Unstable radiative-dynamical interactions

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1988.Includes bibliographical references.by Steven John Ghan.Sc.D

Modelling the synoptic scale relationship between eddy heat flux and the meridional temperature gradient

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Meteorology and Physical Oceanography, 1981.Microfiche copy available in Archives and Science.Bibliography: leaves 63-65.by Steven John Ghan.M.S

The Atmospheric Radiation Measurement Program May 2003 Intensive Operations Period Examining Aerosol Properties and Radiative Influences: Preface to Special Section

Atmospheric aerosols influence climate by scattering and absorbing radiation in clear air (direct effects) and by serving as cloud condensation nuclei, modifying the microphysical properties of clouds, influencing radiation and precipitation development (indirect effects). Much of present uncertainty in forcing of climate change is due to uncertainty in the relations between aerosol microphysical and optical properties and their radiative influences (direct effects) and between microphysical properties and their ability to serve as cloud condensation nuclei at given supersaturations (indirect effects). This paper introduces a special section that reports on a field campaign conducted at the Department of Energy Atmospheric Radiation Measurement site in North Central Oklahoma in May, 2003, examining these relations using in situ airborne measurements and surface-, airborne-, and space-based remote sensing

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty

0360 Radiation: transmission and scattering 0394 Instruments and techniques

Atmospheric aerosols influence climate by scattering and absorbing radiation in clear air (direct effects) and by serving as cloud condensation nuclei, modifying the microphysical properties of clouds, influencing radiation and precipitation development (indirect effects). Much of present uncertainty in forcing of climate change is due to uncertainty in the relations between aerosol microphysical and optical properties and their radiative influences (direct effects) and between microphysical properties and their ability to serve as cloud condensation nuclei at given supersaturations (indirect effects). This paper introduces a special section that reports on a field campaign conducted at the Department of Energy Atmospheric Radiation Measurement site in North Central Oklahoma in May, 2003, examining these relations using in situ airborne measurements and surface-, airborne-, and space-based remote sensing. 2 1.0 Background and Motivation Two key requirements for testing understanding of the influence of radiative processes on climate are: 1) relating observations of radiative fluxes and radiances to the atmospheric composition and, 2) using these relations to develop and test parameterizations to accurately predict the atmospheric radiative properties. These are the primary objectives of th

Workflow Simulation Aware and Multi-Threading Effective Task Scheduling for Heterogeneous Computing

Efficient application scheduling is critical for achieving high performance in heterogeneous computing systems. This problem has proved to be NP-complete, heading research efforts in obtaining low complexity heuristics that produce good quality schedules. Although this problem has been extensively studied in the past, all the related works assume the computation costs of application tasks on processors are available a priori, ignoring the fact that the time needed to run/simulate all these tasks is orders of magnitude higher than finding a good quality schedule, especially in heterogeneous systems. In this paper, we propose two new methods applicable to several task scheduling algorithms for heterogeneous computing systems. We showcase both methods by using HEFT well known and popular algorithm, but they are applicable to other algorithms too, such as HCPT, HPS, PETS and CPOP. First, we propose a methodology to reduce the scheduling time of HEFT when the computation costs are unknown, without sacrificing the length of the output schedule (monotonic computation costs); this is achieved by reducing the number of computation costs required by HEFT and as a consequence the number of simulations applied. Second, we give heuristics to find which tasks are going to be executed as Single-Thread and which as Multi-Thread CPU implementations, as well as the number of the threads used. The experimental results considering both random graphs and real world applications show that extending HEFT with the two proposed methods achieves better schedule lengths, while at the same time requires from 4.5 up to 24 less simulations