Ice Clouds Research Articles

Scale Analysis of Typhoon In-Fa (2021) Based on FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) Observed and All-Sky-Simulated Brightness Temperature

Based on the Final Operational Global Analysis (FNL) data from the National Centers for Environmental Prediction and the ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts, the all-sky brightness temperatures of the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Fengyun-4A satellite (FY-4A) are simulated, which are then used to investigate Typhoon In-Fa (2021). The results show that the all-sky simulations based on ERA5 and FNL for FY-4A GIIRS channels 27 (716.25 cm−1), 90 (755.625 cm−1), and 417 (960 cm−1) can reproduce well the structure and intensity of Typhoon In-Fa. But the FNL simulations overestimate the typhoon intensity with more high ice clouds around the typhoon center. Fourier analysis of Typhoon In-Fa at severe tropical storm (STS) and typhoon (TY) stages is conducted. The results reveal that the dominant features of Typhoon In-Fa are primarily large-scale, with a relatively small proportion of observations and simulations dedicated to small-scale features at the STS stage. However, the proportion of large-scale features decreases while the amount of small-scale information increases during the TY stage. The purpose of this study is to assess the performance of FY-4A GIIRS all-sky simulations based on the ERA5 and FNL data, as well as to prepare for future all-sky data assimilations.

Airborne hydrophilic microplastics in cloud water at high altitudes and their role in cloud formation

Microplastic pollution is occurring in most ecosystem, yet their presence in high altitude clouds and their influence on cloud formation and climate change are poorly known. Here we analyzed microplastics in cloud water sampled at the summits of Japan mountains at 1300–3776 m altitude by attenuated total reflection imaging and micro-Fourier transform infrared spectroscopy. We observed nine microplastics including polyethylene, polypropylene, polyethylene terephthalate, polymethyl methacrylate, polyamide 6, polycarbonate, ethylene–propylene copolymer or polyethylene–polypropylene alloy, polyurethane, and epoxy resin. Microplastic were fragmented, with mean concentrations ranging from 6.7 to 13.9 pieces per liter, and with Feret diameters ranging from 7.1 to 94.6 μm. Microplastics bearing hydrophilic groups such as carbonyl and/or hydroxyl groups were abundant, suggesting that they might have acted as condensation nuclei of cloud ice and water. Overall, our finding suggest that high-altitude microplastics cloud influence cloud formation and, in turn, might modify the climate.

Liquid water content measurement with SEA multi-element sensor in CARDC icing wind tunnel: Calibration and performance

The measurement of cloud liquid water content (LWC) plays a critical role in the development of icing airworthiness standards for aircraft and the calibration of icing wind tunnels. The SEA multi-element sensor, the modern hot-wire device for LWC measurement, still faces several challenges for performance calibration due to the effects of the baseline drift and droplet retention characteristics. To fully calibrate the performance of the sensor, two wind tunnel tests were conducted in the China Aerodynamics Research and Development Center (CARDC) icing wind tunnel including a dry air calibration test and an icing cloud measurement test. Using the in-situ dry power calibration method developed in this study, the compensation function and the empirical formula of dry air Nusselt number for each sense element are obtained, and present great linear characteristics in the range of the test section velocity VTS from 40 to 110 m/s. However, there is an abnormal peak area of total power for the W1 element at the VTS of 120 and 130 m/s, which may be associated with significant water vapor condensation. The consistency and discrepancy of four LWC calculation methods via the combinations of dry and wet power calculation methods are assessed. Further, the LWC response characteristics of the sense elements are examined and the correlations of the droplet retention efficiency for the W2 and W3 elements are acquired as functions of median volume diameter. Finally, the measurement accuracy of the SEA multi-element sensor is validated compared to the icing blade device. It demonstrates that the uncertainty of the W1 element for the sensor is about ±5% at the low LWC and the W1 element has a better ability in the measurement of the high LWC.

