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Habit–Dependent Vapor Growth Modulates Arctic Supercooled Water Occurrence

We present an analysis of long-term data collected at Utqiagvik, Alaska, to explore the impacts of cloud processes on the probability of finding supercooled water given cloud temperature, P(L|T), in the topmost unseeded liquid-bearing layers. P(L|T) has local minima at temperatures around –6°C and –15°C. Simulations using habit-evolving ice microphysics models suggest that these minima are the result of efficient vapor growth by non-isometric habits found at these temperatures. Here, we conclude that habit-dependent vapor growth of ice crystals modulates the macrophysical occurrence of supercooled water in polar clouds, the effect of which should be included in model parametrizations to avoid biases and/or error compensation. Our methodology is adaptable for spherical ice treatments implemented in models (example parametrizations provided), amenable for use with satellite measurements to give global impartial observational targets for model evaluations, and may allow empirical characterization of bulk responses to seeding and possibly secondary ice effects.

54 ENVIRONMENTAL SCIENCES↗

Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks

Marine cold air outbreaks (CAOs) commonly form overcast cloud decks that transition into broken cloud fields downwind, dramatically altering the local radiation budget. In this study, we investigate the impact of frozen hydrometeors on these transitions. We focus on a CAO case in the NW Atlantic, the location of the multi-year flight campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment). We use MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) reanalysis fields to drive large eddy simulations with mixed-phase two-moment microphysics in a Lagrangian framework. We find that transitions are triggered by substantial rain (rainwater paths >25 g m−2), and only simulations that allow for aerosol depletion result in sustained breakups, as observed. Using a range of diagnostic ice nucleating particle concentrations, Ninp, we find that increasing ice progressively accelerates transitions, thus abbreviating the overcast state. Ice particles affect the cloud-topped boundary layer evolution, primarily through riming-related processes prior to substantial rain, leading to (1) a reduction in cloud liquid water, (2) early consumption of cloud condensation nuclei, and (3) early and light precipitation cooling and moistening below cloud. We refer to these three effects collectively as “preconditioning by riming”. Greater boundary layer aerosol concentrations available as cloud condensation nuclei (CCN) delay the onset of substantial rain. However, cloud breakup and low CCN concentration final stages are found to be inevitable in this case, due, primarily, to liquid water path buildup. An ice-modulated cloud transition speed suggests the possibility of a negative cloud–climate feedback. To address prevailing uncertainties in the model representation of mixed-phase processes, the magnitude of ice formation and riming impacts and, thereby, the strength of an associated negative cloud–climate feedback process, requires further observational evaluation by targeting riming hot spots with in situ imaging probes that allow for both the characterization of ice particles and abundance of supercooled droplets.

Marine cold air outbreaks↗

Bounding the Role of Black Carbon in the Climate System: a Scientific Assessment

Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg/yr in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W/sq m with 90% uncertainty bounds of (+0.08, +1.27)W/sq m. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W/sq m. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W/sq m with 90% uncertainty bounds of +0.17 to +2.1 W/sq m. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W/sq m, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (0.50 to +1.08) W/sq m during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (0.06 W/sq m with 90% uncertainty bounds of 1.45 to +1.29 W/sq m). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

black carbon↗

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Advancing the Understanding of Cloud Microphysical Processes and Aerosol Indirect Effects in High-Latitude Mixed-Phase Clouds by Linking ARM Measurements with Climate Model Simulations (Final Report)

The key objectives of this project were to advance our understanding of cloud microphysical characteristics and aerosol indirect effects on mixed-phase clouds in high latitudes. To improve the representation of ice and mixed-phase clouds in Earth System Models (ESMs), we propose an integrated observation and modeling study of cloud macro- and microphysical properties, including spatial heterogeneities, mass partitioning between ice crystals and supercooled liquid water, effects of ice nucleating particles (INPs), and efficiency of secondary ice production (SIP), etc. Specifically, we took four main approaches in this project: (1) examining macro- and microphysical properties of ice and mixed-phase clouds based on in-situ and ground-based observations from multiple field campaigns funded by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program, including the Mixed-Phase Arctic Cloud Experiment (M-PACE), Indirect and Semi-Direct Aerosol Campaign (ISDAC), Ice Nucleating Particle Sources at Oliktok Point (INPOP), ARM West Antarctic Radiation Experiment (AWARE), Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS), and Macquarie Island Cloud and Radiation Experiment (MICRE); (2) evaluating the DOE Energy Exascale Earth System Model (E3SM) simulations based on observations, particularly for ice and mixed-phase cloud microphysical properties; (3) examining the impacts of INPs on ice and mixed-phase clouds. Specifically, a series of comparisons were conducted using observations over the Arctic, Southern Ocean, and Antarctica, including comparisons between the lower and higher southern latitudes as well as comparisons between the northern and southern hemispheres. In addition, aerosol indirect effects from distinct sources of dust particles were examined; and (4) investigating the impacts of SIP. Ultimately, these results helped to improve cloud microphysics and aerosol-cloud interaction parameterizations in the E3SM model. Overall, the project provided improved understanding regarding various factors, including thermodynamic, dynamic, and aerosol conditions, on the micro- and macrophysical properties of ice and mixed-phase clouds in the high latitudes. Resulting analysis helped to provide an improved physical basis for refining the current cloud microphysics parameterizations related to ice and mixed-phase clouds in E3SM.

