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Skill-scores, relative to climatology, for some parameters such as ceiling/visibility and precipitation are much lower than others, such as minimum temperature and pressure gradients. Also, the skill-scores have been improving appreciably faster for forecasts of 36 h (and more) than for forecasts of 24 h (and less). At the shortest ranges, less than 12 h, skill-scores relative to persistence are rather low, with values of 0.0 to 0.5 as typical. Power spectra for wind, temperature, dew point, rainfall rate, cloud reflectivity, and extinction coefficient (inversely related to visibility) were computed for periods of 10 min to 20 days, using fall season data from northeast United States. Analyses of these spectra indicate some of the problems in forecasting. Wind, temperature, and dew point spectra all had considerably more power at periods longer than 24 h than did rainfall rate, cloud reflectivity, and extinction coefficient, which relates to differences in forecast skill-scores. The greatest contribution to change for 2- to 8-h forecasts comes from disturbances with periods of about 8 to 32 h. Disturbances with periods shorter than about 24 h are purposedly filtered from current operational numerical models, in order to improve performance over longer ranges. The disturbances filtered out may be relatively unimportant to wind and temperature forecasts but quiet important for cloud and precipitation forecasts. Disturbances with periods less than about 2 h cannot be adequately resolved temporally or spatially using current weather data, yet these disturbances have sufficient amplitude to contribute noise in the analyses of longer period disturbances.
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Sections 1-2. Keyword Index.--Section 3. Personal author index.--Section 4. Corporate author index.-- Section 5. Contract/grant number index, NTIS order/report number index 1-E.--Section 6. NTIS order/report number index F-Z.

Accessions List

Assessment and Information Services Center (U.S.). Library and Information Services Division

Published: 1983

Total Pages: 606


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Accessions List

United States. National Environmental Satellite, Data, and Information Service. Library and Information Services Division

Published: 1983

Total Pages: 606


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This Book Contains Seven Chapters, Each Dealing With One Major Natural Disaster Encountered In Our Country. Each Of The Authors Is An Expert In That Particular Field. The Outstanding Contribution Of This Book Is That It Not Only Deals With The Forecasting And Description Of The Various Natural Disasters, But Also Stresses The Management Aspect, Exhaustively Detailing The Necessary Steps That Need To Be Taken To Deal With The Fallout In The Wake Of These Disasters. The Book Also Describes The Advances In Remote Sensing And The State-Of-The-Art Technology Available In India For The Monitoring And Prediction Of These Phenomena. It Also Draws Up A Comprehensive Warning System To Be Implemented, In Order To Minimize The Extensive Losses To Life And Property That Occur Year After Year.
With the development of earth observation technologies (such as satellite remote sensing, unmanned aerial vehicle, autonomous underwater vehicle, etc.), an era of big data with important and non-negligible spatial/temporal attributes comes. Novel and rigorous spatiotemporal methodologies and models are needed to process and analyze marine big data. Since many marine environmental processes, such as pollutants diffusion, algae distributions etc., vary or evolve across spatiotemporal domains, detecting the distributions and patterns of marine fauna and, particularly in the coastal regions, will improve our understanding of marine systems and can be beneficial in marine environmental management. The goals of this Research Topic, therefore, are two-fold: (a) to develop methodologies and models in theory and applications, including spatiotemporal geostatistics, geographic information system, deep learning, etc.; (b) to quantitatively gain the knowledge of the marine environment. This Research Topic will provide a platform for researchers to share and exchange their new knowledge gained in a spatiotemporal domain of marine or coastal regions. This Research Topic will cover, but is not limited to, the following areas: • Spatiotemporal variations of physical/chemical/biological indicators (such as chlorophyll, temperature, salinity, colorful dissolved organic matter, suspended solids, nutrients, microplastic, etc.) in marine. • Spatiotemporal variations of potential fishing grounds in marine. • Spatiotemporal variations of the ecosystems in coastal regions, such as salt marshes, mangroves, seagrass, macroalgae, etc. • Spatiotemporal distributions of the pollutants (such as heavy metals, polycyclic aromatic hydrocarbon, etc.) in marine and sediments. • Spatiotemporal evolution pattern modeling and prediction of the marine disasters and abnormal phenomena (such as algal bloom, typhoons, SST anomalies, etc).