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At least 451 records · Page 25

Design and Development of a Laboratory-Scale Ice Adhesion Testing Device

When an aircraft traverses through clouds containing supercooled water droplets, in-flight icing can occur that negatively affects vehicle performance by increasing weight and drag leading to loss of lift. Super-cooled water droplets present in clouds that impact vehicle surfaces can lead to inflight icing any time during the year.1 Most events occur at temperatures ranging from 0 to -20degC. Ice generated on the aircraft can vary between clear/glaze, rime, and mixed (Fig. 1) depending on air temperature (-5 to -20degC), liquid water content (0.3-0.6 g/m3), and droplet size (median volumetric diameter of 15-40 μm). Current strategies to remove ice are based on active technologies such as pneumatic boots, heated surfaces, and deicing agents (i.e., ethylene- and propylene-based glycols). The latter have potential environmental concerns. A passive approach to mitigate accreting ice that is actively being investigated are protective coatings. An ice mitigating coating could potentially be used as a stand-alone material, but more likely in combination with an active approach. In the latter scenario, potential reduction in power consumption by the active approach may be realized. To determine the ice adhesion strength of impact ice that is representative of the aircraft environment is not a trivial matter. Test methods utilizing slowly formed ice (i.e., freezer ice) do not accurately simulate this environment. Likewise, some testing methodologies involve sample relocation from the icing environment to the test chamber that can result in thermal shock to the sample, thus affecting the results. The Adverse Environment Rotor Test Stand (AERTS) located at Pennsylvania State University (PSU) has been demonstrated to simulate impact icing conditions within the icing envelope for the determination of ice adhesion shear strength (IASS) without removal/relocation of the sample.2 Due to the confidence in results obtained from AERTS, this instrument is in high demand and requires a significant amount of lead time and capital investment to obtain IASS results. As a solution for quickly and economically screening coatings in a controlled manner under impact icing conditions, a laboratory-scale ice adhesion test and dead blades were then removed from the rotor/blade assembly to obtain the final mass. The IASS of the live blade was determined from the difference in mass (before and after testing) of the live and dead blades, the ice shed area, and the rpm of the shed event. The same live blade sample was tested in triplicate at all three test temperatures. Surface roughness was determined using a Bruker Dektak XT Stylus Profilometer. Measurements were conducted using a 12.5 μm tip at a vertical range of 65.5 μm with an applied force of 3 mg. Data were collected over a 1.0 mm length at a resolution of 0.056 μm/point. Five single line scans at different locations were collected and processed using a two-point leveling subtraction. The resultant Ra (arithmetic roughness) and Rq (root mean square roughness) average values were calculated.

Smith, Joseph G., Jr.↗

Analysis of Experimental Ice Accretion Data and Assessment of a Thermodynamic Model During Ice Crystal Icing

This paper evaluates a thermodynamic ice crystal icing model that has been previously presented to describe the possible mechanisms of icing within the core of a turbofan jet engine. The model functions between two distinct ice accretions based on a surface energy balance: freeze-dominated icing and melt-dominated icing. Freeze-dominated icing occurs when liquid water (from melted ice crystals) freezes and accretes on a surface along with the existing ice of the impinging water and ice mass. This freeze-dominated icing is characterized as having strong adhesion to the surface. The amount of ice accretion is partially dictated by a freeze fraction, which is the fraction of impinging liquid water that freezes. Melt-dominated icing occurs as unmelted ice on a surface accumulates. This melt-dominated icing is characterized by weakly bonded surface adhesion. The amount of ice accumulation is partially dictated by a melt fraction, which is the fraction of impinging ice crystals that melts. Experimentally observed ice growth rates suggest that only a small fraction of the impinging ice remains on the surface, implying a mass loss mechanism such as splash, runback, bounce, or erosion. The fraction of mass loss must be determined in conjunction with the fraction of freezing liquid water or fraction of melting ice on an icing surface for a given ice growth rate. This mass loss parameter, however, along with the freeze fraction and melt fraction, are the only experimental parameters that are currently not measured directly. Using icing growth rates from ice crystal icing experiments, a methodology that has been previously proposed is used to determine these unknown parameters. This work takes ice accretion data from tests conducted by the National Aeronautics and Space Administration (NASA) at the Glenn Research Center in 2018 that examined the fundamental physics of ice crystal icing. This paper continues evaluation of the thermodynamic model from a previous effort, with additions to the model that account for sub-freezing temperatures that have been observed at the leading edge of the airfoil during icing. The predicted temperatures were generally in good agreement with measured temperatures. Other key findings include the total wet-bulb temperature being a good first order indicator of whether icing is freeze-dominated (sub-freezing values) or melt-dominated (above freezing). Maximum sticking efficiency values, the fraction of impinging mass that adheres to a surface, was calculated to be about 0.2, and retained this maximum value for a range of melt ratios (0.3 to 0.65 and possibly higher), which is defined as the ratio of liquid water content to total water content. Higher air velocities reduced the maximum sticking efficiency and shifted the icing regime to higher melt ratio values. Finally, the leading edge ice accretion angle was found to be related to ice growth (lower growth rates for smaller angles) and melt ratio (smaller melt ratios resulted in smaller angles, likely due to erosion effects).

