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Tal Ezer and George L. Mellor

1. Introduction With the development of more realistic numerical ocean models and the availability of satellite data in almost real time, the prospect of nowcasting and forecasting the ocean, as is done by numerical weather prediction models, becomes increasingly feasible. For example, an experimental coastal forecast system, based on the coupling of the Princeton Ocean Model (POM) used here to a mesoscale atmospheric model, has been running in a quasi-operational mode and producing daily

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Renzo Bechini and V. Chandrasekar

1. Introduction The description of the atmospheric state evolution is inherently a three-dimensional problem involving several variables (e.g., for warm rain process: temperature, humidity, pressure, winds, water vapor, cloud water, rainwater). However, nowcasting by radar is in general intended as the two-dimensional forecast of rainwater q r (g kg −1 ) in the near-surface layer. One possible option for precipitation and wind nowcasting is through the use of numerical weather prediction (NWP

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Huizhen Yu, Hongli Wang, Zhiyong Meng, Mu Mu, Xiang-Yu Huang, and Xin Zhang

to add extra observations for initialization in numerical weather prediction, sensitivity analysis can also be used to identify precursors of a weather system or to examine the possible interaction between different synoptic systems ( Wu et al. 2007 , 2009a ), which could be quite useful for identifying key contributors to a weather event, especially from an operational forecasting point of view. The results of Wu et al. (2009b) showed that adjoint-based methods could capture the signal of the

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Timothy C. Y. Chui, David Siuta, Gregory West, Henryk Modzelewski, Roland Schigas, and Roland Stull

, . Fink , A. H. , and Coauthors , 2011 : Operational meteorology in West Africa: Observational networks, weather analysis and forecasting . Atmos. Sci. Lett. , 12 , 135 – 141 , . 10.1002/asl.324 Graham , R. , 2014 : DFID-Met Office Climate Science Research Partnership (CSRP): CSRP phase 1—Final report. Met Office Tech. Rep., 105 pp.,

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Peter Rogowski, Mark Otero, Joel Hazard, Thomas Muschamp, Scott Katz, and Eric Terrill

-based remote sensing products. Fig . 4. Time series of visibility (orange) and wind speed (gray) observations from an XMET deployed at the Al Asad Air Base in July 2008. The operational successes of the original XMET systems led to a request from the Department of Defense (DoD) for 11 additional units to create a near-real-time MET network in Afghanistan operation areas during OEF. The utilization of an array of systems provided weather forecasters with in situ observations at discrete locations of

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Chih-Chiang Wei

predict the total rainfall during a typhoon when the storm is still several days away from Taiwan. The concept used in this paper is inspired by the previous work of Wei (2014) , who predicted the hourly rainfall during a typhoon invasion in Taiwan. Wei (2014) used meteorological and radar reflectivity data to simulate the operational forecasting of real-time hourly rainfall for developing a rainfall forecasting model for typhoons. When a typhoon makes landfall over Taiwan, no extra energy is added

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S. Mark Leidner, Bachir Annane, Brian McNoldy, Ross Hoffman, and Robert Atlas

wind fields Two sources for 10-m background surface vector winds were used for this study: 1) 6-h forecasts from a Global Forecast System (GFS) global control OSSE ( Casey et al. 2016 ) that used the 2005 operational T382 3D-Hybrid DA system (approximately 35-km resolution), and 2) 6-h forecasts from an HWRF control OSSE ( McNoldy et al. 2017 ; ~9-km regional resolution). The GFS model is described by NWS (2014) and the GFS DA system by NOAA (2015) . Because this study uses simulated

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Christopher W. Fairall and Richard E. Carbone

VOL. 11, NO.I JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY FEBRUARY 1994 EDITORIALTropospheric Profiling--Matching Research and Operational Needs with Emerging Technologies Measurements of the fundamental atmospheric variables are a key in both forecastingand successful research investigation. In the interest of promoting better interactionsamong technologists, operationalists, and researchers, the Second

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Eunha Lim and Juanzhen Sun

1. Introduction Doppler weather radar data have been used extensively in many meteorological applications, such as detection and nowcasting of hazardous weather and quantitative rainfall forecasting using advanced data assimilation techniques that involve numerical forecast models. Doppler velocity, commonly called radial velocity, has a crucial role in data assimilation for improvement of the quantitative prediction of precipitation ( Sun and Crook 1997 ; Sun 2005a ; Xiao et al. 2007 ). One

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Yi Luo, Xudong Liang, Gang Wang, and Zheng Cao

applied to some nowcasting systems, such as the Generating Advanced Nowcasts for Deployment in Operational Land surface Flood Forecasts (GANDOLF; Bowler et al. 2004 ) and Short-Range Warning of Intense Rainstorms in Localized Systems (SWIRLS; Cheung and Yeung 2012 ). Another method for estimating the motion of thunderstorm is the storm cell centroid identification and tracking technique ( Wilk and Gray 1970 ; Zittel 1976 ; Brady et al. 1978 ; Crane 1979 ; Rosenfeld 1987 ). This method was

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