dc.contributor.advisor | James A. Hansen and Kerry A. Emanuel. | en_US |
dc.contributor.author | Goto, Susumu | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Technology and Policy Program. | en_US |
dc.date.accessioned | 2008-02-27T22:17:19Z | |
dc.date.available | 2008-02-27T22:17:19Z | |
dc.date.copyright | 2007 | en_US |
dc.date.issued | 2007 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/40379 | |
dc.description | Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2007. | en_US |
dc.description | Includes bibliographical references (p. 102-112). | en_US |
dc.description.abstract | This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting was developed to overcome the limitations of conventional deterministic weather forecasting. However, despite the achievements of ensemble forecasting techniques and efforts to put them into operation, the implementation and utilization of ensemble forecasting seems limited in society. This thesis studies meteorological aspects, potential uses and value, and policy issues to give an overall picture of ensemble forecasting and suggests directions of measures to increase its utilization. Conventional weather forecasting cannot achieve perfect forecasts due to the chaotic nature of the atmosphere and imperfect analyses of the current atmosphere. The imperfect description of numerical weather prediction models in the forecasting process is another source of the disparity between forecasts and the real atmosphere. Conventional weather forecasting offers only a single scenario, which sometimes fails to predict the actual weather; ensemble forecasting provides probabilistic weather forecasts based on multiple weather scenarios. | en_US |
dc.description.abstract | (cont.) This thesis also illustrates potential uses and values of ensemble forecasting. Ensemble forecasting could help disaster management officers prepare for probable hazardous conditions. It is also useful for risk management in business. Using concepts of information values and real options, this thesis demonstrates that ensemble forecasting can be valuable in decision making. Potential uses of ensemble forecasting in agriculture and the wind electricity sectors are also discussed. Implementation of ensemble forecasting requires huge costs, so collaboration within weather sectors and with non-weather sectors is key. Relationships between public, private, and academic sectors in the weather world are analyzed in this thesis. The public-private relationship seems characterized by dilemmas in both sectors. As for the public-academic relationship, there are different situations in the US and in Japan due to differences in research environment and policies. International collaboration and partnerships between weather sectors and non-weather sectors are also discussed. If all these collaborations among the sectors work well, then ensemble forecasting can give rise to a new generation of weather forecasting. | en_US |
dc.description.statementofresponsibility | by Susumu Goto. | en_US |
dc.format.extent | 112 p. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | |
dc.subject | Technology and Policy Program. | en_US |
dc.title | Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting | en_US |
dc.title.alternative | Potential use and implementation of ensemble forecasting | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Engineering Systems Division | |
dc.contributor.department | Technology and Policy Program | |
dc.identifier.oclc | 191092198 | en_US |