54 ENVIRONMENTAL SCIENCES↗

A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes

Observations of long-lived mixed-phase Arctic boundary layer clouds on 7 May 1998 during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)Arctic Cloud Experiment (ACE)Surface Heat Budget of the Arctic Ocean (SHEBA) campaign provide a unique opportunity to test understanding of cloud ice formation. Under the microphysically simple conditions observed (apparently negligible ice aggregation, sublimation, and multiplication), the only expected source of new ice crystals is activation of heterogeneous ice nuclei (IN) and the only sink is sedimentation. Large-eddy simulations with size-resolved microphysics are initialized with IN number concentration N(sub IN) measured above cloud top, but details of IN activation behavior are unknown. If activated rapidly (in deposition, condensation, or immersion modes), as commonly assumed, IN are depleted from the well-mixed boundary layer within minutes. Quasi-equilibrium ice number concentration N(sub i) is then limited to a small fraction of overlying N(sub IN) that is determined by the cloud-top entrainment rate w(sub e) divided by the number-weighted ice fall speed at the surface v(sub f). Because w(sub c)< 1 cm/s and v(sub f)> 10 cm/s, N(sub i)/N(sub IN)<< 1. Such conditions may be common for this cloud type, which has implications for modeling IN diagnostically, interpreting measurements, and quantifying sensitivity to increasing N(sub IN) (when w(sub e)/v(sub f)< 1, entrainment rate limitations serve to buffer cloud system response). To reproduce observed ice crystal size distributions and cloud radar reflectivities with rapidly consumed IN in this case, the measured above-cloud N(sub IN) must be multiplied by approximately 30. However, results are sensitive to assumed ice crystal properties not constrained by measurements. In addition, simulations do not reproduce the pronounced mesoscale heterogeneity in radar reflectivity that is observed.

Fridlin, Ann↗

Aerosol-deep convection interaction based on joint cell-thermal tracking in Large Eddy Simulations during the TRACER campaign

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

54 ENVIRONMENTAL SCIENCES↗

Responses of Precipitation and Hydrologic Processes to Tropical SST

The goal of the research is to identify the mechanisms in the response of tropical precipitation and atmospheric hydrologic cycle to sea surface temperature (SST) variability at seasonal-to-interannual time scales, and to utilize the knowledge for better understanding of climate feedback processes relevant to global change. As a first step to achieve the goal, we characterize the inter-relationship among convective/stratiform rain, ice/water clouds water vapor, and SST using TRMM satellite data and a cloud-resolving model. We examined the daily hydrologic variables [column water vapor (PW), cloud liquid water (CW), rainfall rates (RR)] as a function of SST using high-resolution data (0.25 x 0.25, daily) derived from TRMM satellite measurements. Comparing the winter of 97/98 (El Nino condition) against the winter of 99/00 (La Nina condition), area-mean values of all four hydrologic variables in cloudy areas within the tropical Pacific are higher in the El Nino winter than in the La Nina winter. This is consistent with previous observational analyses and SST warming experiments (idealized or ENSO-like) that showed the interaction between hydrologic cyclic and radiation at the seasonal to interannual time scales leads to intensified tropical circulation and hydrologic cycle. However, there is evidence that the enhanced hydrologic cycle over the warm pool is accompanied by an expansion of radiatively -driven subsidence in response to a stronger SST gradient between warm pool and surrounding cold pool. The expanding subsidence effectively reduces cloud amounts over the warm pool. Our analysis of daily variability further indicates a more vigorous water cycle characterized by higher PW, CW, and RR in response to overall warming. This is expected from the Clausius Clapeyron relation as a thermodynamic response to warming. However cloudy areas decrease in response to overall warming. This may be due to factors that are fundamentally different. One possibility is that in a warmer climate, there may be alteration in the microphysical processes in clouds, e.g., increased coalescence of cloud size droplets and increased entrainment of dry air from above due to the invigorated convective motions in response to overall warming. As a result, cloud amounts are less. Another interpretation is that, in colder air masses, more ice particles will be produced and, because of their lower densities, are less likely to precipitate, hence the higher cloud amount. This suggests that, when averaged over a sufficiently large area covering both the rising and sinking branches of the tropical circulation, there maybe an increase in the precipitation efficiency in stratiform clouds, in conjunction with increased subsidence in an enhanced water cycle. This is supported by the residence time at different rainrates.

