Engineering topics

Bell, T. L.

Publications and source records attributed to Bell, T. L..

10 records

NASA NTRS2006

"Weekend-effect" evidence for intensification of storms by pollution over U.S.

Aerosols change the way precipitating clouds evolve, due to their effect on condensation and ice formation. The net effect of aerosols on precipitation varies depending on the local environment and synoptic situation, the types of aerosols, and also on how far downstream one looks for effects. Repeated experiments with controlled release of aerosols would be helpful in unraveling how aerosols affect precipitation. The weekly variation in human activity may provide just such a set of experiments. Using the rainfall estimates from the passive microwave instrument on the Tropical Rainfall Measuring Mission (TRMM), which has been orbiting for over eight years and can view areas as far north as about 40 degs, we find that there is indeed a weekly variation in summer (JJA) rainfall over the southeastern U.S. land area, with the average rain rate peaking in the middle of the week (Tue-Thu). Rainfall over nearby oceanic areas, on the other hand, seems to peak on weekends. A bootstrap statistical test indicates that the variations are unlikely to be due to chance. Physically related weekly variations in the statistics of ground-based measurements and model reanalysis data are found. The midweek peak in rainfall over land coincides with the well documented midweek peak in pollution around much of the U.S., and is unlikely to be due to other weekly variations in human influence. The midweek increase is also unlikely to be a consequence of the radiative heating or cooling of the atmosphere by the aerosols.

Bell, T. L.↗

NASA NTRS2005

Midweek Intensification of Rain in the U.S.: Does Air Pollution Invigorate Storms?

The effect of pollution on rainfall has been observed to depend both on the type of pollution and the precipitating environment. The climatological consequences of pollution for rainfall are uncertain. In some urban areas, pollution varies with the day of the week because of weekly variations in human activity, in effect providing a repeated experiment on the effects of pollution. Weekly variations in temperature, pressure, cloud characteristics, hails and lightning are observed in many areas. Observing a weekly cycle in rainfall statistics has proven to be more difficult, although there is some evidence for it. Here we examine rainfall statistics from the Tropical Rainfall Measuring Mission (TRMM) satellite over the southern U.S. and adjacent waters, and find that there is a distinct, statistically significant weekly cycle in summertime rainfall over the southeast U.S., as well as weekly variations in rainfall over the nearby Atlantic and the Gulf of Mexico. Rainfall over land peaks in the middle of the week, suggesting that summer rainfall on large scales may increase as pollution levels rise. Both rain statistics over land and what appear to be compensating effects over adjacent seas support the suggestion that air pollution invigorates convection and outflow aloft.

Bell, T. L.↗

NASA NTRS2002

Scale Dependence of Statistics of Spatially Averaged Rain Rate Seen in TOGA COARE Comparison with Predictions from a Stochastic Model

A characteristic feature of rainfall statistics is that they in general depend on the space and time scales over which rain data are averaged. As a part of an earlier effort to determine the sampling error of satellite rain averages, a space-time model of rainfall statistics was developed to describe the statistics of gridded rain observed in GATE. The model allows one to compute the second moment statistics of space- and time-averaged rain rate which can be fitted to satellite or rain gauge data to determine the four model parameters appearing in the precipitation spectrum - an overall strength parameter, a characteristic length separating the long and short wavelength regimes and a characteristic relaxation time for decay of the autocorrelation of the instantaneous local rain rate and a certain 'fractal' power law exponent. For area-averaged instantaneous rain rate, this exponent governs the power law dependence of these statistics on the averaging length scale $L$ predicted by the model in the limit of small $L$. In particular, the variance of rain rate averaged over an $L \times L$ area exhibits a power law singularity as $L \rightarrow 0$. In the present work the model is used to investigate how the statistics of area-averaged rain rate over the tropical Western Pacific measured with ship borne radar during TOGA COARE (Tropical Ocean Global Atmosphere Coupled Ocean Atmospheric Response Experiment) and gridded on a 2 km grid depends on the size of the spatial averaging scale. Good agreement is found between the data and predictions from the model over a wide range of averaging length scales.

Kundu, Prasun K.↗

NASA NTRS1992

Simulated mission testing and flight performance of a 0.2 lbf Magellan monopropellant thruster

Results are presented of laboratory tests and actual flight performance of a 0.2 lbf Magellan monopropellant thruster subjected to temperatures ranging from 120 to 150 deg C. The results of tests demonstrated that the thruster operated satisfactorily at temperatures up to and including 140 C (thruster performance at 150 C was inconsistent). Flight conditions and thruster performance were monitored during Orbital Transfer Maneuver One and Cycle-2 flights. It was found that, for a given amount of momentum removed during a spacecraft reaction wheel (RW) desaturation, the number of thruster pulses required to remove that RW momentum was exceedingly consistent.

Costanza, R. A.↗

NASA NTRS1986

Theory of optimal weighting of data to detect climatic change

A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

Bell, T. L.↗

NASA NTRS1982

Optimal weighting of data to detect climatic change - Application to the carbon dioxide problem

It is suggested that a weighting of surface temperature data, using information about the expected level of warming in different seasons and geographical regions and statistical information about the amount of natural variability in surface temperature, can improve the chances of early detection of carbon dioxide concentration-induced climatic warming. A preliminary analysis of the optimal weighting method presented suggests that it is 25 per cent more effective in revealing surface warming than the conventional method, in virtue of the fact that 25 per cent more data must conventionally be analyzed in order to arrive at a similar probability of detection. An approximate calculation suggests that the warming ought to have already been detected, if the only sources of significant surface temperature variability had time scales of less than one year.

Bell, T. L.↗

NASA NTRS1982

Sampling errors in the estimation of empirical orthogonal functions

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

North, G. R.↗

NASA NTRS1982

The latitude dependence of the variance of zonally averaged quantities

Geometric characteristics of the spherical earth are shown to be responsible for the increase of variance with latitude of zonally averaged meteorological statistics. An analytic model is constructed to display the effect of a spherical geometry on zonal averages, employing a sphere labeled with radial unit vectors in a real, stochastic field expanded in complex spherical harmonics. The variance of a zonally averaged field is found to be expressible in terms of the spectrum of the vector field of the spherical harmonics. A maximum variance is then located at the poles, and the ratio of the variance to the zonally averaged grid-point variance, weighted by the cosine of the latitude, yields the zonal correlation typical of the latitude. An example is provided for the 500 mb level in the Northern Hemisphere compared to 15 years of data. Variance is determined to increase north of 60 deg latitude.

North, G. R.↗

NASA NTRS1981

Sampling problems

Precipitation estimates from satellites are subject to a number of uncertainties involving design characteristics, satellite positioning, natural variability of precipitation, and the noncontinuous acquisition of data. The sources and sizes of these uncertainties are in need of proper evaluation and estimation. The present sampling and estima-theory seems to be adequate for some measurement problems (e.g., determining precipitation at a point), while others require further theoretical work (e.g., determining the time history of precipitation over large areas).

Flueck, J. A.↗

NASA NTRS1980

Climate sensitivity from fluctuation dissipation - Some simple model tests

Leith has suggested that climatic response to change in external forcing parameters of the climate system may be estimated via the fluctuation-dissipation theorem (FDT). The method, which uses the natural fluctuations of the atmosphere to probe its dynamics, is tested here using a twenty-variable truncation model of the barotropic vorticity equation. Dissipative terms are added to the equations, so that the model is pushed away from the region where it is expected to satisfy the FDT. It is found that, even though the FDT is no longer satisfied in every detail, the FDT continues to provide an excellent estimate of the climatic sensitivity of the model.

Bell, T. L.↗