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Lidar measurements of cloud extinction coefficient distribution and its forward scattering phase function according to multiply scattered lidar returns

The study of the inversion algorithm for the single scatter lidar equation, for quantitative determination of cloud (or aerosol) optical properties, has received much attention over the last thirty years. Some of the difficulties associated with the solution of this equation are not yet solved. One problem is that a single scatter lidar equation has two unknowns. Because of this, the determination of the far-end boundary value, in the case of Klett's algorithm, is a problem if the atmosphere is optically inhomogeneous. Another difficulty concerns multiple scattering. There is a large error in the extinction distribution solution, in many cases, if only the single scattering component is considered, while neglecting the multiple scattering component. However, the use of multiple scattering in the remote sensing of aerosol or cloud optical properties is promising. In our early study, an inversion method for simultaneous determination of the cloud (or aerosol) Extinction Coefficient Distribution (ECD) and its Forward Scattering Phase Function (FSPF) was proposed according to multiply scattered lidar returns with two fields of view for the receiver. The method is based on a parameterized multiple scatter lidar equation. This paper is devoted to further numerical tests and an experimental study of lidar measurements of cloud ECD and FSPF using this method.

Qiu, Jinhuan↗

Influence of ocean surface conditions on atmospheric vertical thermodynamic structure and deep convection

The authors analyze the influence of Sea Surface Temperature (SST) and surface wind divergence on atmospheric thermodynamic structure and the resulting effects on the occurrence of deep convection using National Meteorological Center radiosonde data and International Satellite Cloud Climatology Program data for July 1983-July 1985. The onset of deep convection requires not only the existence of positive convective available potential energy (CAPE), but also an unstable planetary boundary layer (PBL). A stable PBL is observed to suppress deep convection even when CAPE is positive. Variations of SST have a major effect on CAPE, but surface wind divergence can also affect deep convection by changing the lapse rate in the lower troposphere and humidity in the PBL. Specifically, when SST is greater than or equal to 28 C, CAPE is always positive, and surface wind divergence does not qualitatively change the buoyancy profile above the PBL. Strong surface wind divergence, however, stabilizes the PBL so as to suppress the initiation of deep convection. In warm SST regions, CAPE is greater than 0 regardless of assumptions about condensate loading, although the pseudoadiabatic limit is more consistent with the observed deep convection than the reversible moist-adiabatic limit under these circumstances. When SST is less than 27 C, CAPE is usually negative and inhibits convection, but strong surface wind convergence can destabilize the inversion layer and moisten the PBL enough to make the atmosphere neutrally stable in the mean. As a result, deep convection is generally enhanced either when SST is greater than or equal to 28 C in the absence of strong surface wind divergence or when strong surface wind convergence occurs even if SST is less than 27 C. The anomalous suppression of deep convection in the warm area of the equatorial west Pacific lying between the intertropical convergence zone (ITCZ) and south Pacific convergence zone (SPCZ) is probably caused by dryness in the PBL and an inversion in that area. The seasonal cycles of deep convection and surface wind divergence are in phase with the maximum solar radiation and lead SST for one to three months in the central Pacific. The change of PBL relative humidity plays a critical role in the changeover to convective instability in this case. The seasonal change of deep convection and associated clouds seems not to have important effects on the seasonal change of local SST in the central Pacific.

Fu, Rong↗

Macquarie Island Cloud and Radiation Experiment (MICRE) Ice Nucleating Particle Measurements Field Campaign Report

