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Recent calculations of core collapse or massive stars result in explosive ejection of the mantle by a reflected shock. These hydrodynamic results are important for predictions of explosive nucleosynthesis and gamma-ray line emission from supernovae. Previous estimates, based on simple parameterized models or the nucleosynthesis in an average supernova, are compared with these latest results.
An approach to one-on-one air-combat analysis is described which employs discrete gaming of a parameterized model featuring choice between several closed-loop control policies. A preference-ordering formulation due to Falco is applied to rational choice between outcomes: win, loss, mutual capture, purposeful disengagement, draw. Approximate optimization is provided by an active-cell scheme similar to Falco's obtained by a 'backing up' process similar to that of Kopp. The approach is designed primarily for short-duration duels between craft with large-envelope weaponry. Some illustrative computations are presented for an example modeled using constant-speed vehicles and very rough estimation of energy shifts.
The techniques and a FORTRAN 77 MOdal Parameter IDentification (MOPID) computer program developed for identification of the frequencies and damping ratios of multiple flutter modes in real time are documented. Physically meaningful model parameterization was combined with state of the art recursive identification techniques and applied to the problem of real time flutter mode monitoring. The performance of the algorithm in terms of convergence speed and parameter estimation error is demonstrated for several simulated data cases, and the results of actual flight data analysis from two different vehicles are presented. It is indicated that the algorithm is capable of real time monitoring of aircraft flutter characteristics with a high degree of reliability.
The thermal history of the earth is investigated using a parameterized model of mantle convection, that includes the effects of volatile exchange between the mantle and the surface reservoir and the softening of the mantle by the dissolved volatiles. The mantle degassing rate is taken to be directly proportional to the rate of seafloor spreading which depends on the mantle heat flow. It is shown that the dependence of the mantle viscosity on the volatile content has important effects on the thermal evolution of planetary interiors and the evolution of planetary atmospheres. Degassing is compensated by an increase in temperature, while regassing is compensated by a decrease in temperature. Reasonable degassing scenarios can account for an early rapid formation of the earth's atmosphere inferred from noble gas abundances.
Data on neutrinos from SN 1987A are compared here with parameterized models of the neutrino emission using a consistent and straightforward statistical methodology. The empirically measured detector background spectra are included in the analysis, and the data are compared with a much wider variety of neutrino emission models than was explored previously. It is shown that the inferred neutrino emission model parameters are strongly correlated. The analysis confirms that simple models of the neutrino cooling of the nascent neutron star formed by the SN adequately explain the data. The inferred radius and binding energy of the neutron star are in excellent agreement with model calculations based on a wide range of equations of state. The results also raise the upper limit of the electron antineutrino rest mass to roughly 25 eV at the 95 percent confidence level, roughly 1.5-5 times higher than found previously.
Satellite measurements of the effect of clouds on the top of atmosphere radiative energy budget are used to validate model simulations from the National Center for Atmospheric Research Community Climate Model (NCAR CCM). The ability of the NCAR CCM to reproduce the monthly mean global distribution and temporal variability on both daily and seasonal time scales is assessed. The comparison reveals several deficiencies in the CCM cloud representation. Most notable are the difficulties in properly simulating the effect of clouds on the planetary albedo. This problem arises from discrepancies in the model's portrayal of low-level cloudiness and leads to significant errors in the absorbed solar radiation simulated by the model. The CCM performs much better in simulating the effect of clouds on the longwave radiation emitted to space, indicating its relative success in capturing the vertical distribution of cloudiness. The daily variability of the radiative effects of clouds in both the shortwave and longwave spectral regions is systematically overestimated. Analysis of the seasonal variations illustrates a distinct lack of coupling in the seasonal changes in the radiative effects of cloudiness between the tropics and mid-latitudes and between the Northern and Southern Hemisphere. Much of this problem also arises from difficulties in simulating low-level cloudiness, placing further emphasis on the need for better model parameterizations of boundary layer clouds.
