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Elizabeth Satterfield and Istvan Szunyogh

1. Introduction In an earlier paper ( Satterfield and Szunyogh 2010 ) we investigated the performance of the linear space spanned by the ensemble perturbations in capturing the space of uncertainties in 1000-km horizontal length scale local regions. In that paper, we found that in the 72––120-h forecast range: the performance of in capturing the forecast error patterns was strongly flow dependent: the more rapid the error growth, the more reliable was in capturing the forecast errors; and

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Munehiko Yamaguchi and Sharanya J. Majumdar

. (2001) illustrated reasonable forecast performance in the spread of TC tracks and intensities, using the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS; Molteni et al. 1996 ; Leutbecher and Palmer 2008 ) and targeted diabatic (moist) singular vectors (SVs) as a generator of initial perturbations ( Mureau et al. 1993 ; Buizza 1994 ; Buizza and Palmer 1995 ; Palmer et al. 1998 ; Barkmeijer et al. 2001 ). Majumdar and Finocchio (2010) demonstrated

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John E. Janowiak, Peter Bauer, Wanqiu Wang, Phillip A. Arkin, and Jon Gottschalck

1. Introduction Numerical models evolve constantly due to the ever-present demand for more accurate weather and climate forecasts. Similarly, observational datasets improve with time largely due to advances in observing and communication systems, data storage capacity, and computing power. These circumstances warrant continued validation activities to assess potential model improvements with state-of-the-art observing systems. Several investigations of model precipitation

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Mio Matsueda, Masayuki Kyouda, Zoltan Toth, H. L. Tanaka, and Tadashi Tsuyuki

and improvements in blocking prediction in medium-range forecasts, for which the initial-value problem is of greater concern than the boundary-value problem. Advances in these areas may lead to improvements not only in medium-range forecasting skill but also in model performance in climate projections. The NWP technique has progressed rapidly with advances in computer science. A 5-day weather forecast today is as reliable as a 2-day weather forecast 20 years ago, which represents a major

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Warren J. Tennant, Glenn J. Shutts, Alberto Arribas, and Simon A. Thompson

1. Introduction Ensemble prediction systems (EPSs) provide an objective way to estimate uncertainty in weather and climate forecasts ( Buizza et al. 2005 ). The sensitivity of forecasts to changes in initial states discovered by Lorenz (1963) aided in the development of ideas to generate multiple realizations of a numerical model forecast by perturbing the initial conditions ( Leith 1974 ). The basis of the approach was to use Monte Carlo approximations of the stochastic dynamic forecasting

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E. A. Irvine, S. L. Gray, J. Methven, and I. A. Renfrew

1. Introduction The aim of making targeted observations is to improve the forecast for a specified region through the addition of information in regions where the forecast is sensitive to initial-condition errors. Over the past 10 years or so field campaigns and idealized modeling studies have tested the idea that adding a small number of profile observations, over a limited area, can have a significant (positive) downstream impact on the forecast. The results of these studies

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Ronald Gelaro, Rolf H. Langland, Simon Pellerin, and Ricardo Todling

1. Introduction The Observing System Research and Predictability Experiment (THORPEX) is a decade-long World Weather Research Program (WWRP) to accelerate improvements in the accuracy of one-day to two-week high-impact weather forecasts for the benefit of society, the economy, and the environment ( Shapiro and Thorpe 2004 ). A primary goal of THORPEX is to quantify the value of observations provided by the current global atmospheric observing network in terms of their impact on

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Sharanya J. Majumdar, Kathryn J. Sellwood, Daniel Hodyss, Zoltan Toth, and Yucheng Song

past decade, in which the routine observational network has been augmented by a limited number of adaptive observations. These observations have been “targeted” at improving short-range (1–3 day) numerical forecasts of weather events such as frontal cyclones and hurricanes (see Langland 2005 for a review). The instrumentation utilized to date has primarily been Global Positioning System (GPS) dropwindsondes, released from manned aircraft deployed over the oceans. The assimilation of these

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Thomas M. Hamill, Jeffrey S. Whitaker, Michael Fiorino, and Stanley G. Benjamin

1. Introduction The accuracy of official National Hurricane Center tropical cyclone (TC) track forecasts has improved over the past several decades ( Rappaport et al. 2009 ). In part, this can be attributed to the general improvements in numerical weather prediction (NWP) models, such as increased resolution, improved methods of initialization, more realistic physical parameterizations, and the availability of a greater number of skillful models for generating consensus forecasts

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William A. Komaromi, Sharanya J. Majumdar, and Eric D. Rappin

al. 1998 ; Wu and Wang 2000 ). Additionally, piecewise PV inversion ( Davis and Emanuel 1991 ) was employed to diagnose the steering flow and the interaction between the TC and its environment ( Wu and Emanuel 1995a , b ). It was found that the balanced flows deduced via the separation of PV fields were useful in interpreting TC motion. Recently, attention has turned to investigating errors in numerical forecasts of TC motion that arise due in part to inaccuracies in their initial conditions. To

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