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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Surface Crystallization of Supercooled Water in Clouds

The process by which liquid cloud droplets homogeneously crystallize into ice is still not well-understood. The ice nucleation process based on the standard and classical theory of homogeneous freezing, initiates within the interior volume of a cloud droplet. Current experimental data on homogeneous freezing rates of ice in droplets of supercooled water, both in air and emulsion oil samples, show considerable scatter. For example, at -33 C, the reported volume-based freezing rates of ice in supercooled water vary by as much as 5 orders of magnitude, which is well outside the range of measurement uncertainties. Here, we show that the process of ice nucleus formation at the air (or oil)-liquid water interface may help to explain why experimental results on ice nucleation rates yield different results in different ambient phases. Our results also suggest that surface crystallization of ice in cloud droplets can explain why low amounts of supercooled water have been observed in the atmosphere near -40 C.

Tabazadeh, Azadeh↗
DOE OSTI2024

Reduced‐Order Modeling for Linearized Representations of Microphysical Process Rates

Abstract Representing cloud microphysical processes in large scale atmospheric models is challenging because many processes depend on the details of the droplet size distribution (DSD, the spectrum of droplets with different sizes in a cloud). While full or partial statistical moments of droplet size distributions are the typical variables used in bulk models, prognostic moments are limited in their ability to represent microphysical processes across the range of conditions experienced in the atmosphere. Microphysical parameterizations employing prognostic moments are known to suffer from structural uncertainty in their representations of inherently higher dimensional cloud processes, which limit model fidelity and lead to forecasting errors. Here we investigate how data‐driven reduced‐order modeling can be used to learn predictors for microphysical process rates in bulk microphysics schemes in an unsupervised manner from higher dimensional bin distributions. Using simulations characteristic of marine stratiform clouds, we simultaneously learn lower dimensional representations of droplet size distributions and predict the evolution of the microphysical state of the system. Droplet collision‐coalescence, the main process for generating warm rain, is estimated to have an intrinsic dimension of three. This intrinsic dimension provides a lower limit on the number of degrees of freedom needed to accurately represent collision‐coalescence in models. We demonstrate how deep learning based reduced‐order modeling can be used to discover intrinsic coordinates describing the microphysical state of the system, where process rates such as collision‐coalescence are globally linearized. These implicitly learned representations of the DSD retain more information about the DSD than typical moment‐based representations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes

During the past decade, numerical weather and global non-hydrostatic models have started using more complex microphysical schemes originally developed for high resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. These microphysical schemes affect the dynamic through the release of latent heat (buoyancy loading and pressure gradient) the radiation through the cloud coverage (vertical distribution of cloud species), and surface processes through rainfall (both amount and intensity). Recently, several major improvements of ice microphysical processes (or schemes) have been developed for cloud-resolving model (Goddard Cumulus Ensemble, GCE, model) and regional scale (Weather Research and Forecast, WRF) model. These improvements include an improved 3-ICE (cloud ice, snow and graupel) scheme (Lang et al. 2010); a 4-ICE (cloud ice, snow, graupel and hail) scheme and a spectral bin microphysics scheme and two different two-moment microphysics schemes. The performance of these schemes has been evaluated by using observational data from TRMM and other major field campaigns. In this talk, we will present the high-resolution (1 km) GeE and WRF model simulations and compared the simulated model results with observation from recent field campaigns [i.e., midlatitude continental spring season (MC3E; 2010), high latitude cold-season (C3VP, 2007; GCPEx, 2012), and tropical oceanic (TWP-ICE, 2006)].

Tao, Wei-Kuo↗
NASA NTRS2006

Algorithm for Automated Detection of Edges of Clouds

An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

Ward, Jennifer G.↗
NASA NTRS1982

Drop processes in natural clouds

A model of the diffusive mixing of dry and cloudy air, a process considered to be fundamental to the development of natural clouds, is presented. Water drops are formed at the cloud base by condensation upon nuclei and as they rise they grow by vapor diffusion in the slightly supersaturated environment of the clouds. Turbulent mixing between cloudy air and undersaturated air entrained from outside produces fluctuations in supersaturation, not linked to changes in vertical velocity, which cause broadening of the condensate spectrum and the rapid production of droplets large enough to engage in growth by coalescence. The probabilities of permanent union or the production of satellite droplets following the collision of a pair of raindrops is a sensitive function of several parameters. In some circumstances electrohydrodynamic bursting may influence the properties of clouds.