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Macquarie Island Cloud and Radiation Experiment (MICRE) Ice Nucleating Particle Measurements campaign was aligned as a supplemental activity with the second year of the overall MICRE campaign. The purpose of the supplemental campaign was to provide a first-ever annual cycle of ice nucleating particle (INP) measurements at a Southern Ocean (SO) site, toward the investigation/characterization of sources of INPs in the marine boundary layer as being from the production or primary sea spray aerosol (SSA) emissions versus other long-range transport influences. Furthermore, measuring the variability in INPs seasonally in this region, as this may relate to meteorology and ocean biological processes, is expected to help constrain (via parameterizations) numerical model simulations of cloud phase and regional climate. In concert with other SO studies during the time frame of the campaign (March 2017 to March 2018), MICRE sought to evaluate the hypotheses that SSA INPs represent the major INP source in the SO and, due to their generally less efficient INP activation properties compared to terrestrial sources, that they may directly influence the persistence of supercooled clouds in a unique manner for this climatic region. These measurements supplemented the original deployment of primarily radiation measurements provided in the ARM MICRE request and the associated Australian Antarctic Division (AAD) Antarctic Clouds and Radiation Experiment (ACRE). Assistance and collaboration was obtained from the AAD, the Commonwealth Scientific and Industrial Research Organization (CSIRO) and the Australian Bureau of Meteorology (BOM). Follow-up plans will include investigations with their additional aerosol, cloud, and radiative transfer measurements. AAD also saw to the transport to Australia and storage of filters at the end of the campaign. The added effort involved an average of twice-weekly collections (a 48-hour and a 72-hour collection) of pre-sterilized, open-faced, polycarbonate filter samples for post-processing of INP number concentrations and tests to analyze the nature of INP sources. Collections were made by AAD technician Emry Thaggard Crocker after online training from our team. Images of the filter sampler and site are shown in Figure 1. Sampling occurred from an approximate elevation of 4m MSL. Filters were returned frozen to Colorado State University (CSU) at the end of the campaign. Initial processing to obtain INP temperature spectra (0 to -28°C) of the concentrations of INPs active via the immersion freezing mechanism were conducted using the CSU ice spectrometer (IS) instrument systems (Hiranuma et al. 2015; McCluskey et al. 2018). In this method, particles are first removed from filters using ultrapure water while under mechanical agitation. Arrays of the particle suspensions from a portion of filter rinses are then cooled to obtain immersion freezing data per volume of water, and finally are related to sampling volumes to obtain numbers per volume of air following the analysis methods of Vali (1971). A total of 103 filters were collected, including blanks at selected intervals throughout the project. For archival and completion of tasks under this ARM proposal, nearly half of the filter collections (46) were processed for basic temperature spectra, and half of these (23) were also tested for microbial/proteinaceous contributions toward INPs via 95°C pre-treatment of portions of the original suspensions.

Southern Ocean, aerosols, marine clouds, MARCUS ca↗

Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework

Ice microphysics parameterizations in models must make major simplifications relative to observations, typically employing empirical relationships to represent average functional properties of particles. However, previous studies have established that ice particle properties vary even in similar cloud types and thermodynamic environments, and it remains unclear how this so-called “natural variability” impacts simulated deep convection. This uncertainty is addressed by implementing a stochastic framework into the Predicted Particle Properties microphysics scheme in the Weather Research and Forecasting model. The approach stochastically varies the coefficients of the mass-size (m-D) relationship (m=aD b ) for unrimed and partially rimed ice. Using guidance from aircraft in situ measurements obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), the scheme samples from distributions of the prefactor (a) and the exponent (b) of the m-D relationship. Simulations of two MC3E deep convective cases indicate that the stochastic m-D scheme produces considerable variability of anvil cirrus cloud optical depth (τ) distributions, even for the same ice water path (IWP). Thus, the stochastic scheme produces variable cloud radiative forcing that is independent of IWP. This τ-IWP relationship variability is nonexistent using the deterministic m-D ensemble. Additional sensitivity tests are performed in which the fallspeed-size relationship (V=cD d ) is stochastically varied, resulting in variable precipitation amounts and rain rate distributions. Results are presented in the context of satellite and precipitation observations and include comparison with other ensemble configurations using perturbed initial and lateral boundary conditions and small-amplitude noise added to the potential temperature field.

