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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predicting the Evolution of Shallow Cumulus Clouds With a Lotka‐Volterra Like Model

Abstract In numerical weather prediction and climate models, boundary‐layer clouds are controlled by a wide range of subgrid‐scale processes. However, understanding the nature of these processes and their role in the evolution of the cloud size distribution as a whole has been elusive. To address this issue, we adopt a novel empirical framework from the field of population dynamics to model the evolution of cloud size statistics by using the shallow cumulus properties obtained from a large‐eddy simulation (LES). Our approach involves representing the cloud size distribution and the total cloud area using a revised Lotka‐Volterra model and ridge linear model, respectively. The physical interpretation of the total cloud area and coefficients obtained from the optimization of the models reveals three stages probably interpreted by dominant processes: the formation of new clouds, the growth of single clouds, and a steady state with organized transitions involving the growth and decay of multiple clouds. Furthermore, we showcase the potential of this framework to serve as a component of scale‐aware parameterizations of shallow‐convective clouds in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

Luo, Yali↗
DOE OSTI2025

Scientific Directions for Cloud Chamber Research: Instrumentation, Modeling, New Chambers, and Emerging Chamber Concepts

The Workshop on Scientific Directions for Cloud Chamber Research was held 13-14 July 2024 at the National Institute for Meteorological Sciences, Jeju, South Korea. Here, over 75 scientists from 13 countries gathered to learn about and discuss the latest scientific research results from large laboratory cloud chamber facilities, as well as new developments in cloud chamber instrumentation and modeling efforts, and emerging cloud chamber designs that will open new scientific research directions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

A Hierarchical Modeling Study of the Interactions Among Turbulence, Cloud Microphysics, and Radiative Transfer in the Evolution of Cirrus Clouds

This project used a hierarchy of cloud resolving models to address the following science issues of relevance to CRYSTAL-FACE: What ice crystal nucleation mechanisms are active in the different types of cirrus clouds in the Florida area and how do these different nucleation processes influence the evolution of the cloud system and the upper tropospheric humidity? How does the feedback between supersaturation and nucleation impact the evolution of the cloud? What is the relative importance of the large-scale vertical motion and the turbulent motions in the evolution of the crystal size spectra? How does the size spectra impact the life-cycle of the cloud, stratospheric dehydration, and cloud radiative forcing? What is the nature of the turbulence and waves in the upper troposphere generated by precipitating deep convective cloud systems? How do cirrus microphysical and optical properties vary with the small-scale dynamics? How do turbulence and waves in the upper troposphere influence the cross-tropopause mixing and stratospheric and upper tropospheric humidity? The models used in this study were: 2-D hydrostatic model with explicit microphysics that can account for 30 size bins for both the droplet and crystal size spectra. Notably, a new ice crystal nucleation scheme has been incorporated into the model. Parcel model with explicit microphysics, for developing and evaluating microphysical parameterizations. Single column model for testing bulk microphysics parameterizations

Curry, Judith↗
NASA NTRS1997

Model For Dense Molecular Cloud Cores

We present a detailed theoretical model for the thermal balance, chemistry, and radiative transfer within quiescent dense molecular cloud cores that contain a central protostar. In the interior of such cores, we expect the dust and gas temperatures to be well coupled, while in the outer regions CO rotational emissions dominate the gas cooling and the predicted gas temperature lies significantly below the dust temperature. Large spatial variations in the gas temperature are expected to affect the gas phase chemistry dramatically; in particular, the predicted water abundance varies by more than a factor of 1000 within cloud cores that contain luminous protostars. Based upon our predictions for the thermal and chemical structure of cloud cores, we have constructed self-consistent radiative transfer models to compute the line strengths and line profiles for transitions of (12)CO, (13)CO, C(18)O, ortho- and para-H2(16)O, ortho- and para-H2(18)O, and O I. We carried out a general parameter study to determine the dependence of the model predictions upon the parameters assumed for the source. We expect many of the far-infrared and submillimeter rotational transitions of water to be detectable either in emission or absorption with the use of the Infrared Space Observatory (ISO) and the Submillimeter Wave Astronomy Satellite. Quiescent, radiatively heated hot cores are expected to show low-gain maser emission in the 183 GHz 3(sub 13)-2(sub 20) water line, such as has been observed toward several hot core regions using ground-based telescopes. We predict the (3)P(sub l) - (3)P(sub 2) fine-structure transition of atomic oxygen near 63 micron to be in strong absorption against the continuum for many sources. Our model can also account successfully for recent ISO observations of absorption in rovibrational transitions of water toward the source AFGL 2591.

