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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

A general model for Io's neutral gas clouds. I - Mathematical description

A general mathematical formalism for calculating the physical properties of any of Io's neutral gas clouds (Na, K, O, S, SO2) is presented. The dynamical effects of both the gravitational fields of Io and Jupiter and solar radiation pressure are included, in addition to the many complex space- and time-dependent interactions that occur between the neutral clouds and the plasma torus. The importance of this new model in studying both the plasma conditions prevalent in the inner planetary magnetosphere and the nature of Io's local atmosphere is discussed. A numerical method for evaluating the physical properties of the neutral clouds using the new model is described.

Smyth, W. H.↗
NASA NTRS2008

Summertime Coincident Observations of Ice Water Path in the Visible/Near-IR, Radar, and Microwave Frequencies

Accurate representation of the physical and radiative properties of clouds in climate models continues to be a challenge. At present, both remote sensing observations and modeling of microphysical properties of clouds rely heavily on parameterizations or assumptions on particle size distribution (PSD) and cloud phase. In this study, we compare Ice Water Path (IWP), an important physical and radiative property that provides the amount of ice present in a cloud column, using measurements obtained via three different retrieval strategies. The datasets we use in this study include Visible/Near-IR IWP from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flying aboard the Aqua satellite, Radar-only IWP from the CloudSat instrument operating at 94 GHz, and NOAA/NESDIS operational IWP from the 89 and 157 GHz channels of the Microwave Humidity Sounder (MHS) instrument flying aboard the NOAA-18 satellite. In the Visible/Near-IR, IWP is derived from observations of optical thickness and effective radius. CloudSat IWP is determined from measurements of cloud backscatter and assumed PSD. MHS IWP retrievals depend on scattering measurements at two different, non-water absorbing channels, 89 and 157 GHz. In order to compare IWP obtained from these different techniques and collected at different vertical and horizontal resolutions, we examine summertime cases in the tropics (30S - 30N) when all 3 satellites are within 4 minutes of each other (approximately 1500 km). All measurements are then gridded to a common 15 km x 15 km box determined by MHS. In a grid box comparison, we find CloudSat to report the highest IWP followed by MODIS, followed by MHS. In a statistical comparison, probability density distributions show MHS with the highest frequencies at IWP of 100-1000 g/m(exp 2) and CloudSat with the longest tail reporting IWP of several thousands g/m(exp 2). For IWP greater than 30 g/m(exp 2), MODIS is consistently higher than CloudSat, and it is higher at the lower IWPs but lower at the higher IWPs that overlap with MHS. Some of these differences can be attributed to the limitations of the measuring techniques themselves, but some can result from the assumptions made in the algorithms that generate the IWP product. We investigate this issue by creating categories based on various conditions such as cloud type, precipitation presence, underlying liquid water content, and surface type (land vs. ocean) and by comparing the performance of the IWP products under each condition.

Pittman, Jasna V.↗
NASA NTRS1989

Lidar sensing of aerosols and clouds in the troposphere and stratosphere

Advances in the development and application of lidar as a tool for the remote sensing of atmospheric aerosols and clouds are reviewed. The lidar sensing technique is described, and various approaches for solving the lidar equation to retrieve aerosol properties are summarized. Examples are presented of lidar applications to aerosol and cloud sensing in both the troposphere and stratosphere. These include environmental monitoring, atmospheric-boundary-layer studies, retrieval of aerosol optical and physical properties, sensing of clouds, and investigation of volcanic effects in the stratosphere. Comments are offered regarding the future outlook for aerosol and cloud sensing by both ground-based and spaceborne lidars.

Reagan, John A.↗
NASA NTRS1990

The far-infrared polarization of the Orion nebula

Polarization of the 100 micron thermal emission from 10 points in the Orion nebula has been measured. At one of the positions the degree, 5.7 percent, is the largest far-infrared polarization yet discovered. Except at a position in the barlike structure to the south, the position angles of the polarization vectors are well-ordered, suggesting that a uniform magnetic field threads the cloud. The magnetic field strength is estimated to be between 0.7 and 4 mG. The relationship of the degrees of polarization to the physical conditions in the cloud is discussed.