The Burst And Transient Source Experiment (BATSE) has measured homogeneity and isotropy parameters from an increasingly large sample of observed gamma-ray bursts (GRBs), while also maintaining a summary of the way in which the sky has been sampled. Measurement of both of these are necessary for any study of the BATSE data statistically, as they take into account the most serious observational selection effects known in the study of GRBs: beam-smearing and inhomogeneous, anisotropic sky sampling. Knowledge of these effects is important to analysis of GRB angular and intensity distributions. In addition to determining that the bursts are local, it is hoped that analysis of such distributions will allow boundaries to be placed on the true GRB spatial distribution and luminosity function. The technique for studying GRB spatial and luminosity distributions is direct. Results of BATSE analyses are compared to Monte Carlo models parameterized by a variety of spatial and luminosity characteristics.
Horizontal fluxes of atmospheric water vapor are studied for summer months during 1989 and 1992 over North and South America based on analyses from European Center for Medium Range Weather Forecasts, US National Meteorological Center, and United Kingdom Meteorological Office. The calculations are performed over 20 deg by 20 deg box-shaped midlatitude domains located to the east of the Rocky Mountains in North America, and to the east of the Andes Mountains in South America. The fluxes are determined from operational center gridded analyses of wind and moisture. Differences in the monthly mean moisture flux divergence determined from these analyses are as large as 7 cm/month precipitable water equivalent over South America, and 3 cm/month over North America. Gridded analyses at higher spatial and temporal resolution exhibit better agreement in the moisture budget study. However, significant discrepancies of the moisture flux divergence computed from different gridded analyses still exist. The conclusion is more pessimistic than Rasmusson's estimate based on station data. Further analysis reveals that the most significant sources of error result from model surface elevation fields, gaps in the data archive, and uncertainties in the wind and specific humidity analyses. Uncertainties in the wind analyses are the most important problem. The low-level jets, in particular, are substantially different in the different data archives. Part of the reason for this may be due to the way the different analysis models parameterized physical processes affecting low-level jets. The results support the inference that the noise/signal ratio of the moisture budget may be improved more rapidly by providing better wind observations and analyses than by providing better moisture data.
A theoretical interpretation of sounding rocket measurements of intense Langmuir wave fields (less than or equal to 500 mV/m) driven by a stream of 20 eV to 4 keV electrons in the lower auroral zone is developed. This interpretation is based on the ability of the 10 microseconds sampling rate of the wave detector to temporally resolve the structure of the Langmuir wave field envelope. A modified form of the Zakharov equations is used to numerically study beam-driven Langmuir turbulence in the presence of a moderate magnetic field (OMEGA (sub e) approximately equals Omega (sub pe). Strong Landau damping on observed nonthermal scattered electrons, which is treated in a companion paper (Newman et al., this issue), plays an important role by inhibiting backscatter cascade and the development of strong turbulence. A parameterized model of the linear electron stream-driven wave instability is introduced, which incorporates limited quasilinear plateau formation. A reasonable set of parameters is found that yields semiquantitative agreement between observed properties of the Langmuir fields and the results of Zakharov equation simulations, including the amplitude and characteristic frequency of the electric field envelope modulations.
The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.
Energetic neutral atom (ENA) images obtained by the ENA imager on- board the Astrid satellite in the polar cap at 1000 km during a moderate magnetic storm (Dst greater than or equal to 80 nT) on 8 February 1995 are simulated using a parameterized model of the equatorial ion distribution and a six-component Chamberlain exo-sphere with parameters from the MSISE-90 model. By changing the ion parameters until a matching ENA image is obtained one can extract the equatorial ion distribution. Four consecutive images from different view points several of minutes apart are simulated assuming H(+) and O(+), respectively, as parent ions. The optimal set of parameters is extracted by minimizing the chi(exp 2) difference between simulated and observed ENA image using Powell's minimization algorithm. The optimal equatorial model ion distribution consists of O(+) peaked in around dusk. The lower intensity of fluxes obtained from vantage points closer to the pole is an effect of the loss cone of the parent ion distribution being empty.
The RSS-4 team collected several data sets related to leaf, plant, and stand physical, optical, and chemical properties. This data set contains leaf area indices and FPAR measurements that were taken at the three conifer sites in the BOREAS SSA during August 1993 and at the jack pine tower flux and a subset of auxiliary sites during July and August 1994. The measurements were made with LAI-2000 and Ceptometer instruments. The measurements were taken for the purpose of model parameterization and to test empirical relationships that were hypothesized between biophysical parameters and remotely sensed data. The data are stored in tabular ASCII files.
