http://hdl.handle.net/1721.1/7805 http://hdl.handle.net/1721.1/49805 Observational constraints on the number, albedos, size, and impact hazards of the near-Earth asteroids Stuart, Joseph Scott, 1971- This work provides a statistical description of the near-Earth asteroids (NEAs) in terms of number, orbital parameters, reflectance spectra, albedos, diameters, and terrestrial and lunar collision rates. I estimate the size and shape of the NEA population using survey data from the Lincoln Near-Earth Asteroid Research project including more than 1300 NEA detections. The NEA population is more highly inclined than previously estimated and the total number of NEAs with absolute magnitudes (H) brighter than 18 is 1227 +170/-90. The absolute magnitude and orbital parameter distributions for the NEAs are combined with reflectance spectra and albedo measurements. I obtain a debiased estimate of the fraction of NEAs in each of 10 taxonomic complexes, and a debiased average albedo for each. The number of NEAs larger than 1 km is 1090 +/- 180. Next, I determine the impact frequency, collision velocity distribution and collision energy distribution for impacts of NEAs into the Earth and Moon. Globally destructive collisions ([approx.] 1021 J) of asteroids 1 km or larger strike the Earth once every 0.60 +/- 0.1 Myr on average. Regionally destructive collisions with impact energy greater than 4x1018 J ([approx.] 200 m diameter) strike the Earth every 47,000 +/- 6,000 years. The rate of formation of craters expected from the NEAs is found to be in close agreement with the observed number of craters on the Earth and Moon. (cont.) These results combine the largest set of NEA discovery statistics from a single survey, the largest set of physical data on NEAs, and corrections for observational bias. The result is a comprehensive estimate of the total NEA population in terms of orbital parameters, absolute magnitudes, albedos, and sizes. This improved description of the NEAs will help us to plan surveys to find and study the remaining undiscovered NEAs, to connect the NEAs to their origins in the main-belt, to connect the NEAs to meteorite samples, to compare the lunar and terrestrial cratering record to the current population of potential impactors, and to understand the magnitude of the NEA impact hazard to the Earth's biosphere. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2003. Includes bibliographical references (p. 132-144). Tue, 29 Oct 2002 22:58:59 GMT http://hdl.handle.net/1721.1/47846 Toward improved tropical cyclone intensity forecasts : probabilistic prediction, predictability, and the role of verification Moskaitis, Jonathan Robert Over the past two decades, deterministic predictions of tropical cyclone (TC) intensity consistently scored poorly in mean absolute error (MAE) verification, despite the concurrent advancement of TC modeling and observing capabilities. Given the importance of understanding this situation for the future of TC intensity prediction, the "TC intensity prediction problem" is examined here on two fronts: (1) the role of verification in driving the forecast system development process, and (2) the inherent limit of predictability under the extant TC observing network. Verification is first examined from a theoretical perspective. It is shown that the use of certain summary measures of probabilistic forecast performance in the forecast system development process should be favored, because those summary measures promote production of theoretically-optimal predictions. However, the choice of a summary measure for verification of deterministic forecasts is arbitrary, since theoretically-optimal predictions cannot be produced by a deterministic forecast system. It is also demonstrated that the summary measure used in development of TC intensity forecast systems, MAE, does not necessarily drive development of a deterministic dynamical model toward the true system dynamics. A dynamical model should instead be developed in the context of ensemble prediction. Within the current operational environment of deterministic TC intensity prediction, it is shown that MAE provides a very limited view of forecast quality relative to the joint distribution of forecasts and observations. Analysis of the joint distribution reveals the profound influence of MAE-driven TC intensity forecast system development on the quality of operational predictions. Furthermore, the joint distribution inspires an information-theoretic summary measure with appealing properties. (cont.) The predictability of TC intensity is examined in the context of a simple dynamical TC model (the Coupled Hurricane Intensity Prediction System), in which it is feasible to explore an extensive phase space of initial conditions and idealized environmental boundary conditions. Lessons learned about the sensitivity of the simulated intensity are used to interpret ensemble predictions of real TCs. These ensemble predictions, and the associated estimates of analysis error used in formulation of the ensemble perturbations, represent a key step forward toward the goal of real-time probabilistic prediction of TC intensity. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2009. Includes bibliographical references (p. 207-214). Wed, 29 Oct 2008 22:58:59 GMT http://hdl.handle.net/1721.1/47845 Early lunar geology and geophysics Garrick-Bethell, Ian, 1980- Despite a number of human and robotic missions to the Moon, there are still important unanswered questions about its early evolution, and how it came to be the object we observe today. Here we use observational, experimental, and theoretical techniques to examine three important events that took place early in lunar history and have left a lasting signature. The first event is the formation of the largest basin on the Moon, the South Pole-Aitken Basin. We develop a systematic method to define the previously unknown boundaries of this degraded structure and quantify its gross shape. We also combine a number of remote sensing data sets to constrain the origin of heat producing elements in its interior. The second event we examine is the evolution of the lunar orbit, and the coupling between the Moon's early geophysical properties and the growth of orbital eccentricity. We use analytical models for tidal deformations and orbit evolution to show that the shape of the Moon suggests its early orbit was highly eccentric. However, we are also able to explain the presently high eccentricity entirely by traditional, secular tidal growth while the early Moon was hot. The third event we examine is the magnetization of lunar samples. We perform extensive paleomagnetic measurements of an ancient, deep-seated lunar sample, and determine that a long-lived magnetic field like that of a core dynamo is the most plausible explanation for its magnetic remanence. In sum, the earliest portion of lunar history has been largely obscured by later geologic events, but a great deal can still be learned from this formative epoch. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2009. Includes bibliographical references. Wed, 29 Oct 2008 22:58:59 GMT http://hdl.handle.net/1721.1/47844 Ensemble regression : using ensemble model output for atmospheric dynamics and prediction Gombos, Daniel (Daniel Lawrence) Ensemble regression (ER) is a linear inversion technique that uses ensemble statistics from atmospheric model output to make dynamical inferences and forecasts. ER defines a multivariate regression operator using ensemble forecasts and analyses to determine the most probable predict and perturbation associated with the prescribed predictor perturbation resolved by linear combinations of the predictor ensemble anomalies. Because it employs flow-dependent ensemble data, as opposed to the stationary time series data typically used to make statistical forecasts, ER is capable of modeling synoptic scale processes with rapidly evolving covariances. This characteristic is applied in several ways. Firstly, it is shown that the classical dynamical piecewise potential vorticity (PV) inversion of the PV perturbation effectively resolved by the ER operator yields nearly identical geopotential heights to those deduced from an ER performed in the subspace of the leading PV singular vectors. Secondly, using the example of the lagged sensitivity of tropical cyclone tracks to preexisting midtropospheric heights, ER is used to infer dynamical relationships from statistical sensitivities, to identify, in real-time, the dynamical processes that are particularly relevant to specific forecast decisions, and to make preemptive forecasts. Thirdly, it is shown that singular vectors deduced from the ER operator approximate those from the analysis error covariance normed tangent linear model operator, suggesting a simple alternative method for computing singular vectors. Given that ER results are a function of forecast ensemble reliability, theory and applications of a multivariate ensemble reliability verification technique called the minimum spanning tree rank histogram are presented. (cont.) Experiments using Euclidean, variance, and Mahalanobis norms for defining minimum spanning tree distances imply that, unless the number of ensemble members is less than or equal to the number of dimensions being verified, the Mahalanobis norm transforms a spanning tree into a space where model imperfections are most readily identified. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2009. Includes bibliographical references (p. 183-190). Wed, 29 Oct 2008 22:58:59 GMT