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Scott Longmore, Steven Miller, Dan Bikos, Daniel Lindsey, Edward Szoke, Debra Molenar, Donald Hillger, Renate Brummer, and John Knaff

public, as well as monitor weather activity (severe weather in particular) through public posts and images. While severe weather photography contains inherently more information than visual accounts relayed via plain text messaging or phone-in reports, fielding such information from social media can be challenging and time-consuming to forecasters, as they navigate repetitive, irrelevant, or even dubious, conflicting information. This paper presents a photo report (PR) system concept that bypasses

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Pamela G. Posey, Richard A. Allard, Ruth H. Preller, and Gretchen M. Dawson

and the performance of U.S. Navy sea, air, or land (SEAL) swimmers. The U.S. Navy’s globally relocatable tidal prediction model, PCTides, was developed to fill a void in the navy’s global tide forecasting capability. Previously, tidal forecasts available to the navy were confined to coastal locations where water-level data were available. This restricted tidal forecasts to small areas between tidal stations. In addition, these forecasts did not include the effects of wind (surge), which can play a

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M.-I. Pujol, S. Dobricic, N. Pinardi, and M. Adani

four satellites into an oceanographic data analysis system of the northern Atlantic, and he found that the impact of the addition of a fourth satellite was insignificant. However, his result was obtained by a coarse spatial resolution model setup (⅓°) and the weekly assimilation window. In this study we will estimate the impact of the multimission spatial/temporal coverage on the analyses of the Mediterranean Forecasting System (MFS; Pinardi et al. 2003 ; N. Pinardi and Coppini 2010, unpublished

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Xining Zhang and Hao Dai

cost is very high. The data-driven prediction methods for the time series data, which are independent of mathematical and physical models of study objects, examine inherent laws of data characteristics and forecast. The mature techniques are mainly based on supporting vector machine (SVM; Mahjoobi and Mosabbe 2009 ), filters ( Altunkaynak and Özger 2004 ), genetic algorithm (GA; Gaur and Deo 2008 ; Cañellas et al. 2010 ), fuzzy logic ( Özger and Sen 2007 ), and the hybrid of wavelet and fuzzy

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E. Goldberg, R. Kittredge, and A. Polguère

VOL. 5, NO. 4 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY AUGUST 1988Computer Generation of Marine Weather Forecast TextE. GOLDBERGAtmospheric Environment Service, Environment Canada, Toronto, CanadaR. KITTREDGE AND A. POLGU~REDepartement de Linguistique, Universite de Montreal, Montreal, Canada(Manuscript received 19 February 1987, in final form 9 December 1987)ABSTRACT MARWORDS is a natural language text generation

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Chandrasekar Radhakrishnan and V. Chandrasekar

1. Introduction With an expanding populace in urban territories, the precise forecast of extreme weather conditions is basic for sparing property and lives. The World Meteorological Organization (WMO) advises for nowcasting systems to be able to forecast severe weather conditions up to 6 h ahead ( Wang 2017 ). The radar-based nowcasting methods, which use radar reflectivity or radar estimated quantitative precipitation estimation (QPE) fields, are more effective in shorter time spans. The radar

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Colin Y. Shen, Thomas E. Evans, and Steven Finette

1. Introduction It has long been recognized in weather forecasting that the slightest error in the initial state of the forecast may lead to a rapid unrestrained growth of forecast errors, eventually rendering the forecast unreliable ( Lorenz 1963 ). Such an outcome clearly has implications to ocean and climate model predictions as well, which, similar to weather forecasting, must rely on observations to approximate the initial states. To what degree a model prediction can be considered

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M. Benkiran and E. Greiner

1. Introduction Data assimilation in meteorology has generally been performed in an intermittent manner over the last decades. Data are gathered over a given period of time (say 6 h), and some optimal interpolation or 3D variational analysis is performed to produce the best analyzed fields. The model is then restarted from these fields, and run in a forecast mode, over a few days. However, the imbalance between the analysis increment and the model physics generally produces model shock. This

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Faisal S. Boudala, George A. Isaac, Robert W. Crawford, and Janti Reid

prediction (NWP) models also forecast V k , but no systematic way of forecasting RVR has been fully developed. This is partly due to the fact that RVR prediction not only depends on atmospheric extinction ( β ), but also on runway light intensity ( I ) and background light (BL), which are very difficult to forecast. This will be discussed in more detail later. In this paper, new parameterizations that can be used to forecast RVR under snow, rain, and fog conditions will be developed and tested using

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Nathan M. Reiss and James C. Hofmann

368 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY -OLUME5TEACHMET: An Expert System for Teaching Weather Forecasting*NATHAN M. REISS AND JAMES C. HOFMANN**RutgerswThe State University of New Jersey, New Brunswick, New Jersey18 May 1987 and 25 August 1987ABSTRACT Students of weather forecasting need to learn to identify efficiently the information relevant to the elementsthey predict. One way students

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