Doty, Steven D.↗
NASA NTRS1981

Transport of infrared radiation in cuboidal clouds

The transport of infrared radiation in a single cuboidal cloud is modeled using a variable azimuth two-stream approximation. Computations are made at 10 microns for a Deirmendjian (1969) C-1 water cloud where the single scattering albedo is equal to 0.638 and the asymmetry parameter is 0.865. The results indicate that the emittance of the top face of the model cloud is always less than that for a plane parallel cloud of the same optical depth. The hemispheric flux escaping from the cloud top possesses a gradient from the center to the edges which are warmer when the cloud is over warmer ground. Cooling rate calculations in the 8-13.6 micron region demonstrate that there is cooling out of the sides of the cloud at all levels even when there is heating of the core from the ground below. The radiances exiting from model cuboidal clouds are computed by path integration over the source function obtained with the two-stream approximation. Results indicate that the brightness temperature measured from finite clouds will overestimate the cloud-top temperature.

Harshvardhan, MR.↗
DOE OSTI2023

Subsetted model output on pressure levels for cloud-related variables from a LASSO-CACTI WRF simulation

Cloud-related model output interpolated to pressure levels from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. This version of the output is a collection of variables subsetted from the raw WRF output to reduce the file overhead for users not needing the full raw dataset. The subset files are in netCDF format with the height-based variables interpolated to pressure levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High Performance, High Fidelity: A GPU‐Accelerated Doubly‐Periodic Configuration of the Simple Cloud‐Resolving E3SM Atmosphere Model Version 1 (DP‐SCREAMv1)

The development of the Simplified Cloud Resolving Energy Exascale Earth System Atmosphere Model (SCREAMv1) enables global storm-resolving simulations on modern GPU-based supercomputers. However, the high computational cost of SCREAMv1 limits its routine use for process-level studies, creating a need for efficient proxy configurations. This study addresses this gap by introducing DP-SCREAMv1, a doubly periodic cloud-resolving model designed to be fully consistent with SCREAMv1 while enabling high-resolution, long-duration simulations at significantly reduced computational expense by simulating a limited doubly periodic domain rather than the entire globe. Built on a C++/Kokkos architecture, DP-SCREAMv1 achieves exceptional performance scalability on GPU systems and includes a rich library of cases for validation and scientific exploration. In this work, we demonstrate short wall-clock times at SCREAMv1's default resolution and show that DP-SCREAMv1 supports routine execution of large-domain, high-resolution experiments that were previously challenging in practice. Furthermore, we show that DP-SCREAMv1 enables routine execution of “Giga-LES” style simulations and facilitates large-domain, high-resolution simulations that were recently considered burdensome to perform. These results document an efficient, fully consistent process-level configuration for SCREAMv1 (DP-SCREAMv1) and illustrate its use for long-duration and large-domain experiments at cloud-resolving to eddy-permitting resolution.

Environmental sciences↗
NASA NTRS1990

Hierarchical fragmentation model for the evolution of self-gravitating clouds

A hierarchical model for the fragmentation of cold, self-gravitating gas clouds is developed, and the model is applied to the collapse of matter accumulated at the boundaries of large-scale voids in the universe. In this model, the mass function for fragment sizes and the correlation function for fragment positions are naturally related. Using this relationship, the mass function for galaxies is derived from the observed galaxy-galaxy two-point correlation function. Assuming that galaxy masses and luminosities are proportional to one another, the derived luminosity function agrees with the empirical Schecter function at low luminosity. It is argued that the correlation function itself may be a natural outcome of large-scale gravitational instability at each stage of the hierarchy.

Newman, William I.↗
NASA NTRS2011

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Tao, Wei-Kuo↗
DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗
DOE OSTI2020

Modeling Arctic boundary layer cloud streets at grey-zone resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds, we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiagvik (formerly Barrow), Alaska on 2 May 2013 and were observed by the Moderate Resolution Imaging Spectroradiometer (MODIS). The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain. We investigated the model-simulated mesoscale environment, horizontal and vertical cloud structures, boundary layer stability, and cloud properties, all of which were subsequently used to interpret the observed roll-cloud case. Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer. The clouds were stratiform-like in the mesoscale domain, but as the model resolution increased, roll-like structures, aligned along the wind field, appeared with ever smaller wavelengths. A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing. With fixed model grid spacing at 0.333 km, changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment, a stronger vertical water vapor gradient below the cloud layers, and the wavelengths of the rolls decreased slightly. In this study, only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Lai, Hui-Wen↗
NASA NTRS1987

