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At least 577 records · Page 32

The Role of Data Assimilation in the Study of Regional and Global Variability of the Hydrological Cycle

In the coming years, researchers will have at their disposal a host of new observations from advanced space-based sensors (e.g. the Tropical Rainfall Measuring Mission, EOS Terra and PM missions) providing, among other things, a more complete and accurate description of various components of the Earth's hydrological cycle. Also, increasingly more sophisticated and comprehensive geophysical models will provide researchers better tools for simulating the hydrological cycle, and for carrying out mechanistic studies of the role of moist processes in the climate system. In addition, new data sets generated with global four-dimensional data assimilation (4DDA) systems will provide comprehensive and complete information on both the state and forcing of the climate system. Ideally, the 4DDA systems optimally incorporate all relevant information from the observations together with a first guess from a state-of-the-art geophysical model to produce a "best" estimate of the climate state. Furthermore, to the extent that the assimilating models are realistic and are constrained by the observations, they should provide reliable estimates of the associated physical processes or climate forcing fields. While operational weather centers now have a considerable history of providing reliable estimates of the basic atmospheric state variables, the associated processes or diagnostic fields (which are less well constrained by the observations and sensitive to errors in the model's physical parameterizations) are still considered experimental and of uncertain quality. In this study we will examine the current generation of reanalysis products to assess the capabilities of 4DDA systems to represent components of the hydrological cycle. The focus is on the role of the model in providing consistent estimates of moist processes. We will also assess whether current observations provide sufficient constraints on these model- generated fields.

Schubert, Siegfried↗

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were sigmficantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-china peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and gradient, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation apd associated moisture transport and convection.

Wang, Yansen↗

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were significantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-China peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and merit, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation and associated moisture transport and convection.

Wang, Yansen↗

An Ensemble Investigation of the Causes for Regional Air-Quality Model Critical Load Exceedances Prediction Variability in European and North American Domains Using Diagnostics From Phase 4 of the Air Quality Model Evaluation International Initiative

We summarize tentative findings from multi air quality model ensembles for the years 2009 and 2010 in Europe (EU), and 2010 and 2016 in North America (NA), under AQMEII-4. The model predictions of sulphur and nitrogen deposition were used to estimate exceedances of critical loads for acidification and eutrophication, to show the extent to which the ensemble members agree in the magnitude and the trend of ecologically meaningful impacts. Model exceedance variability was analyzed using AQMEII-4 diagnostics. Evaluation against concentration and wet deposition observations, coupled with these diagnostics, identified specific process representations as the causes for variability between model predictions and for reduced model performance. All models predicted reductions in ecosystem acidification impacts in North America between the years 2010 and 2016, in accord with SO2 emissions reduction legislation which started in 2010 (SO2 SIP) However, all models in EU and NA domains had net negative biases for wet deposition of sulphur and nitrogen relative to observations. The wet S deposition average mean bias for the NA ensemble was -0.17 eq ha-1 d-1, and for the EU ensemble -1.15 eq ha-1 d-1. The NA daily wet deposition average mean bias for NH4+ was -0.37 eq ha-1d-1; EU -1.19 eq ha-1 d-1. The daily NA wet NO3- deposition average mean bias was -0.24 eq ha-1d-1; EU -0.69 eq ha-1 d-1. The members of the ensemble diverged (factor of 10) in their North American predictions for Ndep and consequently their eutrophication exceedances. The models with the highest eutrophication predictions also predicted the highest levels of gas-phase ammonia dry deposition (standard deviation of ammonia dry deposition flux across ensemble members was larger than the ensemble average). These models also had negative biases of predicted ammonia concentrations; average mean biases of -0.63 (satellite NH3) and -0.85 ppbv (surface NH3) compared to ensemble averages of -0.30 and -0.34 ppbv. Diagnostics showed that these differences resulted from the manner in which bidirectional ammonia fluxes were parameterized within these models. The second largest source of NA eutrophication prediction variability were models with positive biases in particulate ammonium and nitrate concentrations, and higher particle nitrogen deposition levels ( particle ammonium concentration bias +0.35 ug m-3; ensemble bias +0.15 ug m-3). We believe two factors may have led to these latter overestimates: higher levels of fine mode particle nitrate formation compared to other models (due to the use of an inorganic heterogeneous chemistry algorithm which did not take base cation chemistry into account), and updates to particle dry deposition velocities carried out in the absence of concurrent updates to wet scavenging algorithms. The relative importance of dry gas, dry particulate, and wet deposition towards total sulphur and nitrogen deposition totals differed between EU and North American domains, though all models had negative biases in wet deposition as noted above. Parallel and subsequent work suggests that multiphase hydrometeor scavenging may improve model wet deposition performance. An increased research focus is recommended for four model processes: multiphase hydrometeor scavenging, ammonia bidirectional fluxes, base cation chemistry and emissions, and particle dry deposition.

