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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

In-Orbit Performance of the MWRI Scanning Mechanisms

Scanning Equipment supporting the Millimeter Wave Radiometer Instrument (MWRI) are flying in a sunsynchronized orbit of 850-km altitude with an inclination of 98.8 deg on the FY-3 meteorological satellite (FY = Feng Yun, Wind and Cloud). MWRI is a linearly polarized, ten-channel passive Radiometer; it measures precipitation and water clouds, sea ice, snow/water equivalent, drought and flood index, land temperature and soil moisture. Following the FY3-A, the FY3-B Satellite was launched in autumn 2010. Since that time, the Scanning Equipment was continuously operated. During the last three and a half years in orbit, the Scanning Mechanism has executed about 65 million revolutions, while the Scan Compensation Mechanism (SCM) - used for momentum compensation - has already successfully executed more than one billion revolutions. During the commissioning phase of the instrument and during the first operation phase, random torque spikes, which manifested themselves as a motor current increase, were observed in the Scan Drive Mechanism, whereas the Scan Compensation drive operated nominally from the beginning. The result of the root cause investigations performed in order to isolate the issue, and the consequences for the follow-on MWRI equipment which was successfully launched by end of September 2013 (now flying on the FY 3-C Spacecraft), are discussed.

Schmid, Manfred↗
NASA NTRS2015

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Xu, Kuan-Man↗
NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗
NASA NTRS1981

Precipitation growth in convective clouds

Analytical solutions to the equations of both the growth and motion of hailstones in updrafts and of cloud water contents which vary linearly with height were used to investigate hail growth in a model cloud. A strong correlation was found between the hail embyro starting position and its trajectory and final size. A simple model of the evolution of particle size distribution by coalescence and spontaneous and binary disintegrations was formulated. Solutions for the mean mass of the distribution and the equilibrium size distribution were obtained for the case of constant collection kernel and disintegration parameters. Azimuthal scans of Doppler velocity at a number of elevation angles were used to calculate high resolution vertical profiles of particle speed and horizontal divergence (the vertical air velocity) in a region of widespread precipitation trailing a mid-latitude squall line.

Srivastava, R. C.↗
NASA NTRS1996

Dynamics of the Impacts

The SL9 impacts are best known by their plumes, several of which were imaged towering 3000 km above Jupiter's limb. The heat released when they fen back on the atmosphere produced the famous infrared main events. The reentry shock was observed directly in CO emission and indirectly through thermally glowing dust. The relatively low color temperature of the latter implies that most of the energy released on reentry was radiated. If so, the R impact released some 3 x 10(exp 26) ergs, and the larger L, K, and G impacts as much as 3 x 10(exp 27) ergs. These estimates agree well with impact energies deduced from tidal disruption computations. The duration of the infrared events measures time aloft and hence provides a second measure of plume height. These indicate that plume height was only weakly dependent on impact energy. Evidently all the plumes were launched at roughly 10-13 km/s. Using a semi-analytic model for the deceleration, disintegration, and destruction of intruding bodies by an ever-vigilant atmosphere, we find that similar plume heights is a direct consequence of smaller impactors exploding at higher altitudes, in such a way that the different explosions were geometrically similar. We then compare the predictions of our model to the Venerian cratering record, which provides a good statistical test of impact deceleration by a thick atmosphere. Chemistry should have provided an independent measure of explosion altitude: abundant shock-generated CS, CS2 and HCN indicates a source in dry jovian air, above the putative water clouds. However, the Galileo Probe results seem to imply that we should expect no more. Observed water and S2 are consistent with a somewhat oxidized gas (presumably the comet itself), but the absence of SO2 and CO2 shows that conditions were neither too oxidizing nor the shocks too hot.

Zahnle, Kevin↗
NASA NTRS2002

Monte Carlo Radiative Transfer Modeling of Lightning Observed in Galileo Images of Jupiter

We study lightning on Jupiter and the clouds illuminated by the lightning using images taken by the Galileo orbiter. The Galileo images have a resolution of 25 km/pixel and axe able to resolve the shape of the single lightning spots in the images, which have full widths at half the maximum intensity in the range of 90-160 km. We compare the measured lightning flash images with simulated images produced by our ED Monte Carlo light-scattering model. The model calculates Monte Carlo scattering of photons in a ED opacity distribution. During each scattering event, light is partially absorbed. The new direction of the photon after scattering is chosen according to a Henyey-Greenstein phase function. An image from each direction is produced by accumulating photons emerging from the cloud in a small range (bins) of emission angles. Lightning bolts are modeled either as points or vertical lines. Our results suggest that some of the observed scattering patterns axe produced in a 3-D cloud rather than in a plane-parallel cloud layer. Lightning is estimated to occur at least as deep as the bottom of the expected water cloud. For the six cases studied, we find that the clouds above the lightning are optically thick (tau > 5). Jovian flashes are more regular and circular than the largest terrestrial flashes observed from space. On Jupiter there is nothing equivalent to the 30-40-km horizontal flashes which axe seen on Earth.

