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Ayla Augst and Martin Hagen

1. Introduction Many studies have proven that the knowledge of the three-dimensional wind vector is of great importance for various kinds of atmospheric topics, from diagnostic research of wind and weather systems (e.g., Van Zadelhoff et al. 2014 ), as well as transport processes in the atmosphere (e.g., Woodhouse et al. 2013 ), to nowcasting and numerical forecasting (e.g., Simonin et al. 2014 ). For all of these disciplines, the 3D wind field is directly—or at least indirectly—of interest

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Daniel L. Rudnick, Russ E. Davis, and Jeffrey T. Sherman

public servers, to forecast and hindcast models, and has resulted in many publications ( Davis et al. 2008 ; Todd et al. 2009 ; Todd et al. 2011a , b , 2012 ; McClatchie et al. 2012 ; Ohman et al. 2013 ; Johnston and Rudnick 2015 ; Jacox et al. 2015 ; Powell and Ohman 2015 ). A particular focus has been to observe the local effects of climate variability as caused by El Niño ( ). By any reasonable operational or scientific measure, the CUGN should be

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C. Anderson, J. Figa, H. Bonekamp, J. J. W. Wilson, J. Verspeek, A. Stoffelen, and M. Portabella

information can be inferred from the radar measurements. The main purpose of ASCAT is to provide estimates of the ocean wind vector to be exploited in weather forecasting and nowcasting, ocean modeling, and climate research applications. Operational wind services have been set up in the framework of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System application ground segment. The ASCAT instrument is also exploited in other operational applications, such as

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Charlie N. Barron, A. Birol Kara, Harley E. Hurlburt, C. Rowley, and Lucy F. Smedstad

( Fox et al. 2002b ). Steric SSH is extracted from the 1/16° global Naval Research Laboratory Layered Ocean Model (NLOM), an operational eddy-resolving global ocean nowcast/forecast system ( Smedstad et al. 2003 ). Both are run operationally for the U.S. Navy at the Naval Oceanographic Office (NAVOCEANO). NLOM assimilates altimeter SSH track data using an optimal interpolation (OI) analysis ( Smedstad et al. 2003 ) with mesoscale covariance calculated from TOPEX/Poseidon and European Remote Sensing

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Valliappa Lakshmanan and Travis Smith

testing cases. The objective of this paper is to describe a technique that makes it possible to extract features from large amounts of spatial data (typically remotely observed, although it could also be numerical model assimilated or forecast fields) and use the features to answer questions in an automated manner. Such automated analysis based on large datasets is referred to as data mining. Data mining is a multidisciplinary field that provides a number of tools that can be useful in meteorological

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Lucy M. Bricheno, Albert Soret, Judith Wolf, Oriol Jorba, and Jose Maria Baldasano

Brown et al. (2010b) . Ardhuin et al. (2007) and Bertotti et al. (2012) have found substantial differences between the results of different operational models of wind and waves for an extreme storm in the western Mediterranean Sea concerning the peak values of wind speed and significant wave height, the general distribution of the fields, and the locations of the maxima. Miller et al. (2010) describe the improvements in integrated forecast system (IFS) skills during the last resolution

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Matthias Steiner and James A. Smith

(not shown). This remains the most challenging situation to deal with, particularly for operational applications such as flash flood forecasting and warning ( Smith et al. 1996 ). The 7 July 1993 storm was a major rain event of the Mississippi River flood episode during the summer of 1993 ( Kunkel et al. 1994 ; Gumley and King 1995 ; Giorgi et al. 1996 ; Arritt et al. 1997 ). The quality control procedure successfully flags and removes the most severe AP echoes ( Fig. 6d ). However, because the

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Qifeng Lu and William Bell

1. Introduction In the last three decades, microwave radiance observations from polar-orbiting satellites have been exploited widely for operational numerical weather prediction (NWP) and for climate studies assessing long-term trends in atmospheric temperatures. Observations from discrete channels in the 50–58-GHz range of the microwave spectrum have been particularly valuable in providing altitude-resolved information on atmospheric temperature, albeit at relatively coarse vertical resolution

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

: Mémorie sur l’Intensité et la Porteé des Phares . Dunod, 70 pp . Boudala, F. S. , and Isaac G. A. , 2009 : Parameterization of visibility in snow: Application in numerical weather prediction models . J. Geophys. Res. , 114 , D19202 , doi:10.1029/2008JD011130 . Bourgouin, P. , 2000 : A method to determine precipitation type . Wea. Forecasting , 15 , 583 – 592 . Côté, J. , Gravel S. , Méthot A. , Patoine A. , Roch M. , and Staniforth A. , 1998a : The operational CMC

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Bertrand Bessagnet, Laurent Menut, Florian Couvidat, Frédérik Meleux, Guillaume Siour, and Sylvain Mailler

.02.012 . 10.1016/j.atmosenv.2017.02.012 Rea , G. , S. Turquety , L. Menut , R. Briant , S. Mailler , and G. Siour , 2015 : Source contributions to 2012 summertime aerosols in the Euro-Mediterranean region . Atmos. Chem. Phys. , 15 , 8013 – 8036 , . 10.5194/acp-15-8013-2015 Rouïl , L. , and Coauthors , 2009 : PREV’AIR: An operational forecasting and mapping system for air quality in Europe . Bull. Amer. Meteor. Soc. , 90 , 73 – 83

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