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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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49 records · Page 3

Clarifying remotely-retrieved precipitation of shallow marine clouds from the NSF/NCAR Gulfstream V

Precipitation is a key process within the shallow cloud lifecycle. The Cloud System Evolution in the Trades (CSET) campaign included the first deployment of a 94 GHz Doppler radar and 532 nm lidar. Despite a larger sampling volume, initial mean radar/lidar retrieved rain rates (Schwartz et al. 2019) based on the upward-pointing remote sensor datasets are systematically less than those measured by in-situ precipitation probes in the cumulus regime. Subsequent retrieval improvements produce rainrates that compare better to in-situ values, but still underestimate. Retrieved shallow cumulus drop sizes can remain too small and too few, with an overestimated shape parameter narrowing the raindrop size distribution too much. Three potential causes for the discrepancy are explored: the gamma functional fit to the dropsize distribution, attenuation by rain and cloud water, and an underaccounting of Mie dampening of the reflectivity. A truncated exponential fit may represent the dropsizes below a showering cumulus cloud more realistically, although further work would be needed to fully evaluate the impact of a different dropsize representation upon the retrieval. The rain attenuation is within the measurement uncertainty of the radar. Mie dampening of the reflectivity is shown to be significant, in contrast to previous stratocumulus campaigns with lighter rain rates, and may be difficult to constrain well with the remote measurements. An alternative approach combines an a priori determination of the dropsize distribution width based on the in-situ data with the mean radar Doppler velocity and reflectivity. This can produce realistic retrievals, although a more comprehensive assessment is needed to better characterize the retrieval errors.

54 ENVIRONMENTAL SCIENCES↗

Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar Data

Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter D m from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. Here, this estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

54 ENVIRONMENTAL SCIENCES↗

Graupel and Hail Identification Algorithm for the Dual-frequency Precipitation Radar (DPR) on the GPM Core Satellite

Precipitation consists of many types of hydrometeors, such as raindrops, ice crystals, graupel, and hail. Due to their impacts, graupel and hail (GH) have received particular attention in the literature. Global Precipitation Measurement (GPM) dual-frequency radar (DPR) has proved to be a very reliable system for global precipitation retrievals. This paper aims to develop a GH identification algorithm for GPM DPR. This algorithm is constructed using a precipitation type index (PTI) defined for DPR. The PTI is effective in separating hydrometeor types and is calculated using measurements of reflectivity, dual-frequency ratio, and storm top height data. The output of the algorithm is a Boolean product representing the existence of graupel or hail along with the vertical profile for each Ku- and Ka-band matched footprint. Cross validation is performed with the Weather Service Radar (WSR-88D) network over continental United States as well as during the Remote sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) experiment. Evaluation of the GH identification algorithm is performed on a global basis, which illustrates promising comparisons with the global lightning and hail precipitation maps generated using radar and radiometer.