Dyudine, U. A.↗
NASA NTRS2019

Advances in Neural Network Detection and Retrieval of Multilayer Clouds for CERES Using Multispectral Satellite Data

An artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels, the retrieved total cloud visible optical depth, and vertical humidity profiles is trained to detect multilayer (ML) ice-over-water cloud systems as identified by matched CloudSat and CALIPSO (CC) data. The multilayer ANN, or MLANN, algorithm is also trained to retrieve the optical depth and the top and base heights of the upper-layer ice clouds in ML systems. The trained MLANN was applied to independent MODIS data resulting in a combined ML and single layer hit rate of 80% (77%) for nonpolar regions during the day (night). The results are more accurate than currently available methods and the previous version of the MLANN. Upper-layer cloud top and base heights are accurate to ±1.2 km and ±1.6 km, respectively, while the uncertainty in optical depth is ±0.457 and ±0.556 during day and night, respectively. Areas of further improvement and development are identified and will be addressed in future versions of the MLANN.

CERES↗
NASA NTRS2014

Changes to Saturn's Zonal-Mean Tropospheric Thermal Structure After the 2010-2011 Northern Hemisphere Storm

We use far-infrared (20-200 micrometers) data from the Composite Infrared Spectrometer on the Cassini spacecraft to determine the zonal-mean temperature and hydrogen para-fraction in Saturn's upper troposphere from observations taken before and after the large northern hemisphere storm in 2010-2011. During the storm, zonal mean temperatures in the latitude band between approximately 25 deg N and 45 deg N (planetographic latitude) increased by about 3 K, while the zonal mean hydrogen para-fraction decreased by about 0.04 over the same latitudes, at pressures greater than about 300 mbar. These changes occurred over the same latitude range as the disturbed cloud band seen in visible images. The observations are consistent with low para-fraction gas being brought up from the level of the water cloud by the strong convective plume associated with the storm, while being heated by condensation of water vapor, and then advected zonally by the winds near the plume tops in the upper troposphere.

Saturn↗
NASA NTRS2001

Effect of Aerosols on Cloud Field with Satellite-Derived Data and GCM Simulation

Numerical experiment was performed using an general circulation model (GCM) including aerosol indirect effect into water cloud and the simulated global distribution of cloud droplet radii was compared with the global distribution of cloud effective radii retrieved from Advanced Very High Resolution Radiometer (AVHRR). Comparisons of GCM calculation with AVHRR retrieval showed that our GCM generally can simulate the global characteristics of cloud droplet radii such as a land-sea contrast associated with difference of aerosol abundance and coastal region feature due to aerosol injection from adjacent continental area. AVHRR retrieval and GCM simulation, however, are turned out to show disagreement over tropical region. AVHRR retrieval may tend to overestimate droplet radii due to the contamination of signal by drizzles and ice particles, whereas our GCM does not treat aerosol indirect effect in deep convective clouds predominant over tropics. Over equatorial central Pacific, where satellite retrieval may suffer from statistical biases, satellite retrieval and GCM simulation are also found to be different. Keywords: aerosol indirect effect

Suzuki, Kentaroh↗
NASA NTRS1999

Vertical Photon Transport in Cloud Remote Sensing Problems

Photon transport in plane-parallel, vertically inhomogeneous clouds is investigated and applied to cloud remote sensing techniques that use solar reflectance or transmittance measurements for retrieving droplet effective radius. Transport is couched in terms of weighting functions which approximate the relative contribution of individual layers to the overall retrieval. Two vertical weightings are investigated, including one based on the average number of scatterings encountered by reflected and transmitted photons in any given layer. A simpler vertical weighting based on the maximum penetration of reflected photons proves useful for solar reflectance measurements. These weighting functions are highly dependent on droplet absorption and solar/viewing geometry. A superposition technique, using adding/doubling radiative transfer procedures, is derived to accurately determine both weightings, avoiding time consuming Monte Carlo methods. Superposition calculations are made for a variety of geometries and cloud models, and selected results are compared with Monte Carlo calculations. Effective radius retrievals from modeled vertically inhomogeneous liquid water clouds are then made using the standard near-infrared bands, and compared with size estimates based on the proposed weighting functions. Agreement between the two methods is generally within several tenths of a micrometer, much better than expected retrieval accuracy. Though the emphasis is on photon transport in clouds, the derived weightings can be applied to any multiple scattering plane-parallel radiative transfer problem, including arbitrary combinations of cloud, aerosol, and gas layers.