Interannual Variation in Top-of-Atmosphere Upward Shortwave Flux over the Arctic Related to Sea Ice, Snow Cover, and Land Cloud Cover in Spring and Summer

Abstract We investigated the interannual variations in the annual mean and seasonal cycle of upward shortwave radiation at the top of the atmosphere (TOA SW↑) over the Arctic using the Clouds and the Earth’s Radiant Energy System (CERES) observation data during 2001–20. The annual mean TOA SW↑ over the Arctic showed a decreasing trend from 2001 to 2012 (−2.5 W m−2 decade−1) and had a large interannual variability after 2012. The standard deviation of detrended TOA SW↑ increased from 0.4 W m−2 in 2001–12 to 1.1 W m−2 in 2012–20. Over land, TOA SW↑ variation was related to snow cover in May; snow cover, cloud fraction, and cloud optical depth (COD) in June; and cloud fraction and COD in July. Over ocean, TOA SW↑ variation in June and July was linked to sea ice cover. TOA SW↑ variation over ocean in June and July after 2012 was highly related to the North Atlantic Oscillation (NAO). This study suggests that changes in the large annual mean TOA SW↑ variability after 2012 are explained by the timing of land snow and sea ice melt in spring and summer and cloud variability over land in summer.

Interactive 3D Visual Analysis of Weather Prediction Data Reveals Midlatitude Overshooting Convection during the CIRRUS-HL Field Experiment

Abstract In summer 2021, microphysical properties and climate impact of high- and midlatitude ice clouds over Europe and the North Atlantic were studied during the Cirrus High Latitude (CIRRUS-HL) airborne field campaign. The related forecasting and flight planning tasks provided a testbed for interactive 3D visual analysis. Operational analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) were visualized with the open-source software “Met.3D.” A combination of traditional 2D displays with innovative 3D views in the interactive visualization framework facilitated rapid and comprehensive exploration of the NWP data. By this means, the benefit of interactive 3D visual forecast products in the routine flight planning procedure was evaluated. Here, we describe the use of 3D tropopause and cloud visualizations during a convective event over the Alps, which became one of the CIRRUS-HL observation targets. For the planning of the research flight on 8 July 2021, our analysis revealed that simulated strong convective updrafts locally disturb the tropopause and inject ice water across the dynamical tropopause into the lower stratosphere. The presented example provides a novel 3D perspective of convective overshooting in a global NWP model and its impact on the tropopause and lower stratosphere. The case study shall encourage the atmospheric science community to further evaluate the use of modern 3D visualization capabilities for NWP analysis.

Scallop ice shape characteristics of swept wing based on large-scale icing wind tunnel experiment

Scallop ice is a special phenomenon that occurs during swept wing aircraft passing through icing clouds. It poses a great challenge for the icing safety assessment that the complex scallop ice shape feature and its mechanism are still unclear. In this work, a large-scale icing wind tunnel experiment of swept wing designed by NACA0012 airfoil is conducted in the Icing Wind Tunnel of China Aerodynamics Research and Development Center. The detailed three-dimensional ice shapes under 0°, 15°, 30° and 45° swept angles are obtained by laser scanning technology. The experimental results show that with the swept angle increasing from 0° to 45°, the 2D double ice horn structures show certain spanwise variation, and finally transform into complete scallop ice with ice thickness greatly enhanced in the stagnation line region. The empirical mode decomposition of the spanwise ice curve captures the high-frequency fluctuation on the scallop ice caused by the small-scale roughness element, while the trend with low frequency is not obvious. Based on the experimental data, a new complete scallop ice geometric model, named 5Points-5Lines-2Arcs (5P-5L-2A) model, is proposed, which can provide important basis for the quantitative description of complex scallop ice shape.

