Assimilation of Radar Radial Velocity Data with the WRF Hybrid Ensemble–3DVAR System for the Prediction of Hurricane Ike (2008)

Abstract

An enhanced version of the hybrid ensemble-three-dimensional variational data assimilation (3DVAR) system for the Weather Research and Forecasting Model (WRF) is applied to the assimilation of radial velocity (Vr) data from two coastal Weather Surveillance Radar-1988 Doppler (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 variational cost function using the extended control variable method. The analysis ensemble is generated by updating each forecast ensemble member with perturbed radar observations using the hybrid scheme itself. The Vr data are assimilated every 30 min for 3 h immediately after Ike entered the coverage of the two coastal radars.The hybrid method produces positive temperature increments indicating a warming of the inner core throughout the depth of the hurricane. In contrast, the 3DVAR produces much weaker and smoother increments with negative values at the vortex center at lower levels. Wind forecasts from the hybrid analyses fit the observed radial velocity better than that from 3DVAR, and the 3-h accumulated precipitation forecasts from the hybrid are also more skillful. The track forecast is slightly improved by the hybrid method and slightly degraded by the 3DVAR compared to the forecast from the Global Forecast System (GFS) analysis. All experiments assimilating the radar data show much improved intensity analyses and forecasts compared to the experiment without assimilating radar data. The better forecast of the hybrid indicates that the hybrid method produces dynamically more consistent state estimations. Little benefit of including the tuned static component of background error covariance in the hybrid is found.

Track and Intensity Forecasting of Hurricanes: Impact of Convection-Permitting Resolution and Global Ensemble Kalman Filter Analysis on 2010 Atlantic Season Forecasts

“…The primary difference between the 3DVAR and EnKF methods is with their determination of the background error covariance (e.g., Li et al 2012). The operational GSI 3DVAR for GFS uses static background error covariance derived from historical forecasts using the so-called National Meteorological Center (NMC, now known as NCEP) method (Parrish and Derber 1992).…”

A GSI-Based Coupled EnSRF–En3DVar Hybrid Data Assimilation System for the Operational Rapid Refresh Model: Tests at a Reduced Resolution

“…Based on the variational DA framework of the Advanced Research Weather Research and Forecasting Model (WRF-ARW; Skamarock et al 2005), Wang et al (2008a, b) implemented the ECV-based hybrid, coupling it with an ETKF (Bishop et al 2001) that is used to update the ensemble perturbations (which we call ETKF-En3D-Var hybrid). This WRF hybrid DA system was further applied for tropical cyclone DA Li et al 2012). Most recently, Zhang and Zhang (2012) coupled a mesoscale EnKF system with WRF 4DVar through the WRF hybrid DA framework (hence EnKF-En4D-Var hybrid but they called it E4DVar), and Zhang et al (2013) further compared the performances of EnKFEn3DVar (they called it E3DVar) and EnKF-En4DVar hybrid for mesoscale applications.…”

Diagnostic Pressure Equation as a Weak Constraint in a Storm-Scale Three-Dimensional Variational Radar Data Assimilation System

“…For example, Liu and Xue (2006) and Liu et al (2007) reported efforts to build flow-dependent background error covariance in a 3DVAR system using anisotropic recursive filters and demonstrated improvement in moisture retrieval from GPS slant-path water vapor observations. Hamill and Snyder (2000), Lorenc (2003), Buehner (2005), and Wang et al (2008a,b) advocated a hybrid approach that incorporates flow-dependent background covariance derived from an forecast ensemble into a 3DVAR framework, and the method is recently applied to a radar DA problem for a landfalling hurricane (Li et al 2012). The similar methodology can be extended to 4DVAR also.…”