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Robert P. d’Entremont, Richard Lynch, Gennadi Uymin, Jean-Luc Moncet, Ryan B. Aschbrenner, Mark Conner, and Gary B. Gustafson

-cloud thresholds are adapted to pixel-specific atmospheric, earth surface, and view-illumination geometry conditions using cloud-free radiative transfer model simulations. Statistical techniques are also used in cloud detection models to estimate the radiative characteristics of the clear state. Lyapustin et al. (2008) present a spatial-context approach to prescribing baseline clear-sky conditions using a time series of multispectral MODIS cloud-cleared radiance observations. The U.S. Air Force (USAF) 557th

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Charles A. Doswell III, Alan R. Moller, and Harold E. Brooks

“severe weather”) forecasts, most notably those associated with tornadoes, the recipients of the various forecast products [outlooks, watches, and warnings; see Ostby (1992) ] must accept some level of responsibility for their own safety. Since the pioneering tornado forecasting efforts of United States Air Force meteorologists Ernest J. Fawbush and Robert C. Miller, the public has come to accept that the National Weather Service (hereafter, NWS) will provide forecasts and warnings to help the users

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D. Hudson, A. G. Marshall, O. Alves, G. Young, D. Jones, and A. Watkins

and the Tasman Sea ( Fig. 5 ). Fig . 5. (top) The 500-hPa geopotential height anomalies (m) and (bottom) 200-hPa wind anomalies (m s −1 ; note the different scaling for the vectors) for January 2013 from (left) ERA-Interim ( Dee et al. 2011 ) and (right) the POAMA ensemble mean forecast initialized on 27 Dec 2012. It is not clear what process or driver is providing the predictability for these forecasts. In an attribution study using a suite of coupled-model experiments with natural forcings

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David J. Stensrud and Robert A. Maddox

sinkingair may have helped maintain a capping inversion at the top of a deepening moist layer and apparently wassufficient to inhibit development of new convection even in the face of strong low-level forcing. The caseillustrates the simultaneous development of mesoscale circulations that appear to be acting in opposition toeach other, relative to the initiation of new storms. It further illustrates the complexity of the mesoscale andwhy it is often hard to anticipate the evolution of convective storm

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Blaine C. Thomas and Jonathan E. Martin

-level moisture from the Great Lakes into the clipper ( Harms 1973 ; Vinzani and Changnon 1981 ; Silberberg 1990 , Angel and Isard 1997 ) or as a result of locally intense upper-level forcing in the presence of low conditional stability (either potential or symmetric) ( Smart and Carr 1986 ; Silberberg 1990 ; Gallus and Bresch 1997 ). Often the most significant sensible weather element associated with Alberta clippers is strong wind. Areas in the lee of the Rocky Mountains and Alberta are susceptible to

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John Manobianco and Paul A. Nutter

to as NM99) is designed to assess the utility of the model for weather forecasting in support of operational requirements for the U.S. Air Force 45th Weather Squadron (45WS), National Weather Service (NWS) Spaceflight Meteorology Group (SMG), and NWS Weather Forecast Office in Melbourne, Florida (MLB). The 45WS provides weather support for all ground and launch operations from the Cape Canaveral Air Station/Kennedy Space Center (CCAS/KSC), general aviation at Patrick Air Force Base, and space

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Christopher Grassotti, Ross N. Hoffman, Enrique R. Vivoni, and Dara Entekhabi

-induced river flows and flooding ( Smith et al. 1996a ; Sturdevant-Rees et al. 2001 ; Bedient et al. 2000 ; Vieux and Bedient 1998 ; Yates et al. 2001 ; Pereira Fo and Crawford 1999 ; Landel et al. 1999 ; Carpenter et al. 2001 ; Grecu and Krajewski 2001 ; Finnerty et al. 1997 ). For example, precipitation data derived from NEXRAD reflectivity are now routinely used to force both lumped (e.g., Johnson et al. 1999 ) and distributed (e.g., Carpenter et al. 2001 ) hydrologic models as well as to

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Jonathan L. Case, John Manobianco, Allan V. Dianic, Mark M. Wheeler, Dewey E. Harms, and Carlton R. Parks

1. Introduction The Regional Atmospheric Modeling System (RAMS; Pielke et al. 1992 ) numerical weather prediction (NWP) model is run in real time at the Cape Canaveral Air Force Station (CCAFS) to support operations of the U.S. space program. RAMS represents the NWP portion of the Eastern Range Dispersion Assessment System (ERDAS; Lyons et al. 1993 ), which was developed by the Mission Research Corporation (MRC)/ASTER Division for the U.S. Air Force (USAF). Delivered to the Eastern Range at

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Kathleen L. McInnes, John L. McBride, and Lance M. Leslie

function are presented for the simulated fronts. Consistentstructural relationships are shown to exist between these fields. The front is seen as part of a larger-scale troughextending through the depth of the troposphere, and its location and movement occur in association withsignificant quasigeostrophic forcing. The line of maximum cyclonic ~' corresponds most closely to the surfacewind shift line, and this feature represents the most unambiguous means of defining the front from the modelfields. In

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Parthasarathi Mukhopadhyay, Peter Bechtold, Yuejian Zhu, R. Phani Murali Krishna, Siddharth Kumar, Malay Ganai, Snehlata Tirkey, Tanmoy Goswami, M. Mahakur, Medha Deshpande, V. S. Prasad, C. J. Johny, Ashim Mitra, Raghavendra Ashrit, Abhijit Sarkar, Sahadat Sarkar, Kumar Roy, Elphin Andrews, Radhika Kanase, Shilpa Malviya, S. Abhilash, Manoj Domkawale, S. D. Pawar, Ashu Mamgain, V. R. Durai, Ravi S. Nanjundiah, Ashis K. Mitra, E. N. Rajagopal, M. Mohapatra, and M. Rajeevan

sections 2 – 3 . The synoptic conditions and observations are presented in section 4 . Section 5 aims to explain the forcing and physical mechanism of the rain events based on ERA (ECMWF Reanalyses) analyses. The skill of the high-resolution deterministic and ensemble forecasts is discussed in sections 6 and 7 , and a summary is given in section 8 . 2. Observing convection The India Meteorological Department at Kochi has a dual-polarization Doppler weather radar that operates at 2.832-GHz

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