Ice-Crystal Icing↗

Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia

This study explores the use of a support vector machine (SVM) as the observation operator within a passive microwave brightness temperature data assimilation framework (herein SVM-DA) to enhance the characterization of snow water equivalent (SWE) over High Mountain Asia (HMA). A series of synthetic twin experiments were conducted with the NASA Land Information System (LIS) at a number of locations across HMA. Overall, the SVM-DA framework is effective at improving SWE estimates (~70% reduction in RMSE relative to the Open Loop) for SWE depths less than 200 mm during dry snowpack conditions. The SVM-DA framework also improves SWE estimates in deep, wet snow (~45% reduction in RMSE) when snow liquid water is well estimated by the land surface model, but can lead to model degradation when snow liquid water estimates diverge from values used during SVM training. In particular, two key challenges of using the SVM-DA framework were observed over deep, wet snowpacks. First, variations in snow liquid water content dominate the brightness temperature spectral difference (TB) signal associated with emission from a wet snowpack, which can lead to abrupt changes in SWE during the analysis update. Second, the ensemble of SVM-based predictions can collapse (i.e., yield a near-zero standard deviation across the ensemble) when prior estimates of snow are outside the range of snow inputs used during the SVM training procedure. Such a scenario can lead to the presence of spurious error correlations between SWE and TB, and as a consequence, can result in degraded SWE estimates from the analysis update. These degraded analysis updates can be largely mitigated by applying rule-based approaches. For example, restricting the SWE update when the standard deviation of the predicted TB is greater than 0.05 K helps prevent the occurrence of filter divergence. Similarly, adding a thin layer (i.e., 5 mm) of SWE when the synthetic TB is larger than 5 K can improve SVM-DA performance in the presence of a precipitation dry bias. The study demonstrates that a carefully constructed SVM-DA framework cognizant of the inherent limitations of passive microwave-based SWE estimation holds promise for snow mass data assimilation.

Kwon, Yonghwan↗

An Investigation into the Grain Structure of Impact Ice

To design effective anti-icing and de-icing technology for aircraft, scientists and engineers must obtain a fundamental understanding of the microstructural characteristics of impact ice. This study investigates the effects of icing parameters, such as airspeed and liquid water content (LWC), on impact ice microstructure near the interface to a metal substrate. Ice samples were accreted in the NASA Glenn Icing Research Tunnel and tested in the NASA Revolutionary Icing Materials Evaluation Laboratory. A microtome was used to shave down the ice to a thickness of < 1 mm for examination under a microscope. Samples were imaged at multiple magnifications using bright field imaging. The average grain size was determined for each sample in accordance with ASTM standard methods, and relationships between airspeed, LWC, and grain size were identified. It was observed that the average grain area in a given cross-section was linearly related to the distance of the cross-section from the metal surface. Finally, the effects of annealing and sublimation on the microstructure were also explored. Results show significant variation in the grain structure, suggesting a means by which icing condition influences adhesion strength.

grain↗

The Effect of Stainless Steel 304 Surface Roughness on Ice Adhesion Shear Strength of Accreted Impact Ice

Aircraft in-flight icing is problematic due to the ad-verse effect on vehicle performance. It occurs when supercooled water droplets (SCWD) present in clouds, under the appropriate environmental conditions, col-lide with the aircraft surface resulting in accretion of ice (i.e., impact icing). Impact ice can range from clear/glaze to rime or a combination of the two (i.e., mixed) with the type determined by the air temperature (0 to -20°C), liquid water content (LWC, 0.3-0.6 g/cu.m), and droplet size [median volumetric diameter (MVD) of 15-40 µm] present during accretion.1 These impact icing events generally occur at temperatures ranging from 0 to -20°C. Below -20°C, ice crystals dominate the environment and typically do not adhere to the aircraft surface. A main difference between an impact icing occurrence and a slow growth icing (i.e., freezer ice) one is the speed of the icing event. Besides environmental conditions, ice adhesion strength (IAS) to a metallic substrate depends upon surface roughness. It is known that increasing surface roughness and decreasing temperature lead to in-creases in IAS.