Investigating an indirect aviation effect on mid-latitude cirrus clouds – linking lidar-derived optical properties to in situ measurements

Abstract. Aviation has a large impact on the Earth's atmosphere and climate by various processes. Line-shaped contrails and contrail cirrus clouds lead to changes in the natural cirrus cloud cover and have a major contribution to the effective radiative forcing from aviation. In addition, aviation-induced aerosols might also change the microphysical properties and optical properties of naturally formed cirrus clouds. Latter aerosol–cloud interactions show large differences in the resulting effective radiative forcing, and our understanding on how aviation-induced aerosols affect cirrus cloud properties is still poor. Up to now, observations of this aviation-induced aerosol effect have been rare. In this study, we use combined airborne lidar and in situ ice cloud measurements to investigate differences in the microphysical and optical properties of naturally formed cirrus clouds, which formed in regions that are highly affected by aviation-induced aerosol emissions and, of those, which formed in regions rather unaffected by aviation. Urbanek et al. (2018) showed that those cirrus clouds, which are more affected by aviation-induced soot emission, are characterized by larger values of the particle linear depolarization ratio (PLDR). In this follow-on study we relate collocated lidar measurements performed aboard HALO during the ML-CIRRUS mission of the particle linear depolarization ratio with in situ cloud probe measurements of the number concentration and effective diameter of the ice particles. In situ measurements for both cloud types (high-PLDR-mode – aviation-affected – and low-PLDR-mode – pristine – cirrus) can be reliably compared in a temperature range between 210 and 215 K. Within this temperature range we find that high-PLDR-mode cirrus clouds tend to show larger effective ice particle diameters with a median value of 61.4 compared to 50.7 µm for low-PLDR-mode pristine cirrus clouds. Larger effective ice particles in aviation-influenced (high-PLDR-mode) cirrus are connected to lower ice particle number concentration with a median value of 0.05 compared to 0.11 cm−3 (low-PLDR-mode), which evolved in more pristine regions with only little impact from aviation. We suspect that a suppression of homogeneous ice formation by the heterogeneously freezing soot aerosol particles included in the areas affected by air traffic is the cause of the reduced ice crystal concentrations.

On the Formation of Vinylamine (C2H3NH2) in Interstellar Ice Analogs

Amines—organic molecules carrying the –NH2 moiety—have been recognized as a vital intermediate in the formation of prebiotic molecules such as amino acids and nucleobases. Here we report the formation of vinylamine (C2H3NH2), which was recently detected toward G+0.693–0.027, in interstellar ice analogs composed of acetylene (C2H2) and ammonia (NH3) exposed to energetic electrons. Our experiments mimic cascades of secondary electrons in the tracks of galactic cosmic rays impinging on interstellar ice in molecular clouds. Tunable photoionization reflectron time-of-flight mass spectrometry (PI–Re-TOF–MS), along with isomer-specific assignments, reveals the production of vinylamine (C2H3NH2). Quantum chemical computations suggest that both a radical–radical recombination of the amino (NH2) with the vinyl (C2H3) radical and a one-step concerted route are feasible pathways to vinylamine (C2H3NH2). The results present the first documented route to form vinylamine in interstellar ice analogs. This unsaturated amine, which is isovalent to vinylalcohol (C2H3OH), could be a key precursor for the abiotic synthesis of prebiotic molecules such as amino acids and nucleobases, with implications for the origins-of-life theme.

The snow‐shadow effect of Sado Island on Niigata City and the coastal plain

AbstractJapan's Hokuriku region, near the Sea of Japan, typically experiences heavy snowfall; however, Niigata City, the largest city on the Sea of Japan side, experiences lower levels of snowfall than neighbouring cities. This study investigates the snow‐shadow effect of Sado Island on snowfall in Niigata City, located 45 km away leeward. Statistical analysis of long‐term radar data for 10 winters showed that snow‐shadow effects in the Niigata plain occurred in 151 (80%) of the 188 cases, during which a strong approaching wind reached the island. The location of this snow‐shadow effect was always downwind of Sado Island and depended on the wind direction. Numerical experiments using the Weather Research and Forecasting model predicted that snowfall over the Niigata Plain would be lighter with the island than without it. Additionally, the snow‐shadow effect occurs in areas more than 150 km downwind. The experiments showed that Sado Island reduces heat fluxes from the sea surface by weakening leeward winds. At the same time, the horizontal wind convergence downwind is weakened. Meanwhile, the orographic snowfall over Sado Island reduces the amount of water vapour, cloud water and cloud ice over the leeward sea. Therefore, Sado Island prevents cloud lines from redeveloping over the leeward sea and can further reduce snowfall over the leeward plain, including in Niigata City.

