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We provide the first systematic study of ice formation in idealised shallow clouds from collisions of supercooled water drops with ice particles (‘mode 2’). Using the University of Manchester bin-microphysics parcel model, we investigated the sensitivity of ice formation due to mode 2 for a wide range of parameters: aerosol particle size distribution, updraft speed, cloud base temperature, cloud depth, ice-nucleating particle concentration and freezing fraction of mode 2. We provide context to our results with other secondary ice production mechanisms as single mechanisms and combinations (rime-splintering, spherical freezing fragmentation of drops [‘mode 1’] and ice-ice collisions). There was a significant sensitivity to aerosol particle size distribution when updraft speeds were low (0.5 m s−1); secondary ice formation did not occur when the aerosol particle size distribution mimicked polluted environments. Where secondary ice formation did occur in simulated clouds, significant ice formation in the shallower clouds (1.3 km deep) was due to mode 2 or a combination which included mode 2. The deeper clouds (2.4 km deep) also had significant contributions from rime-splintering or ice-ice collisions SIP mechanisms. While simulations with cloud base temperatures of 7 °C were relatively insensitive to ice-nucleating particle concentrations, there was a sensitivity in simulations cloud base temperatures of 0 °C. Increasing the ice-nucleating particle concentration delayed ice formation. Our results suggest that collisions of supercooled water drops with ice particles may be a significant ice formation mechanism within shallow convective clouds where rime-splintering is not active.

The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (< 200 µm) in certain conditions. This work suggests that the observational evidence for a ubiquitous mode of small ice particles in ice clouds is likely due to a systematic instrument bias. Size distribution parameterisations based on OAP measurements need to be revisited using these improved methodologies.

Correct, timely and meaningful interpretation of polarimetric weather radar observations requires an accurate understanding of hydrometeors and their associated microphysical processes along with well-developed techniques that automatize their recognition in both the spatial and temporal dimensions of the data. This study presents a novel technique for identifying different types of hydrometeors from quasi-vertical profiles (QVPs). In this new technique, the hydrometeor types are identified as clusters belonging to a hierarchical structure. The number of different hydrometeor types in the data is not predefined, and the method obtains the optimal number of clusters through a recursive process. The optimal clustering is then used to label the original data. Initial results using observations from the National Centre for Atmospheric Science (NCAS) X-band dual-polarization Doppler weather radar (NXPol) show that the technique provides stable and consistent results. Comparison with available airborne in situ measurements also indicates the value of this novel method for providing a physical delineation of radar observations. Although this demonstration uses NXPol data, the technique is generally applicable to similar multivariate data from other radar observations.

In situ observations from research aircraft and instrumented ground sites are important contributions to developing our collective understanding of clouds and are used to inform and validate numerical weather and climate models. Unfortunately, biases in these datasets may be present, which can limit their value. In this paper, we discuss artefacts which may bias data from a widely used family of instrumentation in the field of cloud physics, optical array probes (OAPs). Using laboratory and synthetic datasets, we demonstrate how greyscale analysis can be used to filter data, constraining the sample volume of the OAP and improving data quality, particularly at small sizes where OAP data are considered unreliable. We apply the new methodology to ambient data from two contrasting case studies: one warm cloud and one cirrus cloud. In both cases the new methodology reduces the concentration of small particles (µm) by approximately an order of magnitude. This significantly improves agreement with a Mie-scattering spectrometer for the liquid case and with a holographic imaging probe for the cirrus case. Based on these results, we make specific recommendations to instrument manufacturers, instrument operators and data processors about the optimal use of greyscale OAPs. The data from monoscale OAPs are unreliable and should not be used for particle diameters below approximately 100 µm.

