Ice‐nucleating particle emissions from biomass combustion and the potential importance of soot aerosol
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Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly-continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This dataset provides a set of 25 samples from the M-PACE field campaign, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation variables in this dataset include, among others, the ice number concentration, water content, PSD parameters, precipitation rate, mass-weighted fall velocity, vertical air motion, and effective radius, all of which are highly valuable for model evaluation and a general understanding of polar cloud sink processes. Each variable sample includes its mean value and associated uncertainty. Additional variables based on ARM measurements (liquid layer statistics, etc.) are included in this dataset as well. The retrieval algorithm and analysis of this dataset are described in Silber (JGR, 2023, https://doi.org/10.1029/2022JD038202).
Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This data set provides more than 1800 samples of cloud-base ice precipitation properties over Utqiagvik, North Slope of Alaska, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation variables in this data set include, among others, the ice number concentration, water content, PSD parameters, precipitation rate, mass-weighted fall velocity, vertical air motion, and effective radius, all of which are highly valuable for model evaluation and a general understanding of polar cloud sink processes. Each variable sample includes its mean value and associated uncertainty. Additional variables based on ARM measurements (liquid layer statistics, etc.) are included in this data set. The retrieval algorithm and analysis of this data set are described in Silber (JGR, 2023, https://doi.org/10.1029/2022JD038202).
On February 8, 1993, the NASA DC-8 aircraft profiled from 10,000 to 37,000 feet (3.1-11.3 km) pressure altitude in a stratified section of tropical cyclone "Oliver" over the Coral Sea northeast of Australia. Size, shape and phase of cloud and precipitation particles were measured with a 2-D Greyscale probe. Cloud/precipitation particles changed from liquid to ice as soon as the freezing level was reached near 17,000 feet (5.2 km) pressure altitude. The cloud was completely glaciated at -5 C. There was no correlation between ice particle habit and ambient temperature. In the liquid phase, the precipitation-cloud drop concentration was 4.0 x 10(exp 3)/cu m, the geometric mean diameter D(sub g) = 0.5-0.7 mm, and the liquid water content 0.7-1.9 g m(exp-3). The largest particles anywhere in the cloud, dominated by fused dendrites at concentrations similar to that of raindrops (2.5 x 10(exp 3) m(exp -3)) but a higher condensed water content(5.4 g/cu m estimated) were found in the mixed phase; condensed water is removed very effectively from the mixed layer due to high settling velocities of the large mixed particles. The highest number concentration (4.9 x 10(exp 4)/cu m, smallest size (D(sub g) = 0.3-0.4 mm), largest surface area (up to 2.6 x 10 (exp 2) sq cm/cu m at 0.4- 1.0 g/cu m of condensate) existed in the ice phase at the coldest temperature (- 40 C) at 35,000 feet ( 10.7 km). Each cloud contained aerosol (haze particles) in addition to cloud particles. The aerosol total surface area exceeded that of the cirrus particles at the coldest temperature. Thus, aerosols must play a significant role in the upscattering of solar radiation. Light extinction (6.2/km) and backscatter (0.8/sr/km) was highest in the coldest portion of the cirrus cloud at the highest altitude.
Mixed-phase clouds (MPCs) have been identified as significant contributors to uncertainties in climate projections, attributable to model representation of processes controlling the formation and loss of supercooled water droplets and ice particles from the atmosphere. Arctic MPCs are commonly widespread and long-lived, with sustained ice crystal formation processes that challenge current understanding. This study examines the ice-nucleating particle (INP) reservoir dynamics governing immersion-mode heterogeneous freezing in an observed case of Arctic MPCs using a simplified 1D aerosol-cloud model. The model setup includes prescribed dynamical forcings and thermodynamic profiles, and represents INPs as multicomponent and polydisperse particle size distributions. Diagnostic and prognostic approaches to immersion freezing parameterization are compared, including time-independent (singular) number- and surface area-based descriptions and a time-dependent description following classical nucleation theory (CNT). The choice of freezing parameterization defines the size of the INP reservoir. The CNT-based description yields an orders of magnitude larger INP reservoir than the singular parameterizations, which is the dominant factor for sustained ice crystal formation. The efficiency of the freezing process and cloud cooling are of secondary importance. A diagnostic treatment neglecting INP loss is only accurate when the INP reservoir size is large and INP depletion weak. Since a larger INP reservoir sustains ice crystal formation substantially longer, and ice water path scales with ice crystal concentrations for the conditions considered, resolving the source of differences in INP reservoir dynamics due to model implementation is a high priority for advancing climate model physics.