Sui, C.-H.↗

Simulating a Mesoscale Convective System Using WRF with a New Spectral Bin Microphysics: Part 1: Hail vs Graupel

A modified Fast Spectral Bin Microphysics scheme (FSBM-2) embedded into the Weather Research and Forecasting Model (WRF) is used to simulate a mesoscale deep convective system observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). FSBM-2 uses modified source codes as compared to the current FSBM (FSBM-1). In contrast to FSBM-1, FSBM-2 can simulate hail of several cm in diameter and includes additional processes such as spontaneous breakup of raindrops and aerosol regeneration by drop evaporation. It is shown that allowing large hail particles of diameters exceeding about 1 cm substantially increases the agreement between the simulated and observed squall-line structures both in the convective and stratiform regions. In contrast, if graupel particles are used to represent high-density hydrometeors in convective areas, the ratio of convective-to-stratiform areas diverges from the ratio seen in observations and maximum radar reflectivities are substantially underestimated. Analysis of snow size distributions in the stratiform area shows an important link between the ice crystals formed by homogeneous freezing in the convective area to ice particle number concentration in the stratiform region. Simulated raindrop size distributions in the stratiform area below the melting level from FSBM-2 show a good agreement with observations. The regeneration of CCN by droplet evaporation and detrainment of these CCN to the stratiform region increases the concentration of CCN there up to 8-9 km altitude; the additional CCN penetrate clouds and produce new droplets, leading to some convection intensification. Key words: Mesoscale convective systems (MCS), squall lines, spectral bin microphysics, large hail, in-cloud nucleation, size distributions of hydrometeors in MCS.

Shpund, Kobby↗

Tropical Convective Responses to Microphysical and Radiative Processes: A Sensitivity Study With a 2D Cloud Resolving Model

Prognostic cloud schemes are increasingly used in weather and climate models in order to better treat cloud-radiation processes. Simplifications are often made in such schemes for computational efficiency, like the scheme being used in the National Centers for Environment Prediction models that excludes some microphysical processes and precipitation-radiation interaction. In this study, sensitivity tests with a 2D cloud resolving model are carried out to examine effects of the excluded microphysical processes and precipitation-radiation interaction on tropical thermodynamics and cloud properties. The model is integrated for 10 days with the imposed vertical velocity derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The experiment excluding the depositional growth of snow from cloud ice shows anomalous growth of cloud ice and more than 20% increase of fractional cloud cover, indicating that the lack of the depositional snow growth causes unrealistically large mixing ratio of cloud ice. The experiment excluding the precipitation-radiation interaction displays a significant cooling and drying bias. The analysis of heat and moisture budgets shows that the simulation without the interaction produces more stable upper troposphere and more unstable mid and lower troposphere than does the simulation with the interaction. Thus, the suppressed growth of ice clouds in upper troposphere and stronger radiative cooling in mid and lower troposphere are responsible for the cooling bias, and less evaporation of rain associated with the large-scale subsidence induces the drying in mid and lower troposphere.

Li, Xiao-Fan↗

Radiative processes in upper tropospheric mixed-phase clouds

The diffusional mass evolution of hydrometeors in upper tropospheric clouds for various radiative conditions in the cloud and for varying ambient moisture supply is simulated using a time dependent microphysical model. Radiation can play an important role in this mass evolution when only one phase is present. When both liquid droplets and ice crystals are situated in a typical upper tropospheric environment and the moisture supply is limited, radiation produces only a minor effect on the mass evolution of the hydrometeors. In these cases ice crystals grow quickly at the expense of the droplets and the droplets evaporate within several minutes, even under water supersaturation conditions. Radiation does not significantly influence the evaporation rates of the droplets in the coexisting cases. In the absence of ice crystals and under certain radiative conditions, the droplets can survive when the environment is subsaturated. For other radiative conditiions, the droplets can evaporate when the environment is supersaturated.