Heterogeneous Ice Nucleation in Model Crystalline Porous Organic Polymers: Influence of Pore Size on Immersion Freezing.

Heterogeneous ice nucleation activity is affected by aerosol particle composition, crystallinity, pore size, and surface area. However, these surface properties are not well understood, regarding how they act to promote ice nucleation and growth to form ice clouds. Therefore, synthesized materials for which surface properties can be tuned were examined in immersion freezing mode in this study. To establish the relationship between particle surface properties and efficiency of ice nucleation, materials, here, covalent organic frameworks (COFs), with different pore diameters and degrees of crystallinity (ordering), were characterized. Results showed that out of all the highly crystalline COFs, the sample with a pore diameter between 2 and 3 nm exhibited the most efficient ice nucleation activity. We posit that the highly crystalline structures with ordered pores have an optimal pore diameter where the ice nucleation activity is maximized and that the not highly crystalline structures with nonordered pores have more sites for ice nucleation. The results were compared and discussed in the context of other synthesized porous particle systems. Such studies give insight into how material features impact ice nucleation activity.

Oblique laser transmission and scattering characteristics of multilayer ice-water mixed clouds based on the successive scattering method

Clouds are widely distributed in the atmosphere, which is an important factor affecting the laser engineering application. In the paper, we developed a scattering transmission model of laser light in multilayer ice-water mixed clouds for applications in laser communication, laser detection, and laser weapons. Based on the successive scattering method, the direct transmission and first-order scattering of the laser between an aircraft and a target are numerically calculated in different cloud structures. The effects of the vertical structure of the clouds and the position of the aircraft and the target on the laser scattering are analyzed. The results show that the direct transmission can always have minimal and maximal values at the bottom and top of the clouds, respectively, while the peak of the first-order scattering appears near the top of the clouds. Compared to ice clouds, water clouds will produce a huge attenuation of the laser transmission. Our results can provide theoretical guidance for engineering applications in the real cloud environment.

A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product

Abstract. ACM-CAP provides a synergistic best-estimate retrieval of all clouds, aerosols, and precipitation detected by the atmospheric lidar (ATLID), cloud-profiling radar (CPR), and multi-spectral imager (MSI) aboard EarthCARE (Earth Cloud Aerosol and Radiation Explorer). While synergistic retrievals are now mature in many contexts, ACM-CAP is unique in that it provides a unified retrieval of all hydrometeors and aerosols. The Cloud, Aerosol, and Precipitation from mulTiple Instruments using a VAriational TEchnique (CAPTIVATE) algorithm allows for a robust accounting of observational and retrieval errors and the contributions of passive and integrated measurements and for enforcing physical relationships between components (e.g. the conservation of precipitating mass flux through the melting layer). We apply ACM-CAP to EarthCARE scenes simulated from numerical weather model forecasts and evaluate the retrievals against “true” quantities from the numerical model. The retrievals are well-constrained by observations from active and passive instruments and overall closely resemble the bulk quantities (e.g. cloud water content, precipitation mass flux, and aerosol extinction) and microphysical properties (e.g. cloud effective radius and median volume diameter) from the model fields. The retrieval performs best where the active instruments have a strong and unambiguous signal, namely in ice clouds and snow, which is observed by both ATLID and CPR, and in light to moderate rain, where the CPR signal is strong. In precipitation, CPR's Doppler capability permits enhanced retrievals of snow particle density and raindrop size. In complex and layered scenes where ATLID is obscured, we have shown that making a simple assumption about the presence and vertical distribution of liquid cloud in rain and mixed-phase clouds allows improved assimilation of MSI solar radiances. In combination with a constraint on the CPR path-integrated attenuation from the ocean surface, this leads to improved retrievals of both liquid cloud and rain in midlatitude stratiform precipitation. In the heaviest precipitation, both active instruments are attenuated and dominated by multiple scattering; in these situations, ACM-CAP provides a seamless retrieval of cloud and precipitation but is subject to a high degree of uncertainty. ACM-CAP's aerosol retrieval is performed in hydrometeor-free parts of the atmosphere and constrained by ATLID and MSI solar radiances. While the aerosol optical depth is well-constrained in the test scenes, there is a high degree of noise in the profiles of extinction. The use of numerical models to simulate test scenes has helped to showcase the capabilities of the ACM-CAP clouds, aerosols, and precipitation product ahead of the launch of EarthCARE.

