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NASA NTRS2006

Electron Velocity Distribution Function in Magnetic Clouds in the Solar Wind

We present a study of the kinetic properties of the electron velocity distribution functions within magnetic clouds, since they are the dominant thermal component. The study is based on high time resolution data from the GSFC WIND/SWE electron spectrometer and the Berkeley 3DP electron plasma instruments. Recent studies on magnetic clouds have shown observational evidence of anti-correlation between the total electron density and electron temperature, which suggest a polytrope law P(sub e) = alpha(Nu(sub e) (sup gamma)) for electrons with the constant gamma approximates 0.5 < 1. This anti-correlation and small polytropic gamma-values is interpreted in the context of the presence of highly non-Maxwellian electron distributions (i.e. non-thermal) within magnetic clouds. These works suggested that the non-thermal electrons can contribute as much as 50% of the total electron pressure within magnetic clouds. We have revisited some of the magnetic cloud events previously studied and attempted to quantify the nature of the non-thermal electrons by modeling the electron velocity distribution function using a kappa distribution function to characterize the kinetic non-thermal effects. If non-thermal tail effects are the source for the anti-correlation between the moment electron temperature and density and if the kappa distribution is a reasonable representative model of non-thermal effects, then the electron velocity distribution within magnetic clouds should show indication for small K-values when gamma < 1.

Nieves-Chinchil, Teresa↗

NASA NTRS2010

Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. Also included are the clear column radiances used to derive these products which are representative of the radiances AIRS would have seen if there were no clouds in the field of view. All products also have error estimates. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20 percent, in cases with up to 90 percent effective cloud cover. The products are designed for data assimilation purposes for the improvement of numerical weather prediction, as well as for the study of climate and meteorological processes. With regard to data assimilation, one can use either the products themselves or the clear column radiances from which the products were derived. The AIRS Version 5 retrieval algorithm is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates for retrieved quantities and clear column radiances, and the use of these error estimates for Quality Control. The temperature profile error estimates are used to determine a case-by-case characteristic pressure pbest, down to which the profile is considered acceptable for data assimilation purposes. The characteristic pressure p(sub best) is determined by comparing the case dependent error estimate (delta)T(p) to the threshold values (Delta)T(p). The AIRS Version 5 data set provides error estimates of T(p) at all levels, and also profile dependent values of pbest based on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

Susskind, Joel↗

NASA NTRS1991

Corona-producing cirrus cloud properties derived from polarization lidar and photographic analyses

Polarization lidar data are used to demonstrate that clouds composed of hexagonal ice crystals can generate multiple-ringed colored coronas. Although relatively uncommon in the mid-latitude cirrus sample, the coronas are associated with unusual cloud conditions that appear to be effective in generating the displays. Invariably, the cirrus cloud tops are located at or slightly above elevated tropopauses at temperatures between -60 and -70 C. The cloud top region also generates relatively strong laser backscattering and unusually high 0.5-0.7 linear depolarization ratios. Color photograph analysis of corona ring angles indicates crystals with mean diameters of from 12 to 30 microns. The cirrus cloud types were mainly subvisual to thin cirrostratus, but also included fibrous cirrus. Estimated cloud optical thicknesses at the 0.694-micron laser wavelength ranged from about 0.001 to 0.2, where the upper limit reflects the effects of multiple scattering and/or unfavorable changes in particle characteristics in deep cirrus clouds.

Sassen, Kenneth↗

NASA NTRS1981

Climate sensitivity of a one-dimensional radiative-convective model with cloud feedback

The potential complexity of the feedback between global mean cloud amount and global mean surface temperature when variations of the vertical cloud distribution are included is illustrated. This is done by studying the behavior of a one-dimensional radiative-convective model with two types of cloud variation: (1) variable cloud cover with constant optical thickness and (2) variable optical thickness with constant cloud cover. The variable parameter is calculated on the assumption that a correlation exists between cloud amount and precipitation or the vertical flux convergence of latent heat. Since the vertical latent heat flux is taken to be a fraction of the total heat flux, modeled by convective adjustment, the sensitivity of the results to two different critical lapse rates is examined. These are a constant 6.5 K/km lapse rate and a temperature-dependent, moist adiabatic lapse rate. The effects of the vertical structure of climate perturbations on the nature of the cloud feedback are also examined. The model results reveal that changes in the vertical cloud distribution and mean cloud optical thickness can be as important to climate variations as are changes in the total cloud cover.

Wang, W.-C.↗

NASA NTRS2003

Early Results from AIRS/AMSU/HSB

AIRS was launched on EOS Aqua on May 5, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infiared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis.