regional air-quality model↗

Sea breeze-induced mesoscale systems and severe weather

The relationship between thunderstorm activity during the summer months along coastal regions of the Atlantic and Gulf coasts and the dry sea breeze circulation was investigated. Satellite composites of thunderstorm activity for synoptically undisturbed conditions have been obtained for south Florida for a series of days in the summer of 1983. These data were catalogued into different low level synoptic flow regimes. Five synoptic flow regimes were found from the data. A three-dimensional mesoscale numerical model was used for each sysnoptic flow regime to quantitatively predict the location of enhanced thunderstorm activity. This model includes a parameterization of vegetation and soil moisture feedbacks as well as a sophisticated planetary boundary layer representation. Using the results of the satellite image composites, spatial and temporal characteristics of deep convective cloud patterns and their variation with synoptic flow are described. The results from the numerical model have provided explanations for the observed patterns.

Pielke, R. A.↗

Simulation of the zonal mean climatology of the middle atmosphere with a three-dimensional spectral model for solstice and equinox conditions

A 3D spectral model was used to simulate the zonal mean state of the middle atmosphere for solstice and equinox conditions. The model incorporates realistic parameterizations of atmospheric infrared cooling and a gravity wave formulation based on a combination of Lindzen's (1981) and Matsuno's (1982) approaches. The temperature distributions for both seasons and the zonal wind distribution for solstice are found to be in satisfactory agreement with the empirical model of Fleming et al. (1988). Net vertical fluxes of horizontal momentum are in good agreement with systematic observations of gravity waves in the middle atmosphere.

Akmaev, R. A.↗

A Contemporary Analysis of the O'Neill-Glaser Model for Space-Based Solar Power and Habitat Construction

In 1975 Gerard O Neill published in the journal Science a model for the construction of solar power satellites. He found that the solar power satellites suggested by Peter Glaser would be too massive to launch economically from Earth, but could be financially viable if the workforce was permanently located in free space habitats and if lunar and asteroid materials were used for construction. All new worldwide electrical generating capacity could be then achieved by solar power satellites. The project would financially break even in about 20 years after which it would generate substantial income selling power below fossil fuel prices. Two NASA / Stanford University led studies at Ames Research center during the summers of 1974 and 1976 found the concept technically sound and developed a detailed financial parametric model. Although the project was not undertaken when suggested in the 1970s, several contemporary issues make pursuing the O Neill -- Glaser concept more compelling today. First, our analysis suggests that if in the first ten years of construction that small habitats (compared to the large vista habitats envisioned by O Neill) supporting approximately 300 people were utilized, development costs of the program and the time for financial break even could be substantially improved. Second, the contemporary consensus is developing that carbon free energy is required to mitigate global climate change. It is estimated that 300 GW of new carbon free energy would be necessary per year to stabilize global atmospheric carbon. This is about 4 times greater energy demand than was considered by the O Neill Glaser model. Our analysis suggests that after the initial investments in lunar mining and space manufacturing and transportation, that the profit margin for producing space solar power is very high (even when selling power below fossil fuel prices). We have investigated the financial scaling of ground launched versus space derived space solar power satellites. We find that for the carbon mitigation case even modernized ground launched space solar power satellites are not financially viable. For space derived solar power satellites, however, the increased demand makes them break even substantially sooner and yield much higher profit. Third, current awareness is increasing about the dangers of humanity remaining a single planet species. Our technological power has been increasing relative to the size of the planet Earth. Since the middle of the 20th century our technological power has grown large relative to our planet's size. This presents a very real potential for human self-extinction. We argue that the potential for human self-extinction is increasing with time in proportion to the exponential growth of our technological power making self-extinction likely within this century if humanity remains a single planet species. The O Neill model of multiple independent free space habitats, it is argued, can protect humanity from extinction in the same way that portfolio diversification protects ones assets from total loss. We show that about 1 million people for the electricity only case, and about 1 billion people for the carbon mitigation case, can be provided with permanent space habitats and transportation from Earth in 30 years and can be funded by the space derived solar power satellite program. 1.2 Scope of this Chapter The goal of this chapter is to illustrate the power and importance of the O'Neill-Glaser concept in the context of human survival and maintaining a healthy planet Earth. We argue that at this point in human history our technological power is too dangerous to our selves and our home planet for us not to expand into space. We show by the models presented in the chapter that the imminent dangers of global warming and human self-extinction mandate that humanity move aggressively into the solar system in this generation. We show that the production of solar power satellites using space resources and with a work foe living in space provides a viable financial model to mitigate CO2 preventing the worst global warming scenarios, and safeguards humanity against self-extinction by providing hundreds of habitats and a billion people living in space within about 35 years. To accomplish this goal we need only consider the classic O'Neill-Glaser model which was parameterized for 1970's technological projections. Only habitat size optimization for the first ten years of production is added. This is a conservative approach since the innovations of the last 30 years will make the financial projections more favorable. However, the classic O'Neill-Glaser model represented a broad technological consensus. The model is well documented in the references and our calculations can be easily reproduced In this chapter the economics of the O Neill - Glaser model is compared with models that rely exclusively on Earth launched materials. Although many studies of Earth launched Solar Power Satellites have been made, we found that the NASA "Fresh Look Study" was the most comprehensive and well documented. It also provided one of the most optimistic Earth launch financial projections. We thus chose it for comparison purposes.