All-sky infrared radiance data assimilation of FY-4A AGRI with different physical parameterizations for the prediction of an extremely heavy rainfall event

The Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) allows for high-spatiotemporal-resolution observations of the local severe weather systems. The capabilities for assimilating the all-sky AGRI infrared radiances are explored with the WRF three-dimensional variational data assimilation system (WRF-3DVAR) to improve the forecast accuracy of an extremely heavy rainfall event over the Henan Province of China in this study. In particular, data assimilation experiments are conducted with different physical parameterization schemes, including microphysical schemes and cumulus parameterizations. The results show that the all-sky AGRI radiance data assimilation experiments based on the Purdue Lin microphysics scheme and the Kain–Fritsch cumulus scheme can lead to better forecasts of the rainfall intensity and location, respectively. Meanwhile, it is found that the analyzed cloud top temperature fits the observations better when cloudy radiances from the AGRI are assimilated using the Purdue Lin scheme. This finding suggests that proper physical processes could facilitate the effective use of AGRI cloud-affected observations. On the other hand, positive forecast impacts from assimilating the all-sky AGRI radiance data have been confirmed when compared to the experiments that assimilate only the clear-sky AGRI radiances or only conventional observations. The assimilation of the all-sky AGRI water vapor channel is conducive to humidifying the initial conditions in the middle and low troposphere with more realistic analysis increments of water vapor, cloud water, and cloud ice, resulting in improved intensity forecasts of the heavy rainfall system and better forecast skill scores.

Microphysical and thermodynamic phase analyses of Arctic low-level clouds measured above the sea ice and the open ocean in spring and summer

Abstract. Airborne in situ cloud measurements were carried out over the northern Fram Strait between Greenland and Svalbard in spring 2019 and summer 2020. In total, 811 min of low-level cloud observations were performed during 20 research flights above the sea ice and the open Arctic ocean with the Polar 5 research aircraft of the Alfred Wegener Institute. Here, we combine the comprehensive in situ cloud data to investigate the distributions of particle number concentration N, effective diameter Deff, and cloud water content CWC (liquid and ice) of Arctic clouds below 500 m altitude, measured at latitudes between 76 and 83∘ N. We developed a method to quantitatively derive the occurrence probability of their thermodynamic phase from the combination of microphysical cloud probe and Polar Nephelometer data. Finally, we assess changes in cloud microphysics and cloud phase related to ambient meteorological conditions in spring and summer and address effects of the sea ice and open-ocean surface conditions. We find median N from 0.2 to 51.7 cm−3 and about 2 orders of magnitude higher N for mainly liquid clouds in summer compared to ice and mixed-phase clouds measured in spring. A southerly flow from the sea ice in cold air outbreaks dominates cloud formation processes at temperatures mostly below −10 ∘C in spring, while northerly warm air intrusions favor the formation of liquid clouds at warmer temperatures in summer. Our results show slightly higher N in clouds over the sea ice compared to the open ocean, indicating enhanced cloud formation processes over the sea ice. The median CWC is higher in summer (0.16 g m−3) than in spring (0.06 g m−3), as this is dominated by the available atmospheric water content and the temperatures at cloud formation level. We find large differences in the particle sizes in spring and summer and an impact of the surface conditions, which modifies the heat and moisture fluxes in the boundary layer. By combining microphysical cloud data with thermodynamic phase information from the Polar Nephelometer, we find mixed-phase clouds to be the dominant thermodynamic cloud phase in spring, with a frequency of occurrence of 61 % over the sea ice and 66 % over the ocean. Pure ice clouds exist almost exclusively over the open ocean in spring, and in summer the cloud particles are most likely in the liquid water state. The comprehensive low-level cloud data set will help us to better understand the role of clouds and their thermodynamic phase in the Arctic radiation budget and to assess the performance of global climate models in a region of the world with the strongest anthropogenic climate change.

