Search Results

You are looking at 21 - 30 of 1,076 items for :

  • Waves, atmospheric x
  • Weather and Forecasting x
  • All content x
Clear All
Todd D. Sikora, Karen S. Friedman, William G. Pichel, and Pablo Clemente-Colón

elongated sea surface slick acts to dampen the centimeter-scale wind-driven wave state. Examples of SAR image interpretation in the context of the present research will be discussed next. It may be surprising to learn that many microscale and mesoscale SAR signatures of atmospheric phenomena mimic their corresponding cloud signatures. This is because clouds are often tied to the same near-surface wind field that is forcing the SAR signal. For example, while the cloud manifestations of roll vortices are

Full access
Steven G. Decker and David A. Robinson

the interaction between the peculiar geography of High Point and the atmospheric wind and stability profiles present in the region, namely, a downslope windstorm. Section 2 discusses the geography of the area and provides a synoptic overview of the windstorm based on observations and short-term model forecasts. Section 3 uses mountain wave theory to demonstrate that the atmospheric conditions during the windstorm were consistent with those necessary to produce enhanced winds. Section 4

Full access
Haldun Karan, Patrick J. Fitzpatrick, Christopher M. Hill, Yongzuo Li, Qingnong Xiao, and Eunha Lim

1992 ; Ziegler et al. 1995 ; Hane et al. 1993 ; Atkins et al. 1998 ; Karan and Knupp 2006 ). The interaction of CBZs with horizontal convective rolls (HCRs: Xue and Martin 2006 ; Dailey and Fovell 1999 ; Fovell 2005 ; Wakimoto and Kingsmill 1995 ) and collisions with one another ( Intrieri et al. 1990 ; Kingsmill and Crook 2003 ) are some triggers for convection. Gravity waves and atmospheric bores (ABs), commonly observed at the inversion level atop the convective boundary layer (CBL

Full access
Young-Joon Kim and Maria Flatau

atmospheric forecast model. J. Geophys. Res. , 112 , D13104 . doi:10.1029/2007JD008647 . Kim, Y-J. , and Arakawa A. , 1995 : Improvement of orographic gravity wave parameterization using a mesoscale gravity-wave model. J. Atmos. Sci. , 52 , 1875 – 1902 . 10.1175/1520-0469(1995)052<1875:IOOGWP>2.0.CO;2 Kim, Y-J. , and Doyle J. D. , 2005 : Extension of an orographic drag parameterization scheme to incorporate orographic anisotropy and flow blocking. Quart. J. Roy. Meteor. Soc. , 131

Full access
Mary M. Cairns and Jonathan Corey

Users' Workshop, Boulder, CO, NCAR, 49–50 . Durran, D. R. , 1986 : Mountain waves. Mesoscale Meteorology and Forecasting, P. S. Ray, Ed., Amer. Meteor. Soc., 472–492 . Durran, D. R. , 1990 : Mountain waves and downslope winds. Atmospheric Processes over Complex Terrain, Meteor. Monogr., No. 45, 59–81 . Gallus W. A. Jr., , 2000 : The impact of step orography on flow in the Eta Model: Two contrasting examples. Wea. Forecasting , 15 , 630 – 637 . 10

Full access
Shiqiu Peng, Yineng Li, Xiangqian Gu, Shumin Chen, Dongxiao Wang, Hui Wang, Shuwen Zhang, Weihua Lv, Chunzai Wang, Bei Liu, Duanling Liu, Zhijuan Lai, Wenfeng Lai, Shengan Wang, Yerong Feng, and Junfeng Zhang

relatively high accuracy since its establishment. EPMEF, however, is continuously being developed and improved. In the future, a three-way-interactive air–sea–wave coupled system will replace the current one-way-downstream version, with a higher grid resolution for the atmospheric component. Furthermore, a data assimilation package will be incorporated into EPMEF for assimilating both the atmospheric and oceanic observations (including in situ and satellite-derived observations) using three- and four

Full access
Graeme D. Hubbert, Greg J. Holland, Lance M. Leslie, and Michael J. Manton

developed by Hubbert el al. (1990) has been configuredto provide a stand-alone system to forecast tropical cyclone storm surges. The atmospheric surface pressure andsurface winds are derived from the analytical-empirical model of Holland (1980) and require only cyclonepositions, central pressures, and radii of maximum winds. The model has been adapted to run on personalcomputers in a few minutes so that multiple forecast scenarios can be tested in a forecast o~ce in real time. The storm surge model

Full access
Prakki Satyamurty and Daniel Pires Bittencourt

difference in the phase of the short wave in the forecast with respect to the verifying analysis. 5. Summary and conclusions The performance statistics of numerical weather prediction models applied to derived atmospheric fields such as humidity convergence or thermal advection can be quite different from those applied to simple or basic model output variables such as wind components or temperature. The prediction skill as estimated from the anomaly correlation and root-mean-square error with respect to

Full access
Jennifer C. Roman, Gonzalo Miguez-Macho, Lee A. Byerle, and Jan Paegle

1. Introduction A number of atmospheric forecast models have been developed and now display considerable skill in weather prediction. The underlying philosophy of these developments is that improved models and more accurate initial conditions should provide better forecasts. The importance of specific model improvements relative to specific observational enhancements may, nonetheless, still be inadequately understood. White et al. (1999) addressed some of these questions, and suggested the

Full access
David R. Walker and Robert E. Davis

SEPTEMBER 1995 WALKER AND DAVIS 545Error Climatology of the 80-Wave Medium-Range Forecast Model DAVID R. WALKER*Climate Prediction Center, National Meteorological Center, NWS/NOAA, Washington, D.C. ROBERT E. DAVISDepartment of Environmental Sciences, University of Virginia, Charlottesville, Virginia(Manuscript received 7 December 1993, in final form 27 February 1995

Full access