Molecule formation in quasar broad-line cloud gas

Models for the broad-line emitting clouds of quasars typically assume that the clouds have column densities of at most 10 to the 23rd/sq cm. The consequences of relaxing this assumption are examined, and it is shown that: (1) at slightly larger column densities the gas may cool to about 1000 K as a result of molecule formation; (2) in much of the molecule-forming region the temperature may have either of two values, about 1000 K or 6000-8000 K; (3) the strengths of most observable optical lines, including C II semiforbidden 2326-A lines and Fe II lines, are unaffected by such large column densities; and (4) lines from low-ionization species such as Na I are readily formed at large column densities. Observations of such lines provide evidence for large cloud column densities.

Kallman, T.↗
NASA NTRS1995

Magnetic flux rope versus the spheromak as models for interplanetary magnetic clouds

Magnetic clouds form a subset of interplanetary ejecta with well-defined magnetic and thermodynamic properties. Observationally, it is well established that magnetic clouds expand as they propagate antisunward. The aim of this paper is to compare and contrast two models which have been proposed for the global magnetic field line topology of magnetic clouds: a magnetic flux tube geometry, on the one hand, and a spheromak geometry (including possible higher multiples), on the other. Traditionally, the magnetic structure of magnetic clouds has been modeled by force-free configurations. In a first step, we therefore analyze the ability of static force-free models to account for the asymmetries observed in the magnetic field profiles of magnetic clouds. For a cylindrical flux tube the magnetic field remains symmetric about closest approach to the magnetic axis on all spacecraft orbits intersecting it, whereas in a spheromak geometry one can have asymmetries in the magnetic field signatures along some spacecraft trajectories. The duration of typical magnetic cloud encounters at 1 AU (1 to 2 days) is comparable to their travel time from the Sun to 1 AU and thus magnetic clouds should be treated as strongly nonstationary objects. In a second step, therefore, we abandon the static approach and model magnetic clouds as self-similarly evolving MHD configurations. In our theory, the interaction of the expanding magnetic cloud with the ambient plasma is taken into account by a drag force proportional to the density and the velocity of expansion. Solving rigorously the full set of MHD equations, we demonstrate that the asymmetry in the magnetic signature may arise solely as a result of expansion. Using asymptotic solutions of the MHD equations, we least squares fit both theoretical models to interplanetary data. We find that while the central part of the magnetic cloud is adequately described by both models, the 'edges' of the cloud data are modeled better by the magnetic flux tube. Further comparisons of the two models necessarily involve thermodynamic properties, since real magnetic configurations are never exactly force-free and gas pressure plays an essential role. We consider a polytropic gas. Our theoretical analysis shows that the self-similar expansion of a magnetic flux tube requires the polytropic index gamma to be less than unity. For the spheromak, however, self-similar, radially expanding solutions are known only for gamma equal to 4/3. This difference, therefore, yields a good way of distinguishing between the two geometries. It has been shown recently that the polytropic relationship is applicable to magnetic clouds and that the corresponding polytropic index is approximately 0.5. This observational result is consistent with the self-similar model of the magnetic flux rope but is in conflict with the self-similar spheromak model.

Farrugia, C. J.↗
NASA NTRS2010

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Tao, Wei-Kuo↗
NASA NTRS1982

The kinetic chemistry of dense interstellar clouds

A model of the time-dependent chemistry of dense interstellar clouds is formulated to study the dominant chemical processes in carbon and oxygen isotope fractionation, the formation of nitrogen-containing molecules, and the evolution of product molecules as a function of cloud density and temperature. The abundances of the dominant isotopes of the carbon- and oxygen-bearing molecules are calculated. The chemical abundances are found to be quite sensitive to electron concentration since the electron concentration determines the ratio of H3(+) to He(+), and the electron density is strongly influenced by the metals abundance. For typical metal abundances and for H2 cloud density not less than 10,000 molecules/cu cm, nearly all carbon exists as CO at late cloud ages. At high cloud density, many aspects of the chemistry are strongly time dependent. Finally, model calculations agree well with abundances deduced from observations of molecular line emission in cold dense clouds.

Graedel, T. E.↗