The Prediction of Supercooled Large Drops by a Microphysics and a Machine Learning Model for the ICICLE Field Campaign

Abstract The prediction of supercooled large drops (SLD) from the Thompson–Eidhammer (TE) microphysics scheme—run as part of the High-Resolution Rapid Refresh (HRRR) model—is evaluated with observations from the In-Cloud Icing and Large drop Experiment (ICICLE) field campaign. These observations are also used to train a random forest machine learning (ML) model, which is then used to predict SLD from several variables derived from HRRR model output. Results provide insight on the limitations and benefits of each model. Generally, the ML model results in an increase in the probability of detection (POD) and false alarm rate (FAR) of SLD compared to prediction from TE microphysics. Additionally, the POD of SLD increases with increasing forecast lead time for both models, likely since clouds and precipitation have more time to develop as forecast length increases. Since SLD take time to develop in TE microphysics and may be poorly represented in short-term (<3 h) forecasts, the ML model can provide improved short-term guidance on supercooled large-drop icing conditions. Results also show that TE microphysics predicts a frequency of SLD in cold (<−10°C) or high ice water content (IWC) environments that is too low compared to observations, whereas the ML model better captures the relative frequency of SLD in these environments.

Calibration Transfer Methodology for Cloud Radars Based on Ice Cloud Observations

Abstract This article presents a calibration transfer methodology that can be used between radars of the same or different frequency bands. This method enables the absolute calibration of a cloud radar by transferring it from another collocated instrument with known calibration, by simultaneously measuring vertical ice cloud reflectivity profiles. The advantage is that the added uncertainty in the newly calibrated instrument can converge to the magnitude of the reference instrument calibration. This is achieved by carefully selecting comparable data, including the identification of the reflectivity range that avoids the disparities introduced by differences in sensitivity or scattering regime. The result is a correction coefficient used to compensate measurement bias in the uncalibrated instrument. Calibration transfer uncertainty can be reduced by increasing the number of sampling periods. The methodology was applied between collocated W-band radars deployed during the ICE-GENESIS campaign (Switzerland 2020/21). A difference of 2.2 dB was found in their reflectivity measurements, with an uncertainty of 0.7 dB. The calibration transfer was also applied to radars of different frequency, an X-band radar with unknown calibration and a W-band radar with manufacturer calibration; the difference found was −16.7 dB with an uncertainty of 1.2 dB. The method was validated through closure, by transferring calibration between three different radars in two different case studies. For the first case, involving three W-band radars, the bias found was of 0.2 dB. In the second case, involving two W-band and one X-band radar, the bias found was of 0.3 dB. These results imply that the biases introduced by performing the calibration transfer with this method are negligible.

In-orbit cross-calibration of millimeter conically scanning spaceborne radars

Abstract. The planned and potential introduction in global satellite observing systems of conically scanning Ka- and W-band atmospheric radars (e.g., the radars in the Tomorrow.IO constellation, https://www.tomorrow.io/space/, last access: 1 June 2022, and the Wivern (WInd VElocity Radar Nephoscope) radar, https://www.wivern.polito.it, last access: 1 July 2022) calls for the development of methodologies for calibrating and cross-calibrating these systems. Traditional calibration techniques pointing at the sea surface at about 11∘ incidence angle are in fact unfeasible for such fast rotating systems. This study proposes a cross-calibration method for conically scanning spaceborne radars based on ice cloud reflectivity probability distribution functions (PDFs) provided by reference radars like the Global Precipitation Measurement (GPM) Ka-band radar or the W-band radars planned for the ESA-JAXA EarthCARE or for the NASA Atmosphere Observing System missions. In order to establish the accuracy of the methodology, radar antenna boresight positions are propagated based on four configurations of expected satellite orbits so that the ground-track intersections can be calculated for different intersection criteria, defined by cross-over instrument footprints within a certain time and a given distance. The climatology of the calibrating clouds, derived from the W-band CloudSat and Ka-band GPM reflectivity records, can be used to compute the number and the spatial distribution of calibration points. Finally, the mean number of days required to achieve a given calibration accuracy is computed based on the number of calibration points needed to distinguish a biased reflectivity PDF from the sampling-induced noisiness of the reflectivity PDF itself. Findings demonstrate that it will be possible to cross-calibrate, within 1 dB, a Ka-band (W-band) conically scanning radar like that envisaged for the Tomorrow.io constellation (Wivern mission) every few days (a week). Such uncertainties are generally meeting the mission requirements and the standards currently achieved with absolute calibration accuracies.