Gonatas, D. P.↗
NASA NTRS1998

Project S'COOL

The Students Clouds Observations On-Line or S'COOL project was piloted in 1997. It was created with the idea of using students to serve as one component of the validation for the Clouds and the Earth's Radiant Energy System (CERES) instrument which was launched with the Tropical Rainfall Measuring Mission (TRMM) in November, 1997. As part of NASA's Earth Science Enterprise CERES is interested in the role clouds play in regulating our climate. Over thirty schools became involved in the initial thrust of the project. The CERES instrument detects the location of clouds and identifies their physical properties. S'COOL students coordinate their ground truth observations with the exact overpass of the satellite at their location. Their findings regarding cloud type, height, fraction and opacity as well as surface conditions are then reported to the NASA Langley Distributed Active Archive Center (DAAC). The data is then accessible to both the CERES team for validation and to schools for educational application via the Internet. By March of 1998 ninety-three schools, in nine countries had enrolled in the S'COOL project. Joining the United States participants were from schools in Australia, Canada, France, Germany, Norway, Spain, Sweden, and Switzerland. The project is gradually becoming the global project envisioned by the project s creators. As students obtain the requested data useful for the scientists, it was hoped that students with guidance from their instructors would have opportunity and motivation to learn more about clouds and atmospheric science as well.

Green, Carolyn J.↗
NASA NTRS1993

Dynamical characteristics of cirrus clouds from aircraft and radar measurements

Cirrus clouds play an important role in climate and in the development of other types of clouds. Although there are many studies of clouds within the boundary layer, cirrus clouds have been neglected up until the last decade. New tools and in-situ measurements of various physical and dynamical parameters permit us to now study cirrus clouds in much greater detail. Physical and dynamical structures of cirrus clouds were studied in detail by Heymsfield using aircraft measurements. He emphasized the importance of interactions among physical and dynamical processes. Cirrus clouds often exhibit complex physical and dynamical structure. Upper tropospheric flows contain not only coherent structures, but also chaotic movements. The coherent structures (organized movements) transfer significant amounts of heat and momentum while their form, size, and intensity depend strongly on environmental instability. Various dynamical structures including cells, waves, and turbulence are studied in order to understand cirrus cloud formation and development.

Gultepe, I.↗
NASA NTRS1970

Large artificial plasma clouds in space

Large scale artificial plasma cloud experiments for magnetosphere, solar wind and cometary physics, discussing Ba ion and ice clouds released by satellites

Willis, R. G.↗
NASA NTRS2019

Extending XBAER Algorithm to Aerosol and Cloud Condition

The retrieval of cloud optical properties for aerosol contaminated water cloud is challenging because of the complexity of physical processes in such situations. Conventionally, cloud optical data products are typically derived, ignoring the aerosol impacts on radiative transfer in the retrieval process. This is potentially a significant source of error. In this paper, the eXtensible Bremen Aerosol Retrieval (XBAER) algorithm has been optimized for the retrieval of aerosol/cloud properties for the aerosol contaminated cloud (ACC) scenarios. This version of XBAER delivers cloud optical thickness (COT) and cloud effective radius (CER) for ACCs and simultaneously retrieves aerosol optical thickness (AOT). The surface parameterization and aerosol types used in the standard XBAER algorithm have been adapted in this retrieval to account for the ACC conditions. Aerosol types in XBAER for the retrieval of ACC scenarios have been parameterized to comprise weak and strong absorptions. The comparisons of COT, CER, and AOT retrieved using this adapted XBAER algorithm and two new NASA algorithms show good agreements, especially for biomass burning aerosol. The correlation coefficients are >0.9 for AOT, ~0.8 for CER, and ~0.7 for COT. There is also a good agreement for dust plume contaminated cloud scene. The XBAER derived AOT values for dust aerosols are systematically smaller than the NASA retrieval, but both products have the same spatial distribution patterns. The comparison of COT retrieved using the adapted XBAER algorithm and that retrieved from ground-based microwave radiometer (MWR) measurements shows much better agreement for ACC conditions with high AOT.