54 ENVIRONMENTAL SCIENCES↗

Flexoelectricity and New Phenomena

It is easy to miss the scientific implications of our recent work on Triboelectricity. Everyone knows that rubbing and contact can produce static electricity; less appreciated is that the thermodynamic driver has been an open question since static electricity was first observed by Thales of Miletus around 585 BC. People think they understand it, for instance one common explanation that can still be found in the current literature is that differences in the work function drives charge transfer, often called the Volta-Helmholtz hypothesis. As summarized in 1967 by Harper, this fails to explain many experimental observations, for instance that charging can occur when two pieces of the same material are rubbed against each other. We are the first to place triboelectricity on a solid foundation rooted in quantum mechanics – the flexoelectric effect. We were able to explain a significant number of previously unexplained phenomena: 1) Bipolar tribocurrents associated with stick-slip, due to the change in sign of the strain gradients. 2) A one-third power scaling of tribocurrents with indentation force. 3) Tribocharging when two identical materials are used, these being due to local variations in the asperities so there are usually local potential differences. 4) Inhomogeneous charging of insulators, related to the statistical nature of asperities. 5) An experimentally observed reversal in the sign of charge transfer for negative and positive curvature, which is related to a change in the sign of the strain gradient. Exploiting our DOE prior funded work on flexoelectricity, we obtained semi-quantitative matching to existing experimental measurements of the surface charge in triboelectric experiments. The work has been well received in the literature. The work has been the focus of a number of popular science press articles, and also formed the basis for a Podcast for children 6-10 “The Rise and Fall of Static Man” posted in December 2019 by NPR as part of their “Wow in the World” series. I was also briefly interviewed by the Chicago PBS station in January 2020. This work are significant for a wide range of energy applications; to quote from an independent source: "Triboelectric power has plenty of potential, says Wenzhuo Wu, an assistant professor of engineering at Purdue. If the basics of static electricity are better understood, we could maximize the efficiency of wind or wave power generators, Wu says. The body's own movement could be used to power internal medical devices. Imagine being able to create a roof shaped to harness the power of a raindrop — the friction of the rain passing over the surface — to generate triboelectricity, powering the building below it." This is the start of new science, some of which we already partially understand such as the role of band bending in charge transfer. We need to understand charge transfer combining elasticity, quantum mechanics, band bending and defect states. These directly involve several of the DOE Grand Challenges: "How do we control material processes at the level of electrons? How do remarkable properties of matter emerge from complex correlations of the atomic or electronic constituents and how can we control these properties? How do we characterize and control matter away—especially very far away— from equilibrium?" I will argue that this work truly falls into the class of disruptive science; it is not just a simple extension, linear science. Not everyone will accept the approach. Since we explain far more about triboelectricity than anyone before, the preponderance of evidence supports the model. The feedback I have received is that many agree with the work, to quote: "The model makes sense, says Michael McAlpine, a professor of engineering at the University of Minnesota. "It's such a simple explanation, I was surprised I didn't put my finger on that," McAlpine says." The proposal received strong reviews. It was also publicized on the Department of Energy Web Site.

16 TIDAL AND WAVE POWER↗

Surface heat flux and its association with the MJO in the tropical western Pacific using ARM observations

The Madden-Julian oscillation (MJO) is a major atmospheric phenomenon in the tropics that moves eastward every 20 to 100 days. It brings heavy rain and strong winds, influencing extreme weather events far beyond the tropics – including flooding, hurricanes, tornadoes and heavy snow in the United States. Therefore, an improved understanding of the MJO is critical for enhancing weather forecasts and supporting better decision-making for communities, emergency managers, and the private sector. Past studies, based on short-term observations or long-term model data, have emphasized the dominant role of atmospheric humidity in driving the MJO. Our research, using long-term observations (2000-2014) from three U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) sites in the tropical western Pacific (Manus, Nauru, and Darwin) confirms those past findings. However, we also show that atmospheric temperature, especially in the mid and upper troposphere, also plays a key role in the MJO’s evolution from its quiet (suppressed) to convective (active) phase. These findings provide valuable insights into how the MJO evolves and may help evaluate and improve weather and climate models. Our study also examined how the exchange of heat between the Earth's surface and the atmosphere, called surface heat flux, interacts with the MJO. This flux includes components such as latent heat (related to evaporation), sensible heat (related to temperature difference between surface and atmosphere), and radiation. We found that modulation in MJO convection is well connected to surface heat flux over the tropical western Pacific. One surface heat flux component often overlooked is the sensible heat flux due to precipitation (Q P ). Since falling raindrops are typically cooler than the land or ocean surface, they can cool the surface and affect local weather. To test the impact of Q P on convection during MJO, we incorporated it into a weather model, and ran simulations for two periods: April 2009 (when the MJO was active) and June 2006 (when it was not). Including Q P reduced errors in simulating the daily peak of rainfall—by 83% during the strong MJO and 23% during the inactive phase. It also improved the timing of peak daily rainfall and reduced the overall precipitation error by about 10%. These improvements were especially noticeable during periods of heavy rainfall. Our results suggest that even small heat exchanges from rainfall can play a significant role in shaping local weather. Accounting for these effects, particularly in regions like the tropical islands, can lead to more accurate simulations of the MJO-associated precipitation.