Smith, Joseph G., Jr.↗

Icing Formation Strains on Airfoil Skin

Aircraft icing has long presented a safety hazard to the aerospace industry. One problem inherent to aircraft icing is predicting the adhesive properties of the ice-aircraft interface; values commonly reported span multiple orders of magnitude, making shedding prediction and surface evaluation difficult. An effort has been undertaken at the NASA Glenn Research Center to understand the cause of the scatter in the data. Geometry dependencies, variation in testing procedures, and residual stresses in ice samples have previously been identified as significant contributors to the problem. Residual stresses were singled out for this study, which investigated the strains at the leading edge of a Common Research Model (CRM) wind tunnel model in the NASA Glenn Icing Research Tunnel. Sprays were conducted at a particle size median volumetric diameter (MVD) of 20 µm, with liquid water contents (LWC) spanning from 0.4 to 3.0 g/m3. Total temperatures were varied between 0 and -25 °C, and test section velocity between 51 and 118 m/s. The leading edge was instrumented with custom strain gages, resistance temperature detectors (RTDs), optical fibers, and a pressure mat. Results indicate Δ strains, which were the difference between recorded strains and those predicted from isotropic thermal expansion of aluminum, below -400 µε with consistent patterns of strain across a wide variety of tunnel conditions. Isotropic, linear elastic finite element analysis (FEA) was conducted by varying the temperature of simplified airfoil and ice geometries, producing similar strains to those observed in testing. This allowed induced stresses to be predicted. Predicted stresses were above the expected tensile strength for ice, and suggest a source for previously observed cracking in tunnel ice.

Ice Adhesion↗

SLD Instrumentation in Icing Wind Tunnels – Investigation Overview

A collaborative effort to better understand cloud characterization probes in Supercooled Large Drop (SLD) conditions, as well the ability to simulate these conditions in several icing wind tunnels, was undertaken by NASA, NRCC, CIRA, ECCC, FAA and Met Analytics, Inc. Both drop sizing and liquid water content, LWC, were measured with various probes using current to emerging technologies. To ensure the best possible data quality from the newest probes, the probe manufacturers, SEA, Inc. and Artium, Inc. were invited to support testing and data analysis efforts. A common set of probes was identified to test in each of the three participating facilities: NRCC’s Altitude Icing Wind Tunnel, NASA’s Icing Research Tunnel and CIRA’s Icing Wind Tunnel. From the common set of probes, a subset were identified to use for comparison across the three facilities. These were the CDP-2 and 2D-S for drop sizing, and the Multi-wire for LWC. The LWC value was also checked by measuring the ice accretion thickness under hard rime conditions on a NACA-0012 airfoil. A common test matrix with sweeps in both LWC and median volume diameter, MVD, was developed. Each facility achieved these conditions as determined by their own calibration. The MVD ranged from 20 to at least 200 um, and LWC ranged from 0.5 to 3 g/m3. The comparison probes tested at common conditions in each facility were intended to allow for a direct comparison, and check of potential facility bias.

Icing Wind Tunnel↗

Arctic Cloud Response to a Perturbation in Sea Ice Concentration: The North Water Polynya

Surface and atmosphere energy exchanges play an important role in the Arctic climate system by influencing the lower atmospheric stability and humidity, sea ice melt and growth, and surface temperature. Sea ice significantly alters the character of these energy exchanges relative to ice-free ocean. The observed decline in Arctic sea ice since 1979 motivates questions related to the evolving role of surface-atmosphere coupling and potential feedbacks on the Arctic system. Due to the strong wintertime cloud warming effect, a critical question concerns the potential response of low clouds to Arctic sea ice decline. Previous approaches relied on interannual variability to investigate the cloud response to sea ice decline. However, the covariation between atmospheric conditions and sea ice makes it difficult to define an observational control when using interannual variability. To circumvent this difficulty, we exploit the recurring North Water polynya, an episodic opening in the northern Baffin Bay sea ice, as a natural laboratory to isolate the cloud response to a rapid, near-step perturbation in sea ice. Our results show that during the event, (a) low-cloud cover is 10%–33% larger over the polynya than nearby sea ice, (b) cloud liquid water content is up to 400% larger over the polynya than nearby sea ice, and (c) the surface cloud radiative effect is 18 W/sq. m larger over the polynya than nearby sea ice. Our results provide evidence that the low-cloud response during a polynya is a positive feedback lengthening the event.

