The implementation of a multi-scale three dimensional variational (MS3DVAR) data assimilation scheme for use with the Navy Coastal Ocean Model (NCOM) in the Kuroshio Extension western boundary current region is presented here. This work leverages on Li et al. (2013), who initially developed this method. MS3DVAR data assimilation allows for the effective assimilation of both spatially coarse and...

The assimilation of Special Sensor Microwave Imager (SSM/I) data into the Mesoscale Model 5 (MM5) allows for improving the weather forecast. However the results suggested an update the Radiative Transfer Equation (RTE) within the three-dimensional variational (3DVAR) algorithm which is tailored for non rainy conditions only. To this purpose, a new RTE algorithm is tested, in order to account fo...

Many studies have been performed during the past decade aiming to use Doppler radar data for initializing cloud-resolving models. At the Center for Analysis and Prediction of Storms (CAPS), the ARPS Data Analysis System (ADAS, Brewster 2003a, b), with incremental analysis updating capabilities, was developed as the first step towards assimilating radar data and other conventional and remotely-s...

In previous works of this series study, an ensemble Kalman filter (EnKF) has been demonstrated to be promising for mesoscale and regional scale data assimilation in increasingly realistic environments. Parts I and II examined the performance of the EnKF by assimilating simulated observations under both perfect-and imperfect-model assumptions. Part III explored the application of the EnKF to a r...

A Space and Time Mesoscale Analysis System (STMAS) has been developed at Forecast Systems Laboratory (FSL) to generate a grid analysis of surface observations. It is a three-dimensional variational analysis (3DVAR) of horizontal space and time instead of pressure or height levels. It is used to detect boundary layer phenomena, frontal zones, and various nonlinear phenomena, and has been used in...

An enhanced version of the hybrid ensemble-3DVAR data assimilation system for the WRF model is applied to the assimilation of radial velocity (Vr) data from two coastal WSR-88D radars for the prediction of Hurricane Ike (2008) before and during its landfall. In this hybrid system, flow-dependent ensemble covariance is incorporated into the varitional cost function using the extended control var...

Ill-posed inverse problems are ubiquitous in applications. Understanding of algorithms for their solution has been greatly enhanced by a deep understanding of the linear inverse problem. In the applied communities ensemble-based filtering methods have recently been used to solve inverse problems by introducing an artificial dynamical system. This opens up the possibility of using a range of oth...

An attempt was made to evaluate the impact of assimilating Doppler Weather Radar (DWR) reflectivity together with Global Telecommunication System (GTS) data in three-dimensional variational assimilation (3DVAR) system Research Forecast (WRF) model on rain storm prediction Daqinghe basin northern China. The aim this study explore potential effects frequency and outputs from different domain reso...

This study established a WRF/WRF-Hydro coupled forecasting system for precipitation–runoff in the Daqing River basin northern China. To fully enhance skill of system, real-time updating was performed both WRF precipitation forecast and WRF-Hydro forecasted runoff. Three-dimensional variational (3Dvar) multi-source data assimilation implemented using model by incorporating hourly weather radar r...