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Philippe Arbogast, Karine Maynard, and Catherine Piriou

of PV modification, inspired by information derived from satellite imagery ( Rosting et al. 1996 ; Mansfield 1997 ; Browning 1997 ; Demirtas and Thorpe 1999 ). Georgiev and Martin (2001) and Santurette and Georgiev (2005) have shown that model PV fields near the tropopause can be checked against satellite images of water vapor (WV). The idea here is that when an error is detected, one should be able to modify the PV of a model field based on WV observations and subsequently let a numerical

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James J. Gurka, Eugene P. Auciello, Anthony F. Gigi, Jeff S. Waldstreicher, Kermit K. Keeter, Steven Businger, and Laurence G. Lee

-air cyclogenesis. The ability of operational dynamical models to predict East Coast cyclonesand, in particular, explosive cyclogenesis is explored. An operational checklist that utilizes information fromthe Nested Grid Model to forecast the potential for rapid cyclogenesis is also described. A review of signaturesrelated to cyclogenesis in visible, infrared, and water vapor satellite imagery is presented. Finally, a study ofwater vapor imagery for 16 cases of explosive cyclogenesis between 1988 and 1990

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Richard J. Reed and Mark D. Albright

wind data from a research aircraft flying at approximately 300 m above ground level (AGL). A secondary objective is to establish the relationship of the surface front to features seen in satellite visible, infrared, and water vapor imagery. Prior to examining the flight data, a description is given of the development of the cyclone from its complex early beginnings to the mature state that existed at the time of main interest. However, a complete treatment and fully illustrated documentation of the

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Shih-Yu Wang, Tsing-Chang Chen, and S. Elwynn Taylor

rainfall, but numerically examining different CPSs or CPS settings is beyond the scope of this study. Thus, the water vapor budget analysis, which portrays the precipitation process, is used to diagnose forecasted rainfall and provide implications for the deficiency of CPSs. The vertically integrated water vapor flux ( Q ) is expressed as where V is the wind field and q is the specific humidity. Previous hydrological studies focusing on the central United States have recognized the importance

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Douglas K. Miller

available water vapor or through increasing the mean temperature (saturation vapor pressure) in the BL. The model-simulated 24-h liquid equivalent accumulated precipitation in the 1.5-km domain during P34 is shown for three surface LH flux experiments in Fig. 18 and should be compared to the default simulation map plotted in Fig. 13a . Not surprisingly, enhanced surface LH fluxes bring air parcels to saturation sooner, resulting in accumulation increases in both the Cumberland Plateau and near the

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Barry H. Lynn, Guy Kelman, and Gary Ellrod

) as “direct insertion” or nudging. The rationale is that the lightning assimilation does not impact other grid boxes through a spatial correlations approach. Instead, lightning assimilation involves modifying the forecast fields by locating lightning in individual grids at predetermined fixed-time intervals (here, 10 min). Adjustments to the humidity profile are made naturally and gradually at every time step after the update of the water vapor mass within the model (no adjustments to the wind or

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Zuohao Cao and Da-Lin Zhang

forecasting SSR in operation ( Johnson and Moser 1992 ). To determine how efficiently water vapor is converted into cloud water, we compare the cloud coverage between the NARR and the GEM regional model forecast. Table 2 shows a point (in Ottawa) comparison of cloud coverage between the NARR and model-predicted values. The NARR low-, middle-, and high-level cloud 2 coverages at 0300 UTC in Ottawa are 60%–80%, 60%–80%, and >80%, respectively, whereas the model-predicted coverages are about >85%, 28%, and

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Timothy J. Schmit, Wayne F. Feltz, W. Paul Menzel, James Jung, Andrew P. Noel, James N. Heil, James P. Nelson III, and Gary S. Wade

at high temporal resolution. Comparisons of GOES sounder derived total precipitable water vapor (TPW) with the same derived from the CART site microwave radiometer are discussed in section 3 . In addition, moisture retrievals from GOES in conjunction with an upward-looking high spectral resolution infrared instrument are presented. The impact of moisture information on numerical model forecasts provides another means of assessing the quality and applicability of the sounder moisture profiles and

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Dan Bikos, John Weaver, and Brian Motta

recorded in the state. This note examines the utility of Geostationary Operational Environmental Satellite (GOES) imagery in identifying aspects of the synoptic and mesoscale environments not well resolved by numerical models. Water vapor imagery will be shown to reveal an upper-level jet streak that moved into Oklahoma at the time of convective initiation. Jet streaks can be important to severe convective outbreaks. Fawbush et al. (1951) observed that one of the conditions favorable for tornado

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R. Fehlmann, C. Quadri, and H. C. Davies

temporal resolution of 6 h. They constitute a state-of-the-art synoptic-scale dataset. An additional data source for information on the location and structure of the upper-level filament is the Meteosat water vapor imagery. These images are derived from radiance measurements in the spectral region centered around 6.3 μm and provide a measure of the integrated water vapor content above approximately 500 hPa with a horizontal resolution of ∼8 km × 5 km ( Fischer et al. 1981 ). Dark bands on these images

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