This paper builds on previous work that compares numerical simulations of mixed-phase icing clouds with experimental data. The model couples the thermal interaction between ice particles and water droplets of the icing cloud with the flowing air of an icing wind tunnel for simulation of NASA Glenn Research Centers (GRC) Propulsion Systems Laboratory (PSL). Measurements were taken during the Fundamentals of Ice Crystal Icing Physics Tests at the PSL tunnel in March 2016. The tests simulated ice-crystal and mixed-phase icing that relate to ice accretions within turbofan engines. Experimentally measured air temperature, humidity, total water content, liquid and ice water content, as well as cloud particle size, are compared with model predictions. The model showed good trend agreement with experimentally measured values, but often over-predicted aero-thermodynamic changes. This discrepancy is likely attributed to radial variations that this one-dimensional model does not address. One of the key findings of this work is that greater aero-thermodynamic changes occur when humidity conditions are low. In addition a range of mixed-phase clouds can be achieved by varying only the tunnel humidity conditions, but the range of humidities to generate a mixed-phase cloud becomes smaller when clouds are composed of smaller particles. In general, the model predicted melt fraction well, in particular with clouds composed of larger particle sizes.
Soot enters the stratosphere either from the troposphere in deep thunderstorm convection, predominantly in the tropics, from midlatitude forest fires, and directly from aircraft flying above the tropopause. Particles emitted from jet aircraft are relatively ineffective as cloud droplet condensation nuclei (less than 1 percent) compared with those from forest fires (above 50 percent). Chemical and other modification during aging of the particles may influence these results in some circumstances; cloud nucleating properties can be used as a soot tracer. Such aerosols, as they grow to haze drops and ilute in increasing humidity, may form ice particles in the cold polar stratosphere or in tropical cumuli anvils at 18 to 20 km altitude at temperatures as low as -90 C. Ice may also form as particles are removed by descent through troposphere folds and enter midlatitude cirrus at levels below -40 C. In the stratosphere, ice particles may provide surfaces that catalyze heterogeneous chemical reactions; in the upper troposphere, the optical depths of cirrus clouds may be significantly increased.
Abstract Mixed‐phase clouds (MPCs) have been identified as significant contributors to uncertainties in climate projections, attributable to model representation of processes controlling the formation and loss of supercooled water droplets and ice particles from the atmosphere. Arctic MPCs are commonly widespread and long‐lived, with sustained ice crystal formation processes that challenge current understanding. This study examines the ice‐nucleating particle (INP) reservoir dynamics governing immersion‐mode heterogeneous freezing in an observed case of Arctic MPCs using a simplified 1D aerosol‐cloud model. The model setup includes prescribed dynamical forcings and thermodynamic profiles, and represents INPs as multicomponent and polydisperse particle size distributions. Diagnostic and prognostic approaches to immersion freezing parameterization are compared, including time‐independent (singular) number‐ and surface area‐based descriptions and a time‐dependent description following classical nucleation theory (CNT). The choice of freezing parameterization defines the size of the INP reservoir. The CNT‐based description yields an orders of magnitude larger INP reservoir than the singular parameterizations, which is the dominant factor for sustained ice crystal formation. The efficiency of the freezing process and cloud cooling are of secondary importance. A diagnostic treatment neglecting INP loss is only accurate when the INP reservoir size is large and INP depletion weak. Since a larger INP reservoir sustains ice crystal formation substantially longer, and ice water path scales with ice crystal concentrations for the conditions considered, resolving the source of differences in INP reservoir dynamics due to model implementation is a high priority for advancing climate model physics.