Carbon monoxide (CO) is a regulated pollutant and one of the key components determining the oxidizing capacity of the atmosphere. Obtaining a reliable record of atmospheric CO mixing ratios since pre-industrial times is necessary to evaluate climate-chemistry models in conditions different from today. We present high-resolution measurements of CO mixing ratios from ice cores drilled at five different sites on the Greenland ice sheet which experience a range of snow accumulation rates, mean surface temperatures, and different chemical compositions. An optical-feedback cavity-enhanced absorption spectrometer (OF-CEAS) was coupled to continuous melter systems and operated during four analytical campaigns conducted between 2013 and 2019. The CFA-based CO measurements exhibit excellent external precision (ranging 3.3 - 6.6 ppbv, 1σ), and achieve consistently low blanks (ranging from 4.1±1.2 to 12.6±4.4 ppbv). Good accuracy and absolute calibration of CFA-based CO records enable paleo-atmospheric interpretations. The five CO records all exhibit variability in CO mixing ratios that is too large and rapid to reflect past atmospheric mixing ratio changes. Complementary tests conducted on discrete ice samples demonstrate that such patterns are not related to the analytical process (i.e., production of CO from organics in the ice during melting), but very likely are related to in situ CO production within the ice before analyses. Evaluation of signal resolution and co-investigation of high-resolution records of CO and TOC show that past atmospheric CO concentration can be extracted from the records’ baselines at four sites with accumulation rates higher than 20 cm water equivalent per year (weq yr-1). However, such baselines should be taken as upper bounds of past atmospheric CO burden. CO records from four sites are combined to produce a multisite average ice core reconstruction of past atmospheric CO for the Northern Hemisphere high latitudes, covering the period from 1700 to 1957 CE. From 1700 to 1875 CE, this record reveals stable or slightly increasing values remaining in the 100-115 ppbv range. From 1875 to 1957 CE, the record indicates a monotonic increase from 114±4 ppbv to 147±6 ppbv. The ice-core multisite CO record exhibits an excellent overlap with the atmospheric CO record from Greenland firn air which span the 1950-2010 time period. The combined ice-core and firn air CO history, spanning 1700-2010 CE, largely exhibits patterns that are consistent with the recent anthropogenic and biomass burning CO emission inventories. This brand new time series will be compared with the most recent results from Earth System Models involved in the CMIP6-AerChemMIP multi-model exercise.

Important uncertainties remain in our understanding of the spatial and temporal variability of atmospheric hydroxyl radical concentration ([OH]). Carbon-14-containing carbon monoxide (14CO) is a useful tracer that can help in the characterization of [OH] variability. Prior measurements of atmospheric 14CO concentration ([14CO] are limited in both their spatial and temporal extent, partly due to the very large air sample volumes that have been required for measurements (500–1000 liters at standard temperature and pressure, L STP) and the difficulty and expense associated with the collection, shipment and processing of such samples. Here we present a new method that reduces the air sample volume requirement to &approx; 90 L STP while allowing for [14CO] measurement uncertainties that are on par with or better than prior work (&approx; 3 % or better, 1 σ). The method also for the first time includes accurate characterization of the overall procedural [14CO] blank associated with individual samples, a key improvement over prior atmospheric 14CO work. The method was used to make measurements of [14CO] at the NOAA Mauna Loa Observatory, Hawaii, USA, between November 2017 and November 2018. The measurements show the expected [14CO] seasonal cycle (lowest in summer) and are in good agreement with prior [14CO] results from another low-latitude site in the Northern Hemisphere. The lowest overall [14CO] uncertainties (2.1 %, 1 σ) are achieved for samples that are directly accompanied by procedural blanks and whose mass is increased to &approx; 50 micrograms of carbon (µgC) prior to the 14C measurement via dilution with a high-CO, 14C-depleted gas.

The cloud particle concentration, size and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that removes the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data processing protocols, either removing or significantly reducing the concentration of small ice crystals (

Mineral dust is an important component of the climate system, affecting the radiation balance, cloud properties, biogeochemical cycles, regional circulation and precipitation, as well as having negative effects on aviation, solar energy generation and human health. Dust size and composition has an impact on all these processes. However, changes in dust size distribution and composition during transport, particularly for coarse particles, are poorly understood and poorly represented in climate models. Here we present new in-situ airborne observations of dust in the Saharan Air Layer (SAL) and the Marine Boundary Layer (MBL) at the beginning of its trans-Atlantic transport pathway, from the AER-D fieldwork in August 2015, within the peak season of North African dust export. This study focuses on coarse mode dust properties, including size distribution, mass loading, shape, composition, refractive indices and optical properties. Size distributions from 0.1 to 100 µm diameter (d) are presented, fully incorporating the coarse and giant modes of dust. Within the MBL, mean effective diameter (deff) and volume median diameter (VMD) were 4.6 µm and 6.0 µm respectively, giant particles with a mode at 20-30 µm were observed, and composition was dominated by quartz and alumino-silicates at d > 1 µm. Within the SAL, particles larger than 20 µm diameter were always present up to 5km altitude, in concentrations over 10-5 cm-3, constituting up to 40% of total dust mass. Mean deff and VMD were 4.0 µm and 5.5 µm respectively. Larger particles were detected in the SAL than can be explained by sedimentation theory alone. Coarse mode composition was dominated by quartz and alumino-silicates; the accumulation mode showed a strong contribution from sulfate-rich and sea salt particles. In the SAL, measured single scattering albedos (SSAs) at 550nm representing d