Wesley, Douglas A.↗

Systematic Validation of Ensemble Cloud-Process Simulations using Polarimetric Radar Observations and Simulator over the NASA Wallops Flight Facility

The BiLateral Operational Storm-Scale Observation and Modeling (BLOSSOM) project was initiated to establish a long-term supersite to improve understanding of cloud physical states and processes as well as to support satellite and climate model programs over the WFF site via a bilateral approach of storm-scale observations and process modeling. This study highlights a noble systematic validation framework of the BLOSSOM ensemble cloud-process simulations through mixed-phase, light-rain, and deep-convective precipitation cases. The framework consists of creating a domain-shifted ensemble of large-scale forcing datasets, and configuring and performing cloud-process simulations with three different bulk microphysics schemes. Validation uses NASA S-band dual-POLarimetric radar (NPOL) observations in the form of statistical composites and skill scores via a polarimetric radar simulator and newly developed CfRad Data tool (CfRAD). While the simulations capture the overall structures of the reflectivity composites, polarimetric signals are still poorly simulated, mainly due to a lack of representation of ice microphysics diversity in shapes, orientation distributions, and their complex mixtures. Despite the limitation, this new ensemble-based validation framework demonstrates that 1) no particular forcing or microphysics scheme outperforms the rest and 2) the skill scores of coarse- and fine-resolution ensemble simulations with different domain-shifted forcing and microphysics schemes are highly correlated with each other with no clear improvement. On the other hand, this suggests that coarse-resolution ensemble simulations are relevant for selecting the best meteorological forcing and microphysics scheme before conducting computationally demanding large eddy simulations (LESs) in support of aircraft and satellite instrument development as well as cloud-precipitation-convection parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Cirrus Cloud Radiative and Microphysical Properties from Ground Observations and In Situ Measurements During FIRE 1991 and Their Application to Exhibit Problems in Cirrus Solar Radiative Transfer Modeling

Measurements from the FIRE 1991 cirrus cloud field experiment in the central United States are presented and analyzed. The first part focuses on cirrus microphysical properties. Aircraft 2D-probe in situ data at different cloud altitudes were evaluated for cirrus cases on four different days. Also presented are simultaneous data samples from balloonborne videosondes. Only these balloonsondes could detect the smaller crystals. Their data suggest (at least for midlatitude altitudes below 10 km) that ice crystals smaller than 15 microns in size are rare and that small ice crystals not detected by 2D-probe measurements are radiatively of minor importance, as overlooked 2D-probe crystals account for about 10% of the total extinction. The second part focuses on the link between cirrus cloud properties and radiation. With cloud macrophysical properties from surface remote sensing added to the microphysical data and additional radiation measurements at the surface, testbeds for radiative transfer models were created. To focus on scattering processes, model evaluations were limited to the solar radiative transfer by comparing calculated and measured transmissions of sunlight at the surface. Comparisons under cloud-free conditions already reveal a model bias of about +45 W/sq m for the hemispheric solar downward broadband flux. This discrepancy, which is (at least in part) difficult to explain, has to be accounted for in comparisons involving clouds. Comparisons under cirrus cloud conditions identify as the major obstacle in cirrus solar radiative transfer modeling the inability of one-dimensional radiative transfer models to account for horizontal inhomogeneities. The successful incorporation of multidimensional radiative transfer effects will depend not only on better models but critically on the ability to measure and to define characteristic inhomogeneity scales of cloud fields. The relative minor error related to the microphysical treatment is in part a reflection of the improved understanding on solar scattering on ice crystals over the last decade and of the available wealth on ice-crystal size and shape data for this study. In absence of this information, uncertainties from microphysical cirrus model assumptions will remain high.

Kinne, Stefan↗

Updates on Modeling the Water Cycle with the NASA Ames Mars Global Climate Model

Global Circulation Models (GCMs) have made steady progress in simulating the current Mars water cycle. It is now widely recognized that clouds are a critical component that can significantly affect the nature of the simulated water cycle. Two processes in particular are key to implementing clouds in a GCM: the microphysical processes of formation and dissipation, and their radiative effects on heating/ cooling rates. Together, these processes alter the thermal structure, change the dynamics, and regulate inter-hemispheric transport. We have made considerable progress representing these processes in the NASA Ames GCM, particularly in the presence of radiatively active water ice clouds. We present the current state of our group's water cycle modeling efforts, show results from selected simulations, highlight some of the issues, and discuss avenues for further investigation.­

Global Circulation Models (GCMs)↗

Single-Scattering Properties of Melting Precipitation for GPM Passive Microwave and Radar Remote Sensing Applications

