The 8 May 2003 Oklahoma City, Oklahoma, tornadic supercell is predicted with the Advanced Regional Prediction System (ARPS)model using four nested grids with 9-km, 1-km, 100-m, and 50-m grid spacings. The Oklahoma City Weather Surveillance Radar-1988 Doppler (WSR-88D) radial velocity and reflectivity data are assimilated through the ARPS three-dimensional variational data assimilation (3DVAR) a...

1 1 Introduction Our original proposal proposed to work in the following areas: (a) Initial and boundary condition sensitivity studies and adjoint applications and development of ARPS 4DVAR; (b) Initialization and prediction of convective storms using 3DVAR and complex cloud analysis and the impact and refinement of cloud analysis procedures; (c) 3DVAR analysis and assimilation of GPS slant-pat...

The hybrid ensemble transform Kalman filter–three-dimensional variational data assimilation (ETKF– 3DVAR) system developed for the Weather Research and Forecasting (WRF) Model was further tested with real observations, as a follow-up for the observation system simulation experiment (OSSE) conducted in Part I. A domain encompassing North America was considered. Because of limited computational r...

An important advantage of variational data assimilation methods is that observations that differ from the analysis variables can be directly analyzed as long as they can be expressed in terms of the model state variables. Examples include radar radial velocity and reflectivity, the GPS precipitable water, and satellite radiances. A variational method produces an analysis that minimizes a cost f...

Proper dynamic equation constraints in data assimilation (DA) systems can help improve balance of analyzed atmospheric state. The formulation of ensemble-variational DA algorithms allows for easy incorporation of such constraints, but their impacts within such DA systems have been little studied. A dynamic constraint based on the steady momentum equations is incorporated into the WRF (Weather R...

The goal of this Masters project is to implement the WRF model with 3D variational assimilation (3DVAR) at MIT. A working version of WRF extends the scope of experimentation to mesoscale problems in both real and idealized scenarios. A state-of-the-art model and assimilation package can now be used to conduct science or as a benchmark to compare new methods with. The second goal of this project...