984 resultados para Natural Semantic Metalanguage
Resumo:
EXTRACT (SEE PDF FOR FULL ABSTRACT): High-resolution proxy records of climate, such as varves, ice cores, and tree-rings, provide the opportunity for reconstructing climate on a year-by-year basis. In order to do so it is necessary to approximate the complex nonlinear response function of the natural recording system using linear statistical models. Three problems with this approach were discussed, and possible solutions were suggested. Examples were given from a reconstruction of Santa Barbara precipitation based on tree-ring records from Santa Barbara County.
Resumo:
The goal of this work is to examine the properties of recording mechanisms which are common to continuously recording high-resolution natural systems in which climatic signals are imprinted and preserved as proxy records. These systems produce seasonal structures as an indirect response to climatic variability over the annual cycle. We compare the proxy records from four different high-resolution systems: the Quelccaya ice cap of the Peruvian Andes; composite tree ring growth from southern California and the southwestern United States; and the marine varve sedimentation systems in the Santa Barbara basin (off California, United States) and in the Gulf of California, Mexico. An important focus of this work is to indicate how the interannual climatic signal is recorded in a variety of different natural systems with vastly different recording mechanisms and widely separated in space. These high-resolution records are the products of natural processes which should be comparable, to some degree, to human-engineered systems developed to transmit and record physical quantities. We therefore present a simple analogy of a data recording system as a heuristic model to provide some unifying concepts with which we may better understand the formation of the records. This analogy assumes special significance when we consider that natural proxy records are the principal means to extend our knowledge of climatic variability into the past, beyond the limits of instrumentally recorded data.