Latham, J.↗
NASA NTRS1986

A study of the response of deep tropical clouds to mesoscale processes - Three-dimensional numerical experiments

A three-dimensional numerical cloud model is utilized to study the collective feedback effects of cloud systems on the large-scale environment. The characteristic features of the cloud ensemble model are described. The model is applied to a case of a well-defined ITCZ rainband over the eastern tropical Atlantic ocean. The location, number, and configuration of the clouds that formed in the model during the simulations are examined. The cloud heating and moistening, environmental wind shear, and vertical transports of momentum are analyzed. The collective feedbacks of cloud systems on the large-scale temperature, moisture, and horizontal momentum fields are computed after each simulation. The effect of the pressure gradient force on the v-momentum flux is investigated. It is observed that there is good correlation between the model simulations and the observed data.

Tao, Wei-Kuo↗
DOE OSTI2024

Using Machine Learning to Predict Cloud Turbulent Entrainment–Mixing Processes

Different turbulent entrainment–mixing mechanisms between clouds and environment are essential to cloud–related processes; however, accurate representation of entrainment–mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment–mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment–mixing. Specifically, number concentration after entrainment–mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment–mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment–mixing is negatively correlated with liquid water content affected by entrainment–mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment–mixing in weather/climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Cloud Microphysics Budget in the Tropical Deep Convective Regime

Cloud microphysics budgets in the tropical deep convective regime are analyzed based on a 2-D cloud resolving simulation. The model is forced by the large-scale vertical velocity and zonal wind and large-scale horizontal advections derived from TOGA COARE for a 20-day period. The role of cloud microphysics is first examined by analyzing mass-weighted mean heat budget and column-integrated moisture budget. Hourly budgets show that local changes of mass-weighted mean temperature and column-integrated moisture are mainly determined by the residuals between vertical thermal advection and latent heat of condensation and between vertical moisture advection and condensation respectively. Thus, atmospheric thermodynamics depends on how cloud microphysical processes are parameterized. Cloud microphysics budgets are then analyzed for raining conditions. For cloud-vapor exchange between cloud system and its embedded environment, rainfall and evaporation of raindrop are compensated by the condensation and deposition of supersaturated vapor. Inside the cloud system, the condensation of supersaturated vapor balances conversion from cloud water to raindrop, snow, and graupel through collection and accretion processes. The deposition of supersaturated vapor balances conversion from cloud ice to snow through conversion and riming processes. The conversion and riming of cloud ice and the accretion of cloud water balance conversion from snow to graupel through accretion process. Finally, the collection of cloud water and the melting of graupel increase raindrop to compensate the loss of raindrop due to rainfall and the evaporation of raindrop.

Li, Xiao-Fan↗
NASA NTRS2009

Simulation and Interpretation of the Genesis of Tropical Storm Gert (2005) as Part of the NASA Tropical Cloud Systems and Processes Experiment

Several hypotheses have been put forward for the how tropical cyclones (tropical storms and hurricanes in the Atlantic) first develop circulation at the surface, a key event that needs to occur before a storm can begin to draw energy from the warm ocean. One hypothesis suggests that the surface circulation forms from a "top-down" approach in which a storm s rotating circulation begins at middle levels of the atmosphere and builds down to the surface through processes related to light "stratiform" (horizontally extensive) precipitation. Another hypothesis suggests a bottom-up approach in which deep thunderstorm towers (convection) play the major role in spinning up the flow at the surface. These "hot towers" form in the area of the mid-level circulation and strongly concentrate this rotation at low levels within their updrafts. Merger of several of these hot towers then intensifies the surface circulation to the point in which a storm forms. This paper examines computer simulations of Tropical Storm Gert (2005), which formed in the Gulf of Mexico during the National Aeronautics and Space Administration s (NASA) Tropical Cloud Systems and Processes (TCSP) Experiment, to investigate the development of low-level circulation and, in particular, whether stratiform or hot tower processes were responsible for the storm s formation. Data from NASA satellites and from aircraft were used to show that the model did a good job of reproducing the formation and evolution of Gert. The simulation shows that a mix of both stratiform and convective rainfall occurred within Gert. While the stratiform rainfall clearly acted to increase rotation at middle levels, the diverging outflow beneath the stratiform rain worked against spinning up the low-level winds. The hot towers appeared to dominate the low-level flow, producing intense rotation within their cores and often being associated with significant pressure falls at the surface. Over time, many of these hot towers merged, with each merger adding to the rotation of the storm and the pressure falls at the surface. This process continued to increase the strength of the storm until the storm made landfall on the east coast of Mexico. These results support the bottom-up hypothesis for development.

