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Physical conditions in molecular clouds
Recent developments have complicated the picture of the physical conditions in molecular clouds. The discoveries of widespread emission from high-J lines of CD and 12-micron IRAS emission have revealed the presence of considerably hotter gas and dust near the surfaces of molecular clouds. These components can complicate interpretation of the bulk of the cloud gas. Commonly assumed relations between column density or mean density and cloud size are called into question by conflicting results and by consideration of selection effects. Analysis of density and density structure through molecular excitation has shown that very high densities exist in star formation regions, but unresolved structure and possible chemical effects complicate the interpretation. High resolution far-IR and submillimeter observations offer a complementary approach and are beginning to test theoretical predictions of density gradients in clouds.
A physically-based retrieval of cloud liquid water from SSM/I measurements
A simple physical scheme is proposed for retrieving cloud liquid water over the ice-free global oceans from Special Sensor Microwave/Imager (SSM/I) observations. Details of the microwave retrieval scheme are discussed, and the microwave-derived liquid water amounts are compared with the ground radiometer and AVHRR-derived liquid water for stratocumulus clouds off the coast of California. Global distributions of the liquid water path derived by the method proposed here are presented.
Extraction of Profile Information from Cloud Contaminated Radiances
Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.
A survey of interstellar neutral potassium. I - Abundances and physical conditions in clouds toward 188 early-type stars
Observations of interstellar absorption in the resonance doublet 7664, 7698 A of neutral potassium toward 188 early-type stars at a spectral resolution of 8 km/s are reported. The 7664 A line is successfully separated from nearly coincident telluric O2 absorption for all but a few of the 165 stars for which K I absorption is detected, making possible an abundance analysis by the doublet ratio method. The relationships between the potassium abundances and other atomic abundances, the abundance of molecular hydrogen, and interstellar reddening are investigated.
Physics of debris clouds from hypervelocity impacts
The protection scheme developed for long duration space platforms relies primarily upon placing thin metal plates or 'bumpers' around flight critical components. The effectiveness of this system is highly dependent upon its ability to break up and redistribute the momentum of any particle which might otherwise strike the outer surface of the spacecraft. Therefore it is of critical importance to design the bumpers such that maximum dispersion of momentum is achieved. This report is devoted to an in-depth study into the design and development of a laboratory instrument which would permit the in-situ monitoring of the momentum distribution as the impact event occurs. A series of four designs were developed, constructed and tested culminating with the working instrument which is currently in use. Each design was individually tested using the Space Environmental Effects Facility (SEEF) at the Marshall Space Flight Center in Huntsville, Alabama. Along with the development of the device, an experimental procedure was developed to assist in the investigation of various bumper materials and designs at the SEEF. Preliminary results were used to compute data which otherwise were not experimentally obtainable. These results were shown to be in relative agreement with previously obtained values derived through other methods. The results of this investigation indicated that momentum distribution could in fact be measured in-situ as the impact event occurred thus giving a more accurate determination of the effects of experimental parameters on the momentum spread. Data produced by the instrument indicated a Gaussian-type momentum distribution. A second apparatus was developed and it was placed before the shield in the line of travel utilized a plate to collect impact debris scattered backwards. This plate had a passage hole in the center to allow the particle to travel through it and impact the proposed shield material. Applying the law of conservation of angular momentum a backward momentum vector was determined from the angular velocity of the plate. The forward scattered and backward scattered momentum values were then analyzed to judge the distribution of debris. Loss of momentum was attributed to the inaccuracies of the means of measurement. Assumptions of symmetrical debris for the forward and backward scattered directions also contributed to this loss.
A Goddard Multi-Scale Modeling System with Unified Physics
Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. 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 Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article.
Molecules in interstellar clouds
The physical conditions and chemical compositions of the gas in interstellar clouds are reviewed in light of the importance of interstellar clouds for star formation and the origin of life. The Orion A region is discussed as an example of a giant molecular cloud where massive stars are being formed, and it is pointed out that conditions in the core of the cloud, with a kinetic temperature of about 75 K and a density of 100,000-1,000,000 molecules/cu cm, may support gas phase ion-molecule chemistry. The Taurus Molecular Clouds are then considered as examples of cold, dark, relatively dense interstellar clouds which may be the birthplaces of solar-type stars and which have been found to contain the heaviest interstellar molecules yet discovered. The molecular species identified in each of these regions are tabulated, including such building blocks of biological monomers as H2O, NH3, H2CO, CO, H2S, CH3CN and H2, and more complex species such as HCOOCH3 and CH3CH2CN.
