Search

Now showing items 1-10 of 10

Development and Tests of a New Distributed-Memory MM5 Adjoint

Source: Journal of Atmospheric and Oceanic Technology:;2006:;volume( 023 ):;issue: 003:;page 424

Author(s): Ruggiero, Frank H.; Michalakes, John; Nehrkorn, Thomas; Modica, George D.; Zou, Xiaolei

Publisher: American Meteorological Society

Abstract: Updated versions of the Tangent Linear Model (TLM) and adjoint of the fifth-generation Pennsylvania State University?National Center for Atmospheric Research Mesoscale Model (MM5) have been developed and are now available ...

WRF-Fire: Coupled Weather–Wildland Fire Modeling with the Weather Research and Forecasting Model

Source: Journal of Applied Meteorology and Climatology:;2012:;volume( 052 ):;issue: 001:;page 16

Author(s): Coen, Janice L.; Cameron, Marques; Michalakes, John; Patton, Edward G.; Riggan, Philip J.; Yedinak, Kara M.

Publisher: American Meteorological Society

Abstract: wildland fire-behavior module, named WRF-Fire, was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire-behavior model that is two-way ...

Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model

Source: Monthly Weather Review:;2012:;volume( 140 ):;issue: 009:;page 3017

Author(s): Fitch, Anna C.; Olson, Joseph B.; Lundquist, Julie K.; Dudhia, Jimy; Gupta, Alok K.; Michalakes, John; Barstad, Idar

Publisher: American Meteorological Society

Abstract: new wind farm parameterization has been developed for the mesoscale numerical weather prediction model, the Weather Research and Forecasting model (WRF). The effects of wind turbines are represented by imposing a momentum ...

Application of an Adiabatic WRF Adjoint to the Investigation of the May 2004 McMurdo, Antarctica, Severe Wind Event

Source: Monthly Weather Review:;2008:;volume( 136 ):;issue: 010:;page 3696

Author(s): Xiao, Qingnong; Kuo, Ying-Hwa; Ma, Zaizhong; Huang, Wei; Huang, Xiang-Yu; Zhang, Xiaoyan; Barker, Dale M.; Michalakes, John; Dudhia, Jimy

Publisher: American Meteorological Society

Abstract: The tangent linear and adjoint of an adiabatic version of the Weather Research and Forecasting (WRF) Model with its Advanced Research WRF (ARW) dynamic core have been developed. The source-to-source automatic differentiation ...

CORRIGENDUM

Source: Monthly Weather Review:;2013:;volume( 141 ):;issue: 004:;page 1395

Author(s): Fitch, Anna C.; Olson, Joseph B.; Lundquist, Julie K.; Dudhia, Jimy; Gupta, Alok K.; Michalakes, John; Barstad, Idar; Archer, Cristina L.

Publisher: American Meteorological Society

The Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA

Source: Bulletin of the American Meteorological Society:;2012:;volume( 093 ):;issue: 006:;page 831

Author(s): Barker, Dale; Huang, Xiang-Yu; Liu, Zhiquan; Auligné, Tom; Zhang, Xin; Rugg, Steven; Ajjaji, Raji; Bourgeois, Al; Bray, John; Chen, Yongsheng; Demirtas, Meral; Guo, Yong-Run; Henderson, Tom; Huang, Wei; Lin, Hui-Chuan; Michalakes, John; Rizvi, Syed; Zhang, Xiaoyan

Publisher: American Meteorological Society

Abstract: milation is the process by which observations are combined with short-range NWP model output to produce an analysis of the state of the atmosphere at a specified time. Since its inception in the late 1990s, the multiagency ...

Four-Dimensional Variational Data Assimilation for WRF: Formulation and Preliminary Results

Source: Monthly Weather Review:;2009:;volume( 137 ):;issue: 001:;page 299

Author(s): Huang, Xiang-Yu; Xiao, Qingnong; Barker, Dale M.; Zhang, Xin; Michalakes, John; Huang, Wei; Henderson, Tom; Bray, John; Chen, Yongsheng; Ma, Zaizhong; Dudhia, Jimy; Guo, Yongrun; Zhang, Xiaoyan; Won, Duk-Jin; Lin, Hui-Chuan; Kuo, Ying-Hwa

Publisher: American Meteorological Society

Abstract: The Weather Research and Forecasting (WRF) model?based variational data assimilation system (WRF-Var) has been extended from three- to four-dimensional variational data assimilation (WRF 4D-Var) to meet the increasing ...

Prediction of Landfalling Hurricanes with the Advanced Hurricane WRF Model

Source: Monthly Weather Review:;2008:;volume( 136 ):;issue: 006:;page 1990

Author(s): Davis, Christopher; Wang, Wei; Chen, Shuyi S.; Chen, Yongsheng; Corbosiero, Kristen; DeMaria, Mark; Dudhia, Jimy; Holland, Greg; Klemp, Joe; Michalakes, John; Reeves, Heather; Rotunno, Richard; Snyder, Chris; Xiao, Qingnong

Publisher: American Meteorological Society

Abstract: Real-time forecasts of five landfalling Atlantic hurricanes during 2005 using the Advanced Research Weather Research and Forecasting (WRF) (ARW) Model at grid spacings of 12 and 4 km revealed performance generally competitive ...

Regional Climate–Weather Research and Forecasting Model

Source: Bulletin of the American Meteorological Society:;2012:;volume( 093 ):;issue: 009:;page 1363

Author(s): Liang, Xin-Zhong; Xu, Min; Yuan, Xing; Ling, Tiejun; Choi, Hyun I.; Zhang, Feng; Chen, Ligang; Liu, Shuyan; Su, Shenjian; Qiao, Fengxue; He, Yuxiang; Wang, Julian X. L.; Kunkel, Kenneth E.; Gao, Wei; Joseph, Everette; Morris, Vernon; Yu, Tsann-Wang; Dudhia, Jimy; Michalakes, John

Publisher: American Meteorological Society

Abstract: is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) ...

The Weather Research and Forecasting (WRF) Model: Overview, System Efforts, and Future Directions

Source: Bulletin of the American Meteorological Society:;2017:;volume( 098 ):;issue: 008:;page 1717

Author(s): Powers, Jordan G.; Klemp, Joseph B.; Skamarock, William C.; Davis, Christopher A.; Dudhia, Jimy; Gill, David O.; Coen, Janice L.; Gochis, David J.; Ahmadov, Ravan; Peckham, Steven E.; Grell, Georg A.; Michalakes, John; Trahan, Samuel; Benjamin, Stanley G.; Alexander, Curtis R.; Dimego, Geoffrey J.; Wang, Wei; Schwartz, Craig S.; Romine, Glen S.; Liu, Zhiquan; Snyder, Chris; Chen, Fei; Barlage, Michael J.; Yu, Wei; Duda, Michael G.

Publisher: American Meteorological Society

Abstract: arguably the world?s most widely-used numerical weather prediction model, the Weather Research and Forecasting Model offers a spectrum of capabilities for an extensive range of applications.