Braun, Scott A.↗
NASA NTRS1980

Clouding of pyroxene and plagioclase in eucrites - Implications for post-crystallization processing

The clouding of pyroxene and plagioclase in the basaltic eucrites ALHA 77302, Juvinas, Pasamonte, and Stannern, is caused by finely disseminated inclusions. This clouding is interpreted to be the result of exsolution of minor components which became incompatible and crystallized on microfractures and other nucleation sites during postbrecciation metamorphism. The phases found in clouding require reduction of silicate FeO to metallic Fe in both pyroxene and plagioclase and possible redox of Cr(2+) to Cr(3+) in pyroxene. The assemblage of coexisting phases that make up clouding record conditions of T approximately equal to 900 C and f(O2) of 10 to the -16th to 10 to the -18th during slow cooling. Thus, clouding can be a useful indicator of postcrystallization conditions.

Harlow, G. E.↗
DOE OSTI2024

Cloud Water Chemistry and Aerosol Processing: Assessing the Hydroxyl Radical Burst in Newly Formed Cloud Droplets (Field Campaign Report)

Aerosol particles are tiny liquid or solid particles in the atmosphere, ranging in size from a few nanometers to several micrometers in diameter. Aerosol-cloud interactions are the most uncertain aspect of the climate system, and models routinely underpredict aerosol particle formation. Clouds are well known to alter aerosol size, chemical composition, and radiative properties, but the processes are poorly characterized. Organics and sulfates are the most abundant materials in particles, and for each of these there are significant gaps in the understanding of the role of clouds in their formation and/or aging. Many of the cloud processes are driven by aqueous chemistry that depends on hydroxyl (OH) radicals, the subject of this project.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Tropical Convective Responses to Microphysical and Radiative Processes: A Sensitivity Study With a 2D Cloud Resolving Model

Prognostic cloud schemes are increasingly used in weather and climate models in order to better treat cloud-radiation processes. Simplifications are often made in such schemes for computational efficiency, like the scheme being used in the National Centers for Environment Prediction models that excludes some microphysical processes and precipitation-radiation interaction. In this study, sensitivity tests with a 2D cloud resolving model are carried out to examine effects of the excluded microphysical processes and precipitation-radiation interaction on tropical thermodynamics and cloud properties. The model is integrated for 10 days with the imposed vertical velocity derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The experiment excluding the depositional growth of snow from cloud ice shows anomalous growth of cloud ice and more than 20% increase of fractional cloud cover, indicating that the lack of the depositional snow growth causes unrealistically large mixing ratio of cloud ice. The experiment excluding the precipitation-radiation interaction displays a significant cooling and drying bias. The analysis of heat and moisture budgets shows that the simulation without the interaction produces more stable upper troposphere and more unstable mid and lower troposphere than does the simulation with the interaction. Thus, the suppressed growth of ice clouds in upper troposphere and stronger radiative cooling in mid and lower troposphere are responsible for the cooling bias, and less evaporation of rain associated with the large-scale subsidence induces the drying in mid and lower troposphere.

Li, Xiao-Fan↗
NASA NTRS2004

A Study of the Response of Deep Tropical Clouds to Mesoscale Processes: Sensitivities to Microphysics, Radiation, and Surface Fluxes - Part 2

The Goddard Cumulus Ensemble (GCE) model is used to examine the sensitivities of surface fluxes, explicit radiation, and ice microphysical processes on multi-day simulations of deep tropical convection over the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). The simulations incorporate large-scale advective temperature and moisture forcing, as well as large-scale momentum, that are updated every time step on a periodic lateral boundary grid. This study shows that when surface fluxes are eliminated, the mean atmosphere is much cooler and drier, convection and CAPE are much weaker, precipitation is less, and cloud coverage in stratiform regions much greater. Surface fluxes using the TOGA COARE flux algorithm are weaker than with the aerodynamic formulation, but closer to the observed fluxes. In addition, similar trends noted above for the case without surface fluxes are produced for the TOGA flux case, albeit to a much lesser extent. The elimination of explicit shortwave and longwave radiation is found to have only minimal effects on the mean thermodynamics, convection, and precipitation. However explicit radiation does have a significant impact on cloud temperatures and structure above 200 mb and on the overall mean vertical circulation. The removal of ice processes produces major changes in the structure of the cloud. Much of the liquid water is transported aloft and into anvils above the melting layer (600 mb), leaving narrow, but intense bands of rainfall in convective regions. The elimination of melting processes leads to greater hydrometeor mass below the melting layer, and produces a much warmer and moister boundary layer, leading to a greater mean CAPE. Finally, the elimination of the graupel species has only a small impact on mean total precipitation, thermodynamics, and dynamics of the simulation, but does produce much greater snow mass just above the melting layer. Some of these results differ from previous CRM studies of tropical systems, which is likely due to the type of simulated system, total time integration, and model setup.

