population type could be quantified with coefficients of variation on the order of 0.3 in this dataset—a value that was relatively constant and independent of total mass concentration, aerosol population type, and RH. Overall, this work produced new representations of fine-mode aerosol types encountered in marine environments that were broadly consistent with those currently applied in remote sensing and climate modeling. However, the models presented here can account explicitly for the effects of ambient relative humidity, and thus may be useful for next-generation modeling that includes those effects. Future work focused on similar observationally-constrained model development for the marine and littoral coarse mode would be beneficial, as large particles are often significant fractions of optical depth in these regions.