satellite↗
NASA NTRS2020

Sensitivity of Multispectral Imager Liquid Water Cloud Microphysical Retrievals to the Index of Refraction

A cloud property retrieved from multispectral imagers having spectral channels in the shortwave infrared (SWIR) and/or midwave infrared (MWIR) is the effective particle radius (CER), a radiatively relevant weighting of the cloud particle size distribution. The physical basis of the CER retrieval is the dependence of SWIR/MWIR cloud reflectance on the cloud particle single scattering absorption, which in turn depends on the complex index of refraction of bulk liquid water (or ice) in addition to the cloud particle size. There is a general consistency in the choice of the liquid water index of refraction by the cloud remote sensing community, largely due to the few available independent datasets and compilations. Here we examine the sensitivity of CER retrievals to the available laboratory index of refraction datasets in the SWIR and MWIR using the retrieval software package that produces NASA’s standard MODIS/VIIRS continuity cloud products. The sensitivity study incorporates two laboratory index of refraction datasets that include measurements at supercooled water temperatures, one in the SWIR [Kou et al., 1993] and one in the MWIR [Wagner et al., 2005]. Neither has been broadly utilized in the cloud remote sensing community. It is shown that these two new datasets can significantly change CER retrievals (e.g., 1-2 μm) relative to common datasets used by the community. Further, index of refraction data for a 265 K water temperature results in more consistent retrievals between the two spectrally distinct 2.2 μm atmospheric window channels on MODIS and VIIRS. As a result, the 265 K values from the SWIR and MWIR index of refraction datasets were adopted for use in the production version of the continuity cloud product. The results indicate the need to better understand temperature-dependent bulk water absorption and uncertainties in these spectral regions.

MODIS↗
NASA NTRS1990

Optical and morphological properties of Cirrus clouds determined by the high spectral resolution lidar during FIRE

Cirrus clouds reflect incoming solar radiation and trap outgoing terrestrial radiation; therefore, accurate estimation of the global energy balance depends upon knowledge of the optical and physical properties of these clouds. Scattering and absorption by cirrus clouds affect measurements made by many satellite-borne and ground based remote sensors. Scattering of ambient light by the cloud, and thermal emissions from the cloud can increase measurement background noise. Multiple scattering processes can adversely affect the divergence of optical beams propagating through these clouds. Determination of the optical thickness and the vertical and horizontal extent of cirrus clouds is necessary to the evaluation of all of these effects. Lidar can be an effective tool for investigating these properties. During the FIRE cirrus IFO in Oct. to Nov. 1986, the High Spectral Resolution Lidar (HSRL) was operated from a rooftop site on the campus of the University of Wisconsin at Madison, Wisconsin. Approximately 124 hours of fall season data were acquired under a variety of cloud optical thickness conditions. Since the IFO, the HSRL data set was expanded by more than 63.5 hours of additional data acquired during all seasons. Measurements are presented for the range in optical thickness and backscattering phase function of the cirrus clouds, as well as contour maps of extinction corrected backscatter cross sections indicating cloud morphology. Color enhanced images of range-time indicator (RTI) displays a variety of cirrus clouds with approximately 30 sec time resolution are presented. The importance of extinction correction on the interpretation of cloud height and structure from lidar observations of optically thick cirrus are demonstrated.

