The Development of a Terrain-Resolving Scheme for the Forward Model and Its Adjoint in the Four-Dimensional Variational Doppler Radar Analysis System (VDRAS)

AbstractThe four-dimensional Variational Doppler Radar Analysis System (VDRAS) developed at the National Center for Atmospheric Research (NCAR) is significantly improved by implementing a terrain-resolving scheme to its forward model and adjoint based on the ghost cell immersed boundary method (GCIBM), which allows the topographic effects to be considered without the necessity to rebuild the model on a terrain-following coordinate system. The new system, called IBM_VDRAS, is able to perform forward forecast and backward adjoint model integration over nonflat lower boundaries, ranging from mountains with smooth slopes to buildings with sharp surfaces. To evaluate the performance of the forward model over complex terrain, idealized numerical experiments of a two-dimensional linear mountain wave and three-dimensional leeside vortices are first conducted, followed by a comparison with a simulation by the Weather Research and Forecasting (WRF) Model. An observing system simulation experiment is also conducted ...

[1]  J. Lundquist,et al.  An Immersed Boundary Method for the Weather Research and Forecasting Model , 2014 .

[2]  David Simonin,et al.  Performance of 4D‐Var NWP‐based nowcasting of precipitation at the Met Office for summer 2012 , 2016 .

[3]  Juanzhen Sun,et al.  Analysis and Forecasting of the Low-Level Wind during the Sydney 2000 Forecast Demonstration Project , 2004 .

[4]  Richard Rotunno,et al.  Lessons on orographic precipitation from the Mesoscale Alpine Programme , 2007 .

[5]  Oliver Fuhrer,et al.  Numerical consistency of metric terms in terrain-following coordinates , 2003 .

[6]  Ying Zhang,et al.  Analysis and Prediction of a Squall Line Observed during IHOP Using Multiple WSR-88D Observations , 2008 .

[7]  J. Ferziger,et al.  A ghost-cell immersed boundary method for flow in complex geometry , 2002 .

[8]  R. James Purser,et al.  Recursive Filter Objective Analysis of Meteorological Fields: Applications to NESDIS Operational Processing , 1995 .

[9]  R. Franke Scattered data interpolation: tests of some methods , 1982 .

[10]  R. Houze Orographic effects on precipitating clouds , 2012 .

[11]  Lindsay J. Bennett,et al.  An Observational and Modeling Study of the Processes Leading to Deep, Moist Convection in Complex Terrain , 2014 .

[12]  Kazuo Saito,et al.  A Cloud-Resolving 4DVAR Assimilation Experiment for a Local Heavy Rainfall Event in the Tokyo Metropolitan Area , 2011 .

[13]  Juanzhen Sun,et al.  Real-Time Low-Level Wind and Temperature Analysis Using Single WSR-88D Data , 2001 .

[14]  Juanzhen Sun,et al.  Initialization and Numerical Forecasting of a Supercell Storm Observed during STEPS , 2005 .

[15]  Juanzhen Sun,et al.  Assimilating Radar, Surface, and Profiler Data for the Sydney 2000 Forecast Demonstration Project , 2001 .

[16]  C. Peskin Flow patterns around heart valves: A numerical method , 1972 .

[17]  Juanzhen Sun,et al.  The Implementation of the Ice-Phase Microphysical Process into a Four-Dimensional Variational Doppler Radar Analysis System (VDRAS) and Its Impact on Parameter Retrieval and Quantitative Precipitation Nowcasting , 2016 .

[18]  E. Kessler On the distribution and continuity of water substance in atmospheric circulations , 1969 .

[19]  Juanzhen Sun,et al.  Radar Data Assimilation with WRF 4D-Var. Part II: Comparison with 3D-Var for a Squall Line over the U.S. Great Plains , 2013 .

[20]  Juanzhen Sun,et al.  Raindrop Size Distribution and Rain Characteristics during the 2013 Great Colorado Flood , 2016 .

[21]  J. Derber,et al.  Variational Data Assimilation with an Adiabatic Version of the NMC Spectral Model , 1992 .

[22]  Juanzhen Sun,et al.  Dynamical and Microphysical Retrieval from Doppler Radar Observations Using a Cloud Model and Its Adjoint. Part II: Retrieval Experiments of an Observed Florida Convective Storm , 1998 .

[23]  Juanzhen Sun,et al.  Radar Data Assimilation with WRF 4D-Var. Part I: System Development and Preliminary Testing , 2013 .

[24]  Y. Tseng,et al.  An improved hybrid Cartesian/immersed boundary method for fluid–solid flows , 2007 .

[25]  Juanzhen Sun,et al.  Precipitation Forecasting Using Doppler Radar Data, a Cloud Model with Adjoint, and the Weather Research and Forecasting Model: Real Case Studies during SoWMEX in Taiwan , 2011 .

[26]  D. Durran,et al.  A Compressible Model for the Simulation of Moist Mountain Waves , 1983 .

[27]  Takehiko Satomura,et al.  Nonhydrostatic Atmospheric Modeling Using a Combined Cartesian Grid , 2010 .

[28]  C. Schär,et al.  Vortex Formation and Vortex Shedding in Continuously Stratified Flows past Isolated Topography. , 1997 .

[29]  C. Kottmeier,et al.  The convective and orographically-induced precipitation study: A research and development project of the world weather research program , 2008 .

[30]  Volker Wulfmeyer,et al.  RESEARCH CAMPAIGN: The Convective and Orographically Induced Precipitation Study , 2008 .

[31]  Juanzhen Sun,et al.  Dynamical and Microphysical Retrieval from Doppler Radar Observations Using a Cloud Model and Its Adjoint. Part I: Model Development and Simulated Data Experiments. , 1997 .

[32]  Juanzhen Sun,et al.  The influence of erroneous background, beam‐blocking and microphysical non‐linearity on the application of a four‐dimensional variational Doppler radar data assimilation system for quantitative precipitation forecasts , 2014 .

[33]  Ronald B. Smith Linear theory of stratified hydrostatic flow past an isolated mountain , 1980 .

[34]  Ching-Yuang Huang A Forward-in-Time Anelastic Nonhydrostatic Model in a Terrain-Following Coordinate , 2000 .

[35]  Juanzhen Sun,et al.  A Frequent-Updating Analysis System Based on Radar, Surface, and Mesoscale Model Data for the Beijing 2008 Forecast Demonstration Project , 2010 .

[36]  N. A. Phillips,et al.  A COORDINATE SYSTEM HAVING SOME SPECIAL ADVANTAGES FOR NUMERICAL FORECASTING , 1957 .

[37]  Piotr K. Smolarkiewicz,et al.  Low Froude Number Flow Past Three-Dimensional Obstacles. Part I: Baroclinically Generated Lee Vortices , 1989 .

[38]  Juanzhen Sun,et al.  A Velocity Dealiasing Technique Using Rapidly Updated Analysis from a Four-Dimensional Variational Doppler Radar Data Assimilation System , 2010 .

[39]  J. Lundquist,et al.  An Immersed Boundary Method Enabling Large-Eddy Simulations of Flow over Complex Terrain in the WRF Model , 2012 .

[40]  V. Chandrasekar,et al.  The Great Colorado Flood of September 2013 , 2015 .