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Joseph R. Bocchieri and George J. Maglaras

VOL. Ill, NO. 3 MONTHLY WEATHER REVIEW MARCH 1983An Improved Operational System for Forecasting Precipitation Type JOSEPH R. BOCCHIERII AND GEORGE J. MAGLARASTechniques Development Laboratory, National Weather Service, NOAA, Silver Spring, MD 20910(Manuscript received I May 1982, in final form 7 December 1982) ABSTRACT A Model Output Statistics system for forecasting the

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Richard L. Wobus and Eugenia Kalnay

2132 MONTHLY WEATHER REVIEW VOLUME 123Three Years of Operational Prediction of Forecast Skill at NMC PaCHARD L. WOBUS * AND EUGENIA KALNAYDevelopment Division, National Meteorological Center, Washington, D.C.(Manuscript received 28 January 1994, in final form 3 $anuary 1995)ABSTRACT In real time since 1990, the National Meteorological Center (NMC) has been running a system to

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Jenni L. Evans, Justin M. Arnott, and Francesca Chiaromonte

improved operational numerical modeling of these storms ( McAdie and Lawrence 2000 ). Model forecasts for TCs are traditionally assessed predominantly on track, with some attention paid to intensity validation on central pressure ( McBride and Holland 1987 ; Fiorino et al. 1993 ; Surgi et al. 1998 ; Nagata et al. 2001 ; Goerss et al. 2004 ). Little if any attention is paid to the storm structure and validation of quantitative precipitation forecasts for TCs in their infancy. More recently, the

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Sim D. Aberson

12–60-h forecasts) in 15 cases from 1982 to 1995 in the primary numerical guidance for the National Hurricane Center (NHC) official track forecasts ( Burpee et al. 1996 ). These track improvements were as large as the NHC official forecast improvements obtained during the previous 20–25 yr and suggested that operational missions would be effective in reducing numerical track forecast errors. In 1996, NOAA procured a Gulfstream IV-SP (G-IV) jet aircraft, and put it to use in operational “synoptic

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K. F. Dewey

APRIL 1979 K.F. DEWEY 421Lake Erie Induced Mesosystems--An Operational Forecast Model K. F. DEWEYClimatology Program, University of Nebraska, Lincoln 68588(Manuscript received 20 September 1978, in final form 8 January 1979)ABSTRACT All Lake Erie lake-effect days for a 10-year period prior to the 1976-77 snowfall season were utilized in the development of an operational

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Karl W. Hoppel, Stephen D. Eckermann, Lawrence Coy, Gerald E. Nedoluha, Douglas R. Allen, Steven D. Swadley, and Nancy L. Baker

stratospheric meteorological disturbances have unexpectedly large impacts on space weather and its prediction (e.g., Goncharenko et al. 2010 ). Finally, there are emerging defense and civilian technologies that operate in the “near space” environment at altitudes ~20–100 km and require forecast guidance for their operations. The Naval Research Laboratory (NRL) developed an advanced-level physics, high-altitude (ALPHA) prototype of the Navy Operational Global Atmospheric Prediction System (NOGAPS) that

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Steven M. Lazarus, Corey G. Calvert, Michael E. Splitt, Pablo Santos, David W. Sharp, Peter F. Blottman, and Scott M. Spratt

near-infrared-based satellite sensors can consistently provide reliable radiances from which bulk (i.e., upper meter) SST estimates are derived. However, because operational analysis systems generally require contiguous (i.e., no missing data) gridded first-guess fields, some form of compositing is essential. Various compositing techniques may leverage either previous analyses or forecasts, or both. One common approach is a method whereby the warmest pixel or average of the warmest pixels (within a

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Dale A. Lowry and Harry R. Glahn

VOL. 104, NO. 3 MONTHLY WEATHER REVIEW MARCH 1976An Operational Model for Forecasting Probability of Precipitation--PEATMO S PoP DALE A. L0w~y AND HARRY R. GLAHNTechniq,es Development Laboratory, National Weather Service NOAA, Silver Spring, Md. 20910 (Manuscript received 2 September 1975; in revised form 25 November 1975)ABSTRACT A dynamical-statistical model for use in

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Yves Bouteloup

and Derome (1995) . The first one is the method of Lorenz ( Lorenz 1965 ), which is based on the singular modes of the tangent linear model. This method has been adopted operationally at the European Centre for Medium-Range Weather Forecasts (ECMWF) and has been described by Mureau et al. (1993) and Palmer et al. (1993) . They use a Lanczos algorithm to compute, with a T42 primitive equation model, the first eigenvalues of the MM * operator, where M is the tangent linear model and M * its

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Steven E. Peckham, Tatiana G. Smirnova, Stanley G. Benjamin, John M. Brown, and Jaymes S. Kenyon

-frequency perturbations have been removed and the initial model state is balanced. Another challenge is determining the optimal time filtering interval. A longer time interval results in a sharper filter, but also usurps the computational time otherwise available for the operational forecast. A backward–forward two-pass DFI application was developed for the NOAA Rapid Update Cycle (RUC) model/assimilation system ( Benjamin et al. 2004 ) where it was found to be essential to reduce accumulating analysis imbalances for

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