Grund, Christian John↗
NASA NTRS1990

Molecular clouds associated with luminous far-infrared sources in the outer Galaxy

The stellar content and physical properties of the molecular clouds associated with 21 bright far-IR sources in the outer Galaxy have been determined through C-12O, C-13O, 6-cm radio continuum, and IRAS observations. The molecular cloud masses range from 200 to about 10,000 solar masses. The far-IR luminosity-to-mass ratio for these clouds has a mean value of 6.8 solar luminosity/solar masses and shows no correlation with the cloud mass, a result similar to that found for more massive clouds in the inner Galaxy. The radio continuum survey of the 21 bright far-IR sources indicates that most of these regions probably have a single, massive star providing most of the ionization. The cloud masses derived from virial and LTE analyses are in agreement, supporting the assumptions commonly made in their calculations, and a tight, near-linear correlation is found between the C-12O luminosity and the cloud mass. The H2 column density and integrated C-12O intensity are also correlated on a point-by-point basis, although the scatter is larger than the C-12O luminosity-cloud mass relation.

Carpenter, John M.↗
NASA NTRS1997

The Structure of Active Galactic Nuclei

We are continuing our systematic investigation of the nuclear structure of nearby active galactic nuclei (AGN). Upon completion, our study will characterize hypothetical constructs such as narrow-line clouds, obscuring tori, nuclear gas disks. and central black holes with physical measurements for a complete sample of nearby AGN. The major scientific goals of our program are: (1) the morphology of the NLR; (2) the physical conditions and dynamics of individual clouds in the NLR; (3) the structure and physical conditions of the warm reflecting gas; (4) the structure of the obscuring torus; (5) the population and morphology of nuclear disks/tori in AGN; (6) the physical conditions in nuclear disks; and (7) the masses of central black holes in AGN. We will use the Hubble Space Telescope (HST) to obtain high-resolution images and spatially resolved spectra. Far-UV spectroscopy of emission and absorption in the nuclear regions using HST/FOS and the Hopkins Ultraviolet Telescope (HUT) will help establish physical conditions in the absorbing and emitting gas. By correlating the dynamics and physical conditions of the gas with the morphology revealed through our imaging program, we will be able to examine mechanisms for fueling the central engine and transporting angular momentum. The kinematics of the nuclear gas disks may enable us to measure the mass of the central black hole. Contemporaneous X-ray observations using ASCA will further constrain the ionization structure of any absorbing material. Monitoring of variability in the UV and X-ray absorption will be used to determine the location of the absorbing gas, possibly in the outflowing warm reflecting gas, or the broad-line region, or the atmosphere of the obscuring torus. Supporting ground-based observations in the optical, near-IR, imaging polarimetry, and the radio will complete our picture of the nuclear structures. With a comprehensive survey of these characteristics in a complete sample of nearby AGN, our conclusions should be more reliably extended to AGN as a class.

Kriss, Gerard A.↗
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 NTRS2002

A New Statistically based Autoconversion rate Parameterization for use in Large-Scale Models

The autoconversion rate is a key process for the formation of precipitation in warm clouds. In climate models, physical processes such as autoconversion rate, which are calculated from grid mean values, are biased, because they do not take subgrid variability into account. Recently, statistical cloud schemes have been introduced in large-scale models to account for partially cloud-covered grid boxes. However, these schemes do not include the in-cloud variability in their parameterizations. In this paper, a new statistically based autoconversion rate considering the in-cloud variability is introduced and tested in three cases using the Canadian Single Column Model (SCM) of the global climate model. The results show that the new autoconversion rate improves the model simulation, especially in terms of liquid water path in all three case studies.