Curreri, Peter A.↗

A Survey of Modeling Activities by NASA’s Orbital Debris Program Office

NASA’s Orbital Debris Program Office (ODPO) develops and maintains a number of modeling tools to analyze and simulate the orbital debris environment. One of the most important products produced by the NASA ODPO is the Orbital Debris Engineering Model (ORDEM). This model can be used by satellite designers and operators to design missions for better protection against the debris environment. The ODPO is currently working on the next generation, designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and the ability to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. A new addition will be a parameterized debris shape model based on laboratory hypervelocity impact tests, including DebriSat. ORDEM is primarily based on dedicated debris measurements, such as by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, and observations of geosynchronous orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). In addition to ORDEM, the ODPO also maintains other models, such as the LEO-to-GEO Environment Debris (LEGEND) model for studies of long-term evolution of Earth’s debris environment, with the ability to study various mitigation and remediation strategies. Another model, the Satellite Breakup Risk Assessment Model (SBRAM), is used to analyze how satellite breakups may affect critical space missions (such as the ISS) on short notice. In addition to these models, the ODPO maintains other secondary models used to model satellite explosions and collisions, analyze radar, optical, and in situ data, and to model such things as solar activity and orbit evolution. In this presentation, a survey of these models will be presented, showing how the different models are used together to create a comprehensive picture of Earth’s debris environment.

Mark Matney↗

Uptake, Efflux, and Sequestration of Mercury in the Asian Clam, Corbicula fluminea , at Environmentally Relevant Concentrations, and the Implications for Mercury Remediation

(1) Mercury (Hg) is a persistent, ubiquitous contaminant that readily biomagnifies into higher trophic level species in aquatic environments across the globe. It is crucial to understand the movement of environmentally relevant concentrations of Hg in impacted freshwater streams to minimize risks to ecological and human health. (2) The bioconcentration kinetics of aqueous Hg exposure (20, 100, and 200 ng/L) in the invasive Asian Clam, Corbicula fluminea, were measured. A toxicokinetic model, the first parameterized for Hg accumulation in freshwater clams, was developed to estimate uptake and efflux parameters and compared to previous parameter values estimated for other mollusk species. (3) Results demonstrated that even at low Hg concentrations, Corbicula record signals of contamination through bioconcentration, and both direct measurement and toxicokinetic models demonstrate large Hg bioconcentration factors (as high as 1.34 × 10 5 mL/g dry tissue), similar to partitioning coefficients seen in engineered Hg sorbents. (4) Our study found that Corbicula accumulated Hg at aqueous concentrations relevant to impacted streams, but well below regulatory drinking water limits, demonstrating their utility as a sensitive sentinel species and potential bioremediator.

bioaccumulation↗

Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

The research objective of this NASA grant-funded project was to determine in detail how large-scale processes. in combination with cloud-scale radiative, microphysical, and dynamical processes, govern the formation and multi-layered structure of Arctic stratus clouds. This information will be useful for developing and improving 1D (one dimensional) boundary layer models for the Arctic. Also, to quantitatively determine the effects of leads on the large-scale budgets of sensible heat, water vapor, and condensate in a variety of Arctic winter conditions. This information will be used to identify the most important lead-flux processes that require parameterization in climate models. Our approach was to use a high-resolution numerical model, the 2D (two dimensional) University of Utah Cloud Resolving Model (UU CRM), and its 1D version, the University of Utah Turbulence Closure Model (UU TCM), a boundary layer model based on third-moment turbulence closure, as well as a large-eddy simulation (LES) model originally developed by C.H. Moeng.

