The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for High-Resolution Data: The Impact of Airborne Doppler Radar Observations in an OSSE

Abstract

Within the National Oceanic and Atmospheric Administration, the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory has developed the Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) to assimilate hurricane inner-core observations for high-resolution vortex initialization. HEDAS is based on a serial implementation of the square root ensemble Kalman filter. HWRF is configured with a horizontal grid spacing of 9/3 km on the outer/inner domains. In this preliminary study, airborne Doppler radar radial wind observations are simulated from a higher-resolution (4.5/1.5 km) version of the same model with other modifications that resulted in appreciable model error.A 24-h nature run simulation of Hurricane Paloma was initialized at 1200 UTC 7 November 2008 and produced a realistic, category-2-strength hurricane vortex. The impact of assimilating Doppler wind observations is assessed in observation space as well as in model space. It is observed that while the assimilation of Doppler wind observations results in significant improvements in the overall vortex structure, a general bias in the average error statistics persists because of the underestimation of overall intensity. A general deficiency in ensemble spread is also evident. While covariance inflation/relaxation and observation thinning result in improved ensemble spread, these do not translate into improvements in overall error statistics. These results strongly suggest a need to include in the ensemble a representation of forecast error growth from other sources such as model error.

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

“…Recently, several studies have explored the use of ensemble-based DA methods to initialize hurricane forecasts and have shown great promise (e.g.. Torn and Hakim 2009;Zhang et al 2009a;Li and Liu 2009;Hamill et al 2011;Weng et al 2011;Zhang et al 2011;Aksoy et al 2012;Weng and Zhang 2012;Dong and Xue 2012). The key with ensemble-based DA is the use of an ensemble to estimate the forecast error statistics in a flow-dependent manner.…”

“…Recent studies have suggested that hybrid DA systems may represent the "best of both worlds" by combining the best aspects of the variational and EnKF systems (e.g., Buehner 2005;Wang et al 2007aWang et al , 2008aWang et al ,b, 2009Zhang et al 2009b;Buehner et al 2010a,b;Wang 2010). While preliminary tests of the hybrid DA system with real NWP models and data have shown great potential of the method for non-TC forecasts (e.g., Wang et al 2008b;Buehner et al 2010a,b) and for forecasts of TC tracks (e.g., Whitaker et al 2011), and there has been a growing body of literature documenting the success of using the EnKF to assimilate inner-core data for TC initialization at convection-allowing resolutions (e.g., Zhang et al 2009a;Weng et al 2011;Zhang et al 2011 ;Aksoy et al 2012;Weng and Zhang 2012;Dong and Xue 2012), to the authors' best knowledge, to date there is no published study applying a hybrid DA method to the assimilation of radar data at a convection-allowing resolution for TC predictions. This study serves as a pilot study applying the hybrid ensemble-threedimensional variational data assimilation (3DVAR) system developed for the Weather Research and Forecasting Model (WRF) (Wang et al 2008a) to explore its potential for assimilating radar observations for hurricane forecasts.…”

ACCESS-TC: Vortex Specification, 4DVAR Initialization, Verification, and Structure Diagnostics

“…There have been successful and encouraging attempts to use ground-based and airborne Doppler radar data to initialize the inner cores of TCs. This has recently been described by Zhao and Jin (2008), Zhang et al (2009), Xiao et al (2009), Aksoy et al (2012), and Weng and Zhang (2012). Indeed, using a large sample of cases with airborne Doppler radar observations, Zhang et al (2011) clearly demonstrated the need for high-resolution inner-core observations for tropical cyclones from either in situ or remotely sensed observations.…”

Ensemble Data Assimilation and Predictability of Tropical Cyclones

“…( Aksoy et al 2012;Jung et al 2012). We examined the performance of the ensemble-based data assimilation and prediction system with Doppler radar observations systematically for all the 2008-2011 storms that had airborne Doppler missions.…”