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

Abstract

The 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 with the assimilation of simulated radar data to examine the ability of IBM_VDRAS in analyzing orographically forced moist convection. It is shown that the IBM_VDRAS can retrieve terrain-influenced three-dimensional meteorological fields including winds, thermodynamic, and microphysical parameters with reasonable accuracy. The new system, with the advanced radar data assimilation capability and the GCIBM terrain scheme, has the potential to be used for studying the evolution of convective weather systems under the influence of terrain.

Comparison of Environmental and Mesoscale Characteristics of Two Types of Mountain‐to‐Plain Precipitation Systems in the Beijing Region, China

“…The microphysics scheme in VDRAS combines a Kessler warm rain scheme and a simple ice scheme (Chang et al, ). In addition to its use as a research tool for convective‐scale analyses (Friedrich et al, ; Gochis et al, ; Sun, ; Sun & Zhang, ; Tai et al, ), VDRAS has been used for operational nowcasting in several forecasting offices since 2001 (Crook & Sun, ; Mueller et al, ; Sun et al, ; Sun & Crook, ). The observations assimilated in VDRAS are radial velocity and reflectivity from the six Doppler radars and the AWS network shown in Figure , whereas mesoscale forecast data from the National Center for Atmospheric Research's Weather Research and Forecast (WRF) model are used for first guesses and boundary conditions.…”

Initiation and Development of a Squall Line Crossing Hangzhou Bay

“…VDRAS can retrieve mesoscale dynamical and thermodynamic fields with frequent updating of less than 20 min by assimilating radial velocity and reflectivity data from radar networks and surface observations from dense mesonets. It has been used for convective‐scale data assimilation research (Chang et al., 2016; Sun & Crook, 1994; Tai et al., 2017) and for severe convective events studies (Chang et al., 2014; Friedrich et al., 2016; Gochis et al., 2014; Sun & Zhang, 2008). The 3‐dimensional gridded high‐resolution and frequency updated analyses of meteorological fields created by VDRAS can provide valuable information for this study in which meso and convective‐scale dynamical processes play crucial roles.…”

The Study of Inland Eyewall Reformation of Typhoon Fanapi (2010) Using Numerical Experiments and Vorticity Budget Analysis

“…The three-dimensional spatial correlation coefficient between the vertical velocity and vertical vorticity (calculated using Eq. (22) of Tai et al, 2017) within the VHTs inside four squares in Figure 9 is shown in Figure 10. The good spatial correlation between updrafts and cyclonic vorticities, as indicated by the fact that the spatial correlation coefficients between two variables are near 0.5 or above during 0900-1100 UTC, supports the existence of VHTs within the rainband of TC Fanapi.…”