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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

OVOC (Oxygenated Volatile Organic Chemicals) in the Global Atmosphere: Atmospheric Budgets, Oceanic Concentrations, and Uncertainties

Airborne measurements of oxygenated volatile organic chemicals (OVOC), OH free radicals, and tracers of pollution were performed over the Pacific during Winter/Spring of 2001. Large concentrations of OVOC are present in the global troposphere and are expected to play an important role in atmospheric chemistry. Their total abundance (SIGMAOVOC) was nearly twice that of non-methane hydrocarbons (SIGMAC2-C8 NMHC). Throughout the troposphere, the OH reactivity of OVOC is comparable to that of methane and far exceeds that of NHMC. A comparison of these data with western Pacific observations collected some seven years earlier (Feb.-March, 1994) did not reveal significant differences. Analysis of the relative enhancement of selected OVOC with respect to CH3Cl and CO in twelve plumes originating from fires and sampled in the free troposphere (3-11 km) is used to assess their primary and secondary emissions from biomass combustion. The composition of these plumes also indicates a large shift of reactive nitrogen into the PAN reservoir thereby limiting ozone formation. These data are combined with other observations and interpreted with the help of a global 3-D model to assess OVOC global sources and sinks. We further interpret atmospheric observations with the help of an air-sea exchange model io show that oceans can be both net so~rces and sinks. An extremely large oceanic reservoir of OVOC, that exceeds the atmospheric reservoir by more than an order of magnitude, can be inferred to be present. We conclude that OVOC sources are extremely large (150-500 TgC y-1) but remain poorly quantified. In many cases, measured concentrations are uncertain and incompatible with our present knowledge of atmospheric chemistry. Results based on observations from several field studies and critical gaps will be discussed.

Singh, Hanwant B.↗
NASA NTRS2004

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Olson, William S.↗
NASA NTRS2005

The Effects of the Uncertainty of Departures on Multi-Center Traffic Management Advisor (TMA) Scheduling

The Multi-center Traffic Management Advisor (McTMA) provides a platform for regional or national traffic flow management, by allowing long-range cooperative time-based metering to constrained resources, such as airports or air traffic control center boundaries. Part of the demand for resources is made up of proposed departures, whose actual departure time is difficult to predict. For this reason, McTMA does not schedule the departures in advance, but rather relies on traffic managers to input their requested departure time. Because this happens only a short while before the aircraft's actual departure, McTMA is unable to accurately predict the amount of delay airborne aircraft will need to take in order to accommodate the departures. The proportion of demand which is made up by such proposed departures increases as the horizon over which metering occurs gets larger. This study provides an initial analysis of the severity of this problem in a 400-500 nautical mile metering horizon and discusses potential solutions to accommodate these departures. The challenge is to smoothly incorporate departures with the airborne stream while not excessively delaying the departures.' In particular, three solutions are reviewed: (1) scheduling the departures at their proposed departure time; (2) not scheduling the departures in advance; and (3) scheduling the departures at some time in the future based on an estimated error in their proposed time. The first solution is to have McTMA to automatically schedule the departures at their proposed departure times. Since the proposed departure times are indicated in their flight times in advance, this method is the simplest, but studies have shown that these proposed times are often incorrect2 The second option is the current practice, which avoids these inaccuracies by only scheduling aircraft when a confirmed prediction of departure time is obtained from the tower of the departure airport. Lastly, McTMA can schedule the departures at a predicted departure time based on statistical data of past departure time performance. It has been found that departures usually have a wheels-up time after their indicated proposed departure time, as shown in Figure 1. Hence, the departures were scheduled at a time in the future based on the mean error in proposed departure times for their airport.

Thipphavong, Jane↗
NASA NTRS1997

Managing Uncertainty in Preliminary Aeroshell Design Analysis

An analysis tool to aid in preliminary design of re-entry aeroshells for interplanetary exploration is presented. The computational tool addresses a common feature of design analysis, the need to make use of results from several analysis regimes and from several sources.

Design Methods and Models Design Representations C↗
NASA NTRS1996

Identification, Uncertainty Characterization and Robust Control Synthesis Applied to Large Flexible Structures Control

This paper demonstrates an approach to frequency domain identification for the explicit purpose of designing robust H(infinity) controllers. The approach transforms raw experimental data into a plant set estimate directly usable by modern robust control design software(e.g., Matlab Robust Control Toolboxes [11][2]). A key issue in control design from raw data is the question of whether the controller will work when applied to the true system. The main feature fo this approach is that the resulting controller in guaranteed to work as designed(when applied to the true system) to a prescribed statistical confidence. While the overall methodology addresses key theoretical issues, it has at the same time been specifically designed to support practical implementations. A simulation example is included to demonstrate the overall approach.

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