54 ENVIRONMENTAL SCIENCES↗

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the atmosphere boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement Southern Great Plains site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential-absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to obtain a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near the boundary-layer top. Furthermore, we also explore how differences in retrievals may affect results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval shows some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

54 ENVIRONMENTAL SCIENCES↗

Influence of Superparameterization and a Higher-Order Turbulence Closure on Rainfall Bias Over Amazonia in Community Atmosphere Model Version 5

In this work, we evaluate the Community Atmosphere Model Version 5 (CAM5) with a higher-order turbulence closure scheme, named Cloud Layers Unified By Binomials (CLUBB), and a Multiscale Modeling Framework (MMF) with two different microphysics configurations to investigate their influences on rainfall simulations over Southern Amazonia. The two different microphysics configurations in MMF are the one-moment cloud microphysics without aerosol treatment (SAM1MOM) and two-moment cloud microphysics coupled with aerosol treatment (SAM2MOM). Results show that both MMF-SAM2MOM and CLUBB effectively reduce the low biases of rainfall, mainly during the wet season. The CLUBB reduces low biases of humidity in the lower troposphere with further reduced shallow clouds. The latter enables more surface solar flux, leading to stronger convection and more rainfall. MMF, especially MMF-SAM2MOM, unstablizes the atmosphere with more moisture and higher atmospheric temperatures in the atmospheric boundary layer, allowing the growth of more extreme convection and further generating more deep convection. MMF-SAM2MOM significantly increases rainfall in the afternoon, but it does not reduce the early bias of the diurnal rainfall peak; LUBB, on the other hand, delays the afternoon peak time and produces more precipitation in the early morning, due to more realistic gradual transition between shallow and deep convection. MMF appears to be able to realistically capture the observed increase of relative humidity prior to deep convection, especially with its two-moment configuration. In contrast, in CAM5 and CAM5 with CLUBB, occurrence of deep convection in these models appears to be a result of stronger heating rather than higher relative humidity.

58 GEOSCIENCES↗

Interactions Between Clouds and Wind-Driven Surface Heat Exchanges over Land

Earth system model experiments show that increasing horizontal resolution fundamentally alters the simulated soil-moisture-precipitation feedback. Kilometer-scale simulations often produce weaker or even negative feedback compared to coarse-resolution models. A key difference of kilometer-scale models is that they resolve mesoscale secondary circulations, including boundary layer horizontal rolls and cellular structures, in addition to cold pools and downdrafts associated with convective precipitation. However, because the relevant processes occur on yet-smaller scales, these circulations are often poorly resolved. This project demonstrated that boundary layer secondary circulations significantly affect surface heat exchanges and wind gusts, and that current model parameterizations can misrepresent these processes at kilometer-scale resolution. Using DOE Atmospheric Radiation Measurement (ARM) observations and targeted experiments with the DOE Energy Exascale Earth System Model (E3SM), we identified physically unrealistic wind gust and surface flux responses to secondary circulations, diagnosed a systematic overestimation of wind shear in convective cold pools, and uncovered a multivariate relationship between land surface fluxes and the scales of updrafts that form shallow cumulus clouds. These findings provide observation-based recommendations for improving parameterizations of surface fluxes and wind gusts in high-resolution Earth system models, thereby reducing uncertainty in convective storm prediction and land-atmosphere feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Boundary conditions for the paleoenvironment: Chemical and physical processes in the pre-solar nebula

Detailed study of the first interstellar hydrocarbon ring, cyclopropenylidene (C3H2), is continuing. The singly deuterated isotope of this molecule, C3HD, was observed in several cold interstellar clouds. The results of a large survey for C3H2 in galactic sources of various types will soon be completed. It appears that cyclopropenylidene is present in virtually all interstellar clouds of at least moderate density. In order to make the first determinations of the CO2/CO abundance ratio in interstellar sources, observations of protonated CO2 were pursued. The spectrum from 18.5 to 22 GHz for several interstellar clouds is being systematically measured. Particular attention is being given to the cold, dark clouds TMC-1 and L124N, which may be formation sites for solar mass stars. The phenomena of maser emission from molecules of methanol is being studied in certain interstellar clouds. A comparison of 1 millimeter continuum emission from dust with the column density of carbon monoxide as determined from the rare C(18)O isotope for 4 molecular clouds in the Galaxy is nearing completion. Papers published during the period of this report are listed.