Emily E. Monroe↗

Emission Factors and Evolution of SO2 Measured From Biomass Burning in Wildfires and Agricultural Fires

Fires emit sufficient sulfur to affect local and regional air quality and climate. This study analyzes SO2 emission factors and variability in smoke plumes from US wildfires and agricultural fires, as well as their relationship to sulfate and hydroxymethanesulfonate (HMS) formation. Observed SO2 emission factors for various fuel types show good agreement with the latest reviews of biomass burning emission factors, producing an emission factor range of 0.47–1.2 g SO2 kg^(−1) C. These emission factors vary with geographic location in a way that suggests that deposition of coal burning emissions and application of sulfur-containing fertilizers likely play a role in the larger observed values, which are primarily associated with agricultural burning. A 0-D box model generally reproduces the observed trends of SO2 and total sulfate (inorganic + organic) in aging wildfire plumes. In many cases, modeled HMS is consistent with the observed organosulfur concentrations. However, a comparison of observed organosulfur and modeled HMS suggests that multiple organosulfur compounds are likely responsible for the observations but that the chemistry of these compounds yields similar production and loss rates as that of HMS, resulting in good agreement with the modeled results. We provide suggestions for constraining the organosulfur compounds observed during these flights, and we show that the chemistry of HMS can allow organosulfur to act as an S(IV) reservoir under conditions of pH > 6 and liquid water content >10^(−7) g sm^(−3). This can facilitate long-range transport of sulfur emissions, resulting in increased SO2 and eventually sulfate in transported smoke.

Sulfur↗

Secondary Inorganic Aerosol Chemistry and Its Impact on Atmospheric Visibility Over an Ammonia-Rich Urban Area in Central Taiwan

This study investigated the hourly inorganic aerosol chemistry and its impact on atmospheric visibility over an urban area in Central Taiwan, by relying on measurements of aerosol light extinction, inorganic gases, and PM 2.5 water-soluble ions (WSIs), and simulations from a thermodynamic equilibrium model. On average, the sulfate (SO 4 2− ), nitrate (NO 3 − ), and ammonium (NH 4 + ) components (SNA) contributed ∼90% of WSI concentrations, which in turn made up about 50% of the PM 2.5 mass. During the entire observation period, PM 2.5 and SNA concentrations, aerosol pH, aerosol liquid water content (ALWC), and sulfur and nitrogen conversion ratios all increased with decreasing visibility. In particular, the NO 3 − contribution to PM 2.5 increased, whereas the SO 4 2− contribution decreased, with decreasing visibility. The diurnal variations of the above parameters indicate that the interaction and likely mutual promotion between NO 3 − and ALWC enhanced the hygroscopicity and aqueous-phase reactions conducive for NO 3 − formation, thus led to severely impaired visibility. The high relative humidity (RH) at the study area (average 70.7%) was a necessary but not sole factor leading to enhanced NO 3 − formation, which was more directly associated with elevated ALWC and aerosol pH. Simulations from the thermodynamic model depict that the inorganic aerosol system in the study area was characterized by fully neutralized SO 4 2− (i.e. a saturated factor in visibility reduction) and excess NH 4 + amidst a NH 3 -rich environment. As a result, PM 2.5 composition was most sensitive to gas-phase HNO 3 , and hence NOx, and relatively insensitive to NH 3 . Consequently, a reduction of NOx would result in instantaneous cuts of NO 3 − , PM 2.5 , and ALWC, and hence improved visibility. On the other hand, a substantial amount of NH 3 reduction (>70%) would be required to lower the aerosol pH, driving more than 50% of the particulate phase NO 3 − to the gas phase, thereby making NH 3 a limiting factor in shifting PM 2.5 composition.

aerosol chemistry↗

Additional Large-Drop Ice Accretion Test Results for a Large Scale Swept Wing Section from January 2022

In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m 3 . This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.

