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Henry E. Fleming

Abstract

Computed tomography is a medical diagnostic technique in which x-ray transmission measurements at numerous angles through the human body are processed by computer to produce cross-sectional pictures of the body. A modification of this technique, using emitted infrared or microwave radiation instead of transmitted x-ray radiation, can be applied to satellite radiance measurements taken along the orbital track at various angles. Cross sections of the vertical atmospheric temperature structure (or the gaseous constituent density structure) are retrieved from the collection of radiance measurements taken at various angles and frequencies. The advantage of this technique over conventional remote sensing methods is the additional information acquired by viewing a given point in the atmosphere at several angles as well as at several frequencies. The physical and geometric concepts involved are discussed along with the mathematical formulation of the problem and the practical aspects of applying the technique. A method of solution of the resulting large, sparse system of equations is given and is applied to simulated case studies. Temperatures retrieved by the computed tomography technique, when compared with those retrieved by conventional methods, showed an overall average improvement in accuracy of as much as 34% in the study.

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Mitchell D. Goldberg
and
Henry E. Fleming

Abstract

An algorithm for generating deep-layer mean temperatures from satellite-observed microwave observations is presented. Unlike traditional temperature retrieval methods, this algorithm does not require a first guess temperature of the ambient atmosphere. By eliminating the first guess a potentially systematic source of error has been removed. The algorithm is expected to yield long-term records that are suitable for detecting small changes in climate.

The atmospheric contribution to the deep-layer mean temperature is given by the averaging kernel. The algorithm computes the coefficients that will best approximate a desired averaging kernel from a linear combination of the satellite radiometer's weighting functions. The coefficients are then applied to the measurements to yield the deep-layer mean temperature. Three constraints were used in deriving the algorithm: 1) the sum of the coefficients must be one, 2) the noise of the product is minimized, and 3) the shape of the approximated averaging kernel is well behaved. Note that a trade-off between constraints 2 and 3 is unavoidable.

The algorithm can also be used to combine measurements from a future sensor [i.e., the 20-channel Advanced Microwave Sounding Unit (AMSU)] to yield the same averaging kernel as that based on an earlier sensor [i.e., the 4-channel Microwave Sounding Unit (MSU)]. This will allow a time series of deep-layer mean temperatures based on MSU measurements to be continued with AMSU measurements. The AMSU is expected to replace the MSU in 1996.

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Larry M. McMillin
and
Henry E. Fleming

Abstract

In the design of satellite sounding instruments there are many factors that determine the accuracies of the retrieved temperature and moisture profiles. However, the three major factors are: instrument noise, number of channels and weighting function half-widths. The effect of these three factors on retrieved temperatures are examined through simulation studies to determine trade-offs among them. We conclude that the trade-offs among the three factors suggest that year different instrument designs can yield similar accuracies. Consequently, the instrument design that provides optimum performance can be recognized only after a trade-off analysis is made. If the design with the best performance is to be selected, it is particularly important that the designs be given equal benefit of factors which are not intrinsic design differences.

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Henry E. Fleming
,
David S. Crosby
, and
Arthur C. Neuendorffer

Abstract

It is generally assumed that atmospheric transmittance functions are known to an accuracy of no better than about five to ten percent. Consequently, one can expect a major impact of these errors on temperature retrieves based on the inversion of the radiative transfer equation, as opposed to regression methods that do not explicitly use transmittance functions. A numerical simulation study of the sensitivity of the retrieved temperature profiles to errors in transmittance is described. The study shows that most of the transmittance error is propagated into the retrieved profiles in the form of a bias error. A technique for removing this large bias component of the error is given. Furthermore, it is shown how the improper use of regularization transforms sonic of the bias error into an unremovable component of random error. Finally, we show results that indicate how well the bias-error removal technique works in practice using real data. It is found that, despite errors of measurement and errors in the transmittance functions, one can retrieve temperature profiles of good quality.

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Guy P. Brasseur
,
Mohan Gupta
,
Bruce E. Anderson
,
Sathya Balasubramanian
,
Steven Barrett
,
David Duda
,
Gregg Fleming
,
Piers M. Forster
,
Jan Fuglestvedt
,
Andrew Gettelman
,
Rangasayi N. Halthore
,
S. Daniel Jacob
,
Mark Z. Jacobson
,
Arezoo Khodayari
,
Kuo-Nan Liou
,
Marianne T. Lund
,
Richard C. Miake-Lye
,
Patrick Minnis
,
Seth Olsen
,
Joyce E. Penner
,
Ronald Prinn
,
Ulrich Schumann
,
Henry B. Selkirk
,
Andrei Sokolov
,
Nadine Unger
,
Philip Wolfe
,
Hsi-Wu Wong
,
Donald W. Wuebbles
,
Bingqi Yi
,
Ping Yang
, and
Cheng Zhou

Abstract

Under the Federal Aviation Administration’s (FAA) Aviation Climate Change Research Initiative (ACCRI), non-CO2 climatic impacts of commercial aviation are assessed for current (2006) and for future (2050) baseline and mitigation scenarios. The effects of the non-CO2 aircraft emissions are examined using a number of advanced climate and atmospheric chemistry transport models. Radiative forcing (RF) estimates for individual forcing effects are provided as a range for comparison against those published in the literature. Preliminary results for selected RF components for 2050 scenarios indicate that a 2% increase in fuel efficiency and a decrease in NOx emissions due to advanced aircraft technologies and operational procedures, as well as the introduction of renewable alternative fuels, will significantly decrease future aviation climate impacts. In particular, the use of renewable fuels will further decrease RF associated with sulfate aerosol and black carbon. While this focused ACCRI program effort has yielded significant new knowledge, fundamental uncertainties remain in our understanding of aviation climate impacts. These include several chemical and physical processes associated with NOx–O3–CH4 interactions and the formation of aviation-produced contrails and the effects of aviation soot aerosols on cirrus clouds as well as on deriving a measure of change in temperature from RF for aviation non-CO2 climate impacts—an important metric that informs decision-making.

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