Irvine, William M.↗

Study of Antarctic Blowing Snow Storms Using MODIS and CALIOP Observations With a Machine Learning Model

As a common phenomenon over Antarctica, blowing snow (BLSN), especially the large BLSN storms, play an important role in the Antarctic surface mass balance, radiation budget, and planetary boundary layer processes. This study presents the work on BLSN storm identification and analysis with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. Spectral analysis shows that BLSN identification is feasible with MODIS daytime data. A random forest machine learning model is developed and observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization are used for training. Model performance results show that machine‐learning based classification can achieve over 90% overall accuracy when classifying MODIS pixels into cloud, clear, and BLSN categories. The machine learning model is applied to MODIS observations during the month of October 2009 for BLSN storm analysis. Results show that the size of BLSN storms has a large spectrum and can reach hundreds of thousands km2. The MODIS based BLSN storm frequency map extends the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations coverage limit from 82°S to the South Pole. A BLSN storm belt, which extends from the South Pole region to the coastal area between 130°E and 160°E along the Transantarctic Mountains, provides a potential pathway of snow transport. These results are important in improving the understanding of BLSN impact on Antarctic surface mass balance and boundary layer processes.

Antarctic↗

Properties of African squall lines inferred from time-lapse satellite imagery

Analysis of 48 h of time-lapse satellite imagery of a family of squall lines in Africa links the phenomena with a characteristic cloud cluster and with a wind field perturbation which is enhanced in passing through an African easterly wave trough. A thin 'arc line' of low-level developing cumulus, a salient feature of the squall lines on the imagery, is shown to occur at the front boundary of the mesoscale/convective scale subsidence. Analysis of the wind field indicates that a squall line is associated with a vorticity center in the mid-level easterly flow which accompanies the mesoscale subsidence which, in turn, contributes to further forced ascent of subcloud air along the front of the squall line into convective towers which merge into an extensive anvil. The squall lines evolved through a life cycle of 6 to 12 h while the larger cloud cluster and wind perturbation lasted over 48 h. The magnitude of the vertical mass exchange suggests that squall-line families contribute significantly to the tropical energy balance.

Fortune, M.↗

Climatic changes resulting from mass extinctions at the K-T boundary (and other bio-events)

The mass extinctions at the Cretaceous-Tertiary (K-T) boundary include about 90 percent of marine calcareous nannoplankton (coccoliths), and carbon-isotope data show that marine primary productivity was drastically reduced for about 500,000 years after the boundary event, the so-called Strangelove Ocean effect. One result of the elimination of most marine phytoplankton would have been a severe reduction in production of dimethyl sulfide (DMS), a biogenic gas that is believed to be the major precursor of cloud condensation nuclei (CCN) over the oceans. A drastic reduction in marine CCN should lead to a cloud canopy with significantly lower reflectivity, and hence cause a significant warming at the earth's surface. Calculations suggest that, all other things being held constant, a reduction in CCN of more than 80 percent (a reasonable value for the K-T extinctions) could have produced a rapid global warming of 6 C or more. Oxygen-isotope analyses of marine sediments, and other kinds of paleoclimatic data, have provided for a marked warming, and a general instability of climate coincident with the killoff of marine plankton at the K-T boundary. Similar reductions in phytoplankton abundance at other boundaries, as indicated by marked shifts in carbon-isotope curves, suggest that severe temperature changes may have accompanied other mass extinctions, and raises the intriguing possibility that the extinction events themselves could have contributed to the climatic instabilities at critical bio-events in the geologic record.

Rampino, Michael R.↗

A Study of the Response of Deep Tropical Clouds to Mesoscale Processes: Modeling Strategies and Simulations of TOGA-COARE Convective Systems - Part 1

Interactions between deep tropical clouds over the western Pacific warm pool and the larger-scale environment are key to understanding climate change. Cloud models are an extremely useful tool in simulating and providing statistical information on heat and moisture transfer processes between cloud systems and the environment, and can therefore be utilized to substantially improve cloud parameterizations in climate models. In this paper, the Goddard Cumulus Ensemble (GCE) cloud-resolving model is used in multi-day simulations of deep tropical convective activity over the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Large-scale temperature and moisture advective tendencies, and horizontal momentum from the TOGA-COARE Intensive Flux Array (IFA) region, are applied to the GCE version which incorporates cyclical boundary conditions. Sensitivity experiments show that grid domain size produces the largest response to domain-mean temperature and moisture deviations, as well as cloudiness, when compared to grid horizontal or vertical resolution, and advection scheme. It is found that a minimum grid-domain size of 500 km is needed to adequately resolve the convective cloud features. The control experiment shows that the atmospheric heating and moistening is primarily a response to cloud latent processes of condensation/evaporation, and deposition/sublimation, and to a lesser extent, melting of ice particles. Air-sea exchange of heat and moisture is found to be significant, but of secondary importance, while the radiational response is small. The simulated rainfall and atmospheric heating and moistening, agrees well with observations, and performs favorably to other models simulating this case.