Johnson, Daniel↗
NASA NTRS2004

Effects of Cloud-Microphysics on Tropical Atmospheric Hydrologic Processes in the GEOS GCM

The sensitivity of tropical atmospheric hydrologic processes to cloud-microphysics is investigated using the NASA GEOS GCM. Results show that a faster autoconversion - rate produces more warm rain and less clouds at all levels. Fewer clouds enhances longwave cooling and reduces shortwave heating in the upper troposphere, while more warm rain produces increased condensation heating in the lower troposphere. This vertical heating differential destablizes the tropical atmosphere, producing a positive feedback resulting in more rain over the tropics. The feedback is maintained via a two-cell secondary circulation. The lower cell is capped by horizontal divergence and maximum cloud detrainment near the melting/freezing, with rising motion in the warm rain region connected to descending motion in the cold rain region. The upper cell is found above the freezing/melting level, with longwave-induced subsidence in the warm rain and dry regions, coupled to forced ascent in the deep convection region. The tropical large scale circulation is found to be very sensitive to the radiative-dynamic effects induced by changes in autoconversion rate. Reduced cloud-radiation processes feedback due to a faster autoconversion rate results in intermittent but more energetic eastward propagating Madden and Julian Oscillations (MJO). Conversely,-a slower autconversion rate, with increased cloud radiation produces MJO's with more realistic westward propagating transients, resembling a supercloud cluster structure. Results suggests that warm rain and associated low and mid level clouds, i.e., cumulus congestus, may play a critical role in regulating the time-intervals of deep convections and hence the fundamental time scales of the MJO.

Lau, K. M.↗
DOE OSTI2025

Exposing Process‐Level Biases in a Global Cloud Permitting Model With ARM Observations

The emergence of global convective‐permitting models (GCPMs) represents a significant advancement in climate modeling, offering improved representation of deep convection and complex precipitation patterns. In this study, we evaluate the performance of the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) using its doubly periodic configuration (DP‐SCREAM) against large eddy simulations and modern observational data sets from the Atmospheric Radiation Measurement program. We introduce several new transitional cloud regime cases, such as the transition from shallow to deep convection and from stratocumulus to cumulus, as well as cold‐air outbreak scenarios. The results reveal both strengths and limitations of SCREAM, particularly in the accurate simulation of cloud transitions and midlevel convection, with varying degrees of sensitivity to horizontal and vertical resolution. Despite improvements at higher resolutions, key biases remain, including the abrupt transition from shallow to deep convection and the lack of congestus clouds. These findings underscore the need for further refinement in turbulence parameterizations and vertical grid resolution in GCPMs.

Bogenschutz, Peter A. [Lawrence Livermore National↗
DOE OSTI2024

Using MARCUS, MICRE, and COMBLE data to improve understanding and modeling of cloud, aerosol, and boundary layer processes at high-latitudes

Because it is believed general circulation (GCM) and numerical weather prediction (NWP) models underestimate shortwave radiation over the Southern Ocean (SO) due to inadequate representations of boundary layer (BL) and cloud processes, it is critical to improve our understanding of key aerosol, cloud, precipitation, and BL processes. Over the north Atlantic Ocean (NA), cold-air outbreaks are common, yet few studies of the aerosol and environmental controls of the associated convective BL clouds exist as needed to develop and evaluate GCM representations. Although processes cannot be observed, cloud and aerosol properties can be measured in-situ or remotely retrieved, which when combined with numerical simulations enable process level understanding required to improve model representations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

The roles of dry convection, cloud-radiation feedback processes and the influence of recent improvements in the parameterization of convection in the GLA GCM

The Goddard Laboratory for Atmospheres GCM is used to study the sensitivity of the simulated July circulation to modifications in the parameterization of dry and moist convection, evaporation from falling raindrops, and cloud-radiation interaction. It is shown that the Arakawa-Schubert (1974) cumulus parameterization and a more realistic dry convective mixing calculation yielded a better intertropical convergence zone over North Africa than the previous convection scheme. It is found that the physical mechanism for the improvement was the upward mixing of PBL moisture by vigorous dry convective mixing. A modified rain-evaporation parameterization which accounts for raindrop size distribution, the atmospheric relative humidity, and a typical spatial rainfall intensity distribution for convective rain was developed and implemented. This scheme led to major improvements in the monthly mean vertical profiles of relative humidity and temperature, convective and large-scale cloudiness, rainfall distributions, and mean relative humidity in the PBL.

Sud, Y.↗