Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation.
Identifieur interne : 000B75 ( Main/Exploration ); précédent : 000B74; suivant : 000B76Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation.
Auteurs : Kelvin K. Droegemeier [États-Unis]Source :
- Philosophical transactions. Series A, Mathematical, physical, and engineering sciences [ 1364-503X ] ; 2009.
English descriptors
- KwdEn :
- MESH :
- instrumentation : Environmental Monitoring, Meteorology.
- methods : Ecology, Environmental Monitoring, Meteorology.
- trends : Ecology.
- Computer Simulation, Internet, Models, Theoretical, Software, Weather.
Abstract
Mesoscale weather, such as convective systems, intense local rainfall resulting in flash floods and lake effect snows, frequently is characterized by unpredictable rapid onset and evolution, heterogeneity and spatial and temporal intermittency. Ironically, most of the technologies used to observe the atmosphere, predict its evolution and compute, transmit or store information about it, operate in a static pre-scheduled framework that is fundamentally inconsistent with, and does not accommodate, the dynamic behaviour of mesoscale weather. As a result, today's weather technology is highly constrained and far from optimal when applied to any particular situation. This paper describes a new cyberinfrastructure framework, in which remote and in situ atmospheric sensors, data acquisition and storage systems, assimilation and prediction codes, data mining and visualization engines, and the information technology frameworks within which they operate, can change configuration automatically, in response to evolving weather. Such dynamic adaptation is designed to allow system components to achieve greater overall effectiveness, relative to their static counterparts, for any given situation. The associated service-oriented architecture, known as Linked Environments for Atmospheric Discovery (LEAD), makes advanced meteorological and cyber tools as easy to use as ordering a book on the web. LEAD has been applied in a variety of settings, including experimental forecasting by the US National Weather Service, and allows users to focus much more attention on the problem at hand and less on the nuances of data formats, communication protocols and job execution environments.
DOI: 10.1098/rsta.2008.0211
PubMed: 19087934
Affiliations:
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Le document en format XML
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Droegemeier</name><affiliation wicri:level="2"><nlm:affiliation>School of Meteorology, University of Oklahoma, 120 David L. Boren Boulevard, Suite 5900, Norman, OK 73072-7307, USA. kkd@ou.edu</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>School of Meteorology, University of Oklahoma, 120 David L. Boren Boulevard, Suite 5900, Norman, OK 73072-7307</wicri:regionArea><placeName><region type="state">Oklahoma</region></placeName></affiliation></author></analytic><series><title level="j">Philosophical transactions. Series A, Mathematical, physical, and engineering sciences</title><idno type="ISSN">1364-503X</idno><imprint><date when="2009" type="published">2009</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computer Simulation</term><term>Ecology (methods)</term><term>Ecology (trends)</term><term>Environmental Monitoring (instrumentation)</term><term>Environmental Monitoring (methods)</term><term>Internet</term><term>Meteorology (instrumentation)</term><term>Meteorology (methods)</term><term>Models, Theoretical</term><term>Software</term><term>Weather</term></keywords><keywords scheme="MESH" qualifier="instrumentation" xml:lang="en"><term>Environmental Monitoring</term><term>Meteorology</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Ecology</term><term>Environmental Monitoring</term><term>Meteorology</term></keywords><keywords scheme="MESH" qualifier="trends" xml:lang="en"><term>Ecology</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computer Simulation</term><term>Internet</term><term>Models, Theoretical</term><term>Software</term><term>Weather</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Mesoscale weather, such as convective systems, intense local rainfall resulting in flash floods and lake effect snows, frequently is characterized by unpredictable rapid onset and evolution, heterogeneity and spatial and temporal intermittency. Ironically, most of the technologies used to observe the atmosphere, predict its evolution and compute, transmit or store information about it, operate in a static pre-scheduled framework that is fundamentally inconsistent with, and does not accommodate, the dynamic behaviour of mesoscale weather. As a result, today's weather technology is highly constrained and far from optimal when applied to any particular situation. This paper describes a new cyberinfrastructure framework, in which remote and in situ atmospheric sensors, data acquisition and storage systems, assimilation and prediction codes, data mining and visualization engines, and the information technology frameworks within which they operate, can change configuration automatically, in response to evolving weather. Such dynamic adaptation is designed to allow system components to achieve greater overall effectiveness, relative to their static counterparts, for any given situation. The associated service-oriented architecture, known as Linked Environments for Atmospheric Discovery (LEAD), makes advanced meteorological and cyber tools as easy to use as ordering a book on the web. LEAD has been applied in a variety of settings, including experimental forecasting by the US National Weather Service, and allows users to focus much more attention on the problem at hand and less on the nuances of data formats, communication protocols and job execution environments.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Oklahoma</li></region></list><tree><country name="États-Unis"><region name="Oklahoma"><name sortKey="Droegemeier, Kelvin K" sort="Droegemeier, Kelvin K" uniqKey="Droegemeier K" first="Kelvin K" last="Droegemeier">Kelvin K. Droegemeier</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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