Susskind, Joel↗

NASA NTRS2005

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. HSB failed in February 2005, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC in April 2005 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Susskind, Joel↗

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↗

NASA NTRS2016

The Inner Edge of the Habitable Zone for Synchronously Rotating Planets Around Low-Mass Stars Using General Circulation Models

Terrestrial planets at the inner edge of the habitable zone (HZ) of late-K and M-dwarf stars are expected to be in synchronous rotation, as a consequence of strong tidal interactions with their host stars. Previous global climate model (GCM) studies have shown that, for slowly rotating planets, strong convection at the substellar point can create optically thick water clouds, increasing the planetary albedo, and thus stabilizing the climate against a thermal runaway. However these studies did not use self-consistent orbital/rotational periods for synchronously rotating planets placed at different distances from the host star. Here we provide new estimates of the inner edge of the HZ for synchronously rotating terrestrial planets around late-K and M-dwarf stars using a 3D Earth-analog GCM with self-consistent relationships between stellar metallicity, stellar effective temperature, and the planetary orbital/rotational period. We find that both atmospheric dynamics and the efficacy of the substellar cloud deck are sensitive to the precise rotation rate of the planet. Around mid-to-late M-dwarf stars with low metallicity, planetary rotation rates at the inner edge of the HZ become faster, and the inner edge of the HZ is farther away from the host stars than in previous GCM studies. For an Earth-sized planet, the dynamical regime of the substellar clouds begins to transition as the rotation rate approaches ∼10 days. These faster rotation rates produce stronger zonal winds that encircle the planet and smear the substellar clouds around it, lowering the planetary albedo, and causing the onset of the water-vapor greenhouse climatic instability to occur at up to ∼25% lower incident stellar fluxes than found in previous GCM studies. For mid-to-late M-dwarf stars with high metallicity and for mid-K to early-M stars, we agree with previous studies.

Planet and satellite atmospheres↗

NASA NTRS1972

On radiational cooling computations in clouds.

Expressions are derived for the cooling or heating rates for clouds in which the condensed phase is either ice or water. Values are computed for ice and water clouds over a reasonable temperature range for pressures of 1000, 500, and 200 mb. The importance is shown of adequately allowing for the latent load in computations of radiative cooling or heating rates based on measurements of radiative divergence in clouds. It is shown that, other things being equal, the effect of the latent load is always greatest at low levels and higher temperatures.

Knollenberg, R. G.↗

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 NTRS1973

Hot H2 and interstellar shocks

The rotational excitation of H2 molecules by interstellar shock waves is calculated. Level populations integrated through a shock in a cloud with a density of 10 per cu cm have nearly exponential distributions, with effective rotational temperatures T sub r = 15 V to the 1.5 power K, where V is the shock velocity in km/sec. Ortho-para conversion is effective for high shock velocities, but not for low ones, so that the degree of alternation of intensities of rotational lines in the Lyman absorption band should be correlated with V, and therefore with T sub 2. The results are compared with observations of H2 rotational levels made by the Copernicus satellite.

Aannestad, P. A.↗

NASA NTRS1974

20 to 40 micron spectroscopy of the Orion Nebula

Attention is given to a moderate-resolution spectra of the Orion Nebula. Observational data are presented between 20 and 40 microns. Several models are shown that attempt to account for all of the observations from 20 microns to 1 mm. A model in which the dust within the molecular cloud has a clumpy distribution is given. Data show that the individual clumps have effective grain temperatures of 100 deg K and they are optically thick for wavelengths shorter than 400 microns.-

Houck, J. R.↗

NASA NTRS2012

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

Stubenrauch, C. J.↗

NASA NTRS2013

Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from MODIS

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Cloud Properties Observations↗

NASA NTRS1984

The climatic effects of nuclear war

The effects of various US-USSR nuclear-exchange scenarios on global climate are investigated by means of computer simulations, summarizing the results of Turco et al. (1983) and follow-up studies using 3D global-circulation models. A nuclear-scenario model is used to determine the amounts of dust, smoke, radioactivity, and pyrotoxins generated by a particular type of nuclear exchange (such as a general 5,000-Mt exchange, a 1,000-Mt limited exchange, a 5,000-Mt hard-target counterforce attack, and a 100-Mt attack on cities only): a particle-microphysics model predicts the evolution of the dust and smoke particles; and a radiative-convective climate model estimates the effects of the dust and smoke clouds on the global radiation budget. The findings are presented in graphs, diagrams, and a table. Thick clouds blocking most sunlight over the Northern Hemisphere midlatitudes for weeks or months and producing ground-temperature reductions of 20-40 C, disruption of global circulation patterns, and rapid spread of clouds to the Southern Hemisphere are among the 'nuclear-winter' effects predicted for the 5,000-Mt baseline case. The catastrophic consequences for plant, animal, and human populations are considered, and the revision of superpower nuclear strategies is urged.

Turco, R. P.↗

DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗

DOE OSTI2025

Multiscale ACI Satellite Database

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1980

Greenhouse models of Venus' high surface temperature, as constrained by Pioneer Venus measurements

Recent measurements conducted from the Pioneer Venus probes and orbiter have provided a significantly improved definition of the solar net flux profile, the gaseous composition, temperature structure, and cloud properties of Venus' lower atmosphere. Using these data, we have carried out a series of one-dimensional radiative-convective equilibrium calculations to determine the viability of the greenhouse model of Venus' high surface temperature and to assess the chief contributors to the greenhouse effect. New sources of infrared opacity include the permitted transitions of SO2, CO, and HCl as well as opacity due to several pressure-induced transitions of CO2. We find that the observed surface temperature and lapse rate structure of the lower atmosphere can be reproduced quite closely with a greenhouse model that contains the water vapor abundance reported by the Venera spectrophotometer experiment. Thus the greenhouse effect can account for essentially all of Venus' high surface temperature. The prime sources of infrared opacity are, in order of importance, CO2, H2O, cloud particles, and SO2, with CO and HCl playing very minor roles.

Pollack, J. B.↗