54 ENVIRONMENTAL SCIENCES↗

Mind-the-gap - Part III: Doppler velocity measurements from space

Convective motions and hydrometeors microphysical properties are highly sought-after parameters for evaluating atmospheric numerical models. With most of the Earth's surface covered by water, space-borne Doppler radars are ideal for acquiring such measurements at a global scale. While these systems have proven to be useful tools for retrieving cloud microphysical and dynamical properties from the ground, their adequacy, and specific requirements for spaceborne operation still need to be evaluated. Comprehensive forward simulations enable us to assess the advantages and drawbacks of six different Doppler radar architectures currently planned or under consideration by space agencies for the study of cloud dynamics. Radar performance is examined against state-of-the-art numerical model simulations of well-characterized shallow and deep, continental, and oceanic convective cases. Mean Doppler velocity (MDV) measurements collected at multiple frequencies (13, 35 and 94 GHz) provide complementary information in deep convective cloud systems. The high penetration capability of the 13-GHz radar enables to obtain a complete, albeit horizontally under-sampled, view of deep convective storms. The smaller instantaneous field of view (IFOV) of the 35-GHz radar captures more precise information about the location and size of convective updrafts above 5-8 km height of most systems which was determined is the portion of storms where the mass flux peak is typically located. Finally, the lower mean Doppler velocity uncertainty of displaced phase center antenna (DPCA) radars makes them an ideal system for studying microphysics in shallow convection and frontal systems, as well as ice and mixed-phase clouds. It is demonstrated that a 94-GHz DCPA system can achieve retrieval errors as low as 0.05-0.15 mm for raindrop volume-weighted mean diameter and 25% for rime fraction (for a -10 dBZ echo).

54 ENVIRONMENTAL SCIENCES↗

Contrasting characteristics of open- and closed-cellular stratocumulus cloud in the eastern North Atlantic

Abstract. Extensive regions of marine boundary layer cloud impact the radiative balance through their significant shortwave albedo while having little impact on outgoing longwave radiation. Despite this importance, these cloud systems remain poorly represented in large-scale models due to difficulty in representing the processes that drive their life cycle and coverage. In particular, the mesoscale organization and cellular structure of marine boundary clouds have important implications for the subsequent cloud feedbacks. In this study, we use long-term (2013–2018) observations from the Atmospheric Radiation Measurement (ARM) Facility's Eastern North Atlantic (ENA) site on Graciosa Island, Azores, Portugal, to identify cloud cases with open- or closed-cellular organization. More than 500 h of each organization type are identified. The ARM observations are combined with reanalysis and satellite products to quantify the cloud, precipitation, aerosol, thermodynamic, and large-scale synoptic characteristics associated with these cloud types. Our analysis shows that both cloud organization populations occur during similar sea surface temperature conditions, but the open-cell cases are distinguished by stronger cold-air advection and large-scale subsidence compared to the closed-cell cases, consistent with their formation during cold-air outbreaks. We also find that the open-cell cases were associated with deeper boundary layers, stronger low-level winds, and higher rain rates compared to their closed-cell counterparts. Finally, raindrops with diameters larger than 1 mm were routinely recorded at the surface during both populations, with a higher number of large drops during the open-cellular cases. The similarities and differences noted herein provide important insights into the environmental and cloud characteristics during varying marine boundary layer cloud mesoscale organization and will be useful for the evaluation of model simulations for ENA marine clouds.

54 ENVIRONMENTAL SCIENCES↗

Impacts of secondary ice production on Arctic mixed-phase clouds based on ARM observations and CAM6 single-column model simulations

For decades, measured ice crystal number concentrations have been found to be orders of magnitude higher than measured ice-nucleating particle number concentrations in moderately cold clouds. This observed discrepancy reveals the existence of secondary ice production (SIP) in addition to the primary ice nucleation. However, the importance of SIP relative to primary ice nucleation remains highly unclear. Furthermore, most weather and climate models do not represent SIP processes well, leading to large biases in simulated cloud properties. This study demonstrates a first attempt to represent different SIP mechanisms (frozen raindrop shattering, ice–ice collisional breakup, and rime splintering) in a global climate model (GCM). The model is run in the single column mode to facilitate comparisons with the Department of Energy (DOE)'s Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We show the important role of SIP in four types of clouds during M-PACE (i.e., multilayer, single-layer stratus, transition, and frontal clouds), with the maximum enhancement in ice crystal number concentrations up to 4 orders of magnitude in moderately supercooled clouds. We reveal that SIP is the dominant source of ice crystals near the cloud base for the long-lived Arctic single-layer mixed-phase clouds. The model with SIP improves the occurrence and phase partitioning of the mixed-phase clouds, reverses the vertical distribution pattern of ice number concentrations, and provides a better agreement with observations. The findings of this study highlight the importance of considering SIP in GCMs.

