Search Results

You are looking at 1 - 6 of 6 items for

  • Author or Editor: H. W. Church x
  • Refine by Access: All Content x
Clear All Modify Search
R. E. Luna and H. W. Church

Abstract

Estimation of long-term average concentrations from fixed sources is completely straightforward using standard dispersion formulas and occurrence statistics of wind speed classes and wind directions. However, in many cases of practical interest, only the fraction of time within a direction interval and its associated mean wind speed are available from a standard wind rose. While this information is sufficient to make an estimate of the mean concentration, estimates that better reflect the distributed nature of wind speeds can be made using some observed properties of the wind speed distribution. In particular, it is shown that speed distributions from many diverse sites possess a quasi-universal shape which, when approximated analytically, can be adjusted to yield a distribution of wind speeds which have some specified mean value. The distributions are shown to be satisfactorily described with a log-normal function having a typical geometric standard deviation of 1.9 which, in turn, yields a value of 1.5 for the ratio of long-term concentration determined by distributed winds to that determined from the average wind.

Full access
R. E. Luna and H. W. Church

Abstract

Full access
R. E. Luna and H. W. Church

Abstract

Full access
R. E. Luna and H. W. Church
Full access
R. E. Luna and H. W. Church

Abstract

To understand the extent to which the Pasquill stability classes can discriminate the diffusion capability of the atmosphere, a comparison between stability category and both turbulence intensity and stability ratio was performed. Data for stability class were gathered from observations taken at 3-hr intervals at the Augusta, Ga., weather station. Turbulence intensity and stability ratio data were recorded on a tower 13 km away. For each observation at Augusta, the stability category was determined, based on month, hour, cloud cover and character, height, and wind speed. The distribution was then formed from all of the quantitative data for each category.

Results showed a monotonic decrease in median turbulence intensity by an order of magnitude as stability class went from A through F. However, the distribution within a class was characterized by a geometric standard deviation of about 3, indicating large scatter of individual values about the median.

The median of the stability ratio distributions increased as stability changed from class A to F but, for classes D, E, and F, the trend was not well defined. In particular, it appears that category D is not a good predictor of a near adiabatic (neutral) lapse rate.

Full access
Sarah J. Doherty, Stephan Bojinski, Ann Henderson-Sellers, Kevin Noone, David Goodrich, Nathaniel L. Bindoff, John A. Church, Kathy A. Hibbard, Thomas R. Karl, Lucka Kajfez-Bogataj, Amanda H. Lynch, David E. Parker, I. Colin Prentice, Venkatachalam Ramaswamy, Roger W. Saunders, Mark Stafford Smith, Konrad Steffen, Thomas F. Stocker, Peter W. Thorne, Kevin E. Trenberth, Michel M. Verstraete, and Francis W. Zwiers

The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is “unequivocal” and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences on ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.

Full access