Lin, Bing↗
DOE OSTI2023

Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model

Abstract The Department of Energy (DOE)’s Energy Exascale Earth System Model (E3SM), including its atmosphere model (EAM), has many relatively new features. In a previous study we conducted a systematic parametric sensitivity analysis for EAM based on short, perturbed parameter ensemble (PPE) simulations, mainly focusing on global mean climate features and metrics. While parameter values in global climate models are generally invariant in space and time, model response to parameters perturbation may vary by regions and climate regimes, which motivates the need to better understand the EAM model behaviors and physics at regional scale and process level. In this study, using the same set of PPE simulations and a similar sensitivity analysis framework, we identify parameters that cause largest sensitivities over different regions and compare model responses in fast atmospheric processes to the parameters across different cloud regimes for several important cloud-related fidelity metrics. We find that cloud forcing has opposite response to some parameters over mid-latitude vs. tropical land. We also analyze how the parametric sensitivity varies as stratocumulus transitions to shallow convection and to deep convection over ocean. Low cloud forcing and shortwave cloud forcing in the subtropical eastern Pacific are most sensitive to the parameters controlling the width of the probability density function (PDF) of the subgrid vertical velocity ( w’ ) ( gamma ) and the damping of the w’ skewness ( c8 ) near the coast but become more sensitive to the parameter affecting the damping of the w’ variance ( c1 ) further offshore. Detailed interpretation of the spatial dependence of parametric sensitivity is provided. We also investigate how the parametric sensitivity evolves with prediction duration. This study improves our process-level understanding of cloud physics and parameterization and provides insights for developing more advanced regime-aware parameterization schemes in global climate model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Moist Physics Parameterization Based on Deep Learning

Abstract Current moist physics parameterization schemes in general circulation models (GCMs) are the main source of biases in simulated precipitation and atmospheric circulation. Recent advances in machine learning make it possible to explore data‐driven approaches to developing parameterization for moist physics processes such as convection and clouds. This study aims to develop a new moist physics parameterization scheme based on deep learning. We use a residual convolutional neural network (ResNet) for this purpose. It is trained with 1‐year simulation from a superparameterized GCM, SPCAM. An independent year of SPCAM simulation is used for evaluation. In the design of the neural network, referred to as ResCu, the moist static energy conservation during moist processes is considered. In addition, the past history of the atmospheric states, convection, and clouds is also considered. The predicted variables from the neural network are GCM grid‐scale heating and drying rates by convection and clouds, and cloud liquid and ice water contents. Precipitation is derived from predicted moisture tendency. In the independent data test, ResCu can accurately reproduce the SPCAM simulation in both time mean and temporal variance. Comparison with other neural networks demonstrates the superior performance of ResNet architecture. ResCu is further tested in a single‐column model for both continental midlatitude warm season convection and tropical monsoonal convection. In both cases, it simulates the timing and intensity of convective events well. In the prognostic test of tropical convection case, the simulated temperature and moisture biases with ResCu are smaller than those using conventional convection and cloud parameterizations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Abundance of atomic carbon /C I/ in dense interstellar clouds

The abundance of interstellar neutral atomic carbon is investigated by means of its ground state fine-structure line emission at 492 GHz using the 91.5 cm telescope of NASAs Kuiper Airborne Observatory. Atomic carbon is found to be very abundant in dense interstellar molecular clouds with column densities of about 10 to the 19th per sq cm. Because the observations have considerably greater column densities than current theories of carbon chemistry, it is suggested that the physical conditions of these clouds are not as simple as assumed in the models. Various situations are discussed which would lead to large C I abundances, including the possibility that the chemical lifetimes of the clouds are relatively short.

Phillips, T. G.↗
NASA NTRS1983

An investigation of sulfate production in clouds using a flow-through chemical reactor model approach

A flow-through chemical reactor model is developed to describe the mass transfer and chemical processes that atmospheric gases undergo in clouds. The model includes the simultaneous absorption of SO2, NH3, O3, NO(x), HNO3, CO2 and H2O2, the accompanying dissociation and oxidation reactions in cloud water, considers electrical neutrality, and includes qualitative parameterization of cloud microphysics. The model is used to assess the importance of the oxidation reactions H2O2-S(IV), O3-S(IV), and S(IV)-Mn(2+) catalysis, and the effects of cloud parameters such as drop size, rain intensity, liquid water content, and updraft velocity. Both precipitating and nonprecipitating clouds are studied. Model results predict sulfate production rates varying from 3 percent/hr to 230 percent/hr. The actual rate is highly dependent on the chemical composition of the uptake air and the physical conditions of the cloud. Model results also show that both the H2O2 and the O3 oxidation reactions can be significant.

Hong, M. S.↗