Johnson, Daniel E.↗

A Typology of Quantum-Classical Faults

This paper introduces an extended taxonomy of faults specific to hybrid quantum-classical systems, addressing the unique challenges that arise from integrating quantum accelerators into high-performance computing (HPC) infrastructures. Building on the foundational fault classification by Avizienis et al., we incorporate fault types unique to quantum computing-such as qubit decoherence, spontaneous gate errors, and photon loss-alongside traditional and human-induced faults including development errors, operational mistakes, and malicious attacks. Our taxonomy classifies faults by their origin (natural vs. human-made), intent (accidental, deliberate non-malicious, or malicious), system boundaries (internal vs. external), and persistence (transient to permanent). We also explore how different architectural integration patterns-ranging from tight coupling to loose on-premise and cloud-based configurations-shape the manifestation and propagation of faults. These scenarios are analyzed in terms of timing mismatches, interface inconsistencies, and security threats such as data tampering and denial-of-service attacks. Through this fault-centric lens, we aim to support the co-design of dependable quantum-classical systems and highlight the critical role that integration strategies play in ensuring reproducibility, resilience, and security across hybrid computing platforms.

Giusto, Edorado [University of Naples Federico II,↗

Marine Ice Nuclei Collections – MAGIC (MAGIC-IN) Final Campaign Summary

This campaign augmented measurements obtained via deployment of the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Mobile Facility (AMF) in the Marine ARM GPCI1 Investigation of Clouds (MAGIC) field campaign. The measurements, comprised of shipboard aerosol collections obtained during the five legs of the summer 2013 cruises, were sent for offline processing to measure ice nucleating particle (INP) number concentrations. The forty-three sample periods each represented, nominally, 24-hour segments during outbound and inbound transits of the Horizon Spirit. The samples were collected at locations between Los Angeles and Hawaii. Eight samples have been analyzed for immersion freezing temperature spectra thus far, using funding from other grants. Remaining samples are being frozen until support for further processing is obtained. Future analyses will investigate the inorganic/organic proportions of ice nuclei, in addition to determining the genetic composition of the overall biological community associated with INPs. Resulting correlations will be compared with other archived aerosol quantities, meteorological and ocean data (e.g., temperature, wind speed, sea surface temperature, etc…) and satellite ocean color products. These findings will ultimately aid in parameterizing oceanic (e.g., sea spray) INP emissions in regional and global scale models, when illustrating aerosol connections to cloud phases and properties. Independent future analyses of frozen filter samples, as proposed by collaborating investigators at the time of this report, will include single particle analyses of marine boundary layer aerosol compositions and morphology. The MAGIC-IN data are considered representative of the oligotrophic, low Chlorophyll-a (with the exception of near-shore) ocean regions, which exist along the MAGIC transect. Current analyses suggest that INP numbers in the marine boundary layer over this region are typically low, compared to existing measurements over marine areas and those collected in the laboratory as the result of realistic sea spray particle generation. These findings, along with separate studies, confirm the existence of highly variable emission sources for INP from oceans, (though weaker than land-based emissions at modestly cooled temperatures).

54 ENVIRONMENTAL SCIENCES↗

Case studies using GOES infrared data and a planetary boundary layer model to infer regional scale variations in soil moisture

Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.