54 ENVIRONMENTAL SCIENCES↗

Effect of dust on rainfall over the Red Sea coast based on WRF-Chem model simulations

Water is the single most important element of life. Rainfall plays an important role in the spatial and temporal distribution of this precious natural resource, and it has a direct impact on agricultural production, daily life activities, and human health. One of the important elements that govern rainfall formation and distribution is atmospheric aerosol, which also affects the Earth's radiation balance and climate. Therefore, understanding how dust compositions and distributions affect the regional rainfall pattern is crucial, particularly in regions with high atmospheric dust loads such as the Middle East. Although aerosol and rainfall research has garnered increasing attention as both an independent and interdisciplinary topic in the last few decades, the details of various direct and indirect pathways by which dust affects rainfall are not yet fully understood. Here, we explored the effects of dust on rainfall formation and distribution as well as the physical mechanisms that govern these phenomena, using high-resolution WRF-Chem simulations (~1.5 km × 1.5 km) configured with an advanced double-moment cloud microphysics scheme coupled with a sectional eight-bin aerosol scheme. Our model-simulated results were realistic, as evaluated from multiple perspectives including vertical profiles of aerosol concentrations, aerosol size distributions, vertical profiles of air temperature, diurnal wind cycles, and spatio-temporal rainfall patterns. Rainfall over the Red Sea coast is mainly caused by warm rain processes, which are typically confined within a height of ~6 km over the Sarawat mountains and exhibit a strong diurnal cycle that peaks in the evening at approximately 18:00 local time under the influence of sea breezes. Numerical experiments indicated that dust could both suppress or enhance rainfall. The effect of dust on rainfall was calculated as total, indirect, and direct effects, based on 10-year August-average daily-accumulated rainfall over the study domain covering the eastern Red Sea coast. For extreme rainfall events (domain-average daily-accumulated rainfall of ≥ 1.33 mm), the net effect of dust on rainfall was positive or enhancement (6.05 %), with the indirect effect (4.54 %) and direct effect (1.51 %) both causing rainfall increase. At a 5 % significance level, the total and indirect effects were statistically significant whereas the direct effect was not. For normal rainfall events (domain-average daily-accumulated rainfall < 1.33 mm), the indirect effect enhanced rainfall (4.76 %) whereas the direct effect suppressed rainfall (-5.78 %), resulting in a negative net suppressing effect (-1.02 %), all of which were statistically significant. We investigated the possible physical mechanisms of the effects and found that the rainfall suppression by dust direct effects was mainly caused by the scattering of solar radiation by dust. The surface cooling induced by dust weakens the sea breeze circulation, which decreases the associated landward moisture transport, ultimately suppressing rainfall. For extreme rainfall events, dust causes net rainfall enhancement through indirect effects as the high dust concentration facilitates raindrops to grow when the water vapor is sufficiently available. Our results have broader scientific and environmental implications. Specifically, although dust is considered a problem from an air quality perspective, our results highlight the important role of dust on sea breeze circulation and associated rainfall over the Red Sea coastal regions. Our results also have implications for cloud seeding and water resource management.

54 ENVIRONMENTAL SCIENCES↗

Optimizing cloud motion estimation on the edge with phase correlation and optical flow

Abstract. Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transform. In this study, we investigate the performance and the stability of the blockwise PC method by changing the block size, the frame interval, and combinations of red, green, and blue (RGB) channels from the total sky imager (TSI) at the United States Atmospheric Radiation Measurement user facility's Southern Great Plains site. We find that shorter frame intervals, followed by larger block sizes, are responsible for stable estimates of the CMV, as suggested by the higher autocorrelations. The choice of RGB channels has a limited effect on the quality of CMVs, and the red and the grayscale images are marginally more reliable than the other combinations during rapidly evolving low-level clouds. The stability of CMVs was tested at different image resolutions with an implementation of the optimized algorithm on the Sage cyberinfrastructure test bed. We find that doubling the frame rate outperforms quadrupling the image resolution in achieving CMV stability. The correlations of CMVs with the wind data are significant in the range of 0.38–0.59 with a 95 % confidence interval, despite the uncertainties and limitations of both datasets. A comparison of the PC method with constructed data and the optical flow method suggests that the post-processing of the vector field has a significant effect on the quality of the CMV. The raindrop-contaminated images can be identified by the rotation of the TSI mirror in the motion field. The results of this study are critical to optimizing algorithms for edge-computing sensor systems.