Kruegen, Steven K.↗

Optimal parameterizations for observational constraints on thawing dark energy

Time-varying dark energy is often modeled in observational analyses through generic parameterizations of its equation of state w(z), which typically use two free parameters {w 0 , w a } to span a broad range of behaviors as a function of redshift. However, this broad range of behaviors can only approximately capture the dynamics of any given microphysical theory of dark energy. A complementary approach is to use targeted parameterizations designed to model specific classes of dynamical dark energy with greater precision. Focusing on the class of thawing dark energy, we quantify and compare the precision with which nineteen generic and targeted parameterizations can capture the dynamics of physically motivated thawing quintessence theories. We find that a targeted parameterization derived from a Padé expansion of w is the most reliable of these, producing accurate reconstructions of w(z), the expansion history H(z), and cosmological parameters such as H 0 and Ω m for a broad range of microphysical theories.

dark energy experiments↗

Aura MLS Cloud Measurements: First-Year Results

Aura MLS provides the first vertical upper tropospheric cloud profiling from space, enabling global survey of the vertical structure of cloud systems, with seasonal and geographical variations, needed to evaluate the way clouds are parameterized in global models, thereby contributing to the understanding of cloud-climate feedbacks, and improved weather and climate predictions. The vertical structure of cloud systems is fundamentally important for understanding how clouds affect both their regional and large-scale atmospheric and radiative environments. The regional cloud profiles provide a critical tests of important parameterizations that enable the calculation of radiative flux profiles and heating rates throughout the atmospheric column, which in turn also regulates the water and energy cycles in the upper troposphere

Microwave Limb Sounder (MLS)↗

The annual pressure cycle on Mars: Results from the LMD Martian atmospheric general circulation model

We have been developing a General Circulation Model (GCM) of the martian atmosphere since 1989. The model has been described rather extensively elsewhere and only the main characteristics are given here. The dynamical part of the model, adapted from the LMD terrestrial climate model, is based on a finite-difference formulation of the classical 'primitive equations of meteorology.' The radiative transfer code includes absorption and emission by CO2 (carefully validated by comparison to line-by-line calculations) and dust in the thermal range and absorption and scattering by dust in the visible range. Other physical parameterizations are included: modeling of vertical turbulent mixing, dry convective adjustment (in order to prevent vertical unstable temperature profiles), and a multilayer model of the thermal conduction in the soil. Finally, the condensation-sublimation of CO2 is introduced through specification of a pressure-dependent condensation temperature. The atmospheric and surface temperatures are prevented from falling below this critical temperature by condensation and direct precipitation onto the surface of atmospheric CO2. The only prespecified spatial fields are the surface thermal inertia, albedo, and topography.

Hourdin, Frederic↗

High-Fidelity Flash Lidar Model Development

NASA's Autonomous Landing and Hazard Avoidance Technologies (ALHAT) project is currently developing the critical technologies to safely and precisely navigate and land crew, cargo and robotic spacecraft vehicles on and around planetary bodies. One key element of this project is a high-fidelity Flash Lidar sensor that can generate three-dimensional (3-D) images of the planetary surface. These images are processed with hazard detection and avoidance and hazard relative navigation algorithms, and then are subsequently used by the Guidance, Navigation and Control subsystem to generate an optimal navigation solution. A complex, high-fidelity model of the Flash Lidar was developed in order to evaluate the performance of the sensor and its interaction with the interfacing ALHAT components on vehicles with different configurations and under different flight trajectories. The model contains a parameterized, general approach to Flash Lidar detection and reflects physical attributes such as range and electronic noise sources, and laser pulse temporal and spatial profiles. It also provides the realistic interaction of the laser pulse with terrain features that include varying albedo, boulders, craters slopes and shadows. This paper gives a description of the Flash Lidar model and presents results from the Lidar operating under different scenarios.

