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

Abstract

The Australian Community Climate and Earth System Simulator (ACCESS) has been adapted for operational and research applications on tropical cyclones. The base system runs at a resolution of 0.118 and 50 levels. The domain is relocatable and nested in coarser-resolution ACCESS forecasts. Initialization consists of five cycles of four-dimensional variational data assimilation (4DVAR) over 24 h. Forecasts to 72 h are made. Without vortex specification, initial conditions usually contain a weak and misplaced circulation pattern. Significant effort has been devoted to building physically based, synthetic inner-core structures, validated using historical dropsonde data and surface analyses from the Atlantic. Based on estimates of central pressure and storm size, vortex specification is used to filter the analyzed circulation from the original analysis, construct an inner core of the storm, locate it to the observed position, and merge it with the large-scale analysis at outer radii.Using all available conventional observations and only synthetic surface pressure observations from the idealized vortex to correct the initial location and structure of the storm, the 4DVAR builds a balanced, intense 3D vortex with maximum wind at the radius of maximum wind and with a well-developed secondary circulation. Mean track and intensity errors for Australian region and northwest Pacific storms have been encouraging, as are recent real-time results from the Australian National Meteorological and Oceanographic Centre. The system became fully operational in November 2011. From preliminary diagnostics, some interesting structure change features are illustrated. Current limitations, future enhancements, and research applications are also discussed.

Prediction of rapid intensification of tropical cyclone Phailin over the Bay of Bengal using the HWRF modelling system

“…Vortex‐scale data assimilation is an evolving area used to improve intensity prediction (Zhang et al , ; Weng and Zhang, ; Aksoy, ; Davidson et al , ; Aberson et al , ). Davidson et al () demonstrated the credibility of four‐dimensional variational data assimilation (4D‐Var) along with vortex relocation and initialization to define a physically‐based, corrected vortex in terms of location, intensity and structure at the initialization.…”

“…Vortex‐scale data assimilation is an evolving area used to improve intensity prediction (Zhang et al , ; Weng and Zhang, ; Aksoy, ; Davidson et al , ; Aberson et al , ). Davidson et al () demonstrated the credibility of four‐dimensional variational data assimilation (4D‐Var) along with vortex relocation and initialization to define a physically‐based, corrected vortex in terms of location, intensity and structure at the initialization. There have been earlier attempts to improve the prediction skill with increased horizontal grid spacing/resolution (Bhaskar Rao et al , ; Osuri et al , ), physical parametrizations (Bhaskar Rao and Prasad, ; Osuri et al , ; Raju et al , ; Kanase and Salvekar, ), and data assimilation (Singh et al , ; Osuri et al , , ).…”

Application of Contiguous Rain Area (CRA) Methods to Tropical Cyclone Rainfall Forecast Verification

“…This builds a balanced, intense three-dimensional vortex with an appropriate radius of maximum wind and with a well-developed secondary circulation. Mean track and intensity errors for Australian region and northwest Pacific storms have been encouraging (Davidson et al, 2014). However, until now the TC rainfall forecasts lacked verification, which was urgently needed.…”

Data assimilation – Abstracts of the tenth CAWCR Workshop 5-9 December 2016, Melbourne, Australia

“…However, most of the TCs originate over tropical oceans where meteorological observations are generally insufficient to accurately define vortex structure, particularly the inner core structure. Using the position and intensity information of the initial vortex, which can be well determined from satellite imagery, the TC structure can be indirectly recovered through the technique of 4DVAR TC bogus data assimilation (Davidson et al 2014). Our experience with a 4-km grid spacing mesoscale ACCESS for TC forecasting (ACCESS-TCX) during the past two years indicates that the effect of the TC bogus data assimilation (DA) is dependent on many factors, e.g., the quality of large scale background (firstguess) field, the bogus data in single central pressure and its position or more complicated vortex specification forms.…”