Rose, F. G.↗

Global Evaluation of Terrestrial Near-Surface Air Temperature and Specific Humidity Retrievals from the Atmospheric Infrared Sounder (AIRS)

Global observations of near-surface air temperature and specific humidity over land are needed for a variety of applications, including to constrain global estimates of evapotranspiration (ET). Spaceborne hyperspectral observations, such as those from NASA’s Atmospheric Infrared Sounder (AIRS) mission, show promise for meeting this need, yet there are surprisingly few validation studies of AIRS near-surface atmospheric state retrievals. In this study, we use triple collocation to validate AIRS Level 3 retrievals of near-surface atmospheric state over land using twelve years of gridded station observations and two reanalyses. Deseasonalized AIRS retrievals correlate well with deseasonalized ground observations outside the tropics, but correlate less well in the tropics. Lower temporal sensitivity near the surface in the tropics contributes to the lower correlation for near-surface air temperature and is consistent with known physics of the tropical atmosphere, in which temperatures outside the boundary layer (which dominate the AIRS retrieval signal) are poorly correlated with those near the surface. Retrievals in the tropics may also be more susceptible to errors in cloud-clearing algorithms, and to uncertainty in surface emissivity. Since ET is greatest in the tropics, and tropical measurement networks are particularly sparse, this work motivates new approaches for measuring ET in the tropics.

Evapotranspiration↗

Droplet Growth or Evaporation Does Not Buffer the Variability in Supersaturation in Clean Clouds

Abstract Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection–Cloud Chamber generates a turbulent cloud with a microphysical steady state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and collocated Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damköhler number (Da), under conditions corresponding to , i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such that is satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth. Significance Statement The saturation ratio (humidity) in clouds controls the growth rate and formation of cloud droplets. When air in a turbulent cloud mixes, the humidity varies in space and time throughout the cloud. This is important because it means cloud droplets experience different growth histories, thereby resulting in broader size distributions. It is often assumed that growth and evaporation of cloud droplets buffers out some of the humidity variations. Measuring these variations has been difficult, especially in the field. The purpose of this study is to measure the saturation ratio distribution in clouds with a range of conditions. We measure the in-cloud saturation ratio using a convection cloud chamber with clean to polluted cloud properties. We found in clouds with low concentrations of droplets that the variations in the saturation ratio are not suppressed.

54 ENVIRONMENTAL SCIENCES↗

Vertical distribution of boundary layer new particle formation and implications for nanoparticle growth mechanisms (Final Report)

New particles can form high above ground in the atmosphere before such formation events are observed by ground-based instruments. Once formed, these particles can take up significant amounts of water vapor, which has implications on the mechanisms by which nanoparticles grow and, ultimately, impact cloud formation processes. These observations motivated the research performed in this project using a combination of modeling, laboratory experiments, and the analysis of field observations. We hypothesized is that ground-based measurements do not always accurately represent the location and timing of new particle formation events, nor do they adequately characterize the dominant physical and chemical processes that are responsible for the subsequent growth of newly formed particles. Essentially, we wanted to study the new particle formation process under conditions that we expect may be more relevant to the actual location in the atmosphere where such events take place, which are often characterized by higher relative humidities, lower temperatures, and a broader range of precursors and oxidants compared to those observed at ground level. This project had two main objectives, each of which directly addressed our hypothesis. Our first is to investigate the timing, distribution, meteorological conditions, and nanoparticle properties associated with boundary layer new particle formation through the analysis of ARM field campaigns such as HI-SCALE and long-term observations and observations performed in other locales such as in China and India where atmospheric conditions could play a crucial role in determining the mechanisms of new particle formation. This activity provided a comprehensive description, both in time and in space, of the gases and nanoparticle properties that are responsible for these events. We also performed modeling studies to explore the vertical profile and timing of new particle formation events from these campaigns. Our second objective was to perform laboratory and process-level modeling studies to investigate the role that conditions such as low ambient temperature, high relative humidity, and different oxidants such as nitrate radical play in determining unique chemical pathways for nanoparticle growth. In doing so, we revisited the representation of nanoparticle growth in global models and updated assumptions of formation and growth based on the findings of the field, laboratory, and process-level-model work. Our research provides crucial insights into the most important regions of the atmospheric boundary layer for future observational and modeling studies. It also identifies the most relevant environmental conditions, precursors, and oxidants that are responsible for nanoparticle growth, which will aid in the design of laboratory studies and process-level model experiments. The unique pathways that we discovered can be incorporated into regional and global models, thereby improving predictions and attribution of the role of new particle formation in, e.g., air pollution formation and cloud properties.

54 ENVIRONMENTAL SCIENCES↗