%0 Journal Article
%T Using Enstrophy-Based Diagnostics in an Ensemble for Two Blocking Events
%A Andrew D. Jensen
%A Anthony R. Lupo
%J Advances in Meteorology
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/693859
%X Recent research has used enstrophy-based diagnostics to identify the development and dissipation stages of blocking events. These previous studies made use of reanalysis data sets in the calculations of the enstrophy-based diagnostics, such as the NCEP-NCAR reanalysis (2.5¡ã ¡Á 2.5¡ã) of geopotential height and horizontal winds. However, none of these studies has explored the use of the enstrophy-based diagnostics in weather or climate models with higher horizontal resolution. In this paper, the enstrophy-based diagnostics are used to analyze two blocking events, using data from the ERA-Interim reanalysis data set (0.75¡ã ¡Á 0.75¡ã) and also the Global Ensemble Forecast System (GEFS) (1¡ã ¡Á 1¡ã). The results of this work indicate that using an ensemble may be more effective than a single dynamical control forecast in evaluating the enstrophy-based diagnostic quantities, and that the results are similar to those obtained with coarser resolution. 1. Introduction Many studies have noted an upscale cascade of enstrophy upstream of blocking events (see, e.g., [1, 2]). Moreover, in [3], enstrophy and large-scale instability are compared by means of finite-time Lyapunov exponents. Using these ideas and the instability at block onset and decay [4], in a series of recent articles (see [5¨C8]), enstrophy-based diagnostics have been used to study large-scale stability changes during the development and termination of blocking events. These studies used reanalysis data sets such as the NCEP-NCAR reanalysis of geopotential heights and winds to calculate the enstrophy-based diagnostics. However, no work has yet explored the use of these diagnostics in weather or climate models or in an ensemble. The utility of using ensemble-based forecasting to better predict blocking is well known (e.g., [9¨C11]). Several studies note the increased skill of forecasts of blocking episodes over solely dynamical prediction methods. For example, [10] showed that ECMWF ensemble prediction system forecasts of blocking are more skilful than the deterministic and climatology forecasts of Euro-Atlantic sector blocking, although blocking onset was better predicted than block decay overall. In [9], it was found that ensemble forecasts which were calibrated to correct for the under prediction of blocking were more accurate than uncalibrated ensemble forecasts. [11] found the ensemble mean to perform better than the control group for forecast times longer than 3-4 days in two atmospheric models. Errors were found to be largest at block onset and decay (see also [4]). The purpose of this study is to use
%U http://www.hindawi.com/journals/amete/2013/693859/