Secondary ice production via processes like rime splintering, frozen droplet shattering, and breakup upon ice hydrometeor collision have been proposed to explain discrepancies between in-cloud ice crystal and ice-nucleating particle numbers. To understand the impact of this kind of additional ice number generation on surface precipitation, we present one of the first studies to implement frozen droplet shattering and ice-ice collisional breakup parameterizations in a larger-scale model. We simulate a cold frontal rainband from the Aerosol Properties, PRocesses, And InfluenceS on the Earth's Climate campaign and investigate the impact of the new parameterizations on the simulated ice crystal number concentrations (ICNC) and precipitation. Near the convective regions of the rainband, contributions to ICNC can be as large from secondary production as from primary nucleation, but ICNCs greater than 50 L−1 remain underestimated by the model. Addition of the secondary production parameterizations also clearly intensifies the differences in both accumulated precipitation and precipitation rate between the convective towers and non-convective gap regions. We suggest, then, that secondary ice production parameterizations be included in large-scale models on the basis of large hydrometeor concentration and convective activity criteria.

Intense rainfall generated by convective clouds causes flash flooding in many parts of the world. Understanding the microphysical processes leading to the formation of precipitation is one of the main challenges to improving our capability to make quantitative precipitation forecasts. Here, we present microphysics observations of cumulus clouds measured over the Southwest Peninsula of the UK during the COnvective Precipitation Experiment (COPE) in August 2013, which are framed into a wider context using ground-based and airborne radar measurements. Two lines of cumulus clouds formed in the early afternoon along convergence lines aligned with the peninsula. The lines became longer and broader during the afternoon as a result of new cell formation and stratiform regions forming downwind of the convective cells. Aircraft penetrations at −5 °C showed that all the required conditions of the Hallett–Mossop (H–M) ice multiplication process were met in developing regions, and ice concentrations up to 350 L−1 were measured in the mature stratiform regions, indicating that secondary ice production was active. Detailed sampling focused on an isolated liquid cloud that glaciated as it matured to merge with a band of cloud downwind. In the initial cell, a few drizzle drops were measured, some of which froze to form graupel; the ice images are most consistent with freezing drizzle, rather than smaller cloud drops forming the first ice. As new cells developed in and around the cloud, ice concentrations up to two orders of magnitude higher than the predicted ice nuclei concentrations began to be observed and the cloud glaciated over a period of 12–15 min. Ice splinters were captured by supercooled drizzle drops causing them to freeze to form instant-rimers. Graupel and columns were observed in cloud penetrations up to the −12 °C level, though many ice particles were mixed-habit due to riming and growth by vapour diffusion at multiple temperatures. Frozen drizzle/raindrops initially made up the majority of precipitation-sized particles in the H–M zone, while ice splinters required time to grow by vapour diffusion. It is therefore clear that the freezing of supercooled drizzle drops not only provides a pathway to advance the onset of the H–M process, it also accelerates glaciation and the formation of precipitation once it has begun. Accurate representation of both the warm rain and H–M processes, including their interactions with each other and cloud dynamics, appears key to determining the timing and location of precipitation.

In situ airborne observations of cloud microphysics, aerosol properties and thermodynamic structure over the transition from sea ice to ocean are presented from the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign. A case study from 23 March 2013 provides a unique view of the cloud microphysical changes over this transition under cold air outbreak conditions. Cloud base and depth both increased over this transition, and mean droplet number concentrations also increased from approximately 80 cm−3 over the sea ice to 90 cm−3 over the ocean. The ice properties of the cloud remained approximately constant. Observed ice crystal concentrations averaged approximately 0.5–1.5 L−1, suggesting only primary ice nucleation was active; however, there was evidence of crystal fragmentation at cloud base over the ocean. The liquid-water content increased almost four-fold over the transition and this, in conjunction with the deeper cloud layer, allowed rimed snowflakes to develop which precipitated out of cloud base. Little variation in aerosol particle number concentrations was observed between the different surface conditions; however, some variability with altitude was observed, with notably greater concentrations measured at higher altitudes (> 800 m) over the sea ice. Near-surface boundary layer temperatures increased by 13 °C from sea ice to ocean, with corresponding increases in surface heat fluxes and turbulent kinetic energy. These significant thermodynamic changes were concluded to be the primary driver of the microphysical evolution of the cloud. This study represents the first investigation, using in situ airborne observations, of cloud microphysical changes with changing sea ice cover and addresses the question of how the microphysics of Arctic stratiform clouds may change as the region warms and sea ice extent reduces.