Hines, Glenn D.↗

Stress intensity factor models using mechanics-guided decomposition and symbolic regression

The finite element method can be used to compute accurate stress intensity factors (SIFs) for cracks with complex geometries and boundary conditions. In contrast, handbook solutions act as surrogate SIF models that provide significantly faster evaluation times. However, the development of conventional surrogate SIF models relies on manual development based on low-order parameterizations. This limits surrogate model accuracy and generalizability. Here, in this paper, we develop a framework for the automated development of mechanics-guided handbook SIF solutions by using interpretable machine learning via genetic programming for symbolic regression (GPSR). Formalizing the mechanics-based approach of Raju and Newman, SIF training data is decomposed into multiple subsets. This decomposition enables parallel GPSR model development of subfunctions, each of which accounts for specific geometrical corrections with respect to a known analytical model. Using this mechanics-based approach with GPSR allows for equations to be learned with improved accuracy and reduced complexity relative to the Raju Newman equations while maintaining the inherent interpretability of mathematical expressions. In this paper, we present equations that match the complexity of the Raju Newman equations while having reduced error, as well as equations with similar errors and reduced complexity.

42 ENGINEERING↗

Quiescent accretion disks in black hole X-ray novae

We present detailed time-resolved spectroscopy of the Balmer emission lines from two black hole binary systems in quiescence, A0620-00 and Nova Muscae 1991. We find extraordinary similarities between the two systems. There are 30-40 km/s velocity variations of the emission lines over the orbital period, the phases of which are not aligned with the expected phase of the motion of the compact primary. Detailed modeling of both systems is complicated by variable hot spot components, regions of optical thickness, and intermittent excess emission in the blue line wings of the H-alpha lines. Both sources also display low velocities at the outer edge of the accretion disk, implying a large primary Roche lobe and extreme mass ratios. These complications suggest that although simple optically thin, Keplerian alpha-disk models provide a useful parameterization of emission lines from these systems, the straightforward physical models they imply should be treated with great caution.

Orosz, Jerome A.↗

Modeling of the Magnetosphere-Ionosphere-Atmosphere System

This grant covered the transition period between the ISTP/GGS main mission MAMI work (NAGW5-1097) to the extended mission of GGS/SolaxMax. During this period we concentrated on the following subjects: (1) Ionospheric modeling and in particular the coupling of the ionosphere and the magnetosphere require knowledge of the ionospheric conductances. We have an algorithm to derive these conductances from POLAR UVI or POLAR VIS images. The image analysis requires carefully calibrated measurements, separation of auroral brightness from scattered solar EUV and emissions caused by photoelectrons, and modeling of the auroral conditions, Under this grant we evaluated the various sources of uncertainty that contribute to the conductance calculation by comparing different model approaches and we conducted sensitivity studies. A joint modeling effort between our ionospheric models and a global MHD magnetospheric model with S. Slinker and J. Fedder lead to improved parameterizations for the MHD model. The predictions of that new model were validated using data from ground based instruments, POLAR UVI images, and DMSP satellites. These findings were presented at the GEM meeting in Snowmass, and at the Huntsville modeling workshop in Guntersville. A manuscript for publication is in preparation. A study to evaluate the thermospheric effects of large substorms and storms was con- ducted with the TIE-GCM model. Of particular interest are compositional changes of the thermosphere in the southern hemisphere. Southern hemisphere effects are stronger than those on the northern hemisphere because of the larger offset of the magnetic dipole from the rotational axis. These results were presented at the Huntsville modeling workshop in Guntersville.

Source record↗

The Influence of Soil Moisture and Wind on Rainfall Distribution and Intensity in Florida

Land surface processes play a key role in water and energy budgets of the hydrological cycle. For example, the distribution of soil moisture will affect sensible and latent heat fluxes, which in turn may dramatically influence the location and intensity of precipitation. However, mean wind conditions also strongly influence the distribution of precipitation. The relative importance of soil moisture and wind on rainfall location and intensity remains uncertain. Here, we examine the influence of soil moisture distribution and wind distribution on precipitation in the Florida peninsula using the 3-D Goddard Cumulus Ensemble (GCE) cloud model Coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data collected on 27 July 1991 in central Florida during the Convection and Precipitation Electrification Experiment (CaPE). The idealized numerical experiments consider a block of land (the Florida peninsula) bordered on the east and on the west by ocean. The initial soil moisture distribution is derived from an offline PLACE simulation, and the initial environmental wind profile is determined from the CaPE sounding network. Using the factor separation technique, the precise contribution of soil moisture and wind to rainfall distribution and intensity is determined.

Baker, R. David↗