Search Results

You are looking at 1 - 6 of 6 items for :

  • Cloud forcing x
  • State of the Science of Precipitation Research x
  • All content x
Clear All
Dusanka Zupanski, Sara Q. Zhang, Milija Zupanski, Arthur Y. Hou, and Samson H. Cheung

variables The WRF model is configured to run in a regional domain with options to add nested inner domains with finer resolutions. The regional forecast runs use lateral boundary conditions from global forecast systems such as the NCEP Global Forecast System (GFS). The large-scale forcing is applied at the outer domain boundaries. In a nested domain run, the inner-domain boundary conditions are provided through the interaction with the outer domain. The cloud-resolving microphysics from GCE model ( Tao

Full access
Jonathan J. Gourley, Scott E. Giangrande, Yang Hong, Zachary L. Flamig, Terry Schuur, and Jasper A. Vrugt

upgrade the nationwide network of the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar with polarimetric capability. A reasonable expectation is that improvements in rainfall rate estimation will lead to better skill in hydrologic simulation of stream discharge. This is of particular importance in the context of flooding, the second deadliest of all weather-related hazards in the United States; heat is the number one killer ( Ashley and Ashley 2008 ). Accurate forcing data is a prerequisite for

Full access
Timothy J. Lang, Steven A. Rutledge, and Robert Cifelli

of only one particular type ( Boccippio et al. 2005 ). Variability in microphysical structure is commonly observed as a function of meteorological forcing. For example, in the Amazon basin easterly low-level winds typically result in convection that is more continental in character, whereas westerly flow results in a more maritime structure ( Cifelli et al. 2002 , 2004 ; Halverson et al. 2002 ; Petersen et al. 2002 ; Rickenbach et al. 2002 ; Silva Dias et al. 2002 ). Another example is in

Full access
F. M. Ralph, T. Coleman, P. J. Neiman, R. J. Zamora, and M. D. Dettinger

below is motivated by the need to better understand and predict storm total rainfall and streamflow over several hours to several days in extreme events. To do so, the analysis bridges the fields of meteorology and hydrology. Extreme precipitation forecasts are often low by a factor of 2 in the region partly because weather prediction models do not adequately represent key AR characteristics ( Ralph et al. 2010 ), including landfall duration, and the cloud and precipitation microphysical processes

Full access
Yudong Tian, Christa D. Peters-Lidard, and John B. Eylander

-based precipitation estimates contain considerable errors. This is primarily a result of the inherently indirect nature of precipitation remote sensing, which mostly derives precipitation rates from infrared (IR) or microwave signatures of cloud or ice particles, and to the limited spatial and temporal sampling of the space-borne sensors. Most of the current data products take advantage of the availability of multiple IR and microwave sensors to optimally intercalibrate and merge the retrievals from these sensors

Full access
Sandra E. Yuter, David A. Stark, Justin A. Crouch, M. Jordan Payne, and Brian A. Colle

. A. , and Lee W.-C. , 1995 : Forcing of flow reversal along the windward slopes of Hawaii . Mon. Wea. Rev. , 123 , 3466 – 3480 . Castello, A. F. , and Shelton M. L. , 2004 : Winter precipitation on the U.S. Pacific coast and El Niño–Southern Oscillation Events . Int. J. Climatol. , 24 , 481 – 497 . Cayan, D. R. , and Roads J. O. , 1984 : Local relationships between U.S. West Coast precipitation and monthly mean circulation parameters . Mon. Wea. Rev. , 112 , 1276 – 1282

Full access