Over the past two decades, detailed computational simulations of the intricate three dimensional structures of ice-phase crystals and aggregates of those crystals have been developed. The microwave single-scattering properties of these simulated ice particles have been computed and used to improve quantitative estimates of snow rates and to better deRne the vertical structure of snow water contents in deep convective systems, as derived from satellite-borne passive microwave and/or radar remote sensing measurements. The same icephase particles have more recently been used as the starting point for simulations of melting precipitation using computational melting methods. In the current study, a heuristic melting method, as well as a physically-based melting procedure based on smoothed-particle hydrodynamics, are applied to ice particle models to describe the full evolution of the particles from dry snow to liquid drops. The discrete dipole approximation is utilized to calculate the single-scattering properties of the mixed-phase particles throughout the melting process. Then, the properties of the particles are “mapped” into simpliRed microphysical simulations of particle size spectra in the melting layers of stratiform, precipitating clouds. The bulk single-scattering properties of the melting layers and the sensitivity of their properties to modeling assumptions are explored, and the implications for combined radar-radiometer precipitation remote sensing from GPM are discussed.

William S Olson↗

Impacts of Latent Energy and Snow Fall Speed on a Wintertime Midlatitude Cyclone

This study aimed to understand the impacts of latent energy as well as snow fall speeds on precipitation properties and synoptic-scale storm characteristics of a wintertime midlatitude cyclone. Simulations of a potent winter storm that impacted the Rocky Mountains and northern Great Plains of the United States in February 2017 were performed using the Weather Research and Forecasting model with latent heating or cooling from individual microphysical processes systematically turned off and fall speeds adjusted by ±50%. Results indicated substantial impacts on the microphysical characteristics of the simulated storm to fall speed, cooling from sublimation, and warming from deposition. The impacts of cooling and warming were manifested as differences in accumulated snowfall. Increased (decreased) fall speeds led to smaller (larger) ice crystals and total mass, resulting in offsetting effects on the precipitation flux, and thus minimal impacts on snowfall and large-scale characteristics of the storm. Warming and cooling associated with deposition and sublimation, respectively, impacted the synoptic-scale dynamics, whereby removing warming from deposition resulted in an increased meridional temperature gradient near the jet stream, thus increasing the jet strength and causing it to be more westerly with less curvature aloft. This in turn limited upper-level divergence, creating a weaker surface low and shifting the precipitation shield southward. The opposite occurred with the removal of latent cooling due to sublimation. This study highlights the potential importance of latent energy associated with ice sublimation and deposition and fall speeds in the larger-scale characteristics of winter storms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Denitrification mechanisms in the polar stratospheres

Microphysical simulations suggest that the time required for nitric acid particles to sediment from the stratosphere is comparable to the time required for falling ice particles to incorporate nitric acid vapor from the vapor phase. Since nitric acid particles form earlier in the winter than ice particles, these simulations favor denitrification being a separate process from dehydration, with denitrification being due to nitric acid particles and dehydration due to ice particles. In the simulations, the column abundance of nitric acid is only depleted if temperatures low enough for nitric acid particles to exist extend to the altitude above which the column is measured. Such low temperatures are infrequent in the Arctic lower stratosphere, which may be the main reason that the Arctic stratospheric column shows little loss of nitric acid during winter, while the colder Antarctic stratospheric column shows a substantial loss of nitric acid.

Toon, Owen B.↗

Long-term measurements of ice nucleating particles at Atmospheric Radiation Measurement (ARM) sites worldwide

Ice nucleating particles (INPs) play a critical role in cloud microphysics and precipitation formation, yet long-term, spatially extensive observational datasets remain limited. Here, we present one of the most comprehensive publicly available datasets of immersion-mode INP concentrations using a single analytical method, generated through the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility. INP filter samples have been collected across a broad range of environments – including agricultural plains, Arctic coastlines, high-elevation mountain sites, marine regions, and urban areas – via fixed observatories, mobile facility deployments, and vertically-resolved tethered balloon system operations. We describe the standardized processing and quality assurance pipeline, from filter collection and processing using the Ice Nucleation Spectrometer to final data products archived on the ARM Data Discovery portal. The dataset includes both total INP concentrations and selectively treated samples, allowing for classification of biological, organic, and inorganic INP types. It features a continuous 5-year record of INP measurements from a central U.S. site, with data collection still ongoing. Seasonal and site-specific differences in INP concentrations are illustrated through intercomparisons at −10 and −20 °C, revealing distinct regional sources and atmospheric drivers. We also outline mechanisms for researchers to access existing data, request additional sample analyses, and propose future field campaigns involving ARM INP measurements. This dataset supports a wide range of scientific applications, from observational and mechanistic studies to model development, and provides critical constraints on aerosol-cloud interactions across diverse atmospheric regimes (Creamean et al., 2024, 2020b; https://doi.org/10.5439/1770816).

Creamean, Jessie M. [Colorado State Univ., Fort Co↗