Ice accretion, Large drops, Wind tunnel↗

Ice Sheet Melt Water Profile Mapping Using Multi-frequency Microwave Radiometry

For understanding englacial hydrology and its impact on ice sheet mass balance, observations of the liquid water content (LWC) within the ice sheets are needed. Earlier studies have shown the complementary nature of multi-frequency microwave radiometer measurements to detect subsurface LWC distribution in addition to surface LWC, which is critical for understanding the seasonal melt dynamics of ice sheets. In this study, we used 1.4 GHz brightness temperature (TB) measurements from the NASA Soil Moisture Active Passive (SMAP) satellite, and 6.9, 10.7, 18.9, and 36.5 GHz TB measurements from the JAXA Global Change Observation Mission-Water Shizuku (GCOM-W) satellite to investigate the multi-frequency response at pan-Greenland scale. The melt indications derived at different frequencies show trends consistent with persistent seasonal subsurface melt water and delayed subsurface refreezing of the seasonal melt water. The result suggests that the seasonal subsurface persistent melt water occurrences that are not captured by the high-frequency retrievals are both temporally and spatially very significant.

Burgin, Mariko↗

Additional Large-Drop Ice Accretion Test Results for a Large Scale Swept Wing Section from January 2022

In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m3. This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.

Ice accretion↗

Sensitivity of the MAR Regional Climate Model Snowpack to the Parameterization of the Assimilation of Satellite-Derived Wet-Snow Masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production (+66.7 % on average, or +95 Gt), along with a small decrease in surface mass balance (SMB) (−4.5 % on average, or −20 Gt) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will enable the identification of potential issues in modeling near-surface snowpack processes, paving the way for more accurate simulations of snow processes in model projections.

regional climate models↗

Extending the Utility of Space-Borne Snow Water Equivalent Observations Over Vegetated Areas With Data Assimilation

Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24° x 37° domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 %, to within 1 %. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 %. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 %) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 % to within 1 %, and the Nash–Sutcliffe efficiency of runoff improved from −2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability.

Justin Pflug↗

Wind Tunnel PSD and MVD Characterization Using New 1D2D Optical Array Probes

This work explores characterization of the liquid clouds using a combination of a forward scattering probe and two Optical Array Probes. Current OAP probes provide particle shape, size, and number concentration from two-dimensional shadow images. However, past studies have shown that such images are subject to distortion when outside of the focal plane. This affects the retrieval of particle size distributions, particularly in the Supercooled Large Droplet size range. In this article, the use of a Droplet Measurement Technologies Cloud Droplet Probe and two new OAPs produced by Science Engineering Associates, is examined using wind tunnel data, to assess suitability for use in a wind tunnel calibration in SLD conditions. The new OAP probes exploit a flexible and simple grey scale imaging method to eliminate some present shortcomings of commonly used OAPs, and to reduce correction factors. Spinning disk measurements were used to specify probe depth of field, and average size errors. Composite spectra covering the nominal 2-3200 µm size range were formed by crossing over from the CDP to 1D2D-X at 48 µm, and then to the 1D2D-Y at about 400 µm. A good overlap was found at the crossover points without any artificial scaling. Composite spectra adequately closed the liquid water content distribution, and provided integrated LWCs within about 35% of the hot-wire LWCs used for tunnel calibration. This discrepancy was at least partially attributed to LWC underestimation by the hot-wire at high MVD. A model of probe performance was used to show an example of expected accuracy of ideal probes subject to the same OAP distortions and using the same mitigating procedures and corrections, predicting PSD Median Volume Diameter and integrated LWC errors of less than 10%.

Aircraft Icing↗

Estimating Drizzle Parameters by Aircraft Sampling

In-cloud supersaturation is calculated from aircraft derived measurements of the in-cloud vertical gradient of liquid water content, vertical velocity, the pt and 3 rd cloud droplet radius moments and a parameter related to the heat and mass transport during condensation and evaporation of cloud droplets. The aircraft data where taken during the VOCALS 2008 study in marine stratocumulus clouds off the coast of Chile. Approximately 16000 discrete samples, 2.5 meter in length, were used in the present analysis of in-cloud supersaturation and its variability, both of which are indicative of turbulent processes within the cloud and their significant impact on drizzle formation. Two additional drizzle parameters, the eddy persistence time and the variance of fluctuations in in-cloud droplet growth rate were also estimated from this data set. These results will help to constrain parameterizations of underlying turbulent microphysical processes of clouds and thereby advance the future development of warm cloud and precipitation models for climate simulation.

54 ENVIRONMENTAL SCIENCES↗