Technology Reconciliation in the Remote Sensing ERA of United States Civilian Weather Forecasting: 1957 -1987.
This dissertation seeks to advance an understanding of the management of a major technological change in meteorology. The study examines the connection between changes in production and real-time use of data products derived from remote -sensing data collection and the evolution of U.S. civilian weather forecasting 1957-1987. The role of data collection in weather forecasting throughout history is examined, giving most attention to the 1957-1987 period. Critical to the real-time use of remote-sensing data was technology reconciliation. As defined by the author, it is the function or process by which data products and information derived from a new technology are made consistent or congruent with the existing data representations of a science in order to be used effectively. No model had been developed for a technology reconciliation process, or definition of the major role technology reconciliators played in the 30-year evolution of the science of weather forecasting. In order to assess the new remote-sensing data resource and its use in U.S. civilian weather forecasting, a Data Accountability and Review Technique (DART) was developed by the author in 1989. This technique was used to identify 16 of the technology reconciliators who developed and reconciled 25 new remote-sensing data products with the weather charts, maps and computer models of the National Weather Service. In five separate program teams, they were responsible for 15 improvements in the products--forecasts--and 18 improvement in the process of weather forecasting. A model of the technology reconciliation is proposed which can be applied to understanding the contemporary history of other sciences. The model, as well as the methods developed by the author to recognize the process of technology reconciliation has a much more general applicability beyond the sciences. Any field implementing new technology that promises to improve its whole way of working will be faced with the task of technology reconciliation. Scientists, engineers, R & D managers, and science/technology policy -makers should find the case study, the methodology, and the generalized model helpful in guiding them through the complex process of interpreting new data from new technology.
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- Physics: Atmospheric Science; History of Science; Information Science; Remote Sensing