The reaction rate between atmospheric hydrogen chloride (HCl) and chlorine nitrate (ClONO2) is greatly enhanced in the presence of ice particles; HCl dissolves readily into ice, and the collisional reaction probability for ClONO2 on the surface of ice with HCl in the mole fraction range from about 0.003 to 0.010 is in the range from about 0.05 to 0.1 for temperatures near 200 K. Chlorine is released into the gas phase on a time scale of at most a few milliseconds, whereas nitric acid (HNO3), the other product, remains in the condensed phase. This reaction could play an important role in explaining the observed depletion of ozone over Antarctica; it releases photolytically active chlorine from its most abundant reservoir species, and it promotes the formation of HNO3 and thus removes nitrogen dioxide from the gas phase. Hence it establishes the necessary conditions for the efficient catalytic destruction of ozone by halogenated free radicals.
Nitrogen and methane ices on the surface of Triton, Neptune's largest satellite, are exchanged between the summer and winter hemispheres on a seasonal time scale. Images of the satellite's sky obtained by the Voyager 2 spacecraft show the presence of several types of scattering materials that provide insights into this seasonal cycle of volatiles. Discrete clouds, probably composed of N2 ice particles, arise in regions of active sublimation. They are found chiefly poloward of 30 deg S in the southern, summer hemisphere. Haze particles, probably made of hydrocarbon ices, are present above most, but not all places. Recent snowfall may have occurred at low southern latitudes in places where they are absent. The latent heat released in the formation of the discrete clouds may have a major impact on the thermal balance of the lower atmosphere. Triton may have been less red at the time of the Voyager flyby than 12 years earlier due to recent N2 snowfall at a wide range of latitudes.
The relationship between cirrus particle size and cloud top temperature is surveyed on a near-global scale. The cirrus particle size is retrieved assuming ice crystals are hexagonal columns and the cloud top temperature and the radiances in channel 1 and 3 of AVHRR used to retrieve ice particle sizes are from ISCCP product. The results show that for thick clouds over North America, the relation between particle size and cloud top temperature is consistent with a summary of this relationship based on aircraft measurement over that region for thick clouds. However, this relationship is not universal for other regions especially for for tropical zone, which has been found by other in situ measurements.
A Goddard bulk microphysical parameterization is implemented into the Weather Research and Forecasting (WRF) model. This bulk microphysical scheme has three different options, 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on different weather events: a midlatitude linear convective system and an Atlantic hurricane. The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The Goddard 3ICE scheme with the cloud ice-snow-hail configuration agreed better with observations ill of rainfall intensity and having a narrow convective line than did simulations with the cloud ice-snow-graupel and cloud ice-snow (i.e., 2ICE) configurations. This is because the Goddard 3ICE-hail configuration has denser precipitating ice particles (hail) with very fast fall speeds (over 10 m/s) For an Atlantic hurricane case, the Goddard microphysical scheme (with 3ICE-hail, 3ICE-graupel and 2ICE configurations) had no significant impact on the track forecast but did affect the intensity slightly. The Goddard scheme is also compared with WRF's three other 3ICE bulk microphysical schemes: WSM6, Purdue-Lin and Thompson. For the summer midlatitude convective line system, all of the schemes resulted in simulated precipitation events that were elongated in southwest-northeast direction in qualitative agreement with the observed feature. However, the Goddard 3ICE-hail and Thompson schemes were closest to the observed rainfall intensities although the Goddard scheme simulated more heavy rainfall (over 48 mm/h). For the Atlantic hurricane case, none of the schemes had a significant impact on the track forecast; however, the simulated intensity using the Purdue-Lin scheme was much stronger than the other schemes. The vertical distributions of model-simulated cloud species (e.g., snow) are quite sensitive to the microphysical schemes, which is an issue for future verification against satellite retrievals. Both the Purdue-Lin and WSM6 schemes simulated very little snow compared to the other schemes for both the midlatitude convective line and hurricane case. Sensitivity tests with these two schemes showed that increasing the snow intercept, turning off the auto-conversion from snow to graupel, eliminating dry growth, and reducing the transfer processes from cloud-sized particles to precipitation-sized ice collectively resulted in a net increase in those schemes' snow amounts.