Platnick, S.↗
NASA NTRS2006

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Sun-Mack, Sunny↗
NASA NTRS1984

Satellite observations of a monsoon depression

The exploration of a monsoon depression over Burma and the Bay of Bengal is discussed. Aircraft and satellite data were examined, with an emphasis on the Microwave Sounding Unit (MSU) aboard TIROS-N and the Scanning Multichannel Microwave Radiometer (SMMR) aboard Nimbus-7. The structure of the monsoon depression was found to be dominated by cumulus convection. The only systematic large scale behavior discerned was a propagation of the depression westward, and diurnal migration of contours of brightness temperature. These contours in the middle troposphere showed a gradient toward the north with the patterns migrating northward at night. From SMMR and dropwindsonde data, water vapor contents were found to be near 65 mm, increasing to more than 70 mm in the northeast Bay of Bengal. Cloud water contents reached about three mm. Rainfall rates exceeding 5.7 mm/h occurred over a small part of the storm area, while mean rainfall rates in areas of order 20,000 sq km reached approximately 0.5 mm/h. Measured MSU brightness temperatures were reconciled very well with dropwindsonde data and with airborne in situ observations of clouds (by photography) and hydrometeors (by radar). Diffuse scattering was determined to be important in computing brightness temperature.

Warner, C.↗
DOE OSTI2022

Comparison of Lagrangian Superdroplet and Eulerian Double-Moment Spectral Microphysics Schemes in Large-Eddy Simulations of an Isolated Cumulus Congestus Cloud

Abstract Advanced microphysics schemes (such as Eulerian bin and Lagrangian superdroplet) are becoming standard tools for cloud physics research and parameterization development. This study compares a double-moment bin scheme and a Lagrangian superdroplet scheme via large-eddy simulations of nonprecipitating and precipitating cumulus congestus clouds. Cloud water mixing ratio in the bin simulations is reduced compared to the Lagrangian simulations in the upper part of the cloud, likely from numerical diffusion, which is absent in the Lagrangian approach. Greater diffusion in the bin simulations is compensated by more secondary droplet activation (activation above cloud base), leading to similar or somewhat higher droplet number concentrations and smaller mean droplet radius than the Lagrangian simulations for the nonprecipitating case. The bin scheme also produces a significantly larger standard deviation of droplet radius than the superdroplet method, likely due to diffusion associated with the vertical advection of bin variables. However, the spectral width in the bin simulations is insensitive to the grid spacing between 50 and 100 m, suggesting other mechanisms may be compensating for diffusion as the grid spacing is modified. For the precipitating case, larger spectral width in the bin simulations initiates rain earlier and enhances rain development in a positive feedback loop. However, with time, rain formation in the superdroplet simulations catches up to the bin simulations. Offline calculations using the same drop size distributions in both schemes show that the different numerical methods for treating collision–coalescence also contribute to differences in rain formation. The stochastic collision–coalescence in the superdroplet method introduces more variability in drop growth for a given rain mixing ratio.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Advances in Raman Lidar Measurements of Water Vapor, Cirrus Clouds and Carbon Dioxide

Narrow-band interference filters with improved transmission in the ultraviolet have been developed under NASA-funded research and used in the Raman Airborne Spectroscopic Lidar (RASL) in ground- based, upward-looking tests. RASL is an airborne Raman Lidar system designed to measure water vapor mixing ratio, and aerosol backscatter/extinction/depolarization. It also possesses the capability to make experimental measurements of cloud liquid water and carbon dioxide. It is being prepared for first flight tests during the summer of 2006. With the newly developed filters installed in RASL, measurements were made of atmospheric water vapor, cirrus cloud optical properties and carbon dioxide that improve upon any previously demonstrated using Raman lidar. Daytime boundary layer profiling of water vapor mixing ratio is performed with less than 5% random error using temporal and spatial resolution of 2-minutes and 60 - 210, respectively. Daytime cirrus cloud optical depth and extinction- to-backscatter ratio measurements are made using 1-minute average. Sufficient signal strength is demonstrated to permit the simultaneous profiling of carbon dioxide and water vapor mixing ratio into the free troposphere during the nighttime. Downward-looking from an airborne RASL should possess the same measurement statistics with approximately a factor of 5 - 10 decrease in averaging time. A description of the technology improvements are provided followed by examples of the improved Raman lidar measurements.