54 ENVIRONMENTAL SCIENCES↗

KAZR Hydrometeor and Insect Masks

The Ka-band ARM zenith pointing radar (aka, KAZR) is so sensitive that it detects cloud particles and individual insects. While detecting insects with Ka-band radar is beneficial and desirable to advance radar entomology, this sensitivity can be detrimental to radar meteorology because insects could be interpreted as clouds or precipitation. For example, misclassifying insects as clouds has been a problem for the ARM Active Remote Sensing of Clouds (ARSCL) Value Added Product since its inception (Clothiaux et al. 2000). Based on cloud particle and insect radar scattering properties, an algorithm was developed that identifies clouds, raindrops, ice particles, and insects in KAZR co- and cross-polarimeteric Doppler velocity spectra. The algorithm produces affirmative masks in the KAZR native time and height resolution indicating time-height locations of hydrometeors and insects. The hydrometeor mask contains binary information (e.g., yes/no hydrometeor presence), and the insect mask includes a proxy for insect activity that increases when more insects are detected in the Doppler velocity spectra. The algorithm was developed using KAZR medium sensitivity mode (MD) observations and was applied to two summer seasons of KAZR observations at the Southern Great Plains (SGP) Central Facility: May-October 2018 and 2019. In the future, this data set will be expanded to include other KAZR operating modes and observations from other ARM field sites. Details of the algorithm and data set can be found in: Williams, C.R., K.L. Johnson, S.E. Giangrande, J. C. Hardin, R. Oktem, and D. M. Romps, 2021: Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra. Atmospheric Measurement Techniques, submitted 6-Feb-2021. https://amt.copernicus.org/preprints/amt-2021-27/#discussion.For more information on the ARSCL VAP, see Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000; J. Appl. Meteor., 39, 645-665.

54 ENVIRONMENTAL SCIENCES↗

CACTI CSAPR2 Taranis Retrievals

Taranis is an end-to-end processing chain for radar data written in Python with C extension for computation performance. Features include: masking for quality control, specific differential phase (Kdp), attenuation correction for reflectivity factor (Z) and differential reflectivity (Zdr) in rain, and additional geophysical retrievals. Retrievals are mostly drawn from literature or open-source software when appropriate, and have been tested, tuned, and modified to work with one another cohesively rather than using isolated off-the-shelf algorithms. Incorporated algorithms include hydrometeor (echo) identification, rain water content, raindrop mass-weighted mean diameter (gamma size distribution assumption), and rainfall rate (QPE). Taranis data sets exist for CSAPR2 PPI, HSRHI, and sector RHI scans. Cartesian-gridded data sets were also produced as well as a near-surface rain rate retrieval. More details can be found in the README.

54 ENVIRONMENTAL SCIENCES↗

Seasonal Precipitation Classification during Surface Atmosphere Integrated Field Laboratory Campaign

The Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, conducted from September 2021 to June 2023 in Crested Butte, Colorado, aimed to characterize precipitation processes in the Upper Colorado River Basin (UCRB). This increased observations of snowfall accumulation in this hydrologically significant watershed would be useful for quantitative precipitation estimates (QPE). Therefore, the Surface Quantitative Precipitation Estimate (SQUIRE) product was developed using the ARM-supported Colorado State University (CSU) X-band Precipitation Radar. Although SQUIRE will be only released for snowfall, by categorizing precipitation types, users can effectively utilize relevant datasets under diverse meteorological conditions. Moreover, the dataset facilitates validation of the QPE product and the analysis of seasonal variations in precipitation types at the surface. Hydrometeors classes are organized based on their phase and physical characteristics mapping the CSU (both winter Summer) and Py-ART classifications into four groups. 1. Liquid Precipitation: includs drizzle, rain, and large raindrops. 2. Frozen Snow and Ice : Pure Snow, combining ice crystals, aggregates, and vertically oriented ice structures. 3. Dense and Large frozen hydrometeors: including low- and high-density graupel and dry hail. 4.Melting: Wet Snow and Melting Hail, hydrometeors exhibiting both liquid and frozen characteristics.

54 ENVIRONMENTAL SCIENCES↗