Star formation in protogalactic clouds
The physical processes determining the rate of star formation in protogalactic clouds and the resulting effects on the structure of the galaxies are examined with reference to analytical results and numerical simulations. For spheroidal systems, it is found that rapid star formation cannot be prevented once the density exceeds a typical value. The corresponding length scale is comparable to the length scales of spheroidal systems. The gas is converted into stars at a time scale of 2 Gyr or less, during which the total luminosity of the protogalaxy in ionizing photons is 10 exp 43-44 ergs/s, and the gas is enriched to solar abundance with a steep gradient. A simplistic analysis of the resulting stellar distribution finds that de Vaucouleurs profiles may naturally result. The Faber-Jackson relation is also found to follow naturally. The Fischer-Tully relation follows by an analysis similar to that used to derive the Faber-Jackson relation, provided that the peak rotational velocity is determined by the bulge mass.
Explicit Cloud Representation in the Atmos 1D Climate Model for Earth and Rocky Planet Applications
1D climate models are less sophisticated than 3D global circulation models (GCMs), however their computational time is much less expensive, allowing a large number of runs in a short period of time to explore a wide parameter space. Exploring parameter space is particularly important for predicting the observable properties of exoplanets, for which few parameters are known with certainty. Therefore, 1D climate models are still very useful tools for planetary studies. In most of these 1D models, clouds are not physically represented in the atmosphere, despite having a well-known, significant impact on a planetary radiative budget. This impact is simulated by artificially raising surface albedo, in order to reproduce the observed-averaged surface temperature (i.e. 288 K for modern Earth) and a radiative balance at the top of the atmosphere. This non-physical representation of clouds, causes atmospheric long wave and shortwaves fluxes to not match observational data. Additionally, this technique represents a parameter that is highly-tuned to modern Earth’s climate, and may not be appropriate for planets that deviate from modern Earth’s climate conditions. In this paper, we present an update to the climate model within the Atmos 1D atmospheric modeling package with a physical representation of clouds. We show that this physical representation of clouds in the atmosphere allows both long wave and shortwave fluxes to match observational data. This improvement will allow us to study the energy fluxes for a variety of cloudy rocky planets, and increase our confidence in future simulations of temperature profile and net energy balance.
A Multi-Scale Modeling System with Unified Physics
Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. In recent years, exponentially increasing computer power has extended cloud-resolving-mode1 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.
On the fragmentation of rotating interstellar clouds
Simple physical arguments are used to estimate the time scale for fragmentation of a collapsing, rotating, isothermal, interstellar cloud. This time scale is compared with a similarly estimated time scale for the collapse upon itself of a transitory ring structure. It is shown to be plausible for a cloud with a given ratio of rotational to gravitational energy (beta) that as the ratio of thermal to gravitational energy (alpha) is varied, there is an intermediate range of alpha where a ring forms and collapses on itself, prior to fragmentation. For higher or lower alpha, however, the cloud fragments prior to ring self-collapse. The analysis is compared with the results of numerical multidimensional, gravitational, hydrodynamical collapse and shown to be in good agreement with them.
On the Fragmentation of Rotating Interstellar Clouds
Simple physical arguments are used to estimate the time scale for fragmentation of a collapsing, rotating, isothermal, interstellar cloud. This time scale is compared with a similarly estimated time scale for the collapse upon itself of a transitory ring structure. It is shown to be plausible for a cloud with a given ratio of rotational to gravitational energy (beta) that as the ratio of thermal to gravitational energy (alpha) is varied, there is an intermediate range of alpha where a ring forms and collapses on itself, prior to fragmentation. For higher or lower alpha however, the cloud fragments prior to ring self-collapse. The analysis is compared with the results of numerical multidimensional, gravitational, hydrodynamical collapse and shown to be in good agreement with them.
Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.
Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.
Statistical Analyses of Satellite Cloud Object Data from CERES: Comparison with Cloud-Resolving Model Simulations of Tropical Convective Clouds - Part III
The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium- and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Ni o) and March 2000 (weak La Ni a). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud top height while it overestimates the differences in the observed outgoing longwave radiation and cloud top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and in space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems.
The geometry and physical properties of exhaust clouds generated during the static firing of S-1C and S-2 rocket engines
An experimental program was conducted during the static firing of the S-1C stage 13, 14, and 15 rocket engines and the S-2 stage 13, 14, and 15 rocket engines. The data compiled during the experimental program consisted of photographic recordings of the time-dependent growth and diffusion of the exhaust clouds, the collection of meteorological data in the ambient atmosphere, and the acquisition of data on the physical structure of the exhaust clouds which were obtained by flying instrumented aircraft through the clouds. A new technique was developed to verify the previous measurements of evaporation and entrainment of blast deflector cooling water into the cloud. The results of the experimental program indicate that at the lower altitudes the rocket exhaust cloud or plume closely resembles a free-jet type of flow. At the upper altitudes, where the cloud is approaching an equilibrium condition, structure is very similar to a natural cumulus cloud.
New Concepts for Refinement of Cumulus Parameterization in GCM's the Arakawa-Schubert Framework
Several state-of-the-art models including the one employed in this study use the Arakawa-Schubert framework for moist convection, and Sundqvist formulation of stratiform. clouds, for moist physics, in-cloud condensation, and precipitation. Despite a variety of cloud parameterization methodologies developed by several modelers including the authors, most of the parameterized cloud-models have similar deficiencies. These consist of: (a) not enough shallow clouds, (b) too many deep clouds; (c) several layers of clouds in a vertically demoralized model as opposed to only a few levels of observed clouds, and (d) higher than normal incidence of double ITCZ (Inter-tropical Convergence Zone). Even after several upgrades consisting of a sophisticated cloud-microphysics and sub-grid scale orographic precipitation into the Data Assimilation Office (DAO)'s atmospheric model (called GEOS-2 GCM) at two different resolutions, we found that the above deficiencies remained persistent. The two empirical solutions often used to counter the aforestated deficiencies consist of a) diffusion of moisture and heat within the lower troposphere to artificially force the shallow clouds; and b) arbitrarily invoke evaporation of in-cloud water for low-level clouds. Even though helpful, these implementations lack a strong physical rationale. Our research shows that two missing physical conditions can ameliorate the aforestated cloud-parameterization deficiencies. First, requiring an ascending cloud airmass to be saturated at its starting point will not only make the cloud instantly buoyant all through its ascent, but also provide the essential work function (buoyancy energy) that would promote more shallow clouds. Second, we argue that training clouds that are unstable to a finite vertical displacement, even if neutrally buoyant in their ambient environment, must continue to rise and entrain causing evaporation of in-cloud water. These concepts have not been invoked in any of the cloud parameterization schemes so far. We introduced them into the DAO-GEOS-2 GCM with McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme).
Cloud Thickness from Offbeam Returns - Thor Lidar
Physical thickness of a cloud layer, and sometimes multiple cloud layers, can be estimated from the time delay of off-beam returns from a pulsed laser source illuminating one side of the cloud layer. In particular, the time delay of light returning from the outer diffuse halo of light surrounding the beam entry point, relative to the time delay at beam center, determines the cloud physical thickness. The delay combined with the pulse stretch gives the optical thickness. The halo method works best for thick cloud layers, typically optical thickness exceeding 2, and thus compliments conventional lidar which cannot penetrate thick clouds. Cloud layer top and base have been measured independently over the ARM/SGP site using conventional laser ranging (lidar) and the top minus base thickness are compared with a cloud top halo estimate obtained from the NASA/Goddard THOR System (THOR = THickness from Offbeam Returns). THOR flies on the NASA P3, and measures the halo timings from several km above cloud top, at the same time providing conventional lidar cloud top height. The ARM/SGP micropulse lidar provides cloud base height for validation.