Whiteman, David N.↗
NASA NTRS1990

Dependence of marine stratocumulus reflectivities on liquid water paths

Simple parameterizations that relate cloud liquid water content to cloud reflectivity are often used in general circulation climate models to calculate the effect of clouds in the earth's energy budget. Such parameterizations have been developed by Stephens (1978) and by Slingo and Schrecker (1982) and others. Here researchers seek to verify the parametric relationship through the use of simultaneous observations of cloud liquid water content and cloud reflectivity. The column amount of cloud liquid was measured using a microwave radiometer on San Nicolas Island following techniques described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of Advanced Very High Resolution Radiometer (AVHRR) imagery data (Coakley and Beckner, 1988). They present the dependence of the observed reflectivity on the observed liquid water path. They also compare this empirical relationship with that proposed by Stephens (1978). Researchers found that by taking clouds to be isotropic reflectors, the observed reflectivities and observed column amounts of cloud liquid water are related in a manner that is consistent with simple parameterizations often used in general circulation climate models to determine the effect of clouds on the earth's radiation budget. Attempts to use the results of radiative transfer calculations to correct for the anisotropy of the AVHRR derived reflectivities resulted in a greater scatter of the points about the relationship expected between liquid water path and reflectivity. The anisotropy of the observed reflectivities proved to be small, much smaller than indicated by theory. To critically assess parameterizations, more simultaneous observations of cloud liquid water and cloud reflectivities and better calibration of the AVHRR sensors are needed.

Coakley, James A., Jr.↗
NASA NTRS2004

NASA/GSFC Scanning Raman Lidar Measurements of Water Vapor and Clouds During IHOP

The NASA/GSFC Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP) that occurred in May and June, 2002 in the midwestern part of the U.S. The SRL acquired measurements of water vapor, aerosols, cloud liquid and ice water, and temperature for more than 200 hours during IHOP. Here we report on the SRL water vapor and cirrus cloud measurements with particular emphasis being given to the measurements of June 19-20, 2002, which are motivating cirrus cloud model comparison studies.

Whiteman, David N.↗
DOE OSTI2022

Cloud Morphology Evolution in Arctic Cold‐Air Outbreak: Two Cases During COMBLE Period

Abstract Cloud feedbacks play an important role in Arctic warming. Cloud morphology, for example, cloud size and spatial distributions, is among key factors that directly impact their radiative effects. In this work, we use two cases observed during the Cold‐air Outbreak (CAO) in the Marine Boundary Layer Experiment (COMBLE) to study the evolution of cloud size distributions as an air mass is advected from the Arctic over a comparatively warm ocean and cloud mesoscale organization changes from rolls to cells. Cloud objects are identified from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance images through an object segmentation procedure and roll breakup is identified by homogeneities in cloud water path (CWP). Roll breakup is found to be accompanied by a local minimum in wind shear and local maxima in cloud size and marine cold air outbreak index. The mean cloud horizontal aspect ratio has weak fetch dependency and is around 2 in roll, transition, and cell regimes. Regardless of distance from the ice edge, smaller clouds (<10 km 2 ) dominate the population number but not cloud cover. Cloud size distributions show bimodality in transition and cell regimes. For clouds with comparable sizes, mean nearest neighbor distances normalized by equivalent cloud radius converge to a single value for all regimes and for all but the smallest clouds, suggesting that clouds of comparable sizes in CAOs are separated by distance proportional to their sizes. The presented statistical results pave the way to evaluating model simulated cloud organizations during CAO events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Airborne Observations of Particle Density in High Ice Water Content (HWC) Cloud Systems

A series of airborne field campaigns has been conducted since 2014 to measure the microphysical properties of high ice-water content (HIWC) clouds in maritime mesoscale convective systems (MCS) and tropical storms. Two of these, the HIWC RADAR-2 campaign (2018) targeting cloud systems in the Gulf of Mexico and Pacific Ocean, and the HIWC-2022 campaign targeting cloud systems in the Gulf of Mexico, Caribbean Sea, and Atlantic Ocean, have been analyzed to investigate graupel encounters at typical jet aircraft cruise altitudes. In-situ cloud observations from these two campaigns confirmed results from the prior studies, indicating that high concentrations of small ice particles exist in areas of HIWC. However, in the 2022 campaign, 90% of the cloud regions with ice water content (IWC) above 2.0 g/m3 also contained significant amounts of graupel and/or frozen drops. Using a mass-size parameterization that accounts for both small ice and larger high-density particles, we show that the mass distributions in cloud regions above 2.0 g/m3 are often strongly bimodal, with the small particle mode containing roughly half of the collective cloud mass, and the graupel mode containing the other half. In contrast, HIWC cloud passes in a 2018 tropical cyclone contained less relative graupel mass than the MCS cloud systems of 2018 and 2022. We present two different methods of estimating particle mass for mixed populations of small-ice and graupel particles, one using a hybrid two-class approach, and another using a single-class approach that takes both particle size and shape metrics into account. Derived IWC using these methods are compared to bulk IWC measurements collected during the campaigns. We also show the relative occurrence of graupel at various IWC levels and discuss the potential application of these results in evaluating density-aware microphysical schemes in cloud and weather models.

Aircraft Icing↗