An observing system comprised of two lidars in geosynchronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture, both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and yield greatly improved and finer resolution initial conditions for models, make existing costly and cumbersome measurement approaches obsolete, and obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.
An observing system comprised of two lidars in geosychronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and a) yield greatly improved and finer resolution initial conditions for models, b) make existing costly and cumbersome measurement approaches obsolete, and c) obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.
NASA's participation in the North American Carbon Program will include a significant effort for quantifying terrestrial and adjacent ocean sources and sinks of carbon using a variety of land, ocean, and atmospheric measurements. This effort will require improved remote sensing algorithms, new measurement technologies, refined model parameterizations of carbon cycle processes, advanced satellite data assimilation methodologies, and a data management strategy. NASA's plan for pursuing these activities will be presented. Examples of NASA data management capabilities such as the SeaWiFS on-line field data system will be discussed.
The potential role of soil moisture initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997-2001, we generated two 16-member ensembles of 3-month simulations. The first, "AMIP-style" ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with "realistic" soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation data set and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that soil moisture initialization has a statistically significant impact on summertime precipitation and temperature over only a handful of continental regions. These regions agree, to first order, with regions that satisfy three conditions: (1) a tendency toward large initial soil moisture anomalies, (2) a strong sensitivity of evaporation to soil moisture, and (3) a strong sensitivity of precipitation to evaporation. The degree to which the initialization improves forecasts relative to observations is mixed, reflecting a critical need for the continued development of model parameterizations and data analysis strategies.
Establishing the radiative effect of molecular absorption (emission) in the atmosphere is critical to the proper interpretation of satellite retrieved radiances. Without an accurate accounting for molecular absorption, the assignment of radiative transfer processes to observed radiative effects could be fraught errors. Moreover, since the spectral characteristics of molecular absorption can change quickly with wavenumber, the adaptation of climate model parameterizations has the potential to lead to dubious results unless the chosen spectral range corresponds closely to the response function of the satellite instrument. Thus, an initiative has been undertaken to construct parameterizations that will account for the molecular absorption found in the spectral ranges of several satellite radiometers. Because of its efficiency and accuracy in calculating the molecular absorption for nonhomogeneous paths, the correlated k-distribution procedure has proven to be the most effective parameterization (Fu and Liou, 1992, and Kratz, 1995). A further advantage of the correlated k- distribution procedure is its ability to be incorporated directly into multiple scattering routines that consider scattering, as well as absorption, by clouds and aerosol particles.
The Tropical Cloud Systems and Processes experiment is sponsored by the National Aeronautics and Space Administration (NASA) to investigate characteristics of tropical cyclone genesis, rapid intensification and rainfall using a three-pronged approach that emphasizes satellite information, suborbital observations and numerical model simulations. Research goals include demonstration and assessment of new technology, improvements to numerical model parameterizations, and advancements in data assimilation techniques. The field phase of the experiment was based in Costa Rica during July 2005. A fully instrumented NASA ER-2 high altitude airplane was deployed with Doppler radar, passive microwave instrumentation, lightning and electric field sensors and an airborne simulator of visible and infrared satellite sensors. Other assets brought to TCSP were a low flying uninhabited aerial vehicle, and a surface-based radiosonde network. In partnership with the Intensity Forecasting Experiment of the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division, two NOAA P-3 aircraft instrumented with radar, passive microwave, microphysical, and dropsonde instrumentation were also deployed to Costa Rica. The field phase of TCSP was conducted in Costa Rica to take advantage of the geographically compact tropical cyclone genesis region of the Eastern Pacific Ocean near Central America. However, the unusual 2005 hurricane season provided numerous opportunities to sample tropical cyclone development and intensification in the Caribbean Sea and Gulf of Mexico as well. Development of Hurricane Dennis and Tropical Storm Gert were each investigated over several days in addition to Hurricane Emily as it was close to Saffir-Simpson Category 5 intensity. An overview of the characteristics of these storms along with the pregenesis environment of Tropical Storm Eugene in the Eastern Pacific will be presented.