How does cloud-radiative heating over the North Atlantic change with grid spacing, convective parameterization, and microphysics scheme in ICON version 2.1.00?

Abstract. Cloud-radiative heating (CRH) within the atmosphere and its changes with warming affect the large-scale atmospheric winds in a myriad of ways, such that reliable predictions and projections of circulation require reliable calculations of CRH. In order to assess the sensitivities of upper-tropospheric midlatitude CRH to model settings, we perform a series of simulations with the ICOsahedral Nonhydrostatic Model (ICON) over the North Atlantic using six different grid spacings, parameterized and explicit convection, and one- versus two-moment cloud microphysics. While sensitivity to grid spacing is limited, CRH profiles change dramatically with microphysics and convection schemes. These dependencies are interpreted via decomposition into cloud classes and examination of cloud properties and cloud-controlling factors within these different classes. We trace the model dependencies back to differences in the mass mixing ratios and number concentrations of cloud ice and snow, as well as vertical velocities. Which frozen species are radiatively active and the broadening of the vertical velocity distribution with explicit convection turn out to be crucial factors in altering the modeled CRH profiles.

Investigation of Microstructure and Density of Atmospheric Ice Formed by High-Wind-Speed In-Cloud Icing

In-cloud icing occurred on cables, wind turbines, and aircraft wings and may cause power transmission paralysis, energy dissipation, and unsafe flight. The study of atmospheric ice is crucial to facilitate the development of in-cloud icing prediction/detection and anti-/de-icing systems. Herein, atmospheric ice formed by high-wind-speed, in-cloud icing was obtained and reserved during icing tests in the 3 m × 2 m icing wind tunnel located at CARDC. Microstructures of atmospheric ice formed by high-wind-speed, in-cloud icing were observed and analysed using the microscopic observation method. A better description was established to explore the influence of the icing environment on ice microstructures, such as the size and shape of air bubbles and the boundaries of ice grains. Furthermore, an accurate density measurement was developed to allow a better practical density expression to consider the characteristics of the impacted surface and the effect of the flow field.

Cloudiness Parameterization for Use in Atmospheric Models: A Review and New Perspectives

In atmospheric models, the representation of cloudiness is a direct linkage between the moisture amount and associated radiative forcing. This paper begins by providing a review of the parameterization of cloudiness that has been used for numerical weather predictions and climate studies. The inherent uncertainties in representing a partial fraction of clouds for radiation feedback and in evaluating it against the corresponding observations are focused. It is also stated that the major hydrometeor categories of water substances such as cloud ice and water that are responsible for cloud cover are readily available in modern weather and climate models. Inconsistencies in cloud cover and hydrometeors, even in the case of the prognostic method, are discussed. The compensating effect of cloudiness for radiative feedback is found to imply that the condensed water amount itself is more influential on the radiative forcing, rather than the accuracy of the cloudiness. Based on the above perspectives, an alternative diagnostic parameterization method is proposed, utilizing a monotonic relation between the cloud water amounts and cloudiness that are obtained from aircraft and satellite observations. The basic premise of this approach lies in the accuracy of the water substance in the models, indicating that future efforts need to be given to improvements in physical processes concerning hydrometeor properties for the accurate representation of cloud radiative feedback.